Comparison of the Current Field in Fram Strait Derived from ADCP Measurements and Mooring Data

Comparison of the Current Field in Fram Strait derived from ADCP Measurements and Mooring Data

Master Thesis Postgraduate Programme Environmental Physics

Axel Behrendt 30.09.2008

Supervisor: Prof. Dr. Ursula Schauer Second Referee: Prof. Dr. Monika Rhein Contents i

Contents

1 Introduction 1 1.1 Arctic Ocean Warming ...... 3 1.2 Mass Budget and Volume Fluxes ...... 4

2 Motivation and Scientiﬁc Goals 7

3 The Arctic Ocean 9 3.1 Geographical Setting ...... 9 3.2 Circulation and Hydrography ...... 11

4 Techniques and Methods 16 4.1 Moorings and Instruments ...... 16 4.2 ADCP ...... 18 4.3 Tidal Analysis ...... 19 4.3.1 Harmonic Analysis with T_TIDE ...... 21 4.3.2 The AOTIM-5 Model ...... 23

5 Results and Discussion 24 5.1 Tidal Analysis of the Mooring Data ...... 24 5.2 Comparison with Model Results ...... 30 5.3 LADCP Data and Tidal Correction ...... 32 5.4 Volume Transports ...... 34 5.4.1 Transports from LADCP Data ...... 34 5.4.2 Combined Transports from Moorings and LADCP Data ...... 36 5.5 Uncertainties ...... 38 5.6 Summary ...... 40

6 Conclusions and Outlook 41

References 46

Appendix 49 Acknowledgements

Acknowledgements

I am grateful to my supervisor Dr. Ursula Schauer for the opportunity to work in the exciting ﬁeld of physical oceanography and for the great support of my work. I wish to thank her and also Dr. Eberhard Fahrbach for making available the opportunity of participating in the Polarstern cruise ARK XXIII-2. This was a most fascinating experience! On this occasion, I thank the whole oceanography group and the crew on board Polarstern for the great time we had. I am especially thankful to Agnieszka Beszczynska-Möller and Benjamin Rabe for a lot of useful hints, papers, MatLab tools and their presence, whenever I had problems with my LADCP data. I want to thank my second referee Prof. Monika Rhein and Dr. Christian Mertens from the University Bremen for the opportunity to speak in their seminar. My thanks also to Dr. Waldemar Walczowski from the Institute of Oceanology in Sopot, who kindly provided some LADCP data for this study. Many thanks to the whole team of lecturers and the administration of the PEP program, especially to Anja Gatzka for her patience with sleepy students and all the help. Last but not least, some special words of gratitude to my parents, who consistently supported me whenever there were hard times to survive... Thank you !!! Axel Behrendt, Monday, 29. September 2008

Photo by Henri Robert (ARK XXIII-2, 2008) Acronyms

List of Acronyms

ABW Arctic Bottom Water ADCP Acoustic Doppler Current Proﬁler AO Arctic Ocean AOTIM Arctic Ocean Tidal Inverse Model ASW Arctic Surface Water AW Atlantic Water AWI Alfred Wegener Institute for Polar and Marine Research BG Beaufort Gyre CTD Conductivity, Temperature, Depth EGC East Greenland Current GSDW Greenland Sea Deep Water IBCAO International Bathymetric Chart of the Arctic Ocean IHO International Hydrographic Organization IPCC Intergovernmental Panel on Climate Change LADCP Lowered Acoustic Doppler Current Proﬁler NAC Norwegian Atlantic Current NADW North Atlantic Deep Water NAO North Atlantic Oscillation NASC Norwegian Atlantic Slope Current NSIDC National Snow and Ice Data Center RMS Root Mean Square SSH Sea Surface Height TD Transpolar Drift THC Thermohaline Circulation WBC Western Boundary Current WSC West Spitsbergen Current Chapter 1: Introduction 1

1 Introduction

After the release of the fourth IPCC Assessment Report, the Earth’s climate system attracted more interest. Not only the considerable rise in surface temperatures during the recent century but also sea level changes and the amount of globally melting ice masses are immense. Today, numerous international climate research programs are dedicated to get a better understanding of our climate system and to improve the knowledge about the human influence on climate. The Earth’s climate system is characterized by complex interactions between atmosphere, oceans, cryosphere and land surfaces including the marine and terrestrial biosphere. The oceans are a very large heat reservoir and they represent the long-term memory of our climate system. Moreover, they transport vast amounts of energy and contribute approximately as much as the atmosphere to the climatic conditions in our environment. Particularly the polar regions are increasingly recognized as being regions with considerable potential to affect global climate. On the other hand, polar regions are subject to multiple stressors and extremely vulnerable to climate change. Contrary to the Antarctic, large areas of the Arctic are covered with water and therefore receive a high amount of heat. Besides the Antarctic Peninsula, Arctic regions have been the most rapidly warming areas of the globe over the past several decades. The Arctic comprises some of the most sensitive elements of the global environment which are considered to respond rapidly to climate change. The observed melting of ice masses and the reduction of snow cover reduces the high albedo, which leads to reduced reflection of sunlight and thus to an accelerated warming effect (ice-albedo feedback). In addition, a reduced sea ice coverage may have a stronger effect on climate than mid-latitude sea surface temperature changes [Talley, 2002]. Thawing of Arctic permafrost can release enormous amounts of stored greenhouse gases, which in turn has consequences for the global greenhouse effect. Furthermore, the northern polar region is a huge habitat which includes both terrestrial and marine ecosystems and it sustains a human population of approximately 4 million residents in a harsh environment. Therefore, a rapid climate change will also affect the socio-economic system in this region. It is unequivocal that the Arctic undergoes considerable climatic changes and communities and ecosystems are already being affected. Today, there is distinct evidence of strong climatic changes. During the recent decades, the surface air temperatures in this region have warmed at approximately twice the global rate. Since a temperature minimum in the 1960s and 1970s, the averaged surface air temperatures north of 60◦N have increased by 1-2◦C[Anisimov et al., 2007]. The reduction of sea ice, glaciers, river and lake ice and a warming of permafrost throughout the Arctic is consistent with the recent increase of surface temperatures in this region. Arctic sea ice decreased drastically during the recent decades. Today it covers an area of 15 × 106 km2 at maximum extent, reducing to only 7 × 106 km2 in summer [Lemke et al., 2007]. In September 2007, Arctic sea ice retreated to the lowest level since satellite measurements began in 1979. The average sea extent for this month was 4.28 × 106 km2 [NSIDC, 2008]. Furthermore, the discharge of Eurasian rivers draining into the Arctic Ocean (AO) shows a Chapter 1: Introduction 2

significant positive trend [Peterson et al., 2002]. The AO includes areas of deep convection which represent an important driving mechanism for the thermohaline circulation (THC). The intensity of this large scale ocean overturning is crucially regulated by freshwater exported from the Arctic Ocean. The THC is an important part of the Atlantic heat conveyor, and a slow down of the circulation might have serious consequences for the climate in Europe [Hansen et al., 2004; Quadfasel, 2005; Rahmstorf, 2006]. The temperatures in the marine Arctic during the 20th century are marked by strong multi- decadal variations, and in the recent years several authors have reported on a warming of the Atlantic Water layer. Numerous modern synoptic hydrographic surveys have been made in this region and today there is evidence that the Arctic Ocean is in transition towards a warmer state [Polyakov et al., 2005]. The Gulf Stream and its northern extension, the North Atlantic Current, transport large amounts of energy and contribute to the moderate climate in Europe. The northernmost extensions of the North Atlantic Current transport Atlantic Water through Fram Strait into the North Polar region and provide the warmest water masses that enter the Arctic Ocean. The assessment of the impact of these water masses on the Arctic heat budget is one of the major tasks in the observational oceanography section of the Alfred Wegener Institute (AWI). In order to determine both the amount of heat transported northwards and the southward outflow of fresh and shallow surface waters and saline deep waters through Fram Strait, it is essential to know the transported water masses as precisely as possible. For these purposes, an intensive mooring program was established in Fram Strait from 1997 on. The AWI deployed an array of 12-16 moorings at 78.8◦N, to quantify the volume fluxes through the Fram Strait. The moorings are equipped with mechanical and acoustic current meters, measuring the velocity of the ocean currents, and additional sensors to determine salinity and temperature of the sea water. This measuring system, maintained in close cooperation with the Norwegian Polar Institute, covers Fram Strait from the eastern to the western shelf edge and is the only way to perform long-term observations throughout the year. Every year, during the recovery/deployment phase, additional temperature, salinity and velocity measurements have been made along the mooring section in Fram Strait.

Fig. 1.1: Mooring array (white circles) in Fram Strait at 78.8◦N. Chapter 1: Introduction 3

1.1 Arctic Ocean Warming

The inflow of warm Atlantic Water through Fram Strait has been known since Nansen (1902). Although its large contribution to the heat budget of the Arctic Ocean is known, it is not yet fully understood. The Arctic Ocean affects the global climate through (1) the surface heat balance, which is coupled to the stratification of water masses, and (2) the outflow from the Arctic Ocean into the major convective regions, which affects the THC [Aagaard and Carmack, 1994]. Perturbations in the upper ocean can lead to a heat release from warm intermediate Atlantic waters to the atmosphere. Larger freshwater input into the convective regions of the Nordic Seas can disturb the formation of deep water and thus the THC. A warming of the Atlantic Water layer1 in the AO was first noticed by Quad- fasel et al. [1991]. Recent observations revealed an increasing influence of warm Atlantic Water (AW) on the circulation pattern in the Arctic Ocean. The front in the halocline between At- lantic and Pacific Water has shifted from the Lomonosov Ridge to the Al- Fig. 1.2: Long-term variability of temperature of the in- pha-Mendeleyev Ridge. Grotefendt et termediate layer of the Arctic Ocean. Prolonged warm al. [1998] found a warming of the At- (red shade) and cold (blue shade) periods associated lantic layer of about 1 K compared with phases of multi-decadal variability and a back- with data from 1940-1970, and they ground warming trend are apparent from the record of 6- discussed an increased heat flux thro- year running mean normalized AW temperature anoma- ugh Fram Strait as a possible reason. lies (dashed segments represent gaps in the record) Marine warming peaks were found to [Polyakov et al., 2005]. enter the Arctic Ocean as propagating pulse-like temperature signals. These warming events are associated with a growing thickness of the Atlantic layer. Model simulations showed for the 1980-90s two periods of anomalously high temperatures in the northward flowing Atlantic Water. The first warming phase lasted from the early to the middle 1980s, followed by a cold period between 1985 and 1987. The second event was an even warmer period from 1988-1995. During the first warm period (in 1984) and during the second warm period (in 1991), high core temperatures of about 3◦C were found in the Atlantic layer north-east of Spitsbergen [Karcher et al., 2003]. Two more warming peaks were observed in 1997-98 and 2002-03 west of Norway at 63◦N [Polyakov et al., 2005]. The signals propagated northward through Fram Strait and finally reached the Laptev Sea slope after 6 - 6.5 years. The temperature increase of the first signal reached Fram Strait in 1999. The second pulse reached Fram Strait in 2004, and the AW temperatures measured east of Svalbard were 4.2◦C[Polyakov et al., 2005]. Observations suggest that this signal will soon enter the Arctic Ocean and cause further warming. Data from the mooring line in Fram Strait confirmed a significant increase in the temperatures of the northward flowing West Spitsbergen Current (WSC) in the decade from 1997 to 2006 (→ Fig. 1.3). The warming was about 1 K and associated with a record maximum in salinity. The increase was overlaid by seasonal variations of about 0.5 K amplitude [Schauer et al., 2008]. Although the observed temperatures were lowest in winter, the northward heat transport was

1layer between 200 and 900m depth (see chapt. 3) Chapter 1: Introduction 4

highest due to the winter maximum of the volume transport.

