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Spatial and temporal variability of sea ice in the Laptev Sea: Analyses and review of satellite passive-microwave data and model results, 1979 to 2002
Global and Planetary Change 48 (2005) 28 – 54 www.elsevier.com/locate/gloplacha
Spatial and temporal variability of sea ice in the Laptev Sea: Analyses and review of satellite passive-microwave data and model results, 1979 to 2002 J. BareissT, K. Go¨rgen University of Trier, Department of Climatology, 54286 Trier, Germany Received 10 October 2003; received in revised form 21 April 2004; accepted 9 December 2004
Abstract Satellite passive-microwave radiometer-derived sea-ice concentrations have been used to investigate the spatial and temporal variability and trends of sea ice in the Laptev Sea during 24 years from 1979 through 2002. The resulting time series have been further analyzed to provide a climatology for sea-ice and polynya characteristics. The ice regime of the Laptev Sea is characterized by a large seasonal and interannual variability, the latter occurring exclusively in summer. By using a consistent sea-ice data record, we can document negative trends in all the areas studied for the 24-year period, Due to the large interannual variability the trends are not significant. For the entire Laptev Sea the decreases in sea-ice extent and area on a yearly average basis reveal 1.5% decade 1 and 1.7% decade 1, respectively. In summer and early fall large losses in sea-ice cover of up to 7% decade 1 are evident in regional sectors of the Laptev Sea. In addition, an increase in polynya activity in late winter and early spring, a significant shift towards earlier snowmelt onset, and an increase of open-water area in early fall indicating an extension of the length of the summer melt period, has been observed. A brief overview of climate and sea-ice research in the Siberian Arctic is presented. According to observational data and numerical experiments there is still a large degree of uncertainty about the role of dynamic and thermodynamic factors and possible feedback mechanisms in the atmosphere–ice– ocean system, which are responsible for the large interannual variability and the retreat of sea-ice coverage as observed in the 1990s. Summer sea-ice anomalies likely result from synoptic-scale processes superimposed by the large-scale atmospheric circulation during summer and to a lesser extent from preconditioning processes in winter and spring. D 2005 Elsevier B.V. All rights reserved. Keywords: sea ice; polynyas; remote sensing; thermodynamic sea-ice model; cyclone detection and tracking; Laptev Sea; Arctic
1. Introduction T Corresponding author. Fax: +49 651 201 3817. E-mail addresses: [email protected] (J. Bareiss), [email protected] (K. Go¨rgen). 0921-8181/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.gloplacha.2004.12.004
Arctic sea ice and its variability play a crucial role in the regional and Northern Hemisphere climate system as well as global ocean circulation (Zakharov,
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1997). It moderates the energy balance by changing the surface albedo of the ocean and controls the vertical fluxes of heat, mass and momentum between the ocean and the atmosphere. Furthermore, sea ice has an impact on the ocean circulation by providing cold and dense water during the freeze-up period and fresh surface water during the melt-season, predominantly formed in the Arctic marginal seas. Because of its thin layer in the ocean, sea ice might be a sensitive indicator of climate change (Barry et al., 1993). Strong couplings exist between the sea-ice cover, atmosphere and ocean. Among the marginal seas of the Arctic Ocean the Laptev Sea (Fig. 1) represents one of the most significant sites of net ice production in the Arctic (Zakharov, 1966; Dethleff, 1995). As much as 20% of the ice area transported through Fram Strait is produced in flaw leads and polynyas of the Laptev
Fig. 1. Map of the Laptev Sea showing the location of sea-ice study sites and the locations of synoptic meteorological (white circles) and hydrological stations (white squares). The gray and hatched boxes mark the fast-ice and polynya study areas (for names refer to text). The black boxes represent the areas of coastal polynyas affected strongly by river discharge. The black solid lines indicate the 20 m and 200 m isobaths.
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Sea (Rigor and Colony, 1997). Therefore the seasonal cycle of sea ice is of fundamental importance for the sea-ice budget and ocean-ice–atmosphere processes in the Arctic. The impact of Lena River discharge, one of the Arctic’s major rivers discharging roughly 530 km3 annually onto the Laptev Sea shelf, is of particular importance for coastal fast-ice processes (Bareiss et al., 1999; Bareiss, 2003). Furthermore, as large amounts of sediments are entrained on the shallow Laptev Sea shelf during ice formation (Eicken et al., 1997, 2000), ice originating from the Laptev Sea largely determines the amount of sediment transport across the Arctic Ocean via the Transpolar Drift System (Nu¨rnberg et al., 1994; Pfirman et al., 1997). Beside the many foci of climate and sea-ice research in the Laptev Sea, the Russian maritime Arctic and Northern Sea Route attracts international attention like the International Northern Sea Route Programme (INSROP) to analyze risks and cost benefits of transit navigation in the Siberian Arctic (Brigham, 2000). In recent decades numerous changes of sea-ice characteristics have taken place in the Laptev Sea. In September 2002 Arctic sea-ice extent and area reached their lowest values observed since 1978 (Serreze et al., 2003). Besides its strong seasonal and interannual variability, observations from satellite passive-microwave data indicate that between 1978 and 1996 the greatest decreases in the Arctic ice extent occurred in the Laptev and East Siberian seas during summer and early fall (Maslanik et al., 1996; Cavalieri et al., 1997; Parkinson et al., 1999). Hydrographic observations made in the 1990s (e.g. Carmack et al., 1995; Steele and Boyd, 1998; Ekwurzel et al., 2001) and results from coupled models of the Arctic Ocean (e.g. Proshutinsky and Johnson, 1997; Zhang et al., 1998; Maslowski et al., 2000) reveal large-scale changes such as an shift of the Transpolar Drift System to the northern boundary of the Beaufort Sea. From analysis of sea-ice motion data in the 1980s and 1990s, Rigor et al. (2002) note a decreasing sea-ice area adjacent to the fast-ice edge in the western part of the Laptev Sea and an increase in ice area in the eastern part, consistent with the observed negative trend in sea-ice concentration during summer. They further report an increase of ice advection away from the coast of the Laptev Sea during winter in the period 1989 to 1998 and simultaneously an increase in the forming of flaw polynyas, enhancing the production
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of thin new ice. Sea-ice thickness measurements in the Laptev Sea carried out in the 1990s indicate significant interannual variability. Haas and Eicken (2001) found a difference of up to 1 m in ice thickness in the years 1995 and 1996 when anomalous low and high sea-ice extents occurred in the Laptev Sea. It is not yet clear whether a thinning of sea ice has taken place, because there is a fundamental statistical sampling problem in analyzing highly variable (both spatially and temporally) ice-thickness time series. There is a diversity of conclusions concerning the driving mechanisms explaining the variability and negative trends in sea-ice conditions in the Laptev Sea. As will be discussed later, some authors assume dynamic and thermodynamic atmospheric or oceanic causes (e.g. Serreze et al., 1993; Proshutinsky and Johnson, 1997; Johnson and Polyakov, 2001; Rigor et al., 2002). It has been reported by Bareiss et al. (1999) that there is no correlation between springtime river discharge and early summer sea-ice decay in the Laptev Sea as a whole. Only in the vicinity of river mouths an impact on fast ice is clearly evident due to freshwater input by Siberian rivers and the forming of coastal polynyas, enhancing the fast-ice retreat. This work is meant to give an overview of the general sea-ice regime in the Laptev Sea. A special focus is on the spatial and temporal variability (both seasonal and interannual) of the sea-ice, polynya and fast-ice areas. Trend analyses are provided for various sea-ice parameters within regional sectors. The reasons for the large variability of sea-ice area or extent, respectively, are discussed by reviewing recent findings of atmosphere/sea-ice/ocean interactions. These results are supplemented by analyses of the impact of river discharge on fast ice by using a thermodynamic sea-ice model that incorporates river water.
2. Data and methods Satellite-derived passive microwave data is used to obtain time series of sea ice and fast ice in selected regions of the Laptev Sea (Fig. 1). These time series are further used to derive polynya characteristics with a simple threshold technique validated with visible satellite data. The influence of river discharge on the
seasonal fast-ice retreat in the vicinity of the river deltas and estuaries in the Laptev Sea is studied by using a thermodynamic sea ice model and by quantifying the impact parameters on the simulated processes. 2.1. Deriving time series of sea-ice area Satellite passive-microwave data provide sea-ice concentrations and polynya characteristics for all seasons from 1979 through 2002. Consistent iceconcentration data, based on the NASA-Team algorithm (Gloersen et al., 1992; Cavalieri et al., 1999), have been derived from the Scanning Multichannel Microwave Radiometer (SMMR) and since 1987 from the Special Sensor Microwave Imager (SSM/I) at the 37 GHz and 18 GHz (or 19 GHz) channels as provided by the National Snow and Ice Data Center (NSIDC) and the NASA/Goddard Space Flight Center (NASA/GSFC). SMMR data is available on an alternate-day basis, SSM/I data on a daily basis. Total sea-ice concentrations (first-year and multi-year sea ice) from both radiometers are mapped on an equalarea grid with a cell size of 625 km2 (25 km 25 km). Passive microwave derived sea-ice products are sensitive to calibration drift, sensor differences as well as the use of different land and ocean masks, tiepoint adjustments and quality controls by NSIDC and NASA/GSFC. Other sources of error in the ice retrievals include possible effects such as thin ice (new ice, nilas, young ice), snow melt (increase of snow wetness, meltponding) and atmospheric effects (water vapor, liquid water), e.g. Grenfell et al. (1992), Cavalieri et al. (1995), Comiso and Kwok (1996), Fetterer and Untersteiner (1998). Values from both sea-ice data sets reveal no appreciable differences (Serreze et al., 2003). There are minor inconsistencies among sensors and data sets as well as some general loss of information, due to the coarse resolution of SMMR and SSM/I data. Although there are some deficiencies, derived time series from sea-ice concentrations provide valuable details of the variability of sea-ice (drift ice, fast ice) and polynyas (open-water area, location, date of opening, closing and duration of polynya events) on a repetitive basis. The sea-ice data set used in this study has undergone additional processing. Temporal gaps in the SMMR data have been filled by linear interpola-
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tion between adjacent days. A combined land mask of the NSIDC and NASA/GSFC data sets has been applied to the ice concentrations fields. In mapping sea-ice conditions close to land there is always a potential risk of mixing the emissivities from sea ice and adjacent land due to the large footprint of the SMMR and SSM/I sensors. Consequently the combined land mask has been enlarged by one pixel, except for studies of the impact of river discharge on fast ice due to the nearshore location of these study areas. These procedures allow trend and anomalies to be examined with greater confidence. The SMMR- and SSM/I-derived daily total sea-ice concentrations, defined as the mean sea-ice coverage of a grid cell, have been used to calculate total sea-ice coverage and sea-ice, fast-ice as well as open-water areas in selected regions of the Laptev Sea. According to hydrological and sea-ice regimes, the Laptev Sea is divided in a western and eastern part. The boundary between both regions runs along 1268E. Following Parkinson et al. (1999), ice coverage [%] is determined from the ratio between the number of pixels with an ice concentration z 15% and the total number of pixels in the region of interest (including open water). Ice extent [km2] is the cumulative sum of the area of all grid cells in the region of interest, having sea-ice concentrations of at least 15%. The sea-ice and fast-ice areas [km2] represent the area of the ocean actually covered by sea ice. It is the sum of the icecovered area (ice concentration times grid-point area) of all grid points within the subset that have at least an ice concentration of 15%. 2.2. Deriving polynya characteristics Time series of polynya open water-area on a daily basis are derived by subtracting the sea-ice area (see above) within a defined polynya mask from the total area of this mask. The polynya masks (Fig. 1) are defined empirically based on the mean location and extent of the polynyas. The mean location is derived from long-term monthly mean sea-ice concentration maps and distributions of temporal standard deviations of the monthly means from the long-term monthly means (data not shown). A threshold of 1.5% of open-water area in the requested polynya query box is used to decide whether a polynya (or lead) is present. This information is used to calculate
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the timing, the duration and the time-dependent (open water) area of the openings (Fig. 2a). Advanced Very High Resolution Radiometer (AVHRR) data are used to: (1) aid in the derivation of the threshold; (2) validate the derived open-water areas; (3) demonstrate the suitability for the detection of small-scale features of the polynyas and leads from the relatively coarse-resolution sea-ice concentration base-data. Global and Local Area Coverage (GAC, LAC) AVHRR-data at visible- and infrared-wavelengths have been obtained from the NOAA Satellite Active Archive (SAA) and processed with TeraScan software from SeaSpace Corporation. Two comparisons are made for selected dates: (1) sea-ice concentration maps vs. AVHRR images and (2) derived open-water area in polynyas vs. digitized open-water areas from AVHRR images. The 1.5% open-water threshold is derived empirically by comparing georeferenced AVHRR images with SMMR and SSM/I derived open-water areas. During winter polynya areas are underestimated (Eppler et al., 1992; Comiso and Gordon, 1998). This is due to sensor characteristics of passive-microwave radiometers and deficiencies of the NASA-Team algorithm in discriminating unambiguously between open water and newly formed ice which are typical for polynyas (Fig. 2b). We focus entirely on the area of open water within a polynya because of its significance for the turbulent exchange of sensible and latent heat between the ocean and the atmosphere and for its impact on pronounced meteorological features (e.g. arctic stratus, fog, reinforcement of cyclones). Even thin ice (5 cm to 10 cm) reduces heat fluxes between the ocean and atmosphere by an order of magnitude. During spring and early summer, the open-water areas from passive-microwave data are in many cases slightly overestimated due to the enlarged size and increased frequency of leads in the drift ice that is also covered by the defined polynya box. For example, the sea-ice conditions on 31 May 1995 as displayed in the SSM/I-derived ice concentration chart and the visible channel satellite image from NOAA-AVHRR mark the West New Siberian Polynya (Fig. 2c). The open water area in the AVHRR image yields 19 103 km2, while the area indicated as open water in the SSM/I chart is 20.7 103 km2. Such comparisons have been made for numerous polynya events in order to assess the accuracy of our calculations.
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Fig. 2. (a) Example of the application of the polynya detection method. Time series of daily open-water area [km2] within the Western New Siberian polynya query box from November 2001 to June 2002. The horizontal line indicates the 1.5% threshold [km2] for determining polynya characteristics. The sea-ice conditions in the Laptev Sea on (b) 2 January 1995 (left panel) and (c) 31 May 1995 (right panel) as displayed in the visible channel satellite image from NOAA-12 and 14 AVHRR (LAC) and the SSM/I derived ice concentration [%] chart. The polygons mark the area used to calculate the size of the WNS-Polynya. The size of the AVHRR image is approximately 1400 km 845 km.
Small-scale features like leads with a width of less than approximately 5 km are not represented in the coarse-resolution SMMR and SSM/I sea-ice concentration data. The high-resolution 85 GHz channel (12.5 km 12.5 km) of the SSM/I radiometer has not been used to study polynya events as proposed by Markus and Burns (1995) and Markus et al. (1998). Firstly, the 85 GHz channel is highly sensitive to atmospheric effects and secondly the SSM/I sensor is only covers the period from 1987 to the present. The open-water areas determined from the passivemicrowave radiometer based sea-ice concentrations
are generally in good agreement with the areas calculated from reference AVHRR data. Despite of the limited accuracy of the sea-ice concentration estimates the threshold yields reasonable results. Thus the passive microwave data sources are suitable to make long-term studies and will be used in subsequent analyses. 2.3. Thermodynamic sea-ice model A one-dimensional thermodynamic fast-ice model (Bareiss et al., 1999; Bareiss, 2003) has been utilized
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to derive ice melt rates from the energy balance at the upper and lower ice surfaces. The model is based in part on the formulation of Maykut and Perovich (1987) and Dean et al. (1994) and takes into account the presence of overlaying snow as well as heat conduction through snow and ice layers. A surfaceand thickness-dependent albedo parameterization of snow and sea ice based on data of Flato and Brown (1996) and Perovich et al. (1998) is used. Extensive sensitivity studies of the effects of prescribed conditions, forcing data sets and parameterizations are presented in more detail in Bareiss (2003). Two principal cases of fast-ice decay have been considered in more detail: the decay of flooded nearshore fast ice in the mouth of the rivers, and the decay of snow-covered or bare fast ice adjacent to the flooded areas. The energy balance equations at the snow/ice/ water–atmosphere interface can be expressed for fastice that may be covered with snow, river water or bare ice as: 1 afi;s;w RS;A þ RL;A þ RL;z þ QH þ QE þ QR þ QC ( 0 : T0 VTf ¼ ð1Þ qfi;s Lf ðBh=Bt Þ : T0 NTf and for fast ice at the ice–ocean interface as: QR þ QO þ QC ¼ qfi;s Lf ðBh=Bt Þ : QR þ QO þ QC N0;
ð2Þ
where R S,A is the incoming short-wave radiation, a fi,s,w the albedo of fast-ice, snow and flooded fastice. R L,A is the incoming, R L,z the emitted long-wave radiation, Q H and Q E are the sensible and latent heat fluxes, respectively. Q R is the heat flux provided by river water, Q C is the conductive heat flux through the ice to the surface and Q O represents the ocean heat flux. The density of ice and snow is expressed by q fi, and q s, L f is the latent heat of fusion of fast ice, h the ice thickness and t the time. For more details on the model, physical values, and parameterizations of the radiation and turbulent heat flux densities the reader is referred to Bareiss (2003). Forcing data of the sea-ice model include meteorological parameters obtained from international reanalyses projects (ECMWF, NCEP/NCAR) and synoptic weather stations, as well as discharge data from
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various Siberian rivers gauges provided by the Arctic River Data Base. Due to the availability of river discharge data this study was performed over the period 1979 to 1994.
