Flood Vulnerability in Gothenburg

Home , Climate change in Sweden, Cyclone Gudrun, Gothenburg archipelago, Gothenburg Municipality, Port of Gothenburg

UNIVERSITY OF GOTHENBURG Department of Economy and Society, Human Geography & Department of Earth Sciences Geovetarcentrum/Earth Science Centre

Gothenburg & Mölndal`s present

and future vulnerability against

weather-related flood events

Susanna Gelin

ISSN 1400-3821 B801 Master of Science (120 credits) thesis Göteborg 2015

Mailing address Address Telephone Telefax Geovetarcentrum Geovetarcentrum Geovetarcentrum 031-786 19 56 031-786 19 86 Göteborg University S 405 30 Göteborg Guldhedsgatan 5A S-405 30 Göteborg SWEDEN

Front photo (Figure 1): The water level in the moat have increased significantly, due to high sea level in river Göta älv at the passage of the extra-tropical cyclone Sven that struck Gothenburg in December 2013. The picture is taken from the Lejontrappan in front of Gustav Adolfs Torg. In the background, the church Christine Kyrka can be seen. Photo: Susanna Gelin

Department of Earth Sciences

Preface

This Master’s thesis is Susanna Gelin’s degree project in Earth Sciences at the Department of Earth Sciences, University of Gothenburg. The Master’s thesis comprises 60 hec (two semesters of full-time studies).

Supervisors have been Associate Professor Yvonne Andersson-Sköld at the Department of Earth Sciences at the University of Gothenburg and Research and Development Manager at COWI AB, Associate Professor Sofia Thorsson and Dr David Rayner also at the Department of Earth Sciences, at the University of Gothenburg. Examiner has been Professor Roland Barthel at the Department of Earth Sciences, at the University of Gothenburg.

The author is responsible for the content in this thesis.

Gothenburg, September 29, 2014

III

Abstract Introduction: Gothenburg stands on the threshold of a new era. The city center will expand across river Göta älv and transform from old docklands to a new residential and commercial area. Gothenburg and Mölndal (the study area) are already facing problems with flood-related weather extremes such as heavy rain, flooded rivers and storm surges. Climate change is a fact, even if the emissions were to be reduced, we would still be forced to live in a warmer and wetter world. By 2100, Gothenburg’s annual precipitation may increase up to 30%, heavy rains will become more frequent and intense, while the sea level may rise 65-80 cm. Flooding in cities are growing more common. To create resilient cities, which can absorb and control the threats and opportunities of future weather and climate, local authorities are now required to take on the challenge of climate adaptation. Aim: The main purpose of this study starts with identifying weather-related flood events (between the years 1991-2012) causing consequences for Gothenburg and Mölndal municipalities, continuing with investigation of meteorological and oceanographic data related to the observed flood events. Finally, determining and analyzing the future vulnerability to weather-related flood events by applied climate change projections on present vulnerability. Method: Parts of the method Local Climate Impacts Profile (LCLIP) have been used. The purpose is to investigate the vulnerability in Gothenburg and Mölndal to weather-related flood events by searching for past weather-related articles in the local newspaper Göteborgs-Posten. Knowledge about existing vulnerability is the primary opening and preparation for an adaptation strategy. To enhance the vulnerability profile incident reports from the emergency service have been added. The two sources provide a broader knowledge of the vulnerability, and highlights the strengths and weaknesses between them. Through meteorological and oceanographic data, the cause for the consequence can be determined. Results: An additional source to a traditional LCLIP is valuable to receive a broader knowledge of the vulnerability. Gothenburg and Mölndal municipalities are vulnerable to weather-related flood events caused by heavy rains, flooded rivers and high sea levels (especially during storm surges). Today heavy rains are the largest risk causing most consequences for the two municipalities. The categories motorists/roads and flooded basements in buildings are most exposed. The latter, consequently arises from deficiencies and under-dimensioned water and sewer systems. Air pressure and wind are the two main factors affecting high sea levels within the estuary of river Göta älv. According to interviews the biggest challenge for Gothenburg are cooperation between different authorities within the work of adaptation strategy. Conclusion: Gothenburg and Mölndal is vulnerable to weather related flood-events today, especially the heavy rains. By climate change the two municipalities will become even more vulnerable in the future if not a good adaptation strategy is implemented. Keywords: climate change, extreme weather events, flooding, LCLIP, Gothenburg, Mölndal, Göteborgs-Posten, MSB, emergency service, SMHI, warning systems, vulnerability, adaptation strategy.

Sammanfattning Introduktion: Göteborg står på tröskeln inför en ny era. Stadskärnan ska expandera över Göta älv och förvandlas från gamla hamnområden till en ny attraktiv innerstad. Göteborg och Mölndal (studieområdet) har idag problem med översvämnings-relaterade väder händelser så som kraftiga regn, översvämmande åar och stormar. Klimatförändringarna är ett faktum, och även om vi lyckades minska utsläppen kommer vi vara tvungna att leva i en varmare och blötare värld. År 2100 kan Göteborgs årliga medelnederbörd ha ökat med 30%, kraftiga regn kan komma att bli vanligare och mer intensiva, medan havsnivån kan stiga med 65-80 cm. Städer drabbas allt oftare av översvämningar. För att skapa motståndskraftiga städer, som kan absorbera och kontrollera de hot och möjligheter som följer med ett framtida väder och klimat, är nu kommunerna skyldiga att anta utmaningen om klimatanpassning. Syfte: Huvudsyftet med den här studien är att först identifiera väder-relaterade översvämningar (mellan åren 1991-2012) som orsakar konsekvenser för städerna Göteborg och Mölndal, för att sedan undersöka meteorologisk och oceanografisk klimatdata relaterade till de identifierade översvämningarna. Slutligen ska den framtida sårbarheten mot väder-relaterade översvämningar analyseras genom att applicera framtida klimatscenarier på dagens sårbarhet. Metod: Delar av en metod kallad Lokal Klimateffekts Profil (LCLIP) har används. Metoden gör det möjligt att undersöka sårbarheten i Göteborg och Mölndal för väderrelaterade översvämningar, genom att gå igenom artiklar från den lokala nyhetstidningen Göteborgs-Posten. Kunskap om den befintliga sårbarheten är den primära öppningen och förberedelsen för en klimatanpassning. För att utöka sårbarhetsprofilen har incidentrapporter från räddningstjänsten lagts till. De båda källorna skapar en vidare bild över sårbarheten, och kan samtidigt belysa varandras styrkor och brister. Genom meteorologiska och oceanografiska mätningar, kan orsaken till konsekvensen fastställas. Resultat: Genom att lägga till ytterligare en källa till den traditionella LCLIP, fås en vidare kunskap över sårbarheten. Göteborg och Mölndal är sårbara mot väder-relaterade översvämningar orsakade av kraftiga regn, översvämmade åar och höga havsnivåer (särskilt vid storm). Idag är kraftiga regn den orsaken som orsakar mest konsekvenser för de båda kommunerna. Kategorierna bilister/vägar och översvämmade källare i byggnader är sårbarast. Den senare, uppstår framför allt på grund av dåligt underhållna och under-dimensionerade vatten och avloppssystem. Lufttryck och vind är de två huvudfaktorer som påverkar höga havsnivåer inom Göta älvs flodmynning. Ett extremt år idag, kan vara ett genomsnittligt år 2100. Den största utmaningen för Göteborg och Mölndal idag är samarbetet mellan olika myndigheter inom arbetet med klimatanpassning. Slutsats: Göteborg och Mölndal är sårbara mot väder-relaterade översvämningar idag, och speciellt mot skyfall. Klimatförändringarna kommer göra de två kommunerna även mer sårbara i framtiden om inte de inte klimatanpassas. Sökord: klimatförändringar, extrema väderhändelser, översvämning, LCLIP, Göteborg, Mölndal, Göteborgs-Posten, MSB, räddningstjänsten, SMHI, varningssystem, sårbarhet, klimatanpassning.

Table of Content 1. Introduction ...... 1 1.1 Aim ...... 2 1.2 Questions at issue ...... 2 1.3 Structure of approach to achieve present and future vulnerability ...... 3 2. Background ...... 4 2.1 Local climate change ...... 4 2.1.1 Local sea level rise ...... 6 2.2 Extreme weather events ...... 7 2.3 Flooding ...... 8 2.4 Causes for a flood event to occur in Gothenburg ...... 9 2.4.1 Flooding along watercourses ...... 9 2.4.2 Flooding of areas not in direct contact with watercourses, lakes and oceans ...... 9 2.4.3 Flooding of lakes ...... 11 2.4.4 Coastal flooding ...... 11 2.5 Local factors that affect sea level change ...... 12 2.5.1 Air pressure ...... 12 2.5.2 Wind effects for Gothenburg ...... 14 2.6 SMHI’s warning system ...... 14 2.6.1 Warning system development ...... 16 2.7 Risk, vulnerability, exposure and adaptive capacity ...... 16 2.8 Methods to reveal vulnerability ...... 17 2.8.1 LCLIP ...... 18 2.8.2 Application and development of LCLIP in Sweden ...... 19 2.8.3 MSB’s archive ...... 19 3. Study area ...... 21 3.1 Present hydrological and meteorological aspects of Gothenburg ...... 21 3.1.1 Precipitation ...... 22 3.1.2 Catchment area ...... 22 3.2 Mölndal municipality ...... 23 3.2.1 River Mölndalsån ...... 23 4. Methodology...... 24 4.1 Media Trawl in Göteborgs-Posten...... 24 4.1.1 First step (during Bachelor thesis and repeated in this Master’s thesis) ...... 24 4.1.2 Second step (Master’s thesis) ...... 26 4.2 Data from the Swedish Civil Contingencies Agency (MSB) ...... 27 4.3 Comparison between GP and MSB ...... 28 VI

4.4 Meteorological and oceanographic data ...... 29 4.4.1 Precipitation ...... 30 4.4.2 Wind speed and direction ...... 30 4.4.3 Air pressure ...... 31 4.4.4 Sea level ...... 31 4.4.5 METAR-data for the case study Sven...... 31 4.5 Interviews ...... 31 5. Results ...... 32 5.1 Present vulnerability against weather-related flood events ...... 32 5.1.1 Published articles of weather-related events from GP ...... 32 5.1.2 Number of flood-related articles from GP and incident reports from MSB ...... 34 5.1.3 Classification of weather-events ...... 35 5.1.4 Case study – The extra-tropical cyclone Sven ...... 40 5.1.5 Local meteorological and oceanographic parameters affecting flood-events ...... 44 5.1.6 Meteorological and oceanographic elements affecting sea level in Gothenburg ...... 48 5.1.7 Comparison of GP articles, MSB reports, meteorological- and oceanographic data ...... 54 5.1.8 Interviews ...... 61 6. Discussion ...... 64 6.1 Present vulnerability ...... 64 6.1.1 Causes of high sea levels ...... 65 6.1.2 Assumptions and limitations of the method used in this thesis ...... 65 6.2 Future vulnerability ...... 69 6.2.1 Future vulnerability related to changes in precipitation ...... 69 6.2.2 Future vulnerability related to sea level rise and storm surges ...... 70 6.3 Measures to reduce vulnerability ...... 72 7. Conclusions ...... 73 7.1 Further studies and enhancements ...... 74 Acknowledgements ...... 75 References ...... 76 Appendix A ...... I A.1 Keywords for database ...... I Appendix B ...... II B.1 Interview questions ...... II

VII

1. Introduction Gothenburg stands on the threshold of a new era. North and south will soon be re-connected when the city center is expanding across the river Göta älv. Gothenburg and especially the future River City is a low-lying area which is regularly exposed to flooding in connection to weather extremes (Göteborgs Stad, 2011). Heavy- and persistent precipitation are common causes for flooding in Gothenburg (SMHI, 2005b). The city will face flooding if the mean sea level rises. Simultaneously, there will be high sea levels in conjunction with storm surges (Mistra, 2010). Considering damage on buildings and infrastructure, Gothenburg is the most vulnerable city in Sweden (Moback, 2014). Climate change is a fact (Prasad et al., 2009), and the emissions of greenhouse gases are still rising (Raupach et al., 2007). Even if the emissions were to be reduced, we would still be forced to live with climate change due to past emissions (Ruddiman, 2008). Global climate change is by some considered to be one of the biggest challenges for mankind in the 21st century (Fry, 2009). Cities are becoming increasingly vulnerable to flooding because of population growth, rapid urbanization in coastal areas, installation of complex infrastructure, and changes in weather patterns caused by anthropogenic climate change (Willems, Arnbjerg-Nielsen, Olsson, & Nguyen, 2012). Coastal development have led to that two-thirds of the world mega-cities are located in coastal areas and are exposing increasingly numbers of people and sensitive infrastructure to potential effects of high sea levels. Climate change poses risks for human and natural systems (IPCC, 2007). The causes of the flooding are extreme weather and climate events arising from extreme precipitation, high winds, storm surges and sea level rise (Hunt & Watkiss, 2011; IPCC, 2012, 2014). The atmosphere will be warmer and more humid in the future (IPCC, 2007, 2013b; NASA, 2014). The warming will be largest in high latitudes in Northern Europe (Haylock et al., 2008; SOU, 2007). By the end of this century Sweden may be 4-6 °C warmer and have a 65-80 cm higher mean sea level along the southern coastline (Persson et al., 2011). Gothenburg may have up to 30% more annual precipitation (in relation to the reference period 1961-1990) and heavy precipitation events may occur more frequently. Evidence strongly indicate that some types of extreme events, e.g. wet spells and storm surges will increase in number (Coumou & Rahmstorf, 2012; Frich et al., 2002; Weisse, von Storch, Niemeyer, & Knaack, 2012; Woth, Weisse, & Von Storch, 2006). High flows, extreme high flows and flood risks are also expected to increase sharply in number in the County Västra Götalands Län (Andréasson, Bergström, Carlsson, Graham, & Lindström, 2004; Persson et al., 2011; SMHI, 2006; SOU, 2007). Society needs to prepare for the impacts of a changing climate. To create resilient cities, which can absorb and control the threats and opportunities of future weather and climate. The local authorities are now required to take on the challenge of a sustainable development of adaptation capacity (Prasad et al., 2009). Knowledge about existing vulnerability is the primary opening and preparation for an adaptation strategy. This study use a method called Local Climate Impacts Profile (LCLIP) (Carlsson-Kanyama, 2009; UKCIP, 2009). The purpose is to investigate the vulnerability for the local community, in this case Gothenburg and Mölndal municipalities to flood-related weather events, by identifying and classify the reported consequences and compare them to meteorological and oceanographic data. 1

1.1 Aim The aim of this study is to investigate the present vulnerability of weather-related flood events in Gothenburg and Mölndal municipalities by using weather-related news articles from the last decades published in the newspaper Göteborgs-Posten (GP) together with incident reports from the emergency service (ordered from The Swedish Civil Contingencies Agency - MSB). A purpose is to study how these two sources differ from each other and how suitable they are for making an LCLIP. Furthermore, meteorological and oceanographic data (precipitation, sea level, air pressure wind speed and direction) that affects weather-related flood events in Gothenburg and Mölndal have been investigated to determine the cause of the consequences. The future vulnerability of weather-related flood events for these two municipalities will be discussed based on the results found for present vulnerability and by using future climate projections from the Intergovernmental Panel on Climate Change (IPCC) and the Swedish Meteorological Institute (SMHI). 1.2 Questions at issue  What is the present vulnerability against weather-related flood events in Gothenburg and Mölndal municipalities? o How has GP and MSB reported weather-related flood events during the period 1991-2012? How do they differ from each other and how suitable are they for making an LCLIP? o What kind of meteorological and oceanographic features affect weather-related flood events in Gothenburg and Mölndal municipalities? o Future vulnerability will be discussed based on present vulnerability and present climate projections for Gothenburg and Mölndal municipalities.

Figure 2. Increased sea level in river Göta älv, behind the Opera House, due to the extra-tropical cyclone Sven that struck Gothenburg in December 2013. In the background the Freeport-Port area is visible. Photo: Susanna Gelin 2

1.3 Structure of approach to achieve present and future vulnerability To achieve information about present vulnerability and future vulnerability of weather-related flood events in Gothenburg and Mölndal municipalities, a strategy have been used which is a combination of natural and social science. The strategy is described in Figure 3. Letter A stands for achievements in this study while letter B stands for a discussion held in this study. First meteorological and oceanographic data (precipitation, wind speed and direction, air pressure and sea level) have been investigated to assess present climate. To make an impact assessment, articles from GP, incident reports from the emergency service and interviews have been compiled. From the impact assessment and present climate, present vulnerability is determined. By applying future climate projections from IPCC and SMHI future vulnerability can be evaluated and discussed. To minimize the future vulnerability it is of importance to create an adaptation plan and continuously adjust it according to the latest research and knowledge. This study will focus on the present- and future vulnerability. This study may be of help to decision makers to develop adaptation plans for the two municipalities. To broaden and increase the knowledge of present and future vulnerability suggestions for further studies is announced.

Future vulnerability

B Future climate A

Present Present vulnerability Impact climate Assessment s

Incident Articles Climate reports from Suggestions from the data Interviews for further Newspapers emergency studies service

Nature BASE Society Figure 3. Structure of approach to achieve present (A) and future (B) vulnerability against weather-related flood-events for Gothenburg and Mölndal municipalities.

2. Background This chapter begins with a problem definition regarding weather-related flood events for Gothenburg and Mölndal municipalities followed by a short description of local climate change. Further on, extreme weather and flood events are explained. Local factors affecting flooding within the study area will be discussed. Heavy rains and cloudbursts are discussed followed by a description of notions such as risk, vulnerability and hazard. Thereafter, SMHI’s warning system concerning flood events will be presented. Finally, interviews and different methods for investigating vulnerability for a city is provided. Gothenburg and Mölndal have had several flood events during the 21th century with costly consequences for society. According to MSB (2011), Gothenburg is therefore considered to be one of 18 identified areas with significant flood risk in Sweden. In the area were MSB has calculated for the potential estimated peak flow in Gothenburg, 6767 people live and may be exposed. Furthermore around 2511 workplaces with 37 657 employees are expected to be affected. In addition to this there is for example important infrastructure (railroads, tunnels, ports, airports, roads, industrial facilities, power and water supplies, water and sewerage systems) one SOS-emergency central, areas with contaminated land, water protection areas, one nature reserve and one Natura 2000 area, which potentially could be affected by floods. It is therefore important to investigate how vulnerable Gothenburg and the neighboring municipality Mölndal is to flood-events and how the ongoing climate change will affect them in the future (MSB, 2011). The risks posed by climate change in Sweden will likely be most severe along the south-west coast. Regions along river Göta älv will be more exposed for future climate change, as it is located very low. Gothenburg is highly exposed to high water levels in river Göta älv (Andersson-Sköld, Suer, Bergman, & Helgesson, 2014; Hultén, Andersson-Sköld, Ottosson, Edstam, & Johansson, 2007; SOU, 2007). During periods with large amount of precipitation, the water flow within watercourses and the ground water levels will increase. Accordingly, the risk for flooding will increase (Andersson-Sköld, Suer, et al., 2014; Andersson-Sköld, Thorsson, et al., 2014). 2.1 Local climate change Temperature will rise more in Sweden and Scandinavia than the global mean (IPCC, 2013b; SOU, 2007). According to estimates from SMHI the average annual temperature will increase by 4-6oC by the end of the century compared to present climate (Persson et al., 2011). Winter temperature may increase by 7 degrees, most likely in northern Sweden. For Gothenburg the monthly mean summer (June-August) temperature will increase with 3°C and in winter (December-February) the mean temperature is projected to increase with 4-5.5°C. In Gothenburg during winter the mean minimum temperatures will be above 0°C (SMHI, 2005b). The precipitation patterns is projected to change significantly. The annual mean amount of precipitation will increase by 10-30% in relation to the reference period 1961-1990 with a mean annual of about 900 mm (see Fig. 4) (Persson et al., 2011; SMHI, 2014c). The increasing annual precipitation is connected to an increase in the number of days with heavy precipitation (>25 mm/day) and more intensive rains. The increase will be 8-10 more days of heavy

precipitation per year in western Sweden during, autumn, winter and spring (Persson, Bärring, Kjellström, Strandberg, & Rummakainen, 2007). In summertime the climate will be warmer and drier i.e. less days with rain, particularly in southern Sweden, however the extreme rain events may become more common in a warmer climate. It is possible that the extreme rain events in Sweden will occur more frequently and become more intense in a future climate (SMHI, 2013a). The last 10-20 years the annual precipitation have shown a tendency toward higher values as in projections with e.g. emission scenario RCP 8.5. The tendency may be part of the increase projected by 2100, since the reference period is 1961-1990 (SMHI, 2014c).

1990[%] -

reference period1961 reference

Change in precipitation inChange compared

Year Figure 4. Estimated change in annual precipitation in comparison with reference period 1961-1990, in County Västra Götalands Län. Scenario RCP 8.5. The bars show the historical data that is derived from observations. Green bars show precipitation amount greater than the normal and yellow bars show precipitation less than normal. The black curve shows the mean value for an ensemble of nine climate models for scenario RCP 8.5. The gray area shows the range of variation between the highest and lowest value for the members of the ensemble. This climate scenario is developed with the regional climate model RCA4, which has been used with input from different global climate models. (SMHI, 2014c). In Sweden the period of snow covered ground will be reduced by one month at the mid-century. By the 2020s, the proportion of precipitation during winter that falls as rain is expected to double, resulting in less snow stored in the environment. The runoff during spring will therefore decrease while the runoff during autumn and winter will increase (Persson et al., 2011). High flows, with an estimated return period of 100 years (100-year flow), is expected to increase in western Götaland. By 2080 snow will become very rare in the coastal areas of Götaland. According to hydrological calculations (reference period 1963-1992) average annual runoff will increase in particularly western Götaland, leading to higher discharge rates and higher flows in river Göta älv and river Mölndalsån by the end of this century (SMHI, 2012a). Small and medium-sized watercourses around the Gothenburg region will more frequently be flooded during winter, while the flow will decrease during summer (SMHI, 2005b, 2006; SOU, 2007). By the end of this century storms are likely to increase in strength and become more common in the North Sea (Weisse et al., 2012; Woth et al., 2006). Weather extremes like the storm Gudrun in 2005 is likely to occur more often. The westerly wind belt is tending to be pushed north, taking with it the path of low pressure areas and precipitation patterns. Both average wind 5

and maximum gusts may increase according to trends in some of the model scenarios. Westerly winds may also increase as the dominant wind direction. Decreasing sea ice extent in the arctic region will decrease the temperature gradient between the Equator and the Arctic. In combination with warming and destabilization of the lower troposphere and increasing cloudiness the polar jet stream weakens. The slower jet stream will lead to more stationary weather situations in the Northern Hemisphere i.e. weather situations like wet spells may last for longer periods of time (Francis, Chan, Leathers, Miller, & Veron, 2009). 2.1.1 Local sea level rise Since the late 1800s the southern part of Sweden have had a sea level rise of approximately 20 cm (see Fig. 5), and over the past 30 years the rise has increased in speed to almost 3 mm per year (SMHI, 2014a). However, recent still unpublished research have found a higher rate of sea level rise. For Gothenburg the average sea level is expected to rise by 65-80 cm along the country’s coastline at the end of the century (Persson et al., 2011). The sea level will continue to rise for many hundreds of years due to both natural and anthropogenic processes. Some evidence suggest that a relatively small temperature increase could have extensive impacts on coastal regions, due to proxy-record analysis which shows that global ice volumes were significantly smaller in the past than today (Benn & Evans, 2010). There is a concern that the rise of sea level could accelerate if more of the Greenland and parts of the Antarctic ice sheet melts. If the Greenland ice sheet melts completely the world’s oceans would rise by about 7 m and 62 m if Antarctica melts (SOU, 2007). Paleontological data analysis from corals indicate that the global mean sea level was 4-6 m or more above present sea levels during the last interglacial period, about 125 000 years ago. Climate and ice-sheet model simulations indicate that the Northern Hemisphere ice sheets contributed 2.2 to 3.4 m to the higher sea level, with majority of the rise coming from the partial melting of the Greenland ice sheet. Greenland was approximately 3oC warmer at that time, than today (UNEP, 2014).