Fig. 1.3: Time series of the cross-section averaged temperature of Atlantic Water derived from mooring data (Fram Strait). The black line denotes the temperature of northward flowing water that was warmer than 1◦C. The grey line denotes the temperature of southward flowing Atlantic Water. Symbols at the thin lines denote monthly mean values, bold lines are 12-months running means [Schauer et al., 2008]. The temperature of the northward flowing Atlantic Water depends on atmospheric pressure systems and the index of the North Atlantic Oscillation (NAO), which is the standardized winter sea level pressure difference between the Azores High and the Icelandic Low. In the positive mode of the NAO, these pressure systems are strong and cause vigorous winds over the eastern North Atlantic [Mysak, 2001]. This leads to stronger advection of heat into the Nordic Seas and allows warmer Atlantic Water to intrude into the AO [Karcher et al., 2003]. In the 1980-90s, such a positive NAO index drove warm water from the North Atlantic into the Norwegian Sea and subsequently into the Arctic Ocean. Positive NAO states cause stronger boundary currents in the Atlantic Water layer, which leads to an intensified spreading of the warm signals. Also the Bering Strait contributes to the warming of the Arctic Ocean. Although the volume transport is small, Bering Strait heat transports are about 1/5th of the Fram Strait heat transports. The heat transport increased from 3.17 TW to 9.51 TW in the period from 2001- 2004 and is partly responsible for the sea-ice retreat in this region [Woodgate et al., 2006].

1.2 Mass Budget and Volume Fluxes

A prerequisite for calculating heat balances of the Arctic Ocean is the establishment of a thorough mass balance. This can be achieved by relating the total inflow to the total outflow. In the past, the available amount of volume flux data was not sufficient to obtain accurate results for total volume fluxes into and out of the AO. The attempts of determining volume transports in the WSC region were mainly based on geostrophy (dynamic method). The results ranged from 3.2 Sv [Kislyakov, 1960] to 3.7 Sv [Timofeyev, 1962] (1 Sv = 1 · 106 m3 s−1) northward transport and largely underestimated the true transports, as the WSC is known for having large barotropic components [Fahrbach et al., 2001]. In 1971 and 1983, first mooring measurements were made at 79◦N. The resulting values were 7.1 Sv (2 moorings) [Greisman, 1976] and 5.6 Sv (8 moorings) [Hanzlick, 1983] northward transport. Today, the coverage with mooring data, LADCP (Lowered Acoustic Doppler Current Profiler) data and hydrographic sections is much higher and extrapolations can be avoided. However, Chapter 1: Introduction 5

the calculation of a consistent heat and mass balance has not yet been accomplished. Recently, a mass budget of the Arctic Ocean has been developed by Rudels et al. [2008] (→ Fig. 1.4). The transports for Fram Strait have been calculated applying the dynamic method on data from sixteen hydrographic sections taken between 1980 and 2005, and following several special approaches for the calculation of heat and freshwater transports.

Fig. 1.4: Mass budget of the Arctic Ocean. The numbers are taken from Rudels et al. [2008]. The Fram Strait net outflow has been calculated to 2.8 Sv using geostrophy [Rudels et al., 2008]. Since the WSC is strongly barotropic, the use of geostrophy underestimates the inflow through Fram Strait. To take the barotropic part into account, 1.1 Sv is added to the Fram Strait inflow. This results in a net outflow of 1.7 Sv. The transports through the other three passages into the AO were taken from recently published studies. The fluxes through Bering Strait range around 0.8 Sv with a maximum of 1.2 Sv in summer and a minimum of 0.4 Sv in winter [Woodgate et al., 2006]. The mean transport of Atlantic Water into the Barents Sea amounts to 1.5 Sv [Ingvaldsen et al., 2004]. Together with the contribution from the Norwegian Coastal Current (0.7 Sv), this results in an Barents Sea inflow of 2.2 Sv. The freshwater inputs from river runoff and net precipitation sum up to 0.17 Sv [Dickson et al., 2007]. The outflow through the Canadian Archipelago is 1.44 Sv [Dickson et al., 2007] which is very close to the often cited value of 1.5 Sv. Since 1997, the volume transports through Fram Strait have been estimated based on mooring data. Fahrbach et al. [2006] report mean values of 11.6 Sv northward and 13.5 Sv southward transport for the period of mooring observations from 1997 to 2005 (→ Fig. 1.5). The net outflow of 1.9 Sv through the Fram Strait at 79◦N is very close to the value by Rudels et al. [2008]. On short time scales, eddies and wind induced barotropic flows in Fram Strait lead to a considerable spatial and temporal variability, even within days.

The importance of a balanced mass budget can be demonstrated with a simple calculation. The central basins of the Arctic Ocean together with the shelf seas cover an area of 9.5×106 km2. Chapter 1: Introduction 6

Considering a period of 1 month with an imbalance of +1 Sv, the sea level in this area would rise by approximately 25 cm. The sea level of the Arctic Ocean has been recorded by about 60 tide-gauge stations since the 1950s. These data combined with barotropic ice-ocean models, baroclinic models and wind stress data yield a trend of 0.04-0.15 cm/year between 1954-1989. As it is highly correlated with the Arctic Oscillation, most of this trend could be attributed to changes of atmospheric forcing [Mysak, 2001; Proshutinsky et al., 2001]. The values were later adjusted to 0.191 cm/year [Richter-Menge et al., 2006].

Fig. 1.5: Monthly means of the volume transport through the whole Fram Strait section (green bars - net transport, red bars - northward transport and blue bars - southward transport) in 1997-2005 [Fahrbach et al., 2006]. Thus, a sea surface increase of several cm per month is not observed. Therefore, further observations and more precise measurements are needed to obtain a consistent mass balance of the Arctic Ocean. Because of its depth and its in- and outflow characteristics, Fram Strait will play a key role in adjusting these volume fluxes in order to balance the total mass budget. Chapter 2: Motivation and Scientific Goals 7

2 Motivation and Scientiﬁc Goals

Regarding the ongoing research activities on Arctic Ocean warming, the estimation of the contribution of Atlantic Water to the overall heat budget of the AO remains one important task. Since the Fram Strait is the only deep water passage to the central AO, it enables throughﬂow of large masses of warm water. Therefore, the transports of the WSC determine to a large extent the input of heat into the the Arctic Ocean.

Fig. 2.1: Location of Fram Strait and circulation scheme of Atlantic Water in the Nordic Seas. The figure demonstrates the complicated flow structure of the West Spitsbergen Current. NAC: Norwegian Atlantic Current, NASC: Norwegian Atlantic Slope Current, WSC: West Spitsbergen Current, EGC: East Greenland Current. In order to assess the contribution of the WSC water masses to the total heat budget, reliable estimates of its volume transports are required. As the WSC represents a complex and highly variable current system (→ Fig. 2.1), data with high resolution are needed. The mooring program in Fram Strait allows to survey the WSC with a high resolution throughout the year. The measurements yield long velocity time series with a temporal resolution of two hours. This Chapter 2: Motivation and Scientific Goals 8

also enables the investigation of the high temporal variability in this region. But the mooring positions shown in figure 2.2 indicate that the complex flow structure of the WSC cannot be completely resolved due to the large spacings between the single moorings. This results in an under-sampling of the structures and thus in a significant aliasing. The deployment and recovery of the moorings as well as the current meters and instruments itself are very costly. Therefore, the number of moorings cannot simply be increased to more than 16.

Fig. 2.2: Velocity ﬁeld in the WSC region at 200m depth from ship-borne LADCP measurements in August 2006. The mooring positions are shown as white circles.

Since LADCP measurements have been carried out with a higher spatial resolution compared to the moorings, LADCP data can be used to fill the gaps between the moorings with additional information. However, one problem is the short-term fluctuation in the velocities. One LADCP section across Fram Strait usually takes about one week, i.e. the gained velocity data are not synoptic and are therefore aliased by tides and meso-scale features like eddies. For this reason, the tidal signal has to be removed from the LADCP data. This is usually done by applying tidal models. As the available mooring time series are sufficiently long, they can be used to derive the real tidal signal by applying the MatLab toolbox T_TIDE. Therefore, before detiding the LADCP data, the first step in this thesis is the comparison of a barotropic tidal model (AOTIM-5) with the tidal information gained from mooring data. The final task is the validation of previously estimated volume transports through Fram Strait by combining velocity data from the moored current meters and LADCP data. The procedure of this Master Thesis is as follows:

• Comparison of tidal velocities of the AOTIM-5 model and mooring data

• Elimination of the tidal signal from LADCP data

• Calculation of volume transports by combining corrected LADCP data and mooring data

• Comparison of the results with existing transport estimates and results from geostrophic calculations Chapter 3: The Arctic Ocean 9

3 The Arctic Ocean

3.1 Geographical Setting

Fig. 3.1: Ac- cording to the defini- tion of the Interna- tional Hydrographic Organization (IHO), the Arctic Ocean (lighter shaded area) covers an area of 15.5 million km2 and its mean depth is 1201 meters [Jakob- sson, 2002]. How- ever, some parts are more than 5.000 meters deep. Shal- low shelf seas with a depth of only several hundred meters constitute one third of its total area. Large areas of the Arctic Ocean are still per- manently covered by multi-year sea ice. The sea floor of the deeper part shows a complex topography which is divided by several ridges and has considerable influence on the circulation of water masses. The 1.700 km long Lomonosov Ridge reaches up to 950 m below the sea surface and divides the deep sea into the Canadian Basin and the Eurasian Basin. The only four connections of the central Arctic Ocean to the world ocean are: The Fram Strait, The Barents Sea, The Bering Strait and The Canadian Archipelago. The dashed line in the figure marks the Arctic Circle at 66◦33’ N. The geographical North Pole is marked by a white dot.