3. Variability and trends in sea-ice area, openwater area within polynyas and fast-ice area 3.1. General sea-ice regime The total area of the Laptev Sea, according to the grid of the satellite passive-microwave sea-ice data set, comprises 661.25 103 km2 (621.25 103 km2 with enlarged land mask). The ice regime is characterized by three specific sea-ice features: fast ice, flaw polynyas, and drift ice (Fig. 2b,c). Most parts of the Laptev Sea are covered with sea ice from October to June. During summer only the southern and central parts of the shelf become ice-free. In winter when the Vilkitsky, Shokalskogo, Dmitry Laptev, Sannikova and Eterikan straits connecting the Laptev Sea with the Kara and East Siberian Seas, are covered with fast ice, ice export into the Arctic Ocean at the northern boundary dominates. During summer the net ice exchange is balanced; it is characterized by short periods of predominant import and export. Between fast-ice break-up and ice disappearance the ice exchange with the adjacent marginal seas commences but is rather insignificant with some exceptions (Kotchetov et al., 1994). In all seasons but principally in summer, the exchange of sea ice between the Laptev Sea and the Arctic Ocean can experience large interannual fluctuations. Two quasi-stationary major ice fields, clearly apparent in visible and microwave satellite data, occasionally remaining during the summer, can be distinguished: the Taimyr ice massif in the western Laptev Sea east of the Taimyr Peninsula and Severnaya Zemlya, and the Yana ice massif in the southeastern Laptev Sea (Fig. 3). These large assemblages of close ice cover areas at the beginning of August are as large as 150 103 km2 (Taimyr) and 70 103 km2 (Yana), respectively. The Taimyr ice massif originates from Arctic pack ice, whereas the Yana ice massif develops in shallow waters from fast ice. In most years they disappear in the middle of summer. In some years the ice massifs can persist until
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the end of summer seriously hampering navigation (Kotchetov et al., 1994). From systematic observations carried out since the 1930s and summarized in Romanov (1996) the monthly mean thickness of drift ice throughout the Laptev Sea at the end of winter (April) is 1.57 m, its standard deviation S.D. = 0.243 m. Drill hole and electromagnetic induction measurements performed in the summers of record minimum (1995) and record maximum (1996) ice extent revealed a mean modal first-year ice thicknesses of 1.25 m and 1.85 m, respectively (Haas and Eicken, 2001). Fast ice grows in average up to 1.95 m (S.D. = 0.167 m). Mean ice thickness in fast ice according to the data of Russian polar stations account for 1.99 m in the western, 2.11 m in the central and 2.04 m in the eastern portion of
Fig. 3. Sea-ice concentration [%] chart of the Laptev Sea on 11 August 1984 as derived from passive-microwave data (SMMR) showing the Yana ice massif in the southeastern portion of the shelf sea. Ice concentrations are smoothed using a 3 3 Gaussian lowpass filter and values V 5% are defined as water (white). Also shown is the land mask of the sea-ice data set.
the Laptev Sea (Kotchetov et al., 1994). Freshwater fast ice in the vicinity of river mouths reaches a thickness of 2.20 m on average (Dmitrenko, 2000, pers. comm.), and up to 3.0 m in the branches of the Lena and Yana deltas (Nalimov, 1995). More than 50% of the shallow eastern Laptev Sea and up to 25% of the western Laptev Sea are covered with fast ice. Each winter fast ice grows along the coastlines of Severnaya Zemlya, Taimyr Peninsula, the southwestern and eastern Laptev Sea (on average 250 103 km2). Between the Lena Delta and the New Siberian Islands a smooth and freely floating fast-ice cover, consisting of large and thick first-year ice floes, extends as far as 500 km from the Siberian mainland. The fast-ice cover is locally controlled by small islands and shoals (Reimnitz et al., 1994). In the southeastern Laptev Sea it covers an area of about 140 103 km2 (Bareiss, 2003). Along the eastern coast of the Taimyr Peninsula and Severnaya Zemlya the width of the fast-ice belt does not exceed 50 km. The fast-ice extent roughly coincides with the position of the 20 m to 25 m isobaths. In the western Laptev Sea fast ice can sometimes persist during the summer and become multi-year fast ice (Reimnitz et al., 1995). Extensive regions east of the Lena Delta, in the Gulf of Buorkhaya, and near river mouths consist of freshwater ice. Tidal cracks in the fast-ice cover form throughout the winter. In regions more shallow than 2 m the fast ice becomes bottom fast ice (Reimnitz et al., 1995). The position of the fast-ice edge derived from NOAA-AVHRR data in mid-May is presented in Fig. 4. In most parts of the Laptev Sea the fast-ice edge is more or less stationary. According to Dmitrenko et al. (1999) the small-scale variability in the position of the fast-ice edge is caused by the interannual variability of river discharge from the Khatanga, Anabar, Olenek, Lena and Yana rivers. Processes such as grounding play a minor role for the lateral extent of fast ice (Eicken et al., this issue). Fast ice on the Laptev Sea shelf plays a crucial role in the freshwater cycle of the ocean due to storing of freshwater from discharge in winter and releasing it in summer. A further prominent feature of the ice regime in the Laptev Sea are linear-shaped flaw leads and sphericalshaped flaw polynyas (Fig. 5, upper panel), that may extend from some 100 km to nearly 2000 km and reach maximal widths of up to 250 km. They are
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During wintertime the flaw leads consist of open water or young ice of various thicknesses up to 0.70 m. Due to constant offshore-winds new ice is continuously formed. In addition, openings in the pack ice that form during winter are sites of brine formation, affecting the local convection and water mass stratification (Dmitrenko et al., 2001). The wind-driven polynyas result in intense heat loss from the ocean to
Fig. 4. Extent of the fast-ice cover in the Laptev Sea from 1979 to 1994. The black lines represent the position of the fast-ice edge in the Laptev Sea as derived from NOAA-AVHRR images (GAC, LAC) in mid-May of each year.
zones of ice-free water or young ice that are formed between fast ice and seaward drift ice due to regional atmospheric pressure conditions and associated nearsurface wind fields. Polynya openings are caused by offshore winds. In the context of maintenance, the flaw polynyas can be classified as latent heat polynyas driven by the latent heat of fusion which is supplied to the surrounding water masses due to new-ice formation (Smith et al., 1990). The main flaw polynyas, according to Zakharov (1966), occurring in the Laptev Sea are: East Severnaya Zemlya Polynya (ESZ), Northeastern Taimyr Polynya (NET), Taimyr Polynya (T), Anabar-Lena Polynya (AL), West New Siberian Polynya (WNS). Most polynyas in the central Laptev Sea are recurring polynyas (frequency of occurrence N 50%). The flaw polynyas in the northwestern Laptev Sea are temporary ones, with a frequency of occurrence b 50% (ESZ, ET). Due to the prevailing wind direction openings in the eastern and northwestern Laptev Sea occur directly opposed (Kotchetov et al., 1994).
Fig. 5. NOAA AVHRR images (visible channel) of the Laptev Sea polynyas on 3 June 1995 (upper panel) and of the Lena Delta on 19 June 1995 (lower panel) showing the coastal polynya and the flooded nearshore fast ice off the eastern delta channels and the southern part of the Western New Siberian Polynya extending close to the northern delta. The size of the images are approximately 1200 km 1000 km and 300 km 300 km, respectively.
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the atmosphere, controlling the formation of fog banks and low-level clouds (Arctic stratus). Zakharov (1966) estimates from energy balance studies that in all leads and polynyas of the Laptev Sea 910 km3 of new ice is formed from October to April. Dethleff (1995) put into perspective that, compared to the entire mean volume of sea ice formed in the northern hemisphere (20 103 km3), the Laptev Sea flaw polynyas do not contribute significantly (only about 1.3%) to the total ice volume formed during one winter season. However, the polynyas produce relatively large amounts of new ice in respect to their limited areal extent. With the steady increase of solar radiation during spring (May) flaw polynyas turn to areas of heat gain. Mean polynya sizes in the central Laptev Sea (AL and WNS combined) extend to 20 103 km 2 in May, to 50 103 km2 in June, and to 90 103 km2 in July. Maximum polynya areas range from 45 103 km2 in May to 130 103 km2 in July, respectively (Bareiss, 2003). Coastal regions of the Laptev Sea are highly sensitive to river water as discharge interacts directly with the nearshore and offshore fast-ice cover (Nalimov, 1995; Bareiss et al., 1999; Bareiss, 2003). Thus, these coastal polynyas (so-called by Russian scientists) in the vicinity of river mouths can be referred to as sensible heat polynyas, because they are partly formed and maintained by the heat gained from river water (Fig. 5, lower panel). Once the fast ice ahead of the river mouths is flooded by river discharge and sediments the decreasing sea-ice albedo leads to the absorption of short-wave radiation. Atmospheric heat gain dominates the melting process in addition to the influence of the heat supplied by the relatively warm and fresh riverine water.
cover that typically varies in ice area from 190 103 km2 in summer to 610 103 km2 in winter. In individual years ice retreat during August and September is more distinctive in the eastern Laptev Sea than in the western portion (data not shown). On average, minimum and maximum values of all fast-ice areas, including the ice along the shores of Severnaya Zemlya and the Taimyr Peninsula, range from 16 103 km2 in summer to 165 103 km2 in winter. In the southwestern and southeastern Laptev Sea fast ice completely vanishes during summer with the exception of seasons with ice massif events. Passive microwave observations indicate, that the onset of sea-ice melt in the open Laptev Sea proceeds from the South (beginning of June) to the North (end of June). In the areas of developed flaw polynyas and in the vicinity of river mouths and deltas intensive melting also starts in early June. Table 1 summarizes mean representative values of parameters which characterize the temporal sea-ice development in defined regions of the Laptev Sea as recommended by Eicken et al. (1997) and Bareiss et al. (1999). The
3.2. Seasonal variability For regional sectors in the Laptev Sea the characteristic pattern of the increase in sea-ice area during fall freeze-up to its maximum in winter and the decrease to its annual minimum in summer is presented in Fig. 6. As discussed earlier, for all analyses of the temporal sea-ice variability an enlarged land mask is used. The seasonal variability of observed total sea-ice concentrations in the entire Laptev Sea and its western and eastern parts is well pronounced. The 24-year mean seasonality of sea-ice in the Laptev Sea shows an ice
Fig. 6. Time series of SMMR- and SMM/I-derived daily mean seaice area [103 km2] in the entire, western, and eastern Laptev Sea (upper panel) and daily mean fast-ice area of the entire and southeastern Laptev Sea (lower panel) averaged for 1979 to 2002. The gray box marks the period of the early-melt signal as apparent in passive-microwave data.
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early-melt signal in the passive microwave data is determined as the date when the ice-area values drop below a coverage of 85% for the first time during spring. The date of the actual ice retreat is defined by the first maximum of the sea-ice coverage after the local minimum during the period of surface melt (see below). Fall freeze-up is defined by the local minimum in sea-ice area before a steep increase to values z 90%. Fig. 6 illustrates the melt and freeze-up terms. Mean retreat in ice-area commences in the beginning of July (day 187). The duration of ice retreat to its summer minimum lasts for about 9 weeks. In contrast to the entire Laptev Sea fast ice in the southeastern region vanishes completely after 7 weeks (day 232). The average summer minimum of sea-ice area in the Laptev Sea is attained between mid-August and mid-September on day 250, in its eastern part on day 252, and in the western region on day 244. The mean sea-ice area that remains during summer in the 24-year period accounts for 165 103 km2. The rate of sea-ice decline in the eastern portion of the Laptev Sea occurs in general more intensive than in the western sea region. On average, 84% of the eastern and 67% of the western Laptev Sea become ice-free during summer. According to Eicken et al. (1997) and Bareiss et al. (1999), this difference reflects the impact of Lena and Yana river water in the eastern Laptev Sea and the importance of sea-ice advection in the western part. Mean values of ice retreat during the 1980s and the early 1990s reveal substantial differences. The average minimum sea-ice cover during 1984–1988 is on day 256, whereas the average minimum during the period from 1989 to 1997 occurs on day 249.
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In the southern regions that are covered with fast ice the decrease of ice area during the ablation period is not uniformly continuous as in the larger Laptev Sea regions (Fig. 6, lower panel). On average, the apparent reduction in total sea-ice concentration or sea-ice area, respectively, starts in the beginning of June, with a first minimum in ice-area reached about 7 days later (Table 1). This first decline in passivemicrowave data towards a local minimum followed by a subsequent increase after 10 days is deemed an important indicator of surface melt. As discussed in more detail in Bareiss et al. (1999) this passivemicrowave derived early-melt signal can be interpreted as an artifact largely due to changes in surface emissivity occurring in the snowpack and the upper ice layers as a result of warming and in-situ meltwater production. With the forming of a superimposed ice layer, emissivity readjusts towards its pre-melt status, with a corresponding increase in derived sea-ice concentrations. The belt of fast ice starts to break up in early to mid-July. The southeastern Laptev Sea becomes completely ice-free by mid-August. The spatial distribution of the long-term average of mean daily sea-ice cover in the Laptev Sea during summer minima from 1979 through 2002 (7 September) is shown in Fig. 7. In addition to the 5%-isoline of total sea-ice concentration the more common 15% contour line (dashed) is presented that better marks the position of the ice edge. A large part of the shallow central and eastern Laptev Sea becomes free of ice each summer. The mean position of the ice edge is located near the New Siberian Islands but still south of the shelf break. The remaining mean ice cover in the western Laptev Sea extends as far south as 788N,
Table 1 Characteristics of mean parameters of sea-ice development in the entire, western, eastern, and southeastern Laptev Sea derived from passivemicrowave satellite data (SMMR, SSM/I) Early-melt signal Actual start of ice retreat Date of sea-ice minimum Ice-retreat duration Area of sea-ice minimum [103 km2] Date of freeze-up Freeze-up duration
Entire Laptev Sea
Western Laptev Sea
Eastern Laptev Sea
Southeastern Laptev Sea
163 187 250 63 165 268 24
166 187 244 58 110 267 24
161 186 252 66 46 269 23
161 188 232 44 1.8 275 20
(8.2) (8.5) (10.2) (14.1) (85) (8.5) (7.1)
(7.4) (8.7) (17.8) (21.2) (54) (8.7) (8.1)
(8.0) (9.4) (11.3) (14.4) (37) (8.0) (7.7)
(6.9) (9.4) (14.1) (10.7) (6.6) (7.0) (7.9)
Long-term means (day of year) and standard deviations (days in parenthesis) refer to the period from 1979 to 2002. Note that columns of western and eastern Laptev Sea do not always add up to the means of the entire Laptev Sea, since they have been calculated separately for each region.
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although in some years the ice edge retreats north of the Taimyr Peninsula. There is no distinct freeze-up pattern in the Laptev Sea (Kotchetov et al., 1994; Eicken et al., 1997). In most years, predominantly in the 1980s and the late 1990s, new-ice formation starts in early September in the northern Laptev Sea, proceeding southward from the summer drift-ice edge. In the coastal areas the onset of stable fast-ice formation starts at the end of September. In the early and mid-1990s a change to another freeze-up pattern is evident. Ice formation commences in the northern and the southern coastal shallow waters of the Laptev Sea at the same time. The average starting date of fall freeze-up in the total Laptev Sea takes place in mid-September (Table 1). Within 2 to 4 weeks vast areas of the Laptev Sea are covered with young ice. In the southeastern Laptev
Fig. 7. Chart of daily mean sea-ice concentrations [%] of the Laptev Sea at the beginning of September in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I). The dashed line marks the position of the ice edge typically identified as the 15% contour line. Also shown is the land mask of the sea-ice data set.
Sea mean ice formation starts in late September to early October (day 275). Due to the southward progression of the ice edge no difference in the dates of freeze-up are apparent between the western and eastern Laptev Sea. The rate of ice formation is accelerated by strong winds inducing intensive vertical mixing and cooling of the water column, which is even more intensive on the shallow shelf (Kotchetov et al., 1994). As maximum sea-ice coverage is reached already in fall, ice thickness continues to increase until May. During most weeks in fall, winter and spring the Laptev Sea shows a sea-ice coverage between 90% and 100%. Occasional reductions in ice coverage during winter and spring are caused by the formation and development of flaw leads and polynyas. In general, the development of polynyas in the Laptev Sea is fixed in location but differs in time. Polynya activity (frequency, duration, extent) is largely controlled by parameters of the wind regime such as wind speed and direction as well as persistence. Day-to-day changes of important polynya features during the winter season reflect the magnitude, stability and timing in offshore wind speeds. In the Laptev Sea synoptically induced winds are prevalent. In addition to the dynamic forcings of polynya events the absorption of short-wave radiation is of fundamental importance for the areal extent of polynyas in late spring (Zakharov, 1966; Dethleff, 1995; Bareiss et al., 1999). Mean seasonal (November to June) statistics obtained for each of the representative flaw polynyas in the Laptev Sea are given in Table 2. The mean frequency of polynya events in all investigated regions accounts for 12.4. On average, polynyas last for 16 days. The polynyas in the central and eastern Laptev Sea (Al, WNS) are more stable and two to four orders in magnitude larger in extent than the polynyas in the western and northwestern region. The WNS Polynya is the largest polynya in the Laptev Sea covering on average an area of 4 103 km2 in winter. During extremely strong polynya events the WNS Polynya may occupy up to 12% of the entire and even 25% of the eastern Laptev Sea. The predominance of polynyas in the central and eastern part is also confirmed by the mean cumulative area of open-water area. Most polynyas that develop at the end of April or May exist until the adjacent fast-ice cover has retreated.
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Table 2 Mean characteristics of polynya events (frequency and duration, mean and cumulative open-water area) in the winter and spring seasons (November to June) from 1979/1980 to 2001/2002 Laptev Sea polynyas Mean Mean Mean Mean
frequency [days] duration [days] area [103 km2] cumulative area [103 km2]
WNS
AL
T
NET
ESZ
13 (23, 8) 14 (128, 2) 4 (73, 0) 1713
11 (16, 3) 22 (134, 2) 3 (49, 0) 1152
13 (19, 5) 13 (110, 2) 0.8 (17, 0) 211
12 (18, 7) 16 (147, 2) 2 (30, 0) 616
13 (21, 7) 16 (98, 2) 2 (17, 0) 506
Values in parentheses indicate the absolute maximum and minimum.
annual variability. The variability of the 24 seasonal cycles is visualized in Hovmoeller diagrams (Fig. 8). Interannually, the summer minima ice cover exhibit greater variability from year to year than the winter maxima. Noticeable are the years 1979, 1984, 1992 and 1996, when ice retreat started late and vast parts of the Laptev Sea remained ice-covered. In 1990, 1991, 1995 and 1999 nearly the entire Laptev Sea was ice-free. The record minimum and maximum in summer sea-ice coverage occurred in the two successive years of 1995 and 1996. Sea-ice data in the Laptev Sea shows a large amplitude in minimum summer sea-ice cover with an oscillatory behavior. During the 24 years of satellite record periods with increased and decreased summer ice cover are evident. Before conducting the time-series analysis of monthly mean sea-ice areas in each study region the seasonal cycle was removed by subtracting the longterm average of each month. Trends for yearly and monthly averaged ice areas are calculated by using a time-series regression model (ordinary linear least squares) through the data for the period, 1979 to 2002. For each trend the non-parametric Mann–Kendall test
Off the mouths of rivers discharging into the Laptev Sea the presumable dynamic and thermal impact of river water on fast-ice retreat is clearly evident in satellite images by the forming of coastal polynyas (Fig. 5). NOAA-AVHRR data displaying clear sky or low cloud fraction were the primary source to gain information on the dates and areas of river flooding or coastal polynya formation. On average, overflows of the nearshore fast ice start in the beginning of June, and its standard deviation is 4 to 6 days. Dates of flooding of nearshore fast ice by river water are presented in Table 3. The overflows on the ice show low spatial variability at the beginning of the ablation period. Depending on the volume of river discharge, the flooding extends 10 km to 25 km from the coast. Roughly 4 weeks after the flooding coastal polynyas develop. Break-up activity, beginning in July, consists of the seaward extension of the coastal polynya until the remaining fast ice is completely removed. 3.3. Interannual variability and trends The areal extent of sea-ice in the Laptev Sea and in each of its individual regions shows a large inter-
Table 3 Mean start of nearshore fast-ice flooding in the vicinity of river mouths in the Laptev Sea as derived from NOAA AVHRR images Start of fast-ice flooding by river water Anabar Olenek Lena (Olenekskaya) Lena (Tumatskaya) Lena (Trofimovskaya) Lena (Bykovskaya) Yana
Mean (a)
S.D. (a)
Mean (b)
S.D. (b)
Abs. min. (a)
Abs. max. (a)
166 157 154 160 152 159 153
6.6 6.0 4.8 4.1 5.1 4.9 6.2
165 156 154 160 153 159 152
6.9 6.4 4.6 3.9 5.0 4.5 5.6
153 146 148 153 143 150 139
176 171 167 170 166 170 166
(15.6) (06.6) (03.6) (09.6) (01.6) (08.6) (02.6)
(14.6) (05.6) (03.6) (09.6) (02.6) (08.6) (01.6)
(1993) (1990) (1990) (1990) (1990) (1990) (1990)
(1986) (1987) (1987) (1987) (1987) (1987) (1987)
Long-term means, their standard deviations (S.D.) and extreme values refer to the period 1979 through 1994 (a) and 1979 through 1999 (b), respectively.