Recent studies of the Antarctica ice sheet suggest that the sea level is estimated to rise more quickly than proposed by the latest IPCC report. By investigating the grounding line retreat of glacier draining the Amundsen Sea sector of West Antarctica using Earth Remote Sensing satellite radar interferometry shows that this sector of West Antarctica is undergoing a marine ice sheet instability that will significantly contribute to sea level rise in decades to centuries to come (Rignot, Mouginot, Morlighem, Seroussi, & Scheuchl, 2014). Investigations of the Thwaites Glacier in Pine Island Bay of Amundsen Sea show strong evidence that the process of marine ice-sheet destabilization is already ongoing. Although losses are likely to be relatively modest over the next century, rapid collapse will happen in the case where the grounding line reaches the basins deeper regions, which could occur within centuries. Such rapid collapse would probably spill over to adjacent catchments, undermining much of West Antarctica (Joughin, Smith, & Medley, 2014). The most direct effect of rising sea levels are submergence of low-lying coastal areas and increased susceptibility to extreme events such as floods due to storm surges. Other possible damaging effects includes saltwater intrusion into coastal groundwaters and increased coastal erosion (IPCC, 2007). Extreme sea levels during storms with a return period of 100 years, may give a rise of 236 cm in Gothenburg (compared to 165 cm for the years 1987-2010) by 2100 (Persson et al., 2011).

] Sea level [cm level Sea

Year Figure 5. Sea level rise for Sweden 1886-2012. The blue bars show the historical data that is derived from observations. The black curve shows the mean sea level rise (SMHI, 2014a).

IPCC (2013b) use four emission scenarios of CO2 for modelling future climate including global mean sea level rise. The central projection of global mean sea level rise for the four scenarios range from 0.45 m to 0.70 m until year 2100. All scenarios show some variance, the highest emission scenario (RCP8.5) range from 0.52 m to 0.98 m for a 95% confidence interval for the year 2100. At regional scales the sea level rise will possibly deviate some from the global mean (Bergström, 2012; Persson et al., 2007). A number of variables affect the certainty of climate projections. The variables are selection of emission scenarios, selection of global climate models, selection of local climate models and natural variability. To estimate the uncertainty several projections with different initial conditions and models are used to estimate the spread of the projections. The spread results are divided into ranges of percentiles that correspond to certainty of the projections. The method are characterized by several possible climate scenarios, a so called ensemble, and that the results are statistically processed (SMHI, 2012d). However, assumptions (applies in particular physical and mathematical analysis of the models plus the very large uncertainties within the emission scenarios) used in the model of changes in the atmosphere, e.g. levels of greenhouse gases and aerosols, of course only lead to expectations about past and future climate (SMHI, 2009a, 2009c). 2.2 Extreme weather events An extreme weather event is an event that is rare at a particular place and time of year. The extreme weather event would normally be as rare as or rarer than 10th or 90th percentile of a probability density function estimated from observations of the events. The definition of extreme weather may vary from place to place. One definition of extreme weather can be for example that drought lasts for a whole season, which then makes it to an extreme climate event (IPCC, 2013a). Climate change, driven by natural or human forcings, can lead to changes in the likelihood of the occurrence or strength of extreme weather and climate events such as extreme precipitation events (IPCC, 2013b). Evidence strongly indicate that some types of extreme 7

events, e.g. precipitation extremes, will greatly increase in a warming climate and have already done so (Beniston et al., 2007; Coumou & Rahmstorf, 2012). At present, single events cannot generally be directly attributed to anthropogenic influence, although the change in likelihood for the event to occur has been determined for some events by accounting for observed changes in climate. For some climate extremes such as floods, several factors, like duration and intensity need to be combined to produce an extreme event (IPCC, 2013b). Whether an extreme event results in extreme impact on humans and social systems depends on the degree of exposure and vulnerability to that very extreme, in addition to the magnitude of the physical event. Extreme impacts may be associated with non-extreme events where vulnerability and exposure are high (IPCC, 2012). 2.3 Flooding The definition of flood is:

“Temporary covering of land by water outside its normal confines” (FloodSite, 2009; Wolfgang, 2002). Flood is a collective term which consists of several variations of areas which are temporary or permanently under water (Nyberg, 2008). A flood occurs when the ground is saturated and cannot take care of the surplus. Floods often occur in connection to small or large watercourses, nearby lakes, in coastal areas (sea level rise which is often a result of storms) but also locally as a result of heavy rains. (Schanze, Zeman, & Marsalek, 2007). Floods can also be caused by ice dam (isdämning) in streams caused by ice jams (isproppar), swell-ice (svallis) or if a dam building rages (MSB, 2011; SMHI, 2009i). Floods can be systematically grouped after what caused the flood, such as rain (by passing fronts or by convection), snow melting, winds, waves, tidal effects, increased groundwater levels, congested sewer or dam failure (Nyberg, 2008; Schanze et al., 2007). When society is taking measurements, it is important to mention that several ecosystems are adapted and dependent on hydrological variations such as floods (Lif, 2006; Nyberg, 2008). Through time, in some areas, repeated floods have had positive effects as fertilizer on pastures and hay meadows (SMHI, 2009i). Globally, floods are one of the most threatening natural hazards for human society (Schanze et al., 2007) which annually cause highest amount of deaths and the greatest economic loss (SMHI, 2009i). This is evident from the increase in damage in the last 50 years due to a series of extreme floods (Schanze et al., 2007). No populated area in the world is safe from being flooded (Wolfgang, 2002). The urban flood hazard is significant and increasing. Small floods are becoming large floods and large floods are becoming disasters. (Parker, 2000). In Sweden we are relatively spared from such major flood disasters and deaths associated with flooding are here very rare. However, the material costs to society as a result of flooding is significant even for Sweden (MSB, 2011; SMHI, 2009i). Increased urbanization and exploration of areas exposed to risk make the people who may be harmed and the values that can be destroyed during a flood event increase (Kundzewicz, 2001). Consequences of a flood is varying, dependent on frequency and magnitude. Depending on the vulnerability of exposed elements (Schanze et al., 2007) significant consequences for humans, buildings, infrastructure,

agriculture, recreation areas and biodiversity may occur. Floods also cause social and psychological stress on society which can be of large-scale even if the situation is not extreme. People may be forced to move from their homes, personal possessions may be lost and the event may cause fear and insecurity (Tapsell, Penning-Rowsell, Tunstall, & Wilson, 2002). Severe flooding, heavy rains and rising air temperatures may increase the risk of infectious diseases, single-cell parasites and viruses. When the pathogens grow more common the risk of having them in drinking- and bathing water increases, especially within regions with livestock management (Lindgren et al., 2008). Flooding in areas with contaminated soil can lead to leakage of hazardous substances, which in turn can contaminate drinking water and affect human and animal health (Andersson-Sköld et al., 2008). Flooding may affect trading and force production to stop when stocks may be destroyed or transport or infrastructure may be disturbed. Large costs arise in developed areas and may take long time to rebuild. Important public structures such as roads, electricity, heat and water resources can be knocked out or be disturbed for a long time after a flood event. When planning, if flood risks are taken into account, many of these negative consequences will be preventable and might be avoided in the future. Factors to have in mind which affect the consequences after floods are; how well the event can be predicted and how long it takes for the warning to be issued, how fast the water level rises, the speed at which the water comes and what depth the flood will be, and last, for how long the area is flooded before the water retreats (FloodSite, 2009; Keller & Blodgett, 2006). Concepts such as return periods, risk and probability are factors which should be taken into account when planning for a flood event to occur and its potential consequences if it occurs (Marshak, 2008). Structures which hold long life cycles accumulate a large probability for a flood event to occur and even destroy the structure. This is why risk objects such as dams usually set the limit at, or even beyond flows with a return period of about 10 000 years. The probability on 100 years of exposure will then reach about 1%. 2.4 Causes for a flood event to occur in Gothenburg There are different types of causes for a flood event to occur in Gothenburg. Flood can occur along watercourses, in connection to lakes and coasts and due to heavy rains at local areas which is not adjacent to a watercourse (Länsstyrelsen, 2012). Each one is presented below. 2.4.1 Flooding along watercourses Flooding of watercourses occur because the river/stream is supplied with more water than they are able to lead away. When this happens water will rise and eventually overflow the edges and flood areas which is normally dry (Strahler & Strahler, 2005). The water flow will increase and may cause flood even downstream. Heavy rains can within a couple of hours overflow small streams and rivers, while the process becomes more drawn out for larger watercourses (Keller & Blodgett, 2006). This type of flood events will increase in the future due to more precipitation and higher flow rates during autumn, winter and spring (IPCC, 2012, 2013b). 2.4.2 Flooding of areas not in direct contact with watercourses, lakes and oceans Heavy- and persistent rain may cause flooding in areas which are not adjacent to a watercourse (Ackerman & Knox, 2007). When rain falls on saturated ground or on paved surfaces such as asphalt, stone, concrete and roofs it will block the infiltration of water and increase surface

runoff. Cloudbursts are a local phenomenon and are hard to predict. Urban areas have contributed to large areas with impermeable surfaces which make it hard for rainwater to penetrate and will instead be drained away using water and wastewater systems. Cities with combined overloaded systems may experience significant problems with backflow which causes flooding in buildings and overflow of wastewater. The precipitation intensity and frequency will increase in the future, which most of the sewer systems are not designed for (Keller & Blodgett, 2006). Today there are problems in Sweden of dimensional character (see Figure 6 and 7). The sewer system cannot drain the amount of water and when they get full, backflow occur in toilets, sinks and wells (SOU, 2007).

2.4.2.1 Fronts Floods can be caused by heavy rain during the course of a few days. The persistent rain causing floods is often connected to several front passages. A front is the transition zone between two air masses. In a warm front warm air replaces cooler air, while a cold front is the zone where colder air replaces a warmer air mass. Warm fronts have a large horizontal extent and moves slowly (a passage may take several days). The vertical lifting of air is on a large scale and often quite weak, explaining the moderate precipitation that can persist for several days. The cold front moves faster and therefore have a steeper slope at the front zone than the warm front. Usually stronger contrast in temperature and moisture are observed compared to the warm front. There is more vertical motion giving rise to heavy precipitation and sometimes thunderstorms. The cold front passage is usually fast (<24h) connected to more intense precipitation (Ackerman & Knox, 2007).

2.4.2.2 Cloudbursts The amount of precipitation must significantly exceed normal, in for example one month, one day or one hour to be called a cloudburst. According to SMHI the definition for cloudburst is at least 50 mm precipitation during one hour or at least 1 mm precipitation in one minute (SMHI, 2011a). Most of the cloudbursts occur during summer in conjunction with heavy rains and/or thunderstorms (Ackerman & Knox, 2007). If as much as 90 mm precipitation falls within an area of 1000km2 in 24 hours, high flows in small and large watercourses will occur. The most extreme precipitation events in Sweden occur in adjunction with fronts, and the largest parts of the floods occur when many of these fronts come close after each other (SMHI, 2005a). Consequences of heavy rains will affect many sectors such as drinking water supplies, rainwater- and sewer systems (see Figure 6 and 7), disorder in the public transportation, electricity- and gas supplies, tele- and internet communications and heating supplies. Extensive property damage is also seen and is widely affecting the community. Heavy rains may also affect the degree of erosion, landslides and mud flows. Agriculture, livestock management, environmental loss, economic loss, tourism disturbance, health and social consequences, protection and security issues and dam failure are also included in the consequence range of heavy rains (Prasad et al., 2009). The largest precipitation amount measured by SMHI during one day is 198 mm. 185 mm during 3.5 hours and 52 mm within 15 minutes. Extreme events with at least 40 mm are most common during the summer months August and July followed by September and June. Within these four months 85% of the events will be found (SMHI, 2005a). Cloudbursts of 15 minutes are most 10

common during the afternoons/evenings during the second half of July, but can occur during all hours of a day between June and October (SMHI, 2012c). A study by Berg, Moseley, and Haerter (2013) shows that for increasing air temperatures extreme precipitation to a larger extent is caused by convective clouds, rather than stratiform clouds (i.e. fronts). Since flood events are often caused by extreme precipitation, thus, with rising air temperatures flood-events caused by convective clouds is likely to become more common. A changing climate leads to changes in the frequency, intensity, spatial extent, duration, timing of weather and climate extremes, this can result in unprecedented extremes (IPCC, 2012).

Figure 6 and 7. A drainpipe during a cloudburst that struck Mölndal in June 2014. Photo: Susanna Gelin 2.4.3 Flooding of lakes The term lake includes a wide range of water bodies, such as ponds, marshes and swamps (Strahler & Strahler, 2005). In large lakes the time lap for a flood event is more prolonged than in a small watercourse. The water level in a lake is responding to the climate within the catchment area. Factors which will affect water levels in lakes are how large the catchment area is, how the outlet is formed and what the conditions look like downstream. The moderating effect will depend on the lake’s size and how it drains. A flood will occur when the input is larger than the outflow during a sufficient time (SOU, 2007). 2.4.4 Coastal flooding Coastal flooding (see Figure 8 and 12) will contrary to a lake flood-event occur when the sea- level rise due to a passing low pressure and/or heavy winds (Holden, 2008). The most extreme levels will usually last a few hours, and will occur a couple of hours after the storm’s maximum. How extreme the event will be depends on the starting point of the water level. If the water level is low before the storm comes, the levels will probably not be critical (Länsstyrelsen, 11

2012). One example of such a low pressure was on the 5th of December 2013. The storm Sven struck the southern parts of Sweden (see Figure 8) with wind gusts of hurricane force and increased water levels high above normal (122 cm above average sea level) (SMHI, 2013e).

Figure 8. Flooded part of Packhuskajen during the extra-tropical cyclone Sven that struck Gothenburg in December 2013. Photo: Susanna Gelin 2.5 Local factors that affect sea level change The sea level varies over time and the current sea level for a certain place is affected by winds, air pressure, the density of water, land uplift and the world’s oceans water level (SMHI, 2014b). Sea level rise will be felt both through changes in mean sea level but perhaps more importantly, through changes in extreme sea level events, such as storm surges. Even if extreme weather conditions do not increase, extreme sea levels will occur more frequently due to that the sea levels of a given value will be exceeded more frequently. This change in the frequency of extreme events has already been observed at several locations, and this is dependent on local conditions. Events that currently occur once every hundred years could occur once every few years (UNEP, 2014). 2.5.1 Air pressure The lower the air pressure at a certain place, the higher sea level. A pressure decrease of 1 hPa raises the sea level by 1 cm (Holden, 2008). The water levels in the ocean varies day to day and week to week depending on the changing weather situations. The atmospheric pressure has a direct influence on the water level. The average water level in a year is 0 cm and the mean air pressure 1013 hPa. As the air pressure in a normal year varies between 950 hPa and 1050 hPa, the water levels varies because of this between -37 cm and +63 cm (SMHI, 2009d).

2.5.1.1 Low pressure systems Low pressure systems, also known as extra tropical cyclones, are developed as a disturbance at a front zone. In mid-latitudes the low pressure systems are mainly created along the polar front. Most of the low pressure systems hitting Sweden are developed far out in the western Atlantic Ocean. The strongest winds are often found behind (west of) the low pressure system. During winter whole string of pearls of low pressure systems can come wandering across Sweden with only day’s intervals, originating from the Atlantic Ocean and the North Sea. When the cold air mass catches the warm air mass, the transportation of warm and moist air from the ocean surface up in the atmosphere will cease and the low pressure system will decrease in strength (Bernes & Holmgren, 2007).

2.5.1.2 Storm surge Storm surge is an abnormal rise of water generated by a storm. This rise in water level can cause extreme flooding in coastal areas. A storm surge is produced by low pressure and by water being pushed towards the shore by the force of the winds (see relationship below) moving cyclonically around the storm (Abbott, 2008; MetOffice, 2014).

Very low atmospheric presure + strong winds → storm surge The maximum potential of a storm surge for a particular area depends on several different factors. Storm surge is a very complex phenomena due to its sensitivity to the slightest change in storm intensity, forward speed, size, angle of approach to the coast, central pressure and the shape and characteristics of coastal features such as bays and estuaries (MetOffice, 2014; NWS, 2014). Extra tropical cyclones often strike Sweden during winter and autumn. The southern and central parts are the most common places. In Sweden during the last 100 years, six storms have been extreme; 1954, 1967, 1969, 1999, 2005 and 2007 (Rummukainen, 2010). During a storm in the Gothenburg area, there is often westerly winds which bring water from the Atlantic Ocean towards the coast (Göteborgs Stad, 2006). This in a combination of high wind speed, low pressure and high waves that result in high water levels. But this occur with a delay, so the highest water level occurs first a few hours after the storm's maximum, see figure 10 and 11 (Holden, 2008). Storm surge extremes may increase along the North Sea coast towards the end of this century (Weisse et al., 2012; Woth et al., 2006). Low-lying areas are the most threatened, and significant impacts may be associated with changes in interannual variability and changes in extreme sea levels resulting from storms. More extreme storms are expected in the future. Extreme sea level scenarios due to changing storm characteristics are therefore needed to be considered along with mean sea level rise scenarios. Coastal cities are most vulnerable to storm surges and may experience extensive damage to infrastructure and buildings (UNEP, 2014).

In rare cases sea level could change close to the coast and vary more than a meter during a period of only 5-60 minutes. This phenomena is called meteotsunami or meteorological tsunami and emerges in conjunction with a cold front or a thunderstorm due to irregularity in air pressure and/or wind. Meteotsunamis are observed yearly in Sweden, and during its extreme 123-132 cm over normal has been observed (in Ystad) during a time period of 10 minutes (Monserrat, Vilibić, & Rabinovich, 2006; Nyberg, 1979; SMHI, 2009e). Meteotsunamis are a common

phenomenon at the island Marstrand close to Gothenburg. Why some places are more recurring is not properly understood, but may have with the seafloor conditions and otherwise favorable topography to do (Hammarklint, 2014). Since the phenomenon is not fully understood there is a reason to take it into account when investigating local factors that affect sea level change in Gothenburg. Especially since the climate will be warmer in the future resulting in changes in the atmosphere (e.g. heavy precipitation) (IPCC, 2013b). 2.5.2 Wind effects for Gothenburg The wind over the ocean creates both waves and surface currents. Southerly to westerly winds creates waves and a surface current that will carry the water towards the West coast of Sweden. This forms a misalignment of water piling-up against the coast, which means that the water level rises. Similarly, the water level drops when the wind blows away from the coast. The wind is also effecting the short-term variations in sea level connected to waves and swells. (SMHI, 2009h). The size of the wind-generated waves depends on three variables, wind speed, duration of the wind and the fetch. High mean wind speed increases the driving force of the waves, to create large waves the wind must be constant, not just a wind gust here or there. The duration is how long the wind blows over the open water, and the fetch is the distance of open water over which the wind blows (Ackerman & Knox, 2007). The term wind filling means piling-up of water (in this case the Skagerrak and Kattegatt) due to strong low pressure systems and/or persistent strong winds from the west or southwest across the North Sea. The piling-up rises the sea level for the area (SMHI, 2009h). 2.6 SMHI’s warning system SMHI’s forecasting system provides the basis for the task of issuing warnings to prevent and limit injuries and damage to people, property and the environment. The warnings are distributed to government agencies, county administrative boards, municipalities, power companies and water-regulation enterprises and to the media. The warnings are issued on the radio (channel P1), to inform the public. The warnings are also found on SMHI’s website. SMHI’s weather warnings system are today given in three categories, from certain risks to the public and disruption of community functions in category 1, to very extreme weather with great danger to the public and major disruption of important functions in category 3. During categories 2 and 3, the public is encouraged to follow the development trough radio, television and/or on the Internet. The warnings apply for land, sea and mountains. Warnings are issued for wind, rain, lightning, risk of fire, snowfalls, ice, frost, and high flow rates (SMHI, 2009b; SOU, 2007). The warning system for high sea levels within Gothenburg’s estuary started to develop in year 2006. The current warning levels for Kattegatt are:

 High water levels, class 1: water levels ≥ 80 cm. Risk for small marinas and certain quays to be flooded.  High water levels, class 2: water levels ≥ 120 cm. Risk for coastal roads and ports to be flooded.

SMHI warnings for high flows within watercourses:

 High flows, class 1: could cause minor flooding. Occurs on average every two years.

 Very high flows, class 2: flooding problems of vulnerable areas. Occurs on average once every ten years.  Extremely high flows, class 3: causes major flooding. Occurs on average once every fifty years.

SMHI warnings for high water levels within lakes (issued most often in Sweden’s six largest lakes.) are:  High water levels in lakes, class 1: could cause minor flooding. Occurs on average every two years.  Very high water levels in lakes, class 2: flooding of vulnerable areas. Occurs on average once every ten years.  Extremely high water levels in lakes, class 3: causes major flooding. Occurs on average once every fifty years (SMHI, 2014e).

SMHI issue warnings for high water levels 24 hours before the water is expected to reach the warning threshold. This is decided based on the information SMHI receive in their models. If SMHI issues a warning for Kattegatt it is not directly determined that Gothenburg will receive high levels, because the model simulated levels above the threshold for a warning, somewhere along the Kattegatt coast (de Koster, 2013). Currently SMHI has high readiness for flooding, and issue warnings for heavy rains and as mentioned earlier, for high flows in rivers and watercourses due to persistent rain. A serious problem for society is precipitation with short duration and high intensity. SMHI want to expand the warning system for such precipitation (see two examples of future warnings further down). Precipitation is monitored best trough weather radar. In Sweden, almost the whole country is covered with radar, but current (2009) radar system is old and is in great need of an upgrade, which is very costly according to SMHI (SMHI, 2009g). Today there are two warning classes for precipitation:

 Abundant precipitation, class 1: ≥35 mm/12 hours – prevalence area: ≥ 1000km2. Risk for pools of water, risk of flooding in basements and of water and sewer systems.  Very high amount of precipitation, class 2: ≥70 mm/24 hours – prevalence area: ≥ 1000 km2 Very high risk of flooding of water and sewer systems and small streams. Risk of large pools of water, especially in basements and depressions which can result in blocked roads.

SMHI warnings for thunderstorm, which can result in flooding:

 Severe thunderstorm, class 1: extensive and frequent thunderstorm: causing major disruptions in electricity and tele-systems. Locally wind gusts and cloudbursts can also occur.  Very severe thunderstorm, class 2: very extensive and frequent thunderstorm: causing very severe and major disruptions in electricity and tele-systems. Locally, very strong wind gusts and cloudbursts can also occur (SMHI, 2014e).

Possible future warning classes for more extreme rain-events than today:

 10 x 10 km2 – 60 mm/1hour  33 x 33 km2 – 120 mm/24 hours (SMHI, 2009g).