The Arctic Ocean (sometimes also referred to as Arctic Mediterranean) is the ﬁfth and northernmost of the Earth’s oceans. It is situated largely in the North Polar region and is surrounded by the land masses of Eurasia, North America, Greenland and several islands. The total length Chapter 3: The Arctic Ocean 10

of its coastlines amounts to approximately 45.400 kilometers. The Arctic Ocean is the shallow- est of the Earth’s oceans as it includes several shallow seas, e.g. Barents Sea or Laptev Sea, which are located on the continental shelf of Eurasia. The seven largest rivers draining into the Arctic Ocean are: Pechora and Severnaya Dvina (Barents Sea), Ob and Yenisey (Kara Sea), Lena (Laptev Sea), Kolyma (East-Siberian Sea) and in North America the Mackenzie River (Beaufort Sea). The six Eurasian rivers drain about two-thirds of the Eurasian Arctic landmass and include three of the largest rivers on Earth [Peterson et al., 2002]. The topography of the deep sea ﬂoor is characterized by steep ridges, ocean deeps, sills and several deep basins. The Amundsen Basin is part of the Eurasian Basin and by depths of 4.300 m - 4.500 m the deepest of the basins. It borders on the Eurasian side of the Lomonosov Ridge. This gigantic ridge forms a submarine bridge between the north-western part of Greenland and Siberia. The Molloy-Deep (5.608 m), 140 km west of Spitsbergen, is the deepest depression of the entire Arctic Ocean. The Nordic Seas between Greenland and Norway include the Greenland Sea, Iceland Sea and Norwegian Sea. They represent the transition between Arctic Mediterranean Sea and the At- lantic Ocean and comprise large areas of deep convection. There are four connections between the Arctic Mediterranean and the world ocean (→ Fig. 3.1):

The Barents Sea (average depths: 100 - 300 m) is a pure shelf sea that reaches a width of more than 1500 km at 40◦E[Cisewski, 2000]. It is characterized by inﬂow of warm, saline Atlantic Water which loses much of its heat to the atmosphere. The Barents Sea is diﬀerent from other Arctic shelf seas, as it has close connections to the Norwegian Sea as well as the central Arctic Ocean.

The Fram Strait, named after a ship used in polar expeditions by the Norwegian ex- plorers Nansen, Sverdrup and Amundsen, plays a key role in the exchange of water masses between the Atlantic and the Arc- tic. Its sill depth is approximately 2600 m. Via Fram Strait the Nordic Seas commu- nicate with the Arctic Mediterranean and it constitutes the only deep connection to the deep basins of the Arctic Ocean. Warm and saline Atlantic waters flow northwards through the eastern part of the 440 km wide opening. In the western part, ice and Fig. 3.2: Sea floor morphology of Fram Strait. freshwater is exported southwards. The in- Shortest distances between Svalbard’s and Green- flow of Atlantic water through the Fram land’s 250 m isobaths, and coastlines, are shown. Strait is the warmest water that enters the G-S: Greenland-Spitsbergen sill, MD: Molloy Deep Arctic Ocean. [Adapted from (1)].

The Bering Strait (85 km wide and 50 m deep) is the gateway to the Pacific. The flow through this passage is barotropic and directed northwards, from the Bering Sea to the Chukchi Sea. The surface waters from the Pacific have very low salinity and leave the Arctic Mediterranean mostly through the Canadian Archipelago. This water is also clearly recognizable in the outflow through Fram Strait. Chapter 3: The Arctic Ocean 11

The Canadian Archipelago (sill depth: 230m) includes the Northwest Passage as well as several other channels and islands, forming the connection between central Arctic Ocean and the Labrador Sea. Arctic Water ﬂows through the shallow Archipelago to the Baﬃn Bay and from there into the North-Atlantic. Its main source is water from the Bering Strait but also high salinity water from the Barents Sea can be recognized.

Today, the Arctic Ocean is at the center of an ongoing dispute between the adjacent countries. It is considered signiﬁcant because it is expected to contain as much as or more than a quarter of the world’s oil and gas recources. It remains hard to predict how the Arctic Ocean will react on the growing human inﬂuence.

3.2 Circulation and Hydrography

The circulation in Earth’s ocean basins is forced by (1) the winds, through a thin frictional layer (Ekman layer) and through the response of the ocean interior to mass convergences and divergences in this layer, and (2) by heating and cooling and processes that change the amount of freshwater and hence salinity. The first type of circulation is called wind driven and the second is called thermohaline circulation [Talley, 2002]. The circulation in the major ocean basins is dominated by wind forcing. As the Arctic Ocean is a mediterranean sea, its topography and the confinement by land limits the communication with other ocean basins. The circulation in the Arctic Ocean is dominated by thermohaline forcing and wind stress plays a smaller role. Another reason for the limited wind forcing is the large sea ice cover. As a surface circulation, the large subtropical gyre in the North Atlantic is driven by westerly winds on the higher latitude side and easterly trade winds in lower latitudes. The Gulf Stream, the strong West- ern Boundary Current (WBC) in the North Atlantic, is part of the gyre but extends to greater depths. North-east of Cape Hat- teras it turns east, leaves the North Ameri- can coast and starts meandering. The Gulf Fig. 3.3: Main ocean currents in the North Atlantic Stream transports a tremendous volume of and Arctic Ocean. Warm temperatures are indi- warm water towards the North Atlantic cated in red, colder temperatures in blue (2). and provides a northward meridional heat flux in the Atlantic at all latitudes with a maximum of about 1015W. In the vicinity of the Grand Banks of Newfoundland it encounters the cold waters of the Labrador Current. Beyond the Grand Banks it gradually widenes and becomes a slow moving current known as the North Atlantic Current. In the eastern part of the North Atlantic, this current divides into two parts. The southern part flows towards the east and closes the loop of the subtropical gyre. The Chapter 3: The Arctic Ocean 12

northern part decreases speed and continues toward the Nordic Seas. South of Iceland it splits to form the Irminger Current which curves towards the north-west to join the southward flowing, cold East Greenland Current (EGC). The EGC represents a part of the Western Boundary Current of North Atlantic’s subpolar gyre. The second branch crosses the Faroe-Shetland sill, continues in north-easterly direction along the coast of Norway and becomes the Norwegian Atlantic Current (NAC). These warm waters transfer their heat to the atmosphere resulting in a comparably warm climate in north-western Europe. The warmer, more saline eastern branch of the Norwegian Atlantic Current is named Norwegian Atlantic Slope Current (NASC) and flows with speeds up to 117cm/s [Orvik et al., 2000]. The NASC bifurcates after passing the Lofoten Islands (→ Fig. 2.1). From this point on, the warm and saline Altantic Water takes two different ways to enter the central Arctic Mediterranean. Part of the NASC turns east and enters the Barents Sea as the North Cape Current, the other part continues northwards, merges with the western branch of the NAC and flows through Fram Strait as the WSC. West of Svalbard (Spitsbergen), a large part of the WSC recirculates between 78◦ and 80◦N in south-west direction and joins the EGC. The WSC itself splits and one branch crosses the Yermak Plateau directly north of Svalbard, whereas the other branch follows the northwestern slope of the plateau. The main input of water into the Arctic occurs through the Fram Strait and the Barents Sea. Contrary to the Barents Sea, Fram Strait is deep enough to enable throughflow of Atlantic Wa- ter at intermediate depths. The two main flows lose heat to the atmosphere and the Barents Sea branch undergoes further conversions such as cooling, freezing/melting and freshening by river runoff, whereas the Fram Strait branch is preserved at intermediate levels. Formation of sea ice further increases the salinity of the water column. Both flows rejoin in the northern Kara Sea, subduct below the cold and fresh Arctic surface waters and continue in cyclonic boundary currents along the Arctic basin margins (→ Fig. 3.4). This intermediate layer of warm Atlantic Water is covered by a fresh surface layer formed by runoff and cooled Pacific Water from Bering Strait. This effect decouples the Atlantic layer from the atmosphere and helps maintaining a permanent ice cover. Through the Bering Strait, a barotropic flow of low salinity Pacific Water enters the Arctic Mediterranean. Although the Bering Strait inflow is comparably low, its nutrient rich low salinity water provides about one third of the Arctic freshwater and ventilates and strat- ifies the upper Arctic Ocean [Woodgate et al., 2006]. The Pacific Water flows into the Chukchi Sea and continues westward, following the North American coast- Fig. 3.4: Pacific inflow and circula- line as the Alaskan Coastal Current. It leaves the Arc- tion of Atlantic Water in the Arctic Ocean. Blue arrows: Intermediate At- tic Mediterranean through the various channels of the lantic layer, Green arrows: Pacific Wa- Canadian Archipelago and enters Hudson Bay, Baffin ter, Red arrows: Atlantic inflow Bay and the Labrador Sea. The largest freshwater storage of the Arctic Ocean is located in the Beaufort Gyre (BG), iden- tified by a salinity minimum at 5-400 m [Proshutinsky et al., 2002]. The BG occurs as a result of the clockwise wind patterns that typically form above the Beaufort Sea. This circulation results from an average high-pressure system. However, strong currents are inhibited by sea Chapter 3: The Arctic Ocean 13

ice. The gyre makes one complete rotation about every four years, turning the polar ice cap along with it. Occasionally, the gyre reverses direction when storms and low pressure systems move across the Beaufort Sea [NSIDC ]. The BG was found to contribute to the Arctic climate variability.

