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Detection of Potential Areas of Changing Climatic Conditions at a Regional Scale Until 2100 for Saxony, Germany

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Detection of Potential Areas of Changing Climatic Conditions at a Regional Scale Until 2100 for Saxony, Germany Vol. 3 Issue 2 December 2015 Detection of potential areas of changing climatic conditions at a regional scale until 2100 for Saxony, Germany Rico Kronenberg Dresden University of Technology, Department of Hydrosciences, 01069 Dresden, Berg Street 66, Room P 205, Saxony, Germany; Bauman Moscow State Technical University, 105005 Moscow, Baumanskaya 2-ya Street 5, Russia, e-mail: [email protected] Johannes Franke Saxon State Agency for Environment, Agriculture and Geology, 01326 Dresden Pillnitz, August-Böckstiegel Street 1, Saxony, Germany, e-mail: [email protected] Christian Bernhofer Dresden University of Technology, Chair of Meteorology, 01737 Tharandt, Pienner Street 23, Room 108, Saxony, Germany, e-mail: [email protected] Philipp Körner Dresden University of Technology, Chair of Meteorology, 01737 Tharandt, Pienner Street 23, Room 105, Saxony, German, e-mail: [email protected] Abstract: Two different approaches are applied for the investigation of possible changes within the climate regime – as an important component of vulnerability – on a regional scale for Saxony, Germany. Therefore data were applied from the output of the statistical climate models WETTrEG2010 and WErEX-V for a projected period until 2100. In the first step, rain gauge-based precipitation regions with similar statistics have been classified. The results show that stable regions are mainly located in the Ore Mountains, while regions of higher uncertainty in terms of a climate signal exist particularly between the lowlands and mountains. In the second step, station-based data on precipitation, temperature and climatic water balance were interpolated by the regionalisation service raklida. Model runs which lay closest to the observed data for the period 1968 to 2007 were identified. Therefore, regions of similar climates were classified and compared by means of a Taylor diagram. The derived patterns of the observed data are in good agreement with formerly defined climate regions. In the final step, anomalies of 10 yearlong averages from 2021 until 2090 were calculated and then spatially classified. The classification revealed four complex regions of changing climate conditions. The derived patterns show large differences in the spatial distribution of future precipitation and climatic water balance changes. In contrast, tempera- ture anomalies are almost independent of these patterns and nearly equally distributed. Keywords: Multivariate statistics, cluster analysis, climate impact research, WETTrEG2010, WErEX-V, raklida Submitted 13 February 2015, revised 25 June 2015, accepted 23 September 2015 1. Introduction (renner et al. 2013), the hydraulic impact on urban drain- age systems (Berggren et al. 2012), a general increasing Statements about long-term changes of the climate at flood risk (Wilby, keenan 2012) and even impact on hu- a regional scale are becoming of increasing importance for man health (Patz et al. 2005). It must be stated that the decision makers in politics and economics. These changes chosen examples only outline the magnitude of regional result in the challenging task of choosing appropriate climate change and imply the need for analysis of the past action, as it affects a vast number of fields. These range and future spatial and temporal behaviour of the climate from the limitation of freshwater resources (Freitas et al. individually, and at the respective scales. For this reason, 2013), potential increased dangers of crop areas due to me- a number of regional studies investigated different aspects teo-hydrological hazards, i.e. droughts and floods, (Zhang of observed changes of climate variables. Precipitation et al. 2013) observed changes in forestry and land surface and temperature stand out from the pool of potential pa- 18 R. Kronenberg et al. rameters, as they are the most interesting and important in regional changes in the climate regime are identified. We terms of limitations and extremes. define those regions as climate areas with a similar long- Zhang et al. (2013) investigated – with the use of copu- term behaviour of precipitation, temperature and climatic las and Mann-kendall tests – the probabilistic behaviours, water balance. While there exist many studies investiga- trends and changing magnitudes in space and time of pre- ting precipitation and temperature and their properties in cipitation extremes in China. Their findings clearly show, space and time as single factors, a lack of studies con- for the period 1960 to 2005, a significant increase of the taining a more complex spatial analysis (i.e. considering impact on flood and drought-affected crop areas, and they more than one factor in a multivariate analysis) for the outline the necessity of respective adaptation strategies in regional scale must be stated. the context of the world’s most populous nation. Addressing these issues, this paper focuses on the A decrease in observed precipitation