SMHI’s warning system is crucial for reducing the consequences of natural disasters. The warning system should be further supplemented for risks of intensive local rainfall, drought, heat waves and storm-felling. Regarding these weather events, the possibility of creating such a warning system should be developed and analyzed (SOU, 2007). 2.6.1 Warning system development The radar upgrade is taking place right now together with the Swedish National Defense. This is an expensive and time consuming task which will take three more years to complete. SMHI started to operate a new forecasting model in Mars 2014. This model has a higher resolution and will provide a better probability-foundation for heavy rains along with a better picture of the atmospheric state when implemented with radar data. A new radar technology, called Dual Polarization, can distinguish between the types of precipitation. Ensemble modelling is right now the best way to create probability scenarios. The development of radar technology, implementation of radar data in the model input, and the increased model resolution will provide a better tool in the future predicting heavy rain events. The proposed warning level of 60 mm/1 hour is not possible with present technology, so therefor it is put on hold. The greatest challenge right now is the heavy rains during summertime. SMHI’s do not want to warn the public for no reason. If warnings are issued too often and for events that do not occur, the public may ignore the next warning and will not take precautionary actions. Therefore, SMHI is continuously working with the warning system and adjusting its criteria (SMHI, 2014f). 2.7 Risk, vulnerability, exposure and adaptive capacity The following key concept is throughout time well discussed between several authors and defined in many ways in academic literature. Below, a brief explanation to each notion will be given to broaden the knowledge for further discussion about weather-related flood events. Risk is recognized in both the social and natural science as a combination of hazard, vulnerability, exposure and coping capacity. Which components and how they are defined, measured and evaluated differs greatly between these disciplines (Robert, Nadim, & B., 2007). The notion of risk involves both uncertainty and some kind of loss or damage that might be received. In the assessment and analyzing of flood-risk, it is important to remember that risk is entirely a human issue. Floods are a part of the natural hydrological cycle and are random (Samuels, 2006). Hazard is defined as a source of danger while risk is the possibility of loss or injury and the degree of probability of such loss (see relationship below). Increasing the safeguard by awareness will reduces risk (Kaplan & Garrick, 1980). As stated in Andersson-Sköld, Bergman, Johansson, Persson, and Nyberg (2013) has Kaplan and Garrick’s definition since then been used for technical, natural science and medical risk assessments. The definition is nowadays often referred to as a function of consequence and the probability of any event that may cause 16

negative consequences. Risk, consequently, can be reduced either by reducing the probability, the potential consequences of the event or both.

risk = f (probability/uncertainty, damage) Although flooding is considered to be a hazard, and sometimes a disaster, it is important to remember that flooding is a natural process. It becomes a hazard only when people live or build structures close to flood prone areas (Keller & Blodgett, 2006). Variables related to exposure normally include proximity to the source of threat, incident frequency or probability, magnitude, duration or spatial impact (Cutter, 1996). Exposure is the nature and degree to which a system is exposed to significant climatic variations (Füssel & Klein, 2006). Gothenburg’s proximity to the sea makes the city sensitive to global sea level change and extreme sea levels such as for an extra-tropical cyclone passage. The sea level rise and the extra- tropical cyclone are both the source of threat regarding flood events. Heavy rains and cloudbursts along with high levels and discharge in river Göta älv are furthermore sources of threats for flood events to occur in the region (SMHI, 2005b; Stad, 2006). Causes of high flows in river Göta älv with flooding as an outcome are according to Göteborgs Stad (2006) changes in land use, water power expansion, spatial planning and urbanism and climate change. There are several definitions about vulnerability (McCarthy, 2001; Sarewitz, Pielke jr, & Keykhan, 2003; Wisner, 2004). The origin is often the initial point of disagreement. The broad definition of vulnerability indicates a potential for loss. Various elements involved in the vulnerability notion will make the vulnerability to change over time, based on changes in the elements (within which environmental hazards occur) (Cutter, 1996). The definition of vulnerability that IPCC gives in their Third Assessment Report is: “The degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including climate variability and extremes. Vulnerability is a function of the character, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity” (McCarthy, 2001). Within this study, vulnerability is defined as when GP and/or MSB have reported consequences of weather-related flood events for Gothenburg and Mölndal municipalities. The concept of resilience is central to the understanding of urban area vulnerability. Resilience is the capacity of a community or society to adapt when exposed to a hazard (Prasad et al., 2009). Many definitions of adaptive capacity exist e.g. (Adger, 2001; Brooks, 2003; IPCC, 2007; McCarthy, 2001; Spanger-Siegfried, Dougherty, & et.al., 2003). The word sensitivity, Füssel and Klein (2006) describes as the degree to which a system is affected by e.g. climate related stimuli. Consequences of climate change on natural and human systems are depending on the consideration of adaptation. 2.8 Methods to reveal vulnerability Measuring vulnerability against risks and threats in our society is raised in various contexts and is becoming increasingly more important to achieve effective risk management and a robust society. Vulnerability against natural catastrophes and natural disasters is highly geographically, economically and demographically determined. Due to this, great differences 17

are found between developed countries and developing countries (Johansson & Blumenthal, 2009). The risk for natural hazards is increasing in many areas in Sweden and it is necessary to begin the adaptation as soon as possible. It is crucial to create a clear picture of how the vulnerabilities look and where they are located. It is of importance to reflect and draw conclusions from experiences of past weather patterns and disasters, towards reducing risks, vulnerabilities, and negative impacts associated with water-related events. Also to avoid disastrous consequences in the future (UN/ISDR, 2003). One of the essentials for making cities disaster resilient is to know your risk. This could be done by prepare and maintain an up to date database on past hazards, vulnerabilities and disaster losses from past weather events and current potential hazards in the city. (FN, 2005; UN/ISDR, 2012). The vulnerability picture of flooding is complex. By studying historical weather-events which have led to serious disruptions in Sweden, we get a picture of how vulnerabilities look in terms of consequences and management, as well as other aspects such as lessons learned and prevention (Johansson & Blumenthal, 2009). One method to use to reveal vulnerability for a city or locality is to make an LCLIP, the method aims to create a better understanding for local authorities about the city’s exposure and vulnerability against weather and climate, as a long run guidance towards adaptation and resilience to face the changing climate (UKCIP, 2009). 2.8.1 LCLIP LCLIP is a resource that local authorities can use for a better understanding for their exposure to weather and climate. When looking back over the last few years it is possible to learn about present sensitivity to climate risks and how they are manageable. It will also give a picture of what future climate might bring (UKCIP, 2009). An LCLIP is a snapshot in time. LCLIP will show the current vulnerability of a particular organization or locality, to recent weather. The focus for an LCLIP is the consequences that arises from a weather impact. By highlighting the most obvious examples of the impacts, their depth and extensiveness of these impacts, the more extensive the LCLIP will be. Searching for weak points in a system, cataloguing relatively low impacts which are frequently repeated is of importance to achieve a wide and fully reliant LCLIP. This might identify locations that are repeatedly affected, and also especially vulnerable groups within a local population in certain locations. In a wider perspective, who is responsible for what – and when? LCLIP opens up opportunities to consider different kinds of responsibilities between many different actors and decision makers not only on a local scale but also within neighboring communities and their authorities (UKCIP, 2009). The method media trawl is a method developed by UKCIP (2009), to capture important information by monitoring local newspaper articles as a main source. Through weather related news stories information about the weather event and the consequences can easy be captured and framed. By making a spreadsheet, it allows data to be sorted using different criteria, such as date, location, weather type, consequence, responsible agency, etc. This method will raise awareness and understanding of current vulnerability to weather events and climate on a local scale (UKCIP, 2009).

2.8.2 Application and development of LCLIP in Sweden Municipalities that already have produced LCLIP’s in Sweden are Burlöv, Helsingborg, Landskrona, Ljungby and Lomma. In the UK more than 100 councils have produced an LCLIP (FOI, 2014a, 2014b). Results from earlier studies (Carlsson-Kanyama, 2009; Kotecha, Thornes, & Chapman, 2008) show that an LCLIP gives a clear picture of the vulnerability to extreme weather-events for a particular city. Previous studies also gives the recommendation to continue the work with LCLIP’s and to enhance more information and data into the profiles. 2.8.3 MSB’s archive Incident reports for when the emergency service have hade call-outs is collected in a database managed by MSB. The database contains all types of incidents, but for this study focus have been on flood-related weather events (see more in section 4.2). The purpose with this database is among other things to assist scientists with valuable information and statistics.

According to MSB (Asp, 2014) they are developing the design of the incident reports right now. The aims for the improved incident reports are among other things;

 Should be the starting point for deeper investigations, if needed.  Indicate what measures performed on site.  Support the alignment of both the preventive and the damage or injury activity.  Provide a picture of accidents within the organizations geographical area.  Provide a picture of the events in society that causes emergency operations, their causes and consequences.  Identify vulnerable groups within society.  Provide research and other studies with data.

The incident reports should serve both for local and international perspectives. Journalists, researchers and authorities are at regular basis in contact with MSB. Authorities using the information within the incident reports are among others; the Transport department, Transport Board, The State Accident Investigation Board, Police Department, County Administrative Board, Forestry Board and EU (Asp, 2014).

Figure 9. Flooding due to high sea level in river Göta älv at the passage of the extra-tropical cyclone Sven that struck Gothenburg in December 2013.The picture is taken at the Emigrantvägen, between freeway E45 and the Denmark Terminal. Photo: Susanna Gelin

3. Study area Gothenburg, a city founded in year 1621, built on marshland and situated on the Swedish west coast (57o44’N, 11o85’Ö) see Figure 10. Today the city is the second most populated in the country. The municipality has approximately 532.000 inhabitants (Göteborgs Stad, 2014c) on an area of 447 km2 whereas about 15, 5 km2 is water. Gothenburg has the largest port in Scandinavia which has 24 km of quay and transport 42 million tons of goods every year (Port Of Gothenburg, 2014). Almost 1 million people live in the metropolitan area (Boverket, 2014). The city is located at the mouth of river Göta älv, which borders the Kattegatt. The western part of the municipality consists of an archipelago and fjord coast (SNA, 2003). With northern European dimensions the Gothenburg area is a large and growing urban economy and represent one-tenth of the Swedish economy. Since the first part of the 1990’s Gothenburg has a growing population of approximately 7000 inhabitants per year. The region has the second highest economic growth and is the country’s most prominent export region with high availability in global freight network (BRG, 2014).

Figure 10. Gothenburg and Mölndal’s location. 3.1 Present hydrological and meteorological aspects of Gothenburg Gothenburg has a seasonal maritime climate with mild winters and cool summers, due to the ocean and its ability to store heat, which evens out the temperature variations between seasons and also day and night (Persson et al., 2011). According to the Köppen-Gieger climate classification system, the climate is referred to as Cf climate (warm temperate, fully humid) (Kottek, Grieser, Beck, Rudolf, & Rubel, 2006). The Gulf Stream affect the regions climate strongly and brings moist air into land. This makes the region about 11°C warmer than the average latitude temperature. Since Gothenburg is located in the mid-latitudes at the northern hemisphere the climate is characterized by both low and high pressure systems. The area is located within the Westerlies, therefore the most dominant wind direction is western to south- western (SNA, 2003). The wind is influenced by sea breeze during the summer and land breeze during the winter (SMHI, 2013c). Low pressure cells in Scandinavia often originate from the Atlantic Ocean, characterized by warm and cold fronts that moves in easterly direction. The low pressure cells generally start as a small disturbance at the polar front which grows into a large wave pattern. The polar front represents the border between the southern temperate air

masses and the cold polar air masses (Bernes & Holmgren, 2007; SNA, 2003). The mean temperature for Västergötland and Bohuslän is during wintertime (Jan-Feb) -0,5°C to -4°C. The mean temperature for July is for Västergötland and Bohuslän +15o C to +16oC The highest/lowest temperature in the ocean is +20o C and -5o C (SMHI, 2009f). 3.1.1 Precipitation The annual mean precipitation in Gothenburg is ranging from 800 to above 900 mm/year, the lowest values are found in the archipelago e.g. Hönö and Öckerö while the higher values are found inland. Most distinctly is the difference during summer when the sun heats the ground surface more than the sea surface, air above land rises and cools, and creates afternoon showers (SMHI, 2013b). In the catchment area the highest annual means reach above 1000 mm/year (SMHI, 2013b). The monthly mean precipitation during summer is about twice the amount as during winter. However, the precipitation amounts in summer falls in half the time compared to winter due to heavier and more frequent rain. The air during summer contains more water vapor and can produce more rain (SMHI, 2011b). 3.1.2 Catchment area Gothenburg is located close to the sea, different lakes and various types of streams. A large river, meandering creeks and bustling as well as peaceful streams. The lakes and streams occupies approximately 14 km2 which is about three percent of the municipality’s total area. In the region there are small waterfalls and flood irrigation areas as well as swamps and bogs (Göteborgs Stad, 2014b).

3.1.2.1 River Göta älv River Göta älv (see Figure 11) is the water richest river in Sweden with an average water flow of 550 m3/s, which makes the river one of the largest rivers in Europe. The catchment area represent one tenth of the country’s land area and is the largest in the country (GÄV, 2011). River Göta älv begins its course in Vänern and culminates in Gothenburg, with a total distance of 93 km and a flow time of 1.5-5 days. River Göta älv is the only outlet from the lake Vänern, Sweden’s largest and Europe’s third largest lake. The total drop between Vänern and the sea is 44 m with a hydroelectric dam in Trollhättan as equalizer. Kungälv divides river Göta älv into river Göta älv and river Nordre älv. Between 2/3 and 3/4 of the water flow goes into the river Nordre älv (GÄV, 2011). River Göta älv flows through six municipalities; Vänersborg, Trollhättan, Lilla Edet, Ale, Kungälv and Gothenburg (SGI, 2012). The river flows through a changing landscape and is characterized by natural erosion and landslides processes. Higher- and varying flows and floods can cause landslides along the river. The area belongs to one of the most frequent landslide hazardous areas in the country and the largest landslides are due to quick clay. The reason is that the valley of Göta älv is built up with massive and loose clay layers that was once deposited in a marine environment. The landslide risk will increase in a warmer climate. The river is a major transportation route. 2, 4 million tons of goods are transported on the river every year which equals to about 1600 cargo ships and 4000 recreational boats during summer (SGI, 2012). The ports, industries, buildings and infrastructure increase the landslide risk. Increased erosion and landslides will affect areas with contaminated soil and water inlets. Within river Göta älv’s catchment area there are 25 tributaries of which Säveån is the largest, followed by Slumpån, Mölndalsån, Grönån, and Lärjeån.

3.2 Mölndal municipality Mölndal is the third largest municipality in the region Västra Götaland and is located just south of Gothenburg. Mölndal has about 60 000 inhabitants and an area of 152 km2, where approximately 6.5 km2 is water (Mölndals Stad, 2013). 3.2.1 River Mölndalsån Mölndal means the valley of mills. The stream Mölndalsån has an old history of powering all the watermills in Kvarnbyn, an old mill village. The high and narrow long waterfalls gave necessary power to all the watermills, which together with all the windmills on the hills gave birth to early industrialization of Mölndal in the 17th century. Industrial emissions once made Mölndalsån to Sweden’s most polluted stream. Today, however, the water quality has improved significantly. Mölndalsån (see Figure 11) has a long history of floods. Way back in time the river Mölndalsån was called Grodha, which means The often flooded (Svensson & Tjäder, 2007). The last major flood occurred during year 2006, when large parts of Göteborgsvägen (the main road between Mölndal and Gothenburg) stood under water, causing huge damage to houses and infrastructure. After this massive flood the municipality has excavated and deepened the stream so the water can easily pass. Today the municipality of Mölndal, Härryda and Gothenburg collaborates to prevent future flooding. Apart from digging out the stream a surveillance system has been installed, which electronically monitors the water flow and water levels in Mölndalsån (Mölndals Stad, Figure 11. Shows the river Göta älv’s (blue) and 2014a). the river Mölndalsån’s (green) pathway. www.google.se/maps

4. Methodology To investigate Gothenburg and Mölndal and their sensitivity to weather-related events and in this case weather related flood events, the method media trawl has been used. This is a method based on searching for articles in local newspapers. During the very beginning of this project in March 2012, writing my bachelor thesis (Hur har Göteborgs-Posten rapporterat väderhändelser och deras konsekvenser i Göteborg under perioden 1991-2011 – Ett första steg till en lokal klimateffektsprofil över Göteborg) together with my fellow student Marie Svensson, we created a database containing weather-related consequences from 470 articles from the local newspaper Göteborgs-Posten using selected keywords (see Appendix A.1.1). The aim was to find out how vulnerable Gothenburg is to different weather-related events (see the first step in the method below). Throughout this thesis the work with collecting news articles continued (see the second step in the method below). This time, however, only weather-events regarding floods were selected. Furthermore, new articles were found by applying a wider range (1991 to 2013- 09-12) and a wider area (Mölndal municipality was added) and new keywords (see Appendix A.1.2) when searching for articles in Mediearkivet. To obtain a broader perspective on Gothenburg’s vulnerability an additional source of weather-related flood events were selected i.e. incident reports from the emergency service collected from MSB. To be able to investigate the vulnerability even further, a climate dataset were chosen, in this case including the parameters precipitation, sea level, wind speed, wind direction and air pressure. Subsequently, the articles from GP and the incident reports from MSB where compared with climate data. Each one of the data series are explained further down. 4.1 Media Trawl in Göteborgs-Posten Media trawl is a method developed by UKCIP, and is designed to capture important information for authorities by monitoring local newspaper articles as a main source. Through weather- related news it is possible to store information about the weather event and its consequences can easily be captured and framed. The tool LCLIP spreadsheet is made for this particular method. Making a spreadsheet in Excel, data could be sorted using different criteria, such as date, location, weather type, impact, detail of consequence, responsible agencies taking necessary measures etc. The method aims to provide awareness and understanding of current vulnerability to weather events and climate on a local scale. Knowledge about existing vulnerability is the primary opening and also a preparation for an adaptation strategy (Carlsson- Kanyama, 2009; Kotecha et al., 2008; UKCIP, 2009). For further information about the event, interviews with local authority staff and other sources can be implemented (UKCIP, 2009). 4.1.1 First step (during Bachelor thesis and repeated in this Master’s thesis) To broaden the information of all method steps within this thesis, a short explanation is needed for some of the steps performed during the Bachelor thesis and the created original database from 2011. These steps are repeated for this Master’s thesis. The newspaper GP was selected due to its targeting on the Sweden’s west coast and Gothenburg. GP was an obvious choice because it has been the main newspaper in the region since the first half of the 19th century. GP reaches around 600 000 readers every day and provides the public with news, reports, reviews and articles from all over the world but has its main focus on the Gothenburg area (GP, 2013). 24

To limit the study only articles within Gothenburg municipality have been included. When searching for articles two different approaches have been used. Regarding articles between the years 1991 to 1993 microfilms from the Social Science Library earlier called The Undergraduate and Newspaper Library (Kurs och tidningsbiblioteket - KTB) were used (articles before year 1994 are not in digital form). For the years 1994 to 2011 the digital news archive Mediearkivet (Retriever, 2014) has been used. During the search on microfilms the emphasis has been placed on the front page, the news section and the local news section. Other news sections such as the international news and the political news have only been skimmed through as it was gradually noted that no relevant information was to be found here. To get an idea of the quantity, about 120 hours have been put into research for microfilmed articles. 108 microfilm rolls have been screened, representing approximately 1090 newspapers. Mediearkivet is the most extensive digital news archive in Scandinavia. It stores printed material from all the major newspapers, provincial newspapers and hundreds of magazines, journals and periodicals. Retriever is the Swedish, Norwegian and Danish distributor of Lexis Nexis, the world’s largest database of international news and business information (Retriever, 2013a). More than 25 000 articles and 25 000 blog entries pour into the massive archive every day (Retriever, 2013b). Before searching for articles in Mediearkivet trough the search engine Retriever a number of keywords where selected (presented in Appendix A.1.1, first step) in order to set a limit and to sort out relevant articles from GP. The keywords were chosen by how the weather-events had been referred to on the microfilms. GP was the only newspaper selected in Retriever along with the optional Swedish printed media, and the chosen time period (1994- 2011). Also optional was the word Göteborg which was selected to limit the hits to only contain articles including the word Gothenburg. During the search, the keywords where sought after in the whole article and not just in the heading. Each year received between 400 and 600 hits due to the keywords, a total of between 6 800-10 200 articles. These articles were read and the ones of relevance, that contributed by answering given research questions where then added to the database. The relevant articles had to fulfill a set of criteria; have occurred within the selected study area, the event occurred due to the weather and the event gave consequences for society. All together 470 articles were found in Mediearkivet and on microfilms regarding weather related events during the period 1991-2011. A cross-match test were made early in the article search to investigate if the same article was found both in Mediearkivet and on microfilm. One article was randomly selected from one of the microfilms from year 2000 about a flood event. This article were then searched for in Mediearkivet and was not found. It is important to mention that due to this some articles probably failed to be discovered. However, the chance for finding all relevant articles on microfilm are greater, because all pages were manually researched. One can suppose that even if the amount of keywords are limited, most of the relevant articles are believed to be found because many of the keywords are used throughout the articles. Information from all relevant news articles from GP were then stored in a database as Excel sheets. The headers for each column were for example; date of issue, date for the event, type of event, reported consequences, place, time/length, measure, heading and source.

4.1.2 Second step (Master’s thesis) During the second step all reported weather-events regarding flood-events where selected from the original database (from first step) to fit the aim for this study. Articles from the categories wind, precipitation, high water levels and weather warnings were examined and articles not including flood-events were discarded. A new search in Mediearkivet was made with new keywords concerning floods (presented in Appendix A.1.2, second step) and an extended time period (1994-01-01 to 2013-09-12). Following the same principle as during the search in the first step. To broaden the study area the municipality Mölndal was added. Additional headers were added to the excel sheets: sub-group designation and headings for what kind of social function that was affected such as for example infrastructure, buildings or an congested emergency service. The extended database, is now containing a total of 617 articles. Articles from first step plus new flood articles (for this thesis) and new heat articles (for Marie Svensson’s master’s thesis). All weather related articles from GP were sorted into 10 categories depending on what caused the consequences driven from the weather event. For example a snowstorm is placed in the group precipitation and not in the group wind, while a storm (absent of snow) is placed under wind and not rain. The categorization is dependent on what was described in the article. In an article about a storm, we can assume that it has been raining. But if rain is not mentioned in the article about the storm it cannot belong to the category precipitation, it is then placed in the category wind, see Table 1. The classification categories are; high temperature, low temperature, wind (from the category wind, only articles concerning winds with high water levels and/or referred to as storm event in GP are included), precipitation, high water levels, wildfire, drowning and swimming accidents, weather information, weather warnings and others, which contains the inversions, mist events and landslides, see Figure 14.

Table 1. Explanation of which events that are included in each specific categories (see also Fig.14).