Fig. 3.5: Upper panel: Surface circulation in the Arctic Ocean (red color: warm Atlantic Water, PI: Pacific Inflow, BG: Beaufort Gyre, TD: Transpolar Drift, WSC: West Spitsbergen Current, AI: Atlantic Inflow , EGC: East Greenland Current, GG: Greenland Gyre). Middle panel: Section from A to B. Stratification of water masses and areas of deep convection. Lower panel: Deep convection and mixing in the Greenland Gyre [Adapted from (3)]. Another predominant current is the so called Transpolar Drift. This wind driven stream carries ice masses and freshwater from the Siberian rivers across the North Pole towards the western Fram Strait. Here it joins the EGC, which is deflected by Coriolis Force and remains close to the coastline of Greenland. When considered over a long period of time, both the Beaufort Gyre and the Transpolar Drift transport most of the polar sea ice. Chapter 3: The Arctic Ocean 14

By far, the greatest volume of water leaves the Arctic Mediterranean as the EGC. It is com- posed of fresh and shallow Arctic surface waters and an outflow of dense, saline deep waters. Before the deep EGC outflow crosses, to some extent, the Greenland-Scotland Ridge through the Denmark Strait (→ Fig. 3.6), it also affects the water mass modifications in the Nordic Seas. This region plays a major role in driving the global THC of the world ocean and therefore represents a focal point for the global climate. The Arctic Mediterranean transforms Atlantic Water into high density intermediate and deep waters, which are exported through Fram Strait and eventually cross the Greenland-Scotland Ridge to supply the North Atlantic Deep Water (NADW) [Meincke et al., 1997]. Since around 1960, large parts of the open sea areas north of the Greenland-Scotland Ridge have freshened, and so have the deep overflows. But also the strength of the overflows is weakening. The Faroe Bank Channel overflow was found to have decreased by about 20% from 1950 to 2000 [Hansen et al., 2004; Quadfasel, 2005]. These trends can contribute to a future weakening of the THC in the Atlantic and give rise to scientific discussions about the impact of the THC on global climate. The deep water in the Arctic Ocean, the Arctic Bottom Water (ABW), has two sources. One source is found on the Arctic shelf regions. The shelf water is diluted by river input and has low salinity. Losing heat to the atmosphere, this water forms ice and rejects salt to the layers below. When the water is about -1.8◦C cold and salinity exceeds values of 35, it is dense enough to sink down to the bottoms of the deep basins.

Fig. 3.6: Formation of deep water and movement of water masses in the North Atlantic and Arctic Ocean. The NADW is an important water mass for the meridional overturning cell in the Atlantic Ocean and therefore crucial for maintaining the global THC.

The second source for ABW is the Greenland Sea Deep Water (GSDW). In the northern Green- land Sea, the Polar Front, associated with the southward flowing EGC, and the Arctic Front, associated with the northward flowing WSC, form a large eddy, the so called Greenland Gyre (→ Fig. 3.5). Intense vertical convection occurs only during winter in the center of this cyclonic circulation. This region is characterized by weak stratification and its deep water, the GSDW, belongs to the coldest (about -1.1◦C) and densest in the entire Arctic Ocean. Part of the GSDW enters the southern Norwegian Sea, mixes with Norwegian Sea Deep Water, and recirculates Chapter 3: The Arctic Ocean 15

into the deep basins of the Arctic Sea [Tomczak and Godfrey, 2001]. Another predominant gyre in the Nordic Seas is the Iceland Gyre which is centered at about 68◦N and 10◦W. It has about half the size of the Greenland Gyre and reaches less deep. In the Iceland Sea, intermediate waters are renewed by ventilation [Karstensen et al., 2005]. The contribution from the Arctic shelves is evident from a salinity maximum in the EGC at 1500m. This water together with the GSDW and outflowing intermediate waters form the Greenland-Scotland Ridge overflow. Together the Labrador Sea Water and this NADW overflow form the deep western boundary current in the North Atlantic. Arctic Bottom Water fills all deep basins of the Arctic Mediterranean and in most parts it has potential temperatures between -0.8◦C and -0.9◦C[Tomczak and Godfrey, 2001]. But the bottom water in the Canadian Basin is not colder than -0.4 to -0.5◦C, as the Lomonosov Ridge prevents colder waters from exchanging between the main basins [Tomczak and Godfrey, 2001]. This lack of movement in the deep waters causes a stagnant pool of very cold water at the bottom of the Arctic Mediterranean. Above the ABW and the deep water layers, the intermediate layer of warm, saline Atlantic Water is situated in depths ranging from 200 - 900 m. This layer is warmer than the deep water (in the WSC 1-4◦C) and also warmer than the fresh Arctic surface layer. The temperature maximum of the Atlantic Water can be traced from Svalbard at 150 m up to the Canadian Basin at 500m. At the shelf slope, Atlantic Water is mixed with the dense shelf waters and contributes to the formation of warm and saline deep water. The Arctic Surface Water (ASW) ranges from the surface down to 50m and is partly formed by river runoff and meltwater. ASW has temperatures close to the freezing point (-1.5◦C to -1.9◦C) with almost no variation over depth. Although the temperatures are nearly constant over depth, salinity shows a gradient between 50-200 m. This "cold halocline" is formed by Atlantic Water which gets diluted by meltwater and gradually cools. North of the Laptev Sea, it is covered by a fresh layer of runoff from Siberian rivers and in the Canadian Basin additionally by cooled Pacific Wa- ter from Bering Strait. The resulting salinity gradient forms an extremely stable stratification, which inhibits convection. Thus, the cold halocline forms a protective heat shield against the Atlantic layer below and helps maintaining a permanent ice cover. There are differences in the stratification of the upper layer between the Eurasian and Canadian basin. The weak temperature gradient in the halocline is larger in the Eurasian basin, which results in a weaker density stratification [Aagaard and Carmack, 1994]. Fig. 3.7: Stratification of water masses in the Arctic Ocean. Chapter 4: Techniques and Methods 16

4 Techniques and Methods

This chapter provides an overview of the diﬀerent measurement techniques used to obtain the data, which are processed for the studies in this thesis. Furthermore, several calculation methods and data processing tools are introduced. Since velocity data are used to calculate volume transports for this thesis, the descriptions are mainly focused on those instruments and methods that determine the speed of ocean currents.

4.1 Moorings and Instruments

Moorings are the only available tool to perform observations at a fixed place in the ocean. Basically, a mooring consists of a Kevlar rope, which can be up to several thousand meters long. An anchor (about 1t weight) holds the mooring on the sea floor. To keep the rope nearly vertically in the water column, plastic covered evacuated glass spheres are attached to the rope. These robust "buoyant floats" also force the mooring back to the sea surface after the rope is released from the bottom weight. The rope can be released by a sound signal which is sent from a ship. A mechanical actuator, mounted directly above the bottom weight, receives the signal and separates the rope from the weight. The upper floats are placed several tens of meters below the sea surface to avoid the influence of the moving sea surface on the measurements, and to avoid damage by passing ships or drifting icebergs. Moor- ings may be equipped with various oceanographic measuring and sampling instruments, which are mounted on the rope at certain distances (→ Fig. 4.1). Frequently used instruments are: Bottom pressure recorders, combined conductivity-temperature-pressure recorders, upward looking ADCPs and current meters. Mechanical current meters (like the RCM 7 from Aandreaa Instru- ments) are widely used devices to measure the velocity of water flows at certain depths. The speed of the current is detected by measuring the rotation speed of a paddle wheel which is accelerated Fig. 4.1: Mooring ar- by the water flow. Counting the number of revolutions of the rotor rangement. during a certain interval of time yields the mean velocity of the water flow in this interval. The current meter is equipped with a rod that can be shackled into the mooring line. Chapter 4: Techniques and Methods 17

A vane assembly allows the instrument to swing freely and to align with the flowing water. The recording unit contains the measuring system, a battery, a data storage unit and optional salinity, temperature or pressure sensors. A built-in clock triggers the instrument at preset intervals [Aanderaa, 2000]. Other current meters (e.g. RCM 9) send lateral sound pulses and determine the current speed by the Doppler shift in the frequency of the reflected sound signal. Current meters are able to determine the current direction with an internal magnetic compass. Temperature of sea water is mostly measured with thermistors. A thermistor is a semiconductor having resistance that varies rapidly with temperature. These thermometers have very high accuracy and are also used on moored instruments. Since the salinity of most of the ocean’s water ranges from 34.60 to 34.80 parts per thousand (200ppm), measurements with high resolution are needed. To- day, salinity is determined through the conductivity of sea water. A change in salinity has a mea- Fig. 4.2: Rotor current meter (left) and sureable influence on the conductivity of water. It Doppler current meter (right). 1: paddle is measured between two platin electrodes in a non- wheel, 2: additional sensors, 3: recording conducting borosilicate glass tube [Stewart, 2006]. unit, 4: vane assembly, 5: connection to Pressure, and therefore depth, is often measured mooring rope, 6: Doppler current sensor, with pressure transducers. These instruments con- 7: sound pulse. tain a diaphragm that is deformed by the pressure, which can be measured by a strain gage element (accuracy about ±1%). Very precise measurements can be made with quartz crystals. The natural frequency of these crystals depends on pressure, which can be measured with an accuracy of ±0.015% [Stewart, 2006]. The temperature, salinity and pressure values are used to calculate density. The distribution of density inside the ocean is directly related to the distribution of horizontal pressure gradients and thus to ocean currents.

Table I: Moored Intruments in Fram Strait

Instrument Type Accuracy

Aanderaa RCM 7 Rotor Current Meter ±1 cm/s

Aanderaa RCM 8 Rotor Current Meter ±1 cm/s

Aanderaa RCM 9 Doppler Current Meter ±0.15 cm/s

Aanderaa RCM 11 Doppler Current Meter ±0.15 cm/s

FSI 3-dim ACM Doppler Current Meter ±0.5 cm/s Chapter 4: Techniques and Methods 18

4.2 ADCP

Today, the measurement of ocean currents by ADCPs (Acoustic Doppler Current Proﬁlers) is a widely used operational tool to study the dynamics of the ocean. The method is based on the Doppler Eﬀect which alters the pitch of ultrasonic sound pulses that are transmitted by the instrument.

Fig. 4.3: Working principle of ADCP.