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Fig. 8. Hovmoeller diagrams (time/time) of daily total sea-ice concentrations [%] in the entire (upper left), western (upper right), eastern (lower left) and southeastern (lower right) Laptev Sea from May through October in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I).
was performed to detect monotonic trends in the timeseries data at the 95% confidence level for the trend slope in order to assess the statistical significance of the trend. Time series of sea-ice extent and area show downward trends in the Laptev Sea and its individual regions over the 24-year period. The overall trend for
the entire Laptev Sea indicate a decrease in ice extent and area by 970 km2 year 1 and 1100 km2 year 1, respectively. For all regional sectors time series of anomalies in monthly sea-ice area, including the linear least squares fit and the 95% confidence intervals are plotted in Fig. 9. Qualitatively, our results correspond well with earlier findings of negative trends in the
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Siberian Arctic (Maslanik et al., 1996; Parkinson et al., 1999; Go¨rgen et al., 2001). The magnitude of the negative trends are more moderate than the slopes obtained by Maslanik et al. (1996), who used a larger study area and a shorter time series for the period 1979 to 1995, not including the extreme summer maximum year of 1996, and hence suggesting an accelerated decline. Time series of the date of the minimum sea-ice cover in the Laptev Sea shows a
Fig. 9. Time series of monthly anomalies of the sea-ice and fast-ice (lower panel) area [103 km2] in the entire, western, eastern and southeastern Laptev Sea in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I). Also shown is the trend line of linear least squares fit through the data and the 95% confidence interval (dotted line).
41
large interannual variability and a weak negative trend towards an earlier summer minimum (data not shown). As sea-ice extent includes open-water as well, it is ambiguous to explain whether the decline in ice extent is caused by either open-water or sea-ice area. Therefore, the trend analysis is conducted with the latter. The slopes of the linear least square trend lines and the 95% confidence intervals are summarized in Table 4. The decreases in sea-ice extent and area for the entire Laptev Sea on a yearly average basis reveal 1.5% decade 1 and 1.7% decade 1, respectively. The overall downward yearly trends are strongly driven by summer and early fall anomalies. By analyzing monthly trends, we can show that the seaice area decreased in August by 5.5% decade 1 or more than 4.5% decade 1 in September and October (Table 4). Regionally, the western Laptev Sea exhibits largest negative trends at 6.9% decade 1 in August and the eastern Laptev Sea at 5.0% decade 1 in October. In the southeastern Laptev Sea the decrease in fast-ice area are more pronounced in July ( 6.4% decade 1) and October ( 4.6% decade 1). It has to be noted that due to the large variance of summer sea-ice data all trends assessed except the trend in May in the southeastern Laptev Sea are not significant at 95% confidence level. Considering trend analyses of yearly and monthly sea-ice data in the entire Laptev Sea (data not shown), it is evident that the decrease of ice-extent is weaker over the 24-year period compared to the decrease of ice-area. The diverting linear trends indicate an increase of open-water area on a yearly basis due to polynya activity and being strongest during early summer (May to July). In August and September however, no trends in open water area are found. Strong increasing trends in open-water area have also been detected in all sub-regions in October. The detected positive trends of open-water area indicate an increase in the length of the summer open-water season. To evaluate the interannual variability of polynya activity in the Laptev Sea, mean open-water areas of single polynya events in each polynya sub-region during winter (November to June) have been analyzed. These data are presented in Fig. 10 (left panel) for the WNS and AL polynyas as they are the largest
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Table 4 Slopes of the trend lines (SLT) of linear least squares fit through sea-ice area data (yearly and single months) and the 95% confidence interval [103 km2 year 1] in the entire, western, eastern and southeastern Laptev Sea in the period 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I) Entire Laptev Sea Year May Jun Jul Aug Sep Oct
Western Laptev Sea
Eastern Laptev Sea
Southeastern Laptev Sea
SLT
S
CD
SLT
S
CD
SLT
S
CD
SLT
S
CD
1.1 F1.4 0.7 F 0.1 1.6 F 2.3 2.3 F 3.3 3.6 F 4.1 3.1 F 4.8 2.9 F 3.9
91 80 79 72 82 77 77
1.7 1.1 2.4 3.6 5.5 4.7 4.5
0.6 F 0.8 0.5 F 0.6 0.9 F 1.4 1.2 F 1.8 2.4 F 2.5 1.8 F 2.9 1.4 F 1.8
82 88 79 75 74 63 77
1.8 1.3 2.6 3.4 6.9 5.1 4.1
0.5 F 0.8 0.3 F 0.5 0.6 F 1.2 1.1 F1.8 1.2 F 2.2 1.3 F 2.3 1.5 F 2.1
77 74 68 77 65 84 72
1.6 0.9 2.2 3.8 4.0 4.2 5.0
0.14 F 0.22 0.07 F 0.10 0.06 F 0.34 0.68 F 0.61 0.39 F 0.65 0.02 F 0.54 0.49 F 0.77
85 97 60 92 0 86 70
1.3 0.7 0.5 6.4 3.7 0.2 4.6
Also presented is the statistical significance (S) of the trend and the change of sea-ice area (CD) [% decade
openings with the strongest local impact in the Laptev Sea during winter. Although leads and polynyas occur in each time of the winter, open-water areas peak in the end of winter or spring. Large polynya events of the prominent openings in the central and eastern Laptev Sea are present in most late winter/spring seasons. The open water areas are remarkably high in the 1990s. However, in mid-May of 1982, 1984, 1987, 1992 and 1996 large polynya openings were
1
].
absent. In the western and northwestern Laptev Sea (T, NET, ESZ) the activity of polynyas was anomalously low in May during the period from 1979 to 1988. Instead, most polynyas in this region start to form in June or even later. Exceptionally in 1984, when most of the Laptev Sea was still covered with ice by July, the NET and ESZ polynyas were existent. Mean open-water areas of the largest WNS and AL Polynya events in late winter or spring (January to
Fig. 10. Time series of open-water area within the ice pack [103 km2] as an indicator of polynya activity of the Western New Siberian (WNS) and Anabar Lena (AL) polynyas from 1979 to 2002. The interannual variability of all polynya events during winter (November to June) are shown in the left panel. The number of bars indicates the variable frequency of polynya events. The right panel represents mean (gray bars) and maximum (white bars) open-water areas of the largest polynya event during late winter and spring (January to June) per year. The black stars mark the date of polynya openings [day of year].
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June) range from 4 103 km2 to 37 103 km2 and from 12 103 km2 to 23 103 km2 (Fig. 10, right panel). As the WNS and AL Polynyas are often connected to each other, they form a large ice-free area during spring. The years in the order of maximum polynya size 1995, 1993, and 2000 represent the years with the largest positive anomalies of mean open-water area in the WNS and AL Polynya boxes. The average of maximum open-water areas of the largest polynya events during winter and spring is calculated to be 48.5 103 km2 (WNS) and 30 103 km2 (AL). Five years, 2000, 1988, 1993, 1995, and 1997, exhibit open-water areas in the central and eastern Laptev Sea greater than 100 103 km2, covering an area between 15% and 20% of the entire Laptev Sea. From 1979 to 2002 all Laptev Sea polynyas show an increase in the frequency of polynya events during the entire winter (November to June), being strongest in the ESZ and AL Polynyas. In contrast, the WNS Polynya shows a decrease in the number of single polynya events during this time span. All polynyas exhibit a decrease in the duration of polynya events. On average, the duration of polynya events in the central and eastern Laptev Sea was 21 days in the mid-1980s and only 13 days in the early 1990s, whereas in the western Laptev Sea no significant changes occurred. Although polynya events appear to be shortened, all polynyas with the exception of the AL Polynya reveal an increase in mean open-water area during the winter months (November to June) over the 24-year period.
4. Discussion The most dominant sea-ice feature in the Laptev Sea is the substantial interannual variability and oscillatory behavior of the summer ice cover, as illustrated in Figs. 7 and 8. There is a variety of possible conclusions from where these observed yearto-year changes and trends in summer sea-ice conditions likely result. Changes in sea-ice decay and summer ice coverage may be associated with changes in large-scale atmospheric circulation regimes, synoptic activity, associated warm air advection and the impact of continental freshwater input. The aim of this section is to provide an overview of the current state of knowledge about dynamic and thermodynamic forc-
43
ings of the atmosphere, the ocean and river water, which are likely to affect sea-ice variability in the Laptev Sea. 4.1. Linkages to atmospheric forcings The Arctic climate exhibits a marked increase of surface air temperature during the last three decades from 1970 to the present. Multidecadal time series of model results and observations show a decrease in Arctic sea-level pressure (SLP) and an increase in cyclonic vorticity of winds in the late 1980s and early 1990s (Walsh et al., 1996; Rigor et al., 2002). Concurrent with the changes in SLP fields is an increase of the frequency of cyclones penetrating into the Eurasian Arctic as documented by Serreze et al. (1993). The following discussions treat large- and synoptic-scale interactions between the atmosphere and sea ice separately. At longer time scales (weeks to months) sea-ice variability in the Arctic and its marginal seas is mainly controlled by changes in the large-scale atmospheric circulation (Proshutinsky and Johnson, 1997; Mysak and Venegas, 1998; Polyakov et al., 1999; Deser et al., 2000). There are a number of terms, such as the Arctic Oscillation (Thompson and Wallace, 1998), Arctic Ocean Oscillation (Proshutinsky and Johnson, 1997) and Low Frequency Oscillation (Polyakov and Johnson, 2000), which describe the decadal and multidecadal variability of atmospheric and oceanic circulation patterns in the Northern Hemisphere and the Arctic. These authors suggest that the Arctic atmosphere alternates between two regimes of a weakened or strengthened anticyclonic circulation (Beaufort Gyre) and an intensified or suppressed cyclonic circulation in the eastern Arctic. Much of these changes can be linked to the Arctic Oscillation (AO). The changes between the atmospheric circulation regimes are in general associated with variations in mean sea-ice drift patterns and an eastward shift of the Transpolar Drift System. In this context, Proshutinsky and Johnson (1997) define the two arctic-wide observed wind-driven oceanic circulation patterns as the anticyclonic and cyclonic circulation regime (ACCR, CCR), each of which is persisting from 5 to 7 years. During these regimes the atmospheric circulation forces a convergent or divergent ice motion (ACCR/low AO-index or CCR/high
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AO-index) with thicker or thinner sea-ice (Walsh et al., 1996). At the same time decreases or increases in atmospheric vorticity cause higher or lower sea-ice coverage (Polyakov et al., 1999). According to Deser et al. (2000), summer sea-ice conditions in the Laptev Sea appear to be initiated by atmospheric circulation anomalies in the high Arctic in late spring. They suggest that the positive icealbedo feedback processes account for the long delay of atmospheric forcing and maximum ice response. This mechanism is generally believed to be a key factor in amplifying sea-ice variations. Rigor et al. (2002) note as well that the ice situation in summer and fall is preconditioned by the winter conditions. They suggest that during high-index periods of the Arctic Oscillation in winter atmospheric processes enhance the thinning of sea ice, the decrease of ice area and extent, and the delay of freezing in fall in the Laptev Sea. These changes may occur due to the formation of a cyclonic sea-ice motion pattern in the Arctic Basin promoting ice divergence in the Eurasian Arctic (i.e. an enhanced northward ice-drift). The interannual variability of sea-ice circulation in the Laptev Sea and ice exchange with the Arctic Ocean in the period 1979 to 1995 have been studied in detail by Alexandrov et al. (2000). In winter an extensive ice exchange, predominantly ice export, with the Arctic Ocean through the northern and northeastern boundaries exists. Alexandrov et al. (2000) calculate from remote sensing data and numerical modeling that in winter the total areal ice export into the Arctic Ocean accounts for roughly 500 103 km2 on average (1979–1995), ranging from about 250 103 km2 (1984/1985) to 750 103 km2 (1988/1989). Unlike the winter conditions, during summer the exchange of sea ice between the Laptev Sea and the Arctic Ocean is occasionally opposite in sign and can experience large interannual fluctuations. The average summer sea-ice import and export amounts to 40 103 km2 and 70 103 km2, respectively. In three quarters of investigated summers seaice import from the Arctic Ocean to the Laptev Sea was predominant except for those of 1982, 1985, 1987, 1991, and 1995 (Alexandrov et al., 2000). According to Proshutinsky and Johnson (1997), the Transpolar Drift System is located north of the Laptev Sea. Hence, during ACCR years the average winter ice export through the northern boundary was higher
and the summer ice import was lower than the ice exchange during CCR years. In contrast, during CCR years when the Transpolar Drift is shifted east towards the North American Arctic, most of the sea ice was exported from the Laptev Sea to the East Siberian Sea both in winter and in summer. By considering winter and summer ice-exchange rates, Alexandrov et al. (2000) found a large increase of total annual ice export for the period from 1990 to 1995 as compared to preceding years. The total ice export during the winters of 1989/1990, 1992/1993, 1994/1995 and the subsequent summers was above the average. The authors conclude in terms of preconditioning that the enhanced northward advection of ice associated with changes in the sea-ice circulation in the Laptev Sea during spring and summer explains, at least in part, negative sea-ice anomalies in subsequent summers. Besides these large-scale hemispheric processes described above, regional or synoptic-scale processes such as cyclone activity have profound effects on Arctic warming in winter and on sea-ice variability in spring. Sea-ice anomalies in relatively small areas and on time-scales of several days to some weeks seem to be strongly coupled with cyclones. Numerous authors (e.g. Serreze et al., 1993; Serreze, 1995; Proshutinsky and Johnson, 1997; Polyakov et al., 1999; Deser et al., 2000) make shifts in the atmospheric circulation regimes (ACCR/low AO-index or CCR/high AOindex) and associated variations in cyclone frequency responsible for the changes in sea-ice coverage along the Siberian coast in the 1990s. Serreze et al. (1993) and Serreze (1995) document links between the frequency of summer cyclones that are formed along the Arctic front over northern Eurasia and low ice concentrations in the Laptev Sea. Maslanik et al. (1996) show that ice-extent anomalies in the 1990s (e.g. 1990, 1993, 1995) are linked to increases in cyclone activity. Maslanik et al. (2000) and Rinke et al. (2003) used regional coupled atmosphere–ice–ocean models (ARCSyM, HIRHAMMOM) and observational data to explain the causes of the large sea-ice anomaly of 1990 in the Siberian Arctic. Based on detailed case studies, they suggest that the observed negative sea-ice anomalies occurred due to unusual patterns of ice advection and a coupling and a positive feedback between sea-ice dynamics and thermodynamics. As confirmed by Serreze et al. (2003), extreme negative sea-ice
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anomalies as in 2002 in the Laptev Sea seem to be linked with invasions of anomalous warm southerly air masses in spring, advecting sea ice northward from the Siberian coast while simultaneously enhancing ice melt. During the following summer persistent low sealevel pressure and above the normal near surface air temperatures over the Arctic Ocean further promote ice divergence, early break-up, rapid melt and subsequent reductions in surface albedo (Serreze et al., 2003). For example, as described by Haas and Eicken (2001) the advection of warm air from central Siberia can be considered to contribute significantly to the observed minimum in Laptev Sea ice extent during 1995. It has to be noted, that it is difficult to separate thermodynamic effects (ice melt) from dynamic components (ice drift) in explaining ice-extent anomalies (Maslanik et al., 1996; Bareiss et al., 1999). Though substantial progress has been made on the basis of numerical climate modeling and observations since the late 1990s, the understanding of atmospheric forcing mechanisms affecting summer sea-ice anomalies remain elusive. There are a number of apparent discrepancies in all theories that try to explain the response of the Laptev Sea ice cover during summer to recurrent modes of the Arctic atmospheric and oceanic behavior. An outstanding matter not resolved yet is why the wintertime AO index is in numerous years in coherence with summer sea-ice anomalies in the Siberian Arctic and in some years no correlation is evident. Deser et al. (2000) and Rigor et al. (2002) propose that large-scale atmospheric circulation patterns like the wintertime Arctic or North Atlantic Oscillation are linked to changes in the summer seaice coverage of the Siberian Arctic. Thompson and Wallace (1998) point out, that the wintertime AO pattern accounts for only 22% of the variance of the SLP field in the Northern Hemisphere. The interannual variability of the winter AO index (JFM) and the standardized anomalies of summer sea-ice area (JJAS) in the entire Laptev Sea are presented for the period from 1979 to 2002 in Fig. 11. The late 1980s and early 1990s experienced a high-index AO phase. In recent years it is varying from a weakly positive to a weakly negative index. The period also includes one of the largest year-to-year changes of record as the long positive period was interrupted by the very low AO-index in winter 1996. The wintertime AO-index
45
is weakly correlated with the summer sea-ice anomalies in the Laptev Sea. The Pearson correlation coefficient of both time series is calculated to 0.28 with a significance of 83% and removal of the linear trends. Serreze et al. (2003) is skeptical about the linkage between the AO and summer sea-ice anomalies along the Siberian coast as argued by Rigor et al. (2002). Serreze et al. (2003) suggest that the summer cyclone regime (Arctic low) and consequently low sea-ice concentrations are not linked to the AO and keys to the circulation variability should be sought elsewhere. For instance, Serreze et al. (2001) show that the summer cyclone regime in the Arctic Ocean is in part maintained by cyclogenesis along northeastern Eurasia in association with the Arctic frontal zone. The negative trends and interannual variability of sea-ice area in May and June reflect changes in the in onset date of snowmelt (see discussion of early-melt signal), which are caused by low-frequency atmospheric circulations, according to Drobot and Anderson (2001). They show that variations in the AO explain a significant amount of the variation in mean annual snowmelt-onset dates. During high-AO-index years increased cyclone activity favors enhanced advection of warm air masses. In contrast, low-AO-index periods with an anticyclonic atmospheric circulation cause low cyclone activity delaying the onset of snowmelt. The alternating regimes of cyclonic and anticyclonic wind-driven circulation in the Arctic Basin (CCR, ACCR) as described by Proshutinsky and Johnson (1997) seem to have numerous effects on climate and sea ice in the Laptev Sea. Winds may be responsible for substantial changes in ice conditions.
Fig. 11. Time series of winter AO-index (JFM) vs. standardized anomalies of summer sea-ice area (JJAS, dotted) in the Laptev Sea from 1979 to 2002.