Weather event All articles concerning the weather event, for example: High temperature Heat wave or Drought, Heat record Low temperatures Cold snap or Slippery roads Wind All wind related articles such as storms and high wind speeds. Precipitation All precipitation related articles such as heavy rainfall, persistent rain, thunderstorms and snow-related articles including snowstorm. High water levels Articles concerning high sea water levels and flooded river events Wildfire Forest and grass fires D&S accidents Drowning and swimming accidents Weather information Articles like The weather of the month or weather records, weather forecasts Weather warnings SMHI issued storm warning or SMHI issued warning for high water flows. Others The smallest groups: inversion, mist and landslides

A total of 86 articles were selected containing only flood-related weather events with consequences for Gothenburg and Mölndal municipalities during the time period 1991-2012. Note, that to make comparisons between data from year to year the GP articles from 2013 is not included in the datasets. This is due to that GP data for 2013 lack data for all twelve months (2013-09-12 to 2013-12-31 is missing). All data is still in the database, even the incomplete year, where it may be of interest for future research. It is those (1991-2012) 86 articles that serve the purpose for this thesis, and only these have been processed further. The 86 articles from GP were then sorted into 4 sub-groups depending on what information they contained describing what kind of event that caused the event; high sea level-, rain- and flooded river events and unknown cause (Fig. 16). Only if a certain article had clear information of what the cause was, they were included. If the information was unclear or missing they ended up in the sub-group unknown cause (which are not processed further). Note that one single article from GP may be included in several sub-groups (i.e. heavy rain-, flooded river- and high sea level events) if the article describes several causes for the consequences to appear. For example, the river Mölndalsån has flooded and it is due to heavy rains. This article will end up in sub-group heavy rain events and the sub-group flooded river events. Articles with no declared consequences have not been included in this study (a small amount of 5 articles). 4.2 Data from the Swedish Civil Contingencies Agency (MSB) Incident reports were ordered from MSB, containing all accident scenarios for the emergency services in major Gothenburg (Stor-Göteborg) regarding water damage, other types of water damage, storm damage, and flooding of rivers during the period 1998 to 2012. All together 20 841 incident reports. Incident reports from the emergency service operating in Gothenburg and Mölndal was then selected, a total of 2283 reports. The column accident sequence and operation implementation is the emergency service’s explanation of what actually happened on the location of the occurred accident. These were studied and all reports concerning weather related flood events were selected, a total of 484 incident reports. These 484 reports served the purpose for this thesis, and like with GP only these have been processed further. Incidents that were excluded were for example when broken pipes flooded apartments due to human negligence or when waterbeds, dishwashers, WCs or aquariums broke etc. To access this material an agreement of confidentiality was required, because sensitive information was included, such as street addresses and named tenants and owners of buildings and companies. As with the GP articles, the 484 incident reports were then sorted into 4 sub-groups depending on what information they contained about the weather cause (see Fig. 16). The sub-group titles are the same as for GP (heavy rain-, flooded river-, high sea level events and unknown cause). Articles were included only if a certain incident report had clear information in the column accident sequence and operation implementation of what type of weather that caused the emergency. If the information was unclear or missing the articles ended up in the group unknown cause. Incident reports mentioning heavy rains in conjunction with flooded river events have been included in both sub-groups heavy rain- and flooded river events. In contrary to GP articles, MSB reports seldom specify the rain event as a cloudburst or persistent rain. Important to emphasize is that the incident reports are of varying quality. In the column accident

sequence and operation implementation the information has sometimes been sparse, making it hard to determine the weather-cause of the incident. If the report states a flooded basement, - in some incidents it has not been determined if it is related to weather events or to other factors such as a house with a broken pipe. To get an as accurate picture as possible of the cause of the incidents, information from all incidents have been manually evaluated. If other reports from the same day indicate a heavy rainfall, the uncertain accident probably was due to the same cause. This kind of report has been included but referred to as unknown in the sub-groups. If other reports in the dataset, did not indicate a rain fall, and precipitation data did not indicate any large amount of rain, the report has been excluded. Incident reports without call-outs or which immediately was handed over to another instance (e.g. water and sewer) it has been excluded (only a few articles). 4.3 Comparison between GP and MSB The date of the weather-related event stated in GP was the date used in the comparison with MSB reports and climate data, and not the date the article was published. If GP did not declare a specific date for when the weather event occurred, the day before the published article was chosen. Most likely the article is printed in the newspaper the day following the event. From here on, all dates are the date of the event and not the published date. In both GP articles and MSB incident reports consequences are reported. Firstly, consequences reported in GP were divided into consequence-categories (see Fig. 17 and 19) of what kind of society function that was affected (private residence, public building, motorists/roads, tunnels/bridges, public transportation, boats, aircrafts, sport and entertainment events and water and sewer systems). Each consequence-category includes the three sub-groups that states the cause of the consequence (heavy rain-, flooded river- and high sea level events). The same sub- groups are also divided into other consequence-categories (see Fig. 18) of in what way the consequences appear (emergency service summoned, electricity and communication, fire, storm damage, flood, personal injuries). All the included articles are mentioned in the newspaper as heavy rain, flooded river or high sea level. In approximately 40% of the articles, flooding is not directly mentioned, but the text reveals that flooding is the absolute cause. For example, a football game had to change date due to heavy rains. Here it is understood that the football field was water saturated. This is a consequence of heavy rain and is therefore sorted into that sub-group. Secondly, the same type of categorization was made for the MSB reports (Fig. 19), but with other consequence-categories (private residence, public building, motorists/roads, tunnels/bridges, public transportation, water and sewer systems, basements and electricity and communication). Note that for both GP and MSB, one article/report can appear in several sub- groups and several consequence-categories. Why the articles/reports are divided into different categories are because the content in the articles and the reports are varying from each other. Investigating the relationship between articles from GP, reports from MSB and the precipitation or sea level, the Fischer’s exact test

of independence has been used (calculated at webpage1). The test shows if the input parameters are significantly independent, hence otherwise they will be dependent on each other. Four combinations are made of all days for the period 1998 to 2012 using the categorization day with/without articles or reports and days with/without weather-related event. For MSB, the reports in sub-group heavy rain- and flooded river events have been compared to the grid-data of precipitation (explained in section 5.1.7.2). If the grid-data for a day is > 1 mm it has been considered as a day with rain, on the other hand if the grid-data is < 1 mm it has been considered a day without rain. A day can contain reports, or contain no reports. This form four categories:

 Day with rain and GP/MSB report.  Day with rain, but without GP/MSB report.  Day without rain, but with GP/MSB report.  Day without rain and without GP/MSB report.

The days of each category are counted. Then assuming a null hypothesis that the relative proportions of one variable is independent of the second variable, a p-value can be calculated. If the p-value is close to zero the null hypothesis can be discarded, thus the variables depend on each other (see Table 4 and 5). For more information about Fischer’s exact test and the Null Hypothesis se webpage2. The same test has also been performed with the parameter sea level >80 cm and <80 cm (explained in section 5.1.7.3). Over all, the numbers of GP articles are relatively low, so for some figures to achieve as good as possible statistics, articles for the whole GP period (1991-2012) were selected. When a comparison between GP and MSB is made, the same time period is used (1998-2012). Note that, direct comparisons between the number of GP articles and MSB reports are rather irrelevant when studying the vulnerability. More important is whether the consequences are reported or not (consequence detection), since the number of GP articles is always low. By comparing the two sources differences are easily discovered, thus, pros and cons may be evident. By investigating precipitation patterns during the past days (2, 3 and 5 days) before consequences occur, analyzes of the importance of the precipitation’s time interval and whether the ground is likely to be saturated (i.e. several days in a row with precipitation) can be made (Fig. 34). 4.4 Meteorological and oceanographic data The climate data is used to analyze e.g. seasonal and annual values of the climate parameters precipitation, sea level, wind speed and direction, and air pressure. Each of the climate parameter datasets are explained further down. When sorting the meteorological data into seasons, the following definitions have been used; the spring months are; March, April and May. Summer months; June, July and August. Autumn months; September, October and November and finally the winter months are December, January and February.

1 http://www.langsrud.com/fisher.ht 2 http://udel.edu/~mcdonald/statfishers.html.

4.4.1 Precipitation Precipitation data were downloaded from SHMI’s webpage3, which is based on gridded daily values for Gothenburg during the period 1961-2012 with 4 x 4 km horizontal resolution (SMHI, 2014d). The mean value for each grid cell and time indication is specified. At luftwebb the observed precipitation has been adjusted for the measure losses which is mainly caused by precipitation blowing past the measurement tool at the weather station. Gridded data is very useful for many purposes, and is much easier to use if you compare with traditionally stored observation data from a weather station. The data is well suited for creating time series for a special locality (SMHI, 2014d). luftwebb has been used because the observation data from the weather stations are too sparse over the specific area and time period. According to SMHI this gridded data is not intended for use, when you are looking for heavy rainfall, because the resolution is too low (4 x 4 km). Cumulonimbus with heavy rainfall may have only a horizontal length of 1 kilometer which is too small to detect (Holton & Hakim, 2012). Note also that gridded data is derived from station observations, and the station density is too sparse to guarantee that heavy rain from thunderstorms will actually fall into a rain gauge. In this case, the grids will underestimate rain at a point. The opposite can also happen, if heavy rain does fall into a gauge, the gridding process will smooth the observed rainfall out. In such cases, rainfall for areas outside the storm path can be overestimated (SMHI, 2014d). SMHI has about 130 automatic meteorological weather stations in Sweden which measures precipitation each 15 minutes and about 700 climatological weather stations (approximately 25 km between the stations) which measure daily precipitation (SMHI, 2010). As mentioned before, convective rain is a local phenomenon with an extent of only a couple of kilometers. Rain from these kind of clouds may fall outside the weather stations, due to the stations sparse distribution. This precipitation will obviously fall outside the statistics. All information about precipitation measuring is defined in the source SMHI (2012b) and Wern (2012). One thing to have in mind is that gridded data always includes some kind of interpolation in time and space, which, with present technology gives equalization of the rain pattern. This means that, above all, short term extreme values in sporadic spots will become equalized. 4.4.2 Wind speed and direction Wind speed and direction comes from SMHI station 7142, Rantorget 57.708°N 11.992°E. The wind speed is a mean value for the last 10 minutes of every hour. There are some uncertainties present about the location of the weather station where wind speed and direction data are coming from. According to SMHI the weather station 7142 Rantorget was in use 01-10-95 to 31-05-98, and there after moved to Skansen Lejonet, and started their measurements 1999-03- 01which is still in operation. There is a time gap of 9 months while the station moved. Data before year 1995 comes from the weather station at Säve (Zinderland, 2012) The data used in this thesis have the same station number 7142, but is not missing any data for the time gap of 9 months while the station moved. Where this data comes from is uncertain, but probably the gaps are filled out with data from the station at Säve. These two stations had the same station number whilst the station at Säve was still in operation.

3 luftwebb.smhi.se 30

4.4.3 Air pressure Air pressure data is a composite of NCEP/NCAR reanalysis 1991-2010, and ERA-Interim 2011- 2013. The data is in daily minimum value. ERA-Interim is the latest ECMWF global atmospheric reanalysis of the period 1979 to present (Dee et al., 2011) and the NCEP-NCAR (R1) is the original reanalysis effort and it was extended back to 1948 and continues to this day (Kalnay et al., 1996).

4.4.4 Sea level Sea level data comes from one of SMHI’s weather station, Havspegel Torshamnen, Göteborg, station number 2109, latitude 57°̍ 41’05” and longitude 11° 47’26”. The series of data is for the period 1991-2013 and includes daily maximum value. In this study, the usage of the words “sea level” are referring to the water levels within river Göta älv’s estuary. Assuming that the levels at river Göta älv’s estuary are closely related to the sea level in Torshamnen (where observations have been made). Note that when referring to flooded river events they are concerning the river Mölndalsån, not river Göta älv. 4.4.5 METAR-data for the case study Sven METAR-data (METeorological Aerodrome Report) is distributed from SMHI and comes from the weather station at Säve airport. The METAR-data is surface observations and has hourly values. This data has only been used for the case study: the storm Sven. The data is in UTC- time (Axell, 2013). 4.5 Interviews To broaden the knowledge of the vulnerability against weather-related flood events in Gothenburg and Mölndal five people have been interviewed by phone or email. Interviews have been held with; the Emergency Service (questions about the incident reports and vulnerability against flood events), the City Planning Department in Gothenburg (questions about vulnerability against flood events), SMHI (questions about the warning system), MSB (questions about their database) and SKANSKA (questions about responsibility and flooding). All questions asked is found in Appendix B. The answers are found in section 5.1.8. Interview with Chief Editor at GP is found in Gelin and Svensson (2012).

Figure 12. Flooding of a part of The Fishing Port during the extra-tropical cyclone Sven that struck Gothenburg in December 2013. Photo: Susanna Gelin 31

5. Results This chapter begins with showing weather-related articles published in GP during the period 1991 to 2012 covering Gothenburg’s municipality. Followed by showing only flood-related articles from GP (1991-2012) together with all flood-related MSB incident reports (1998-2012) covering both Gothenburg and Mölndal municipalities. Consequences reported in GP and described in the incident reports from the emergency service are divided into different sub- groups. A case study is presented of the storm Sven, which struck Gothenburg in December 2013. Next section shows meteorological and oceanographic variations causing flood, during the time period 1991-2012 along with the parameters causing high sea level in Gothenburg. All the articles and incident reports are then compared to each other and to the meteorological and oceanographic data. Lastly, interviews with involved experts are summarized. 5.1 Present vulnerability against weather-related flood events 5.1.1 Published articles of weather-related events from GP During the period 1991 to 2012 GP published a total of 617 articles related to weather-events that contained consequences within the region Västra Götaland. 487 articles concerned Gothenburg municipality (see keywords in Appendix A.1.1). Figure 13 shows the total annual amount of reported weather-related articles from the newspaper GP during the period 1991 to 2012 for Gothenburg municipality. The largest number of reported articles with weather-related events occurred during year 1995 (59 articles), followed by 1996 (40 articles). The year with lowest amount of reported articles is 2009 (7 articles). The annual mean is 22.7 reported articles and the median is 19 reported articles.

Figure 13. Annual amount of reported weather-related events found in the newspaper Göteborgs-Posten, during the period 1991-2012 covering the Gothenburg municipality.

All 487 reported articles from GP during the period 1991 to 2012 covering Gothenburg’s municipality were divided into 10 categories and here shown in figure 14. In each category the reported articles have mentioned the type of weather event (see Table 1) The most reported weather event in Gothenburg is wind (109 articles), followed by precipitation (105 articles), wildfire (80 articles), high temperature (74 articles) and articles containing general weather information (52 articles). The category with the smallest amount of reports is weather warnings (4 articles). The categories investigated further in this study are wind, precipitation, high water levels and weather warnings which contains articles related to flooding. The results from this study show that Gothenburg is affected by weather-related events today. According to the reported events in GP, Gothenburg is most affected by the weather-categories wind, precipitation, wildfires and high temperatures.

Figure 14. Number of weather-related articles in specified categories found in the newspaper Göteborgs-Posten during the period 1991 to 2012 (according to our GP database of weather-related events) covering Gothenburg municipality. The category others contains inversions, landslides and mist events.

5.1.2 Number of flood-related articles from GP and incident reports from MSB The categories included in this particular project is articles/reports concerning the categories wind, (included are only articles concerning winds with high water levels and/or referred to as storm events in GP), precipitation, high water levels and weather warnings related to flooding. A total of 86 articles from GP and 484 incident reports from MSB were found. Figure 15 shows the number of articles and incident reports per year during the chosen time period (1991-2012) for Gothenburg and Mölndal municipalities. The amount of articles from GP varies from year to year. The year with the highest amount of articles is year 1995 with 12 articles and the years with lowest amount of articles is 2009 with zero articles. The mean value for GP is 3.9 articles per year, while the median value is 3 articles. The number of MSB reports show an even larger variation from year to year than GP. The year with the highest amount of incident reports from MSB is year 2006 with 116 reports (this is the year river Mölndalsån flooded, which could be one reason for the large amount of reports). The year with the lowest amount is 2009 with 7 reports. The mean value for MSB is 22 reports per year, while the median value is 15 reports. The year with the largest difference between MSB and GP is year 2006 with 5 from GP and 116 reports from MSB. The year with the smallest difference is year 2002 with 11 incident reports from MSB and 4 articles from GP. Figure 15 shows that Gothenburg and Mölndal is affected by weather-related flood events according to GP and MSB and that there is a large annual variation in the number of reports.

Figure 15. Annual number of articles concerning weather-related flood events published in GP during the period 1991-2012 along with annual number of incident reports from MSB during the period 1998-2012.

5.1.3 Classification of weather-events All the 86 articles from GP and the 484 incident reports from MSB are divided into 4 sub- groups describing what kind of weather event that caused the flood. The sub-groups are; heavy rain-, flooded river-, high water level events and unknown cause (see Fig. 16). For further explanation see method section 4.1.2 and 4.2. The largest group for both GP articles and MSB reports are the sub-group heavy rain events, with 65 GP articles and 351 MSB reports. The sub-group flooded river events contains 9 GP articles and 78 MSB reports, while the sub-group high sea level events contains 11 GP articles and 29 MSB reports. The sub-group unknown cause contains 14 GP articles and 95 MSB reports (this sub-group represent reported consequences which do not specify the related weather event). Gothenburg and Mölndal is most impacted by primarily heavy rains-, but also flooded rivers- and high sea level events according to GP and MSB.

Figure 16. Number of articles from GP (1991-2012) and incident reports from MSB (1998-2012) divided into four sub-groups; heavy rain events, flooded river events, high sea level events and unknown cause for the municipalities Gothenburg and Mölndal.

5.1.3.1 Reported consequences from GP To get an idea of what kind of consequences GP have reported and what kind of consequences the two municipalities are impacted by today, two figures have been made (Fig. 17 and 18). Figure 17 shows the number of articles containing consequences from GP describing which society function is impacted by which sub-group; heavy rain-, flooded river- and high sea level events for Gothenburg and Mölndal municipalities during period 1991 to 2012.

Figure 17. Shows the number of articles from GP and consequences within the society function for each sub- group; heavy rain (dark blue), flooded river (light blue) and high sea level (purple) covering Gothenburg and Mölndal’s municipalities during the period 1991 to 2012. Heavy rain events are the most common cause for all categories of consequences except for the category boats. Consequences risen from heavy rains are the ones that the emergency service most frequently are called out to. Problems with water and sewer systems are commonly linked to these floods (14 articles). Motorists/roads have most published consequences due to heavy rain events (31 articles), the consequences are primarily due to flooded roads and railways. Concerning sport and entertainment events, the heavy rain events are the only sub- group with reported consequences for this category. Usually this involves canceled football games or flooded indoor sport centers (13 articles).

Flooded river events are most frequently reported as impacting public buildings (5 articles), motorists/roads (5 articles), private residences (4 articles) and public transportations (3 articles). The buildings often have flooded basements. Problems with the water and sewer system are not that commonly reported in connection to flooded river or high sea level events (one article each) as compared to the sub-group heavy rain (14 articles). For flooded river events, one article each have mentioned consequences for boats, tunnels/bridges and aircrafts. High sea level events have been reported most frequently as consequences for the category boats (5 articles), note that the consequences only have occurred during storms. A storm affects mainly the public ferry traffic (both traffic to the islands in the archipelago and Stena Line’s ferry traffic), but also private boats and cargo ships. Sometimes the boat’s moorings break, and the boats drift away. Articles concerning sea level events report consequences for 36

tunnels/bridges (4 articles), often due to floods and/or power loss. The category motorists/roads (3 articles) have reported consequences in form of water masses on roads, under viaducts, in tunnels or on bridges. Private residences (3 articles) and public buildings (2 articles) also have reported flood consequences, in this case often flooded basements. Water and sewer systems consequences have not been reported so frequently (1 article), while sport and entertainment events have not been reported at all in the articles related to high sea levels. Figure 18 shows the number of articles from GP divided into sub-groups (heavy rain-, flooded river- and high sea level events) and in what way the consequences appear for Gothenburg and Mölndal municipalities during the period 1991 to 2012. Note that one article may appear in several sub-groups and in several consequence-categories. Floods may create secondary consequences such as fires, power shutdown or personal injuries (see method section 4.3 for a deeper explanation).

Figure 18. Number of articles from the newspaper GP divided into sub-groups; heavy rain events (dark blue), flooded river events (light blue) and high sea level events (purple) and in what way the consequences appear for the Gothenburg and Mölndal municipalities during the period 1991 to 2012. Heavy rain events are the sub-group with most reports in all types of consequences. Among those, floods are most often reported (44 articles). The emergency service have often been summoned (31 articles), most often to bilge pump basements. Effects from floods on electricity and communication systems (6 articles) and floods causing fires (5 articles) have been reported as consequences. Personal injuries are mentioned in 4 articles (includes traffic accidents and lightning accidents in conjunction with heavy rains).

Flooded river events, GP have reported consequences from floods (8 articles) and that the emergency service have been summoned (8 articles). The emergency service’s operations involve bilge pumping basements, but also helping house- or business owners to put out sandbags for protection against water from the flooded river. Problems with electricity and communication systems (2 articles) and one article about personal injuries (one person stuck in a car due to flooding under a viaduct) have been reported. Storm damage has also been reported

simultaneously to a flood in one article concerning flooded river events. Fires have not been reported in connection to flooded river events during this time period. High sea level events, when river Göta älv has high water levels the most common consequences reported in GP are flooding (8 articles), followed by emergency services summoned (5 articles). Consequences for the electricity and communication systems have been reported (2 articles) and one article reports personal injuries. Storm damages have been reported in three articles connected to high sea levels.

5.1.3.2 Reported consequences from MSB Figure 19 provides information on consequences that have been reported by MSB and are related to flood-events. All 484 incident reports from the emergency service, are divided into sub-groups and consequence-category for Gothenburg and Mölndal municipalities during the period 1998 to 2012. Note that one incident report can appear in several sub-groups and several consequence-categories.

Figure 19. Shows the number of reports from MSB and consequences for each sub-group; heavy rain events (red), flooded river events (yellow) and high sea level events (orange) covering Gothenburg and Mölndal municipalities during the period 1998 to 2012. Heavy rain events is the most common cause for all categories of consequences except the electricity and communication category. The number of reports with consequences follow the same pattern except for the categories public transportation and electricity and communication. Heavy rain events have caused the most consequences for basements and private residences. This is often connected to problems with the water and sewer system due to poor maintenance, malfunction or underdimensioned pipes. Most often the basement is the subject for the flood. The emergency service is also called out to bilge pump roads and viaducts, which is also most sensitive to heavy rain events in general. The ratio of the number of reports with the water and sewer systems issues compared to number of reports concerning basements is 0.67, meaning that these two categories are linked to the same report in 2/3 times.

Flooded river events have the most reports in the category public buildings where the basements often are effected. The ratio of number of reports concerning the water and sewer system compared to number of reports concerning basements is 0.44 for flooded river events, which is smaller than for heavy rain events. Regarding the reports of consequences three types of public buildings could be distinguished within the data. The business community have 138 reports of flooding, schools 23 reports and hospitals have 16 reports. Personal injuries have not been reported within the MSB data. High sea level events is the sub-group which has the largest amount of reports in the category public buildings, than what it has in the category private residences. Both categories are struggling with floods in their basements. The business community is the most frequently affected group within the public buildings with 37 reports, schools have four reports while hospitals and nursing homes have three reports. Problems with the water and sewer systems is common to contribute to the floods in basements (ratio of 0.59 for number of water and sewer system compared to flooded basement reports). Electricity and communication are often endangered in conjunction with floods caused by high sea levels. During passages of low pressure systems in Gothenburg consequences may occur from all sub- groups; heavy rain, flooded river and high sea level. An extra-tropical cyclone that struck Gothenburg in December 2013 was Sven, which is described in section 5.1.4.

5.1.3.3 Vulnerability against heavy rain and cloudbursts This study shows that heavy rains are the most common cause for flooding (according to GP and MSB) in Gothenburg and Mölndal municipalities, thus also this is the weather-related event that Gothenburg is most vulnerable to. Heavy rains gave consequences for all society functions investigated in this study according to GP. Private residences, public buildings, motorists/roads, tunnel/bridges, public transportations, boats, aircrafts, sport and entertainment events and water and sewer system. Due to heavy rains the emergency service are often summoned, electricity and communication are vulnerable and sometimes side-effects such as fires are reported. Personal injuries are also reported in conjunction to heavy rains. The consequences are often connected to deficiencies in the water and sewer systems, such as backflow and under- dimensioned rainwater systems. The result from the problems with the water and sewer system may be leakage of sewer water, creating further consequences such as contamination. According to MSB all types of buildings are affected of heavy rains. Most frequently reported are flooding in basements due to deficiencies and under-dimensioned water and sewer systems. Motorists/roads, tunnels/bridges, public transportation and electricity and communication are also vulnerable to heavy rains. Private residences are often facing problems with bad maintained sewers and rainwater systems, often resulting in backflow in wells inside the houses (most often in basements). Poor drainage, clogged surface water drains (most often due to leaves and branches) frequently resulting in flooding.

5.1.3.4 Vulnerability against flooded rivers Flooded rivers are not as common as heavy rains, even though the rain is the cause for them to flood. When they occur severe and expensive damages are reported. According to GP, private residences, public buildings, motorists/roads, tunnels/bridges, public transportations, boats,

aircrafts and water and sewer systems are vulnerable. The emergency services have been summoned, electricity and communication is affected and personal injuries are reported. The reported consequences from MSB illuminates the vulnerability for many parts within the society. However, consequences for boats, air crafts and personal injuries have not been reported by MSB.

