Laptev Sea and East Siberian Sea Landfast Ice: Mechanisms of Formation and Variability of Extent

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LAPTEV SEA AND EAST SIBERIAN SEA LANDFAST ICE: MECHANISMS OF FORMATION AND VARIABILITY OF EXTENT

Valeria Selyuzhenok

A thesis submitted in partial fulﬁllment of the requirements for the degree of

Doctor of Philosophy in Geosciences

Approved Dissertation Committee

Prof. Dr. Rüdiger Gerdes, Jacobs University Bremen, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven Prof. Dr. Joachim Vogt, Jacobs University Bremen Dr. Thomas Krumpen, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven

Date of Defense: October, 13, 2017

Physics & Earth Sciences

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Abstract

Landfast ice is a motionless continuous with the shore sea ice over. It forms seasonally in the majority of the Arctic coastal areas. Although it comprises a only small fraction of winter Arctic sea ice extent, it plays a signiﬁcant role in the global climate system and is particularly important for coastal ecosystems and human activity. Along with the ongoing changes in the Arctic sea ice cover, the reduction of fast ice season and extent were reported in the majority of the Arctic marginal seas. A detail understanding of the mechanisms controlling fast ice development on a regional scale is important to predict future changes in fast ice cover and coastal environment. The main goal of this thesis is to investigate the variability of the fast ice extent in the Laptev and East Siberian seas and to ﬁnd the mechanisms responsible for this variability.

Using operational sea ice charts produced at the Arctic and Antarctic Research Institute (Russia) we analyzed seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013 and in the East Siberian Seas between 1999 and 2015. We characterized seasonal fast ice development in these regions by identifying key events in the course of fast ice growth and decay. Analyzing the timing of the fast ice key events, we found a decrease in duration of fast ice season in both regions with a rate of 2.8 d/y in the Laptev Sea and 1.5 d/y in the East Siberian Sea. This changes are caused by both a later beginning and earlier end of fast ice season, which can be partially explained by long-term trends in the onset of freezeup and melt. The winter fast ice extent did not show any changes during the investigation period, however previous studies report on the reduction in winter fast area (Yu et al., 2014).

A time series of Synthetic Aperture Radar (SAR) imagery was used to investigate small-scale processes contributing to the advance of fast ice edge to its winter location in the southeastern Laptev Sea. A detailed examination of SAR-based ice drift showed that several grounded ice features are formed oﬀshore prior to fast ice expansion. These features play a key role in oﬀshore advance of the fast ice edge and serve as stabilizing points for surrounding pack ice as it becomes landfast. Contrary to previous studies (Eicken et al., 2005; Karklin et al., 2013), we conclude that grounding is a key mechanism of fast ice development in the southeastern Laptev Sea. The position and shape of fast ice edge in the East Siberian Sea suggests that formation of grounded ice ridges might be responsible for interannual variations in winter fast extent.

In addition, the SAR data were used to study the processes of sediment incorporation into the Laptev Sea fast ice. The study showed that up to 10% of the annually exported sediment load may be incorporated during a coastal polynya event. Further delay in the beginning of fast ice season or occurrence of mid-winter breakup events might impact viii the regional sediment budget and have further consequences for radiation balance within the export pathways of the Laptev Sea ice into the Transpolar Drift. Contents

1 Introduction 1 1.1 Arctic sea ice as a part of the climate system ...... 1 1.2 Arctic fast ice ...... 3 1.2.1 Deﬁnition and variability of the Arctic fast ice extent ...... 3 1.2.2 Importance of fast ice for climate, ecology and human activity .5 1.2.3 Recent changes in the Arctic fast ice cover ...... 6 1.3 Scope of this work ...... 6 1.4 Overview of papers ...... 6

2 Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013 9

3 Mechanisms of fast ice development in the southeastern Laptev Sea: A Case study for winter of 2007/08 and 2009/10 27

4 East Siberian Sea fast ice: Interannual variations in winter extent and linkage with atmospheric forcing 39 4.1 Introduction ...... 40 4.2 Data and Methods ...... 41 4.2.1 Fast ice information ...... 41 4.2.2 Freezeup and Melt onset. Freezing (FDDs) and thawing (TDDs) degree days ...... 42 4.2.3 Atmospheric dynamic factors ...... 42 4.3 Results ...... 43 4.3.1 Seasonal cycle ...... 43 4.3.2 Key events and trends ...... 45 4.3.3 Linkage with thermodynamic factors ...... 45 4.3.4 Linkage with atmospheric circulation ...... 45 4.4 Discussion ...... 48 4.5 Conclusion ...... 50

5 Sediment entrainment into sea ice and transport in the Transpolar Drift: a case study from the Laptev Sea in winter 2011/2012 51

6 Discussion and Outlook 63

ix x Contents

List of Figures 67

List of Tables 69

Bibliography 71

Acknowledgements 85

Statutory Declaration 85 Chapter 1

Introduction

This thesis is organized as follows: Chapter 1 introduces the topic of this thesis by providing the background information on sea ice and in particular on Arctic fast ice. The objectives of this work are presented in Section 1.3. Section 1.4 links four papers (Chapters 2 – 5) which comprise the main outcome of the work. Chapter 6 elaborates on the ﬁndings and summarizes the main results.

1.1 Arctic sea ice as a part of the climate system

Sea ice is a distinctive feature of polar regions and a key component of the global climate system. The sea ice cover is characterized by a strong annual cycle: It advances during cold seasons and retreats during warm seasons. At its annual maximal extent sea ice covers about 5 % of the northern and 8 % of the southern hemisphere (Lubin and Massom, 2006; Gloersen et al., 1993). The presence of sea ice in the polar regions regulates the energy balance of the climate system. Because sea ice has signiﬁcantly higher albedo (the capability of a surface to reﬂect radiation) than the ocean surface, the sea ice covered ocean receives less energy compared to the ice-free ocean. Changes in sea ice area imply a positive feedback loop which is called ice-albedo feedback: Reduction in sea ice area leads to a decrease in surface albedo, as a consequence more energy is absorbed by the surface which in turn facilitates the reduction of sea ice. The positive feedback also applies in case of increasing sea ice covered area.

Regulating the amount of energy received by the surface, sea ice aﬀects the intensity of heat redistribution between the mid-latitudes and the polar regions. Changes in sea ice cover impact temperature gradients between the polar region and mid-latitudes, which in turn modify the global atmospheric circulation (Budikova, 2009). Furthermore, during the formation and melt of sea ice, a great amount of freshwater is exchanged between the ocean and sea ice which can aﬀect the global thermohaline ocean circulation (Barry et al., 1993; Mauritzen and Hakkinen, 1997).

1 2 Chapter 1 Introduction

Forming an insulating layer between the ocean and the atmosphere, sea ice regulates the ﬂux of heat, moisture and momentum between the two systems. Sea ice is also an important component of the ecological system as it provides habitats for microorganisms and a hunting platform for mammals.

In the northern hemisphere, sea ice has a great impact on human activity. The presence of sea ice restricts navigation and natural resource extraction. For indigenous people sea ice serves as platform for hunting, ﬁshing and traveling (Laidler, 2006). Hazards related to sea ice such as ride-up and pileup pose a risk to coastal infrastructure (Meier et al., 2014).

Sea ice conditions in the Arctic have been changing dramatically over the last decades. The total sea ice extent has been declining at an average rate of 4% per decade (Cavalieri and Parkinson, 2012; Comiso and Hall, 2014; Meier et al., 2014). Furthermore the melt season length has increased by about 20 days (Markus et al., 2009). Extremely low summer sea ice extents were observed in 2007, 2011 and the minimal extent was recorded in 2012. Moreover, thinning of Arctic sea ice and consecutive reduction in its volume were reported (Rothrock et al., 1999; Giles et al., 2008; Kwok et al., 2009; Lindsay and Schweiger, 2015). As a result, the Arctic ice cover is getting more and more sensitive to climate anomalies (Ricker et al., 2017). It is debatable whether the changes in the Arctic sea ice is a response to atmospheric greenhouse gas loading (Stroeve et al., 2012) or only a random change caused by the internal variability (Swart, 2017). Nevertheless, climate models agree that the sea ice extent will further decline through the 21st century (Serreze et al., 2007; Wang and Overland, 2009, 2012).

The changes in Arctic sea ice are already having an impact on the weather and climate in the Arctic (Vihma, 2014) as well as the local flora and fauna. The changes are also affecting people living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction (Meier et al., 2014). As the human activity in the Arctic region is concentrated in the marginal Arctic Seas (traditional hunting and fishing, shipping and resource extraction) it is of great importance to asses the changes in the Arctic coastal regions and understand the factors driving these changes. In regards to sea ice, the most prominent feature of the Arctic coastal region is fast ice. 1.2 Arctic fast ice 3

S i b Alaska e

Greenland 0 500 km

land open water fast ice pack ice no-data Figure 1.1. Sea Ice Review Chart for March 2015 (AARI). Fast ice extent is shown in red.

1.2 Arctic fast ice

1.2.1 Deﬁnition and variability of the Arctic fast ice extent

Fast ice is a prominent feature of Arctic coastal regions. Reviewing numerous definitions of fast ice (landfast ice, shore-fast ice) found in literature, Mahoney et al. (2006) underline that in practice it is difficult to identify fast ice explicitly. All fast ice definitions agree that there are two main criteria characterizing fast ice: 1) fast ice is adjacent to the shore and 2) it is characterized by a lack of motion. However, there is no specific time interval over which these conditions must occur (Mahoney et al., 2006). The World Meteorological Organization (WMO) defines fast ice as sea ice which remains fast along the coast, where it is attached to the shore, to an ice wall, to an ice front, or over shoals, or between grounded icebergs (WMO, 1970).

Arctic fast ice is typically grounded in shallow waters along the coast and at the shoals (Dmitrenko et al., 1999; Divine et al., 2004). Grounded ice ridges play an important role along the Alaska coast, while the Siberian fast ice is characterized by lack of ridges. A schematic drawing of the two diﬀerent regimes that are representative for Arctic fast ice is shown in Figure 1.2. Fast ice can be divided into 1) bottom fast ice (develops when 4 Chapter 1 Introduction

A Grounded B Attached ice pressure ridges Near-shore ice Bottomfast ice Fast ice Flaw lead Pack ice < 1-5 km

Tidal crack

2 m

Figure 1.2. Cross-sections of fast ice cover: A. Alaskan fast ice (adopted from Petrich et al. (2012)) B. Laptev Sea fast ice (adopted from Eicken et al. (2005)). the whole water column freezes to the bottom) and 2) ﬂoating fast ice. Usually the border between the bottom and ﬂoating parts is delineated by tidal cracks (Bogorodskij et al., 2007) (Fig.1.2 b).

Fast ice forms seasonally in the majority of the Arctic marginal seas. Multiyear fast ice is an exceptional phenomenon in the Arctic. Its occurrence is limited to the Canadian Archipelago (Mahoney et al., 2007b), parts of the Taymyr Peninsula (Reimnitz et al., 1995) and Greenland (Sneed and Hamilton, 2016). Zubov (1945) describes fast ice development as a process of dynamical attachments of ice ﬂows to the land or seaward fast ice edge: The onshore winds push ice towards the fast ice edge where it undergoes hummocking and freezes to fast ice. By April-May fast ice usually reaches its maximal winter extent (Fig. 1.1). It varies strongly on a regional scale from tens of kilometers along Alaska’s coast to hundreds of kilometers in the southeastern Laptev and East Siberian seas.

The regional differences in fast ice extent are often associated with local topography and bathymetry. On average, the fast ice edge is located within the 10 - 25 m depth range (Zubov, 1945; Divine et al., 2004; Mahoney et al., 2007a). However, the factors governing variability of winter fast ice extent differ from region to region. One of the most well- understood fast ice regions is the Alaska’s coast and namely the Chukchi and Beaufort Seas. There, fast ice appears to be controlled by alongshore chains of grounded ridges and thermodynamic forcing (onset of freezing and thawing temperatures) (Mahoney et al., 2007a, 2014). Less is known about the Siberian fast ice cover. The interannual variations in winter fast ice extent in the Kara, Laptev and East Siberian Seas were first were linked to the river runoff (Dmitrenko et al., 1999). However, later studies showed that variations in the Kara Sea fast ice extent can as well be explained by surface winds and air temperature (Divine et al., 2004, 2005). The connection between wind forcing and development of fast ice was also reported for the Hudson Bay (Larouche and Galbraith, 1989). The state-of-the-art knowledge about the Laptev Sea is based on low-quality fast ice information (visual observation from ship and air reconnaissance flight) or limited to seasonal case studies. The Laptev Sea fast ice processes are closely linked with the Lena River runoff. First, Laptev Sea fast ice is primarily composed of river water (Eicken et al., 2005). Second, there are indications that the position 1.2 Arctic fast ice 5 of fast ice edge in winter is predefined by the intensity of Lena River summer runoff (Dmitrenko et al., 1999). Third, spring fast ice breakup in the region is triggered when near-shore fast ice is flooded by river water (Bareiss et al., 1999). To the best of our knowledge, there is no literature on the East Siberian fast ice seasonal and interannual variability. However, due to the geographical similarity of the East Siberian and the Laptev Sea fast, fast ice cover is considered to have similar characteristics in the two regions.

1.2.2 Importance of fast ice for climate, ecology and human activity

Although fast ice comprises only a very small part of the Arctic sea ice (Fig. 1.1), it plays an important role in the climate and ecosystems and aﬀects human activities:

• The location of the fast ice edge controls the position and shape of coastal polynyas. Coastal polynyas are ice free areas that develop when oﬀshore winds drift the pack ice away from the fast ice edge. They are sites of strong ice production and ocean-to-atmosphere moisture and heat losses and as such alter oceanic and atmospheric processes (Maqueda et al., 2004; Itkin et al., 2015);

• In the shallow zones, and in the spits of the shelf seas, the presence of fast ice is important in helping to maintain submarine permafrost (Rachold et al., 2000);

• Fast ice protects the coast from erosion and thus controls coastal morphology (Rachold et al., 2000; Eicken et al., 2005);

• Fast ice provides a habitat for micro-organisms and a hunting platform for large animals (Gjertz and Lydersen, 1986; Krell et al., 2003);

• Fast ice responds quickly to atmospheric and oceanic forcing (Mahoney et al., 2007b; Heil, 2006) it might be a sensitive indicator of climate change (Mahoney et al., 2007a; Divine et al., 2003);

• The distribution of fast ice has signiﬁcant implications for polar marine navigation and oﬀshore exploration, particularly for the seas, situated along the North-East passage (Johannessen et al., 2005; Hughes et al., 2011);

• Fast ice serves as a platform for cargo unloading and transportation and as a runway for small aircrafts (Weintrit, 2013). 6 Chapter 1 Introduction

1.2.3 Recent changes in the Arctic fast ice cover

Along with changes in arctic sea ice cover (see section 1.1), long-term changes were also found in the fast ice regime. Studies report on a decrease of fast ice extent in the Kara and Chukchi Seas (Divine et al., 2003; Mahoney et al., 2014) and trend towards later formation and earlier disappearance of fast ice in the Chukchi Sea during the last four decades (Mahoney et al., 2014). In addition there are indication of fast ice thickness loss in the Siberian Arctic (Polyakov et al., 2003a, 2012). These regional changes are reﬂected in Arctic-wide reduction in fast ice area and shortening of the fast ice season in the 1990s (Yu et al., 2014).

1.3 Scope of this work

Recent drastic changes in Arctic sea ice cover, create a need to gain further insight into fast ice regime and processes controlling it. Although the Laptev Sea and the East Siberian Seas are characterized by the broadest fast ice extent in the Arctic, there is no comprehensive study on the linkage between fast ice climatology, atmospheric forcing and bathymetry in the regions. This PhD project aim to ﬁll the gap in knowledge on the Siberian fast ice cover by linking the variability of fast ice extent in the Laptev and East Siberian Seas to these factor. The main objectives of the thesis are:

1. To describe the annual fast ice cycle and reveal the mechanisms driving the seasonal development of fast ice.

2. To evaluate changes in fast ice cover on interannual scales and link them to climate processes.

Since fast ice responds quickly to atmospheric and oceanic forcing (Mahoney et al., 2007b; Heil, 2006) it might be a sensitive indicator of climate change (Mahoney et al., 2007a; Divine et al., 2003). Assessment of the local changes to the fast ice regime can help to indicate the regions most vulnerable to the changing environment. Understanding the mechanisms which control fast ice development is essential to accurately incorporate fast ice in the numerical models. Representation of fast ice in numerical models is important for realistic simulation of numerous sea ice and ocean variables.

1.4 Overview of papers

As the Laptev Sea has been an object of extensive multidisciplinary research since 1990 (Hubberten et al., 1999) many process related to pack ice (drifting ice) are well- understood in the region. This develops a substantial base for in-depth study of the 1.4 Overview of papers 7 fast ice cover in the Laptev Sea. Therefore, the Laptev Sea was a focus region for a detail investigation of fast ice seasonal cycle. In the ﬁrst paper:

Selyuzhenok, V., Krumpen, T., Mahoney, A., Gerdes, R. (2015): Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013, Journal of Geophysical Research: Oceans, 120, pp.7791- 7806. doi: 10.1002/2015JC011135. we investigate seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea. Using weekly operational sea ice charts produced by Arctic and Antarctic Research Institute (AARI, Russia) from 1999 to 2013 we identiﬁed ﬁve main key events that characterize the annual evolution of fast ice in the region. Linking the occurrence of the key events with the atmospheric forcing, bathymetry, freezeup and melt onset, we examined the processes driving annual fast ice cycle. The study showed that fast ice extent in the Laptev Sea is primarily controlled by thermodynamic processes. However, some mechanisms of fast ice formation in the region were not understood due temporal resolution of the applied AARI fast ice climatology. Therefore, in the second paper:

Selyuzhenok, V., Mahoney, A. R., Krumpen, T., Castellani, G., Gerdes, R. (accepted for publication in Polar Research, 13 June 2017): Mechanisms of fast ice development in the southeastern Laptev Sea: A Case study for winter of 2007/08 and 2009/10. we use high-resolution satellite imagery and in-situ ice thickness measurements to investigate mechanisms contributing to the advance of fast ice edge to its winter location in the southeastern Laptev Sea. Contrary to previous studies, we conclude that grounding is a key mechanism of fast ice development in the region.

Comparing seasonal fast ice cycle in the Laptev and East Siberian Seas we found that the fast ice regimes in the two regions diﬀer signiﬁcantly. In the third paper:

Selyuzhenok, V., Krumpen, T., Leppäranta, M, Gerdes, R, Haas. C. (in preparation) East Siberian Sea fast ice: Interannual variations in winter extent and linkage with atmospheric forcing. we focus on the mechanisms distinguishing Laptev Sea and East Siberian fast ice regimes. Unlike in the Laptev Sea, East Siberian Sea fast ice showed high interannual variability in maximal winter extent. A bimodal fast ice coverage, characterized by years of high fast ice extent reaching far oﬀshore, and low fast ice extent limited to shallow water (less than 20 m) was identiﬁed using the same fast ice climatology applied in Paper 1. To better understand mechanisms contributing to the bi-modal distribution, individual modes 8 Chapter 1 Introduction were compared (air temperature, accumulated freezing degree days) and dynamic factors (local wind speed and direction, arctic osculation index, ice drift).

A case study presented in fourth paper:

Wegner, C., Wittbrodt, K., Hölemann, J. A., Janout, M. A., Krumpen, T., Se- lyuzhenok, V., Novikhin, A., Polyakova, Ye., Krykova, I., Kassens, H., Timo- khov, L.(2017): Sediment entrainment into sea ice and transport in the Trans- polar Drift: A case study from the Laptev Sea in winter 2011/2012, Continen- tal Shelf Research,141, pp.1-10. doi: https://doi.org/10.1016/j.csr.2017.04.010. provides an example of how local events on the Siberian shelf contribute to the Arctic- wide processes. Large volume of sediment-laden sea ice forms on the Laptev Sea during freezeup. The ice is then transported with the Transpolar drift towards the Fram straight. The sedimatns released during the ice melt, settle on the sea-floor and serve as a proxy for Arctic ice-transport on geological time scales. In the paper, the process of sediment incorporation in the fast ice cover were investigated using field data and satellite imagery. The analysis showed that the sediment incorporation during a coastal polynya event provide a significant contribution to the variability of the Laptev Sea’s sediment budget. Reduction of fast ice stability leading to mid-winter breakup events might then impact the regional sediment budget and further have consequences for radiation balance within the export pathways of the Laptev Sea ice in the Transpolar Drift. Chapter 2

Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013

Reprinted from Journal of Geophysical Research: Oceans, 120, 7791 - 7806, V.Selyuzhenok1, T. Krumpen1, A. Mahoney2, M. Janout1, and R. Gerdes1,3, Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013, with permission of the American Geophysical Union.

1Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremer- haven, Germany 2Geophysical Institute, University of Alaska, Fairbanks, AK, United States 3Jacobs University Bremen, Bremen, Germany

9 10 Chapter 2 Laptev Sea fast ice PUBLICATIONS

Journal of Geophysical Research: Oceans

RESEARCH ARTICLE Seasonal and interannual variability of fast ice extent in the 10.1002/2015JC011135 southeastern Laptev Sea between 1999 and 2013

Special Section: V. Selyuzhenok1, T. Krumpen1, A. Mahoney2, M. Janout1, and R. Gerdes1,3 Forum for Arctic Modeling and Observational Synthesis (FAMOS): Results and 1Alfred-Wegener-Institut Helmholtz-Zentrum fur€ Polar- und Meeresforschung, Bremerhaven, Germany, 2Geophysical Synthesis of Coordinated Institute, University of Alaska, Fairbanks, Alaska, USA, 3Department of Physics and Earth Sciences, Jacobs University Experiments Bremen, Bremen, Germany

Key Points: Annual fast ice cycle in the Abstract Along with changes in sea ice extent, thickness, and drift speed, Arctic sea ice regime is charac- southeastern Laptev Sea is terized by a decrease of fast ice season and reduction of fast ice extent. The most extensive fast ice cover in characterized the Arctic develops in the southeastern Laptev Sea. Using weekly operational sea ice charts produced by The main factors controlling annual fast ice cycle are revealed Arctic and Antarctic Research Institute (AARI, Russia) from 1999 to 2013, we identified five main key events The trends in timing of the annual that characterize the annual evolution of fast ice in the southeastern Laptev Sea. Linking the occurrence of cycle are estimated the key events with the atmospheric forcing, bathymetry, freezeup, and melt onset, we examined the processes driving annual fast ice cycle. The analysis revealed that fast ice in the region is sensitive to thermody- Correspondence to: namic processes throughout a season, while the wind has a strong influence only on the first stages of fast V. Selyuzhenok, [email protected] ice development. The maximal fast ice extent is closely linked to the bathymetry and local topography and is primarily defined by the location of shoals, where fast ice is likely grounded. The annual fast ice cycle Citation: shows significant changes over the period of investigation, with tendencies toward later fast ice formation Selyuzhenok, V., T. Krumpen, and earlier breakup. These tendencies result in an overall decrease of the fast ice season by 2.8 d/yr, which A. Mahoney, M. Janout, and R. Gerdes is significantly higher than previously reported trends. (2015), Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013, J. Geophys. Res. Oceans, 120, 7791–7806, doi:10.1002/ 2015JC011135. 1. Introduction Numerous studies report that Arctic sea ice cover has experienced significant changes during the last three Received 11 JUL 2015 Accepted 29 OCT 2015 decades. Total Arctic sea ice extent shows a negative trend in all months since 1979, with a larger magnitude Accepted article online 2 NOV 2015 for the recent decade [Comiso and Hall, 2014; Meier et al., 2014]. Along with the reduction of total extent, there Published online 12 DEC 2015 are indications of sea ice thinning [Rothrock et al., 1999; Kwok et al., 2009; Laxon et al., 2013] and increased sea ice drift speed [Spreen et al., 2011] and deformation rate [Herman and Glowacki, 2012]. Long-term changes were also found in the fast ice regime. Investigating Kara Sea fast ice, Divine et al. [2003] found a reduction in fast ice area in March–May, 1990–2000 relative to 1950–1960. Mahoney et al. [2014] report on a decrease of fast ice extent and a trend toward later formation and earlier disappearance of fast ice in the Chukchi Sea during the last four decades. In addition, there are indications of fast ice thickness loss in the Siberian Arctic [Poly- akov et al., 2003, 2012]. These regional changes are reflected in Arctic-wide reduction in fast ice area and shortening of the fast ice season in the 1990s reported by Yu et al. [2014]. Although fast ice only comprises a small fraction of overall Arctic sea ice extent, it is of particular importance for the coastal systems for a number of reasons. The fast ice edge defines the location of polynyas and thereby controls local ocean processes governed by sea ice formation and brine rejection, as well as atmospheric mesoscale motion [Maqueda et al., 2004]. Fast ice damps tidal motion and influence mixing processes by blocking the momentum flux from the atmosphere to the ocean [Proshutinsky et al., 2007]. In central and VC 2015. The Authors. east Siberia, bottom-fast ice helps to maintain submarine permafrost and protects the coast from erosion This is an open access article under the terms of the Creative Commons [Rachold et al., 2000]. The presence of bottom-fast ice controls the spring freshwater outflow in the vicinity Attribution-NonCommercial-NoDerivs of river deltas [Are and Reimnitz, 2000]. In the Laptev Sea, fast ice plays a crucial role in the freshwater cycle License, which permits use and of the ocean by storing a great amount of riverine freshwater in winter and releasing it in summer [Bareiss distribution in any medium, provided and Gorgen, 2005; Eicken et al., 2005]. Fast ice also affects human activities. In the western Arctic, it serves as the original work is properly cited, the a platform for traditional hunting and fishing. The distribution of fast ice has significant implications for use is non-commercial and no modifications or adaptations are polar marine navigation and offshore exploration, particularly for the seas situated along the North-East pas- made. sage [Johannessen et al., 2005; Hughes et al., 2011].

SELYUZHENOK ET AL. FAST ICE EXTENT IN THE LAPTEV SEA 7791 11

Journal of Geophysical Research: Oceans 10.1002/2015JC011135

Fast ice forms seasonally in the majority of the Arctic marginal seas. The winter extent of fast ice varies strongly on a regional scale from tens of kilometers along Alaska’s coast to hundreds of kilometers in the southeastern Laptev and East Siberian Seas. The regional differences in fast ice extent are often associated with local topography and bathymetry. On average, the fast ice edge is located within the 10–25 m depth range [Zubov, 1945; Divine et al., 2004; Mahoney et al., 2007a, b]. However, the factors governing interannual and seasonal variability of fast ice extent differ from region to region. According to Dmitrenko et al. [1999], the interannual variations in the location of fast ice edge in the Kara, Laptev, and East Siberian Seas are controlled by river runoff. In contrast, Divine et al. [2004, 2005] found that the typical maximum extent of fast ice in the Kara Sea is sensitive to the dynamic atmospheric forcing and the variability of fast ice extent can be explained by variations in surface winds and air temperature. In contrast to the Kara Sea, the typical maximum extent of fast ice along the northern Alaskan coast appears to be controlled largely by local bathymetry, although there is evidence of diminished fast ice extent in the Chukchi Sea since the 1970s [Mahoney et al., 2014]. In the Laptev Sea, fast ice processes are closely linked with the Lena River runoff. First, Laptev Sea fast ice is primarily composed of the river water [Eicken et al., 2005]. Second, there are indications that the position of fast ice edge in winter is predefined by the intensity of Lena River summer runoff [Dmitrenko et al., 1999]. Third, spring fast ice breakup in the region is triggered when nearshore fast ice is flooded by river water [Bareiss et al., 1999]. Although the southeastern Laptev Sea is characterized by the widest fast ice extent in the Arctic, no study has investigated the linkage between fast ice climatology and atmospheric forcing and bathymetry. The first aim of this study is to examine seasonal evolution of fast ice extent in the southeastern Laptev Sea and link it to the onset of freezeup and melt, air temperature, wind, and bathymetry by analyzing 14 annual fast ice cycles between 1999 and 2013. As fast ice extent and duration of fast ice season has decreased during the last decades, our second aim is to examine the interannual variability and timing of fast ice season in the region.

2. Data and Methods 2.1. AARI Charts The information on fast ice extent used in this study is taken from operational sea ice charts provided by the Arctic and Antarctic Research Institute (AARI), Russia. AARI produces the charts since 1933 to support marine navigation and to assist other commercial and scientific purposes. The charts show total sea ice concentration, partial concentration of different stages of sea ice development and fast ice. Sea ice conditions are mapped manually based on air reconnaissance flights, ship reports, observations from polar meteorological stations, drift buoys, and satellite imagery. A detailed description of data sources and chart production are provided in Mahoney et al. [2008]. Due to limited observational data, temporal and spatial coverage of charts are inconsistent from 1933 to 1998. Since 1999, the frequency of coverage is higher because charts are primarily based on satellite remote sensing data. Detailed regional charts for the Eurasian Arctic shelf seas are available on a weekly basis in a vector Sea Ice Grid format (SIGRID-3). Fast ice is classified based on the criteria of immobility as well as other visual attributes such as absence of leads in the sea ice cover. The information analyzed by an expert is compiled for a period of 2–5 days prior to the issue date while the previous chart is used as a reference. Therefore, fast ice is defined as sea ice cover which remains stationary along the coast during a period of 2–7 days. In this study, 524 charts covering the period from October 1999 to December 2013 were used [World Mete- orological Organisation, 2013]. For practical reasons, we converted the vector format to a grid (EASE-Grid 2.0) with 1.25 km cell size for the region of interest (Figure 1). Hereafter, the gridded data are referred to as AARI charts. Although the temporal and spatial data coverage is highest for the period after 1998, there are no data available between January and July 2002. There are a number of 1–2 week gaps occurring sporadi- cally in the data set.

2.2. Identification of Key Events and Periods of Annual Fast Ice Cycle Seasonal development of fast ice area in the southeastern Laptev Sea follows a characteristic pattern (Figure 2) with a rapid advance of fast ice in fall, small variability in winter and rapid decline in summer. We defined five key events describing this pattern (Figure 3): beginning of fast ice season (Key event 1), beginning and end of the rapid development (Key events 2 and 3), beginning of breakup (Key event 4), and end of fast ice season (Key event 5). These events were identified automatically using arbitrary thresholds for fast ice area and speed

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Figure 1. Region of interest and bathymetry. The red box indicates the area of the southeastern Laptev Sea for which the analysis was performed. The dash line shows the mean maximal fast ice extent between 1999 and 2013. The compass rose in the bottom left corner shows the four sectors (N, E, S, and W) which correspond to the analyzed wind directions (see section 2.4.4). of areal growth presented in Table 1. The date of a speciﬁc key event is related to the date of chart issue. Because the maps are made from up to 1 week old information, the event dates may be biased up to 6 days. We assume that the error associated to this is normally distributed. The key events divide the fast ice season six periods: Period 1: Preformation, Period 2: Initial formation, Period 3: Rapid development (RDP), Period 4: Period of maximal extent, Period 5: Breakup (Figure 3).

2.3. Accuracy of AARI Charts AARI does not provide an uncertainty estimate for the operational charts produced since 1998. However, the errors in ice edge location for the chart issued before 1998 vary from 2–10 [Polyakov et al., 2003] to 50 km [Mahoney et al., 2008]. In general, the quality of operational sea ice charts depends strongly on the resolution of the input data and the expertise of sea ice analysts. With the introduction of high-resolution satellite data in the mapping process after 1998, the quality of charts was signiﬁcantly improved. In order to assess the quality of AARI charts for the period of our investigation, we compared them with fast ice maps derived from ENVISAT Synthetic Aperture Radar (SAR) imagery. The SAR images were acquired for the southeastern Laptev Sea between 2003 and 2012 and have a pixel resolution of 1503150 m. The fast ice edge was mapped manually based on visual discrimination between motionless fast ice and drifting pack ice from consecutive image pairs. The average time span between images in a pair is 3–7 days, which is consistent with the frequency of fast ice maps issued by AARI. Like the AARI charts SAR-based maps represent snapshots of fast ice extent on the date of the latest image in a pair. Overall, we obtained 73 maps of fast ice extent from the time series of SAR images. Most of the SAR scenes were acquired between January and April, when fast ice was at its maximal winter extent. Only a few scenes cover the RDP and no scenes were acquired during Breakup period.

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Journal of Geophysical Research: Oceans 10.1002/2015JC011135 2 km 3 Area, 10

Figure 2. Annual cycle of fast ice area between 1999 and 2013.

Figure 4 shows a cross comparison of fast ice areal extent between the SAR-based data and the AARI charts. The difference between the data sets is smallest when fast ice extent is relatively small or close to the maximum. The highest deviations correspond to the RDP. By interpretation of SAR images, we encountered difﬁ- culties discriminating between pack ice and fast ice during this period, since the transition from drifting to motionless state is often subtle. Therefore, it is likely that the differences between the data sets during the

Duration of fast ice season

2 3 4 2.Initial formation 4. Maximal extent

1.Pre-formation 3.Rapid development 5.Breakup 2 km 3

events of rapid Melt Freezeup development End of season Area, 10 5 Beginning of season 1

Figure 3. A typical annual fast ice cycle (2000–2001). The key events are numbered and the periods of annual fast ice cycle are labeled in blue.

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RDP are attributed to subjective Table 1. Key Events and Identification Criteria classification of sea ice types. Due Key Event Identification Criteria to the high inaccuracies in fast ice Beginning of season Fast ice area reaches 5 3 103 km2 classification, we neglected the (4% of maximal area) correspond to narrow strip of fast ice along the coast single events of rapid develop- Beginning of RDP Beginning of the first event when the ment (Figure 3) and considered speed of mean weekly areal development exceeds 14 3 103 km2 only the dates of the beginning End of RDP End of the last event when the speed and end of the period (Key events of mean daily weekly 2 and 3). Excluding the RDP, we development exceeds 14 3 103 km2 Beginning of breakup Beginning of the first event when the estimated the mean deviation speed of mean weekly areal between the two data sets as 3 2 decrease exceeds 10.5 3 10 km 2:03103 6 of 2.3 3 103 km2. End of breakup/End Fast ice area drops below 5 3 103 km2 of season (4% of maximal area) 2.4. Ancillary Data 2.4.1. Bathymetry We used the International Bathy- metric Chart of the Arctic Ocean (IBCAO Version 3 [Jakobsson et al., 2012]) in order to retrieve water depth at the location of the fast ice edge for every AARI chart. The IBCAO grid is in Polar Stereographic projection and has a resolution of 5003500 m. It was regridded to the 1.25 km EASE-Grid by nearestneighborinterpolation.Sincethe IBCAO depths for the Russian marginal seas are primarily derived from Russian nautical charts contours, the distribution of water depths in the region shows artificial modes at water depths multiple of 5. In order to remove the artificial modes, we used 5 m bin width to derive histograms of water depth occupied by fast ice edge. 2.4.2. Onset of Freezeup and Melt To link the key events of the annual fast ice cycle to the onset of freezing and melting season, we used the Arctic-wide maps of freezeup and melt onset derived from SSM/I/SMMR brightness temperatures [Markus et al., 2009]. The data are mapped to the 25 km polar stereographic grid and contain information on dates of early (the first occurrence of melting/freezing conditions) and permanent freezeup/melt. In this study, we define freezeup and melt onset as the mean dates of the first occurrence of freezing or melting conditions in the region. 2.4.3. Freezing and Thawing Degree Days We examined cumulative freezing (FDDs) and thawing (TDDs) degree days in order to understand the influence of air temperatures on seasonal development and interannual variations in fast ice extent. Cumulative degree days were calculated Fast Ice Area, 103 km2 from NCEP daily 2 m air temperature [Kalnay et al., 1996]. First, mean daily air temperatures for the region of interest were extracted. Then, FDDs were calculated as a sum of negative temperatures since the onset of freezeup. TDDs were calculated as a sum of positive tempera-

SAR ture since the onset of melt. 2.4.4. Wind Speed and Direction In order to analyze the effect of different wind directions and speed on the evolution of fast ice area, we derived wind speeds for four directions (N, E, S, and W) shown in Figure 1. AARI Taking into account that on average the ice drift deviates by Figure 4. Cross comparison of fast ice area derived from AARI charts and SAR imagery between 2003 and 2012. The white circles correspond to area estimates made during the 208 [Lepparanta€ , 2011] from the RDP, and the blue circles indicate estimates made outside this period. wind direction, the wind sectors

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were set in a way that N and E correspond to the wind advecting ice offshore from the mainland (N) and the Lena Delta (E), and S and W wind cause onshore ice drift. The wind analysis was performed for four periods of annual fast ice cycle: Preformation, Initial formation, Rapid development, and Breakup periods. First, 6-hourly wind speed and direction were derived from the reanalysis data (NCEP 10 m wind) [Kalnay et al., 1996] for the region of interest. Then the scalar wind speed values were assigned to one of four sectors based on the direction. For each period, we derived sector’s mean wind speed as a sum of wind speeds in a sector divided by a total number of measurements for a period. Therefore, the mean wind speed of a sector characterizes the intensity of the wind for the individual periods. In the following, we compare the duration of the four periods with the mean wind speed in four directions. 2.4.5. Lena River Runoff and Breakup To identify the date of Lena River breakup, we use the discharge data from the Kusur gauging station (70.708N/127.658E) located around 200 km south of the Lena Delta. According to Bareiss et al. [1999], breakup of fast ice in the vicinity of the Lena Delta is associated with the breakup of the Lena River. The authors ﬁnd the strongest connection between the annual maximal discharge at Kusur station and early sea ice melt signal. To be consistent with their study, we deﬁne the Lena River breakup as the date when spring discharge at the Kusur station reaches its maximal value.

3. Results 3.1. Variability of Fast Ice Extent Figure 2 shows 14 annual cycles of fast ice development from October to July. It illustrates that the interannual variability of fast ice extent is very low in February–June and higher in October–January and July. In most years, the extent is within 12:83103 km2 of the 14 years mean for any given week of a month (for February–June) and within 37:53103 km2 (for October–January and June). Only two annual cycles (1999 and 2009) showed an exceptional behavior. In fall 1999, fast ice started to develop remarkably early, after which the development of fast ice area slowed down and the winter extent was reached relatively late in the season. The year 2009 is characterized by a distinct winter breakup event in January–February, which was not observed in any of the other 12 annual cycles. The spatial variability of fast ice extent can be seen in Figure 5. The monthly maps were derived by stacking all available AARI charts for each calendar month. High occurrence regions (shown in red) indicate the patterns of fast ice extent common to each calendar month, while regions with lower fast ice occurrence provide information on interannual variability (e.g., the exensive blue region in October corresponds to the early advance in 1999). As Figure 5 illustrates, fast ice starts forming as a narrow band along the Lena Delta shore, and the Yana Bay in October–November. Next, fast ice fills the Buor-Khaya Bight. During December–January, fast ice expands in the north-west direction connecting the shore of Yana Bay with the New Siberian Islands. The fast ice edge east of the Lena Delta at this stage of development has a characteristic u-shaped configuration. The tendency of fast ice to advance into shallower waters first (see section 3.4) is demonstrated by the higher occurrence frequencies seen over the shoal north of Stolbovoy Island in December (Figure 5). In Feb- ruary–March, fast ice is still slowly advancing seaward, but the increase in area does not exceed 8%. The maximal extent is reached in March–April, and thereafter this, the fluctuations of the extent are very small and do not exceed 4.5%. The winter maximal extent does not vary significant from year to year (Table 2), as well as shape and location of fast ice edge at the maximal extent. The first indication of fast ice breakup can be seen as a decrease in occurrence frequencies along the Lena Delta in Figure 5 in June. The summer breakup is more abrupt than the rapid development in fall. While in June, the fast ice area remains close to its maximum extent, there is no area in the Laptev Sea that remains covered by fast ice throughout the month of July for the entire observation period. Breakup of fast ice starts along the Lena Delta and progresses eastward. At the same time, the seaward fast ice edge retreats to the south. The fast ice cover in-between the New Siberian Islands breaks up last. This spatial pattern of fast ice disintegration is different to the advance of fast ice in fall. In fall, the fast ice advances in a southeast-to- northwest direction, while the summer fast ice edge retreats mainly from the west to the east. However, the u-shape pattern of low frequencies east of the Lena Delta is characteristic for both the advancement of fast ice in fall and its retreat in summer. This area becomes covered with fast ice last and gets free of fast ice first.