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For example, mean values of polynya and cyclone characteristics as well as ice retreat during ACCR (1984 to 1988) and CCR (1989 to 1997) periods reveal significant differences. During CCR years the mean frequency of polynyas, the mean area of polynyas per winter, and the area of maximum polynya events in spring are higher than during ACCR years, but the duration of single polynya events is reduced by several days on average. For example, the mean area of the WNS polynya during the ACCR period from 1984 to 1988 accounts for roughly 16 103 km2 and during the CCR period from 1989 to 1997 about 22 103 km2. The strongest changes of polynya activity occur in the western Laptev Sea during anticyclonic and cyclonic circulation regimes. The mean frequency of cyclones entering the Laptev Sea region in July is increased by 5 events and the mean central pressure during CCR years is reduced as compared to ACCR years. The average minimum sea-ice cover during the anticyclonic circulation regime is on day 256, whereas the average minimum during the predominance of the cyclonic circulation regime occurs on day 249. The
circulation regimes seem to affect the freeze-up dates as well, causing ice formation during the cyclonic regime at a later day. As documented in Alexandrov et al. (2000), the magnitude and direction of ice exchange in the Laptev Sea agree with the large-scale drift pattern in the Arctic Ocean during ACCR and CCR years. Though a large fraction of the interannual variability of sea-ice exchange can be explained by the shift of large-scale atmospheric circulation patterns in the Arctic, in some years a correlation is not evident. For example in 1990, when ice export was low during winter and ice was imported during summer, the ice extent in the Laptev Sea was anomalously low. Of similar ambiguity are the sea-ice conditions during 1995 (anomalously low) and 1996 (anomalously high). Observed monthly mean sea-ice coverage and sea-ice motion derived from satellite data (Fowler, 2003) and monthly mean SLP and 10 m wind field as simulated by the regional climate model HIRHAM4 (Dethloff et al., 1996) for August 1995 and 1996 are shown in Fig. 12. Both record minimum and maximum ice extents occurred in a period of
Fig. 12. Monthly mean SLP [hPa] and 10 m wind field [m s 1] (gray) simulated by the HIRHAM4 model, observed monthly mean sea-ice coverage [%] and sea-ice motion [cm s 1] (black) derived from satellite data for August 1995 and 1996. Every 5th motion vector is drawn. The gray box marks the Laptev Sea region. Projection: HIRHAM4 model grid (110 100).
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prevailing cyclonic circulation in the Arctic Ocean. During August 1995 the ice edge rapidly retreated toward the north, with almost the entire Laptev Sea ice-free. In contrast, in 1996 almost the entire Laptev Sea including the central and eastern parts remained ice-covered. This comparison shows that in spite of the existence of large-scale circulation regimes the local wind field that prevails during a certain period contributes most to the sea-ice anomaly (Deser et al., 2000; Maslanik et al., 2000). Haas and Eicken (2001) report that in 1995 southerly winds helped to compact and push the summer ice edge toward the North and in 1996 northerly winds resulted in a southward displacement of the ice edge. Numerous past studies have documented links between summer cyclone activity and sea-ice anomalies (e.g. Maslanik and Barry, 1989). Maslanik et al. (1996) reports that the increase of cyclone events in northern Siberia since 1989 coincides with the negative sea-ice anomalies in the Laptev Sea during the early 1990s. This favors stronger and more frequent warm, southerly winds affecting snowmelt, surface albedo and sea-ice drift. Similar to the seasonal cycle of sea ice, cyclone events in the Laptev Sea show a minimum during
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winter and a sharp increase in May with maximum frequency, lowest center pressures of cyclones occurring in summer. Time series of monthly cyclone counts and anomalies for the Laptev Sea region are presented in Fig. 13. The cyclone activity is derived from surface pressure fields at 6-h intervals with a similar detection and tracking method as proposed by Serreze et al. (1993). Mean monthly cyclone activity has increased in the period 1989 to 1995, with associated reductions in mean central pressure. At the same time ice reductions in the Laptev Sea occurred. Cyclone frequency in July 1996 accounted for 9 events as compared to 1995 when 20 cyclone events in the Laptev Sea were apparent. From July on the sea-ice cover becomes vulnerable to cyclone activity and wind stress cause mechanical ice break-up of weakened ice zones. Mechanical deterioration is favored by the microstructure of sea ice, because internal melting processes lead to increased porosity and decreased compactness (Zubov, 1963). It has to be noted, that it still is not known whether a reduced ice coverage provide a significant energy source (release of latent heat) for maintaining cyclone intensity (Maslanik and Barry, 1989).
Fig. 13. Time series of the frequency of registered cyclone events per month (upper panel) and corresponding anomalies from long-term monthly means (lower panel) in the Laptev Sea region from 1979 to 2002. A low-pass filtered (6 elements) time series is added. Only low pressure events of cyclones with a life-time of more than 1 day are considered. White/gray horizontal bars mark anticyclonic and cyclonic circulation regimes.
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Cyclone activity in the Laptev Sea region during the summer months seems to cause a combination of dynamic and thermodynamic atmospheric processes such as sea-ice drift, enhanced absorption of shortwave radiation in polynyas and warm air advection from the Eurasian land masses. These factors imply a key role for existing sea-ice anomalies in the Laptev Sea. The findings are supported by Maslanik et al. (1996), Bareiss et al. (1999), Haas and Eicken (2001) as well as Serreze et al. (2003). 4.2. Linkages to oceanic forcing Although oceanic processes cannot be isolated from riverine and atmospheric processes or atmosphere/sea-ice interactions, the impact of the ocean on sea-ice variability will be treated separately. During high-index phases of the AO or CCR years, respectively, a delayed ice-ocean response leads to a shift of the Transpolar Drift System, the extent of Atlantic Water, and the freshwater distribution to the East. It is still under discussion, if the weakening or retreat of the cold halocline (Steele and Boyd, 1998) is accompanied by a decrease of sea-ice thickness in the Arctic Ocean (e.g. Johannessen et al., 1995; Zhang et al., 1998; Rothrock et al., 1999) due to an increased upward heat flux from the ocean to the ice cover. Atmospheric processes in combination with oceanic processes, such as salinification of the upper water masses, as well as solar heating of flaw polynyas and leads and their subsequent increase in area have significant impacts on sea-ice retreat in the Laptev Sea, predominantly in its northern parts. Observational and modeling results provide evidence that increased atmospheric cyclone activity in the 1990s resulted in a dramatic increase of the salinity in the Laptev Sea. The mechanisms that account for the salinity increase during CCR years are an eastward shift of Siberian river water and increased brine formation due to enhanced ice production in numerous flaw leads and polynyas in the Laptev Sea. Both freshwater redistribution and brine rejection from ice growth in numerous leads result in a strong salinification of the halocline over the Laptev Sea. These processes lead to the weakening of the vertical stratification. The thinning and reduction of the seaice cover is attributed to the retreat of the cold halocline layer and consequently increased vertical
heat fluxes from the salty and relatively warm Atlantic water towards the sea-ice cover. During the ACCR period the redistribution of Siberian river discharge and summer ice melt lead to a freshening of the surface waters and thus to an increase in ice thickness and sea-ice area in the Laptev Sea (Maslowski et al., 2000; Johnson and Polyakov, 2001). The formation of polynyas in the Laptev Sea have a strong impact on the summer ice retreat of both the pack-ice and the fast-ice cover. With the onset of spring, Laptev Sea flaw leads and polynyas are converted from centers of heat loss and ice production to centers of heat gain. The additional heat is used for the bottom and lateral melt of the ice cover. Zakharov (1966) has estimated that the heat gain by short-wave radiation in all flaw leads and polynyas of the Laptev Sea adds up to nearly 3.7 1016 kJ by the end of June. Based on observations from SMMR and SSM/I passive-microwave data, monthly mean areal extents of polynyas in the central Laptev Sea (AL, WNS) range from 20.2 103 km2 in May to 49.6 103 km2 in June and to 88.1 103 km2 in July. To illustrate the possible impact, the net atmospheric heat gain by short-wave radiation of the recurrent polynyas in the central Laptev Sea accounts for 9.8 1015 kJ by the end of May, 2.9 1016 kJ by the end of June, and 4.9 1016 kJ by the end of July. This total heat input by the end of July is hypothetically sufficient to melt about 145 103 km2 of 2-m-thick fast ice, roughly 22% of the total sea-ice cover in the Laptev Sea (Bareiss, 2003). In addition to the lateral and bottom ice melt, mechanical processes play an important role in the disintegration of the sea-ice cover (Zubov, 1963). With increasing fetch-lengths of the openwater areas, the combined thermal and mechanical deterioration (wind-induced and tidal waves) of the ice cover (both the drift and fast ice) proceeds. For example, this phenomena is evident in visible satellite images when large floes with sizes of up to 20 103 km2 break off the ice cover along the fast-ice edge (Bareiss, 2003). The investigation of the temporal and spatial variability of open-water areas from passive-microwave observations reveals that from 1988 on late winter/spring polynyas start to develop earlier than in the period from 1979 to 1987. In some years when no polynya existed in May (e.g. 1984, 1992, 1996), fastice retreat started later than on average. An early
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formation and a large extent of polynyas like in 1990, 1995 and 2000 leads to an early break-up of fast ice in the Laptev Sea. Our findings correspond well with results from Proshutinsky and Johnson (1997), which show the existence of two dominant atmospheric and oceanic circulation patterns. In the period 1984 to 1988 when the ACCR was predominating, polynya activity in the Laptev Sea was low due to ice convergence. The period 1989 to 1997, in contrast, was characterized by a CCR pattern, causing high polynya activity due to ice divergence. The mean frequency and the mean area of polynya events increased as compared to the ACCR period from 1984 to 1988. 4.3. Linkages to freshwater input The Siberian shelf and in particular the Laptev Sea is considered to be a key study area to investigate environmental processes of the Arctic land-shelf system (Forman and Johnson, 1998). Although the Laptev Sea has experienced most significant changes in summer ice coverage during the last two decades, little research has been carried out on the impact of continental river runoff on sea-ice retreat in the Siberian coastal regions. In one of the few studies on coastal fast ice, Bareiss et al. (1999) show that in the southeastern Laptev Sea the influence of Lena River water on ice retreat is clearly evident. With the arrival of snowmelt floods in late May large parts of the fast ice at the delta fronts become affected by river water. Satellite images show that the strongest impact of fast-ice flooding by river water is apparent in the northeastern region of the Lena Delta. With nearly 85% of the Lena River discharge, the eastern branches (e.g. Trofimovskaya channels) of the delta contribute to the largest fraction of freshwater from spring discharge to the Laptev Sea. The flooded fast-ice belt off the northeastern Lena Delta is roughly 25 km wide and 100 km long. Overflows of coastal ice at river mouths of the Yana, Olenek and branches of the Lena River at the western delta are much smaller. After several days, the flood waters drain through the melting nearshore ice cover leaving thin layers of sediments on the ice and open water in front of the channel mouths. The overflows cover the fast ice only for a few days. As spring progresses, most of the above-freezing river water is discharged beneath
49
the nearshore fast-ice for several weeks. The fast-ice further off the coastline, referred to as offshore fast ice in this study, is merely affected by river water at its lower surface causing basal melt. Enhanced melting processes in coastal regions receiving river discharge lead to the formation of coastal polynyas. From early July onward, the coastal polynyas provide additional energy to melt the adjacent fast ice. The role of fresh water in the stratification of the Arctic Ocean and the formation of sea ice has been discussed in detail by Aagaard and Carmack (1989). From results of coupled ice–ocean models Lemke (1987) and Weatherly and Walsh (1996) suggest that reductions in the fluvial fresh-water input lead to reductions of up to 10% in sea-ice thickness caused by a weakening and retreat of the halocline layer (Steele and Boyd, 1998). Observational and modeling results provide evidence that increased atmospheric cyclone activity in the 1990s resulted in a dramatic increase of the salinity in the Laptev Sea (Maslowski et al., 2000; Johnson and Polyakov, 2001). The mechanisms that account for the salinity increase are an eastward shift of Siberian river water and increased brine formation due to enhanced ice production in numerous flaw leads and polynyas in the Laptev Sea. The weakening of the vertical stratification of the halocline leads to a rise in released heat from the ocean to the ice cover, causing large-scale reduction of sea ice in the Arctic Ocean. These findings are supported with ice-thickness measurements carried out in the central Arctic Ocean which show reduction in ice thickness by roughly 20% during the period 1991 to 2001 (Haas et al., 2002). Since the early 1980s the effect of possible Soviet river diversions on sea ice in the Eurasian and Siberian Arctic has been investigated systematically. Treshnikov and Ivanov (1980) along with numerous other Russian scientists suggest that the reduced input of river water onto the shelf initializes inflow of cold arctic surface waters towards the shelf, causing a delay in summer sea-ice retreat. Contrariwise, an increase in the input of river water may cause a reinforced melting of sea ice. These assumptions were supported by Holt et al. (1984) and Cattle (1985). Manak and Mysak (1989) showed the existence of a positive lagged correlation between sea ice and discharge, with discharge leading by 12 months. Based on hydrometeorological observations, Dmitrenko et al. (1999)
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show that an increase in river discharge leads to a freshening of the surface waters in the Laptev Sea and hence, in the subsequent winter to an increase in the fast-ice area. In detailed studies of the impact of river discharge on sea ice, Bareiss et al. (1999) document that, in contrast to previous reports, the interannual variability in summer sea-ice coverage in the Laptev Sea is not controlled by the impact of river water. Instead, coastal fast ice in the vicinity of river mouths, predominantly in the southeastern Laptev Sea, is influenced considerably by river water. The use of the one-dimensional thermodynamic fast-ice model allows to study the influence of river discharge on the seasonal fast-ice retreat and, what is more important, to quantify the impact parameters on this process. Model runs were performed for each river mouth in the East Siberian Arctic for single years (1979 to 1994) on a daily basis (Bareiss, 2003). As an example, Fig. 14 represents model simulations of fastice thickness off the northeastern Lena and Yana deltas under nearshore and offshore conditions using long-term averages of daily forcing data. According to the fast-ice model, simulations indicate that the decay of flooded nearshore ice starts about 1 to 2 weeks earlier than the disintegration of offshore fast ice. Decay of offshore fast ice is characterized by a gradual decrease in ice thickness. Depending on the study area, areas of nearshore fast ice become ice free by the end of June, roughly 4 to 6 weeks earlier than the offshore fast ice, that melts completely by the end of July or beginning of August. Passive-microwave data clearly show the forming of open water offshore from river mouths and the slow decay of fast ice farther seaward. The control run was performed by using the fast-ice model without river heat. Without river discharge the ablation period of nearshore fast ice increases by several weeks, whereas the ablation period of offshore fast ice is delayed only by a few days. The much longer ablation period of fast ice under nearshore conditions is caused by modified parameter settings for the model start, for instance the start value of fast-ice thickness, and the absence of ocean heat (Bareiss, 2003). The relevance of river discharge on fast-ice retreat is assessed by comparing the net atmospheric heat flux with the heat flux from river water as derived from the fast-ice model. With the flooding of nearshore fast ice a drastic increase of the short-wave
Fig. 14. Simulated long-term average (1979 to 1994) of mean daily fast-ice thickness including snow cover under nearshore (gray lines) and offshore (black lines) conditions by the Lena at the Trofimovskaya channel (upper panel) and Yana (lower panel) rivers. The dashed lines indicate the experiments where no river heat is applied to the fast-ice cover. The atmospheric forcing is obtained from the daily re-analysis data of the ECMWF.
radiation balance occurs in June, enhancing fast-ice ablation. Changes in the short-wave radiation balance are primarily controlled by variations of surface conditions and cloud cover. The long-wave radiation balance, turbulent energy fluxes over fast ice and the conductive heat flux trough the ice play a minor role during the ablation period. The comparison of modeled heat fluxes in the southeastern Laptev Sea reveals that the net fluxes of atmospheric and riverine heat (at the upper and lower ice surface) contribute with 53% and 47%, respectively, to the melt of nearshore fast ice (Table 5). The large input of energy at the upper surface generates higher melt rates at the upper than at the lower ice surface. The relative contribution from absorbed short-wave radiation and river heat at the upper surface of flooded fast ice is about 70% to 30%. Hence, the rapid melting of
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nearshore fast ice is caused to a significant part due to a sharp decrease in surface albedo, greater solar heating of the floodwater and the sediment-covered ice surface after draining. For the melting of offshore fast ice 90% of the energy is derived from the atmosphere and only 10% from river water. Mean temperatures of river water rise steadily from about 2 8C to 3 8C in June to about 12 8C by the end of July (Nalimov, 1995). The long-term average of the total amount of energy supplied by rivers in June ranges between 7.05 1013 kJ (Yana River) and 1.33 1015 kJ (Lena River at Trofimovskaya channels), according to 5.6 km3 and 106 km3 of discharge, respectively. For instance, off the northeastern Lena Delta the heat content of river water is sufficient to melt on average roughly 2000 km2 of 2.2 m thick fast ice. Rivers that discharge into the southeastern Laptev Sea have the ability to melt about 3500 km2 of fast ice by the end of June. This area accounts for only 2.5% of the total fast-ice area in that region. In years with record discharge the heat input by river water is sufficient to melt about 4% of the total fast-ice area. The ice-free areas develop to coastal polynyas in July and gradually widen due to lateral melt. Trend analyses of sea-ice data indicate a decrease of fast-ice area in the southeastern Laptev Sea during May and July. These findings reflect the warming during early summer in central and northern Siberia (Bareiss et al., 1999), the advance of the snow-melt season in Siberia from June into late May (Yang et al., 2002) and the observed large increases in river water during May and June of all rivers discharging into the Laptev Sea (Bareiss et al., 1999; Bareiss, 2003). At the same time a negative trend of the onset of river ice break-up (Smith, 2000) and spring discharge (Lammers et al., 2001; Bareiss, 2003), based on hydro-
Table 5 Comparison of long-term means of the simulated energy input [%] from the atmosphere ( Q a) and river water ( Q r) into the nearshore and offshore fast ice off the eastern Lena Delta (Trofimovskaya channel) and the northeastern Yana Delta for the period from 1979 to 1994 Nearshore Offshore
Q a [%] Q r [%] Q a [%] Q r [%]
Lena Trof.-Ch.
Yana NE-Delta
49 51 84 16
57 43 98 2
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logical records, is evident. Consequently, fast ice is affected much stronger in the coastal regions, which receive river water. Fast-ice model experiments have been made for variations of the timing of the spring snowmelt floods at the Lena River. These results confirm that snowmelt floods occurring up to several weeks earlier strongly affect fast-ice decay.
5. Conclusions In this study the spatial and temporal variability of the sea-ice regime in the Laptev Sea has been examined. The SMMR and SSM/I passive-microwave data record of total sea-ice concentrations span a period of 24 years, from January 1979 through December 2002. The major findings of this survey are summarized as follows: (1) The ice regime of the Laptev Sea is characterized by a variety of features such as drift ice, fast ice, ice massifs, flaw and coastal polynyas. The large seasonal cycle of sea-ice area in the entire Laptev Sea varies from a summer minimum of about 190 103 km2 to a winter maximum of roughly 610 103 km2. Our results indicate a high interannual variability of summer seaice coverage. The minima of the daily mean summer ice areas have been shown to vary between 9.3 103 km2 (1995) and 339 103 km2 (1996). (2) The time series of ice area data suggest negative trends in all the areas of the Laptev Sea studied. However, the trend is statistically significant at the 95% level in only one of the regions. The 24 years of satellite derived ice observations reveal a decrease in sea-ice area by 5.5% decade 1 in August or more than 4.5% decade 1 in September and October. Regionally, the western Laptev Sea exhibits largest negative trends in August at 6.9% decade 1 and the eastern Laptev Sea at 5.0% decade 1 in October. In the southeastern Laptev Sea the decrease in fast-ice area are more pronounced in July ( 6.4% decade 1) and October ( 4.6% decade 1). In addition, an increase in polynya activity in late winter/early spring, a shift towards earlier snowmelt-onset, and an increase in open-water area during early fall, indicating an extension of the length of the summer melt period, has been observed. (3) None of the dynamic and thermodynamic factors alone can explain the large interannual
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variability and retreat of sea-ice coverage during summer and early fall as observed in the 1990s. Despite the preliminary understanding of driving processes, there is still a large degree of uncertainty about the role of each factor and coupled mechanisms. Fully coupled regional climate models accurately treating land, ocean, sea-ice and atmospheric processes and giving only a small number of external boundary conditions will provide valuable insight in these couplings and may help to understand sea-ice response to changes of forcing (Maslanik et al., 2000; Rinke et al., 2003). Our analysis support earlier research concluding that ice conditions in the study region are influenced by a combination of dynamic and thermodynamic factors operating over a variety of spatial and temporal scales between climate subsystems. No clear and direct link to large-scale atmospheric modes such as the AO is obvious. (4) In all regions of the southern Laptev Sea the impact of river water on fast-ice retreat is clearly evident. In fast-ice areas exposed to surface flooding coastal polynyas develop after 4 weeks on average, whereas adjacent fast ice melts after 8 weeks. According to our model results, the net fluxes of atmospheric and riverine heat contribute with 53% and 47%, respectively, to the melt of nearshore fast ice. This is to a significant part due to the sharp decrease in surface albedo and greater solar heating of the flooded or sediment-covered upper ice surface. For the melting of offshore fast ice 90% of the energy is derived from the atmosphere and only 10% from river water.