5.1.3.5 Vulnerability against high sea levels and storm surges During storms like Sven, Gothenburg are highly vulnerable to the frequently occurring high sea levels caused by low pressure and often strong winds (mainly from south to north-west). GP articles show a vulnerability for several parts of society, i.e. private residences, public buildings, motorists/roads, tunnels/bridges, public transportation, boats and water and sewer systems. The emergency service have often been summoned and personal injuries have been reported. Articles have been reporting about collapse in the district heating system and about electricity shutdowns. The public ferry service are during most storms affected, likewise bridges and tunnels. Many fallen trees within the metropolitan area disturbs the public transportation and motorists along many streets and/or roads in the region. Fallen trees have also damaged parked cars. According to MSB reports public buildings and private residences are the most vulnerable. Basements are frequently affected due to deficiencies in the water and sewer system such as backflow in wells Buildings in general close to the river Göta älv are most vulnerable, e.g. The Fishing Port (Fig. 12 and 37), Casino Cosmopol (Fig. 38), and Stena-line etc. Electricity and communication systems have been affected due to high sea levels and strong winds, likewise bridges and tunnels. In conjunction to the low pressures (storms) with high sea levels, heavy rains often occur simultaneously. Heavy rains as described in 2.4.2 is the most common cause for flooding consequences in Gothenburg and Mölndal. During storms the vulnerability is higher due to heavy rains, high sea levels and strong winds simultaneously and will therefor create a larger impact to society. Several storm damages have been reported in incident reports from MSB, but these have not been included in this study, since they are not a direct consequence connected to flooding. Often it involves fallen trees, road signs, commercial signs, scaffoldings and different types of walls and roofs sheeting breakage. Other frequently reported consequences are broken lights, windows, antennas and awnings. The most recurring is trees that have fallen down on roads, bike lanes and houses. Large Christmas trees at squares have been reported blown over repeatedly during strong winds. These consequences are just briefly mentioned here, as they have been visible in some articles and reports, thus storm damages needs its own investigation. 5.1.4 Case study – The extra-tropical cyclone Sven During this thesis work, on the 5th of December 2013 the storm Sven struck the southern and the western parts of Sweden with wind gusts of hurricane force (see Figure 1, 2, 8, 9, 12, 37 and 38). The storm increased the water levels high above normal (Fig. 21 and 22) in many places around the Swedish south and West coast. Waves were in some places over 10 m high. The 6th of December, strong northerly winds of storm strength (Fig. 21) swept across the West coast. Three water level records were observed, the highest in Öresund (by the south coast) with +167 cm above normal. In Gothenburg the sea level dropped temporarily on the 5th, to rise again 40

on the 6th due to the strong northwesterly winds (Fig. 21 and 22) with a storm force (24,5- 32m/s) which pushed the water levels up to extreme, 122 cm along the West coast and Öresund (SMHI, 2013e). At Vinga island in the Gothenburg archipelago wind gusts up to 38 m/s were observed (SMHI, 2013f). According to the newspaper Svenska Dagbladet (SvD) eight people lost their life’s due to the storm Sven (SvD, 2014). According to a news article from GP, published on the 5th and updated the 6th of December 2013, Gothenburg faced a lot of problems due to the storm. The article describes how the whole district heating-network collapsed. The districts Angered, Säve, Torslanda and Tuve were without electricity for several hours. Other parts of the city had major problems with electricity coming and going. The ferry traffic service to the islands were canceled or greatly reduced. The bridge Älvsborgsbron was closed and the public transportation net had disturbances with canceled trams and fallen trees blocking the roads/streets. In fact a lot of fallen trees blocked several roads/streets in the metropolitan area. Between 18:00 and 20:00 the 5th of December at least 60 trees had fallen down over roads/streets in the county. The trees also destroyed several parked cars and one electric line supporting trams. In western Sweden numerous traffic accidents occurred and the emergency service told people to stay indoors (GP, 2014b). The low pressure center moved east-south-east on its path across Sweden. Figure 20 describe the location at the border of the regions Östergötland/Småland at 23:00 the 5th of December. When the low pressure passed Gothenburg the center was located at a latitude between Strömstad and Oslo.

Figure 20. Pressure chart with isobars during the storm Sven that struck Sweden’s south and west coast 5th of December 2013. The image is from 23:00. The legend, to the right shows wind gusts in m/s at 10m elevation. (http://www.smhi.se/klimatdata/meteorologi/vind/2.2402#). SMHI issued warning for high wind speed (varning för kuling) class 1 for Skagerrak and Kattegatt the 5th to 6th of December 2013 and class 2 warning for high sea levels in Kattegatt the 6th and the 7th of December 2013 (SMHI Axell, 2014). Figure 21 shows sea level change during the storm Sven 5th -7th of December 2013 in comparison with mean wind speed and direction during the same period in UTC-time (local

time is UTC +1h). The highest sea levels above 100 cm are noted during the 6th of December. The wind speed peaks earlier in the 6th indicating a time lag in sea level compared to wind speed. From 14:00 at the 5th until 02:00 at the 6th the sea level experience great changes. Starting at a value of 100.8 cm (14:00), decreasing to 7.6 cm in 6 hours (20:00) and then in the next six hours (02:00) increasing to 93.4 cm. The wind for the same period of time starts southwesterly during the decrease, just before the increase the wind speed increases and changes to a more westerly to north northwesterly wind direction. On the morning of the 6th the sea level started to increase further. From 11:00 to 18:00 the sea level constantly was above 110 cm, peaking at 122.1 cm at 16:00. The wind was north-westerly turning to more northerly in the afternoon, at the same time the wind speed dissipates. The highest observed wind speed at Säve airport was recorded during the night between the 5th and the 6th with mean wind speed of 16.5 m/s and gusts up to 21.5 m/s. Figure 22 shows sea level change during the storm Sven compared to air pressure during the same period. The highest sea level was observed in the afternoon on the 6th of December and peaked at +122.1 cm compared to normal. The minimum air pressure noted during the period was during the evening (18:30) on the 5th of December with 964 hPa corresponding to the passage of the low pressure center.

Figure 21. Observed sea level compared to mean wind speed and direction during the storm Sven in Gothenburg during the period 5th to 7th of December 2013.

Figure 22. Air pressure compared to sea level during the storm Sven in Gothenburg during the period 5th to 7th of December 2013. The extra-tropical cyclone Sven is a good example of extreme weather events which regularly affects Gothenburg and its surroundings. In the past there have been several similar events e.g. Septemberorkanen 1969, the extra-tropical cyclone Gudrun 2005 and Per 2007 which have all affected Gothenburg (SMHI, 2013d). During these extremes, high sea level, large amount of precipitation and flooding is common (Ackerman & Knox, 2007).

5.1.5 Local meteorological and oceanographic parameters affecting flood-events According to SMHI (2009i) there are several weather parameters affecting floods. The ones affecting Gothenburg and Mölndal municipalities are heavy precipitation, high flows in rivers and lakes and high sea levels. To get an idea of the fluctuation during the chosen time period (1991-2012) these have been investigated. Firstly, the precipitation variation for the region is investigated and presented, followed by the sea level fluctuation in the estuary of river Göta älv and observed high sea levels above 80 and 120 cm and also described by season. Air pressure, wind speed and direction and finally precipitation are also compared to sea level changes. The variation in water flow for the river Mölndalsån is not included in this study.

5.1.5.1 Precipitation (sub-groups heavy rain- and flooded river events) The two sub-groups heavy rain events and flooded river events are dependent on how much it rains. The articles from GP in the sub-group heavy rain events are most often caused by cloudbursts. However, in the incident reports from MSB it is more difficult to define the cause for the consequences. The cloudbursts often arise from a cumulonimbus cloud or a cold front, while the sub-group flooded river events are due to continuous rain from front passages (often more than one front passage during a few days). The annual precipitation for the Gothenburg area during the period 1991-2012 is shown in Fig. 23. The smallest amount of annual precipitation was during 1996 with 715 mm, while the highest amount of annual precipitation was during 2006 with 1402 mm. The trend line in red shows a gradual increase of 13.2 mm precipitation per year during the time period. The coefficient of determination between the observed values and the trend line, R2 = 0.37 (statistically significant) which shows some support to the trend. The annual mean is 1060.4 mm precipitation. When investigating the mean precipitation per month during the period 1991 to 2012, the month with largest amount of precipitation is October (118 mm), followed by August (114 mm) and July (100 mm). April (60 mm) and March (61 mm) is the months with the lowest amount of precipitation. Overall, the amount of precipitation is quite equally distributed over the year.

Figure 23. Total amount of precipitation per year in Gothenburg during the period 1991-2012. The red line represents the trend.

5.1.5.2 Sea level (sub-group high sea level events) When investigating the GP articles and MSB reports from the sub-group high sea level events, it is important to get an idea of how the daily sea level maximum has varied during the time period 1991-2012. As mentioned before, SMHI issues warnings if the models indicate levels above 80 cm (class 1 warning) and above 120 cm (class 2 warning), these levels are used as a reference limit to high sea levels. Figure 24 shows daily sea level maximum during the period 1991 to 2012 in Torshamnen, Gothenburg. According to Fig. 13 the daily maximum sea level has been above 80 cm 88 days and above 120 cm 7 days during these 22 years (3 days 2011). The highest recorded sea level for the period is 149.2 cm during the storm Gudrun on the 8th of January 2005 (Note that data is from Torshamnen and may be much lower in this part of the estuary than further in, closer to the city). Note also that this is the number of days and not the number of events (storms/low pressures).

Figure 24. Daily sea level maximum for the period 1991-2012 observed at Torshamnen in Gothenburg. The two black lines represent levels of 80 cm above normal sea level and 120 cm above normal.

When investigating all the days with sea levels above 80 cm more closely, as in Fig. 25, the results show that levels above 80 cm occurs from 0 to 12 days a year. Levels above 120 cm occurs from 0 to 3 days per year. Year 2012 is the only year with 3 days of sea levels above 120 cm. The years with the largest amount of days with sea level above 80 cm are 2007 and 2011 with 12 days, while the minimum is noted for the years 2001 and 2010 with 0 days. The mean value for sea level above 80 cm is 3.9 days per year. Note that Fig. 25 is made of observed maximum sea level data and not from data when SMHI have issued warnings for high sea levels. The data is from Torshamnen, which is located far out in the estuary. The sea level close to the city center could therefore be of different levels. Note also that this is the number of days and not the number of events (storms/low pressures). For example 1993, January had several days in a row or close to each other with high sea levels. If it was the same event or several events in a row is not clear.

Figure 25. Days of sea level above 80 cm (light blue), and above 120 cm (dark blue) observed in Torshamnen, Gothenburg during the period 1991-2012.

To examine the seasonal variation of sea levels above 80 cm all events of sea level above 80 cm are divided between the four seasons. Figure 26 shows all days with sea level above 80 cm by season. A total of 88 days during the period 1991-2012. A maximum of 12 days per year is noted in 2007 and 2011, while the minimum is noted for years 2001 and 2010 with zero days. Winter is the season with largest number of days with sea level above 80 cm (58 days). The second largest season is autumn, with 22 days, followed by spring with 8 days. During summer there has been zero days with sea level above 80 cm during this certain period according to the oceanographic data. Note that this is number of days and not number of events (storms/low pressures). With this said, Gothenburg is most exposed during winter and the least exposed during summer for events causing high sea levels. Sea levels above 120 cm are found during the period 27 November to 22 February for 1991-2012.

Figure 26. Seasonal number of days with sea level above 80 cm for Gothenburg during the period 1991-2012.

5.1.6 Meteorological and oceanographic elements affecting sea level in Gothenburg River Göta älv and its estuary is affected by the catchment area of River Göta älv and the Kattegatt ocean. The rivers within the catchment area are affected by heavy rains, mostly consistent rain but also the smaller streams of cloudbursts. The sea levels in the ocean outside Gothenburg are being affected of several other reasons (see background section 2.4). In this section, the meteorological parameters which may affect the sea level within the estuary of River Göta älv are investigated. Starting with air pressure, followed by wind and precipitation.

5.1.6.1 Air pressure A meteorological element which may affect sea level rise in the estuary of river Göta älv is air pressure (see background section 2.4.1). To be able to find a possible relationship between sea level and air pressure, these two datasets are compared. Figure 27 shows air pressure and daily sea level maximum for Gothenburg during the period 1991-2012. The two horizontal lines represent sea level above 80 cm and sea level above 120 cm. The vertical line represent the highest air pressure (1006.2 hPa) observed for a day with sea level above 80 cm. Most of the recorded sea levels above 80 cm are connected to low pressure systems passing, note that no high sea levels (above 80 cm) have occurred at standard atmospheric pressure (1013 hPa).The correlation line slope is -1.21, i.e. an increase of 1.21 cm sea level per hPa pressure decrease. The coefficient of determination R2 is 0.45, showing that the trend is significant. The variance in sea level is larger for low air pressures than for high air pressures. The observations of sea level when pressure is low deviates the most from the correlation line. High pressures show a lower variance in sea level, and rather consistent low sea levels.

Figure 27. Observations (blue stars) of daily sea level maximum and air pressure in Gothenburg during the period 1991 to 2012. The two horizontal lines (black solid lines) represent sea levels at 80 cm and sea levels at 120 cm. The vertical line (black solid line) represents the highest air pressure (1006.2 hPa) recorded for a sea level above 80 cm. The black dashed line represents the correlation.

To be able to find certain seasonal patterns for the air pressure, the air pressure data has been divided into four seasons. Figure 17 shows seasonal distribution of daily minimum air pressure in Gothenburg during the period 1991 to 2012. Summer is the season where daily minimum air pressure shows the least dispersion while spring and autumn show more spread in the air pressure, both the minimum and maximum for the period is lower respectively larger than the summer pressure. The winter season shows the largest dispersion in the observations, and the most extreme pressures (highs and lows) have been observed during the winter (see Table 2). As can be seen in figure 28, the lowest pressure is observed during winter and is well in line with the observed higher frequency of flooding during winter than during the other seasons. Days with sea levels above 80 cm (see Fig. 26) are also observed during winter. During summer more high pressures are observed while low pressures are less common.

Table 2. Seasonal distribution of daily minimum air pressure during the period 1991-2012 for Gothenburg.

Season Max observed Min observed % within air pressure % of air pressure air pressure air pressure range 995-1030 hPa below 995 hPa Summer 1033.1 982.0 98.9 0.7 Autumn 1045.3 968.6 86.9 7.9 Winter 1048.7 959.6 72.3 14.3 Spring 1043.5 963.3 89.2 5.3

Figure 28. Seasonal distribution (fractions) of daily minimum air pressure in bins of 5 hPa for Gothenburg during the period 1991 to 2012.

5.1.6.2 Wind speed and direction The second meteorological parameter investigated as a contributor to sea level rise in the estuary of river Göta älv is wind speed and direction (see background section 2.4.2). It is of interest to study wind speed and direction in conjunction to high sea levels in Gothenburg to identify if a certain wind direction and wind speed is significant for the highest sea levels. Figure 29 shows hourly values of sea level (Torshamnen) and wind direction during the period 1991 to 2012. For sea levels above 80 cm the most common wind direction varies from southerly (180°) to westerly (270°) to Sea levels above 120 cm correspond only to hourly values of wind direction from 180°-270°.

Figure 29. Hourly values of sea level (Torshamnen) and wind direction for Gothenburg during the period 1991- 2012. The two horizontal lines (black solid lines) represent sea levels at 80 cm and sea levels at 120 cm.

Studying the certain wind speed in conjunction with sea levels above 80 cm for Gothenburg, the most frequent wind speed ranges in the interval 0-15 m/s. There are a small amount of values in the interval 15-20 m/s. For sea levels above 120 cm the only observed values lays in the interval 5-15 m/s (see Fig. 30).

Figure 30. Hourly values of sea level (Torshamnen) and wind speed for Gothenburg during the period 1991- 2012. The two horizontal lines (black solid lines) represent sea levels at 80 cm and sea levels at 120 cm.

When investigating wind speed and direction for all the days with sea levels above 80 cm and 120 cm more closely, further information is found. Figure 31 shows mean wind speed and direction for all sea levels (hourly values) above 80 cm and 120 cm in Gothenburg during the period 1991 to 2012 (see Table 3). The most common wind direction at high water levels are westerly (270°) to southerly (180°), while the wind speed ranges between 0 and 16 m/s. The average wind speed for those occasions is 8.5 m/s (median is 8.3 m/s) while the mean wind direction is 246° (median is 250°) which is about west-north-west. The highest observed wind speed is 16.2 m/s for sea levels above 80 cm. Sea levels above 120 cm have only been observed corresponding hourly values of wind direction from 180°-270° (South to West). The average mean wind speed is 9.1 m/s (median is 8.9 m/s), the minimum observed mean wind speed is 5.6 m/s while the maximum mean wind speed is 13.9 m/s. Thus, no observations of sea levels above 120 cm have been made when the mean wind speed is lower than 5.6 m/s. There are 27 observations (hourly) of sea levels above 120 cm for the period 1991-2012.

Figure 31. Hourly mean wind speed and direction for sea level above 80 cm and 120 cm in Gothenburg during the period 1991-2012.

Table 3. Number of hourly values of sea level above 80 cm in respectively wind speed interval for Gothenburg during the period 1991-2012

Interval of wind speed Number of hourly values [m/s] with sea level above 80 cm 0 3 0-4 31 4-8 279 8-12 317 >12 85

5.1.6.3 Precipitation Also the potential contribution of precipitation to high sea levels in the estuary of river Göta älv was investigated. Figure 32 shows the correlation between daily sea level maximum and daily precipitation during the period 1991 to 2012 in Gothenburg. The largest distribution of precipitation events is between 0 and 60 cm sea level (which are the most common sea levels) with a spreading of precipitation between 0 mm and 65 mm. High sea levels above 100 cm always correspond with precipitation for this investigated period. The highest amount of precipitation lies in the most common interval of sea level (0-60 cm). The lowest sea levels are usually observed absent of or with low amounts of precipitation. As expected, the air pressure (see Fig. 27) is the main reason for high sea levels in Gothenburg and not the amount of precipitation, based on the very low/no correlation (see Fig. 32). When investigating elements affecting sea level in Gothenburg, step-wise regression could be one alternative to determine the ranking of elements. The river flow, which depends on precipitation and releases from Vänern in a complex system, may have impacts on the sea level but this needs more in-depth investigations and have not been investigated here.

Figure 32. Scatter plot (blue stars) of sea level maximum compared to grid-data precipitation in Gothenburg during the period 1991-2012. The horizontal lines (black solid) represents sea levels of 80 cm and 120 cm respectively.

5.1.7 Comparison of GP articles, MSB reports, meteorological- and oceanographic data To be able to investigate Gothenburg’s and Mölndal’s vulnerability against weather-related flood events a survey of climatic features which affect flood events are necessary. This is done by applying the defined sub-groups in Fig. 16, which show what kind of event that caused the flooding (heavy rain-, flooded river-, high sea level events and unknown cause). River Mölndalsån flooded the year 2006 when the annual precipitation were 1402 mm, the highest annual amount for the period 1991-2012. The following years the river was dredged. The year 2006 was also the year with the most articles/reports, partly because of the exceptional flooding. This indicates a vulnerability to increasing annual amounts of precipitation. The highest vulnerability to heavy rains are found for days with ≥ 50 mm, where the few events that have occurred have had very large consequences. Days with precipitation in the interval 35 to ≥ 50 mm, have also shown a high number of reported consequences, but the number of days are higher. Gothenburg is also vulnerable to the precipitation interval 0 to 5 mm, consequences appearing in this interval are likely due to cloudbursts not captured in the grid-data, which the community also is vulnerable to. Gothenburg is vulnerable against sea levels above 80 cm, the level where most consequences starts to be reported. When comparing daily maximum sea level with the number of articles from GP and incident reports from MSB (for the sub-groups high sea level) consequences starts to appear at 40 cm above average sea level and the amount of reports from MSB are increasing along with increasing sea level. A conclusion will be that Gothenburg is vulnerable to especially these sea levels above 80 cm shown in figure 25 and even more vulnerable to sea levels above 120 cm, which have occurred 88 days and 7 days respectively during this time period. Gothenburg is most vulnerable against high sea levels during winter, were most events have occurred and most consequences have been reported. In conjunction to high sea levels Gothenburg is most vulnerable to southerly to westerly winds, which are the most common wind direction for sea levels above 80 and 120 cm. No observations of sea levels above 120 cm have been made when the mean wind speed is lower than 5.6 m/s, which may indicate a certain vulnerability for low pressures with wind speed above 5.6 m/s. If comparing the other way around, dates with high sea levels in Gothenburg with articles from GP and incident reports from MSB, several days with high sea levels have not had any articles or incident reports. There could be several reasons for this, further explained in the discussion section. The most affecting parameter for high sea levels within the estuary is air pressure. The highest observed air pressure for days with sea levels above 80 cm is 1006.2 hPa (Fig.27), which indicate a larger vulnerability when the passing low pressure have less pressure than 1006.2 hPa. Gothenburg is most vulnerable and exposed to low pressures during winter. Rain does not affect the sea levels within the estuary of river Göta älv. SMHI’s warning levels at 80 and 120 cm are good thresholds for the city today, because consequences are rarely reported under 80 cm, however, sea levels above 80 are the most dangerous.

5.1.7.1 Cross-match of reported dates of GP articles and MSB reports In figure 33 a comparison is shown between the dates when consequences were reported from GP articles and dates of issued MSB incident reports. There are three alternatives, either a date with only a GP article or only a date with MSB report or they are issued at the same date. The period ranges from 1998 to 2012 when both datasets are complete. From the database the dates with only GP articles, however, often are followed by MSB reports the next day (5 of 22 dates), but the GP articles are only rarely preceded by MSB reports the day before (1 of 22 dates). The reported cause of the GP articles of single dates, are cloudbursts (7 cases), storm (9 cases) and flooded river (6 cases). In about half of the GP articles concerning storms the emergency service were mentioned in the article. The emergency service was also mentioned in 2 of the 7 cloudburst and in 1 of the 7 flooded river articles.

Figure 33. Ratio compared to total number of dates with articles/reports. Ratio of GP articles and MSB reports coinciding (purple), ratio of GP dates (blue) respectively MSB dates (red) when reported independently. For the Gothenburg and Mölndal municipalities, during the period 1998-2012. The results showed in figure 33, GP and MSB show large differences. MSB is reporting more frequently than GP, which results in a broader picture of the vulnerability than by using only GP as a source. GP articles only covers 25% of the dates with reported consequences from either source. The coverage of MSB is 88% of the dates with reported consequences. The large number of MSB reports are due to the higher coverage of events with minor consequences, such as single basement flooding. The magnitude and severeness can often be reflected by the number of reports that day. The number of reports will give estimations of the workload for the emergency service. Newspapers do not report all events, and especially small single events and consequences are omitted. GP on the other hand reports for example about disturbances within the public transportation and canceled sports and entertainment events which the emergency service have not been called out to (at least not within this dataset of incident reports). GP may also show vulnerable sectors within society which the emergency service have not been involved in (consequences may be dealt with, without the emergency service, such as disruptions in the public transportation). This shows the importance of having several sources when investigating the vulnerability of a certain locality. This also shows that putting one additional source next to GP when investigating the vulnerability of weather-related flood events is an accurate choice. Using only newspapers as a source may result in a misleading interpretation of an LCLIP. Using several sources enhance the validity of the used method. 55

5.1.7.2 Comparison between GP articles, MSB reports and precipitation data To investigate if there is a relationship between published articles from GP, incident reports from MSB and precipitation a Fischer’s exact test is done (see method section 4.3). The results in table 4 show that there is a relationship between incident reports from MSB, articles from GP for the sub-group heavy rain events to precipitation. Values close to zero represent a relationship, while values close to one represent no relationship.

Table 4. Shows the division between number of articles from GP (A) and incident reports from MSB (B) (for the sub-group heavy rain events) to precipitation of more than 1 mm and less than 1 mm. Four combinations are possible for each category.

A No articles GP Articles GP Fischer’s p- [days] [days] value

Precipitation > 1 mm 2275 35 1.5 × 10-11 = 0 Precipitation < 1 mm 3167 2 B No reports MSB Reports MSB Fischer’s p- [days] [days] value Precipitation > 1 mm 2238 72 5.7 × 10-21 = 0 Precipitation < 1 mm 3163 6

The results in table 5 show a relationship between incident reports from MSB, articles from GP for the sub-group flooded river events to precipitation. On occasions with reported flood events a correlations is found between amount of precipitation and the amount of reported flood events.