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Figure 5. Monthly frequency of fast ice occurrence. The maps are derived by stacking all available fast ice maps for each calendar months. The color code represents at which fraction of the stacked maps fast ice was present. The isobaths are shown in black, thick contour corresponds to 20 m water depth.

3.2. Timing of Key Events We identified the timing of the key events described in section 2.2 in each of the annual fast ice cycles from 1999 to 2013. Due to a gap in the AARI data set in winter 2002, the identification of the Key events 3, 4, and 5 was not possible for this period. The interannual variability and trends in the timing of the five key events and corresponding periods of annual fast ice cycle is shown in Figure 6. Minimal, maximal, and mean, as well as the standard deviation of the timing of key events are presented in Table 3. On average, the fast ice season starts on the first week of November, which is 25 (68.4) days after the onset of freezeup. The season ends on the first week of June, 51 (64.7) days after melt onset. The interannual variability in timing of the Key events 1 and 5 is remarkably low (Figure 6c). However, there are statistically significant tendencies toward later beginning and earlier end of fast ice season. These tendencies result in a decrease of the fast ice season by 22.9 d/yr (Figure 6d). The RDP starts between October and December. In three out of 14 seasons, the beginning of rapid development coincides with the onset of fast ice formation. For the other seasons, the time lag between these two key events (Key events 1 and 2) ranges between 2 and 11 weeks. The beginning and end of rapid development (Figure 6a) shows twice as high variability in timing compared to the other key event (Table 3). The duration of RDP varies from 1 to 13 weeks. The following period of Maximal extent lasts for 22 6 4 weeks and its duration does not show any interannual changes.

Table 2. Variability of Maximal Areal Extent In contrast, the Breakup period tends to Area (103 km2) Datea become shorter (Figure 6b). Mean SD Min Max Mean SD (days) Min Max Overall, the timing of the key events 134.4 0.6 (4.5%) 123.9 141.9 13 Mar 34 6 Feb 3 Jun exhibits low interannual variability,

aThe ﬁrst date after which areal increase does not exceed 4.5%. except for the beginning and end of

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rapid development. We also found trends in timing of the marginal events of the annual fast ice cycle. While timing of the beginning and end of the fast ice season is shifting, there are no statistically signiﬁcant trends in the timing of the RDP, beginning of breakup, as well as duration of the Maximal extent period (Table 4).

3.3. Wind Speed and Direction Figure 7 shows the time series of mean wind speeds over four periods of annual fast ice cycle (Peri- ods1,2,3,5)fordirectionsN,E,S, and W (for the deﬁnitions see section 2.4.4 and Figure 1) together with duration of the periods. The wind speeds are consistent between the periods and show low interannual variability. On average, the mean wind speed for any of the four sectors varies between 0 and 2 m s21 rarely exceeding 3 m s21. Comparing the duration of the four periods with the time series of wind speed, we found strong to moderate correlations for periods of Preformation and Initial

Figure 6. Timing of key events and duration of corresponding periods of annual fast ice formation and weak or no corre- cycle. The events with star and two stars sign show a trend signiﬁcant at 99% and 90% lations for RDP and Breakup conﬁdence level correspondingly. (Table 5). Overall, correlations for the Preformation period are higher than for the other periods, indicating a stronger relationship with the wind forcing. Remarkably, the correlations for the offshore (N: r 5 0.48, p 5 0.07; E: r 5 0.73, p < 0.01) and onshore (S: r 520.35, p 5 0.21; W 520.57, p 5 0.03) winds are comparable in magnitudes and have opposite signs. The duration of the Preformation period decreases with stronger onshore winds (S and W) and weaker offshore wind (N and E), and vice versa. This suggests the importance of mechanical fast ice growth due to advection of pack ice toward the shore. Although the S winds show a strong correlation with the duration of Initial formation, there is no causal relationship between the variables. The positive relationship between the onshore sector and the duration of Initial formations is based on three extreme years, when the duration of Initial Table 3. Variability of Dates of the Key Events formation was minimal and characterized Key Event Mean SD (days) Min Max by absence of S winds. However, S wind is 1. Beginning of 1 Nov 10 17 Oct 17 Nov also absent in years with relatively long fast ice season 2. Beginning of RDP 2 Dec 20 20 Oct 28 Dec duration of Initial formation (e.g., 2001 3. End of RDP 23 Jan 24 5 Dec 7 Mar and 2002). In addition, the wind speed 4. Beginning of breakup 23 Jun 8 8 Jun 7 Jul and its variation are very low (below 1 m 5. End of season 19 Jul 9 3 Jul 30 Jul s21) throughout the time series.

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3.4. Water Depth at Fast Ice Edge Table 4. Trends in Timing of Key Events and Periods of Annual Fast Ice Cycle 2 In this section, we examine the vari- Key Event/Period Trend (d/yr) prrest ability of water depth occupied by the 1. Beginning of season 1.7 <0.01 0.56 0.4 2. Beginning of RDP 0.0 0.98 <0.01 1.3 fast ice edge during the annual cycle. 3. End of RDP 0.4 0.07 0.02 1.6 Figure 8 shows the distribution of 4. Beginning of breakup 0.3 0.63 0.02 0.6 depths at the location of the fast ice 5. End of season 21.0 0.06 0.26 0.5 Rapid development (RDP) 20.3 0.92 <0.01 2.4 edge for each month. Mahoney et al. Maximal extent 21.4 0.46 0.05 1.8 [2007a, 2014] suggest that the most Breakup 21.3 0.05 0.30 0.6 frequently observed water depths cor- Fast ice season 22.8 <0.01 0.63 0.6 respond to the depth at which the fast ice edge is most stable. The water depths occupied by the fast ice edge show a unimodal distribution. In October, the mode is at 0–5 m depths. In the following 6 months, the dominant mode gradually shifts from 10–15 to 15–20 m to greater depths as fast ice expands. This range corresponds to the most frequent depths in the region and therefore the frequencies of fast ice occurrence are expected to be higher between 10 and 20 m. Fast ice edge reaches the deepest location in March–April with the most frequent occurrence between 20 and 25 m. The beginning of fast ice breakup in June is characterized by small changes in the water depths distribution. While a considerably large areal decrease takes place in July, the water depths distributions at the fast ice edge are very similar to those found during winter.

Figure 7. Time series of wind speed in sectors N, E, S, and W (see Figure 1) over periods between key events, freezeup, and melt onset. The bold lines indicate wind directions which have the highest correlation with the duration of the corresponding period (see Table 5).

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Figure 8. Monthly histograms of water depth at fast ice edge.

4. Discussion In the following section, we link the seasonal and interannual variability of fast ice extent to the onset of freezeup and melt, air temperature (FDDs and TDDs), wind, bathymetry, and Lena River runoff. We follow the annual fast ice cycle and discuss each key event and period of fast ice development in the order they occur within a season.

4.1. Beginning of Fast Ice Season To form a stable motionless fast ice band along the coast, newly formed sea ice needs to reach a certain thickness that allows it to withstand wind, tidal and wave action. According to observations from the Rus- sian polar stations, formation of fast ice in the Laptev Sea starts when ice thickness reaches 5–10 cm, which takes place on average 10–15 days after freezeup [Karklin et al., 2013]. Compared to these observations, our analysis shows a longer time lag between the freezeup onset and beginning of fast ice season (25 6 8 days). The difference to the on-site observations is related to different definitions of the beginning of fast ice season. While observations refer to the first occurrence of fast ice at the coast, our definition corresponds to a more advanced stage of fast ice development (see section 1). Still, there is a strong correlation

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Table 5. Correlation Between Wind Speed and Duration of Periods of Annual Fast Ice Cycle Periods N p E p S p W p 1. Preformation 0.48 0.07 0.73 <0.01 20.35 0.21 20.57 0.03 2. Initial formation 0.08 0.79 20.16 0.57 0.55 0.03 20.19 0.49 3. Rapid development (RDP) 0.17 0.58 0.15 0.62 0.26 0.40 0.06 0.85 4. Breakup 20.22 0.47 20.15 0.59 20.08 0.78 0.08 0.79

between the onset of freezeup and the beginning of fast ice season (Table 6). This suggests that the beginning of the fast ice season in the southeastern Laptev Sea is controlled to a large extent by thermodynamic processes. Air temperatures and oceanic heat control sea ice growth rates and hence, the time needed to reach an ice thickness of 5–10 cm by thermodynamic growth, which is required to withstand external stresses. While year-round mooring observations from the deeper (>40 m) Laptev Sea shelf show surface warmed waters that may be trapped in the interior water column into fall and winter [Janout et al., 2013], significant amounts of heat were not observed in the shallower waters within the fast ice zone. Bauch et al. [2009] reported on a temperature maximum in the intermediate water layer, which persister under fast ice until May in the immediate vicinity of the Lena River outflow. However, based on their temperature profile, the amount of heat stored would only melt the equivalent of 4 cm of ice and was capped by strong stratification. More recent under fast-ice profiles from the area taken in April 2012 were generally at near-freezing temperature, but showed that salinity stratification can persist throughout the winter (unpublished data, M. Janout (2015)). Late fall profiles from September 2013 and 2014 (unpublished data, M. Janout (2015)) from shallow nearshore areas either show a fresher warmer surface layer above a cold and saline lower layer, or a well-mixed water column by tides and winds. These data indicate that storage of a significant amount of heat in the shallow (<20 m) water is unlikely. The oceanographic conditions in the Laptev Sea fast ice area are such that warm ocean temperatures may delay the first formation of sea ice. However, considering that the fast ice season starts 3 weeks after the freezeup, oceanic heat does not have a considerable impact on the Laptev Seas fast ice processes. In order to examine the influence of air temperature, we calculated FDDs between the onset of freezeup and the beginning of the fast ice season. As we consider the freezeup onset as a reference point for the calculations of FDDs, we assume that the water column is at a freezing temperature. Therefore, the FDDs reflect influence of the air temperature only. The high variability of FDDs (Table 7) indicates that the beginning of fast ice development is regulated by a dynamic component in addition to the thermodynamic processes. It is difficult to distinguish between the influence of thermodynamic and dynamic factors on fast ice formation. While atmospheric and oceanic heat fluxes impact thermodynamic sea ice growth, the wind contributes to ice growth by rafting and ridging. The time lag between freezeup and the beginning of fast ice season can also be affected by local wind conditions. According to Zubov [1945], the onshore wind favors development of fast ice by pushing pack ice toward the coast, while offshore wind may slow down the advance of fast ice by dragging pack ice away from the fast ice edge. In the southeastern Laptev Sea, fast ice first starts to form along the eastern shore of the Lena Delta and in the Yana Bay (Figure 5). The corresponding offshore winds (N and E) delay the formation of fast ice in the region as reflected by a positive correlation between wind speed and the delay of fast ice season relative to freezeup (Table 5). The onshore winds (S and W) have the opposite effect on fast ice formation, confirming the hypothesis of Zubov [1945]. On interannual time scales, the beginning of the fast ice season exhibits the highest rate of change compared to other key events during the annual fast ice. The trend toward a later Table 6. Correlation Between Key Events, Freezeup, and Melt Onset and Lena beginning of the fast ice season (1.7 d/ River Breakup yr) is consistent with a delayed Lena River Events Freezeup p Breakup p Melt p freezeup (1.5 d/yr) in the region. Both trends are statistically significant at Key event 1 0.62 0.01 Key event 2 0.29 0.29 99% confidence level. According to Key event 3 0.55 0.05 Markus et al. [2009], the Laptev Sea has Key event 4 0.54 0.09 0.26 0.38 the most significant delay in freezeup Key event 5 0.54 0.06 0.81 <0.01 since 1996 compared to other Arctic

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marginal seas. Further changes in timing of Table 7. FDDs and TDDs Accumulated Prior the Key Events freezeup onset are likely to be reflected in the Key Event Mean SD (%) Min Max timing of fast ice formation. FDDS Key event 1 333 46 85 573 4.2. Rapid Development Period (RDP) Key event 2 1119 43 203 1869 Key event 3 2578 27 1336 4095 Because the AARI charts have the highest TDDs uncertainties during the RDP (see section 2.3), Key event 4 31 46 8 55 Key event 5 83 18 57 112 we did not investigate the advance of fast ice within this period, but we rather focused on the two key events—the beginning and end of rapid development (Key events 2 and 3). In terms of areal extent, both events are characterized by a low variability (Figure 2). Also, the configuration of fast ice at the end of the RDP is consistent throughout the 14 years of investigation (Figure 9). The high frequencies (70–100%) of fast ice occurrence coincide with the location of the shoals (Figure 1). Reoccurrence of the fast ice edge at the same locations indicates that this configuration of fast ice has a high stability. This stability can be obtained by grounding of fast ice at the shoals. During most years, the rapid development of fast ice stops once fast ice connects Kotelny Island with the shoals and the Lena Delta (Figure 9). Therefore, we suggest that the location of the fast ice edge at the end of the RDP is defined by the local bathymetry. The beginning of the RDP does not appear to be linked with thermodynamic processes, since the timing of this key event is not correlated with the onset of freezeup (Table 6). In addition, the number of FDDs acquired prior to the beginning of rapid fast ice development exhibits high variability (Table 7). There are also no strong indications of a linkage between the wind forcing and timing of the event. Given the high variability in timing (Table 3), it is likely that the rapid development of fast ice is triggered by a combination of several processes which should be investigated using data sets of higher accuracies. While it is not clear which mechanisms control the beginning of rapid development, there are indications that thermodynamics defines the duration of the RDP. First, there is a correlation between the freezeup onset and the end of rapid development. Second, the variability of FDDs at the end of the RDP is relatively low (Table 7), suggesting a linkage between the two. Also, we find that the duration of the period has a strong connection to FDDs (Figure 10). The longest duration of the RDP correspond to the year 1999, when minimal number of FDDs was acquired prior to the beginning of rapid development. Vice versa, when the number of FDDs increases, RDP spans over a shorter period. This relationship indicates that rapid fast ice development is closely linked to sea ice thickness growth. A relatively thin sea ice cover can stay motionless over the vast areas in calm conditions; however, it is prone to breakup under the action of strong wind. Although the quality of AARI charts within the RDP has to be treated cautiously, we assume that the decrease in fast ice area in fall 1999 (Figure 2) is related to a breakup of thin fast ice cover. Thick ice, on the other hand, is more resistant to the dynamic forcing and therefore it needs a shorter time to reach the stable configuration since its advance does not alternate with events of breakup. The low variability of FDDs at the end of the rapid development period indicates that at the time fast ice area approaches its winter extent, the thickness of fast ice is consistent from year to year. This confirms that mechanisms responsible for rapid fast ice development are dependent on sea ice thickness.

4.3. Period of Maximal Fast Ice Extent The period of maximal fast ice extent corresponds to the time interval between the Key events 3 (end of rapid development) and 4 (beginning of breakup). Usually, by the end of the RDP, fast ice continues to expand at slow rate and reaches its absolute maximum in mid-March. On both interannual and seasonal time scales, the variations of maximal fast ice extent are very small. While local topography and bathymetry appear to define the stable configuration of the fast ice edge at the end of rapid development, it is unclear which factors control the further development of fast ice. According to Dmitrenko et al. [1999], small variations in winter fast ice extent are defined by the intensity of Lena River runoff and location of the fresh water plume. The fresh riverine water overflows more saline water heated by solar radiation during summer. The resulting strong stratification preserves the heat in the intermediate water layer. Dmitrenko et al. [1999] suggest that this heat is released during fall and winter at the periphery of the river plume which affects the location of fast ice edge. However, a comparison of the

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AARI winter fast ice extent with hydrographic patterns does not confirm the findings of Dmi- trenko et al. [1999]. For example, according to hydrographic surveys in the southeastern Laptev Sea, the winters of 2008 and 2009 were characterized by substantially different surface salinity patterns [Dmitrenko et al., 2010]. In 2008, Lena River outflow was shifted eastward by predominant westerly winds. In contrast, in 2009, river water accumulated near the Lena Delta due to easterly winds over the East Siberian Sea and northerly winds over the Laptev Sea. Although both hydrographic patterns differed from the long-term mean surface salinity distribution, we did not find significant variations between these two seasons in the winter location of the fast ice edge, its areal extent and transition through the annual key events. Figure 9. Frequency of fast ice occurrence (%) at the end of RDP (Key event 3). The dash line shows the mean maximal fast ice extent between 1999 and 2013. Bathymetry is another factor which is widely associated with the fast ice edge in winter, since the fast ice edge often reshapes isobaths of different depth. Along the Siberian coast the fast ice edge occupies depths of 20–25 m [Zubov, 1945]. These depths are characteristic for a typical location of fast ice edge in the southeastern Laptev Sea in March–April. In the Alaskan Arctic, there is a similar overall relationship between fast ice extent and bathymetry, which appears to depend on the presence of recurring grounded ice features distributed along the 1500 coast in water depths around 20 m [Mahoney et al., 2014]. In contrast, Laptev Sea fast ice lacks deformation features along the 1000 fast ice edge [Eicken et al., 2005]. Given that the maximal fast ice extent in the southeastern Laptev Sea does not differ significantly

FDDs at Key event 2 event Key FDDsat 500 from the fast ice extent at the end of RDP, we suggest that the maximal winter extent is prede- termined by the location of the 20 40 60 80 100 120 140 shoals, where the ice is Duration of RDP, days presumably grounded. Further advancement of fast ice to the Figure 10. Scatterplot between the duration of RDP and FDDs acquired prior to the beginning of rapid development (Key event 2). The correlation coefﬁcient between the variables greater water can result from a is 20.70 (p < 0.01). combination of several processes,

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60 i.e., mechanical attachment of pack ice during onshore drift events (or in absence of ice drift), 50 as well as attachment of young ice formed at the fast ice edge 40 during a polynya event. Since the changes in fast ice extent are rather small after the end of RDP, 30 based on this study it is impossi- days ble to attribute them to individ- 20 ual physical processes. Despite the reported warming 10 Breakup period and overall reduction of fast ice melt - Key event 4 extent in the Arctic [Yu et al., melt - Key event 5 2014], we did not find statisti- 0 2000 2002 2004 2006 2006 2010 2012 cally significant trends in maximal fast ice extent. Investigating Figure 11. The duration of Breakup period and time lags between melt onset and Key the variability of fast ice extent events 4 and 5. The correlation coefficient between the duration of Breakup period (blue) between 1979 and 2007, Yu and time intervals between melt onset and Key event 4 (red) and melt onset and Key et al. [2014] analyze the mean event 5 (green) are 20.89 (p < 0.01) and 0.46 (p 5 0.12), correspondingly. fast ice extent from January through March from operational charts. As fast ice is still advancing during January (Figure 5), the area of fast ice in this month does not reflect changes in maximal winter extent. We suggest that the reduction in fast ice area reported by Yu et al. [2014] is partly associated with a shift in timing of key events and shortening of Maximal extent period rather than the loss of the lateral extent.

4.4. Breakup Period and End of Fast Ice Season Breakup of fast ice in the Laptev Sea is linked with Lena River breakup [Bareiss et al., 1999; Bauch et al., 2013]. The role of the spring river runoff is twofold: (1) overflowing fast ice, riverine water decreases the surface albedo and (2) it contributes to the direct input of heat. In their investigation Bareiss et al. [1999] concluded that the river input plays only a local role in breakup near the Lena Delta and the major part of fast ice breaks up and melts due to atmospheric forcing. The pattern of fast ice retreat in July (Figure 5) also suggests a strong impact of river discharge on the breakup processes. The lowest frequencies of fast ice occurrence correspond to the area of Lena River discharge. As the fast ice breaks up along the shore, it continues to retreat eastward. The area of open water formed along the Lena Delta facilitates lateral melt of fast ice. A similar mechanism takes place in the vicinity of the Yana River mouth. The fast ice edge there retreats from the shore northward. As a result, fast ice shrinks to the center of the southeastern Laptev Sea where it is sta- bilized by the New Siberian Islands. Hence, the distribution of the water depths at the fast ice edge remains similar to winter months (Figure 8). The timing of fast ice breakup does not show any significant changes during the period of investigation. Confirming the results of Bareiss et al. [1999], we find a positive correlation between the Lena River breakup and the beginning of fast ice breakup (Table 6). The timing of Lena River breakup shows a small negative trend of 20.5 d/decade between 1935 and 2011, which is not observed on a shorter time scale. Moreover, the Lena River discharge in May increased by 63% since 1935 [Yang et al., 2002]. Consequently, more heat is provided by the river runoff at the beginning of the breakup period. Taking into account a strong relationship between the river breakup and breakup of fast ice and the long-term changes in Lena River hydrography, it is likely that the timing of fast ice breakup is also shifting on a longer time scale. In contrast to the beginning of breakup, the end of the fast ice season is strongly correlated to the onset of melt (Table 6) and it is tending to occur earlier in the season (Table 4). This tendency contributes to the shortening of the breakup period. However, the time lag between the onset of melt and beginning of fast ice breakup appears to have a stronger influence on the duration of the breakup period than the onset of melt itself (Figure 11). An increasing time lag between onset of melt and beginning of breakup allows for

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higher TDDs to be accumulated prior the breakup. As a consequence ice becomes more permeable due to higher porosity and/or presence of cracks. Therefore, the river water is not spread as far as in case of cold and less permeable ice and its sensible heat is transferred in a smaller region. However, the inﬂuence of this process on fast ice breakup can act in both directions. On one hand, the localized transport of sensible heat will lead to an increased internal melting of fast ice. On the other hand, the effect of decrease albedo will affect only a small area of the fast ice cover.