Acknowledgements
We very much appreciate the comments and suggestions of C. Haas from the Alfred-WegenerInstitute for Polar and Marine Science (Bremerhaven, Germany) and H. Eicken from the Geophysical Institute of the University of Alaska Fairbanks. SMMR and SSM/I passive-microwave and ice drift data were provided by the National Snow and Ice data Center, Boulder (CO, U.S.A.). NCEP/NCAR reanalysis data were obtained from the NOAA-CIRES Climate Diagnostics Center, Boulder (CO, U.S.A.) and ECMWF re-analysis data from the European
Centre for Medium-Range Weather Forecasts (Reading, U.K.). Computational resources and software were provided by the German High Performance Computing Centre for Climate- and Earth System Research (Hamburg, Germany). This study was partly financially supported by the German Research Foundation (DFG) under contract He 1929/3-1. Two anonymous reviewers provided valuable suggestions to improve the manuscript.
References
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Spatial and temporal variability of sea ice in the Laptev Sea: Analyses and review of satellite passive-microwave data and model results, 1979 to 2002 J. BareissT, K. Go¨rgen University of Trier, Department of Climatology, 54286 Trier, Germany Received 10 October 2003; received in revised form 21 April 2004; accepted 9 December 2004
Abstract Satellite passive-microwave radiometer-derived sea-ice concentrations have been used to investigate the spatial and temporal variability and trends of sea ice in the Laptev Sea during 24 years from 1979 through 2002. The resulting time series have been further analyzed to provide a climatology for sea-ice and polynya characteristics. The ice regime of the Laptev Sea is characterized by a large seasonal and interannual variability, the latter occurring exclusively in summer. By using a consistent sea-ice data record, we can document negative trends in all the areas studied for the 24-year period, Due to the large interannual variability the trends are not significant. For the entire Laptev Sea the decreases in sea-ice extent and area on a yearly average basis reveal 1.5% decade 1 and 1.7% decade 1, respectively. In summer and early fall large losses in sea-ice cover of up to 7% decade 1 are evident in regional sectors of the Laptev Sea. In addition, an increase in polynya activity in late winter and early spring, a significant shift towards earlier snowmelt onset, and an increase of open-water area in early fall indicating an extension of the length of the summer melt period, has been observed. A brief overview of climate and sea-ice research in the Siberian Arctic is presented. According to observational data and numerical experiments there is still a large degree of uncertainty about the role of dynamic and thermodynamic factors and possible feedback mechanisms in the atmosphere–ice– ocean system, which are responsible for the large interannual variability and the retreat of sea-ice coverage as observed in the 1990s. Summer sea-ice anomalies likely result from synoptic-scale processes superimposed by the large-scale atmospheric circulation during summer and to a lesser extent from preconditioning processes in winter and spring. D 2005 Elsevier B.V. All rights reserved. Keywords: sea ice; polynyas; remote sensing; thermodynamic sea-ice model; cyclone detection and tracking; Laptev Sea; Arctic
1. Introduction T Corresponding author. Fax: +49 651 201 3817. E-mail addresses: [email protected] (J. Bareiss), [email protected] (K. Go¨rgen). 0921-8181/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.gloplacha.2004.12.004
Arctic sea ice and its variability play a crucial role in the regional and Northern Hemisphere climate system as well as global ocean circulation (Zakharov,
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1997). It moderates the energy balance by changing the surface albedo of the ocean and controls the vertical fluxes of heat, mass and momentum between the ocean and the atmosphere. Furthermore, sea ice has an impact on the ocean circulation by providing cold and dense water during the freeze-up period and fresh surface water during the melt-season, predominantly formed in the Arctic marginal seas. Because of its thin layer in the ocean, sea ice might be a sensitive indicator of climate change (Barry et al., 1993). Strong couplings exist between the sea-ice cover, atmosphere and ocean. Among the marginal seas of the Arctic Ocean the Laptev Sea (Fig. 1) represents one of the most significant sites of net ice production in the Arctic (Zakharov, 1966; Dethleff, 1995). As much as 20% of the ice area transported through Fram Strait is produced in flaw leads and polynyas of the Laptev
Fig. 1. Map of the Laptev Sea showing the location of sea-ice study sites and the locations of synoptic meteorological (white circles) and hydrological stations (white squares). The gray and hatched boxes mark the fast-ice and polynya study areas (for names refer to text). The black boxes represent the areas of coastal polynyas affected strongly by river discharge. The black solid lines indicate the 20 m and 200 m isobaths.
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Sea (Rigor and Colony, 1997). Therefore the seasonal cycle of sea ice is of fundamental importance for the sea-ice budget and ocean-ice–atmosphere processes in the Arctic. The impact of Lena River discharge, one of the Arctic’s major rivers discharging roughly 530 km3 annually onto the Laptev Sea shelf, is of particular importance for coastal fast-ice processes (Bareiss et al., 1999; Bareiss, 2003). Furthermore, as large amounts of sediments are entrained on the shallow Laptev Sea shelf during ice formation (Eicken et al., 1997, 2000), ice originating from the Laptev Sea largely determines the amount of sediment transport across the Arctic Ocean via the Transpolar Drift System (Nu¨rnberg et al., 1994; Pfirman et al., 1997). Beside the many foci of climate and sea-ice research in the Laptev Sea, the Russian maritime Arctic and Northern Sea Route attracts international attention like the International Northern Sea Route Programme (INSROP) to analyze risks and cost benefits of transit navigation in the Siberian Arctic (Brigham, 2000). In recent decades numerous changes of sea-ice characteristics have taken place in the Laptev Sea. In September 2002 Arctic sea-ice extent and area reached their lowest values observed since 1978 (Serreze et al., 2003). Besides its strong seasonal and interannual variability, observations from satellite passive-microwave data indicate that between 1978 and 1996 the greatest decreases in the Arctic ice extent occurred in the Laptev and East Siberian seas during summer and early fall (Maslanik et al., 1996; Cavalieri et al., 1997; Parkinson et al., 1999). Hydrographic observations made in the 1990s (e.g. Carmack et al., 1995; Steele and Boyd, 1998; Ekwurzel et al., 2001) and results from coupled models of the Arctic Ocean (e.g. Proshutinsky and Johnson, 1997; Zhang et al., 1998; Maslowski et al., 2000) reveal large-scale changes such as an shift of the Transpolar Drift System to the northern boundary of the Beaufort Sea. From analysis of sea-ice motion data in the 1980s and 1990s, Rigor et al. (2002) note a decreasing sea-ice area adjacent to the fast-ice edge in the western part of the Laptev Sea and an increase in ice area in the eastern part, consistent with the observed negative trend in sea-ice concentration during summer. They further report an increase of ice advection away from the coast of the Laptev Sea during winter in the period 1989 to 1998 and simultaneously an increase in the forming of flaw polynyas, enhancing the production
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of thin new ice. Sea-ice thickness measurements in the Laptev Sea carried out in the 1990s indicate significant interannual variability. Haas and Eicken (2001) found a difference of up to 1 m in ice thickness in the years 1995 and 1996 when anomalous low and high sea-ice extents occurred in the Laptev Sea. It is not yet clear whether a thinning of sea ice has taken place, because there is a fundamental statistical sampling problem in analyzing highly variable (both spatially and temporally) ice-thickness time series. There is a diversity of conclusions concerning the driving mechanisms explaining the variability and negative trends in sea-ice conditions in the Laptev Sea. As will be discussed later, some authors assume dynamic and thermodynamic atmospheric or oceanic causes (e.g. Serreze et al., 1993; Proshutinsky and Johnson, 1997; Johnson and Polyakov, 2001; Rigor et al., 2002). It has been reported by Bareiss et al. (1999) that there is no correlation between springtime river discharge and early summer sea-ice decay in the Laptev Sea as a whole. Only in the vicinity of river mouths an impact on fast ice is clearly evident due to freshwater input by Siberian rivers and the forming of coastal polynyas, enhancing the fast-ice retreat. This work is meant to give an overview of the general sea-ice regime in the Laptev Sea. A special focus is on the spatial and temporal variability (both seasonal and interannual) of the sea-ice, polynya and fast-ice areas. Trend analyses are provided for various sea-ice parameters within regional sectors. The reasons for the large variability of sea-ice area or extent, respectively, are discussed by reviewing recent findings of atmosphere/sea-ice/ocean interactions. These results are supplemented by analyses of the impact of river discharge on fast ice by using a thermodynamic sea-ice model that incorporates river water.
2. Data and methods Satellite-derived passive microwave data is used to obtain time series of sea ice and fast ice in selected regions of the Laptev Sea (Fig. 1). These time series are further used to derive polynya characteristics with a simple threshold technique validated with visible satellite data. The influence of river discharge on the
seasonal fast-ice retreat in the vicinity of the river deltas and estuaries in the Laptev Sea is studied by using a thermodynamic sea ice model and by quantifying the impact parameters on the simulated processes. 2.1. Deriving time series of sea-ice area Satellite passive-microwave data provide sea-ice concentrations and polynya characteristics for all seasons from 1979 through 2002. Consistent iceconcentration data, based on the NASA-Team algorithm (Gloersen et al., 1992; Cavalieri et al., 1999), have been derived from the Scanning Multichannel Microwave Radiometer (SMMR) and since 1987 from the Special Sensor Microwave Imager (SSM/I) at the 37 GHz and 18 GHz (or 19 GHz) channels as provided by the National Snow and Ice Data Center (NSIDC) and the NASA/Goddard Space Flight Center (NASA/GSFC). SMMR data is available on an alternate-day basis, SSM/I data on a daily basis. Total sea-ice concentrations (first-year and multi-year sea ice) from both radiometers are mapped on an equalarea grid with a cell size of 625 km2 (25 km 25 km). Passive microwave derived sea-ice products are sensitive to calibration drift, sensor differences as well as the use of different land and ocean masks, tiepoint adjustments and quality controls by NSIDC and NASA/GSFC. Other sources of error in the ice retrievals include possible effects such as thin ice (new ice, nilas, young ice), snow melt (increase of snow wetness, meltponding) and atmospheric effects (water vapor, liquid water), e.g. Grenfell et al. (1992), Cavalieri et al. (1995), Comiso and Kwok (1996), Fetterer and Untersteiner (1998). Values from both sea-ice data sets reveal no appreciable differences (Serreze et al., 2003). There are minor inconsistencies among sensors and data sets as well as some general loss of information, due to the coarse resolution of SMMR and SSM/I data. Although there are some deficiencies, derived time series from sea-ice concentrations provide valuable details of the variability of sea-ice (drift ice, fast ice) and polynyas (open-water area, location, date of opening, closing and duration of polynya events) on a repetitive basis. The sea-ice data set used in this study has undergone additional processing. Temporal gaps in the SMMR data have been filled by linear interpola-
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tion between adjacent days. A combined land mask of the NSIDC and NASA/GSFC data sets has been applied to the ice concentrations fields. In mapping sea-ice conditions close to land there is always a potential risk of mixing the emissivities from sea ice and adjacent land due to the large footprint of the SMMR and SSM/I sensors. Consequently the combined land mask has been enlarged by one pixel, except for studies of the impact of river discharge on fast ice due to the nearshore location of these study areas. These procedures allow trend and anomalies to be examined with greater confidence. The SMMR- and SSM/I-derived daily total sea-ice concentrations, defined as the mean sea-ice coverage of a grid cell, have been used to calculate total sea-ice coverage and sea-ice, fast-ice as well as open-water areas in selected regions of the Laptev Sea. According to hydrological and sea-ice regimes, the Laptev Sea is divided in a western and eastern part. The boundary between both regions runs along 1268E. Following Parkinson et al. (1999), ice coverage [%] is determined from the ratio between the number of pixels with an ice concentration z 15% and the total number of pixels in the region of interest (including open water). Ice extent [km2] is the cumulative sum of the area of all grid cells in the region of interest, having sea-ice concentrations of at least 15%. The sea-ice and fast-ice areas [km2] represent the area of the ocean actually covered by sea ice. It is the sum of the icecovered area (ice concentration times grid-point area) of all grid points within the subset that have at least an ice concentration of 15%. 2.2. Deriving polynya characteristics Time series of polynya open water-area on a daily basis are derived by subtracting the sea-ice area (see above) within a defined polynya mask from the total area of this mask. The polynya masks (Fig. 1) are defined empirically based on the mean location and extent of the polynyas. The mean location is derived from long-term monthly mean sea-ice concentration maps and distributions of temporal standard deviations of the monthly means from the long-term monthly means (data not shown). A threshold of 1.5% of open-water area in the requested polynya query box is used to decide whether a polynya (or lead) is present. This information is used to calculate
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the timing, the duration and the time-dependent (open water) area of the openings (Fig. 2a). Advanced Very High Resolution Radiometer (AVHRR) data are used to: (1) aid in the derivation of the threshold; (2) validate the derived open-water areas; (3) demonstrate the suitability for the detection of small-scale features of the polynyas and leads from the relatively coarse-resolution sea-ice concentration base-data. Global and Local Area Coverage (GAC, LAC) AVHRR-data at visible- and infrared-wavelengths have been obtained from the NOAA Satellite Active Archive (SAA) and processed with TeraScan software from SeaSpace Corporation. Two comparisons are made for selected dates: (1) sea-ice concentration maps vs. AVHRR images and (2) derived open-water area in polynyas vs. digitized open-water areas from AVHRR images. The 1.5% open-water threshold is derived empirically by comparing georeferenced AVHRR images with SMMR and SSM/I derived open-water areas. During winter polynya areas are underestimated (Eppler et al., 1992; Comiso and Gordon, 1998). This is due to sensor characteristics of passive-microwave radiometers and deficiencies of the NASA-Team algorithm in discriminating unambiguously between open water and newly formed ice which are typical for polynyas (Fig. 2b). We focus entirely on the area of open water within a polynya because of its significance for the turbulent exchange of sensible and latent heat between the ocean and the atmosphere and for its impact on pronounced meteorological features (e.g. arctic stratus, fog, reinforcement of cyclones). Even thin ice (5 cm to 10 cm) reduces heat fluxes between the ocean and atmosphere by an order of magnitude. During spring and early summer, the open-water areas from passive-microwave data are in many cases slightly overestimated due to the enlarged size and increased frequency of leads in the drift ice that is also covered by the defined polynya box. For example, the sea-ice conditions on 31 May 1995 as displayed in the SSM/I-derived ice concentration chart and the visible channel satellite image from NOAA-AVHRR mark the West New Siberian Polynya (Fig. 2c). The open water area in the AVHRR image yields 19 103 km2, while the area indicated as open water in the SSM/I chart is 20.7 103 km2. Such comparisons have been made for numerous polynya events in order to assess the accuracy of our calculations.
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Fig. 2. (a) Example of the application of the polynya detection method. Time series of daily open-water area [km2] within the Western New Siberian polynya query box from November 2001 to June 2002. The horizontal line indicates the 1.5% threshold [km2] for determining polynya characteristics. The sea-ice conditions in the Laptev Sea on (b) 2 January 1995 (left panel) and (c) 31 May 1995 (right panel) as displayed in the visible channel satellite image from NOAA-12 and 14 AVHRR (LAC) and the SSM/I derived ice concentration [%] chart. The polygons mark the area used to calculate the size of the WNS-Polynya. The size of the AVHRR image is approximately 1400 km 845 km.
Small-scale features like leads with a width of less than approximately 5 km are not represented in the coarse-resolution SMMR and SSM/I sea-ice concentration data. The high-resolution 85 GHz channel (12.5 km 12.5 km) of the SSM/I radiometer has not been used to study polynya events as proposed by Markus and Burns (1995) and Markus et al. (1998). Firstly, the 85 GHz channel is highly sensitive to atmospheric effects and secondly the SSM/I sensor is only covers the period from 1987 to the present. The open-water areas determined from the passivemicrowave radiometer based sea-ice concentrations
are generally in good agreement with the areas calculated from reference AVHRR data. Despite of the limited accuracy of the sea-ice concentration estimates the threshold yields reasonable results. Thus the passive microwave data sources are suitable to make long-term studies and will be used in subsequent analyses. 2.3. Thermodynamic sea-ice model A one-dimensional thermodynamic fast-ice model (Bareiss et al., 1999; Bareiss, 2003) has been utilized
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to derive ice melt rates from the energy balance at the upper and lower ice surfaces. The model is based in part on the formulation of Maykut and Perovich (1987) and Dean et al. (1994) and takes into account the presence of overlaying snow as well as heat conduction through snow and ice layers. A surfaceand thickness-dependent albedo parameterization of snow and sea ice based on data of Flato and Brown (1996) and Perovich et al. (1998) is used. Extensive sensitivity studies of the effects of prescribed conditions, forcing data sets and parameterizations are presented in more detail in Bareiss (2003). Two principal cases of fast-ice decay have been considered in more detail: the decay of flooded nearshore fast ice in the mouth of the rivers, and the decay of snow-covered or bare fast ice adjacent to the flooded areas. The energy balance equations at the snow/ice/ water–atmosphere interface can be expressed for fastice that may be covered with snow, river water or bare ice as: 1 afi;s;w RS;A þ RL;A þ RL;z þ QH þ QE þ QR þ QC ( 0 : T0 VTf ¼ ð1Þ qfi;s Lf ðBh=Bt Þ : T0 NTf and for fast ice at the ice–ocean interface as: QR þ QO þ QC ¼ qfi;s Lf ðBh=Bt Þ : QR þ QO þ QC N0;
ð2Þ
where R S,A is the incoming short-wave radiation, a fi,s,w the albedo of fast-ice, snow and flooded fastice. R L,A is the incoming, R L,z the emitted long-wave radiation, Q H and Q E are the sensible and latent heat fluxes, respectively. Q R is the heat flux provided by river water, Q C is the conductive heat flux through the ice to the surface and Q O represents the ocean heat flux. The density of ice and snow is expressed by q fi, and q s, L f is the latent heat of fusion of fast ice, h the ice thickness and t the time. For more details on the model, physical values, and parameterizations of the radiation and turbulent heat flux densities the reader is referred to Bareiss (2003). Forcing data of the sea-ice model include meteorological parameters obtained from international reanalyses projects (ECMWF, NCEP/NCAR) and synoptic weather stations, as well as discharge data from
33
various Siberian rivers gauges provided by the Arctic River Data Base. Due to the availability of river discharge data this study was performed over the period 1979 to 1994.