The ADCP instrument sends ultrasonic sound pulses which are backscattered by moving parti- cles (mainly phytoplankton) in the sea-water. The phytoplankton, which has nearly the same size as the ultrasonic wavelength (for 300 kHz: 5mm), scatters the sound waves back to the instrument. Within the short period of the sound pulse phytoplankton does not perform any measurable movements relative to the water, i.e. the basic assumption is, that the transported scatterers directly display the velocity of the ocean current. The backscattered pulse is received by the ADCP transducer where the signal is processed. The velocity of the flowing water can be calculated from the frequency shift of the received signal. An ADCP can be mounted under a ship’s body, into a mooring or it can be lowered into deeper water layers by a wire. The vessel-mounted ADCP can measure ocean currents down to 300 m whereas the lowered ADCP (LADCP) enables the measurement of complete velocity profiles down to several thousand meters. The ADCP principle is shown in figure 4.3, where ¡f is the Doppler shift in frequency, f the frequency when everything is at rest, v the velocity of the scatterers, c the speed of the sound 1500 m ¢ signal (≈ s in water) and the angle between v and the backscattered acoustic beam. Under the assumption that Chapter 4: Techniques and Methods 19

v 1, (1) c

the received Doppler shift for the shown geometry is given by

v ¡f = 2f cos(¢). (2) c

The 2 in this equation indicates, that the Doppler shift occurs twice. The ﬁrst time, when the sound pulse is emitted by the ADCP transducers and received by the scatterers, and the second time, when the sound pulse is backscattered and received by the transducers of the ADCP [RDI, 1996]. An ADCP is equipped with four transducers. Three beams are required to compute the three dimensional velocities, the fourth one is used to evaluate the data quality. Since the ADCP/LADCP carries out motions due to ship movement, some correction has to be applied. The ADCP contains a ﬂux-gate compass to determine the heading and inclinometers to determine pitch and roll of the device. They allow to transform the velocity data from beam coordinates, which follow the direction of the acoustic beam, into earth coordinates, i.e. north-, east- and upward velocity components [Walter and Huhn, 2008]. There are two approaches of processing measured LADCP data, the shear solution and the inverse solution. Both are described in detail in Visbeck [2001].

Fig. 4.4: Vessel- mounted ADCP

4.3 Tidal Analysis

Tides are the manifestation of strong gravitational forcing at precisely repeating periods. They can create currents with speeds up to several m/s and they contribute to ventilation processes in the Arctic Ocean [Holloway and Proshutinsky, 2007]. Baroclinic, or internal tides, play a role in mixing in the deep ocean and in shallow seas. In a stratified ocean, when the vertically uniform horizontal velocities of barotropic tides interact with rough topography, disturbing isotherms and isopycnals, they generate baroclinic tides, for which the velocities are not vertically uniform [Robertson and Ffield, 2005]. The semidiurnal periodic rise and fall of the sea surface caused by the Moon is not the only response of the ocean on tidal forcing. There are many other tide generating forcings with different frequencies, resulting in a rather complicated hydrodynamic response of the ocean. Thus, tidal theory is a vast field and there are several books dealing only with tides and tidal modelling. Chapter 4: Techniques and Methods 20

Sun and Moon are the two celestial bodies which cause the tides on Earth. The driving force is the gradient of the gravity field of the Moon and Sun. The strong semidiurnal lunar tide (M2) on Earth is produced by the gravitational attraction of water masses by the Moon, and on the opposite side by the centripetal acceleration at Earth’s surface, as the Earth and Moon circle around a common center of mass [Stewart, 2006]. The same principle is valid for Earth and Sun. Other tidal components result from different periodically changing orbital parameters (e.g. rotating elliptical orbits or changes in eccentricity or declination) and the orientation of the Earth axis relative to the orbital planes. The superposition of these frequencies produces a very complicated periodic signal containing a large number of different tidal signals which arise from planetary motions.

Fig. 4.5: The horizontal component of the tidal force is directed toward a point right under the Moon (left) and the image on the opposite side of the Earth (right). Here the Moon stands over North Africa and the image is located north of New Zealand in the Pacifc Ocean. The same force ﬁeld will appear if the Moon is located above the image point. As the Earth rotates, the ﬁeld will move westward [Gjevik, 2006].

For a spinning Earth, the tidal potential on a certain spot can be separated into three diﬀerent groups having semidiurnal, diurnal and long periods. Doodson (1922) selected six fundamental frequencies to express any tidal constituent as a combination of these frequencies:

f = n1f1 + n2f2 + n3f3 + n4f4 + n5f5 + n6f6 (3)

f1: Local mean lunar time (period: 1 lunar day), f2: Moon’s mean longitude (period: 1 month), f3: Sun’s mean longitude (period: 1 year), f4: Longitude of Moon’s perigee (period: 8.847 yrs), f5: Longitude of Moon’s ascending node (period: 18.613 yrs), f6: Longitude of Sun’s perigee (period: 20940 yrs)

The integers ni are named Doodson numbers. Although this method yields up to 399 diﬀerent tidal constituents, only a few of them are considered in a tidal analysis. A list of the strongest constituents is given in Table II. Chapter 4: Techniques and Methods 21

Table II: List of major tidal harmonic constituents

Tidal Species Symbol Period Frequency Frequency [h] [10−4rad/s] [◦/h]

Semidiurnal: Principal lunar M2 12.42 1.40519 28.99 Principal solar S2 12.00 1.45444 30.00 Lunar elliptic N2 12.66 1.37880 28.44 Lunisolar K2 11.97 1.45842 30.08 Diurnal: Lunisolar K1 23.93 0.72933 15.04 Principal lunar O1 25.82 0.67594 13.94 Principal solar P1 24.07 0.72508 14.96 Elliptic lunar Q1 26.87 0.64953 13.40 Long Period: Fortnightly Mf 327.85 0.05323 1.098 Monthly Mm 661.31 0.02639 0.544 Semiannual Ssa 4383.05 0.00398 0.082

Separation of tidal and non-tidal energy is often the ﬁrst task in the analysis of oceanic time series. In classical harmonic analysis the tidal signal is modelled as the sum of a ﬁnite set of sinusoids.

4.3.1 Harmonic Analysis with T_TIDE To analyze the tidal signal of the time series from the moored current meters, the MATLAB toolbox T_TIDE is used. The programm performs classical harmonic analysis for periods of about one year or shorter, accounts for (some) unresolved constituents and computes conﬁdence intervals for the analyzed components. Using Doodson’s development, the tidal potential can be written in the form

2 " # = X ( ) X 0 (2 ) + 0 ( ) X 0 (2 ) V Gn1 ϕ An1,...,n6 cos πVa Gn1 ϕ Bn1,...,n6 sin πVa , (4) n1=0 n2,...,n6 n2,...,n6

where ni are the Doodson numbers. Sets with a common n1 are called a species (slow, diurnal = 0 1 2 ( ) 0 ( ) and semidiurnal species for n1 , and , respectively). Gn1 ϕ and Gn1 ϕ are called geodetic functions and vary with latitude (ϕ) and species, and they depend on other constants like the radius of the Earth and the masses of Earth, Moon and Sun. For a given Doodson number 0 0 set either the amplitude A or B is nonzero, but not both [Pawlowicz et al., 2002]. Va is an astronomical argument and is equal to equation (3). The frequency of any tidal constituent is deﬁned as dV σ = 2π a . (5) k dt Chapter 4: Techniques and Methods 22

T_TIDE models the tidal response x(t) as a set of spectral lines either in a complex approach

X iσkt −iσkt x(t) = bo + b1(t) + ake + a−ke , (6) k=1,...,N

or in a real approach

X x(t) = bo + b1(t) + Ak cos(σkt) + Bk sin(σkt). (7) k=1,...,N

t: time, N: number of tidal constituents, σk : constituent frequency, bo: oﬀset, b1(t): linear drift, ak, a−k :

complex amplitudes, Ak, Bk : real amplitudes

The modelled tidal response is ﬁtted to the recorded time series y(t) of measured velocities by minimizing the cost function

X 2 E = |x(tm) − y(tm)| . (8) k

After the least squares fit is performed, the program applies different corrections and calculates confidence intervals for each tidal constituent. The calculation is based on estimations of spectral density. Confidence intervals are a useful tool in order to assess to which degree the fitted constituent represents a tidal process and is not the result of a non-tidal broadband variability process. Tidal currents are often described using a tidal ellipse, which is traced by the tip of the current vector during one complete cycle. T_TIDE calculates ellipse parameters from the complex amplitudes ak and a−k:

L = |ak| + |a−k| , (9)

l = |ak| − |a−k| , (10)

( ) + ( ) ¢ = ang ak ang a−k 180 2 mod , (11) Fig. 4.6: Velocity vector (blue) tracing

g = v − ang(ak) + ¢, (12) out a tidal ellipse.

where L is the semi-major axis, l the semi-minor axis, ¢ the inclination of the northern semi- major axis counter-clockwise from east, v the equilibrium phase and g the Greenwich phase. The Greenwich phase (or phase lag) is the phase of the tidal response at the time when the equilibrium forcing is at its largest positive value at 0◦ longitude. Chapter 4: Techniques and Methods 23

4.3.2 The AOTIM-5 Model Since LADCP stations record current proﬁles within only a few hours, these measurements do not yield time series which can be used to ﬁt a tidal response with T_TIDE. Therefore, LADCP data have to be corrected for tides by applying models. In this thesis, a barotropic tidal model developed by Padman and Erofeeva [2004] is used. The Arctic Ocean Tidal Inverse Model (AOTIM-5) is a high resolution model that assimilates all available data from up to 310 coastal and benthic tide gauges and the TOPEX/Poseidon (T/P) and ERS satellite missions. It is the most accurate Arctic tide model available at this time [Padman and Erofeeva, 2004]. The model domain uses the International Bathymetric Chart of the Arctic Ocean (IBCAO) digitized on a uniform 5-km grid. The domain is partitioned into 7 regions for model-data comparisons.

Fig. 4.7: Model domain, showing locations of tide gauge data (red squares), and ERS and TOPEX/Poseidon radar altimetry (magenta and yellow dots, respectively) [Padman and Erofeeva, 2004].

Satellite data are available from the T/P and ERS satellite radar altimeters: T/P measures sea surface height (SSH) for ice-free ocean to approximately 66◦N, while ERS measures SSH for ice-free ocean to approximately 82◦N. The AOTIM-5 model itself simulates only the 4 most energetic tidal constituents (M2,S2,O1, and K1), while four other constituents (N2,K2,P1, Q1) are used from a previous model which is based on numerical solution of the shallow water equations. Chapter 5: Results and Discussion 24

5 Results and Discussion

The results of this study are presented according to the procedure outlined in chapter two. Additionally, the single steps of the applied methods are described in this chapter. In this thesis, mooring data from 2004, 2005, 2006 and corresponding LADCP measurements of the same years were used. The LADCP data were recorded on cruises of RV Oceania (2004, 2005) and RV Maria S. Merian (2006).