5. Conclusions By using AARI operational sea ice charts, we analyzed seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013. We identified five key events in each annual fast ice cycle and linked the occurrence of these events to freezeup and melt onset, air temperature (FDDs and TDDs), wind, bathymetry, and Lena River breakup. The analysis reveals that fast ice in the region is sensitive to thermodynamic processes throughout a season, while the wind has an influence only on the first stages of fast ice development. The beginning of fast ice season is correlated to the onset of freezeup in the region and the delay between freezeup and formation of fast ice is affected by wind. Eastward and southward winds drag pack ice away from the shore of the Lena Delta and Yana Bay where fast ice forms first, delaying the beginning of fast ice season. Westerly and northerly winds favor earlier formation of fast ice. While it is not clear what triggers the following rapid development of fast ice, the advance of fast ice is likely controlled by ice thickness growth, as certain ice strength is required to withstand dynamic forces. The per- sistence of the fast ice edge at the same location at the end of the RDP suggests that the bathymetry and local topography are important factors controlling lateral extent of fast ice. The variations in winter fast ice extent are very small. Although the changes in maximal fast ice extent were previously attributed to the variability of FDDs and Lena River spring discharge, we did not find any connection to these factors. Confirming the findings of Bareiss et al. [1999] we found a correlation between the Lena River breakup and beginning of fast ice breakup. The duration of breakup period has a strong relationship to the number of TDDs obtained between the onset of melt and Lena River breakup. Analyzing the timing of the fast ice key events, we found a decrease in duration of fast ice season of 2.8 d/yr. The rate of changes in the duration of fast ice season during the last 14 years is stronger than the one reported for the period between 1979 and 2007 by Yu et al. [2014]. The changes in the duration of fast ice season are caused by both a later beginning and earlier end of fast ice season. In its turn, an earlier end of fast ice season is related to a shortening of the period required for fast ice breakup. Acknowledgments This work was funded by Helmholtz Graduate School for Polar and Marine References Research POLMAR. The operational sea Are, F., and E. Reimnitz (2000), An overview of the Lena River Delta setting: Geology, tectonics, geomorphology, and hydrology, J. Coastal ice maps were obtained freely through Res., 16(4), 1083–1093. the World Meteorological Organisation Bareiss, J., and K. Gorgen (2005), Spatial and temporal variability of sea ice in the Laptev Sea: Analyses and review of satellite passive- project ‘‘Global Digital Sea Ice Data microwave data and model results, 1979 to 2002, Global Planet. Change, 48(1–3), 28–54, doi:10.1016/j.gloplacha.2004.12.004. Bank Project’’ (http://wdc.aari.ru/ Bareiss, J., H. Eicken, A. Helbig, and T. Martin (1999), Impact of river discharge and regional climatology on the decay of sea ice in the Lap- datasets/d0004/Lap/sigrid/). The tev Sea during spring and early summer, Arct. Antarct. Alp. Res., 31(3), 214–229, doi:10.2307/1552250. ENVISAT SAR images were obtained Bauch, D., I. Dmitrenko, S. Kirillov, C. Wegner, J. Holemann, S. Pivovarov, L. Timokhov, and H. Kassens (2009), Eurasian Arctic shelf hydrogra- through the European Space Agency phy: Exchange and residence time of southern Laptev Sea waters, Cont. Shelf Res., 29(15), 1815–1820, doi:10.1016/j.csr.2009.06.009. project ‘‘Formation, Transport and Bauch, D., J. A. 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Chapter 3

Mechanisms of fast ice development in the southeastern Laptev Sea: A Case study for winter of 2007/08 and 2009/10

Reprinted from Polar Research, 36:1, 1411140, V. Selyuzhenok1,3, A. Mahoney2, T. Krumpen3, G. Castellani3, and R. Gerdes3,4, Mechanisms of fast ice development in the southeastern Laptev Sea: A Case study for winter of 2007/08 and 2009/10.

1Nansen International Environmental and Remote Sensing Centre, St Petersburg, Russia 2Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK , United States 3Alfred Wegener Institute Helmoholtz-Zentrum für Polar- und Meeresforschung, Bre- merhaven, Germany 4Jacobs University Bremen, Bremen, Germany

27 28 Chapter 3 Mechanisms of fast ice development in the Laptev Sea

POLAR RESEARCH, 2017 VOL. 36, 1411140 https://doi.org/10.1080/17518369.2017.1411140

RESEARCH ARTICLE Mechanisms of fast-ice development in the south-eastern Laptev Sea: a case study for winter of 2007/08 and 2009/10

Valeria Selyuzhenok a,c,e, Andrew Mahoneyb, Thomas Krumpenc, Giulia Castellanid & Rüdiger Gerdesc aClimate Variability and Change in High Northern Latitudes, Nansen International Environmental and Remote Sensing Centre, St Petersburg, Russia; bGeophysical Institute, University of Alaska Fairbanks, University of Alaska, Fairbanks, AK, USA; cSea Ice Physics, Alfred Wegener Institute Helmoholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany; dPolar Biological Oceanography, Alfred Wegener Institute Helmoholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany; eDepartment of Cartography & Geoinformatics of the Institute of Earth Sciences, St Petersburg State University, St Petersburg, Russia

ABSTRACT KEYWORDS Accurate representation of fast ice in numerical models is important for realistic simulation of Landfast ice; stamukha; SAR; numerous sea-ice and ocean variables. In order to simulate seasonal and interannual varia- EM sea-ice thickness; bility of fast-ice extent, the mechanisms controlling fast-ice development need to be thor- Lagrangian drift oughly understood. The objective of this paper is to investigate mechanisms contributing to the advance of fast-ice edge to its winter location in the south-eastern Laptev Sea. The study ABBREVIATIONS is based on time series of synthetic aperture radar (SAR) imagery for winter 2007/08 and EM: electromagnetic; ENVISAT: Environmental 2009/10. A detailed examination of SAR-based ice drift showed that several grounded ice Satellite; GDSIDB: Global features are formed offshore prior to fast-ice expansion. These features play a key role in Digital Sea Ice Data Bank, offshore advance of the fast-ice edge and serve as stabilizing points for surrounding pack ice maintained by the World as it becomes landfast. Electromagnetic ice thickness measurements suggest that the Meteorological Organization grounded ice ridges over water depths of ca. 20 m water might be responsible for interannual and the Arctic and Antarctic variations in fast-ice edge position. Contrary to previous studies, we conclude that grounding Research Institute (St. is a key mechanism of fast-ice development in the south-eastern Laptev Sea. Petersburg); IPS: upward- looking ice-profiling sonar; SAR: synthetic aperture radar

Fast ice is a dominant sea-ice feature of the Arctic winter fast-ice extent appears to be controlled largely coastal region. Accurate representation of fast ice is by a system of grounded pressure ridges, which sta- found to be important for realistic simulations of bilize the fast-ice edge at depths of around 20 m Arctic sea-ice concentration and thickness (Reimnitz et al. 1994; Mahoney et al. 2007). The (Jakobsson et al. 2012), ocean height (Proshutinsky presence of grounded ice island and tabular icebergs et al. 2007), Arctic halocline stability (Itkin et al. leads to the formation of extensive fast-ice cover 2015) and upwelling of North Atlantic water north-east of Greenland (Hughes et al. 2011). The (Pickart et al. 2011). The majority of today’s coupled Laptev Sea and East Siberian Sea are characterized sea-ice–ocean models are not capable of representing by the broadest fast-ice extent in the Arctic. Because seasonal variability of fast-ice extent. To improve ice– of geographical similarity of the two regions, the East ocean models and successfully incorporate fast ice, Siberian Sea and Laptev Sea fast-ice covers are con- the mechanisms controlling seasonal fast-ice develop- sidered to have similar characteristics (Timokhov ment need to be further explored and thoroughly 1994); however, there is no comprehensive study of understood. the East Siberian fast ice. In the south-eastern Laptev The lateral extent of fast ice as well as the mechan- Sea, the fast-ice edge advances to 20–25 m water isms controlling it differs on a regional scale. In the depth (Selyuzhenok et al. 2015). However, the pro- Kara Sea, fast ice forms between a chain of islands cesses leading to the development of up to 500 km- and the mainland, extending up to 300 km offshore wide fast-ice cover in the south-eastern Laptev Sea over waters deeper than 100 m (Divine et al. 2004; are not well-understood. According to previous stu- Olason 2016). The interannual variability of Kara Sea dies (Reimnitz et al. 1994; Eicken et al. 2005), the lack fast-ice extent is linked to the prevailing atmospheric of ridges of significant height along the fast-ice edge circulation patterns (Divine et al. 2005). A narrower indicates that the extent of fast ice is not directly 5–50 km fast-ice band forms along the Alaska coast controlled by ice deformation and the grounding in the Chukchi and Beaufort seas. There, the typical position of the deepest pressure ridge keels.

CONTACT Valeria Selyuzhenok [email protected], 14 liniya V.O. 7, St Petersburg 199034, Russia Supplementary material for this article can be accessed here. © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 29

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In the south-eastern Laptev Sea the annual fast-ice cycle begins with a gradual advance of the fast-ice edge to water depths around 10 m. This is typically followed by a series of rapid development events, which advance fast-ice edge to its maximum winter location, which it occupies from February to July. From the lack of deformed ice, Eicken et al. (2005) concluded that fast ice in the Laptev Sea develops via a gradual accretion of ice floes, while Karklin et al. (2013) suggested that a shift in atmospheric circulation from offshore to onshore wind triggers rapid fast-ice development. Based on a 14-year time series from operational sea-ice charts, Selyuzhenok et al. (2015) suggested that the time required for fast ice Figure 1. Annual development of fast-ice area in the south- in the Laptev Sea to reach its maximum winter extent eastern Laptev Sea (71–77°N/125–139°E), derived from depends on the growth rate of the sea-ice thickness. GDSIDB operational sea-ice charts (WMO 2016). The grey However, the accuracy and temporal resolution of curves show mean fast-ice area (thick line) and two standard – fast-ice data used by Selyuzhenok et al. (2015) did deviations (dashed line) calculated for 1999 2013 (from Selyuzhenok et al. 2015). The blue and red curves show the not allow a conclusive analysis of any linkage to the fast-ice areas in 2007/08 and 2009/10, respectively, and the direction of cross-shore winds. vertical lines indicate the periods of investigation. In this paper, we investigate more closely the mechanisms contributing to the advance of fast-ice edge to its winter location in the south-eastern Laptev Lagrangian drift of sea-ice features in the area by Sea through a combination of high-resolution satellite manually tracking the features on consecutive and observational data. Using time series of SAR images. The features were selected such that they images, we track the development of fast ice in the were well distributed over the whole area and had winters of 2007/08 and 2009/10. Then we analyse recognizable backscatter patterns to allow for fea- patterns of fast-ice development and wind conditions ture tracking. In the course of investigation some in the two seasons. Last, the sea-ice thickness mea- features were lost as a result of sea-ice deformation. surements are used to discuss the role of ice ridging In such cases, we identified a new feature in the in the development of fast ice in the region. vicinity of the lost one and the lost feature was removed from subsequent analysis. As a result of sea-ice deformation and spatially irregular SAR- Methods coverage, the number of times each feature was observed is not constant. Hence, for the final ana- Drift detection and classification lysis we selected features with three or more obser- We used a time series of geolocated ENVISAT vations. Overall, we selected 31 features in 2007/08 C-band SAR images to follow the development of and 37 features in 2009/10. Their initial locations fast ice in the 2007/08 and 2009/10 winter seasons. are shown in Fig. 2. For each season the investigation started on an arbi- For each sea-ice feature we calculated a time series of trary date in the fall, when most of the area was the drift speed (Supplementary Figs. S1, S2) based on covered with pack ice, and ends once the SAR images the feature displacement and the time interval between indicated the presence of a fast-ice cover that is close the SAR scenes. Assuming that image geolocation error to its winter extent (ca. 130∙103 km2). The areal does not exceed one pixel and the position errors of development of fast ice during the investigation per- manual feature selection is less than three pixels, we iod is shown in Fig. 1. estimate the overall error of the tracking approach to Overall, we obtained 21 SAR scenes between 3 not exceed 600 m. The corresponding error of drift − − December 2007 and 23 January 2008 and 10 scenes estimates ranges from 0.05 cm∙s 1 to 1.7cm∙s 1 depend- between 1 December 2009 and 15 February 2010. The ing on the time span between image pairs. images have a pixel resolution of 150 m. The time Next, each feature was attributed with a date when interval between acquisitions varied between 10 hours it was incorporated into fast ice. This date was and four days for the 2007/08 season, and between three defined as the first date on which a feature was and 14 days for the 2009/10 season. The spatial coverage observed at a location that it subsequently occupied of the SAR data is shown in Fig. 2. for at least one week without moving (detected drift Using the Environment for Visualizing Images speed of a feature is less than the corresponding error tool (Harris Geospatical Solutions) we derived of drift estimate). In the event of a non-zero drift 30 Chapter 3 Mechanisms of fast ice development in the Laptev Sea

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Figure 2. Study area and SAR coverage. The grey colour corresponds to a fraction of SAR scenes obtained over the area of interest. The initial position of the tracked sea-ice features is shown in circles. The dashed blue line shows the position of the fast-ice edge on (a) 23 January 2008 and (b) 16 Feburary 2010, taken from GDSIDB operational sea-ice charts (WMO 2016).

measurement after that date (features 29–31 in 2007/ Sea-ice draft and keels information 08 and 32–38 in 2009/10), it was marked as a The main information on sea-ice ridging was derived break-out. from helicopter-borne EM measurements taken on 29 The accuracy with which it is possible to determine April 2008. Since no other extensive fast-ice thickness the fast-ice incorporation date depends on the number measurement was performed during the period of of observations and therefore is different for every fast- investigation, we use an additional EM ice-thickness ice feature. To reduce the biases we classify the features data set obtained during 16–20 April 2012 and in four fast-ice groups (Group I- IV) according to the upward-looking sonar data obtained in November– date when a feature was classified as fast ice. Group I February 2013. includes the features that were immobile already on The aim of the 2008 campaign was to estimate ice the first image pair and therefore classified as fast ice production over polynyas, hence, only a little fast-ice on the first day of the investigation period. The rest of area was covered. In fact, fast-ice measurements are investigation period was split into three equal intervals limited to areas close to the fast-ice edge. In 2012 (Fig. 3a, c). Groups II-IV comprise features that were however, extensive flights over fast-ice areas located incorporated into the fast ice during a corresponding further inshore were made. Because the EM ice thick- time interval. Note that the intervals are different for ness can be significantly overestimated in shallow each season. waters, both profiles were made over the water depth greater than 10 m (Hendricks et al. 2014). For both profiles, sea-ice thickness and sea-ice surface elevation were derived using an electromag- Auxiliary data netic-induction system (EM-bird) and a Riegel LD90- Wind data 3100HS laser altimeter (Haas et al. 2009). The EM To examine the role of wind action during the course sea-ice thickness has an average point spacing of 4 m of fast-ice development we used 6-hour ERA-Interim and a footprint of 40–50 m. The accuracy of level-ice reanalysis wind data extracted from a position located thickness estimates within a footprint is approxi- in the centre of the area of interest (75°N/133.5° E). mately 10 cm (Pfaffling et al. 2007; Haas et al. These data were used to derive the distribution of 2009). The point spacing of the laser altimetry data wind speed in different directions for two seasons is 30–40 cm and the accuracy is within 1.5 cm. A (Fig. 3). To facilitate the comparison of wind and combination of a low and high pass filter was applied drift directions, we define wind direction as the direc- to the altimeter data to remove the variations of the tion the wind is blowing to. Hence, northward wind surface elevation resulting from the helicopter move- corresponds to the offshore wind blowing to the north. ment (Hibler 1972). 31

4 V. SELYUZHENOK ET AL.

Figure 3. Wind speed and direction at the location 75°N/133.5°E for two seasons: 2007/08 and 2009/10. (a, c) Time series of wind vectors and (b, d) the corresponding wind rose. In (a) and (c), the background colour corresponds to fast-ice groups (Group I-IV) and indicates time intervals of fast-ice formation for a corresponding group. In (b) and (d), the sign convention is that the northward wind direction corresponds to the bar directed to the north.