Table 5. Shows the division between number of articles from GP (A) and number of incident reports from MSB (B), (for the sub-group flooded river events) and precipitation of more than 1 mm and less than 1 mm. Four combinations are possible for each category.

A No articles GP Articles GP Fischer’s p- [days] [days] value Precipitation > 1 mm 2303 7 1.5 × 10-11 = 0 Precipitation < 1 mm 3168 1

B No reports MSB Reports MSB Fischer’s p- [days] [days] value Precipitation > 1 mm 2298 12 5.7 × 10-21 = 0 Precipitation < 1 mm 3167 2

Figure 34A shows the correlation between annual number of articles from GP and reports from MSB together with annual precipitation in Gothenburg during the period 1998 to 2012. Only the sub-groups heavy rain events and flooded river events are presented (R2 = 0.17). There is not a correlation between GP articles, the sub-groups flooded river events and heavy rain events, and the annual amount of precipitation. Also for the sub-group flooded river events there is no pronounced trend (slope 0.003, R2 = 0.38). For the reported events in MSB sub-group heavy rain show a small positive correlation with precipitation. The correlation for MSB sub-group flooded river and precipitation is also positive but low, a 100 mm increase in precipitation per year would result in an increase of 3.2 articles per year. The R2 value is 0.35. To summarize the results for figure 34A, the MSB reports show a significant trend where the correlation is about the same for heavy rain and flooded river. The GP articles show a small trend where the flooded river shows a stronger correlation than the heavy rain sub-group. Figure 34B shows how the number of articles from GP and reports from MSB correlate to the precipitation during the last two days of precipitation. The articles and reports are from the sub- group heavy rain events during the period 1998 to 2012. The dates selected contained at least one article or report, but both articles and reports do not necessarily contain a non-zero value each date. There is no trend or correlation between GP articles and the total amount of precipitation during the last two days (R2 value is 0.005). For the incident reports from MSB the correlation is greater (R2 = 0.15). Figure 34C shows the correlation for number of articles/reports from GP and MSB to the total amount of precipitation during the last three days of precipitation. The articles/reports are from the sub-group flooded river events during the period 1998 to 2012 for the Gothenburg and Mölndal municipalities. Due to the small amount of articles/reports in the sub-group flooded river events the zero-values are ignored (when no articles were reported on a day with incident reports or vice versa).There is relatively high correlation (R2 = 0.44) between articles from GP and the total amount of precipitation during the last three days. The correlation between reports from MSB and the total amount of precipitation during the last three days is also relatively high (R2 = 0.42). Figure 34D shows the number of articles from GP and articles from MSB compared to precipitation during the last five days, for the municipalities Gothenburg and Mölndal during the period 1998 to 2012. There is no correlation (R2 = 0.1) between articles from GP and precipitation during the last five days. There is, however, a strong correlation (R2 = 0.58) between the number of reports from MSB and the precipitation during the last five days. The trend slope is 0.34.

A B

C D

Figure 34A. Annual number of articles from GP (during the period 1991-2012) and reports from MSB (during the period 1998-2012) for the sub-groups heavy rain events and flooded river events compared to each year’s annual precipitation for the municipalities Gothenburg and Mölndal. Figure 34B. Number of articles from GP during the period 1991 to 2012 and reports from MSB during the period 1998-2012 for the sub-group rain events compared to precipitation during the last two days for the municipalities Gothenburg and Mölndal. Figure 34C. Number of articles from GP during the period 1991-2012 and reports from MSB during the period 1998-2012 for the sub-group flooded river events compared to precipitation during the last three days the municipalities Gothenburg and Mölndal. Figure 34D. Number of articles from GP during the period 1991-2012 and reports from MSB during the period 1998-2012 for the sub-group flooded river events compared to precipitation during the last five days, for the municipalities Gothenburg and Mölndal.

Figure 35 shows the investigation of which precipitation intervals that caused consequences for the two municipalities, the amount of articles/reports were compared to their respective daily precipitation. All articles/reports are from the sub-group heavy rain. The number of reported consequences increase with the amount of precipitation. The interval ≥ 50 mm (orange circle) has had large reported consequences for the two municipalities during the 6 days the precipitation has been that high. The large amount of MSB reports during these days show that Gothenburg and Mölndal is most affected by precipitation in the interval ≥ 50 mm. The largest number of GP articles and number of days with articles/reports are found in the 15-25 mm interval, thus this is the interval causing consequences most often. The largest increase of reported consequences is found between the two intervals 35-50 mm to ≥ 50 mm, the higher precipitation interval has about the same number of reported consequences in just ¼ of the days with events. The three intervals in 15-50 mm (blue circle) have many consequences reported, however the number of days with precipitation are far more than in the interval ≥ 50 mm. Within the blue circle the amount of reported consequences increase gradually with amount of precipitation. The precipitation interval 0-5 mm and 5-15 mm (green circle) has the smallest amount of reported consequences. Even though the precipitation intervals 0-5 mm and 5-10 mm have low amount of precipitation, consequences were still reported. Reported consequences even occurred at 0 mm precipitation in the grid-data. Most of the reported events occurred during the summer months (June-August), most likely due to heavy rains originating from cumulonimbus clouds, a local phenomenon which is not visible within the grid-data.

Figure 35. Number of articles from GP (blue bar) and incident reports from MSB (red bar) for the sub-group heavy rain events and number of days with precipitation in each interval compared to daily precipitation from grid-data divided into intervals during 1998-2012. The relationships between the intervals in the green, blue and yellow circles are discussed in the text.

5.1.7.3 Comparison between GP articles, MSB reports and sea level data Firstly, the relationship between published articles/reports and sea level needs to be determined. This is done by Fischer’s exact test (see method section 4.3). When calculating the relationship between incident reports from MSB, articles from GP for the sub-group high sea level events to sea level above and below 80 cm, a relationship is found (Table 6).

Table 6. Shows the division between number of articles from GP (A) and number of incident reports from MSB (B) (for the sub-group high sea level events) to sea level above and below 80 cm. Four combinations are possible for each category.

A No articles GP Articles GP Fischer’s p- [days] [days] value Sea level > 80 cm 60 5 1.2 × 10-9 = 0 Sea level < 80 cm 5413 1

B No reports MSB Reports MSB Fischer’s p- [days] [days] value Sea level > 80 cm 58 7 1.9 × 10-13 = 0 Sea level < 80 cm 5413 1

Figure 36 shows the number of articles from GP and the number of incident reports from MSB for the sub-group high sea level compared to daily maximum sea level during the period 1998 to 2012 in Gothenburg. There is no correlation between articles from GP and high sea levels (R2 is 0.02). Between reports from MSB and high sea levels the correlation is larger (R2 = 0.36). SMHI issues warnings for high sea levels when the sea levels are expected to be above 80 cm (class 1 warning) and above 120 cm (class 2 warning). Figure 36 shows how consequences have been reported at lower levels than 80 cm by both GP and MSB.

Figure 36. Number of articles from GP during the period 1991-2012 (blue diamonds) and reports from MSB during the period 1998-2012 (red stars) for the sub-group high sea level compared with daily maximum sea level for the same day in Gothenburg. Correlation lines of GP articles (solid blue line) and MSB reports (red solid line) compared to sea level. There have been four articles from GP when daily maximum sea level has been below 80 cm. Two (same event) at just above 40 cm, one just below 60 cm and one just below 80 cm. Three articles have reported consequences for daily maximum sea level right above 80 cm, originating

from two days with high sea levels. Three GP articles have reported consequences above 120 cm. According to MSB’s incident reports, one report is from when the sea level has been just above 40 cm and four reports concerning two events close to, but above 80 cm. A total of 11 GP articles concerning 8 events and a total of 29 MSB incident reports concerning eleven events. For three events above 120 cm consequences have been reported from MSB with a total of 19 incident reports. The three articles from GP concerning water levels below 80 cm are three storm events where consequences have been reported. The first, 1997-02-11, referred to as a storm with high water levels of 96 cm above normal. Most consequences were storm damages such as fallen trees and storm-felled power lines at the bridge Älvsborgsbron. The second one, 1998-10-23, referred to as a storm with flooding, with water levels of 0.5 m above normal. Consequences such as storm damages, floods and canceled ferries were reported. Last, 2011-12-11, referred to as heavy winds and high sea level. Reported consequences were flooding, and two women’s injured (their cars were stuck in water masses). To summarize the results in section 5.1.7, it is of importance to analyze several sources when investigating cities’ vulnerability and weather related impacts. Numerous sources may not just bring more information, they may also support each other and bring more accuracy to the investigation. The total annual amount of consequences will escalate with increased annual precipitation. The precipitation amount during the last few days is important for the magnitude of consequences. If the precipitation falls within a short time interval the consequences will be greater. Thus, very small amounts also rises consequences which indicate the lack of visual local cloudbursts within the grid-data. Consequences also increases with higher sea levels. 5.1.8 Interviews This section will provide a summary for each interview held with the involved authorities regarding vulnerability against weather-related flood events in Gothenburg and Mölndal municipalities. All interview-questions are found in Appendix B.

5.1.8.1 Interview with the City Planning Department of Gothenburg The infrastructure is today protected against high sea levels and storms. This is done by safety margins. For normal constructions a safety margin of 1 m is set relative to the extreme high tide. If the construction is classified as a vital public function the safety margin is 2 m. For existing tunnels the Transport Department have a safety margin at 0.7 m. The future tunnel Västlänken has a planned safety margin at 2.2 m. Regarding heavy- and persistent rain there are no formal policies yet, but informally the city should withstand a CDS-rain (Chicago Design Storm) with a return period of 100 years. For such events, a level of 0.1 m of surface water (rain) is considered acceptable on public places and up against building facades. The reference values will be formally written in the thematic extension Blue ÖP (Översiktsplan). The City Planning Department’s think the SMHI warning system is becoming more and more accurate, but are especially aware of the challenges with predicting heavy rains. The sea level predictions have higher accuracy, though they see a great potential for improvements in the warning systems. The City Planning Department’s opinion about vulnerability against weather-related flood events can be summed up in one sentence: “Today the biggest challenge for Gothenburg is the heavy rains and in the future the biggest challenge will be the rising sea”. 61

5.1.8.2 Interview with the emergency service in Gothenburg “The municipality is responsible for the planning and adaptation in Gothenburg regarding weather-related flood events, we are mainly dealing with the consequences of floods. However, flooding is a cross-border problem demanding cooperation from several authorities”. MSB use the emergency service incident reports in their datasets. The emergency service has an internal reporting system which they use to make statistical analyses. However, the emergency service is not working strategically with flooding events. Flooding of basements is considered the owners responsibility, but we will provide help if necessary and there are resources available. More important for us is the vital public functions within the society. Mapping of vulnerable areas are interesting to us, for efficient work when flooding occur. “We do not have the resources to deal with adaptation plans, we focus on the consequences”. About the future, “the city is working hard with the three strategies (attack, defend and retreat)”. The emergency service thinks that it is hard to say what Gothenburg needs to work with. Probably, physical measures and strategic work. “One of the greatest challenges for Gothenburg is the cooperation between authorities, everybody need to find their role and know their responsibilities”. “The water does not care who the landowner is, therefore the efforts need to be coordinated”. The emergency service says that, “SMHI is a valuable source for us, we are using the warning system. SMHI is sending us direct alerts about class 2 and 3 warnings. We also follow the forecasts on the internet. Today SMHI’s warning system does not correspond to our needs”. The emergency service however finds the warning system too inaccurate and with insufficient geographical resolution. “There is a need for more detailed information, since local phenomenon can cause severe consequences and emergencies. An example is high flows in the river Mölndalsån, which are not processed by SMHI since the watercourse is considered too small. Thus, we have to rely on our own experience and knowledge when floods occur, says the emergency service. To predict cloudbursts the technology or the knowledge is not existing today, it is a surprise every time”. If a storm is approaching Gothenburg, special planning is required together with the municipality. “We still have the standard emergencies to take care of, in addition to the consequences of the storm”. The City Planning Department have an emergency coordination group that convene if the situation is expected to become severe. “We support the municipalities, the police and the Transport Department in situations like that. Our vigilance is raised, but we rarely call in extra staff, since there is a limited amount of vehicles available. Thus, more staff would not mean a more efficient emergency service. Sometimes denser shifts are required”. The emergency service do not consider they need more gear and vehicles for these kind of situations.

5.1.8.3 Interview with SKANSKA The construction company SKANSKA do not actively work with flooding. If they do, it is in conjunction with city planning together with authorities and when creating new neighborhoods. SKANSKA think that the primary responsibility of climate adaptation should be placed on the authorities, they should set the thresholds. According to SKANSKA there is a poor interest of

these kind of questions (climate adaptation, resilience etc.) both from tenants and buyers. However, SKANSKA is putting a lot of effort into developing energy efficient houses. There is no demand for e.g. green roofs, but when offered most customers think it is nice. SKANSKA try to minimize hard surfaces, but often find difficulties when they do not own land around the property. They think flooding is an important question that they need to consider and be a part of, perhaps even more in the future.

6. Discussion 6.1 Present vulnerability This study has found that Gothenburg and Mölndal are presently impacted by weather-related flood events caused by heavy rains, flooded rivers and high sea levels. Consequences caused by floods have been found for several society functions e.g. buildings, roads, tunnels, bridges, public transportation, airports and personal injuries have been reported in some cases. There have also been several reports of floods where the cause have been due to deficiencies in the water and sewer systems. The emergency services have been summoned in several reports due to floods. Therefore, to limit the consequences and the costs for society it is important for Gothenburg and Mölndal municipalities to put resources into adapting measures. Today heavy rains and cloudbursts are the largest risks and the cause of most flood consequences for the two municipalities.

Heavy rains and cloudbursts have proved to be the event causing most reported consequences and emergency call-outs. One reason may be that for example The Fishing Port and other sea side areas is accustomed to flooding caused by high sea levels, because it happens several times a year. To some degree the sea side companies have adapted, due to the repeated consequences (see Fig. 37). Cloudbursts, on the other hand, are local (SMHI, 2009g), and the same area is not exposed regularly. It is harder to be prepared and to adapt if you have never experienced it before. Another reason is the insufficient warning system for the category cloudbursts (SMHI, 2009g, 2014e), which, as already mentioned are hard to predict. This may be some of the reasons for the high vulnerability against cloudbursts found in this study. The increased precipitation in Northern Europe since 1950 (up to +70mm/decade) (Haylock et al., 2008) may be an additional contribution to the reported vulnerability against cloudbursts. The results in this study are showing an increase in precipitation during the chosen time period (1991-2012) compared to the reference period 1961-1990. Storms can generate devastating consequences for society (SOU, 2007) once they occur. Storms usually bring more severe and wide consequences compared to cloudbursts. But cloudbursts occur more frequently, abruptly and requires resources on a day to day basis in the studied area. Therefore, the vulnerability is larger to cloudbursts today. It is also important to remember the difficulties of measuring Figure 37. Flooded part of The Fishing Port during the extra- tropical cyclone Sven that struck Gothenburg in December 2013. precipitation (SMHI, 2012b). Photo: Susanna Gelin

6.1.1 Causes of high sea levels Today Gothenburg is vulnerable against storm surges, since consequences have been reported, though not as frequently as consequences by cloudbursts. Storm surges cause more consequences when the wind direction is westerly, since the westerly wind push sea water against the coast and into the estuary of river Göta älv. Regarding which meteorological and oceanographic elements that affect the sea level in Gothenburg the most, the results from this study show that air pressure is the main element affecting the sea level. Wind speed and direction have also been shown to strongly affect the sea level. On the subject of air pressure and its connection to sea level (section 5.1.6.1) there is a correlation of a sea level rise of 1.21 cm for a decrease of 1 hPa in air pressure (-1.21 cm/hPa). Physically, the sea level should rise by 1 cm for each 1 hPa decrease (considering only direct forcing from atmosphere to sea) (Holden, 2008). The value found in this study is of the same order as the theoretical value, but slightly larger (20%). The stronger increase in sea level from observations is connected to low pressure phenomenon such as strong winds, internal waves of the ocean, and the local bathymetry (Ackerman & Knox, 2007). To distinguish the forcing from each of these affecting parameters is out of range for this study, however this could be an interesting topic to investigate further. During extreme winds there can be a tilt of the water surface across the estuary, called wind stowage. The resulting tilt can be up to 0.2-0.3 m between the north and the south shore of the estuary (Persson et al., 2011). During extreme events with rapid wind increase, these values could increase with an additional 50 to 75% for a short time. The sea level data in this thesis is retrieved from Torshamnen, located in the outer part of the estuary of river Göta älv, and the values is therefore not representative for the whole estuary. Especially not for the central parts of Gothenburg located farther in. The sea levels closer to the central parts may differ at least a few decimeters from Torshamnen's sea level due to the wind stowage and other local phenomena. However, the dataset from Torshamnen is the most complete dataset for the area. 6.1.2 Assumptions and limitations of the method used in this thesis 6.1.2.1 Assessment of vulnerability from GP articles and MSB incident reports This study have used GP articles, MSB incident reports, meteorological, oceanographic data and interviews to investigate Gothenburg and Mölndal’s present and future vulnerability against weather-related flood events. Two sources of information have provided a large dataset of consequences, and shows the importance of having several sources when investigating the vulnerability of a certain locality. MSB reports even the smallest consequences, and GP reports depending on space and global news situation but reports very thoroughly. The magnitude of an event can be determined from MSB reports, since they provide direct information of measures taken by the emergency service. This also shows that putting one additional source next to news articles when investigating the vulnerability of weather-related flood events is an accurate choice. Using only newspapers or incident reports as a source may result in a misleading interpretation of an LCLIP. Using several sources enhance the validity of the used method, which is also suggested by Kotecha et al. (2008). The amount of articles from GP are varying from year to year. There are several probable reasons for the variation. Except the obvious that weather situations are unique for each year,

an explanation for the varying numbers of weather-related articles could be the reporting of global news. If there is a low activity of major news stories, the newspapers tend to write more about local news such as e.g. heavy rains and minor flooding’s. The selected keywords allow the possibility for some articles to be neglected in the search at Mediearkivet. The years with the smallest amount of articles are 2001, 2009 and 2010 (see Fig. 13). Some of the top news stories 2009 was among others the economic crisis in the U.S. and Iceland, the health care reform (U.S). During 2010 one of the top news was the earthquake in Haiti and Wiki Leaks. 2001 had the terrorist attack against World Trade Center. The large amount in reports year 1995 were due to a large amount of articles about the severe snowstorm. The articles are divided into different categories, the largest categories are wind and precipitation, and this is probably due to the location of the West coast within the global circulation. Gothenburg is placed within the westerly wind belt and the weather is therefore characterized by front passages and extra tropical cyclones which bring windy and wet weather (Bernes & Holmgren, 2007). At our latitudes this weather is common and will probably be reflected as the most common weather situation causing consequences for the society as well. When journalists are referring to different types of weather events such as cloudbursts or heat waves the categorization does not follow the meteorologically correct thresholds made by SMHI, and meteorological observations especially of precipitation have been deficient. One cannot be sure that it was a meteorological storm when the newspaper reported it, but one can be sure that it was very windy and that the event had impacts worth reporting for GP. Uncertainty may also be due to measurement sites being moved in Gothenburg and that the wind-dataset therefore is not fully consistent for the period. The difference in amount of GP articles and MSB incident reports are probably because GP reports once or twice about a weather event, while MSB on the other hand writes one incident report per emergency (Nyqvist, 2014). MSB and GP also differ on what kind of flood events they report (see Fig. 15). It can be several call-outs per weather event. Misleading is however that only one incident report is written for each address, but it does not tell if more than one emergency vehicle have been used. The magnitude of each call-out is therefore hard to estimate. Thus, the magnitude of a weather event are easier to estimate with the support of MSB reports along with GP articles. GP alone, will not give a clear picture of the efforts that have been made and how often consequences actually have occurred. The considerable differences between GP and MSB reports complement each other well, in the effort of making an LCLIP as suggested by Kotecha et al. (2008). GP often report consequences from several involved sectors of society, such as impacts on the public transportation services such as disturbances in the ferry traffic, tram-lines, delayed trains and traffic jams. GP also reports of canceled sport and entertainment events or flooded basements in private or public buildings. GP reports give a more general picture of the disturbances within the society and works as a comprehensive overview of the consequences. It seems like the emergency service is not called out on disturbances in the public transportation to a large extent (see more about consequences in section 5.1.3.1 and 5.1.3.2). The MSB reports only, will not reflect all impacts on society. The peak in MSB reports during 2006 is due to the flooding of river Mölndalsån. This is also the year with the largest amount of precipitation (1402 mm precipitation). An assumption based on this would be, that a high annual amount of precipitation result in a high risk of large

consequences from floods. Since the annual precipitation is projected to increase, the future risk of flooding is likely to increase. The differences in number of reports per year could have several reasons except for the weather situation. If the emergency service has been occupied with for example a severe traffic accident or a large fire, the resources may be re-located. A flooded basement may not be priority at that time. As already mentioned, one reason for GP would be the global news situation. In general, concerning reported consequences from MSB, there is a lack of information in many of the incident reports, especially regarding the cause of the event. The experience from reading some of the reports is that they are not intended to ever be read again, since they are carelessly filled out. An improvement of how the incident reports are designed would be very useful to this type of study. Another reason for poor reports could be that the person writing them does not know that they can be used for research and statistics. Information and education would therefore be of importance and will raise the value of the massive dataset. All information that actually exists within the archives of incident reports could be invaluable for vulnerability analysis. Improvements could for instance be other/more types of categorizations, so the incidents ends up within the right category. The emergency service is not as good as GP in declaring what actually caused the flood event. Nearly always they write what they did on scene, for example bilge pump a basement, but often they do not write why the basement was filled with water. GP on the other hand is much better on declaring why a certain event appeared, this is of course due to the readers, who demands more information. No traffic accidents have been reported in the categories concerning floods from MSB. The reason for this is that only reports regarding water damage, other types of water damage, storm damage and flooding of rivers were included in the dataset provided from MSB. Car accidents (e.g. hydroplaning) caused by for example a cloudburst are probably referred to as traffic accidents and are therefore not included in this dataset. For this reason the consequence category motorists/roads is much smaller for the MSB reports than the GP articles. This may be the case for several incident reports, the cause may not be visible. There has been few reported personal injuries due to weather-related flood events, this may also be due to category errors within the incident reports. Leakage of hazardous substances into drinking water supplies can be a result of flooding occurring in areas with contaminated soils (Andersson-Sköld et al., 2008), articles concerning this have not been reported in either GP or MSB. This leakage category may also end up within another categorization of incident reports at MSB and is therefore not visible within this dataset. On the other hand, it was found that GP reported about sewer water leaking into river Göta älv a couple of times. Pathogens in drinking water supplies as a result of flooding and higher temperatures (Lindgren et al., 2008) have not been reported in GP or MSB during this time period, but has been heard of in other parts of the country (e.g. Östersund). Concerning Gothenburg and Mölndal, work have already begun to avoid this kind of consequences. Hopefully, these two municipalities will be prepared when and if this threat appears. Incident reports from MSB do not report as much as GP about consequences for the public transportation. One reason could be that Gothenburg’s tram service most of the time resolves the disorder themselves.