5.1 Tidal Analysis of the Mooring Data

Mooring Data: The moorings extended from 6◦26’W, at the eastern Greenland shelf break, to 8◦40’E, at the western shelf break oﬀ Spitsbergen. For 2004 and 2005, data of 14 moorings are available, respectively. The dataset of 2006 contains only 7 moorings ranging from 0◦24’W to 8◦20’W, because not all moorings could be recovered in 2007. The current meters were moored on the depth levels 60m, 250m, 750m, 1500m and on the sea ﬂoor. The data are available as velocity time series for each current meter. Depending on the recovery and deployment time, the individual time series have a length of 12 to 13 months. Partial time series, which occurred due to instrument failure, have been removed. For the years 2004 and 2005, 59 and 55 full records are available, respectively. For 2006 only 31 records are available. The sample rates of the current meters were set to 2 hours, except for some acoustic current meters in 2004, which measured every hour. Before the deployment and after the recovery, the instruments were sent for calibration.

Tidal Analysis: The tidal signals were derived by using T_TIDE. The number of resolved tidal constituents depends on the individual length of each time series. The program resolves around 68 constituents for most of the time series. To enable the processing with T_TIDE, the time series had to be interpolated to obtain 1 hour steps. The T_TIDE procedure was automized for each dataset (2004, 2005 and 2006), resulting in 59, 55 and 31 tidal analyses, respectively (→ Fig. 5.1). In this thesis, only the M2 and K1 tidal constituents are considered, as they could be identiﬁed as strongest tidal signals in all of the datasets. First, the values for tidal ellipses were calculated and the ellipses for each current meter were plotted on the mooring line at 78.8◦N(→ Fig. 5.2). The ﬁgure shows strong tidal currents on the shelf regions near Greenland and Svalbard, where the shallow water depth is responsible for the enhancement of tidal motion. At the sea surface, the strongest tidal currents, ranging Chapter 5: Results and Discussion 25

Fig. 5.1: Result of a tidal analysis with T_TIDE. Upper panel: Raw velocity data and fitted tidal velocities. Middle panel: Raw data and detided data. Lower panel: Frequencies and amplitudes of the resolved tidal constituents. The 95% confidence interval is indicated as dotted line. Significant constituents are shown in blue color. Mooring: F9-6, depth: 60m, data from 2004.

Fig. 5.2:M2 tidal ellipses in Fram Strait (depth: 60m, mooring data from 2004). The names of the single moorings and the mean depth of the current meters are shown in the upper subplot. Chapter 5: Results and Discussion 26

from 5.4cm/s (data from 2004) up to 8cm/s (data from 2005), can be found at the westernmost moorings. As the water depth increases in the middle of Fram Strait, the surface tides become weaker and the ellipses are mainly oriented in north-south direction along the Fram Strait trench with inclination angles around 80◦-90◦. The tidal ellipses were plotted for each of the five depth levels. The ellipses of the M2 constituent change their size with depth, which indicates the generation of internal tides. Significant peaks of tidal velocities were found at the 1500m level in all of the datasets. The example in figure 5.3 shows comparably large ellipses near 3-4◦E and 2◦W.

Fig. 5.3: Left: M2 tidal ellipses in Fram Strait (depth: 1500m, mooring data from 2004). The red arrows indicate the tidal maxima. The names of the single moorings and the mean depth of the current meters are shown in the upper subplot. Right: Depth proﬁles of the semi-major and ◦ semi-minor axes of M2 tidal ellipses at 4 E. The error bars are 2σ conﬁdence intervals.

At some positions, the speeds of the tidal currents almost double from the 60-250m level down to 1500m (→ Fig. 5.3, right). As only meridional velocities through the Fram Strait section are considered for the calculation of volume ﬂuxes, meridional tidal velocities are needed for the correction of LADCP data. Therefore, the meridional component of the semi-major axis of each tidal ellipse was calculated for M2 and K1. Then, vertical proﬁles for each mooring were obtained by linear interpolation between the instruments in 20m intervals. Finally, the velocities between the single moorings were linearly interpolated.

Figure 5.4 (upper panel) shows two velocity peaks (about 3.3cm/s) of the M2 tide in 1500m depth and velocities of up to 4.8cm/s on the Svalbard shelf edge in 2004. Contrary to the M2 tide, the K1 tidal velocities show a more barotropic behaviour at all stations. Nevertheless, the ◦ peak at 1500m around 2 W can also be identiﬁed for K1. ◦ In the data from 2005 (→ Fig. 5.4, middle panel) the peak of the M2 tide at around 4 E is of a similar magnitude (3.8cm/s) as in 2004. Although no mooring was present at 2◦W in 2005, the existence of the western peak at 1500m can be inferred from the comparably high tidal velocities (around 2.7cm/s) at the neighboring current meter to the east. A strong benthic baroclinic tide with amplitudes of 3.8cm/s occurs near 3 degrees west. This deep maximum also exists for K1 and represents the highest tidal velocity peak (3.5cm/s) of this constituent measured in Chapter 5: Results and Discussion 27

2005. The meridional maxima of K1 are lowest on the shelf regions (about 0.5cm/s), because here the tidal ellipses are oriented in east-west direction and the maximum is determined by the semi-minor axis. For 2006 (→ Fig. 5.4, lower panel) the spacial resolution is reduced, but the M2 peak at 1500m can still be recognized.

As geometry and stratification play a relevant role in the generation of internal tides, tidal waves travel with different speeds depending on density differences, friction close to the bottom or the base of sea ice and also on the steepness of the bathymetry. Thus, the steep seafloor near 2◦W and 4◦E might be responsible for the velocity peaks at these positions in 1500m depth, which are most evident in the data of 2004. In addition, the mooring line lies near the critical latitude for semidiurnal constituents (74.5- ◦ 86 ). Here the Coriolis frequency almost equals the M2 tidal frequency:

ω = |f| = 2 sin(ϕcrit) (13)

ω: constituent frequency, f: Coriolis frequency, : Earth’s angular velocity, ϕcrit: critical latitude

Tidal currents are known to have a strong depth dependence near ϕcrit. Similarly to the amplitudes of the tidal velocities, the Greenwich phase angles show a baroclinic pattern with a series of minima and maxima for the M2 tide, and a mainly barotropic structure for the K1 tide (→ Fig. 5.5). Furthermore, the phase angles of K1 are higher than the M2 phases in all of the datasets. Minima of both M2 and K1 can be found on the shelf regions and at the 60m level near 7◦E in 2004 and 2006. Comparing the years 2004 and 2005, the ◦ M2 phase lags show a high temporal variability. The angles around the 0 meridian at 1500m depth increase by approximately 25 degrees within one year, whereas the K1 phase angles are more stable over time. Interannual changes in stratiﬁcation and water masses are known for signiﬁcantly altering the Greenwich phase lags near the critical latitude [Makinson et al., 2006]. Chapter 5: Results and Discussion 28

Fig. 5.4: Vertical transects across Fram Strait with the meridional maxima of M2 (left column) and K1 tidal velocities (right column) for 2004 (upper panel), 2005 (middle panel) and 2006 (lower panel). The locations of the moored instruments are indicated by grey circles. Chapter 5: Results and Discussion 29

Fig. 5.5: Vertical transects across Fram Strait with Greenwich phase angles of the meridional component of M2 (left column) and K1 tides (right column) for 2004 (upper panel), 2005 (middle panel) and 2006 (lower panel). The locations of the moored instruments are indicated by grey circles. Chapter 5: Results and Discussion 30

5.2 Comparison with Model Results

In order to investigate the differences of the tidal velocities between the moorings and the tidal model, the T_TIDE results and the corresponding results of AOTIM-5 have been combined in the following graphs. The two examples of depth profiles in figure 5.6 indicate, that in most cases the modelled tidal velocities do not reflect the observed tides.

Fig. 5.6: Depth proﬁles of tidal velocities at 4◦E (2005). (a) Absolute values of the semi-major and semi-minor axes of M2 tidal ellipses. (b) Absolute values of the semi-major and semi-minor axes of K1 tidal ellipses. Red lines are results from the barotropic model (AOTIM-5), black lines are results from the T_TIDE analysis. The error bars are 2σ conﬁdence intervals.

Fig. 5.7:M2 tidal ellipses in Fram Strait. The white ellipses are from the T_TIDE analysis (depth: 250m, mooring data from 2005), the red ellipses are modelled by AOTIM-5. The names of the single moorings and the mean depth of the current meters are shown in the upper subplot. Chapter 5: Results and Discussion 31

Mainly the major axes of the tidal ellipses (especially M2 → Fig. 5.7) are overestimated by the model, with diﬀerences exceeding the observational uncertainty as determined by T_TIDE. In comparison with that, most values of the minor axes lie either within the conﬁdence intervals or are slightly underestimated.

Fig. 5.8: Surface plot of the meridional maxima of the M2 tidal velocities over the complete vertical transect in Fram Strait. The mooring data (lower surface) are from 2005. The upper surface (dark blue) represents the corresponding velocities from the AOTIM-5 model.

It is apparent from ﬁgure 5.8, that the modelled velocities exceed the measured values from the mooring time series. Compared with the measurements, the model overestimates the meridional tidal velocity maxima of M2, averaged over the entire transect, by 36%, 34% and 45% for 2004, 2005 and 2006, respectively. The K1 constituent is overestimated by 30%, 22% and 39%. However, the AOTIM-5 results reasonably reproduce the measured tidal velocities in the shelf regions near Greenland and Svalbard, suggesting that the model gives better results for shallow water. Contrary to the velocities, the Greenwich phase lags are underestimated by the model (→ table III).

Table III: Mean values and rms of the diﬀerences between model results and mooring data. The values are given for velocity maxima and Greenwich phase lags of the meridional component of the constituents M2 and K1.

Tide M2 K1

Velocity [cm/s] Phase [deg] Velocity [cm/s] Phase [deg]

2004 0.9±0.6 | -26.8±11.9 0.4±0.3 | -12.3±15.0

2005 0.9±0.8 | -27.7±10.6 0.3±0.6 | -18.0±39.0

2006 1.0±0.4 | -55.8±11.1 0.5±0.2 | -30.3±10.3 Chapter 5: Results and Discussion 32

The discrepancies between the model and the measured tides can be attributed to baroclinicity, which is not included in the model, and inaccuracies in bathymetry. Another reason might be the sparse coverage with available tide data in the Fram Strait region (→ Fig. 4.7).