Following Castellani et al. (2015), we identified Laptev Sea at mooring locations 1893 (76°N/126°E the sea-ice ridges along the profiles from EM and at 25 m instrument depth) and Taymyr (77.25°N/ laser altimeter measurements. First, the sea-ice bot- 116°E at 24 m instrument depth). These systems tom topography was derived as a difference of the were sampling the distance to ice surface at an inter- surface elevation and EM ice thickness for each val of 1 second between October and July and recov- point where both measurements are available. The ered in September 2014. The measured parameters – minima in the bottom topography deeper than sound pulse travel time, instrument tilt, temperature 1.5 m were identified as keel bottoms. Two adjacent and pressure – were converted by ASL into ice draft keels were classified as separate features if they following their standard processing routines (Melling satisfied the Rayleigh criterion: the minimum point et al. 1995). Based on the accuracy and precision of between two separate keels must be separated by a the acoustic, pressure, tilt and temperature sensor of point whose depth is less than half of the maximum the IPS, the error of the obtained draft thickness is depth of the keel (Hibler 1975; Wadhams & Davy within ± 0.05 m. 1986). Because of a large footprint and the presence of seawater in the keel’s cavities, the EM method underestimates the real-ridge thickness by 40–80% Results (Reid et al. 2003; Haas 2004; Hendricks 2009). Sea-ice and wind conditions in 2007/08 and Taking into account the typical underestimation of 2009/10 50% (Pfaffhuber et al. 2012), the maximum depths of detected keels were multiplied by a factor of two According to GDSIDB operational maps (WMO in order to account for the systematic underestima- 2016), the development of fast-ice area in 2007/08 tion of the EM method (Haas 2004). closely followed the 1999–2013 average areal devel- Additional information on fall sea-ice draft thick- opment (Fig. 1) and is representative for the majority ness in the Laptev Sea was collected at two seafloor of seasons. In comparison to 2007/08, the winter of observatories. In September 2013, two Ice Profiling 2009/10 was characterized by an unusual break-out Sonars (version 5), manufactured by ASL event in January-February (Fig. 1). The initial sea-ice Environmental Science Inc., and two Acoustic conditions at the beginning of investigation for the Doppler Current Profilers were deployed in the two seasons were slightly different. According to a 32 Chapter 3 Mechanisms of fast ice development in the Laptev Sea

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passive-microwave data set (Markus et al. 2009), the In 2007/08 the drift speed for Groups II-IV was freeze-up in 2007/08 occurred on 6 October. The first relatively high between days 55 – 65 and dropped − analysed SAR scene was taken 58 days after the after day 65 to 1–2ms 1. Afterwards, the drift speed freeze-up. It showed that the area of interest was decreased gradually. Only Group IV showed a slight almost entirely covered with pack ice (nearly 100% peak in the drift speed towards the end of the concentration). A small patch (ca. 3∙103 km2)of investigation. newly-formed ice along the east Lena Delta developed In 2009/10 only Group I features were tracked during a coastal polynya event. A significantly bigger from the beginning of the investigation. As a result area (> 21∙103 km2) of newly formed ice was present of deformation of the vast thin ice zone formed dur- along the Lena Delta on the first SAR scene (taken ing a polynya event and covering a substantial part of 52 days after freeze-up) in 2009/10. Freeze-up in the area of interest, many features were lost at the 2009/10 took place seven days later than in 2007/08. beginning of the investigation period. This resulted in The two seasons were also characterized by different shorter drift time series of Group II-IV. The pattern wind conditions. In general, the wind circulation in the of Group II-IV drift speed, however, looks similar to Laptev Sea can be described by two main regimes: an the one in 2007/08: there was a drop in drift speed anticyclonic regime with a dominant northward (off- followed by a gradual decline in velocity to zero shore) component and a cyclonic regime with a domi- motion. This indicates that the formation of fast ice nant north-eastward component (wind towards the in both seasons did not occur abruptly, but was a East Siberian Sea) (Dmitrenko et al. 2005). In 2007/08 gradual process of ice flow accretion, as suggested by north-, west- and north-westward wind with an average Eicken et al. (2005). − speed of 5–8ms1 was predominant (Fig. 3b). The final location of all tracked features is shown in Remarkably, the offshore wind (in north-west–north Fig. 5. In both seasons, Group I features are located not direction) persisted for two weeks (days 71–86 in (Fig. only in the vicinity (< 50 km) of the shore, where fast 3a). The season 2009/10 was characterized by slightly ice is typically expected to start forming, but also higher wind speeds (Fig. 3c) and more scattered direc- further offshore, surrounded by mobile pack ice. The tions. The predominant wind direction for that season location of these offshore features corresponds to the was north-east–east (Fig. 3d). The beginning of a period shallow banks, suggesting that the ice was grounded − of strong wind speed (up to 26 m s 1) in north and there. The mean water depth at the location of Group I north-east direction between day 103 and day 110 (Fig. features was 10 m (Fig. 6). Notably, the Group I fea- 3c) coincided with the timing of fast-ice break-up that tures re-occurred at the same location in both seasons. was observed in January–February between days 90 and The location of Group II and III features does not show 119. Overall, the season 2007/08 was characterized by any spatial pattern. Features that remained mobile until stronger offshore wind component (anticyclonic the latter third of each investigation period (Group IV) regime) and the season 2009/10 shows stronger east- occupied the deepest waters (Fig. 6) and were found in ward wind component (cyclonic regime). two different regions (Fig. 5). Most were observed in the seaward most portion of fast ice, which is typically last to stabilize. However, a number of features were Fast-ice development based on drift classification observed to continue drifting with low speed near the Figure 4 shows the time series of mean drift speed for mouth of the Buor-Khaya Bight despite being sur- the four fast-ice groups (Groups I-IV). By definition, rounded by stationary fast ice. Group I showed zero drift speed from the beginning Duringthecourseoffast-iceformationsomeof of the investigation. Groups II-IV were characterized the features (Fig. 5) were incorporated in fast ice, by higher drift speed at the beginning of the investi- but later became mobile again. These events were gation period; this speed decreased towards the end. classified as break-out events. In 2007/08 break-

Figure 4. Time series of 10-days mean drift speed for Groups I-IV. The error bars show range of drift for each time step. 33

6 V. SELYUZHENOK ET AL.

Figure 5. Final location of the tracked features: (a) 2007/08, (b) 2009/10. Dot colour corresponds to a feature’s fast-ice group (Group I-IV). The days of fast-ice formation are given in days after freeze-up. The dashed blue line shows the position of fast-ice edge on (a) 23 January 2008 and (b) 16 February 2010, taken from GDSIDB operational sea-ice charts (WMO 2016).

Figure 6. Scatter plot of water depth at the final ice feature location against the day of fast-ice formation. Dot colour corresponds to a feature’s fast-ice group. out events affected one feature in the fast-ice depth of few identified sea-ice ridges did not exceed interior (feature 31) and two features closer to 9 m which is significantly smaller than the water depth fast-ice edge (feature 29, 30). In contrast, an at their location. In contrast, measurements that were extensive break-out event took place in 2009/10 made close to the fast-ice edge in 2008 show large (Fig. 1), reflected in five neighbouring features differences in mean (2.8 m) and modal thickness (feature 32–36) detaching north of Buor-Khaya (1.4 m) and the histogram characterized by a distinct Bight (Fig. 5b). tail. The profile taken on 29 April 2008 (Fig. 8) shows a deep ice ridge with an estimated ice draft of 18 m. The ridge is located in the fast-ice zone in the vicinity of Sea-ice ridging fast-ice edge where the water depth does not exceed 20 m and therefore is potentially grounded. Deep ice Histograms and flight tracks of surveys performed in keels were also observed by IPS in the pack ice area in 2008 and 2012 are shown in Fig. 7. The histogram of fall 2013 (Fig. 9) While the minimum (level ice) ice thickness measurements for flights made in 2012 is observed sea-ice draft in November–December does characterized by bimodal distribution. The most fre- not exceed 1 m, the maximal draft (ridge keels) values quently occurring ice thickness, the mode of the dis- reach up to 10–18 m. tribution, represents level ice thickness. An analysis of SAR images obtained in the winter of 2012 showed that fast-ice areas characterized by 0.6 m modal thickness Discussion are associated to zones that were formed later, while thicker ice (modal thickness around 1.2 m) were Investigating the development of fast ice by means of formed earlier in the season. The fraction of dynami- high resolution satellite and observational data we cally deformed ice is represented by the length and the described the formation of fast-ice cover in winter shape of the tail of the thickness distribution. For 2012, 2007/08 and 2009/10. In both seasons, the fast-ice the tail is rather narrow, pointing to the absence of cover was mainly formed from the drifting sea ice deformation in the survey area. The maximal keel produced during freeze-up in the region (most of the 34 Chapter 3 Mechanisms of fast ice development in the Laptev Sea

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Figure 7. (a) The ice thickness distribution measured in April 2008 and 2012. (b) The EM measurements taken along tracks close to the fast-ice edge. The dashed lines show the fast-ice edge on 7 May 2008 (red) and 17 April 2012 (black).

in 2007/08 and a more prolonged development period in 2009/10, which included a partial breakout and temporary decrease of fast-ice extent. In 2007/08 the persistent offshore wind facilitated gradual concre- tion of the thickening pack ice. The offshore grounded features restricted sea-ice motion away from the region which resulted in fast-ice consolidation over a large area. The stronger wind in 2009/10 led to higher sea-ice deformation and opening of a lead east of the Lena Delta where new ice was produced. Consequently, fast-ice cover was formed from thinner sea ice and broke out under a strong wind action. Nevertheless, there was a common pattern of fast-ice formation. First, the formation of extensive fast-ice cover started with development of offshore Figure 8. The sea-ice surface and bottom topography profiles measured on 29 April 2008. The identified keels depths and stationary ice zones (Group I features). Second, dur- derived keel depths are shown in circles. The error bars ing fast-ice consolidation, areas of moving ice were corresponds to possible ranges of estimated keel depths present between the seaward fast-ice edge and the resulted from different identified-to-derived keel depths mainland. ratio found in the literature. The grounded features formed over shoals with the water depth less than 10 m (taken from the International Bathymetric Chart of the Arctic Ocean [Jakobsson et al. 2012]) and re-occurred in both years. The presence of grounded ice at the shoals (stamukhi) is a well-known phenomenon in the Laptev Sea (Gorbunov et al. 2008). The stamukhi were mapped during air reconnaissance flights in 1960-90s. However, there was no information on the timing of their formation, since the flights were done mainly during the navigation period (March– Figure 9. Ice draft data obtained by the two IPS systems, October). According to our investigation, the Taymyr (77.25°N/116°E) and 1839 (76°N/126°E). The solid, dashed and dotted lines show daily maximum, mean and grounded features formed less than two months minimum draft thickness recorded. after the freeze-up, when the sea-ice thermodynamic thickness (calculated from freezing degree days, using Lebedev 1938 ice growth model) did not exceed features were tracked from the beginning until the 50 cm. end of investigation). Different sea-ice and wind con- According to IPS data, newly formed ice of less ditions during the two seasons led to typically rapid than 50-cm thickness is capable of forming ice keels development of the maximum winter fast-ice extent deep enough to become grounded. The data indicate 35

8 V. SELYUZHENOK ET AL. that as early as November–December first-year ice shoals remained stationary, while the ice located had an ice keel of 10 to 18 m (Fig. 9). The bathymetry over the deeper area east of the Lena Delta broke of the Laptev Sea is based on 5-m contour charts out. This area was also covered with fast ice relatively (Jakobsson et al. 2012), which could result in a late in 2007/08, although no distinct break-out took smoother representation of underwater relief. place (Fig. 5). A similar pattern of spatial fast-ice Taking into account that the International development in two seasons with different atmo- Bathymetric Chart of the Arctic Ocean water depth spheric forcing confirms that the location of the over the shoals is 5–15 m, an inaccuracy of a few grounded ice pre-defines winter fast-ice extent metres can explain grounding of not strongly (Selyuzhenok et al. 2015). deformed sea ice. This could explain absence of While re-occurrence of the grounded ice features deformation features on satellite imagery in the in the central part of the south-eastern Laptev Sea region, as reported by Eicken et al. (2005). constrains the position of the fast-ice edge in this The grounded ice features play a key role in fast- region and reduces interannual variability in fast-ice ice formation. First, they become an obstacle for the extent, the deep ridges might be responsible for local export of sea-ice offshore. Although in 2007/08 the variations in the shape of fast-ice edge in winter. The main wind direction was offshore, there was almost ridges pin fast ice at their location and serve as no northward transport of ice out of the area south of stabilizing points. Such ridges were detected at the the grounded features. The only features that exited fast-ice edge by the EM method in April 2008. the study area were those that were initially located However, the origin of the ridges is not clear: they between the Lena Delta and the chain of shoals near could form though a deformation within the pack or the longitude of 133°E. Second, grounded features as a result of deformation at the fast-ice edge. The serve as anchors for the surrounding pack ice. As a data indicate that ice ridges with deep keels can be result, fast ice develops around the grounded features. brought to the south-eastern area from the north of Therefore, the fast-ice expansion takes place not only the Laptev Sea. Numerical studies confirm that in an offshore direction by attachment of pack ice to grounding is one of the key mechanisms of fast-ice the seaward fast-ice edge, but also from the central formation in the Laptev Sea. Parameterization of part of the region. grounded ridges contributes to more realistic simula- Since grounded fast ice over the shoal areas forms tions of the seasonal fast-ice cycle (Lemieux et al. ahead of the main fast-ice edge, sometimes areas of 2015; Lemieux et al. 2016). mobile ice can be found between the seaward fast-ice edge and the land. Formation of mobile ice patches within the fast-ice cover can also occur in regions Conclusion where there is a possibility of ice stabilization off- A detailed examination of SAR-based ice drift in the shore. Moving ice can be trapped between the main- winters of 2007/08 and 2009/10 showed that ground- land and ice ridges along the Alaskan shore or ing is a key mechanism of fast-ice formation in the between chain of islands and the mainland in the south-eastern Laptev Sea. The grounded ice features Kara Sea. The presence of mobile ice within fast-ice (stamukhi) are formed offshore prior to fast-ice cover has several implications. Because of low drift expansion. These features become an obstacle speed, small-scale and the presence of fast ice sea- restricting the motion of the surrounding ice before ward, operational sea-ice charts might misclassify it becomes stationary and serve as stabilizing points these areas of mobile ice as part of fast-ice cover. during fast-ice formation. The re-occurrence of However, unlike within a consolidated fast-ice grounded features reduces interannual variability in cover, formation of leads and deformed ice is likely fast-ice extent in the region. Small interannual varia- in these areas. This can endanger local communities tions in fast-ice edge position can be explained by in Alaska (John et al. 2004), and to a lesser extent in formation of deep ridges further offshore. However, the Siberian Arctic, in which people hunt and travel there is lack of observational data confirming this on fast ice. The presence of open water can also hypothesis. The formation of grounded ridges in the benefit marine mammals that require active open- vicinity of fast-ice edge and their role in fast-ice ings. The numerical models that simulate seasonal formation in the Laptev Sea requires further and interannual variability of fast-ice use drift speed investigation. to define fast ice (Wang et al. 2014). Mobile ice behind the fast-ice edge might result in higher mean drift velocities, which might affect simulated timing Acknowlegements and spatial pattern of fast-ice formation. The IPS data were obtained within the framework of Laptev The grounded features also provide additional sta- Sea System, a Russian–German cooperative research project. bility for the fast-ice cover later in the season. During The study reported here was carried out as part of the same the break-out event in 2009/10, fast ice over the project and the project Quantifying Rapid Climate Change in 36 Chapter 3 Mechanisms of fast ice development in the Laptev Sea

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the Arctic: Regional Feedbacks and Large-Scale Impacts, the OTC Arctic Technology Conference. Offshore funded by the German Federal Ministry of Education and Technology Conference, 10–12 February, Houston, TX. Research (grant no. 03F0777A). VS acknowledges support of Hibler W.D. 1972. Removal of aircraft altitude variation Russian Science Foundation project no. 17-17-01151. from laser profiles of the Arctic ice pack. Journal of Constructive comments by Jean-François Lemieux and an Geophysical Research 77, 7190–7195. anonymous reviewer improved the manuscript. Hibler W.D. 1975. Characterization of cold-regions terrain using airborne laser profilometry. Journal of Glaciology 15, 329–347. Disclosure statement Hughes N.E., Wilkinson J.P. & Wadhams P. 2011. Multi- satellite sensor analysis of fast-ice development in the No potential conflict of interest was reported by the authors. Norske Øer Ice Barrier, northeast Greenland. Annals of Glaciology 52, 151–160. Itkin P., Losch M. & Gerdes R. 2015. Landfast ice affects Funding the stability of the Arctic halocline: evidence from a numerical model. Journal of Geophysical Research— This work was supported by the Bundesministerium für Oceans 120, 2622–2635. Bildung und Forschung (03F0777A); Russian Science Jakobsson M., Mayer L., Coakley B., Dowdeswell J.A., Foundation (17-17-01151). Forbes S., Fridman B., Hodnesdal H., Noormets R., Pedersen R., Rebesco M. & Schenke H.W. 2012. The ORCID International Bathymetric Chart of the Arctic Ocean (IBCAO) version 3.0. Geophysical Research Letters 39, Valeria Selyuzhenok http://orcid.org/0000-0001-9388- L12609, doi: 10.1029/2012GL052219 5706 John C., Huntington H.P., Brewster K., Eicken H., Norton D.W. & Glenn R. 2004. Observations on shorefast ice dynamics in Arctic Alaska and the responses of the – References Iñupiat hunting community. Arctic 57, 363 374. Karklin V.P., Karelin I.D., Julin A.V. & Usol‘ceva E.A. 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WlK., Weingartner T.J., ing with airborne electromagnetics-grounded ridges and Woodgate R.A., Aagaard K. & Shimada K. 2011. ice shear zones near Barrow, Alaska. Paper presented at Upwelling in the Alaskan Beaufort Sea: atmospheric 37

10 V. SELYUZHENOK ET AL.

forcing and local versus non-local response. Progress in Timokhov L.A. 1994. Regional characteristics of the Laptev Oceanography 88,78–100. and the East Siberian seas: climate, topography, ice Proshutinsky A., Ashik I., Häkkinen S., Hunke E., phases, thermohaline regime, circulation. Berichte zur Krishfield R., Maltrud M., Maslowski. W. & Zhang J. Polarforschung 144,15–31. 2007. Sea level variability in the Arctic Ocean from Wadhams P. & Davy T. 1986. On the spacing and draft AOMIP models. Journal of Geophysical Research— distributions for pressure ridge keels. Journal of Oceans 112, C04S08, doi: 10.1029/2006JC003916. Geophysical Research—Oceans 91, 10697–10708. Reid J.E., Vrbancich J. & Worby A.P. 2003. A comparison Wang J., Mizobata K., Bai X., Hu H., Jin M., Yu Y., Ikeda M., of shipborne and airborne electromagnetic methods for Johnson W., Perie W. & Fujisaki A. 2014. A modeling Antarctic sea ice thickness measurements. Exploration study of coastal circulation and landfast ice in the near- Geophysics 34,46–50. shore Beaufort and Chukchi seas using CIOM. Journal of Reimnitz E., Dethleff D. & Nürnberg D. 1994. Contrasts in Geophysical Research—Oceans 119, 3285–3312. Arctic shelf sea-ice regimes and some implications: WMO (World Meterological Organization) 2016. Global beaufort Sea versus Laptev Sea. Marine Geology 119, digital sea ice data bank project. WDCB (World Data 215–225. Center – B “Oceanography“) Sea Ice. Arctic and Selyuzhenok V., Krumpen T., Mahoney A., Janout M. & Antarctic Research Institute 7-days period generalized Gerdes R. 2015. Seasonal and interannual variability of ice charts for the Russian Arctic and seasonal ice cover fast ice extent in the southeastern Laptev Sea between seas and the Greenland Sea for 1998-2013. Accessed on 1999 and 2013. Journal of Geophysical Research—Oceans the internet at http://wdc.aari.ru/datasets/d0004/ on 23 120, 7791–7806. September 2016.

Chapter 4

East Siberian Sea fast ice: Interannual variations in winter extent and linkage with atmospheric forcing

Paper in preparation

V.Selyuzhenok1, T. Krumpen1, M. Leppäranta2, R. Gerdes1,3

1Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremer- haven, Germany 2University of Helsinki, Department of Physics, Helsinki, Finland 3Jacobs University Bremen, Bremen, Germany

39 40 Chapter 4 East Siberian Sea fast ice

4.1 Introduction

The continental shelf of the East Siberian Sea (ESS) is the widest and shallowest in the World Ocean (Semiletov et al., 2005; Stein et al., 2004). The influence of the river runoff and oceanic inflow from both the Atlantic and the Pacific Ocean in combination with shallow and extensive shelf make the East Siberian Sea one of the most active biogeochemical marine environment (Anderson et al., 2011). Numerous studies indicate changes in the East Siberian Sea coastal environments. First, an increased degradation of submarine permafrost leads to the release of methane through the shallow water column to the atmosphere (Shakhova and Semiletov, 2007; Shakhova et al., 2010a; Semiletov et al., 2012). An abrupt release of only a small fraction of the methane held in the East Siberian Arctic Shelf sediments could trigger climate warming (Shakhova et al., 2010b). Second, there is an intensification of the coastal erosion in the region (Overduin et al., 2014). Sea ice and particularly fast ice plays an important role in the processes of methane release and in coastal dynamics. Fast ice protects coasts from erosion by reducing the impact of waves (Overduin et al., 2014). By decoupling ocean and atmosphere, fast ice cover traps the released from the sediments methane. The gas leaks to the atmosphere during polynya events or it is released abruptly upon summer breakup (Shakhova and Semiletov, 2007).

Although fast ice is an important component of the coastal environment, only little is known about the East Siberian fast ice cover. Due to the geographical similarity of the two regions, the East Siberian Sea and Laptev Sea fast ice covers are considered to have similar characteristics (Timokhov, 1994), however there is no comprehensive study on the East Siberian fast ice. Hence, the aim of this study is to examine the seasonal and interannual variability of fast ice extent in the East Siberian Sea. Our ﬁrst objective is to describe the seasonal fast ice cycle and evaluate changes occurring in the annual cycle during the past 1.5 decades. Understanding the mechanism controlling fast ice development is essential for an assessment of future changes in fast ice regime and their possible impact on coastal environment. The air temperature, atmospheric circulation and bathymetry are often reported as the main factors controlling the variability of Arctic fast ice (Divine et al., 2004, 2005; Mahoney et al., 2007a, 2014; Selyuzhenok et al., 2015). As the Arctic cyclone activity intensiﬁes and the air temperature rises (Polyakov et al., 2003b; Zhang et al., 2004; Tilinina et al., 2014), our second objective is to investigate the role of atmospheric forcing in the regime of the East Siberian Sea fast ice. 4.2 Data and Methods 41

70°N Kolyma Gulf Medvezhyi Islands

75°N

Lyakhovsky Islands De Long Islands A n z h u I s l a n d s

170°E 160°E 150°E 140°E

> 25 20 15 10 5 0 Land

Water depth in m Figure 4.1. East Siberian Sea bathymetry from the International Bathymetric Chart of the Arctic Ocean (IBCAO Version 3, Jakobsson et al. (2012)). The shades of blue show the water depth (m). Red frame outlines the region for which fast ice area was extracted.