was found by analysis and investigation of climate regions from a hydro- romano and Preziosi (2013) for the Tiber region in Italy. climatic perspective for the area of Saxony, Germany They analysed the annual and the seasonal regime of the through the use of multivariate statistics and cluster analy- number of rainy days, the mean intensity and maximum sis. The main issues can be summed up in the form of the daily precipitation. following motivational questions: These two studies already illustrate the strong invari- 1. Which element is the driving force for detecting poten- ance of precipitation in the past, which was also sum- tial areas of changing climatic conditions on a regional marised by reiter et al. (2011). In their study, precipitation scale? in the Upper danube region showed lower significance 2. How large is the spatial heterogeneity of the projected values than temperature data for the observed trends. This, element-spanning anomalies? according to the authors, was explained by the higher spa- 3. To what extent do regions have higher uncertainty in tial and temporal variability of precipitation, and the fact terms of a climate signal, with relation to precipitation, that precipitation held positive as well as negative trends in Saxony? on seasonal and annual time series. The authors argue that This study aims to identify potential areas in Saxony due to the fact that the observed trend was not unique, affected by regional climate change, and to provide simple a general statement for the investigated alpine region yet significant results for further impact related studies. could not be made. The results are presented in a way that makes them acces- Furthermore, Wójcik et al. (2014) revealed in their sible for climate impact research from any of the affected study that the variability of precipitation challenges sta- fields. tistical downscaling approaches. They concluded that this was because long-term average values of gamma 2. Study region and data parameters for precipitation can be precisely reproduced by means of canonical correlation analysis, but that the The study region is spatially limited to the federal short-term variability of precipitation distribution cannot. boundaries of the Free State of Saxony. This region spans ashcroft et al. (2013) observed a considerable varying an area of 18420.15 km². The topography within this area in the large-scale circulation features on minimum and can be divided into lowlands, uplands and high mountain maximum precipitation and mean sea level pressure over ranges up to 1200 m above sea level (Mannsfeld, Syrbe three sub-periods for long-term time series of different sta- 2008). The climate is marked by significant differences. tions in australia – this covered the period from 1871 to The annual mean temperature of the northern lowlands 2009, and was considered natural climate variability by and central Saxon uplands lies between 8.5 and 10 degrees the authors. Celsius for the period 1991-2005, whilst the mean tempe- In a study Nguyen et al. (2013), which had a fo- rature of the mountain ridges ranges between 6 and 7.5 cuson spatial patterns, changes in precipitation region degree Celsius. The mean annual precipitation is distribut- boundaries for Vietnam were observed. The results were ed in a similar manner from 500 to 800 mm in the lowlands carried out for the period from 1971 to 2010 by deploying and 900 to 1200 mm in the southern mountains (SMUL a k-means clustering on four sub-periods – each 10 years 2008). Osborn et al. (2000), drogue et al. (2006) and in length – for monthly values. daniels et al. (2013) were able to show that despite the The observed and projected climate change and its large inter-annual variability of precipitation, topography immediate consequences demand concrete strategies and plays an important role in the distribution of precipitation, adaptation measures from local authorities (IPCC 2008). even in northwestern Europe where gradients between For this reason, it is of immense importance that potential precipitation and altitude are rather small. Franke et al. Detection of potential areas of changing climatic conditions at a regional scale until 2100 for... 19 (2008) showed that a strong dependency between precipi- kLIma-daten’ Service-raklida, which is only avail- tation occurrence and altitude exists in the study region, able under www.rekis.org. This service was designed to and this leads to higher precipitation in the southern moun- provide raster-based data for climate analysis and related tains. In contrast, the northwestern part of the study region impact models. The produced raster data sets have a spa- is on average the warmest area, with the lowest amount of tial resolution of 1 km. rr; CW and TM were derived by precipitation. means of a so called residual interpolation, which is based For the study region, different station-based data sets on vertical gradient approach (VG). VG is combined with of mean temperature (TM), bias corrected precipitation an Inverse distance Weighting (IdW) to increase the (rr) and climatic water balance (CW) in daily resolution unbiasedness of the estimates. This combination means are available.
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