5.3 LADCP Data and Tidal Correction

LADCP Data: The LADCP data of the Fram Strait section cover the region of the northward ﬂowing WSC. They range from 1.49 to 9.26◦E (2004), 2.35 to 9.28◦E (2005) and 0.09 to 9.08◦E (2006) and have a vertical resolution of 20m. Because the mooring information was later used to subtract the tidal signal from the LADCP data, LADCP stations east and west of the mooring array have been removed, resulting in 12

Fig. 5.9: Vertical transects of the meridional current velocities through Fram Strait, measured by LADCP in 2004, 2005 and 2006. The LADCP stations are marked by grey lines and blue triangles on top. Mooring positions are indicated by white circles on the sea ﬂoor. Positive velocities are directed northwards.

and 10 remaining stations for the datasets of 2004 and 2005, respectively. For 2006, the spatial resolution is higher (38 stations). To obtain ﬁelds of full data coverage, the data were gridded Chapter 5: Results and Discussion 33

on a rectangular grid with 200 × 20m cell size by using the MatLab toolbox obana3 by Martin Visbeck and Gerd Krahmann. The sea ﬂoor was subtracted afterwards.

Figure 5.9 shows the current structure of the WSC at 78.8◦N. The WSC appears as a strongly barotropic stream of approximately 100-120km width and reaches from the shallow shelf region to the deeper part of the continental slope. The current has two cores, separated by a southward flow in the middle part, which is most evident in the data of 2004 and 2005. In 2004 and 2005, maximum northward speeds of 32-42cm/s were measured in the upper 250m. In 2006, maximum velocities of around 30cm/s were measured at 800-1000m depth on the upper shelf slope. In comparison with 2004 and 2005, the data of 2006 extend further west and indicate the typical flow structure in Fram Strait, which is marked by alternating bands of northward and southward flow. The differences in speed and shape of the WSC between 2004 and 2006 reflects the strong interannual variability, which has already been proved in previous studies [Fahrbach et al., 2001; Walczowski et al., 2005].

Tidal Correction: Two separate tidal corrections were made to remove the tidal signal from the LADCP data and to compare differences between the results. Both the AOTIM-5 model and T_TIDE have been used to predict the tidal velocities for each LADCP station at the corresponding measuring time. The corrections were first done for the M2 tide. As a LADCP is usually lowered with speeds of around 1m/s, a downcast to 2600m takes 1 about 45 minutes. For the M2 constituent, 45 minutes constitute approximately 16 th of the total period. Depending on the amplitude and phase, tidal currents can change their velocity considerably during this time. To take this into account, the tidal signal at each LADCP station has been modelled as a time series, starting at the surface with the given date and time of the LADCP measurement and going down to the deepest level with an assumed mean vertical profiling speed of 1m/s. An example of the resulting velocity field from the AOTIM-5 model is shown in figure 5.10 (a).

Fig. 5.10:M2 tidal velocities for the correction of the LADCP section from 2004. (a) Modelled velocities by AOTIM-5. (b) Predicted velocities by using information from the T_TIDE analysis.

AOTIM-5 is able to predict tidal velocities at any given point in the Arctic Ocean. Contrary Chapter 5: Results and Discussion 34

to the model, T_TIDE can only be used to predict tides at the positions of the moored current meters. As the positions of many LADCP stations differ from the mooring positions, the tidal predictions with T_TIDE were calculated for the two closest moorings east and west of each station, and the resulting velocities have been interpolated. Similarly to the above described procedure with the model, time series corresponding to a downcast velocity of 1m/s were con- structed for every LADCP station. For this purpose, the predictions for each current meter were made for the starting time of the LADCP downcast plus a time delay, which corresponds to the depth of the current meter. The resulting tidal velocity field for the data of 2004 is shown in figure 5.10 (b).

In the model, the amplitudes and phases of tides are barotropic, i.e. the variation of the tidal velocities over depth at one LADCP station only depends on time. As shown above, the M2 tide in Fram Strait is highly baroclinic, and the tidal velocities additionally depend on the spatial variation of amplitudes and phases. In figure 5.10 this can be seen from the different shape of the tidal field compared to the AOTIM-5 result. The tidal velocity peak at 1500m depth appears as dark blue spot on the left side of figure 5.10 (b). However, the directions of the tidal signals in both velocity fields agree quite well. Thus, the small differences were not expected to cause significant disparities in the volume transports.

5.4 Volume Transports

In this section, the calculated volume transports are discussed. The transports were estimated from both the raw LADCP velocity data and the data which were corrected for tidal signals. In the second part, the transports obtained from combined LADCP/mooring data are discussed.

5.4.1 Transports from LADCP Data

Uncorrected data: For each year, the transports were calculated from the interpolated velocity field shown in figure 5.9. To obtain the transport through the entire LADCP section, the area of every grid cell was multiplied with the corresponding velocity value, and the resulting transports were summed up at the end. The transport estimates from LADCP data are associated with errors arising from the measurements of the current velocities. For the calculation of the error propagation a typical error of 5cm/s [Walter and Huhn, 2008] was assumed. To take the barotropic character of the WSC into account, the correlation coefficient of the single velocities within one LADCP station was set to r=1. The velocity correlation between single LADCP stations was assumed to be zero (r=0), which seems a reasonable assumption considering the spatial variability of the WSC. The results of the transport estimates for 2004, 2005 and 2006 are presented in table IV.

Compared to the result for 2005, the high northward volume fluxes in 2004 can be attributed to lower southward flow and higher velocities measured in the WSC core (→ Fig. 5.9). In 2005, the calculated northward transports are almost half of the result for 2004, because the distance covered by the LADCP section in 2005 is smaller and the measured velocity maxima in the WSC are lower than in 2004. Furthermore, there was a strong southward flow around 2.5◦E Chapter 5: Results and Discussion 35

in 2005. The LADCP section of 2006 covers a range of 170km and includes a broad band of southward ﬂow, which is responsible for the low northward volume transport compared to the data of 2004 and 2005. For the high number of LADCP stations in 2006, the assumption that the velocities between the single stations are not correlated is not correct anymore. This might be responsible for the large error of about 64%.

Table IV: Volume transports calculated from raw and corrected LADCP data. The tidal correction was made for the M2 signal by using both AOTIM-5 and information from the moored current meters. Transports to the north are positive.

Raw LADCP Data Corrected Data

AOTIM-5 Moorings

2004 8.0±1.5 Sv 7.7 Sv 7.6 Sv

2005 4.4±1.3 Sv 3.3 Sv 3.8 Sv

2006 2.8±1.8 Sv 4.1 Sv 3.7 Sv

Corrected data: Notably, the transport estimates of detided LADCP data from 2004 and 2005 result in smaller values than those derived from raw data, whereas the transports for the data of 2006 are increased by tidal correction. In 2004, the north- and southward tidal velocities correspond to the directions of the measured current velocities and the resulting corrected transport is very close to the initial value of 8 Sv. In 2005, the tidal correction weakens large parts of northward flow and simultaneously strength- ens regions of southward flow, resulting in a smaller northward transport compared to the raw LADCP data. Contrary to the LADCP measurements in 2004 and 2005, which were recorded in continuous sections from east to west within two days, the measurements of 2006 were not made contin- uously and took about three weeks. The increasing volume transport shows that the effect of a tidal correction can be very different and depends on time and duration of the LADCP measurements.

Although the AOTIM-5 tidal velocities exceed the measured tidal signals of the mooring array, the diﬀerences between the volume transports, which were calculated after applying both types of tidal correction, are small. This suggests that AOTIM-5 yields reasonable tidal corrections for LADCP data and for the calculation of volume transports in Fram Strait. As the K1 tidal constituent has a weaker signal as M2, the tidal correction for the K1 signal was not expected to signiﬁcantly alter the transport estimates. Therefore, the further corrections were only done for the M2 signal. Chapter 5: Results and Discussion 36

5.4.2 Combined Transports from Moorings and LADCP Data To enable a higher spatial resolution of the velocity field, mooring data and LADCP data were combined. Whereas the LADCP profiles consist of single measurements, the mooring data are available as time series. Thus, the data had to be adapted. The mooring data were corrected for the M2 tide by predicting and subtracting the tidal signal with T_TIDE. For the combination with LADCP data, mean values have been calculated from the corrected mooring time series. The mean values for each current meter were calculated from the velocities which have been recorded in the time interval of the corresponding LADCP section. For the period of the LADCP measurements in July 2004, no corresponding mooring data were available. For 2005 and 2006, the LADCP data were corrected for the M2 tidal signal by using mooring information (see section 5.3). Then, the data were combined with the above described velocity means of those moorings which were covered by the LADCP section. The resulting velocity field was gridded (200×20m cell size) by using the obana3 software and volume transports were calculated (→ table V).

Table V: Volume transports calculated from LADCP data and combined LADCP/mooring data for the LADCP sections of 2005 and 2006 (→ Fig. 5.9). All data were corrected for the M2 tidal signal before.

LADCP LADCP + Moorings

2005 3.8 Sv 3.5 Sv

2006 3.7 Sv 4.4 Sv

Compared to the volume transports which were calculated from LADCP data, the combination of LADCP and mooring data results in a slightly decreased northward transport for 2005. Contrary to that, the transport from the data of 2006 is increased by the additional mooring information. The decreasing northward transport for 2005 can be explained by the fact that most of the mooring positions almost coincide with LADCP stations and the velocity means of these moorings are lower than the measured LADCP values. The following interpolation with obana3 considerably reduced the velocities for these positions, resulting in values which did not reflect the measurements anymore. For 2006, the increase of 0.7 Sv can be attributed to the reduced number of moorings. There were no instruments in the region of southward flow (→ Fig. 5.9, 2006), i.e. the moorings mainly measured northward flow during the period of the LADCP measurements in August/September 2006.

In the next step, volume transports were calculated from pure mooring data and combined LADCP/mooring data. The spatial resolution of the mooring velocity ﬁeld was increased by Chapter 5: Results and Discussion 37

adding LADCP proﬁles between the mooring positions. LADCP stations which coincide with mooring positions have been removed to avoid the above mentioned interpolation error. The data were corrected for tides and then gridded by obana3. The resulting transports are presented in ﬁgure 5.11.

Fig. 5.11: Volume transports calculated from mooring data and combined LADCP/mooring data for 2005 and 2006. All data were corrected for the M2 tidal signal before. Positive values are northward transports.

For the selected region in 2005, the northward flow measured by the current meters is nearly balanced by southward flow, and the resulting net northward volume flux of the WSC is small. After increasing the spatial resolution by adding LADCP information (5 profiles), the volume flux decreases by 2.2 Sv, resulting in a net southward transport. Although the amount of additional velocity information from LADCP data is small, the effect on the volume transport is considerable and can be attributed to the clearly increased southward flow at the westernmost LADCP station. The improved spatial resolution is most evident in the fine structures of the velocity field between mooring F6-8 und F4-7 (→ Fig. 5.12, right). For the considered period in 2006, almost no southward flow was measured by the current meters. The resulting northward transport is correspondingly high. The additional LADCP information (28 profiles) include large areas of southward flow which were not resolved by the moorings, and the net northward transport decreases by 11.4 Sv after combining the data. The high velocities near the sea floor at mooring F6-10 (→ Fig. 5.12, right) originate from the LADCP data, and the shape of the peak is a result of the interpolation method.