4.2 Data and Methods

4.2.1 Fast ice information

The information of fast ice extent from 1999 to 2015 was extracted from AARI weekly operational sea ice charts (for data description see Chapter 2). Overall, we analyzed 601 maps for the period between January 1999 and December 2015. The fast ice area was extracted for the region shown on Figure 1. The areal thresholds used to identify the key events of fast ice annual cycle are given in Table 4.1.

Every annual cycle was described by two main key events: Key event 1 - Beginning of fast ice season and Key event 2 - End of fast ice season. Due to gaps in the AARI data set it was not possible to detect Key event 1 for the season of 2013 and Key event 2 for the seasons of 2002 and 2012. Two additional key events (Key event 3 and Key event 4) were identiﬁed for the seasons when fast ice cover developed a large extent or L-mode (see section 4.3.1). This development is characterized by a rapid increase of fast ice area from ∼ 100 × 103 km2 to more than 250 × 103 km2 (Figure 4.2 b). 42 Chapter 4 East Siberian Sea fast ice

Table 4.1. Key events and identification criteria Key event Identification criteria (1)Beginning of season Fast ice area reaches 11 ×103km2 (∼ 5 % of S-mode maximal winter area) corresponds to narrow strip of fast ice along the coast (2)End of season Fast ice area drops below 11 ×103km2 (∼ 5 % of S-mode maximal winter area) (3)Beginning of L-mode development After fast ice area reaches 130 ×103km2, beginning of the first event when the speed of mean weekly areal development exceeds 16 ×103km2 (4)Fully developed L-mode End of the last event when the speed of mean daily weekly development exceeds 16×103km2

4.2.2 Freezeup and Melt onset. Freezing (FDDs) and thawing (TDDs) degree days

To investigate the role of thermodynamic factors in annual fast evolution, we link the timing of fast ice key events to the onset of freezing and melting season, and freezing (FDDs) and thawing (TDDs) degree days. The dates of freezeup and melts onset were obtained from the passive-microwave dataset (Markus et al., 2009). We deﬁned the date of freezeup/melt as a mean date for the region when the freezing/melting conditions occurred.

Freezing degree days (FDDs) were calculated from ERA-Interim 6-hourly 2-m air temperature. First the mean air temperature for the marine part of the region was calculated. Then FDDs we calculate as a sum of negative temperatures since the onset of freezeup. Thawing degree days (TDDs) we calculates similarly, as a sum of positive temperature since the onset of melt.

4.2.3 Atmospheric dynamic factors

In this study we analyzed the role of the atmospheric dynamic factors on winter fast ice extent. Because the advance of fast ice edge to its winter location takes place in February-May, the analysis was performed for these months.

A linkage between the arctic-wide wind circulation and winter fast ice extent were investigated by examination of the Arctic Oscillation (AO) index. The AO index describes a state of the atmospheric circulation over the Arctic. The polarity of AO index reﬂects a pattern of atmospheric circulation and sea ice drift (Rigor et al., 2002). 4.3 Results 43

The inﬂuence local wind on fast ice winter extent were examined using a wind-time interval parameter. Following Divine et al. (2004) we calculated the sum of wind speed over the winter period for four 90◦-sectors centered at N, E, S, and W, as well as total sum of wind speed in all directions (see Chapter ??). The wind integral value shows how intense was the wind in certain direction over a period of time. Wind speed and direction were taken from the ERA-Interim 6-hourly 10-m wind data for a point 73.5◦ N/154.5◦ E.

Finally, single wind events were compared to the events of fast ice development. In order to do this, we calculated the wind stress on the sea ice surface (τa expressed in N·m−2) following Larouche and Galbraith (1989):

τa = ρaC10 | U10 | U10 cos (θ), (4.1)

−3 where ρa is the air density, 1.3 kg·m , U10 is the wind speed at 10 m expressed in −1 −3 m·s , C10 is a drag coefficient, 1.5 × 10 (a value representative for a first-year level sea ice) and θ is an angle between the wind direction and the main axis (E-W). The main axis was chosen because the distribution of the winter wind suggests that wind in E-W direction can be possibly linked to the development of an extensive fast ice cover (see section 4.3.4). The positive peak in the wind stress reflect wind action on the sea ice cover in the direction towards the New Siberian Islands, while negative peaks correspond to the wind action in opposite direction.

4.3 Results

4.3.1 Seasonal cycle

The fast ice season in the East Siberian Sea lasts from November until August. The fast ice cycle shows high interannual variability in maximal fast ice extent. There are two distinctive modes: a small (fast ice area does not exceed 250 × 103 km2) and a large (fast ice area exceeds 250 × 103 km2) extent (Figure 4.2). During small mode (S-mode) the fast ice develops gradually in fall, reaches its maximal winter extent in March-April and gradually disintegrates in June-August. The S-mode fast ice develops an arch-shaped edge going from the Anzhu Islands to the mainland. The large mode (L-mode) is characterized by a gradual development in fall, following by a rapid fast ice areal growth in February-May. Compared to the S-mode, the fast ice extents further north and its edge forms a straight NW-SE line going from the eastern Anzhu Island to the mainland on the east of the sea (Figure 4.3). The breakup of L-mode fast ice takes place in June-August. As for the S-mode, it fully disintegrates during this three months. 44 Chapter 4 East Siberian Sea fast ice

Small-mode Large-mode

1999 2008 2001 1998 2009 2003 2006 2010 2002 400 2000 2012 2011 2007 2004 2013 2014

2 2005 300 km 3 200

Area, 10 100

0 Jul Jul Nov Dec Jan Feb Mar Apr May Jun Aug Nov Dec Jan Feb Mar Apr May Jun Aug Figure 4.2. East Siberia Sea fast ice annual cycle. The year corresponds the year of fall when seasonal fast ice formation started (e.g. 1999 curve shows development of fast ice from October 1999 to August 2000).

A. Small - mode B. Large - mode

70°N 70°N

-10 -10

-30 -20 -30 -20

75°N 75°N

170°E 160°E 150°E 140°E 170°E 160°E 150°E 140°E % 0 10 20 30 40 50 60 70 80 90 100 February - May fast ice occurrence Figure 4.3. Mean February-May frequency of fast ice occurrence for (a) S- and (b) L-mode.

The L-mode occurs almost twice as often as the S-mode. The long-lasting L-mode developed during 7 seasons: 1998, 2000, 2004, 2005, 2009, 2012 and 2013. During the seasons 2003, 2011 and 2014 the large extent developed only for a short period of 1 to 3 weeks and than reduced to the small extent which persisted until the summer breakup. The S-mode was observed during 5 seasons: 1999, 2006, 2007, 2008, 2010. Due to gaps in the AARI data set there is only limited information on winter fast ice for the seasons of 2001 and 2002 which did not allow to attribute these seasons to one of the two fast ice modes. These two seasons were excluded from the analysis related to the modes occurrence. 4.3 Results 45

4.3.2 Key events and trends

Timing of key events onset and trends are presented in Table 4.2 and Table 4.3 correspondingly. We find that the events connected with L-mode development have very high variability, while timing of the Beginning and End of fast ice season is less variable. Non of the key events shows changes in their timing for the period between 1999 and 2015 (Table 4.3). However, there is a statistically significant (at 95% confidence level) trend towards shorter fast ice season by 1.5 d/y.

Table 4.2. Variability of dates of the key events Key event mean stdev (days) min max (1) Beginning of fast ice season 02-Nov 8 17-Oct 21-Nov (2) End of season 21-Jul 7 03-Jul 02-Aug (3) Beginning of L-mode development 15-Feb 22 15-Jan 11-Apr (4) Fully developed L-mode 25-Mar 38 13-Jan 05-May

Table 4.3. Trends in timing of key events and periods of annual fast ice cycle 2 Key event/Period Trend (day/year) p r σest (1) Beginning of season 0.6 0.18 0.12 0.42 (2) End of season -0.6 0.15 0.16 0.42 (3) Beginning of L-mode development 1.5 0.48 0.08 2.0 (4) End of L-mode development 2.4 0.34 0.11 2.4 Fast ice season -1.5 0.02 0.43 0.5 L-mode period -1.57 0.57 0.05 2.6

4.3.3 Linkage with thermodynamic factors

The correlation coeﬃcient between timing of the key events and onset of freezeup and melt are presented in Table 4.4. A statistically signiﬁcant linkage was found only between the onset of freezeup and Beginning of fast ice season. The variability of FDDs and TDDs accumulated prior the onset of the key events (Table 4.5) is higher for Beginning and End of fast ice season (> 30 %) and lower for the events of L-mode development (< 25 %).

4.3.4 Linkage with atmospheric circulation

We used the AO index to analyze inﬂuence of atmospheric circulation on winter fast ice extent. Figure 4.4 shows the time series of AO indexes for 1998-2015. Most of L-mode fast ice seasons are characterized by negative AO index in February-May, while most of 46 Chapter 4 East Siberian Sea fast ice

Table 4.4. Correlation between key events, freezeup and melt onset. Events Freezeup p Melt p (1) Beginning of season 0.82 <0.01 - - (2) Beginning of L-mode development 0.36 0.34 - - (3) End of L-mode development 0.23 0.52 - - (4) End of season - - 0.10 0.74

Table 4.5. FDDs and TDDs accumulated prior the key events Key event FDDs mean stdev, % min max (1) Beginning of season 211 35 79 314 (2) Beginning of L-mode development 2391 22 1793 3306 (3) End of L-mode development 3146 23 2005 4070 TDDs (4) End of season 59 31 29 107

S-mode seasons show positive winter AO index. There is one S-mode season (2007) and tree L-mode seasons (2011, 2013, 2014) which do not agree with this patter. However, in 2011 and 2014 large fast ice extent developed only for short period and broke out to the S-mode in less than three weeks after formation. 3 2 1 0 1 2 monthly AO monthly 3 4 5

199819992000200120022003200420052006200720082009201020112012201320142015 S-mode L-mode short L-mode undefined

Figure 4.4. Time series of AO index. The vertical bars mark February-May period. The color of the bars correspond to the fast ice mode formed during the season.

Figure 4.5 shows the February-May distribution of wind direction and speed for the seasons characterized by L- and S- fast ice modes. The L-mode histogram (Figure 4.5a) shows unimodal distribution of wind direction with a pronounced mode for winds in WSW-WNW direction (directions the wind blows to). The modal direction also shows the highest occurrence of strong winds (10-15 m·s−1). The S-mode histogram (Figure 4.3 Results 47

4.5b) does not show a distinctive mode, but slightly higher wind frequency occurred in W-WNW and NE-ENE directions compared to other directions. L -mode S -mode N N 10.6 8.5

N-W 8.5 N-E N-W 6.8 N-E

6.4 5.2

4.3 3.5

2.2 1.8

W E W E

S-E S-E S-W S-W 0-2 S S 2-5 5-10 10-15 S-W >15 wind speed, m/s Figure 4.5. Average February-May wind rose histograms for (a) L- and (b) S-mode seasons. The bars direction corresponds to the direction the wind blows to.

The February-May wind integral speed is shown on Figure 4.6. The values show how intense the wind was during winter months, but they do not necessarily represent a speciﬁc circulation pattern. According to the Figure 4.6, the westward wind is the most intense in the region almost every winter. The overall the pattern of wind intensity looks similar for both S- and L-modes.

The role of single wind events during the development of large fast ice extent were analyzed using the winds stress parameter. Since the westward wind appear to be associated with L-mode (Figure 4.6), the wind stress we calculated along the E-W axis for every L-mode season. The analysis showed that there is no pattern of local wind events which can be linked to the L-mode development. The time series of wind stress, its direction and speed during the L-mode development for three selected seasons are shown in Figure 4.7. During the formation of the large fast ice extent in 2009, there were several positive wind stress peaks (Figure 4.7a), while the season of 2004 is characterized by very low wind stress (Figure 4.7b) and the season of 2003 showed positive as well as negative peaks in wind stress (Figure 4.7c). 48 Chapter 4 East Siberian Sea fast ice

3500

3000

2500

L S 2000 total wind N E 1500 S W

1000

Feb-May wind integral speed, m/s 500

0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Figure 4.6. Integral February-May wind speed. The black symbols correspond to the total wind speed, while the color symbols shows north, east, south and west components (direction the wind blows to). The L-mode seasons are shown in ﬁlled circles and S-mode seasons are shown in blank squares.

Figure 4.7. Time series of wind stress in E-W direction during L-mode development (a), (b), (c) and fast ice area (d), (e), (f). Positive peaks in wind stress correspond to strong wind blowing to the west and negative peaks correspond to the opposite wind direction. The dash vertical lines correspond to the events of rapid fast ice areal growth.

4.4 Discussion

Thermodynamic factors appear to control fast ice development throughout the season. The high correlation between onset of freezeup and Beginning of fast ice season confirms the importance of thermodynamic processes for fast ice annual cycle. Compared to the Laptev Sea (Chapter 2), the correlation coefficient is higher and the variability of FDDs at the Beginning of fast ice season is lower. This suggests that the East Siberian Seas 4.4 Discussion 49 fast ice is more sensitive to changes in thermodynamic factors in fall, compared to the Laptev Sea fast ice. However, it should be noted that the definition of the key events is based on an arbitrary areal threshold, therefore the timing of the key events and attributed characteristics (FDDs, correlation with freezeup onset) for the two regions are not directly comparable. There is no relation between the End of fast ice season and the onset of melt (Table 4.4), however the timing of the key event can be linked to a narrow range of accumulated TDDs. Overall, low variability of FDDs and TDDs accumulated prior the onset of all key events (Table 4.5) suggests that air temperature plays an important role in seasonal fast ice cycle. Nevertheless, air temperature does not control the occurrence of fast ice modes since the FDDs accumulated prior L-mode development are characteristic for every winter between 1999 and 2015.

The analysis of dynamic factors showed that the development of L-mode extent can not be attributed to as single wind events. Also, a comparison of the winter wind integral speed shows very similar situation between all seasons (Figure 4.6). The time integral allows estimation of the inﬂuence of wind speed and direction on fast ice formation, however, it is not related to an atmospheric circulation patter. E.g. period of scattered wind can result in similar time integral values as a period of consequently changing intervals with persistent wind direction. A good agreement between the seasons with L-/S-modes and negative/positive winter AO index suggests that there is a linkage between general pattern of Arctic atmospheric circulation and the fast ice extent.

Rigor et al. (2002) showed that during negative AO phases the sea ice is imported to the East Siberian Sea from the east. A positive AO phases are characterized by presence of a weak cyclonic gyre on the east of the region which prevents sea ice inﬂow to the western part of East Siberian sea. Figure 4.8 shows the backtrack trajectories of sea ice located at 74◦N\158◦E for all S-mode (black) and L-mode (red) seasons. This location is occupied by the fast ice during L-mode and stays covered by pack ice during S-mode. A narrow spread of S-mode tracks indicates that the ice was formed in the region, while L-mode trajectories track back further east. This conﬁrms that the large fast ice extent forms from the imported sea ice. The sea ice import to the East Siberian Sea might result in higher rate of sea ice deformation in the region compared to no-import seasons. Therefore, during positive AO phases, formation of sea ice ridges that are thick enough to ground and thereby stabilize the extensive fast ice cover is more likely. Mahoney et al. (2014) suggested that the location of grounded ice ridges can be inferred from the convergence of fast ice edge (”nodes”) on frequency occurrence maps. Figure 4.3b show that such ”nodes” occur north-east of Anzhu Islands and north of small shoals in the middle of the region (show on map). Therefore, we hypnotize that development of large fast ice extent in the East Siberian Sea is controlled by formation of grounded ice ridges. 50 Chapter 4 East Siberian Sea fast ice

70°N

75°N

Figure 4.8. The trajectories of an ice feature from a location occupied by fast ice during L-mode and pack ice during S-mode (74 N/158 E). The points show the origin of the ice feature and the lines correspond to its drift trajectory. Red color corresponds to L-mode season and back color shows S-mode seasons.

4.5 Conclusion

By using AARI operational sea ice charts we analyzed seasonal and interannual variability of fast ice extent in the East Siberian Sea between 1999 and 2015. We identiﬁed key events in each annual fast ice cycle and linked the occurrence of these events to freezeup and melt onset and air temperature (FDDs and TDDs). The analysis reveals that fast ice in the region is sensitive to the thermodynamic processes throughout a season. On the interannual time scale we found a tendency towards shorter fast ice season. The duration of fast ice season reduces by 1.5 d/y which is in agreement with Arctic-wide trend.

Analyzing fast ice annual cycle in the East Siberian Sea we describe two modes of fast regime charactered by small (S-mode) and large (L-mode) extent. By liking the occurrence of the modes to thermodynamic and dynamic factors we suggest the large fast ice extent forms during seasons with atmospheric circulating favoring sea ice import to the East Siberian Sea. This likely results in a higher rate of sea ice deformation and formation of grounded sea ice ridges which stabilize extensive fast ice cover. To conﬁrm this hypotheses, the processes of ice ridging in the East Siberian Sea further investigated. Chapter 5

Sediment entrainment into sea ice and transport in the Transpolar Drift: a case study from the Laptev Sea in winter 2011/2012

Reprinted from Continental Shelf Research, Volume 141, C. Wegner1, K. Wittbrodt2, J.A. Hölemann3, M.A. Janout3, T. Krumpen3, V. Selyuzhenok3, A. Novikhin4, Ye. Polyakova5, I. Krykova6, H. Kassens1, L. Timokhov4, Sediment entrainment into sea ice and transport in the Transpolar Drift: a case study from the Laptev Sea in winter 2011/2012, Pages 1-10, Copyright (2017), with permission from Else- vier.

1 GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany 2 Christian-Albrechts University, Kiel, Germany 3 Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremer- haven, Germany 4 State Research Center - Arctic and Antarctic Research Institute, St. Petersburg, Russia 5 Lomonosov Moscow State University, Moscow, Russia 6 P.P.Shirshov institute of Oceanology, Russian Academy of Sciences, Moscow, Russia

51 52 Chapter 5 Sediment entrainment in fast ice

Continental Shelf Research 141 (2017) 1–10

Contents lists available at ScienceDirect

Continental Shelf Research

journal homepage: www.elsevier.com/locate/csr

Research papers

Sediment entrainment into sea ice and transport in the Transpolar Drift: A MARK case study from the Laptev Sea in winter 2011/2012 ⁎ C. Wegnera, K. Wittbrodtb, J.A. Hölemannc, , M.A. Janoutc, T. Krumpenc, V. Selyuzhenokc, A. Novikhind, Ye. Polyakovae, I. Krykovaf, H. Kassensa, L. Timokhovd a GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany b Christian-Albrechts University, Kiel, Germany c Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany d State Research Center – Arctic and Antarctic Research Institute, St. Petersburg, Russia e Lomonosov Moscow State University, Moscow, Russia f P.P.Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia

ARTICLE INFO ABSTRACT

Keywords: Sea ice is an important vehicle for sediment transport in the Arctic Ocean. On the Laptev Sea shelf (Siberian Sediment transport Arctic) large volumes of sediment-laden sea ice are formed during freeze-up in autumn, then exported and Sea ice transported across the Arctic Ocean into Fram Strait where it partly melts. The incorporated sediments are Sea-ice algae released, settle on the sea ﬂoor, and serve as a proxy for ice-transport in the Arctic Ocean on geological time Continental shelf scales. However, the formation process of sediment-laden ice in the source area has been scarcely observed. Arctic Sediment-laden ice was sampled during a helicopter-based expedition to the Laptev Sea in March/April Siberia Laptev Sea 2012. Sedimentological, biogeochemical and biological studies on the ice core as well as in the water column give insights into the formation process and, in combination with oceanographic process studies, on matter ﬂuxes beneath the sea ice. Based on satellite images and ice drift back-trajectories the sediments were likely incorporated into the sea ice during a mid-winter coastal polynya near one of the main outlets of the Lena River, which is supported by the presence of abundant freshwater diatoms typical for the Lena River phytoplankton, and subsequently transported about 80 km northwards onto the shelf. Assuming ice growth of 12–19 cm during this period and mean suspended matter content in the newly formed ice of 91.9 mg l−1 suggests that a minimum sediment load of 8.4×104 t might have been incorporated into sea ice. Extrapolating these sediment loads for the entire Lena Delta region suggests that at least 65% of the estimated sediment loads which are incorporated during freeze-up, and up to 10% of the annually exported sediment load may be incorporated during an event such as described in this paper.