3. Variability and trends in sea-ice area, openwater area within polynyas and fast-ice area 3.1. General sea-ice regime The total area of the Laptev Sea, according to the grid of the satellite passive-microwave sea-ice data set, comprises 661.25 103 km2 (621.25 103 km2 with enlarged land mask). The ice regime is characterized by three specific sea-ice features: fast ice, flaw polynyas, and drift ice (Fig. 2b,c). Most parts of the Laptev Sea are covered with sea ice from October to June. During summer only the southern and central parts of the shelf become ice-free. In winter when the Vilkitsky, Shokalskogo, Dmitry Laptev, Sannikova and Eterikan straits connecting the Laptev Sea with the Kara and East Siberian Seas, are covered with fast ice, ice export into the Arctic Ocean at the northern boundary dominates. During summer the net ice exchange is balanced; it is characterized by short periods of predominant import and export. Between fast-ice break-up and ice disappearance the ice exchange with the adjacent marginal seas commences but is rather insignificant with some exceptions (Kotchetov et al., 1994). In all seasons but principally in summer, the exchange of sea ice between the Laptev Sea and the Arctic Ocean can experience large interannual fluctuations. Two quasi-stationary major ice fields, clearly apparent in visible and microwave satellite data, occasionally remaining during the summer, can be distinguished: the Taimyr ice massif in the western Laptev Sea east of the Taimyr Peninsula and Severnaya Zemlya, and the Yana ice massif in the southeastern Laptev Sea (Fig. 3). These large assemblages of close ice cover areas at the beginning of August are as large as 150 103 km2 (Taimyr) and 70 103 km2 (Yana), respectively. The Taimyr ice massif originates from Arctic pack ice, whereas the Yana ice massif develops in shallow waters from fast ice. In most years they disappear in the middle of summer. In some years the ice massifs can persist until
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the end of summer seriously hampering navigation (Kotchetov et al., 1994). From systematic observations carried out since the 1930s and summarized in Romanov (1996) the monthly mean thickness of drift ice throughout the Laptev Sea at the end of winter (April) is 1.57 m, its standard deviation S.D. = 0.243 m. Drill hole and electromagnetic induction measurements performed in the summers of record minimum (1995) and record maximum (1996) ice extent revealed a mean modal first-year ice thicknesses of 1.25 m and 1.85 m, respectively (Haas and Eicken, 2001). Fast ice grows in average up to 1.95 m (S.D. = 0.167 m). Mean ice thickness in fast ice according to the data of Russian polar stations account for 1.99 m in the western, 2.11 m in the central and 2.04 m in the eastern portion of
Fig. 3. Sea-ice concentration [%] chart of the Laptev Sea on 11 August 1984 as derived from passive-microwave data (SMMR) showing the Yana ice massif in the southeastern portion of the shelf sea. Ice concentrations are smoothed using a 3 3 Gaussian lowpass filter and values V 5% are defined as water (white). Also shown is the land mask of the sea-ice data set.
the Laptev Sea (Kotchetov et al., 1994). Freshwater fast ice in the vicinity of river mouths reaches a thickness of 2.20 m on average (Dmitrenko, 2000, pers. comm.), and up to 3.0 m in the branches of the Lena and Yana deltas (Nalimov, 1995). More than 50% of the shallow eastern Laptev Sea and up to 25% of the western Laptev Sea are covered with fast ice. Each winter fast ice grows along the coastlines of Severnaya Zemlya, Taimyr Peninsula, the southwestern and eastern Laptev Sea (on average 250 103 km2). Between the Lena Delta and the New Siberian Islands a smooth and freely floating fast-ice cover, consisting of large and thick first-year ice floes, extends as far as 500 km from the Siberian mainland. The fast-ice cover is locally controlled by small islands and shoals (Reimnitz et al., 1994). In the southeastern Laptev Sea it covers an area of about 140 103 km2 (Bareiss, 2003). Along the eastern coast of the Taimyr Peninsula and Severnaya Zemlya the width of the fast-ice belt does not exceed 50 km. The fast-ice extent roughly coincides with the position of the 20 m to 25 m isobaths. In the western Laptev Sea fast ice can sometimes persist during the summer and become multi-year fast ice (Reimnitz et al., 1995). Extensive regions east of the Lena Delta, in the Gulf of Buorkhaya, and near river mouths consist of freshwater ice. Tidal cracks in the fast-ice cover form throughout the winter. In regions more shallow than 2 m the fast ice becomes bottom fast ice (Reimnitz et al., 1995). The position of the fast-ice edge derived from NOAA-AVHRR data in mid-May is presented in Fig. 4. In most parts of the Laptev Sea the fast-ice edge is more or less stationary. According to Dmitrenko et al. (1999) the small-scale variability in the position of the fast-ice edge is caused by the interannual variability of river discharge from the Khatanga, Anabar, Olenek, Lena and Yana rivers. Processes such as grounding play a minor role for the lateral extent of fast ice (Eicken et al., this issue). Fast ice on the Laptev Sea shelf plays a crucial role in the freshwater cycle of the ocean due to storing of freshwater from discharge in winter and releasing it in summer. A further prominent feature of the ice regime in the Laptev Sea are linear-shaped flaw leads and sphericalshaped flaw polynyas (Fig. 5, upper panel), that may extend from some 100 km to nearly 2000 km and reach maximal widths of up to 250 km. They are
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During wintertime the flaw leads consist of open water or young ice of various thicknesses up to 0.70 m. Due to constant offshore-winds new ice is continuously formed. In addition, openings in the pack ice that form during winter are sites of brine formation, affecting the local convection and water mass stratification (Dmitrenko et al., 2001). The wind-driven polynyas result in intense heat loss from the ocean to
Fig. 4. Extent of the fast-ice cover in the Laptev Sea from 1979 to 1994. The black lines represent the position of the fast-ice edge in the Laptev Sea as derived from NOAA-AVHRR images (GAC, LAC) in mid-May of each year.
zones of ice-free water or young ice that are formed between fast ice and seaward drift ice due to regional atmospheric pressure conditions and associated nearsurface wind fields. Polynya openings are caused by offshore winds. In the context of maintenance, the flaw polynyas can be classified as latent heat polynyas driven by the latent heat of fusion which is supplied to the surrounding water masses due to new-ice formation (Smith et al., 1990). The main flaw polynyas, according to Zakharov (1966), occurring in the Laptev Sea are: East Severnaya Zemlya Polynya (ESZ), Northeastern Taimyr Polynya (NET), Taimyr Polynya (T), Anabar-Lena Polynya (AL), West New Siberian Polynya (WNS). Most polynyas in the central Laptev Sea are recurring polynyas (frequency of occurrence N 50%). The flaw polynyas in the northwestern Laptev Sea are temporary ones, with a frequency of occurrence b 50% (ESZ, ET). Due to the prevailing wind direction openings in the eastern and northwestern Laptev Sea occur directly opposed (Kotchetov et al., 1994).
Fig. 5. NOAA AVHRR images (visible channel) of the Laptev Sea polynyas on 3 June 1995 (upper panel) and of the Lena Delta on 19 June 1995 (lower panel) showing the coastal polynya and the flooded nearshore fast ice off the eastern delta channels and the southern part of the Western New Siberian Polynya extending close to the northern delta. The size of the images are approximately 1200 km 1000 km and 300 km 300 km, respectively.
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the atmosphere, controlling the formation of fog banks and low-level clouds (Arctic stratus). Zakharov (1966) estimates from energy balance studies that in all leads and polynyas of the Laptev Sea 910 km3 of new ice is formed from October to April. Dethleff (1995) put into perspective that, compared to the entire mean volume of sea ice formed in the northern hemisphere (20 103 km3), the Laptev Sea flaw polynyas do not contribute significantly (only about 1.3%) to the total ice volume formed during one winter season. However, the polynyas produce relatively large amounts of new ice in respect to their limited areal extent. With the steady increase of solar radiation during spring (May) flaw polynyas turn to areas of heat gain. Mean polynya sizes in the central Laptev Sea (AL and WNS combined) extend to 20 103 km 2 in May, to 50 103 km2 in June, and to 90 103 km2 in July. Maximum polynya areas range from 45 103 km2 in May to 130 103 km2 in July, respectively (Bareiss, 2003). Coastal regions of the Laptev Sea are highly sensitive to river water as discharge interacts directly with the nearshore and offshore fast-ice cover (Nalimov, 1995; Bareiss et al., 1999; Bareiss, 2003). Thus, these coastal polynyas (so-called by Russian scientists) in the vicinity of river mouths can be referred to as sensible heat polynyas, because they are partly formed and maintained by the heat gained from river water (Fig. 5, lower panel). Once the fast ice ahead of the river mouths is flooded by river discharge and sediments the decreasing sea-ice albedo leads to the absorption of short-wave radiation. Atmospheric heat gain dominates the melting process in addition to the influence of the heat supplied by the relatively warm and fresh riverine water.
cover that typically varies in ice area from 190 103 km2 in summer to 610 103 km2 in winter. In individual years ice retreat during August and September is more distinctive in the eastern Laptev Sea than in the western portion (data not shown). On average, minimum and maximum values of all fast-ice areas, including the ice along the shores of Severnaya Zemlya and the Taimyr Peninsula, range from 16 103 km2 in summer to 165 103 km2 in winter. In the southwestern and southeastern Laptev Sea fast ice completely vanishes during summer with the exception of seasons with ice massif events. Passive microwave observations indicate, that the onset of sea-ice melt in the open Laptev Sea proceeds from the South (beginning of June) to the North (end of June). In the areas of developed flaw polynyas and in the vicinity of river mouths and deltas intensive melting also starts in early June. Table 1 summarizes mean representative values of parameters which characterize the temporal sea-ice development in defined regions of the Laptev Sea as recommended by Eicken et al. (1997) and Bareiss et al. (1999). The
3.2. Seasonal variability For regional sectors in the Laptev Sea the characteristic pattern of the increase in sea-ice area during fall freeze-up to its maximum in winter and the decrease to its annual minimum in summer is presented in Fig. 6. As discussed earlier, for all analyses of the temporal sea-ice variability an enlarged land mask is used. The seasonal variability of observed total sea-ice concentrations in the entire Laptev Sea and its western and eastern parts is well pronounced. The 24-year mean seasonality of sea-ice in the Laptev Sea shows an ice
Fig. 6. Time series of SMMR- and SMM/I-derived daily mean seaice area [103 km2] in the entire, western, and eastern Laptev Sea (upper panel) and daily mean fast-ice area of the entire and southeastern Laptev Sea (lower panel) averaged for 1979 to 2002. The gray box marks the period of the early-melt signal as apparent in passive-microwave data.
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early-melt signal in the passive microwave data is determined as the date when the ice-area values drop below a coverage of 85% for the first time during spring. The date of the actual ice retreat is defined by the first maximum of the sea-ice coverage after the local minimum during the period of surface melt (see below). Fall freeze-up is defined by the local minimum in sea-ice area before a steep increase to values z 90%. Fig. 6 illustrates the melt and freeze-up terms. Mean retreat in ice-area commences in the beginning of July (day 187). The duration of ice retreat to its summer minimum lasts for about 9 weeks. In contrast to the entire Laptev Sea fast ice in the southeastern region vanishes completely after 7 weeks (day 232). The average summer minimum of sea-ice area in the Laptev Sea is attained between mid-August and mid-September on day 250, in its eastern part on day 252, and in the western region on day 244. The mean sea-ice area that remains during summer in the 24-year period accounts for 165 103 km2. The rate of sea-ice decline in the eastern portion of the Laptev Sea occurs in general more intensive than in the western sea region. On average, 84% of the eastern and 67% of the western Laptev Sea become ice-free during summer. According to Eicken et al. (1997) and Bareiss et al. (1999), this difference reflects the impact of Lena and Yana river water in the eastern Laptev Sea and the importance of sea-ice advection in the western part. Mean values of ice retreat during the 1980s and the early 1990s reveal substantial differences. The average minimum sea-ice cover during 1984–1988 is on day 256, whereas the average minimum during the period from 1989 to 1997 occurs on day 249.
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In the southern regions that are covered with fast ice the decrease of ice area during the ablation period is not uniformly continuous as in the larger Laptev Sea regions (Fig. 6, lower panel). On average, the apparent reduction in total sea-ice concentration or sea-ice area, respectively, starts in the beginning of June, with a first minimum in ice-area reached about 7 days later (Table 1). This first decline in passivemicrowave data towards a local minimum followed by a subsequent increase after 10 days is deemed an important indicator of surface melt. As discussed in more detail in Bareiss et al. (1999) this passivemicrowave derived early-melt signal can be interpreted as an artifact largely due to changes in surface emissivity occurring in the snowpack and the upper ice layers as a result of warming and in-situ meltwater production. With the forming of a superimposed ice layer, emissivity readjusts towards its pre-melt status, with a corresponding increase in derived sea-ice concentrations. The belt of fast ice starts to break up in early to mid-July. The southeastern Laptev Sea becomes completely ice-free by mid-August. The spatial distribution of the long-term average of mean daily sea-ice cover in the Laptev Sea during summer minima from 1979 through 2002 (7 September) is shown in Fig. 7. In addition to the 5%-isoline of total sea-ice concentration the more common 15% contour line (dashed) is presented that better marks the position of the ice edge. A large part of the shallow central and eastern Laptev Sea becomes free of ice each summer. The mean position of the ice edge is located near the New Siberian Islands but still south of the shelf break. The remaining mean ice cover in the western Laptev Sea extends as far south as 788N,
Table 1 Characteristics of mean parameters of sea-ice development in the entire, western, eastern, and southeastern Laptev Sea derived from passivemicrowave satellite data (SMMR, SSM/I) Early-melt signal Actual start of ice retreat Date of sea-ice minimum Ice-retreat duration Area of sea-ice minimum [103 km2] Date of freeze-up Freeze-up duration
Entire Laptev Sea
Western Laptev Sea
Eastern Laptev Sea
Southeastern Laptev Sea
163 187 250 63 165 268 24
166 187 244 58 110 267 24
161 186 252 66 46 269 23
161 188 232 44 1.8 275 20
(8.2) (8.5) (10.2) (14.1) (85) (8.5) (7.1)
(7.4) (8.7) (17.8) (21.2) (54) (8.7) (8.1)
(8.0) (9.4) (11.3) (14.4) (37) (8.0) (7.7)
(6.9) (9.4) (14.1) (10.7) (6.6) (7.0) (7.9)
Long-term means (day of year) and standard deviations (days in parenthesis) refer to the period from 1979 to 2002. Note that columns of western and eastern Laptev Sea do not always add up to the means of the entire Laptev Sea, since they have been calculated separately for each region.
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although in some years the ice edge retreats north of the Taimyr Peninsula. There is no distinct freeze-up pattern in the Laptev Sea (Kotchetov et al., 1994; Eicken et al., 1997). In most years, predominantly in the 1980s and the late 1990s, new-ice formation starts in early September in the northern Laptev Sea, proceeding southward from the summer drift-ice edge. In the coastal areas the onset of stable fast-ice formation starts at the end of September. In the early and mid-1990s a change to another freeze-up pattern is evident. Ice formation commences in the northern and the southern coastal shallow waters of the Laptev Sea at the same time. The average starting date of fall freeze-up in the total Laptev Sea takes place in mid-September (Table 1). Within 2 to 4 weeks vast areas of the Laptev Sea are covered with young ice. In the southeastern Laptev
Fig. 7. Chart of daily mean sea-ice concentrations [%] of the Laptev Sea at the beginning of September in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I). The dashed line marks the position of the ice edge typically identified as the 15% contour line. Also shown is the land mask of the sea-ice data set.
Sea mean ice formation starts in late September to early October (day 275). Due to the southward progression of the ice edge no difference in the dates of freeze-up are apparent between the western and eastern Laptev Sea. The rate of ice formation is accelerated by strong winds inducing intensive vertical mixing and cooling of the water column, which is even more intensive on the shallow shelf (Kotchetov et al., 1994). As maximum sea-ice coverage is reached already in fall, ice thickness continues to increase until May. During most weeks in fall, winter and spring the Laptev Sea shows a sea-ice coverage between 90% and 100%. Occasional reductions in ice coverage during winter and spring are caused by the formation and development of flaw leads and polynyas. In general, the development of polynyas in the Laptev Sea is fixed in location but differs in time. Polynya activity (frequency, duration, extent) is largely controlled by parameters of the wind regime such as wind speed and direction as well as persistence. Day-to-day changes of important polynya features during the winter season reflect the magnitude, stability and timing in offshore wind speeds. In the Laptev Sea synoptically induced winds are prevalent. In addition to the dynamic forcings of polynya events the absorption of short-wave radiation is of fundamental importance for the areal extent of polynyas in late spring (Zakharov, 1966; Dethleff, 1995; Bareiss et al., 1999). Mean seasonal (November to June) statistics obtained for each of the representative flaw polynyas in the Laptev Sea are given in Table 2. The mean frequency of polynya events in all investigated regions accounts for 12.4. On average, polynyas last for 16 days. The polynyas in the central and eastern Laptev Sea (Al, WNS) are more stable and two to four orders in magnitude larger in extent than the polynyas in the western and northwestern region. The WNS Polynya is the largest polynya in the Laptev Sea covering on average an area of 4 103 km2 in winter. During extremely strong polynya events the WNS Polynya may occupy up to 12% of the entire and even 25% of the eastern Laptev Sea. The predominance of polynyas in the central and eastern part is also confirmed by the mean cumulative area of open-water area. Most polynyas that develop at the end of April or May exist until the adjacent fast-ice cover has retreated.
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Table 2 Mean characteristics of polynya events (frequency and duration, mean and cumulative open-water area) in the winter and spring seasons (November to June) from 1979/1980 to 2001/2002 Laptev Sea polynyas Mean Mean Mean Mean
frequency [days] duration [days] area [103 km2] cumulative area [103 km2]
WNS
AL
T
NET
ESZ
13 (23, 8) 14 (128, 2) 4 (73, 0) 1713
11 (16, 3) 22 (134, 2) 3 (49, 0) 1152
13 (19, 5) 13 (110, 2) 0.8 (17, 0) 211
12 (18, 7) 16 (147, 2) 2 (30, 0) 616
13 (21, 7) 16 (98, 2) 2 (17, 0) 506
Values in parentheses indicate the absolute maximum and minimum.
annual variability. The variability of the 24 seasonal cycles is visualized in Hovmoeller diagrams (Fig. 8). Interannually, the summer minima ice cover exhibit greater variability from year to year than the winter maxima. Noticeable are the years 1979, 1984, 1992 and 1996, when ice retreat started late and vast parts of the Laptev Sea remained ice-covered. In 1990, 1991, 1995 and 1999 nearly the entire Laptev Sea was ice-free. The record minimum and maximum in summer sea-ice coverage occurred in the two successive years of 1995 and 1996. Sea-ice data in the Laptev Sea shows a large amplitude in minimum summer sea-ice cover with an oscillatory behavior. During the 24 years of satellite record periods with increased and decreased summer ice cover are evident. Before conducting the time-series analysis of monthly mean sea-ice areas in each study region the seasonal cycle was removed by subtracting the longterm average of each month. Trends for yearly and monthly averaged ice areas are calculated by using a time-series regression model (ordinary linear least squares) through the data for the period, 1979 to 2002. For each trend the non-parametric Mann–Kendall test
Off the mouths of rivers discharging into the Laptev Sea the presumable dynamic and thermal impact of river water on fast-ice retreat is clearly evident in satellite images by the forming of coastal polynyas (Fig. 5). NOAA-AVHRR data displaying clear sky or low cloud fraction were the primary source to gain information on the dates and areas of river flooding or coastal polynya formation. On average, overflows of the nearshore fast ice start in the beginning of June, and its standard deviation is 4 to 6 days. Dates of flooding of nearshore fast ice by river water are presented in Table 3. The overflows on the ice show low spatial variability at the beginning of the ablation period. Depending on the volume of river discharge, the flooding extends 10 km to 25 km from the coast. Roughly 4 weeks after the flooding coastal polynyas develop. Break-up activity, beginning in July, consists of the seaward extension of the coastal polynya until the remaining fast ice is completely removed. 3.3. Interannual variability and trends The areal extent of sea-ice in the Laptev Sea and in each of its individual regions shows a large inter-
Table 3 Mean start of nearshore fast-ice flooding in the vicinity of river mouths in the Laptev Sea as derived from NOAA AVHRR images Start of fast-ice flooding by river water Anabar Olenek Lena (Olenekskaya) Lena (Tumatskaya) Lena (Trofimovskaya) Lena (Bykovskaya) Yana
Mean (a)
S.D. (a)
Mean (b)
S.D. (b)
Abs. min. (a)
Abs. max. (a)
166 157 154 160 152 159 153
6.6 6.0 4.8 4.1 5.1 4.9 6.2
165 156 154 160 153 159 152
6.9 6.4 4.6 3.9 5.0 4.5 5.6
153 146 148 153 143 150 139
176 171 167 170 166 170 166
(15.6) (06.6) (03.6) (09.6) (01.6) (08.6) (02.6)
(14.6) (05.6) (03.6) (09.6) (02.6) (08.6) (01.6)
(1993) (1990) (1990) (1990) (1990) (1990) (1990)
(1986) (1987) (1987) (1987) (1987) (1987) (1987)
Long-term means, their standard deviations (S.D.) and extreme values refer to the period 1979 through 1994 (a) and 1979 through 1999 (b), respectively.