The value of 1.9 Sv southward transport (2005) is very close to the minimum value (-1.4 Sv) observed by Hanzlick [1983] in 1977. However, the velocity means of the current meters in 2005 are very low and might not reﬂect the true velocity at the time of the LADCP measurements. The transport value for 2006 (+5.6 Sv) is equal to the yearly mean transport for the section at 79◦N between 3.5◦E and 8.5◦E given by Hanzlick [1983]. This value is about half of the northward transport through the entire Fram Strait published by Schauer et al. [2008] (12 Sv). Chapter 5: Results and Discussion 38

Fig. 5.12: Velocity ﬁeld in Fram Strait in 2005 and 2006. Left: Mooring data. Right: Combined mooring/LADCP data. Locations of the current meters are shown as grey circles, names of the moorings are given on top, LADCP stations are indicated by grey lines and blue triangles.

5.5 Uncertainties

T_TIDE is a precise tool for the tidal analysis of mooring data including the baroclinic component of the tides. But amplitudes and phases of baroclinic tides depend on the depth profile of stratification and the interaction with lower-frequency flows. If they change, then the T_TIDE assumption that each constituent is steady-state is wrong. Thus, there might be still tidal-band signals remaining in the residual. But the effect on transport estimates should be marginal.

Transport estimates are subject to several uncertainties which depend on station spacing and measurement accuracy. The measurements with LADCP and moored current meters are affected by instrumental errors, whereas systematic errors were avoided by calibration. Large errors occur due to the limited spatial instrumental resolution. This error was reduced by the combination of mooring data with additional velocity information. Nevertheless, the calculated Chapter 5: Results and Discussion 39

errors for the LADCP data range from 19% to 64%. This also affects the significance of the tidal correction. It is apparent from figure 5.13 that the tidal correction of LADCP data does not create significant changes in the volume transports. If an LADCP velocity error of 2cm/s [Walczowski et al., 2005] instead of 5cm/s is selected, the transport error decreases to ±0.6, ±0.5 and ±0.7 Sv for 2004, 2005 and 2006, respectively. Then, the differences between uncorrected and corrected transports for 2005 and 2006 exceed the level of significance. The transport estimates are also affected by the mean values which were calculated from the velocity time series of the moored current meters. In most cases, the mean values are lower than the measured LADCP values from the same position. Since most mooring positions directly coincide with LADCP stations, the error should reduce by finding the velocity value in the time series, which corresponds to the time of the LADCP measurement.

Fig. 5.13: Volume transports calculated from raw and detided LADCP data for 2004, 2005 and 2006.

Another error source is the applied interpolation method with the obana3 software. The gridded velocity field reacts sensitively to changes of the parameters influence radius and cut-off radius. Compared to a simple interpolation with the MatLab commands Interp1 and contourf, obana3 reproduced the shape of the current field very well, but decreased the velocity peaks. By lowering the influence radius, the initial velocity distribution could be reproduced, but the shape of the current field was distorted. The difference between the two parameter settings caused changes in the transport estimates of up to 0.3 Sv. This error was reduced by finding the optimal setting for the influence radius, and by visual inspection of the velocity field in order to keep the velocity distribution and the shape of the current as realistic as possible. Chapter 5: Results and Discussion 40

5.6 Summary

The tidal field in Fram Strait was investigated by analyzing time series from moored current meters, and the result was compared to corresponding results of a barotropic tidal inverse model. Both the information from the mooring array and the model were used to detide LADCP data from eastern Fram Strait. Transport estimates were calculated from the corrected data and the differences between both results were assessed. The corrected LADCP data were used to fill the gaps between the mooring positions in the WSC region, and volume transports were calculated from the combined data. The main outcomes of this study are summarized below.

• The M2 tidal ﬁeld in Fram Strait is strongly baroclinic and rich in structures of changing amplitudes and phase lags. Contrary to M2, the K1 tidal ﬁeld has a barotropic character.

• The AOTIM-5 model overestimates the tidal velocities in the Fram Strait transect by about 30%. However, the model results for shallow water on the Greenland and Svalbard shelves are very close to the measured tidal signals.

• The volume transports, which were calculated from data corrected by AOTIM-5, do not diﬀer signiﬁcantly from those transports, which were calculated from data that were corrected by using mooring information.

• Depending on the considered distance and the number of moorings and LADCP stations, volume transports from moored current meters can decrease signiﬁcantly after improving the spatial resolution by adding LADCP data. Chapter 6: Conclusions and Outlook 41

6 Conclusions and Outlook

The obtained volume transports based on LADCP observations are in good agreement with other published values and reflect the high temporal variability of the WSC. However, these values do not represent the net Atlantic Water volume that is transported into the AO, because the recirculation in central Fram Strait is not covered by the sections, i.e. the transports estimates must not be seen in isolation ignoring the flow field in the central and western Fram Strait.

The array of moorings in Fram Strait provides valuable information about the temporal variability of the WSC. Nevertheless, the ﬂow structure is under-sampled, which in turn aﬀects the estimates of volume transports. The transports from mooring data, which were calculated in this thesis, seem either too large (results for 2006) or too small (results for 2005) when compared to other values published by Schauer et al. [2008] and Fahrbach et al. [2001]. However, it should be mentioned that a direct comparison of these values it hardly possible. Whereas the published values represent yearly or monthly means, the transports calculated in this thesis are mean values from two days (2004, 2005) or almost three weeks (2006) of measurements.

To overcome the limitations of the low spatial resolution and to obtain more precise quasi- synoptic transport values, the use of additional LADCP data is an easily applicable method. It could be shown that transport estimates can be altered significantly by adding a set of LADCP stations to the transect. The resulting volume fluxes of the WSC are lower than other published values. This is mainly due to the velocity mean values of the mooring time series. The comparison with corresponding LADCP velocities showed that the mooring mean values are too low. As a consequence, the flow field presented in this thesis cannot be seen as a perfectly reliable description, but represents a good approximation to the real conditions, especially regarding the improved spatial resolution.

For future research it would be promising to further investigate the behaviour of volume fluxes by using high resolution velocity data from vessel-mounted ADCPs. With ADCP datasets cov- ering the entire Fram Strait, the regions of recirculation in the central Fram Strait as well as the EGC region could be included. To integrate the incomplete mooring time series, gaps in the record could be filled with the record length averages. The velocity field itself could be improved by using additional information from CTD sections, as applied by Fahrbach et al. [2001]. For more accurate quantitative estimates, a thorough error calculation for the combined mooring/LADCP transports could be made, including the accuracy of all types of current meters and LADCP measurements. Additional geostrophic calculations would allow the assessment of the baroclinic component of the WSC. Chapter 6: Conclusions and Outlook 42

Overall, the results of this project suggest that the combination of mooring data with additional LADCP information provides a useful tool in order to validate transport estimates and to get a better understanding of the volume ﬂuxes through Fram Strait. The application of this technique together with other methods, like "kriging" or the combination with CTD information, could lead to even more precise transport estimates and, consequently, more reliable heat transports into the Arctic Ocean. List of Figures 43

List of Figures 1.1 Mooring array in Fram Strait ...... 2 1.2 Variability of temperature in the intermediate layer of the AO ...... 3 1.3 Cross-section averaged AW temperature in Fram Strait ...... 4 1.4 Mass budget of the Arctic Ocean ...... 5 1.5 Monthly means of volume transport through Fram Strait ...... 6 2.1 Circulation in the Nordic Seas ...... 7 2.2 Velocity field at 78.8◦N (200m), 2006 ...... 8 3.1 Map of the Arctic Ocean ...... 9 3.2 Fram Strait bathymetry ...... 10 3.3 Main ocean currents, North Atlantic and AO ...... 11 3.4 Circulation of AW in the AO ...... 12 3.5 AO surface circulation and water masses ...... 13 3.6 Formation of water masses in the AO and Nordic Seas ...... 14 3.7 Stratification of water masses ...... 15 4.1 Mooring arrangement ...... 16 4.2 Current meters ...... 17 4.3 ADCP working principle ...... 18 4.4 Vessel-mounted ADCP ...... 19 4.5 Tidal forcing on Earth’s surface ...... 20 4.6 Tidal ellipse ...... 22 4.7 AOTIM domain ...... 23 5.1 Tidal analysis with T_TIDE ...... 25 5.2 M2 tidal ellipses, 60m, 2004 ...... 25 ◦ 5.3 M2 tidal ellipses (1500m) and depth profiles of M2 tide at 4 E, 2004 ...... 26 5.4 Meridional maxima of M2 and K1 tidal velocities in Fram Strait, 2004,05,06 . . . 28 5.5 Phase angles of M2 and K1 tides in Fram Strait, 2004,2005,2006 ...... 29 ◦ 5.6 Depth profile of M2 and K1 tide from T_TIDE and AOTIM-5, 4 E, 2005 . . . . 30 5.7 M2 tidal ellipses from T_TIDE and AOTIM-5, 250m, 2005 ...... 30 5.8 Surface plot of M2 tidal amplitudes ...... 31 5.9 LADCP velocities at 78.8◦N, 2004,05,06 ...... 32 5.10 Tidal correction from AOTIM and T_TIDE,2004...... 33 5.11 Volume transports from mooring data and combined LADCP/mooring data, 2005,2006...... 37 5.12 Velocity field from moorings and mooring/LADCP data, 2005 and 2006 . . . . . 38 5.13 Volume transports from raw and detided LADCP data ...... 39 List of Figures 44

Sources

(1) http://www.nature.com/nature/journal/v447/n7147/ﬁg_tab/nature05924_ft.html (2) http://www.whoi.edu/cms/images/oceanus/GlobeCurrentsMap_550_47170.jpg (3) http://www.amap.no List of Tables 45

List of Tables

Table I: Moored current meters in Fram Strait ...... 17 Table II: List of major tidal harmonic constituents ...... 21 Table III: Mean values and rms of the diﬀerences between tidal velocities from model results and mooring data . . . . 31 Table IV: Volume transports calculated from raw and corrected LADCP data...... 35 Table V: Volume transports calculated from LADCP data and combined LADCP/mooring data ...... 36 References 46

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Appendix Appendix 50

Photo by Kai-Uwe Ludwichowski (ARK XXIII-2, 2008)