1. Introduction export (Krumpen et al., 2013). Generally sea ice serves as an important vehicle for sediment transport in the Arctic Ocean (e.g. Polyak et al., Arctic Ocean sea ice extent and thickness, as well as volume and age 2010; Darby et al., 2011). In particular on the Laptev Sea shelf, of multiyear ice has decreased over the last 20 years (e.g. Serreze et al., sediments are incorporated into newly formed ice during autumn 2007; Maslanik et al., 2007; Comiso et al., 2008; Mahoney et al., 2008; freeze-up (e.g. Eicken et al., 1997, Wegner et al., 2005) and transported Kwok et al., 2009). This decrease is concurrent with an increase in the across the Arctic Ocean via the Transpolar Drift toward Fram Strait and Arctic sea ice drift speed of about 10% decade−1 with the strongest the East Greenland shelf, where the ice melts and releases the material increase after 2004 (46% decade−1; Spreen et al., 2011). With into the water column (e.g. Reimnitz et al., 1994; Dethleﬀ et al., 2000, decreasing ice coverage and the recent high sea ice export through Eicken et al., 1997, 2000). The Laptev Sea shelf is ice covered from Fram Strait, the annual sea ice export increased by 5% (Smedsrud mid-October until June and features fast ice, ﬂaw polynyas, and drift et al., 2011). A substantial part of the sea ice found in Fram Strait is ice (Bareiss and Görgen, 2005). Fast ice covers more than 50% of the assumed to be formed on the Siberian shelf seas, in particular in the shallow eastern Laptev Sea shelf and up to 25% of the western Laptev Laptev Sea as the most important region for sea-ice production and Sea (Bareiss and Görgen, 2005). Its extent roughly coincides with the

⁎ Correspondence to: Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany. E-mail address: [email protected] (J.A. Hölemann). http://dx.doi.org/10.1016/j.csr.2017.04.010 Received 15 September 2015; Received in revised form 26 April 2017; Accepted 28 April 2017 Available online 29 April 2017 0278-4343/ © 2017 Elsevier Ltd. All rights reserved. 53

C. Wegner et al. Continental Shelf Research 141 (2017) 1–10 position of the 20 m isobath (Bareiss and Görgen, 2005). Polynyas are an electrical conductometer (HI 8733, Hanna Instruments). open water regions that develop north of the landfast ice edge during Complementary water samples were collected during the expedition offshore-directed winds (Bareiss and Görgen, 2005). Mean polynya on the fast ice near the major outlets of the Lena River (TI12_03, areas in the central Laptev Sea range from 20×103 km2 in May to TI12_05, TI12_10) and near the fast ice edge of the West New Siberian 90×103 km2 in July (Bareiss and Gören, 2005). The largest polynya Polynya (TI12_01, TI12_06, TI12_09). Under-ice seawater for phyto- with an area of 4×103 km2 in winter is the West New Siberian Polynya plankton study was sampled with a Niskin water sampler at standard (Zakharov, 1966; Bareiss and Görgen, 2005). Sediment entrainment water depths. Wind conditions during sampling varied between processes on the vast Siberian shelf seas are assumed to be most 4.9 m s−1 at TI12_06 and 12 m s−1 from E at TI_12_01 and _02. effective during the autumn freeze-up (Eicken et al., 2005; Wegner Atmospheric conditions and climatological reference for mean et al., 2005) in water depth less than 20 m (e.g. Kempema et al., 1989; November-December winds were investigated based on NCEP Sherwood, 2000). Previous studies suggested that suspension freezing Reanalysis over the eastern Lena Delta (Fig. 2). also takes place in polynyas in late-winter in water depths between 20 and 30 m (e.g. Dethleff, 2005). Sediments are generally incorporated 2.1. Quantitative and qualitative SPM analysis into sea ice by two entrainment processes: primarily by suspension freezing in frazil ice (e.g. Reimnitz et al., 1992; Eicken et al., 2000; SPM was measured from the ice core and water column samples. Dethleff and Kempema, 2007) and to a smaller extent by anchor ice For quantitative studies in the water column direct (water sampling) entrainment (e.g. Darby et al., 2011). Suspension freezing requires and indirect measurements (turbidity measurements) were carried out. open water to allow for wave activity, bottom currents or wind-driven SPM concentrations from water and melted sea ice samples were Langmuir helical cells, leading to resuspension of bottom sediments derived by filtering the samples through pre-weighed filters during episodes of frazil ice formation (e.g. Eicken et al., 2005, Dethleff (MILLIPORE Durapore membrane filters, 0.45 µm pore size) by and Kempema, 2007). Shelf sources in sea-ice samples from the outer applying the traditional weighing procedures. A Seapoint turbidity Laptev Sea and from Fram Strait were mainly identified based on meter connected to a CTD (Conductivity Temperature Depth; sedimentological, clay mineralogical and geochemical aspects (e.g. SBE19plus, Seabird, USA) was used in order to collect water column Eicken et al., 1997; Dethleff, 2005; Dethleff and Kuhlmann, 2010). turbidity, salinity, and temperature measurements. The turbidity meter However, only few direct observations of sediment entrainment into emits light of 880 nm wavelength with a sampling rate of 10 Hz. It sea ice exist from the Siberian shelves (e.g. Hölemann et al., 1999a, detects light scattered by particles within the water column and 1999b; Lindemann et al., 1999), mainly due to the region’s inaccessi- generates an output voltage proportional to particles in the water bility during early and mid-winter. column, with high backscatter indicating high SPM concentration. The In the Chukchi and Beaufort Seas, there is evidence for an increase output is given in Formazine Turbidity Unit (FTU), a calibration unit of sediment-laden ice due to an increase in mid-winter landfast ice based on formazine as a reference suspension. break-out events (Eicken et al., 2005). In the Laptev Sea, Krumpen Additionally the echo intensity of the upward-looking ADCP et al. (2013) observed a positive trend in sea ice export from the shelf (Acoustic Doppler Current Profiler; Workhorse Sentinel 300 kHz, during the last 20 years, likely as a consequence of a thinning and more RD-Instruments) deployed at the mooring station Khatanga was used mobile ice cover. Changes in the amount of sediment-laden ice not only as a relative measure for SPM concentration in the entire water column impact the across- and along-shelf transport of suspended particulate with increased echo intensity indicating increased SPM concentration matter (SPM), but also the biological productivity in and below the sea (e.g. Gartner and Cheng, 2001, Wegner et al., 2006). ADCP measure- ice (e.g. Eicken et al., 2005, Junge et al., 2004) as well as the potential ments were carried out at intervals of 1 min and averaged over 30 min dispersion of pollutants. However, the implications of changing sea ice in 1 m depth bins with the first bin measuring 3 m above bottom. For conditions on the Siberian shelves for sediment entrainment, export more information on the Khatanga mooring and data processing please and transport across the Arctic Basin are poorly understood. refer to Hölemann et al. (2011) and Janout et al. (2013). A helicopter-based Russian-German expedition to the southeastern For qualitative studies regarding grain size distribution and SPM Laptev Sea in late winter (TRANSDRIFT XX; 19 March – 24 April composition scanning electron microscope (SEM) measurements with 2012) provided the rare opportunity to study sediment-laden sea ice by a CamScan-CS-44 were carried out at the REM-laboratory in the sampling and analyzing ice cores and water column parameters. Institute of Geosciences at the Christian-Albrechts-University Kiel Biogeochemical, sedimentological and microalgae analysis of the sea (Germany) on filtered water (TI_12_06) and sediment-laden sea ice ice core are combined with fast-ice based water sampling and remote samples (TI_12_07). sensing data to reconstruct the origin and entrainment conditions and discuss the importance of sea ice transport for sediment export from 2.2. Nutrients the shelf. In addition a year-round oceanographic mooring “KHATANGA” deployed in the vicinity of the West New Siberian Nutrients were sampled in the water column as well as in sea ice. Polynya (Fig. 1) was investigated for potential entrainment processes The sea ice samples were filtered when necessary. The 125 ml samples in the polynya region. were added to Nessler cylinders with 35 ml for silicates and with 50 ml for phosphates analysis. 4 ml of a mixed reagent and 1 ml of ascorbic 2. Material and method acid were added sequentially to the phosphate samples in order to analyze the samples with a photo-colorimeter FC-3 after a 10-min The ice core was drilled on the fast ice of the inner eastern Laptev exposure. 1 ml of a mixed reagent, 1 ml of oxalic and 1 ml of ascorbic Sea shelf (TI12_07; Fig. 1) on 12 April 2012 at air temperatures of acid were added sequentially to the silicate samples to obtain the color. −20 °C using an electromechanical ice corer (Kovacs Enterprise, USA) They were analyzed after 30 min' exposition with a photo-colorimeter with an inner core diameter of 9 cm. The 1.80 m long sea ice core FC-3. All frozen samples were then transported to the Russian-German contained layers with sediment inclusions in the upper parts of the Otto Schmidt Laboratory for Polar and Marine Research (OSL) in St. core. The ice core was placed in polyethylene bags and transported Petersburg and analyzed with an autoanalyzer Skalar Sun Plus System. frozen to the land-based laboratory in Tiksi. Within several hours after coring the ice core was split into 10 cm long segments, and placed in 2.3. CDOM absorption polyethylene boxes to melt in the dark at room temperature for SPM and colored dissolved organic matter (CDOM) analysis, and at < 4 °C Immediately after melting the sea ice samples were subjected to for phytoplankton investigations. Sea ice salinity was determined with vacuum filtration (with a 250 ml Nalgene filtration set at approx. 400

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Fig. 1. Bathymetric map of the Laptev Sea. The black rectangle shows the position of the detailed ENVISAT synthetic aperture radar (SAR) scene of the eastern Laptev Sea shelf from April 8, 2012 with the ice coverage of the area, the locations of the presented measuring sites during TRANSDRIFT XX and of the long-term mooring station KHATANGA.

Fig. 2. a) 6-hourly zonal NCEP winds (blue bars) and total wind speed (red line) [m s−1] in November – December 2011 around the assumed entrainment period (green box) over the eastern Lena Delta (72.5°N, 130°E). (b) Mean November-December zonal wind anomalies (blue bars) [m s−1] including one standard deviation (dashed lines). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) mbar) through a Whatman GF/F glass microfiber filter (4.7 cm into two storage bottles (high density polyethylene), and stored in a diameter) with a nominal pore size of approx. 0.7 µm. The filter was dark and cold environment. CDOM was measured immediately after pre-washed with ~20 ml Milli-Q water and ~ 20 ml of the seawater the expedition at the OSL using a UV/VIS Spectrophotometer sample. After washing the filter, 200 ml of seawater was filtered, filled (Specord200, analytik jena). Optical Density (OD) spectra of the

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filtrates were measured from 300 nm to 750 nm in 1 nm steps using a In the sediment-laden core Section 2 (10–70 cm) SPM concentra- 10 cm cuvette. Absorption (m−1) was calculated using 2.303×OD/0.1. tions varied between 57.3 and 144.1 mg l−1 with the maximum In this study, we present the CDOM absorption at a wavelength of concentration at 30–40 cm core depth (Fig. 3). The SEM picture of 375 nm. one of the ice core filters with high SPM concentration is characterized by a constant background matrix of particles and valves of the 2.4. Algae processing and enumeration planktonic diatom Thalassiosira antarctica (Fig. 4). The majority of the particles are smaller than 10 µm, only rarely exceeding 30–40 µm. The melted sea ice and under-ice seawater samples were filtered The phosphate concentration reached its maximum of 6.4 µmol l−1, through nuclear pore filters (1 µm pore size) at a pressure of < 0.2 bar which is an order of magnitude higher than the summer concentration until 10–30 ml of melt water or seawater remained over the filter. The in the Laptev Sea (0.5–1.4 µmol l−1; Pivovarov et al., 2004) and the remaining samples were fixed with neutralized formalin to a final winter concentration in the Lena River (0.1–0.36 µmol l−1, Arctic Great concentration of 4% in the laboratory in Tiksi. Further processing of all Rivers Observatory). Studies on first-year sea ice in the Sea of Okhotsk samples was carried out at the OSL and the Lomonosov Moscow State showed the same correspondence of sediment-laden layers and ex- University (Geographical Faculty, Scientific-Research Laboratory of tremely high phosphate concentration considerably enriched compared Pleistocene Palaeogeography). The algae were washed off the filters by to the seawater signal suggesting remineralization of the incorporated means of a soft brush and re-suspended in petri-dishes. In case the particulate organic matter (Nomura et al., 2010). Although the initial algae concentration was low the sample was concentrated and mixed concentrations of CDOM and inorganic nutrients in the water column thoroughly before analysis (Okolodkov, 1992, 1996). are not known, the results indicate that dissolved nutrients and CDOM, The enumeration and identification of microalgae cells were carried like the sea salt, are not completely removed from the ice during the out in 0.05-ml Naujotte counting chamber under a Zeiss Axioscope-40 freezing process. Nevertheless, seawater in the near-delta mixing zone non-inverted light microscope at a magnification of 100 - 400. If (salinity ~5) usually shows CDOM absorptions that are an order of sufficient material was available > 300 cells were counted. The bio- magnitude higher than the values that were measured in dirty sea ice of volume was calculated from the volumes of appropriate stereometrical the same salinity (~7 m−1 vs. ~0.64 m−1 at 375 nm). The ice core bodies (Hillebrand et al., 1999; Olenina et al., 2006). Taxa were further contained numerous and abundant freshwater diatoms, which identified to species level according to Medlin and Priddle (1990), are typical for the Lena River phytoplankton (Aulacoseira islandica, Tomas et al. (1996), Bérard-Therriault et al. (2000), Gogorev et al. A.italica and others). They comprised 21.79 – 22.25% of total diatom (2006). The ecological preferences of diatom and dinoflagellate species abundances. and their phytogeographical distribution were identified in accordance Section 3 (70–130 cm) is defined by low SPM and phosphate with Pankow (1990), Okolodkov and Dodge (1997), Okolodkov (2005), concentrations, CDOM absorption, and algal abundances. Polyakova (2003), and Poulin et al. (2011). Section 4 (130–180 cm) is the youngest part of the sea ice core and characterized by low SPM. Phosphate concentrations slightly increase 2.5. Remote Sensing, ice age reconstruction, and back-trajectories up to 1.14 µmol l−1 at the ice-water interface, suggesting that the spring calculations bloom started at the time of sampling. CDOM absorption increased probably due to autochthonous CDOM caused by high algal abun- In this paper, we reconstruct the age and origin of fast ice in the dances. The algal abundances and biomass reached their maximum vicinity of the sampling sites TI12_01_06 & _07, TI12_03_05 & with up to 118.4 cells/ml and 18482.9 µg C ml−1. The ice-associated _010 and TI12_02_07 using Environmental Satellite (ENVISAT) species which were recorded in the lower part of the ice core (130– imagery. In total, 30 synthetic aperture radar (SAR) scenes were 180 cm) are common in early-spring sea-ice communities in the Arctic obtained over the south-eastern Laptev Sea between November 2011 region. All of these species belong to the same class (Bacillariophyceae and April 2012. The data are VV polarized with a spatial resolution of or diatoms). Pennate diatoms (bilaterally symmetrical; Pauliella tae- 150 m×150 m and a footprint of 400 km×400 km. niata, Navicula vanhoeffenii, Fragilariopsis oceanica, F. cylindrus, The fast ice age and origin as well as subsequent pathways of the Nitzschia frigida, N. neofrigida, Fossula arctica, Haslea vitrea, sampled sites were determined by means of geographical information Pseudogomphonema arcticum, Entomoneis kjelmanii) dominated in software (ArcGIS, ESRI). First, prominent fast ice features such as the lower part of the ice core ( > 70% of total biomass and abundance; zones of homogenous backscatter that are likely to be of same age, were Fig. 3b). They occurred as solitary cells or as ribbon-shaped colonies. manually identified on SAR images obtained in March 2012. Then The cell size (length) varied from 10 to 100 µm. The lowermost part of these zones were identified on the preceding images and thereby traced the core (170–180 cm) was characterized by a presence of typical backward in time until they reach an area where intensive ice Arctic early-spring marine planktonic species (Thalassiosira nordens- production took place. Thus the origin of ice formation and ice drift kioeldii, Сhaetoceros socialis). These are centric diatoms (radially vectors were reconstructed. symmetrical) which usually form colony consisting of several cells. The average cell size (width) was > 50 µm. The highest algae abun- 3. Results dances and biomass is found in the lowermost part of this first-year sea ice core, which agrees well with previous sea-ice studies (e.g., Poulin 3.1. Sedimentological and biogeochemical properties of the sea ice et al., 1983; Syvertsen, 1991; Okolodkov, 1992, 1996; Melnikov, 1997; core Melnikov et al., 2002).

Generally the ice core TI12_07 can be divided into four different 3.2. Under-ice sediment dynamics sections in terms of SPM and phosphate concentrations, CDOM absorption and algal abundances (Fig. 3). Sea ice salinities varied Generally the SPM concentrations in the upper 10 m of the water between 8 and 4 in the older part (0–40 cm core depth) and around 4, column were low with 0.3–1.1 mg l−1 (Fig. 5). Maximum concentra- so that the near steady state salinity value for sea ice was reached (Notz tions of up to 10 mg l−1 were found near the seafloor in the bottom and Worster, 2008) in core sections > 60 cm core depth (Fig. 3). nepheloid layer (Fig. 5b). Turbidity meter measurements generally Section 1 (0–10 cm) is influenced by surface processes, and was present similar patterns at the northernmost stations (TI12_01, _06, partly covered by snow. It is characterized by high salinity and low SPM _09; Fig. 5b, e) with low turbidity in the upper water column and a and phosphate concentrations, CDOM absorption, and the absence of pronounced layer of increased turbidity close to the bottom, character- algae cells. istic for the 5–9 m thick bottom nepheloid layer. At the ice core stations

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−1 −1 -l Fig. 3. (a) Salinity (orange), phosphate concentration (PO4 [µmol l ], red), CDOM absorption at 375 nm ([m ], blue), SPM concentration ([mg l ], purple), and (b) algal abundances [cells ml−1] in the ice core TI12_07. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

Fig. 4. Scanning electron microscope (SEM) pictures of (a) sea ice sample TI_12_07 from 10 to 20 cm core depth with a SPM concentration of 57.3 mg l-l, water samples from (b) 2 m water depth just beneath the sea ice with a SPM concentration of 0.6 mg l-l, and (c) from the bottom nepheloid layer in 17 m water depth with a SPM concentration of 10 mg l-l.