When comparing the dates for reported articles and incident reports from MSB, it is not expected to find GP articles without any incident reports, especially when the emergency service has been mentioned in the GP article, however, some were found. The most likely explanation is that the reports from the emergency service have been included in other categories. When comparing dates of observed high sea levels in Gothenburg, with articles and reports from GP and MSB, several dates with observed high sea levels have not had any articles or incident reports. There could be several reasons for this. The articles from GP was not found due to the selected keywords or no emergency service were called out to some regularly flooded areas where their presence would not make any difference. By including interviews to an LCLIP knowledge of how authorities work and how they discuss vulnerability is achieved. According to several of the interviews, argument that many agree upon, is that one of the greatest challenges for Gothenburg in the work with climate adaptation is the cooperation between authorities. A description of the problem would be that the authorities have different experience and functions. The emergency service is handling the consequences, and have the greatest knowledge about them and the vulnerability since they work with it regularly. The adaptation policies are determined by the municipality. The building companies are actually making the adaptation adjustments when they build according to set adaptation policies. Adaptation is a complex process, to achieve a resilient city even closer cooperation is needed along with even clearer guidelines and making use of other professions.

6.1.2.2 Assessment of vulnerability regarding meteorological and oceanographic data It is important to investigate the meteorological and oceanographic data in comparison to identified flood-related weather events (Kotecha et al., 2008; UKCIP, 2009), to find thresholds within the data when consequences have appeared. When consequences have occurred from a weather-related flood event, the investigation could be used to find out if the data is representable for the area being investigated. If consequences from a rain-event is identified, but there is no visible rain in the data, one can conclude that the weather event is not resolved in the data. It could therefore, also be determined if the weather-station’s location is optimal for the measurements. This shows that meteorological and oceanographic thresholds are best determined using incident reports from MSB. The extent of consequences are shown by the number of incident reports from the emergency service. Thus, thresholds related to the magnitude of the event can be distinguished. The number of GP articles from each event are very few (almost exclusively 1-2), and the number of articles cannot be used as a measure of the magnitude of the event. When using news articles to investigate vulnerability the articles should be categorized in a scale of severeness, ranging from 1-3 as a suggestion, to improve the quality of the LCLIP. The sparse information in the incident reports is the reason for the sub-group unknown cause to be as large as it is. The sub-group unknown cause is not included in the results of consequences published in articles from GP due to lack of information about the weather cause, hence some of the consequences are missing. If a cloudburst or a flooded river caused a flooded basement, it would be of interest for studies like this that the incident report was filled out more detailed.

6.2 Future vulnerability At present Gothenburg and Mölndal is vulnerable to heavy rains and high sea levels. Future increased precipitation amounts, heavy rains and sea level rise will result in a higher vulnerability for the city without adaptation measures. Mölndal and Gothenburg municipalities may also face a higher flood risk of river Mölndalsån in the future due to increased precipitation and annual runoff. 6.2.1 Future vulnerability related to changes in precipitation The annual mean precipitation is projected to increase by 10-30% until year 2100 compared with the reference period 1961-1990 (Persson et al., 2011). The uncertainties in the models and from the emission scenarios may lead to an even higher increase in precipitation, or the increase is not as strong as expected. Regarding heavy rains, the region is already facing an increased precipitation compared to the reference period 1961-1990 (Fig. 23). During the period 1991- 2012 the mean annual precipitation was 1060 mm. Assuming an increase of 30% to the reference period 1961-1990 with 900 mm annual precipitation, this will result in a future annual mean at about 1200 mm. The most reported consequences in a year was 2006, when the annual precipitation was 1402 mm. Present extreme events of annual precipitation, is likely to be closer to the mean in the future. Future extreme events are likely to be higher than today assuming the same variance. With future increased annual mean precipitation and annual extreme events the number of consequences is likely to increase unless society adapts. The number of days of heavy precipitation (>25 mm) will increase in most of the country during winter, autumn and spring, with as much as 8 days per year (about twice as many as today) (Persson et al., 2007). There will be a significant increase in the most intensive rains (IPCC, 2013b; Persson et al., 2011). Intensive rains cause the highest impacts today. When the number of days with heavy rains increase, the probability of what today is considered an extreme heavy rain also will increase. Increased precipitation for Gothenburg may trigger more frequent and severe flood events. The increased number of flood events will put more pressure on the water and sewer system, private and public buildings, motorists/roads and the public transportation, since those parts of society are most affected today according to the GP articles and the MSB reports. If new houses still are being built with rainwater systems dimensioned for the climate period 1961-1990, more houses may suffer consequences when the precipitation increases. One of the reasons for the existing vulnerability against heavy rains could be due to the current warning system that SMHI provides, as the technology and resolution cannot forecast cloudbursts driven by convective clouds such as cumulonimbus, that primarily occur in summertime (SMHI, 2009g). They will cause small streams and ditches to fill up fast and the culverts and rainwater systems are not able to drain the water which may result in flooded roads, railroads, tunnels and bridges that may become impassable and dangerous to travel on. Basements will be flooded and unpurified water may leak into lakes and streams. Damage in society and especially in traffic can become very large and expensive. Future increased precipitation in winter and less precipitation stored in the environment as snow result in higher flows in rivers during autumn and winter, and a lower spring runoff (Persson et al., 2011). This may increase the impacts with consequences in the future. The possible increasing annual amounts of precipitation and the possibly increasing heavy rains (Persson et

al., 2007) will increase the probability for higher annual fluxes in watercourses (Andréasson et al., 2004) which may lead to river Mölndalsån to flood more often than today. Recent studies indicate more wet spells and more stationary weather situations (Francis et al., 2009) which pose a larger risk for flooded rivers than previously thought. In the future even higher maximums will be present which results in more frequent flooded rivers. It is not the annual mean that directly affect flooded rivers, but it gives an indication. Based on previous flood- events, similar events will occur and possibly increase in the future, unless preventive measures are taken. This will further affect the emergency service, especially the emergency service and their location in Gårda. The public transportation may also suffer to a larger extent in the future. The prediction and warning system for high flows in rivers are better than for cloudbursts. When a river floods it is, however, hard to control the often large amounts of water. One can put out sandbags or other temporary protection walls, but still this is difficult to master. 6.2.2 Future vulnerability related to sea level rise and storm surges Future global sea level rise (IPCC, 2013b; UNEP, 2014), means a sea level rise by 65-80 cm in Gothenburg by the end of this century. The content of this means that the normal state will be much higher than it is today. Furthermore, sea level rise is a contributing factor to a higher maximum sea level from storm surges in the future. Today’s consequences are reported already at 40 cm above normal mean sea level, but most consequences occur at levels from 80 to 120 cm. With sea levels at 120 cm above normal, consequences are more costly and will disrupt social functions to a larger extent. Many buildings and roads are flooded at these levels. 80 cm above normal sea level today will be the initial state in the future. A future storm surge by 2100 are projected to be about 236 cm above present mean sea level. This will cause larger impacts for Gothenburg than what a storm surge does today (Persson et al., 2011). The new extreme high sea level will flood a much greater area than today, therefore, new areas will be impacted. The extra-tropical cyclone Sven that struck Gothenburg in December 2013 is far from the worst storm Gothenburg has been exposed to (Dalhov, 2012; GP, 2014a), yet it caused a lot of consequences for society. The storm Gudrun struck Gothenburg in 2005 and caused sea levels of 180 cm above normal (Fahlgren, 2013). As already mentioned, a possible increase of storm extremes in the North Sea due to climate change (Wang et al., 2008; Weisse et al., 2012; Woth et al., 2006), increase of average wind and maximum gusts (SOU, 2007) and that weather situations are becoming more stationary (Francis et al., 2009), may all contribute to higher and more frequent sea level extremes. If the weather situations become more stationary, it is possible that high sea levels last longer and that several low pressure systems follow each other causing larger and more costly consequences when water levels stay high for a longer time. Sea level rise is certain (IPCC, 2013b; UNEP, 2014) and combined with some of the other mentioned factors Gothenburg is very likely to face a larger vulnerability against high sea levels in the future. Urbanization in coastal areas combined with sea level rise over the last century has exacerbated the damage to fixed structures from modern storms that would have been relatively minor a century ago (Zhang, Douglas, & Leatherman, 2000). The westerly wind belt is tending to be pushed north, taking with it the path of low pressure areas and precipitation patterns, however this may also affect the magnitude of storm surges in the future. Westerly winds is projected to be the most dominant wind direction in the future and may therefor cause more severe storm surges (SOU, 2007). 70

Gothenburg has a lot of important infrastructure along the coast, which comprise tunnels, bridges, ports, docks, refineries, many companies and residences. Gothenburg is now expanding the city center across the river Göta älv, with 10 000 new residences and as many working places (Göteborgs Stad, 2014d) within this low-lying area. It is important for the city to grow and to make these ventures, but it needs to be done with caution and consideration and with a good adaptation strategy. With this said, the most flood prone area in Gothenburg will be developed. Areas close to river Göta älv are attractive neighborhoods within the municipality, and therefore more areas are being developed around the river. A seaside living has always been desirable, and will probably continue to be so. It is of importance to build these new areas resistant, so they can withstand future climate. As seen in figure 38, Casino Cosmopol have suffered consequences from high sea levels, and should along with other sea side companies have a prominent interest in adaptation measures. A continuous good warning system for low pressures and storm surges are of great importance. During most storms electricity are facing disturbances e.g. due to fallen trees across power lines, which may cause further consequences. For example a flooded basement where a bilge pump, driven by electricity, is used and will stop working if the power is shutdown, thus leading to larger consequences (more damage and costs) for the victim. Several incident reports describes problems where householders have a bilge pump, but it is broken. It is important for frequent exposed houses to regularly test and maintain their equipment to minimize their vulnerability.

Figure 38. Backflow in the water and sewer system in conjunction with high sea levels during the storm Sven that struck Gothenburg in December 2013. Photo: Susanna Gelin

6.3 Measures to reduce vulnerability Within this study buildings are found to be most vulnerable to flooding and that is why policy changes are needed. The water and sewer system needs to be well-dimensioned to withstand heavy rains and storm surges. To reduce both current and potential future risks of floods, adaptation measures must be taken. Adaptation strategies to prevent weather-related flood events are for example maintenance, improvements and adjustments of rainwater and sewer systems (especially in areas close to water or in depressions), build water storage possibilities (under or above ground), green roofs with water storage systems, plantings of trees or shrubs, high pavements, permanent protection walls, using water and moisture-resistant materials, high quaysides and build houses without basements and other depressions (attics may be a better alternative). If the new-built houses are not adapted to the future increasing rain amounts and sea level rise the number of houses vulnerable in the future will be larger than it is today. Therefore, it is important to start adapting now, and change the legal climate thresholds for buildings to withstand climate changes. Higher resolution models are under development, which will lead to better accuracy. With improved technology, better warnings and maintenance of drainage systems will provide a lower vulnerability. A well-functioning warning system for cloudbursts are hard to achieve, as they in the future still will be local and hard to predict. If people would control their drainpipes and wells correctly when the future warnings will be issued, consequences may be reduced. Storms and high flows in rivers and lakes are easier to predict, and warnings can be issued in advance. Future higher annual precipitation (Persson et al., 2011) and higher flows in rivers (Andréasson et al., 2004) may increase the impacts with consequences in the future. One concern arises, is the dredging of the river Mölndalsån enough for preventing future floods due to high flows? To reduce impacts of flooding permanent protections (walls, levees and underground reservoirs for water) may be needed. High sea levels will be one of the largest challenges for Gothenburg in the future (Moback, 2014) and as mentioned, the extreme high sea levels today may be the average in the future. In order to reduce the consequences of sea level rise combined with storm events an additional class 3 warning level of high sea levels (e.g. 160 cm above normal) may be appropriate in the future to prevent damage along the coasts and to prepare business owners to take the right measures. Building barriers may be one way to minimize the consequences of a storm surge, but may not be enough protection for global sea level rise in the long run. Maybe, a slow retreat is necessary eventually. However, a large population growth on the planet may inevitably result in constructions on and under the water, taking advantage of the water and its space. It is important to have in mind that the uncertainties within the models and from the emission scenarios may mislead prevention measures, both concerning higher annual precipitation and higher flows in rivers. A potential faster melting of ice at the poles could accelerate the sea level rise even more. A higher sea level will result in even more devastating storm surges. With a potential future increase of storm surge extremes in the North Sea (Weisse et al., 2012; Woth et al., 2006), the coastal communities will face not only a more severe but also a higher frequency of storm surges disturbing elementary community functions.

7. Conclusions This study have used GP articles, MSB incident reports, meteorological, oceanographic data and interviews to investigate Gothenburg and Mölndal’s present and future vulnerability against weather-related flood events. Two sources of information have provided a large dataset of consequences, and shows the importance of having several sources when investigating the vulnerability of a certain locality. MSB reports even the smallest consequences, and GP reports depending on space and global news situation but reports very thoroughly. The magnitude of an event can be determined from MSB reports, since they provide direct information of measures taken by the emergency service. This also shows that putting one additional source next to news articles when investigating the vulnerability of weather-related flood events is an accurate choice. Using only newspapers or incident reports as a source may result in a misleading interpretation of an LCLIP. Using several sources enhance the validity of the used method.

This study has found that Gothenburg and Mölndal is presently impacted by weather-related flood events caused by heavy rains, flooded rivers and high sea levels. Today heavy rains and cloudbursts are the largest risks and the cause of most consequences for the two municipalities. Weather-related flood events have caused consequences for the society functions (private residences, public buildings, motorists/roads, tunnel/bridges, public transportation, boats, aircrafts, sport and entertainment events, and water and sewer systems). The categories motorists/roads and flooded basements in buildings are the most exposed. The latter, consequently evolved from deficiencies and under-dimensioned water and sewer systems. The two dominating factors affecting sea level changes in river Göta älv is, firstly, air pressure and, secondly, wind speed and direction. High sea levels only occur when air pressure is low. Westerly winds and especially strong westerly winds push water against the coast and into the estuary of river Göta älv leading to sea level rise. At present Gothenburg and Mölndal is vulnerable to heavy rains and high sea levels. Future increased precipitation amounts, heavy rains and sea level rise will result in a higher vulnerability for the city without adaptation measures. Mölndal and Gothenburg municipalities may also face a higher flood risk of river Mölndalsån in the future due to increased precipitation and annual runoff. The biggest challenge by the end of the century will be the rising sea and storm surges in conjunction with low pressure systems. Complex infrastructures adjacent to the coast or water courses will be more exposed in the future. Increased precipitation for Gothenburg and Mölndal may trigger more frequent and severe flood events, which will result in more call outs for the emergency service. The pressure will increase on water and sewer systems designed for a non-changing climate. When the water and sewer systems cannot manage the runoff several more society functions will face more consequences as well. Today there is an insufficient warning system for heavy rains, but with an enhanced warning system in the future, it may be possible to issue warnings and prevent some of the consequences. According to interviews, the biggest challenge for Gothenburg today regarding climate adaptation is the cooperation between different authorities.

7.1 Further studies and enhancements Further investigations about Gothenburg’s and Mölndal’s vulnerability against weather-related events are needed to be able to achieve a robust society taking into account the climate change and increased densification in coastal areas. One proposal would be to add more sources of data to create a more comprehensive LCLIP. This study shows that except for news articles, incident reports from the emergency service combined with interviews will broaden the understanding of the vulnerability as a basis for measures to be taken. Within this study an attempt to collect statistics from the insurance company IF and the decontamination company EBE-skadeservice was performed without success. Additional sources for further studies and a broaden LCLIP, would be to add statistics from these two sources and other insurance companies, decontamination firms and real estate owners. The port of Gothenburg, power companies and the two airports Säve and Landvetter could also have valuable information. MSB has several incident reports in the category storm damage, these could be investigated further to broaden the knowledge about Gothenburg’s vulnerability against storms and storm surges. Traffic accidents, such as hydroplaning could also be investigated. Grid-data is not good enough when investigating cloudbursts, a recommendation for further studies would be to add radar data. Further investigations of adaptation measures for Gothenburg and Mölndal are needed. When investigating elements affecting sea level in Gothenburg, step-wise regression could be one alternative to determine the ranking of elements. For future scientific work within the field of risk, vulnerability and climate change it would be of interest for all actors involved to have one large risk-database with consequences and measures. A place were all can submit their work, ideas and statistics. This would make the work easier to survey and time efficient. Actors like local and regional authorities, insurance companies, emergency services, the police department, ports, energy suppliers, decontamination firms, air ports and risk assessment companies etc. should rectify their work and research. The database created for this project is quite extensive and contains a lot of valuable information where all is not used in this thesis. I think the information about weather-related consequences might become useful for further studies and projects in the future. For further studies and a broaden LCLIP, and to be able to find other angles of vulnerability for the two municipalities, it is important to have an interdisciplinary approach.

Acknowledgements

I would firstly like to thank my advisors at the Department of Earth Sciences at the University of Gothenburg, Yvonne Andersson-Sköld (also at COWI), Sofia Thorsson and David Rayner for their advice and guidance. I would also like to thank COWI for giving me the opportunity to write my master’s thesis at the unit of Environment, Risk and Safety. I would like to thank all the employees at COWI for their friendly response and for lending me the workspace. I would also like to thank Morgan Asp at MSB for his help to acquire incident reports, SMHI for answering all my questions about the meteorological and oceanographic data used in this thesis. Furthermore, I would also like to convey my thanks to all my interview subjects who has contributed with valuable information. Special thanks goes to my co-worker fellow student and friend Marie Svensson. It has really been supportive to have you by my side during the past year. Special thanks goes also to Jalle Hiltunen for his meteorological guidance, and Jennike Öhman for her language skills. You two have taught me so much through this project. I would also like to thank the Department of Earth Sciences at the University of Gothenburg for these five years of studies. It has been an inspiring, exiting and a very developing time, although it has been hard work, but most of the time it has been a lot of fun. I have met interesting people from all over, and made many unforgettable journeys around the world. I think this was the perfect choice of education - for me.

References Abbott, P. L. (2008). Natural disasters (Vol. Eight Edition): McGraw-Hill New York. Ackerman, S. A., & Knox, J. A. (2007). Meteorology - Understanding the Atmosphere (Vol. Second edition). USA: Thomson Higher Education. Adger, W. N. (2001). Social capital and climate change. Tyndall Centre for Climate Change Research. Andersson-Sköld, Y., Bergman, R., Johansson, M., Persson, E., & Nyberg, L. (2013). Landslide risk management - a brief overview and example from Sweden of current situation and climate change. International Journal of Disaster Risk Reduction, 3, 44-61. Andersson-Sköld, Y., Fallsvik, J., Hultén, C., Jonsson, A., Hjerpe, M., & Glaas, E. (2008, September). Climate change in Sweden - geotechnical and contaminated land consequences. In WSEAS International conference on environmental and geological science and engineering (Vol. 1, pp. 52-57). Andersson-Sköld, Y., Suer, P., Bergman, R., & Helgesson, H. (2014). Sustainable decisions on the agenda - a decision support tool and its application on climate change adaption. Local Environment, Accepted. Andersson-Sköld, Y., Thorsson, S., Rayner, D., Lindberg, F., Janhäll, S., Jonsson, A., . . . Granberg, M. (2014). An intergrated method for assessing climate related risks and adaptation alternatives in urban areas. Climate Risk Management, Submitted. Andréasson, J., Bergström, S., Carlsson, B., Graham, L. P., & Lindström, G. (2004). Hydrological change-climate change impact simulations for Sweden. AMBIO: A Journal of the Human Environment, 33(4), 228-234. Asp, M. (2014). MSB's work. Interviewer, S. Gelin (Ed.). Axell, T. (2013). [METAR-data SMHI]. Beniston, M., Stephenson, D. B., Christensen, O. B., Ferro, C. A., Frei, C., Goyette, S., . . . Koffi, B. (2007). Future extreme events in European climate: an exploration of regional climate model projections. Climatic change, 81(1), 71-95. Benn, D. I., & Evans, D. J. (2010). Glaciers and glaciation: Hodder Education. Berg, P., Moseley, C., & Haerter, J. O. (2013). Strong increase in convective precipitation in response to higher temperatures. Nature Geoscience. Bergström, S. (2012). Framtidens havsnivåer i ett hundraårsperspektivkunskapssammanställning 2012. SMHI Klimatologi(5). Bernes, C., & Holmgren, P. (2007). Meteorologernas Väderbok. Värnamo, Sverige Fälth & Hässler. Boverket. (2014). Storgöteborg har 13 kommuner. Retrieved 2014-01-23, from http://www.boverket.se/Boende/Analys-av- bostadsmarknaden/Bostadsmarknadsenkaten/Region-karta-over- kommuntyper/Storgoteborg/ BRG. (2014). Tillväxt i Göteborgsregionen. Retrieved 2014-01-23, from http://goteborg.se/wps/wcm/connect/36aa978045f439479a71da93cac393f3/Tillv%C3%A4xt +i+G%C3%B6teborgsregionen_underlag+BRG.pdf?MOD=AJPERES&CACHEID=36aa978045f43 9479a71da93cac393f3 Brooks, N. (2003). Vulnerability, risk and adaption: A conceptual framework. Tyndall Centre for Climate Change Research Working Paper 38. Carlsson-Kanyama, A. (2009). Extrema väderhändelser i Skåne - Pressklipp 2003-2007, ett moment inom LCLIP. Coumou, D., & Rahmstorf, S. (2012). A decade of weather extremes. Cutter, S. L. (1996). Vulnerability to environmental hazards. Department of Geography, University of South Carolina, Columbia, USA. Human Geography 20,4 (1996) pp. 529-539. Dalhov, G. (2012). Den glömda stormen, Göteborgs-Posten. Retrieved from http://www.dalhov.com/new/PDF/4-februariGP-VG.pdf de Koster, S. (2013). Officer in charge oceanographer at SMHI. Interviewer, S. Gelin (Ed.).

Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., . . . Bauer, P. (2011). The ERA‐ Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553-597. Fahlgren, M. (2013, 2013-09-23). Portar eller vallar mot havet en miljardfråga. from http://www.vartgoteborg.se/prod/sk/vargotnu.nsf/1/ovrigt,portar_eller_vallar_mot_havet_ en_miljardfraga FloodSite. (2009). Flood risk assessment and flood risk management. An introduction and guidance based on experiences and findings of FLOODsite (an EU-funded Integrated project) FN. (2005). Hyogo Framework for Action 2005-2015: Building the resilience of nations and communities to disasters. A/conf. 206/6, extract from the final report of the world conference on disaster reduction. . FOI. (2014a). FOI Climatools. Retrieved 2014-03-11, from http://www.foi.se/en/Customer-- Partners/Projects/Climatools/Climatools/ FOI. (2014b). Local Climate Impacts Profile. Retrieved 2014-02-13, from http://www.foi.se/en/Customer--Partners/Projects/Climatools/Climatools/Tools/Local- Climate-Impacts-Profile/ Francis, J. A., Chan, W., Leathers, D. J., Miller, J. R., & Veron, D. E. (2009). Winter Northern Hemisphere weather patterns remember summer Arctic sea‐ice extent. Geophysical Research Letters, 36(7). Frich, P., Alexander, L., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A., & Peterson, T. (2002). Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Research, 19(3), 193-212. Fry, C. (2009). The Impact of Climate Change: The World's Greatest Challenge in the Twenty-First Century. London: New Holland. Füssel, H.-M., & Klein, R. J. T. (2006). Climate change vulnerability assessments: an evolution of conceptual thinking. Climatic Change (2006) 75: 301-329. Gelin, S., & Svensson, M. (2012). Hur har Göteborgs-Posten rapporterat väderhändelser och deras konsekvenser i Göteborg under perioden 1991 - 2011 Ett första steg till en lokal klimateffektsprofil över Göteborg. (Bachelor 15 etc), University of Gothenburg. Gothenburg, P. O. (2014). About the port. from http://www.portofgothenburg.com/ GP. (2013). Göteborgs-Posten. Lokalsinne i världsklass. Retrieved 2013-12-18, from http://info.gp.se/omgp/1.1139529 GP. (2014a). Minns du de här stormarna? Retrieved 2014-05-07, from http://www.gp.se/gpplus/bildergp/1.474174-minns-du-de-har-stormarna- GP. (2014b). Vindar och snöfall slog hårt mot Göteborg. http://www.gp.se/nyheter/goteborg/1.2201194-vindar-och-snofall-slog-hart-mot-goteborg GÄV. (2011, 2011-02-17). Fakta om Göta älvs avrinningsområde. Retrieved 2014-01-22, from http://www.gotaalvvvf.org/faktaomgotaalv/faktaomgotaalvsavrinningsomrade.4.101b29861 2d0e33932680001836.html Hammarklint, T. (2014). Sjösprång/Meteotsunami. In S. Gelin (Ed.). Haylock, M., Hofstra, N., Klein Tank, A., Klok, E., Jones, P., & New, M. (2008). A European daily high‐ resolution gridded data set of surface temperature and precipitation for 1950–2006. Journal of Geophysical Research: Atmospheres (1984–2012), 113(D20). Holden, J. (2008). An introduction to Physical Geography and the Environment (Vol. Second edition): Pearson Prentice Hall. Holton, J. R., & Hakim, G. J. (2012). An introduction to dynamic meteorology: Academic press. Hultén, C., Andersson-Sköld, Y., Ottosson, E., Edstam, T., & Johansson, Å. (2007). Case studies of landslide risk due to climate change in Sweden. Hunt, A., & Watkiss, P. (2011). Climate change impacts and adaptation in cities: a review of the literature. Climatic Change. 104 (1). pp. 13-49. ISSN 0165-0009. . IPCC. (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. In S. 77

Solomon, D.,Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.) (Ed.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp. IPCC. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. In J. Handmer, Y. Honda, Z.W. Kundzewicz, N. Arnell, G. Benito, J. Hatfield, I.F. Mohamed, P. Peduzzi, S. Wu, B. & K. T. Sherstyukov, and Z. Yan [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)] (Eds.). Cambridge University Press, Cambridge, UK, and New York, NY, USA, 582 pp. IPCC. (2013a). Annex III: Glossary [Planton, S. (ed.)]. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.) (Ed.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. IPCC. (2013b). Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovern- mental Panel on Climate Change In T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.) (Ed.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. IPCC. (2014). Working group II Report Impacts, Adaptation and vulnerability. Johansson, M., & Blumenthal, B. (2009). Att mäta sårbarhet mot naturolyckor - Om sårbarhet som begrepp och indikatorer . . Joughin, I., Smith, B. E., & Medley, B. (2014). Marine Ice Sheet Collapse Potentially Under Way for the Thwaites Glacier Basin, West Antarctica. Science, 344(6185), 735-738. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., . . . Woollen, J. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of the American meteorological Society, 77(3), 437-471. Kaplan, S., & Garrick, B. J. (1980). On The Quantitative Definition of Risk. Risk Analysis, Vol. 1, No. 1, 1980. Keller, E. A., & Blodgett, R. H. (2006). Natural Hazards: Earth's Processes as Hazards, Disasters, and Catastrophes. USA: Pearson Prentice Hall. Kotecha, R., Thornes, J., & Chapman, L. (2008). Birmingham’s Local Climate Impacts Profile (LCLIP) University of Birmingham, Birmingham. Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World map of the Koppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259-263. Kundzewicz, Z. W. (2001). Non-structural Flood Protection and Sustainability. Lif, M. (2006). Översvämningar - Positiva och negativa effekter, samt människans roll Lindgren, E., Albihn, A., Andersson, Y., Forsberg, B., Olsson, G., & Rocklöv, J. (2008). Ändrat klimat får konsekvenser för hälsoläget i Sverige Klinik och Vetenskap (Vol. 105, pp. 2018-2023). Länsstyrelsen. (2012). Västra Götaland i ett förändrat klimat. In C. Källerfeldt, C. Valen, J. Magnusson, S. Hogdin, A. Bergstedt Söderström, M. Möller, F. Fredriksson & S. Wolme (Eds.). Trosa tryckeri: Länsstyrelsen Västra Götalands Län. Marshak, S. (2008). Earth - Portrait of a planet. New York & London: W.W Norton & Company. McCarthy, J. J. (2001). Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change: Cambridge University Press. MetOffice. (2014, 2014-02-05). Storm Surge. Retrieved 2014-03-10, from http://www.metoffice.gov.uk/learning/learn-about-the-weather/weather- phenomena/storm-surge

Mistra. (2010, 2010-10-26). Gothenburg protected from submergence. Retrieved 2014-03-20, from http://www.mistra.org/en/mistra/news/news-archive/2010-10-26-gothenburg-protected- from-submergence.html Moback, U. (2014). Gothenburg against flooding. Interviewer, S. Gelin (Ed.). Monserrat, S., Vilibić, I., & Rabinovich, A. (2006). Meteotsunamis: atmospherically induced destructive ocean waves in the tsunami frequency band. Natural Hazards and Earth System Science, 6(6), 1035-1051. MSB. (2011). Identifiering av områden med betydande översvämningsrisk. Steg 1 i förordningen (2009:956) om översvämningsrisker - preliminär riskbedömning. Slutrapport. : Enheten för skydd av samhällsviktig verksamhet. NASA. (2014). Global Climate Change - Vital Signs of the Planet. Climate change - How do we know? . from http://climate.nasa.gov/evidence NWS. (2014). Storm Surge Overview. from http://www.nhc.noaa.gov/surge/ Nyberg, L. (1979). Sjösprång. Förste stadshydrolog SMHI. Nyberg, L. (2008). Översvämningar och riskhantering - en forskningsöversikt. Centrum för klimat och säkerhet - Karlstads Universitet. Nyqvist, P. (2014). The emergency service in Gothenburg. Interviewer, S. Gelin (Ed.). Parker, D. J. (2000). Floods (Vol. 1): Routledge. Persson, G., Andréasson, J., Eklund, D., Hallberg, K., Nerheim, S., Sjökvist, E., . . . Åström, S. (2011). Klimatanalys för Västra Götalands län. Persson, G., Bärring, L., Kjellström, E., Strandberg, G., & Rummakainen, M. (2007). Climate indices for vulnerability assessments: SMHI. Prasad, N., Ranghieri, F., Shah, F., Trohanis, Z., Kessler, E., & Sinha, R. (2009). Climate resilient cities. A Primer on Reducing Vulnerabilities to Disasters. Washington, DC: The World Bank. Raupach, M. R., Marland, G., Ciais, P., Le Quéré, C., Canadell, J. G., Klepper, G., & Field, C. B. (2007). Global and regional drivers of accelerating CO2 emissions. Proceedings of the National Academy of Sciences, 104(24), 10288-10293. Retriever. (2013a). The most extensive digital news archive in Scandinavia. from http://www.retriever-info.com/en/category/news-archive/ Retriever. (2013b). Our media monitoring saves your time. from http://www.retriever- info.com/en/category/media-coverage/ Retriever. (2014). Mediearkivet. Available from TT-Gruppen Mediearkivet https://web-retriever- info-com.ezproxy.ub.gu.se/services/archive.html Rignot, E., Mouginot, J., Morlighem, M., Seroussi, H., & Scheuchl, B. (2014). Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith, and Kohler glaciers, West Antarctica, from 1992 to 2011. Geophysical Research Letters. Robert, N. J., Nadim, F., & B., K. (2007). Quantification of vulnerability to natural hazards. . First International Symposium on Geotechnical Safety & Risk. Shanghai Tongji University, China. Ruddiman, W. F. (2008). Earth's Climate - Past and Future. (Second edition ed.). New York: W. H. Freeman and Company. Rummukainen, M. (2010). En kunskapsöversikt om Extrema väderhändelser och klimatförändringarnas effekter (Vol. Mistra-SWECIA Report No 3). Samuels, P. G. (2006). A European perspective on current challenges in the analysis of inland flood risks Flood Risk Management: Hazards, Vulnerability and Mitigation Measures (pp. 21-34): Springer. Sarewitz, D., Pielke jr, R., & Keykhan, M. (2003). Vulnerability and Risk: Some Thoughts from a Political and Policy Perspective. . Risk Analysis, vol. 23, No. 4, 2003. Schanze, J., Zeman, E., & Marsalek, J. (2007). Flood Risk Management: Hazards, Vulnerability and Mitigation Measures: Hazards, Vulnerability and Mitigation Measures (Vol. 67): Springer. SGI. (2012). Skredrisker i Göta älvdalen i ett förändrat klimat Slutrapport Del 1 - Samhällskonsekvenser. Linköping.

SMHI. (2005a, 2005). Extrem nederbörd 1900 - 2004. Retrieved 2014-03-13, from http://www.smhi.se/polopoly_fs/1.1422!extremnbd_uppd%5B1%5D.pdf SMHI. (2005b). Klimatunderlag för sårbarhetsanalys Göteborgs Stad. Rapport nr. 2005-42. In Lindahl Sture, Bergström Sten, Krieg Roland, Persson Gunn, Kindell Sven & W. Lennart (Eds.). SMHI. (2006). Klimatunderlag för sårbarhetsanalys Göteborgs Stad - Etapp 2, sannolikhets- och riskbedömningar. Rapport nr. 2006-16. In L. Sture, B. Sten, J. Lasse, K. Sven, K. Roland, L. Helma, M. Fredrick & W. Lennart (Eds.). SMHI. (2009a, 2009-01-16). Hur fungerar en klimatmodell? , 2014-06-08, from http://www.smhi.se/kunskapsbanken/klimat/hur-fungerar-en-klimatmodell-1.470 SMHI. (2009b, 2009-10-27). Hydrologiska prognos- och varningstjänsten. Retrieved 2014-03-19, from http://www.smhi.se/omsmhi/hydrologiska-prognos-och-varningstjansten-1.7973 SMHI. (2009c, 2009-09-17). Klimatförändringar. Retrieved 2014-03-05, from http://www.smhi.se/kunskapsbanken/klimat/klimatforandringar-1.7206 SMHI. (2009d, 2009-05-29). Lufttryck och havsvattenstånd. Retrieved 2014-03-04, from http://www.smhi.se/kunskapsbanken/oceanografi/lufttryck-och-havsvattenstand-1.3096 SMHI. (2009e, 2009-07-13). Sjösprång. Retrieved 2014-03-10, from http://www.smhi.se/kunskapsbanken/oceanografi/sjosprang-1.4200 SMHI. (2009f). Sveriges landskapsklimat Faktablad nr 42 (pp. 31). SMHI. (2009g). Utökad varningstjänst för extremväder - Rapport till regeringen. In P.-O. Hårsmar (Ed.). SMHI. (2009h, 2009-05-29). Vind och havsvattenstånd. Retrieved 2014-03-04, from http://www.smhi.se/kunskapsbanken/oceanografi/vind-och-havsvattenstand-1.3098 SMHI. (2009i, 2009-08-14). Översvämningar - Kundskapsbanken. Retrieved 2014-02-25, from http://www.smhi.se/kunskapsbanken/hydrologi/oversvamningar-1.5949 SMHI. (2010, 2010-02-11). Detta är SMHI. Retrieved 2014-03-13, from http://www.st-smhi.org/ SMHI. (2011a, 2011-10-28). Rotblöta och skyfall. Retrieved 2014-03-07, from http://www.smhi.se/kunskapsbanken/rotblota-1.17339 SMHI. (2011b, 2011-10-28). Sommar. Retrieved 2014-01-22, from http://www.smhi.se/kunskapsbanken/meteorologi/sommar-1.1084 SMHI. (2012a, 2012-06-19). Förändrad framtida vattentillgång jämfört med 1963-1992. from http://www.smhi.se/klimatdata/klimatscenarier/klimatanalyser/forandrad-framtida- vattentillgang-1.22606 SMHI. (2012b, 2012-12-19). Hur mäts nederbörd? Retrieved 2014-03-13, from http://www.smhi.se/kunskapsbanken/meteorologi/hur-mats-nederbord-1.637 SMHI. (2012c, 2012-08-14). Korttidsnederbörd i Sverige 1995-2008. Retrieved 2014-03-13, from http://www.smhi.se/kunskapsbanken/meteorologi/korttidsnederbord-i-sverige-1995-2008- 1.23634 SMHI. (2012d, 2012-06-19). Variation och osäkerhet. Retrieved 2014-06-08, from http://www.smhi.se/klimatdata/klimatscenarier/klimatanalyser/variation-och-osakerhet- 1.22671 SMHI. (2013a, 2013-08-22). Extrem punktnederbörd. 2014-07-16, from http://www.smhi.se/kunskapsbanken/meteorologi/extrem-punktnederbord-1.23041 SMHI. (2013b, 2013-11-22). Nederbörd. Retrieved 2014-01-22, from http://www.smhi.se/kunskapsbanken/meteorologi/nederbord-1.361 SMHI. (2013c, 2013-09-16). Sjöbris. Retrieved 2013-12-12, from http://www.smhi.se/kunskapsbanken/meteorologi/sjobris-en-sval-bris-soliga-sommardagar- 1.3814 SMHI. (2013d, 2013-08-09). Stormar i Sverige Retrieved 2014-05-26, from http://www.smhi.se/kunskapsbanken/meteorologi/stormar-i-sverige-1.5770 SMHI. (2013e, 2013-12-10). Stormen Sven gav nya vattenståndsrekord i Öresund. Retrieved 2014- 02-13, from http://www.smhi.se/nyhetsarkiv/stormen-sven-gav-nya-vattenstandsrekord-i- oresund-1.34732 80

SMHI. (2013f, 2013-12-06). Sven var förhållandevis extremast vid Bohuskusten. Retrieved 2014-02- 13, from http://www.smhi.se/nyhetsarkiv/sven-var-forhallandevis-extremast-vid- bohuskusten-1.34671 SMHI. (2014a, 2014-01-21). Havsnivåhöjning. 2014-06-17, from http://www.smhi.se/kunskapsbanken/oceanografi/havsvattenstand-1.3090 SMHI. (2014b, 2014-01-21). Havsvattenstånd. Retrieved 2014-03-04, from http://www.smhi.se/kunskapsbanken/oceanografi/havsvattenstand-1.3090 SMHI. (2014c). Klimatscenarier. 2014-06-17, from http://www.smhi.se/klimatdata/framtidens- klimat/klimatscenarier#area=eur&dnr=0&sc=rcp85&seas=ar&var=t SMHI. (2014d). SMHI LuftWebb. Retrieved 2014-01-14, from http://www.smhi.se/nyhetsarkiv/klimatdata-for-nedladdning-pa-luftwebb-1.21123 SMHI. (2014e). SMHI Varningar. Retrieved 2014-03-25, from http://www.smhi.se/vadret/vadret-i- sverige/Varningar/varning_tabell_n1_sv.htm SMHI (2014f, 2014-04-24). [Warning system development]. SMHI Axell, T. (2014). Varningar under stormen Sven. In S. Gelin (Ed.). SNA. (2003, 2003-11-27). Västra Götaland Västra Götaland. Retrieved 2013-12-12, from http://friatlasgis.sna.se/sna/webb.atlas?book=X SOU. (2007). Sweden facing climate - threats and opportunities. Final Report from the Swedish Commission on Climate and Vulnerability. Swedish Government Official Report, 60. Stockholm, Sweden. Spanger-Siegfried, E., Dougherty, B., & et.al. (2003). The Adaptation Policy Framework: USER'S GUIDEBOOK. Final draft. Göteborgs Stad. (2006). Extrema vädersituationer - Hur väl rustat är Göteborg? Göteborgs Stad. (2011, 2011-02-17). RiverCity Gothenburg. Retrieved 2014-03-20, from http://www.centralaalvstaden.nu/wp- content/uploads/2012/01/Invitation_Workshop_RiverCity.pdf Mölndals Stad. (2013, 2013-10-15). Fakta om Mölndal. from https://www.molndal.se/medborgare/kommunochpolitik/faktaommolndal.4.16eccd66132d 06f5218800029802.html Mölndals Stad. (2014a, 2014-01-16). Mölndalsån. from http://www.molndal.se/medborgare/byggaboochmiljo/naturvardparker/sjoarochvattendrag /molndalsan.4.47315bb7131d8f123cf800017764.html Göteborgs Stad. (2014b). Vatten såklart. Retrieved 2014-01-22, from http://goteborg.se/wps/portal/invanare/bygga-o-bo/kommunens-planarbete/oversiktlig- planering/fordjupningar-och-tillagg/vatten-saklart/ Göteborgs Stad. (2014c). Välkommen till statistik Göteborg. Retrieved 2014-01-22, from http://www4.goteborg.se/prod/G-info/statistik.nsf Göteborgs Stad. (2014d). Älvstaden. Retrieved 2014-01-21, from http://alvstaden.goteborg.se/vad- hander-nu/frihamnen-aktuellt-just-nu/ Strahler, A., & Strahler, A. (2005). Physical Geography: Science and systems of the human environment (Vol. Third edition). USA: John Wiley & Sons, Inc. SvD. (2014). Dödligaste stormen sedan Gudrun. http://www.svd.se/nyheter/inrikes/dodligaste- stormen-sedan-gudrun_8802138.svd Svensson, M., & Tjäder, A. (2007). Mölndalsån - från källan till Drömmarnas kaj. Alingsås: Hammar Förlag. Tapsell, S. M., Penning-Rowsell, E. C., Tunstall, S. M., & Wilson, T. (2002). Vulnerability to flooding: health and social dimensions. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 360(1796), 1511-1525. UKCIP. (2009). A local climate impacts profile: how to do an LCLIP. Oxford: School of Geography and Environment.

UN/ISDR. (2003, 2003-10-23). PRESS RELEASE International Day for Disaster Reduction turns the tide on water-related disasters. Retrieved 2014-03-14, from http://www.unisdr.org/2003/campaign/pa-camp03-pressrelease-eng.htm UN/ISDR. (2012). How To Make Cities More Resilient: A Handbook For Local Government Leaders. Geneva: United Nations - International Strategy for Disaster Reduction. UNEP. (2014). Global outlook for ice and snow. In C. A., NichollsRobert, H. E. & GornitzVivien (Eds.), Ice and Sea-level Change (Chapter 6C). Wang, S., McGrath, R., Hanafin, J., Lynch, P., Semmler, T., & Nolan, P. (2008). The impact of climate change on storm surges over Irish waters. Ocean Modelling, 25(1), 83-94. Weisse, R., von Storch, H., Niemeyer, H. D., & Knaack, H. (2012). changing north sea storm surge climate. Ocean & Coastal Management. Wern, L. (2012). Extrem nederbörd i Sverige under 1 till 30 dygn, 1900 - 2011. Willems, P., Arnbjerg-Nielsen, K., Olsson, J., & Nguyen, V. (2012). Climate change impact assessment on urban rainfall extremes and urban drainage: Methods and shortcomings. Atmospheric research, 103, 106-118. Wisner, B. (2004). At risk: natural hazards, people's vulnerability and disasters: Psychology Press. Wolfgang, K. (2002). Keynote lecture: Flood risk = hazard x exposure x vulnerability. Science Press. Woth, K., Weisse, R., & Von Storch, H. (2006). Climate change and North Sea storm surge extremes: an ensemble study of storm surge extremes expected in a changed climate projected by four different regional climate models. Ocean Dynamics, 56(1), 3-15. Zhang, K., Douglas, B. C., & Leatherman, S. P. (2000). Twentieth-century storm activity along the US east coast. Journal of Climate, 13(10). Zinderland, M. (2012). In S. Gelin & M. Svensson (Eds.).

Appendix A

A.1 Keywords for database

A.1.1 First step  Gräsbrand (grass fire)  Hagel (hail)  Hård vind (strong wind)  Inversion  Kraftig vind (heavy wind)  Köldrekord (cold records)  Orkan (hurricane)  Orkanbyar (hurricane wind gusts)  Oväder (bad weather)  Regn (rain)  Skogsbrand (wildfire)  Skred (landslide)  Skyfall (heavy rain)  Snö (snow)  Snödrev (drifting snow)  Snöstorm (blizzard)  Storm/-ar (storm/-s)  Torka (drought)  Tromb (tornado)  Värme (heat)  Värmebölja (heat wave)  Värmerekord (heat records)  Åskväder (thunderstorm)  Översvämning, (flooding)

A.1.2 Second step  Höga vattennivåer (high water levels)  Höga vattenstånd (high water levels)  Länspump* (bilge pump)  Nederbörd (precipitation)  Översväm* (flood)

Jokers [*] are added behind words to make sure derivations such as floods (översvämningar) are covered, this will show all hits connected with all words related to flood.

Appendix B

B.1 Interview questions

B.1.1 Questions for the Emergency service in Gothenburg  Hur arbetar ni med Göteborgs sårbarhet gällande väderrelaterade översvämningar? (How do you work with Gothenburg’s vulnerability regarding weather-related flooding?)  Använder ni själva de material (incidentrappotrer) som ni skickar vidare till MSB? (Do you use the material (incident reports) that you send to MSB?)  Hur tar ni tillvara på tidigare erfarenheter? (How do you capitalize experiences?)  Hur ser ni på framtiden med ökande nederbördsmängder, stigande havsnivå och stormar? (How do you look upon the future with increased rainfall, rising sea levels and storms?)  Arbetar ni kontinuerligt med att minska konsekvenserna efter väderrelaterade översvämningar? (Do you work continuously to reduce the consequences of weather-related flooding?)  Vad anser du Göteborg behöver arbeta med för att göra staden tillräckligt motståndskraftig mot översvämningar? (What do you think Gothenburg needs to work with to make the city resilient enough to flooding?)  Utifrån er roll i samhället, anser ni att ni behöver mer resurser eller behöver utveckla arbetet med anpassning för att minska konsekvenserna från översvämningar? (Based on your role in society, do you think you need more resources or need to develop the work with adaptation to reduce the consequences of flooding?)  Skrivs en incidetrapport per adress? Finns det intresse av att förbättra utformandet av incidetrapporter? (Do you write one incident report per address? Is there any interest of improving the design of the incident reports?)  Tar ni hänsyn till SMHI’s varningar? (Do you take into account the SMHI warning system?)  Bemannar ni annorlunda beroende på SMHI’s varningar? (Do you staff differently depending on the SMHI warnings?)  Tycker ni att SMHI’s varningar (parametrarna gällande översvämningar) är tillräckliga? (Is the SMHI warning system (the parameters essential for flooding) sufficient?)

B.1.2 Questions for the City Planning Department in Gothenburg  Hur arbetar ni med att skydda infrastrukturen mot stigande havsnivå och stormar idag? Hur ska man skydda den i framtiden?

(How do you work to protect the infrastructure against rising sea levels and storm surges today? How should you protect it in the future?)  Vad finns för strategier mot skyfall och ihållande regn? (What are the strategies against heavy- and persistent rain?)  Anser man att SMHI’s varningssystem (det som är väsentliga för översvämningar) är tillräckliga? (Is the SMHI warning system (the parameters essential for flooding) sufficient?)  Vad är Göteborgs största utmaning inför framtiden? (What is the biggest challenge for Gothenburg in the future?)

B.1.3 Questions for MSB  Vad är syftet med databasen för incidentrapporter? (What is the purpose of the data base containing incident reports?)  På vilket sätt använder ni materialet i databasen? (How do you use the material in the data base?)  Använder andra myndigheter eller forskare materialet i databasen? (Do other agencies or researchers use the material in the data base?)  Finns det ett behov av att förbättra utformandet och innehållet i incidentrapporterna? (Is there a need for improvement of the design and content in the incident reports?)

B.1.4 Questions for SMHI  Hur arbetar ni med att förbättra varningssystemet mot kraftiga regn? (How do you work with the enhancement of the warning system against heavy rain?)

B.1.5 Questions for SKANSKA  Hur arbetar ni med översvämningsrisken idag? (How do you work with the risks of flooding today?)  Hur tror ni att ni kommer arbeta med översvämningsrisken i framtiden? (How do you think you will work in the future with the risk of flooding?)  Finns det ett behov att bli bättre gällande klimatanpassning och då specifikt översvämningar? (Is there a need to improve your knowledge concerning climate adaptation, especially about flooding?)  Vems ansvar är det att bygga ”översvämningsanpassat”? (Who is responsible for building flood-resilient constructions?)  Vilka resurser krävs och av vem? (What resources are required and by whom?)  Hur upplevs kunskapen om översvämningsrisken hos hyresgäster och köpare? (How do you experience the knowledge of flood risk among tenants and buyers?)

III