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Fig. 8. Hovmoeller diagrams (time/time) of daily total sea-ice concentrations [%] in the entire (upper left), western (upper right), eastern (lower left) and southeastern (lower right) Laptev Sea from May through October in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I).
was performed to detect monotonic trends in the timeseries data at the 95% confidence level for the trend slope in order to assess the statistical significance of the trend. Time series of sea-ice extent and area show downward trends in the Laptev Sea and its individual regions over the 24-year period. The overall trend for
the entire Laptev Sea indicate a decrease in ice extent and area by 970 km2 year 1 and 1100 km2 year 1, respectively. For all regional sectors time series of anomalies in monthly sea-ice area, including the linear least squares fit and the 95% confidence intervals are plotted in Fig. 9. Qualitatively, our results correspond well with earlier findings of negative trends in the
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Siberian Arctic (Maslanik et al., 1996; Parkinson et al., 1999; Go¨rgen et al., 2001). The magnitude of the negative trends are more moderate than the slopes obtained by Maslanik et al. (1996), who used a larger study area and a shorter time series for the period 1979 to 1995, not including the extreme summer maximum year of 1996, and hence suggesting an accelerated decline. Time series of the date of the minimum sea-ice cover in the Laptev Sea shows a
Fig. 9. Time series of monthly anomalies of the sea-ice and fast-ice (lower panel) area [103 km2] in the entire, western, eastern and southeastern Laptev Sea in the period from 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I). Also shown is the trend line of linear least squares fit through the data and the 95% confidence interval (dotted line).
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large interannual variability and a weak negative trend towards an earlier summer minimum (data not shown). As sea-ice extent includes open-water as well, it is ambiguous to explain whether the decline in ice extent is caused by either open-water or sea-ice area. Therefore, the trend analysis is conducted with the latter. The slopes of the linear least square trend lines and the 95% confidence intervals are summarized in Table 4. The decreases in sea-ice extent and area for the entire Laptev Sea on a yearly average basis reveal 1.5% decade 1 and 1.7% decade 1, respectively. The overall downward yearly trends are strongly driven by summer and early fall anomalies. By analyzing monthly trends, we can show that the seaice area decreased in August by 5.5% decade 1 or more than 4.5% decade 1 in September and October (Table 4). Regionally, the western Laptev Sea exhibits largest negative trends at 6.9% decade 1 in August and the eastern Laptev Sea at 5.0% decade 1 in October. In the southeastern Laptev Sea the decrease in fast-ice area are more pronounced in July ( 6.4% decade 1) and October ( 4.6% decade 1). It has to be noted that due to the large variance of summer sea-ice data all trends assessed except the trend in May in the southeastern Laptev Sea are not significant at 95% confidence level. Considering trend analyses of yearly and monthly sea-ice data in the entire Laptev Sea (data not shown), it is evident that the decrease of ice-extent is weaker over the 24-year period compared to the decrease of ice-area. The diverting linear trends indicate an increase of open-water area on a yearly basis due to polynya activity and being strongest during early summer (May to July). In August and September however, no trends in open water area are found. Strong increasing trends in open-water area have also been detected in all sub-regions in October. The detected positive trends of open-water area indicate an increase in the length of the summer open-water season. To evaluate the interannual variability of polynya activity in the Laptev Sea, mean open-water areas of single polynya events in each polynya sub-region during winter (November to June) have been analyzed. These data are presented in Fig. 10 (left panel) for the WNS and AL polynyas as they are the largest
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Table 4 Slopes of the trend lines (SLT) of linear least squares fit through sea-ice area data (yearly and single months) and the 95% confidence interval [103 km2 year 1] in the entire, western, eastern and southeastern Laptev Sea in the period 1979 to 2002 as derived from passive-microwave data (SMMR, SSM/I) Entire Laptev Sea Year May Jun Jul Aug Sep Oct
Western Laptev Sea
Eastern Laptev Sea
Southeastern Laptev Sea
SLT
S
CD
SLT
S
CD
SLT
S
CD
SLT
S
CD
1.1 F1.4 0.7 F 0.1 1.6 F 2.3 2.3 F 3.3 3.6 F 4.1 3.1 F 4.8 2.9 F 3.9
91 80 79 72 82 77 77
1.7 1.1 2.4 3.6 5.5 4.7 4.5
0.6 F 0.8 0.5 F 0.6 0.9 F 1.4 1.2 F 1.8 2.4 F 2.5 1.8 F 2.9 1.4 F 1.8
82 88 79 75 74 63 77
1.8 1.3 2.6 3.4 6.9 5.1 4.1
0.5 F 0.8 0.3 F 0.5 0.6 F 1.2 1.1 F1.8 1.2 F 2.2 1.3 F 2.3 1.5 F 2.1
77 74 68 77 65 84 72
1.6 0.9 2.2 3.8 4.0 4.2 5.0
0.14 F 0.22 0.07 F 0.10 0.06 F 0.34 0.68 F 0.61 0.39 F 0.65 0.02 F 0.54 0.49 F 0.77
85 97 60 92 0 86 70
1.3 0.7 0.5 6.4 3.7 0.2 4.6
Also presented is the statistical significance (S) of the trend and the change of sea-ice area (CD) [% decade
openings with the strongest local impact in the Laptev Sea during winter. Although leads and polynyas occur in each time of the winter, open-water areas peak in the end of winter or spring. Large polynya events of the prominent openings in the central and eastern Laptev Sea are present in most late winter/spring seasons. The open water areas are remarkably high in the 1990s. However, in mid-May of 1982, 1984, 1987, 1992 and 1996 large polynya openings were
1
].
absent. In the western and northwestern Laptev Sea (T, NET, ESZ) the activity of polynyas was anomalously low in May during the period from 1979 to 1988. Instead, most polynyas in this region start to form in June or even later. Exceptionally in 1984, when most of the Laptev Sea was still covered with ice by July, the NET and ESZ polynyas were existent. Mean open-water areas of the largest WNS and AL Polynya events in late winter or spring (January to
Fig. 10. Time series of open-water area within the ice pack [103 km2] as an indicator of polynya activity of the Western New Siberian (WNS) and Anabar Lena (AL) polynyas from 1979 to 2002. The interannual variability of all polynya events during winter (November to June) are shown in the left panel. The number of bars indicates the variable frequency of polynya events. The right panel represents mean (gray bars) and maximum (white bars) open-water areas of the largest polynya event during late winter and spring (January to June) per year. The black stars mark the date of polynya openings [day of year].
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June) range from 4 103 km2 to 37 103 km2 and from 12 103 km2 to 23 103 km2 (Fig. 10, right panel). As the WNS and AL Polynyas are often connected to each other, they form a large ice-free area during spring. The years in the order of maximum polynya size 1995, 1993, and 2000 represent the years with the largest positive anomalies of mean open-water area in the WNS and AL Polynya boxes. The average of maximum open-water areas of the largest polynya events during winter and spring is calculated to be 48.5 103 km2 (WNS) and 30 103 km2 (AL). Five years, 2000, 1988, 1993, 1995, and 1997, exhibit open-water areas in the central and eastern Laptev Sea greater than 100 103 km2, covering an area between 15% and 20% of the entire Laptev Sea. From 1979 to 2002 all Laptev Sea polynyas show an increase in the frequency of polynya events during the entire winter (November to June), being strongest in the ESZ and AL Polynyas. In contrast, the WNS Polynya shows a decrease in the number of single polynya events during this time span. All polynyas exhibit a decrease in the duration of polynya events. On average, the duration of polynya events in the central and eastern Laptev Sea was 21 days in the mid-1980s and only 13 days in the early 1990s, whereas in the western Laptev Sea no significant changes occurred. Although polynya events appear to be shortened, all polynyas with the exception of the AL Polynya reveal an increase in mean open-water area during the winter months (November to June) over the 24-year period.
4. Discussion The most dominant sea-ice feature in the Laptev Sea is the substantial interannual variability and oscillatory behavior of the summer ice cover, as illustrated in Figs. 7 and 8. There is a variety of possible conclusions from where these observed yearto-year changes and trends in summer sea-ice conditions likely result. Changes in sea-ice decay and summer ice coverage may be associated with changes in large-scale atmospheric circulation regimes, synoptic activity, associated warm air advection and the impact of continental freshwater input. The aim of this section is to provide an overview of the current state of knowledge about dynamic and thermodynamic forc-
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ings of the atmosphere, the ocean and river water, which are likely to affect sea-ice variability in the Laptev Sea. 4.1. Linkages to atmospheric forcings The Arctic climate exhibits a marked increase of surface air temperature during the last three decades from 1970 to the present. Multidecadal time series of model results and observations show a decrease in Arctic sea-level pressure (SLP) and an increase in cyclonic vorticity of winds in the late 1980s and early 1990s (Walsh et al., 1996; Rigor et al., 2002). Concurrent with the changes in SLP fields is an increase of the frequency of cyclones penetrating into the Eurasian Arctic as documented by Serreze et al. (1993). The following discussions treat large- and synoptic-scale interactions between the atmosphere and sea ice separately. At longer time scales (weeks to months) sea-ice variability in the Arctic and its marginal seas is mainly controlled by changes in the large-scale atmospheric circulation (Proshutinsky and Johnson, 1997; Mysak and Venegas, 1998; Polyakov et al., 1999; Deser et al., 2000). There are a number of terms, such as the Arctic Oscillation (Thompson and Wallace, 1998), Arctic Ocean Oscillation (Proshutinsky and Johnson, 1997) and Low Frequency Oscillation (Polyakov and Johnson, 2000), which describe the decadal and multidecadal variability of atmospheric and oceanic circulation patterns in the Northern Hemisphere and the Arctic. These authors suggest that the Arctic atmosphere alternates between two regimes of a weakened or strengthened anticyclonic circulation (Beaufort Gyre) and an intensified or suppressed cyclonic circulation in the eastern Arctic. Much of these changes can be linked to the Arctic Oscillation (AO). The changes between the atmospheric circulation regimes are in general associated with variations in mean sea-ice drift patterns and an eastward shift of the Transpolar Drift System. In this context, Proshutinsky and Johnson (1997) define the two arctic-wide observed wind-driven oceanic circulation patterns as the anticyclonic and cyclonic circulation regime (ACCR, CCR), each of which is persisting from 5 to 7 years. During these regimes the atmospheric circulation forces a convergent or divergent ice motion (ACCR/low AO-index or CCR/high
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AO-index) with thicker or thinner sea-ice (Walsh et al., 1996). At the same time decreases or increases in atmospheric vorticity cause higher or lower sea-ice coverage (Polyakov et al., 1999). According to Deser et al. (2000), summer sea-ice conditions in the Laptev Sea appear to be initiated by atmospheric circulation anomalies in the high Arctic in late spring. They suggest that the positive icealbedo feedback processes account for the long delay of atmospheric forcing and maximum ice response. This mechanism is generally believed to be a key factor in amplifying sea-ice variations. Rigor et al. (2002) note as well that the ice situation in summer and fall is preconditioned by the winter conditions. They suggest that during high-index periods of the Arctic Oscillation in winter atmospheric processes enhance the thinning of sea ice, the decrease of ice area and extent, and the delay of freezing in fall in the Laptev Sea. These changes may occur due to the formation of a cyclonic sea-ice motion pattern in the Arctic Basin promoting ice divergence in the Eurasian Arctic (i.e. an enhanced northward ice-drift). The interannual variability of sea-ice circulation in the Laptev Sea and ice exchange with the Arctic Ocean in the period 1979 to 1995 have been studied in detail by Alexandrov et al. (2000). In winter an extensive ice exchange, predominantly ice export, with the Arctic Ocean through the northern and northeastern boundaries exists. Alexandrov et al. (2000) calculate from remote sensing data and numerical modeling that in winter the total areal ice export into the Arctic Ocean accounts for roughly 500 103 km2 on average (1979–1995), ranging from about 250 103 km2 (1984/1985) to 750 103 km2 (1988/1989). Unlike the winter conditions, during summer the exchange of sea ice between the Laptev Sea and the Arctic Ocean is occasionally opposite in sign and can experience large interannual fluctuations. The average summer sea-ice import and export amounts to 40 103 km2 and 70 103 km2, respectively. In three quarters of investigated summers seaice import from the Arctic Ocean to the Laptev Sea was predominant except for those of 1982, 1985, 1987, 1991, and 1995 (Alexandrov et al., 2000). According to Proshutinsky and Johnson (1997), the Transpolar Drift System is located north of the Laptev Sea. Hence, during ACCR years the average winter ice export through the northern boundary was higher
and the summer ice import was lower than the ice exchange during CCR years. In contrast, during CCR years when the Transpolar Drift is shifted east towards the North American Arctic, most of the sea ice was exported from the Laptev Sea to the East Siberian Sea both in winter and in summer. By considering winter and summer ice-exchange rates, Alexandrov et al. (2000) found a large increase of total annual ice export for the period from 1990 to 1995 as compared to preceding years. The total ice export during the winters of 1989/1990, 1992/1993, 1994/1995 and the subsequent summers was above the average. The authors conclude in terms of preconditioning that the enhanced northward advection of ice associated with changes in the sea-ice circulation in the Laptev Sea during spring and summer explains, at least in part, negative sea-ice anomalies in subsequent summers. Besides these large-scale hemispheric processes described above, regional or synoptic-scale processes such as cyclone activity have profound effects on Arctic warming in winter and on sea-ice variability in spring. Sea-ice anomalies in relatively small areas and on time-scales of several days to some weeks seem to be strongly coupled with cyclones. Numerous authors (e.g. Serreze et al., 1993; Serreze, 1995; Proshutinsky and Johnson, 1997; Polyakov et al., 1999; Deser et al., 2000) make shifts in the atmospheric circulation regimes (ACCR/low AO-index or CCR/high AOindex) and associated variations in cyclone frequency responsible for the changes in sea-ice coverage along the Siberian coast in the 1990s. Serreze et al. (1993) and Serreze (1995) document links between the frequency of summer cyclones that are formed along the Arctic front over northern Eurasia and low ice concentrations in the Laptev Sea. Maslanik et al. (1996) show that ice-extent anomalies in the 1990s (e.g. 1990, 1993, 1995) are linked to increases in cyclone activity. Maslanik et al. (2000) and Rinke et al. (2003) used regional coupled atmosphere–ice–ocean models (ARCSyM, HIRHAMMOM) and observational data to explain the causes of the large sea-ice anomaly of 1990 in the Siberian Arctic. Based on detailed case studies, they suggest that the observed negative sea-ice anomalies occurred due to unusual patterns of ice advection and a coupling and a positive feedback between sea-ice dynamics and thermodynamics. As confirmed by Serreze et al. (2003), extreme negative sea-ice
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anomalies as in 2002 in the Laptev Sea seem to be linked with invasions of anomalous warm southerly air masses in spring, advecting sea ice northward from the Siberian coast while simultaneously enhancing ice melt. During the following summer persistent low sealevel pressure and above the normal near surface air temperatures over the Arctic Ocean further promote ice divergence, early break-up, rapid melt and subsequent reductions in surface albedo (Serreze et al., 2003). For example, as described by Haas and Eicken (2001) the advection of warm air from central Siberia can be considered to contribute significantly to the observed minimum in Laptev Sea ice extent during 1995. It has to be noted, that it is difficult to separate thermodynamic effects (ice melt) from dynamic components (ice drift) in explaining ice-extent anomalies (Maslanik et al., 1996; Bareiss et al., 1999). Though substantial progress has been made on the basis of numerical climate modeling and observations since the late 1990s, the understanding of atmospheric forcing mechanisms affecting summer sea-ice anomalies remain elusive. There are a number of apparent discrepancies in all theories that try to explain the response of the Laptev Sea ice cover during summer to recurrent modes of the Arctic atmospheric and oceanic behavior. An outstanding matter not resolved yet is why the wintertime AO index is in numerous years in coherence with summer sea-ice anomalies in the Siberian Arctic and in some years no correlation is evident. Deser et al. (2000) and Rigor et al. (2002) propose that large-scale atmospheric circulation patterns like the wintertime Arctic or North Atlantic Oscillation are linked to changes in the summer seaice coverage of the Siberian Arctic. Thompson and Wallace (1998) point out, that the wintertime AO pattern accounts for only 22% of the variance of the SLP field in the Northern Hemisphere. The interannual variability of the winter AO index (JFM) and the standardized anomalies of summer sea-ice area (JJAS) in the entire Laptev Sea are presented for the period from 1979 to 2002 in Fig. 11. The late 1980s and early 1990s experienced a high-index AO phase. In recent years it is varying from a weakly positive to a weakly negative index. The period also includes one of the largest year-to-year changes of record as the long positive period was interrupted by the very low AO-index in winter 1996. The wintertime AO-index
45
is weakly correlated with the summer sea-ice anomalies in the Laptev Sea. The Pearson correlation coefficient of both time series is calculated to 0.28 with a significance of 83% and removal of the linear trends. Serreze et al. (2003) is skeptical about the linkage between the AO and summer sea-ice anomalies along the Siberian coast as argued by Rigor et al. (2002). Serreze et al. (2003) suggest that the summer cyclone regime (Arctic low) and consequently low sea-ice concentrations are not linked to the AO and keys to the circulation variability should be sought elsewhere. For instance, Serreze et al. (2001) show that the summer cyclone regime in the Arctic Ocean is in part maintained by cyclogenesis along northeastern Eurasia in association with the Arctic frontal zone. The negative trends and interannual variability of sea-ice area in May and June reflect changes in the in onset date of snowmelt (see discussion of early-melt signal), which are caused by low-frequency atmospheric circulations, according to Drobot and Anderson (2001). They show that variations in the AO explain a significant amount of the variation in mean annual snowmelt-onset dates. During high-AO-index years increased cyclone activity favors enhanced advection of warm air masses. In contrast, low-AO-index periods with an anticyclonic atmospheric circulation cause low cyclone activity delaying the onset of snowmelt. The alternating regimes of cyclonic and anticyclonic wind-driven circulation in the Arctic Basin (CCR, ACCR) as described by Proshutinsky and Johnson (1997) seem to have numerous effects on climate and sea ice in the Laptev Sea. Winds may be responsible for substantial changes in ice conditions.