(TI12_02, _07; Fig. 5c, f) the turbidity measurements revealed a salinity increased in the surface layer during the repeat-sampling of bottom nepheloid layer as well as increased turbidity in the upper 2 m this station (TI12_02 & _07; Fig. 5f). The southernmost station suggesting a slight inﬂuence of riverine waters (Fig. 5f), even though (TI12_05, _10; Fig. 5a, d) did not show a bottom nepheloid layer at

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Fig. 5. Turbidity [FTU] and salinity distribution in the water column at the southern (a, d), the northern (b, e) and the sea ice core stations (c, f). any time, but a layer of increased turbidity in the upper 2 m, suggesting diatom fragments belong to marine and freshwater species of a riverine influence. Thalassiosira, Aulacoseira and Cyclotella genera (Fig. 4c), probably Water sampling for the analysis of under-ice phytoplankton dis- originating from the bottom sediments. tribution at the ice core position was conducted twice on 27 March The acoustic record at Khatanga shows generally higher echo 2012 (TI_12_02) and 12 April 2012 (TI_12_07). Obtained results intensity corresponding with increased SPM concentration in the revealed an increase of the algal abundance in the water column. In the bottom nepheloid layer, while the echo intensity near the surface was end of March (TI12_02; results not shown) only single cells of sea-ice low, suggesting very low SPM concentration in the upper water column diatoms (Entomoneis kjelmanii, Nitzschia frigida, Pauliella taeniata) (Fig. 7). In general the depth-averaged echo intensity decreased and dinoflagellates (Dinophysis acuminate, Protoperidinium ovatum) gradually from December 2011 until March 2012, and SPM dynamics were found in the upper water column (2–10 m). In the middle of April slowed down. Beginning in mid-May 2012, the echo intensity in the (TI12_07; Fig. 6a) total algae abundances was slightly higher (5.7 near-surface layer suddenly increased, which may be indicative of cells/l) compared to our March records. . Sea-ice diatoms (Pauliella riverine influence due to the high number of particles that are usually taeniata, Fragilariopsis oceanica, Nitzschia frigida) dominated as- found in the Lena River plume (e.g. Wegner et al., 2005). semblages (75.3–100%) throughout all depths, which may be due to vertical mixing of the water column. In the uppermost layer (2 m) and 4. Discussion in 15 m water depth algae assemblages contained freshwater, mainly riverine planktonic diatoms (Aulacoseira italica, A. islandica; Fig. 4b). Sediment entrainment into sea ice during autumn freeze up in the The average particle size was ≤10 µm. SEM pictures from the bottom Siberian Arctic Shelf Seas is well documented in water depths of less nepheloid layer in contrast were characterized by a constant matrix of than 20 m (Eicken et al., 1997; Hölemann et al., 1999a; Lindemann, 5 µm particles, reaching rarely 10 µm (Fig. 4c). The small amount of 1999; Eicken et al., 2000). Modelling studies, laboratory experiments

Fig. 6. (a) Total algae abundances [cells ml−1] (blue), portion of freshwater diatoms (purple), of sea-ice diatoms in the marine group (green), and of the marine-brackish diatoms (red) beneath the sea-ice core (TI12_07); (b) SPM concentration [mg l-l] from water samples from the northernmost station (TI12_06, purple, TI12_09, red), and sea ice core position (TI12_07, green). (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

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Based on theoretical considerations it was proposed that sediment suspension freezing can also take place in winter polynyas in water depths between 20 and 30 m (Dethleff, 2005). However, while mooring-based observations from the Laptev Sea shelf did indicate frazil ice formation, they did not show any sediment incorporation within the West New Siberian Polynya region in water depths of ~25 m (Dmitrenko et al., 2010) probably due to missing SPM at those depths where frazil ice forms. At the long-term mooring Khatanga peaks in echo intensity in the bottom nepheloid layer were not reflected in the surface layer (Fig. 7) indicating that upward-mixing of material was not taking place. Earlier studies on winter sediment dynamics on the Laptev Sea shelf highlighted events of bottom-sediment resuspension and transport within the West New Siberian Polynya, but no upward mixing of material in the upper water column (Wegner et al., 2005). As data from long-term mooring deployments in mid-shelf polynyas (water depth > 20 m) provide no indication of sediment entrainment, the formation of sediment-laden sea ice in shallow coastal areas during the first month of winter seems to be the dominant process that leads to the formation of sediment-laden sea ice in the Laptev Sea. Unfortunately, the majority of sea ice that formed during early winter Fig. 7. Echo intensity at the 43 m-deep long-term mooring from October 2011 to June in the coastal area is already far off shore at the end of winter 2012 near the bottom (37–39 m water depth; blue), near the surface (3–7 m water (Krumpen et al., 2013) and therefore out of range for helicopter based depth; red), and depth averaged (black) with generally higher intensities and therefore higher SPM concentration in the bottom nepheloid layer. The depth-averaged echo expeditions which require daylight due to safety regulations. Therefore intensity decreased gradually from December 2011 until March 2012, because material sediment-laden sea ice from near-shore polynyas that is eventually partly settled and SPM dynamics slowed down. The distinct increase in mid-May 2012 incorporated into the immobile fast ice belt provides an excellent might be related to the riverine influence. (For interpretation of the references to color in opportunity to study the sediment entrainment process in near-shore fi this gure legend, the reader is referred to the web version of this article.) polynyas. Sea ice back-trajectories indicate a shallow (~10 m) near-shore area fi and eld observations (Sherwood, 2000; Smedsrud, 2003) have shown close to one of the main outlets of the Lena River as a potential source that wave-induced turbulence and sediment resuspension in combina- region for the sampled sea ice (Fig. 8) in this study. Based on a fi tion with freezing in unstrati ed waters are essential requirements for reconstructed sea ice age of 92 days (Fig. 8) its formation time was sediment entrainment into newly formed sea ice. The Laptev Sea has as around 5 December 2011. SAR images from December 5–10, 2011 much as 1000 km of fetch at the end of summer, when freezing storms show a period when the fast ice opened near the main Lena River outlet move in and large waves can form. In addition, during early winter and frazil ice formation took place (Fig. 9). Due to prevailing westerly (October-December), the polynya is maintained in the vast sediment- winds with speeds > 15 m s−1 (Fig. 2a) the open water area enlarged laden near-shore waters between the coast and the ~10 m-isobath and new ice formation continued until December 10, 2011 (Fig. 9b). (Reimnitz et al., 1994) and thus provides ideal conditions for sediment These high wind speeds are within one standard deviation of the long- entrainment. term mean during this time of year (Fig. 2b), suggesting that near-

Fig. 8. Fast ice age and sea-ice drift reconstructions for the entire TRANSDRIFT XX region with the red line marking the fast ice edge during the expedition (a), details for the ice core position (b) and a photograph of the sampled ice core at TI12_07 (c). (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

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Fig. 9. ENVISAT SAR scene of the eastern Laptev Sea shelf from December 5, 2011 (a), showing a very narrow strip of fast ice along the Lena Delta coast and the pack ice zone east of the fast ice edge. The scene from December 10, 2011 (b) additionally shows an open-water area with new ice formation (coastal polynya) in the potential formation area of the sea ice core (TI12_07) between the fast ice and the pack ice zone east of the fast ice edge. The striped area represents the open water area used for sea ice formation estimates.

shore polynya events such as the one described in this study might be Ocean into Fram Strait might be small during years of high winter ice quite common during prevailing westerly winds. The water depth in the export, when the exported ice cover is generally thinner (Krumpen specific formation area is about 10 m and shallow enough that waves et al., 2013) and therefore melts faster and might hence release and/or wind-induced currents could have resuspended sediments. sediments earlier within the Transpolar Drift. As surface waves are a function of fetch and wind speed, the potential wave height generally deceases with wind fetch (Pavlov, 1996; 5. Summary and conclusions Lintern et al., 2013). However, studies within the potential source area during freeze-up in October 1995 with calm weather conditions and A sediment-laden sea ice core was sampled during a helicopter- mean wave heights of 1 m (Lindemann et al., 1999) found SPM based expedition to the Laptev Sea in March/April 2012, which allowed concentrations in sea ice up to 250 mg l−1, with a median SPM content for new insights regarding the incorporation of sediments into sea ice of 149 mg l−1 (Lindemann et al., 1999). These numbers are similar to during winter. Sedimentological (SPM concentration, SEM analysis), the maximum content found after the nearshore ice-formation event biogeochemical (CDOM absorption, nutrients) and biological (algal described in this study that occurred much later in the year than in abundances) studies on the ice core in combination with satellite 1995. After its formation, the sea ice drifted about 85 km to the images and ice drift back-trajectories allowed to reconstruct the sampling area. formation process and area. The sediments were found in the upper The sediments in sea ice core Section 2 cover a wide range of grain part of the core (10–70 cm, Fig. 3) along with abundant freshwater sizes with particles of up to 30 µm and fresh water diatoms (Fig. 4), diatoms typical for Lena River phytoplankton and further with max- which might be related to the bottom material in the source area. The imum phosphate concentrations being an order of magnitude higher dominant particle size of 5–10 µm comprises the typical range for SPM than Laptev Sea summer and the Lena River winter concentrations. (Dethleff and Kuhlmann, 2010). Sections 3 and 4 of the sea ice core can The sediments were incorporated near the shallow (10 m) Lena Delta be related to the period of ice growth during drift (Fig. 3). during a nearshore polynya event, caused by westerly winds of > We estimated a maximum open water area of 7630 km2 (Fig. 9b) 15 m s−1 (Fig. 2). The event likely caused wave- or current-induced for the nearshore polynya event in December 2011 for 3–5 days. The resuspension of bottom sediments, which were then incorporated into ice growth rate calculated from a simple freezing degree days model frazil ice and transported ~ 80 km northeastward onto the shelf results in the formation of 12–19 cm of ice during this period. (Fig. 8). Complementary fast ice-based water column and oceano- Assuming a mean SPM content in the newly formed ice of graphic process studies near the Lena Delta and the West New Siberian 91.9 mg l−1 suggests that 8.4×104 - 1.3×105 t of sediments might have Polynya during March/April 2012 found no evidence for sediment been incorporated into sea ice in this polynya. Extrapolating these incorporation into sea ice near polynyas, but instead showed near- sediment loads for the entire Lena Delta region suggests that about bottom matter transport beneath the sea ice during winter. The event 3.9×105 t could be incorporated during such an event and subsequently lasted for 4 days and affected an area of ~ 7630 km2 and results in an transported onto the outer shelf or even off-shelf. This sediment load estimated total sediment incorporation of 8.4×104 - 1.3×105 t, which would be 65% of the minimum estimated sediment loads of 6×105 t suggests that these events provide a significant contribution to the (Lindemann, 1998) to be incorporated during freeze-up and 9.8% of variability of the Laptev Sea’s sediment budget. sediments to be exported annually off the Laptev Sea shelf (roughly Studies on the Chukchi and Beaufort shelves (Eicken et al., 2005) 4×106 t; Eicken et al., 1997, 2000). Nearshore polynya events such as suggest an increase of sediment entrainment into sea ice in late winter the one described in this paper might therefore contribute significantly due to changes in the sea ice regime towards more frequent mid-winter to the sediment export into the deep Arctic Ocean. However, the breakup events. If a similar trend existed on eastern Arctic shelves, an contribution of these events on the sediment budget across the Arctic increase in the occurrence of sediment-laden ice can be expected in the

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Laptev Sea as well, which might then impact the regional sediment saline water in response to sea ice drift on the Laptev Sea shelf. J. Geophys. Res. Oceans 118, 563–576. http://dx.doi.org/10.1029/2011JC007731. budget and further have consequences for radiation balance within the Junge, K., Eicken, H., Deming, J.W., 2004. Bacterial activity at -2 to -20 °C in Arctic export pathways of the Laptev Sea ice in the Transpolar Drift. winter time sea ice. Appl. Environ. Microbiol. 70, 550–557. Kempema, E.W., Reimnitz, E., Barnes, P.W., 1989. Sea ice sediment entainment and rafting in the Arctic. J. Sediment. Res. 59 (2), 308–317. Acknowledgement Krumpen, T., Janout, M., Hodges, K.I., Gerdes, R., Girard-Ardhuin, F., Hölemann, J.A., Willmes, S., 2013. Variability and trends in the Laptev Sea outflow between 1992– This work was carried out as part of the Russian-German coopera- 2011. Cryosphere 7, 349–363. http://dx.doi.org/10.5194/tc-7-349-2013. tion “Laptev Sea System”, funded by German Federal Ministry of Kwok, R., Cunningham, G.F., Wensnahan, M., Rigor, I., Zwally, H.J., Yi, D., 2009. Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008. J. Geophys. Education and Research (grant BMBF 03G0833) and the Ministry of Res. 114, C07005. http://dx.doi.org/10.1029/2009JC005312. Education and Science of the Russian Federation. The authors thank Lindemann, F., Hölemann, J.A., Korablev, A., Zachek, A., 1999. Particle entrainment into – the scientists and helicopter pilots for their support during the newly forming sea ice freeze-up studies in October 1995. In: Kassens, H., Bauch, ’ H.A., Dmitrenko, I., Eicken, H., Hubberten, H.-W., Melles, M., Thiede, J., Timokhov, expedition and Matt O Regan and one anonymous reviewer for their L. (Eds.), Land-Ocean Systems in the Siberian Arctic: Dynamics and History. stimulating reviews of this manuscript. 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Chapter 6

Discussion and Outlook

Using operational sea ice charts from Arctic and Antarctic Research Institute (AARI), we analyze seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea (Chapters 2) and in the East Siberian Sea (Chapters 4) during the past 1.5 decades. With this study we provide the most up-to-date information on the fast regime and it’s the recent changes in the Siberian Arctic. Our findings confirm previously reported arctic-wide trends toward a shortening of the fast ice season (Yu et al., 2014). In Chapters 2, we show that the shortening of the fast ice season, in both the Laptev Sea and East Siberian Sea is the consequence of a delayed formation of fast ice (due to a later freezeup) and earlier fast ice disintegration (due to an earlier river breakup and rising air temperatures in spring). The shortening of the fast ice season has far-reaching implications for the coastal environment. A shorter fast ice season leads to an increased impact of waves on the coast, which intensifies coastal erosion. According to Overduin et al. (2014) the rate of coastal erosion in the Laptev Sea almost doubled since the beginning of the 21-st century, which might be partially explained by the shortening of the fast ice season length. Furthermore, in areas of high biogeochemical activity such as the East Siberian shelf, a shorter fast ice season can lead to an acceleration of submarine permafrost degradation (Semiletov et al., 2012) and an increase in the amount of methane release (Shakhova et al., 2010b). Later formation of fast ice may further lead to higher frequencies of coastal polynyas in winter, intensified ice production and water mass modification, as well as an increase in the rates of sediments being incorporated into sea ice (Chapter 5). As the presence of sediment in the sea ice decreases the surface albedo, higher sediment rates could intensify sea ice melt leading to a more rapid disintegration of fast ice in spring. Finally, fast ice is used to access and supply remote settlements situated along the coast of the Laptev and East Siberian sea. A shortening of the fast ice season due to later formation and earlier breakup, may limit accessibility of these areas.

Although fast ice in the Laptev Sea and East Siberian Sea tends to form later and breakup earlier, the winter fast ice extent does not show any signiﬁcant changes during the past 1.5 decades. This is in contrast to ﬁndings of Yu et al. (2014), who showed that

63 64 Chapter 6 Discussion and Outlook

Fast Ice Area 400 ESS, 1999-2016 LS, 1999-2013 +/-2 std +/-2 std 350

300

250 2

km 200 3 10 150

100

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Figure 6.1. Mean seasonal cycle of fast ice area for the south-eastern Laptev Sea (red) and East Siberian Sea (blue). Two standard deviations from the mean indicate the interannual variability of fast ice extent (ﬁlled area). mean winter fast ice area in the Laptev and East Siberian has decreased since 1970s. Nevertheless, the reduction of fast ice winter area might be a part of a multi-decade trend which is not observed on the timescale of our study.

With respect to the maximal extent of fast ice in winter, the Laptev Sea and East Siberian Sea are characterized by significantly different fast ice regimes. While the Laptev Sea fast ice exhibits little interannual variability, winter fast ice extent in the East Siberian Sea strongly varies on interannual timescale (Figure 6.1). By means of high resolution satellite images (SAR) in combination with thickness observations from upward looking sonar and airborne surveys (Chapter 2) and tracking of sea ice parcels (Chapter 4), we show that grounding of sea ice is the key mechanisms controlling maximal fast ice extent in winter in the southern Laptev Sea and East Siberian sea. This finding is in close agreement with numerical simulations that confirm the importance of sea ice grounding for fast ice development. According to Lemieux et al. (2015, 2016) a parameterization representing the effect of grounded ridges lead to a more realistic simulation of fast ice seasonal cycle in the Laptev and East Siberian seas. Since the occurrence of grounding is closely linked to the bathymetry, differences in the annual cycle of the Laptev Sea and East Siberian Sea fast ice are related to contrasting topographic features. Multiple shoals in the southeastern Laptev Sea allows for grounding of relatively thin ice (Chapter 3) which stabilizes the fast ice over a large territory. The expansion of fast ice further offshore contributes to only little (<4.5%) increase in fast ice area. These small variations in winter fast ice extent can be explained by occurrence of grounded sea ice ridges over the water depth greater than 20 m. Ice 65 grounding in deeper shelf of the East Siberian Sea requires thicker sea ice ridges. Such ridges are likely to form during seasons of sea ice import from the east, when sea ice deforms during its drift to the East Siberian Sea shelf (Chapter 4). However, this hypothesis needs to be further verified.

The core fast ice extent dataset used in this work (Chapters 2 and 4) was derived from weekly operational sea ice charts (AARI data set). Since 1998 the charts are produced on a weekly basis and therefore fast ice is deﬁned as the sea ice cover which remains stationary along the coast during a period of two to seven days. The temporal resolution of the charts allows to investigate the interannual variability of fast ice extent and evaluate changes in fast ice regime. However, chart’s temporal and spatial resolution is no suﬃcient to observe small-scale processes such as formation of grounded sea ice features (stamukhi) in the Laptev Sea. In Chapter 3, we therefore apply an alternative method to resolve fast ice growth at high resolution. In particular the application of SAR imagery, with a spatial resolution of less several tens of meters, can contribute to a better understanding of the processes controlling fast ice cover on regional scale. A new method of automatic sea ice drift detection (Demchev et al., 2017) can potentially improve the manual approach of imagery analysis introduced in Chapter 3.

This thesis provides the state-of-the-art knowledge on the Siberian Arctic fast ice, nevertheless few aspects can be addressed in future research. First, the processes of fast ice breakup in the Siberian Arctic are still not fully understood. The fast ice breakup is related to several interacting atmospheric and oceanic processes as well as regional feedback mechanisms. E.g. the onset of fast ice breakup in the southeastern Laptev Sea is controlled by river breakup (Bareiss et al., 1999), while the time it takes for fast ice to completely diminish is rather associated to surface melt and rising temperatures (Chapter 2). A new study of Itkin and Krumpen (2017) indicates that in addition to the onset of surface melt, years of strong oﬀshore advection precondition earlier end of the fast ice season and shortening of the duration of the breakup period, and vice versa. The authors argue that during years of high ice export and early melt of thin ice zones, shallow waters heat up quickly and more heat is available to favor bottom melt of grounded ridges at the fast ice edge. Melting away the anchor points controlling fast ice extent in winter may then accelerate its retreat in spring. The tendency towards earlier fast ice retreat may therefore not only be related to rising temperatures in spring and earlier onset of surface melt, but also to the acceleration of pack ice drift and increased oﬀshore advection. Second, the ecological and oceanographic implication of the changing fast ice regime is a logical area for further research. Finally, assessment of fast ice stability in the Siberian Arctic is a topical direction for research in the context of increasing use of fast ice by industry for transportation and as a platform for exploration.

List of Figures

1.1 Arctic Fast Ice Extent ...... 3 1.2 Cross-sections of Fast Ice Cover ...... 4

4.1 East Siberian Sea bathymetry ...... 41 4.2 East Siberia Sea fast ice annual cycle ...... 44 4.3 S-mode and L-mode fast ice extent ...... 44 4.4 Arctic Oscillation index ...... 46 4.5 Winter wind rose histograms ...... 47 4.6 February-May wind intensity ...... 48 4.7 Wind stress during L-mode development ...... 48 4.8 Ice backtracking ...... 50

6.1 Mean seasonal fast ice cycle: Laptev and East Siberian seas ...... 64

List of Tables

4.1 Key events and identiﬁcation criteria ...... 42 4.2 Variability of dates of the key events ...... 45 4.3 Trends in timing of key events and periods of annual fast ice cycle . . . 45 4.4 Correlation between key events, freezeup and melt onset...... 46 4.5 FDDs and TDDs accumulated prior the key events ...... 46

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Acknowledgements

This work would not have been archived without help of many people. First, I would like to thank my advisors and PhD committee membered Prof. Rüdiger Gerdes, Dr. Thomas Krumpen and Prof. Dr. Joachim Vogt for guiding me through my PhD time. I am especially grateful to Dr. Thomas Krumpen whose keen interest in my work and devoted supervision was a great support at every stage of this project.

I am grateful to Dr. Andy Mahoney and Prof. Dr. Hajo Eicken for the most inspiring and encouraging research experience during my stay at the University of Alaska, Faibanks.

This work was finacialy supported by the Helmholtz Graduate School for Polar and Marine Research - POLMAR. I would like to thank personally Dr. Claudia Hanfland and Dr. Claudia Sprengel for their efforts in creating a perfect environment for POLMAR PhD students.

I am also grateful to the Master Program for Marine and Polar Sciences POMOR for opening up all sorts of possibilities for doing polar research for me and many others.

I would like to thank Nansen International Environmental and Remote Sensing Centre for providing me an opportunity to continue the work on the PhD project during my ﬁnal year.

There are many others in Bremerhaven, Saint Petersburg and Fairbakns who have contributed directly or indirectly to the completion of this project.