Fig. 11. Time series of winter AO-index (JFM) vs. standardized anomalies of summer sea-ice area (JJAS, dotted) in the Laptev Sea from 1979 to 2002.
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For example, mean values of polynya and cyclone characteristics as well as ice retreat during ACCR (1984 to 1988) and CCR (1989 to 1997) periods reveal significant differences. During CCR years the mean frequency of polynyas, the mean area of polynyas per winter, and the area of maximum polynya events in spring are higher than during ACCR years, but the duration of single polynya events is reduced by several days on average. For example, the mean area of the WNS polynya during the ACCR period from 1984 to 1988 accounts for roughly 16 103 km2 and during the CCR period from 1989 to 1997 about 22 103 km2. The strongest changes of polynya activity occur in the western Laptev Sea during anticyclonic and cyclonic circulation regimes. The mean frequency of cyclones entering the Laptev Sea region in July is increased by 5 events and the mean central pressure during CCR years is reduced as compared to ACCR years. The average minimum sea-ice cover during the anticyclonic circulation regime is on day 256, whereas the average minimum during the predominance of the cyclonic circulation regime occurs on day 249. The
circulation regimes seem to affect the freeze-up dates as well, causing ice formation during the cyclonic regime at a later day. As documented in Alexandrov et al. (2000), the magnitude and direction of ice exchange in the Laptev Sea agree with the large-scale drift pattern in the Arctic Ocean during ACCR and CCR years. Though a large fraction of the interannual variability of sea-ice exchange can be explained by the shift of large-scale atmospheric circulation patterns in the Arctic, in some years a correlation is not evident. For example in 1990, when ice export was low during winter and ice was imported during summer, the ice extent in the Laptev Sea was anomalously low. Of similar ambiguity are the sea-ice conditions during 1995 (anomalously low) and 1996 (anomalously high). Observed monthly mean sea-ice coverage and sea-ice motion derived from satellite data (Fowler, 2003) and monthly mean SLP and 10 m wind field as simulated by the regional climate model HIRHAM4 (Dethloff et al., 1996) for August 1995 and 1996 are shown in Fig. 12. Both record minimum and maximum ice extents occurred in a period of
Fig. 12. Monthly mean SLP [hPa] and 10 m wind field [m s 1] (gray) simulated by the HIRHAM4 model, observed monthly mean sea-ice coverage [%] and sea-ice motion [cm s 1] (black) derived from satellite data for August 1995 and 1996. Every 5th motion vector is drawn. The gray box marks the Laptev Sea region. Projection: HIRHAM4 model grid (110 100).
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prevailing cyclonic circulation in the Arctic Ocean. During August 1995 the ice edge rapidly retreated toward the north, with almost the entire Laptev Sea ice-free. In contrast, in 1996 almost the entire Laptev Sea including the central and eastern parts remained ice-covered. This comparison shows that in spite of the existence of large-scale circulation regimes the local wind field that prevails during a certain period contributes most to the sea-ice anomaly (Deser et al., 2000; Maslanik et al., 2000). Haas and Eicken (2001) report that in 1995 southerly winds helped to compact and push the summer ice edge toward the North and in 1996 northerly winds resulted in a southward displacement of the ice edge. Numerous past studies have documented links between summer cyclone activity and sea-ice anomalies (e.g. Maslanik and Barry, 1989). Maslanik et al. (1996) reports that the increase of cyclone events in northern Siberia since 1989 coincides with the negative sea-ice anomalies in the Laptev Sea during the early 1990s. This favors stronger and more frequent warm, southerly winds affecting snowmelt, surface albedo and sea-ice drift. Similar to the seasonal cycle of sea ice, cyclone events in the Laptev Sea show a minimum during
47
winter and a sharp increase in May with maximum frequency, lowest center pressures of cyclones occurring in summer. Time series of monthly cyclone counts and anomalies for the Laptev Sea region are presented in Fig. 13. The cyclone activity is derived from surface pressure fields at 6-h intervals with a similar detection and tracking method as proposed by Serreze et al. (1993). Mean monthly cyclone activity has increased in the period 1989 to 1995, with associated reductions in mean central pressure. At the same time ice reductions in the Laptev Sea occurred. Cyclone frequency in July 1996 accounted for 9 events as compared to 1995 when 20 cyclone events in the Laptev Sea were apparent. From July on the sea-ice cover becomes vulnerable to cyclone activity and wind stress cause mechanical ice break-up of weakened ice zones. Mechanical deterioration is favored by the microstructure of sea ice, because internal melting processes lead to increased porosity and decreased compactness (Zubov, 1963). It has to be noted, that it still is not known whether a reduced ice coverage provide a significant energy source (release of latent heat) for maintaining cyclone intensity (Maslanik and Barry, 1989).
Fig. 13. Time series of the frequency of registered cyclone events per month (upper panel) and corresponding anomalies from long-term monthly means (lower panel) in the Laptev Sea region from 1979 to 2002. A low-pass filtered (6 elements) time series is added. Only low pressure events of cyclones with a life-time of more than 1 day are considered. White/gray horizontal bars mark anticyclonic and cyclonic circulation regimes.
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Cyclone activity in the Laptev Sea region during the summer months seems to cause a combination of dynamic and thermodynamic atmospheric processes such as sea-ice drift, enhanced absorption of shortwave radiation in polynyas and warm air advection from the Eurasian land masses. These factors imply a key role for existing sea-ice anomalies in the Laptev Sea. The findings are supported by Maslanik et al. (1996), Bareiss et al. (1999), Haas and Eicken (2001) as well as Serreze et al. (2003). 4.2. Linkages to oceanic forcing Although oceanic processes cannot be isolated from riverine and atmospheric processes or atmosphere/sea-ice interactions, the impact of the ocean on sea-ice variability will be treated separately. During high-index phases of the AO or CCR years, respectively, a delayed ice-ocean response leads to a shift of the Transpolar Drift System, the extent of Atlantic Water, and the freshwater distribution to the East. It is still under discussion, if the weakening or retreat of the cold halocline (Steele and Boyd, 1998) is accompanied by a decrease of sea-ice thickness in the Arctic Ocean (e.g. Johannessen et al., 1995; Zhang et al., 1998; Rothrock et al., 1999) due to an increased upward heat flux from the ocean to the ice cover. Atmospheric processes in combination with oceanic processes, such as salinification of the upper water masses, as well as solar heating of flaw polynyas and leads and their subsequent increase in area have significant impacts on sea-ice retreat in the Laptev Sea, predominantly in its northern parts. Observational and modeling results provide evidence that increased atmospheric cyclone activity in the 1990s resulted in a dramatic increase of the salinity in the Laptev Sea. The mechanisms that account for the salinity increase during CCR years are an eastward shift of Siberian river water and increased brine formation due to enhanced ice production in numerous flaw leads and polynyas in the Laptev Sea. Both freshwater redistribution and brine rejection from ice growth in numerous leads result in a strong salinification of the halocline over the Laptev Sea. These processes lead to the weakening of the vertical stratification. The thinning and reduction of the seaice cover is attributed to the retreat of the cold halocline layer and consequently increased vertical
heat fluxes from the salty and relatively warm Atlantic water towards the sea-ice cover. During the ACCR period the redistribution of Siberian river discharge and summer ice melt lead to a freshening of the surface waters and thus to an increase in ice thickness and sea-ice area in the Laptev Sea (Maslowski et al., 2000; Johnson and Polyakov, 2001). The formation of polynyas in the Laptev Sea have a strong impact on the summer ice retreat of both the pack-ice and the fast-ice cover. With the onset of spring, Laptev Sea flaw leads and polynyas are converted from centers of heat loss and ice production to centers of heat gain. The additional heat is used for the bottom and lateral melt of the ice cover. Zakharov (1966) has estimated that the heat gain by short-wave radiation in all flaw leads and polynyas of the Laptev Sea adds up to nearly 3.7 1016 kJ by the end of June. Based on observations from SMMR and SSM/I passive-microwave data, monthly mean areal extents of polynyas in the central Laptev Sea (AL, WNS) range from 20.2 103 km2 in May to 49.6 103 km2 in June and to 88.1 103 km2 in July. To illustrate the possible impact, the net atmospheric heat gain by short-wave radiation of the recurrent polynyas in the central Laptev Sea accounts for 9.8 1015 kJ by the end of May, 2.9 1016 kJ by the end of June, and 4.9 1016 kJ by the end of July. This total heat input by the end of July is hypothetically sufficient to melt about 145 103 km2 of 2-m-thick fast ice, roughly 22% of the total sea-ice cover in the Laptev Sea (Bareiss, 2003). In addition to the lateral and bottom ice melt, mechanical processes play an important role in the disintegration of the sea-ice cover (Zubov, 1963). With increasing fetch-lengths of the openwater areas, the combined thermal and mechanical deterioration (wind-induced and tidal waves) of the ice cover (both the drift and fast ice) proceeds. For example, this phenomena is evident in visible satellite images when large floes with sizes of up to 20 103 km2 break off the ice cover along the fast-ice edge (Bareiss, 2003). The investigation of the temporal and spatial variability of open-water areas from passive-microwave observations reveals that from 1988 on late winter/spring polynyas start to develop earlier than in the period from 1979 to 1987. In some years when no polynya existed in May (e.g. 1984, 1992, 1996), fastice retreat started later than on average. An early
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formation and a large extent of polynyas like in 1990, 1995 and 2000 leads to an early break-up of fast ice in the Laptev Sea. Our findings correspond well with results from Proshutinsky and Johnson (1997), which show the existence of two dominant atmospheric and oceanic circulation patterns. In the period 1984 to 1988 when the ACCR was predominating, polynya activity in the Laptev Sea was low due to ice convergence. The period 1989 to 1997, in contrast, was characterized by a CCR pattern, causing high polynya activity due to ice divergence. The mean frequency and the mean area of polynya events increased as compared to the ACCR period from 1984 to 1988. 4.3. Linkages to freshwater input The Siberian shelf and in particular the Laptev Sea is considered to be a key study area to investigate environmental processes of the Arctic land-shelf system (Forman and Johnson, 1998). Although the Laptev Sea has experienced most significant changes in summer ice coverage during the last two decades, little research has been carried out on the impact of continental river runoff on sea-ice retreat in the Siberian coastal regions. In one of the few studies on coastal fast ice, Bareiss et al. (1999) show that in the southeastern Laptev Sea the influence of Lena River water on ice retreat is clearly evident. With the arrival of snowmelt floods in late May large parts of the fast ice at the delta fronts become affected by river water. Satellite images show that the strongest impact of fast-ice flooding by river water is apparent in the northeastern region of the Lena Delta. With nearly 85% of the Lena River discharge, the eastern branches (e.g. Trofimovskaya channels) of the delta contribute to the largest fraction of freshwater from spring discharge to the Laptev Sea. The flooded fast-ice belt off the northeastern Lena Delta is roughly 25 km wide and 100 km long. Overflows of coastal ice at river mouths of the Yana, Olenek and branches of the Lena River at the western delta are much smaller. After several days, the flood waters drain through the melting nearshore ice cover leaving thin layers of sediments on the ice and open water in front of the channel mouths. The overflows cover the fast ice only for a few days. As spring progresses, most of the above-freezing river water is discharged beneath
49
the nearshore fast-ice for several weeks. The fast-ice further off the coastline, referred to as offshore fast ice in this study, is merely affected by river water at its lower surface causing basal melt. Enhanced melting processes in coastal regions receiving river discharge lead to the formation of coastal polynyas. From early July onward, the coastal polynyas provide additional energy to melt the adjacent fast ice. The role of fresh water in the stratification of the Arctic Ocean and the formation of sea ice has been discussed in detail by Aagaard and Carmack (1989). From results of coupled ice–ocean models Lemke (1987) and Weatherly and Walsh (1996) suggest that reductions in the fluvial fresh-water input lead to reductions of up to 10% in sea-ice thickness caused by a weakening and retreat of the halocline layer (Steele and Boyd, 1998). Observational and modeling results provide evidence that increased atmospheric cyclone activity in the 1990s resulted in a dramatic increase of the salinity in the Laptev Sea (Maslowski et al., 2000; Johnson and Polyakov, 2001). The mechanisms that account for the salinity increase are an eastward shift of Siberian river water and increased brine formation due to enhanced ice production in numerous flaw leads and polynyas in the Laptev Sea. The weakening of the vertical stratification of the halocline leads to a rise in released heat from the ocean to the ice cover, causing large-scale reduction of sea ice in the Arctic Ocean. These findings are supported with ice-thickness measurements carried out in the central Arctic Ocean which show reduction in ice thickness by roughly 20% during the period 1991 to 2001 (Haas et al., 2002). Since the early 1980s the effect of possible Soviet river diversions on sea ice in the Eurasian and Siberian Arctic has been investigated systematically. Treshnikov and Ivanov (1980) along with numerous other Russian scientists suggest that the reduced input of river water onto the shelf initializes inflow of cold arctic surface waters towards the shelf, causing a delay in summer sea-ice retreat. Contrariwise, an increase in the input of river water may cause a reinforced melting of sea ice. These assumptions were supported by Holt et al. (1984) and Cattle (1985). Manak and Mysak (1989) showed the existence of a positive lagged correlation between sea ice and discharge, with discharge leading by 12 months. Based on hydrometeorological observations, Dmitrenko et al. (1999)
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show that an increase in river discharge leads to a freshening of the surface waters in the Laptev Sea and hence, in the subsequent winter to an increase in the fast-ice area. In detailed studies of the impact of river discharge on sea ice, Bareiss et al. (1999) document that, in contrast to previous reports, the interannual variability in summer sea-ice coverage in the Laptev Sea is not controlled by the impact of river water. Instead, coastal fast ice in the vicinity of river mouths, predominantly in the southeastern Laptev Sea, is influenced considerably by river water. The use of the one-dimensional thermodynamic fast-ice model allows to study the influence of river discharge on the seasonal fast-ice retreat and, what is more important, to quantify the impact parameters on this process. Model runs were performed for each river mouth in the East Siberian Arctic for single years (1979 to 1994) on a daily basis (Bareiss, 2003). As an example, Fig. 14 represents model simulations of fastice thickness off the northeastern Lena and Yana deltas under nearshore and offshore conditions using long-term averages of daily forcing data. According to the fast-ice model, simulations indicate that the decay of flooded nearshore ice starts about 1 to 2 weeks earlier than the disintegration of offshore fast ice. Decay of offshore fast ice is characterized by a gradual decrease in ice thickness. Depending on the study area, areas of nearshore fast ice become ice free by the end of June, roughly 4 to 6 weeks earlier than the offshore fast ice, that melts completely by the end of July or beginning of August. Passive-microwave data clearly show the forming of open water offshore from river mouths and the slow decay of fast ice farther seaward. The control run was performed by using the fast-ice model without river heat. Without river discharge the ablation period of nearshore fast ice increases by several weeks, whereas the ablation period of offshore fast ice is delayed only by a few days. The much longer ablation period of fast ice under nearshore conditions is caused by modified parameter settings for the model start, for instance the start value of fast-ice thickness, and the absence of ocean heat (Bareiss, 2003). The relevance of river discharge on fast-ice retreat is assessed by comparing the net atmospheric heat flux with the heat flux from river water as derived from the fast-ice model. With the flooding of nearshore fast ice a drastic increase of the short-wave
Fig. 14. Simulated long-term average (1979 to 1994) of mean daily fast-ice thickness including snow cover under nearshore (gray lines) and offshore (black lines) conditions by the Lena at the Trofimovskaya channel (upper panel) and Yana (lower panel) rivers. The dashed lines indicate the experiments where no river heat is applied to the fast-ice cover. The atmospheric forcing is obtained from the daily re-analysis data of the ECMWF.
radiation balance occurs in June, enhancing fast-ice ablation. Changes in the short-wave radiation balance are primarily controlled by variations of surface conditions and cloud cover. The long-wave radiation balance, turbulent energy fluxes over fast ice and the conductive heat flux trough the ice play a minor role during the ablation period. The comparison of modeled heat fluxes in the southeastern Laptev Sea reveals that the net fluxes of atmospheric and riverine heat (at the upper and lower ice surface) contribute with 53% and 47%, respectively, to the melt of nearshore fast ice (Table 5). The large input of energy at the upper surface generates higher melt rates at the upper than at the lower ice surface. The relative contribution from absorbed short-wave radiation and river heat at the upper surface of flooded fast ice is about 70% to 30%. Hence, the rapid melting of
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nearshore fast ice is caused to a significant part due to a sharp decrease in surface albedo, greater solar heating of the floodwater and the sediment-covered ice surface after draining. For the melting of offshore fast ice 90% of the energy is derived from the atmosphere and only 10% from river water. Mean temperatures of river water rise steadily from about 2 8C to 3 8C in June to about 12 8C by the end of July (Nalimov, 1995). The long-term average of the total amount of energy supplied by rivers in June ranges between 7.05 1013 kJ (Yana River) and 1.33 1015 kJ (Lena River at Trofimovskaya channels), according to 5.6 km3 and 106 km3 of discharge, respectively. For instance, off the northeastern Lena Delta the heat content of river water is sufficient to melt on average roughly 2000 km2 of 2.2 m thick fast ice. Rivers that discharge into the southeastern Laptev Sea have the ability to melt about 3500 km2 of fast ice by the end of June. This area accounts for only 2.5% of the total fast-ice area in that region. In years with record discharge the heat input by river water is sufficient to melt about 4% of the total fast-ice area. The ice-free areas develop to coastal polynyas in July and gradually widen due to lateral melt. Trend analyses of sea-ice data indicate a decrease of fast-ice area in the southeastern Laptev Sea during May and July. These findings reflect the warming during early summer in central and northern Siberia (Bareiss et al., 1999), the advance of the snow-melt season in Siberia from June into late May (Yang et al., 2002) and the observed large increases in river water during May and June of all rivers discharging into the Laptev Sea (Bareiss et al., 1999; Bareiss, 2003). At the same time a negative trend of the onset of river ice break-up (Smith, 2000) and spring discharge (Lammers et al., 2001; Bareiss, 2003), based on hydro-
Table 5 Comparison of long-term means of the simulated energy input [%] from the atmosphere ( Q a) and river water ( Q r) into the nearshore and offshore fast ice off the eastern Lena Delta (Trofimovskaya channel) and the northeastern Yana Delta for the period from 1979 to 1994 Nearshore Offshore
Q a [%] Q r [%] Q a [%] Q r [%]
Lena Trof.-Ch.
Yana NE-Delta
49 51 84 16
57 43 98 2
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logical records, is evident. Consequently, fast ice is affected much stronger in the coastal regions, which receive river water. Fast-ice model experiments have been made for variations of the timing of the spring snowmelt floods at the Lena River. These results confirm that snowmelt floods occurring up to several weeks earlier strongly affect fast-ice decay.
5. Conclusions In this study the spatial and temporal variability of the sea-ice regime in the Laptev Sea has been examined. The SMMR and SSM/I passive-microwave data record of total sea-ice concentrations span a period of 24 years, from January 1979 through December 2002. The major findings of this survey are summarized as follows: (1) The ice regime of the Laptev Sea is characterized by a variety of features such as drift ice, fast ice, ice massifs, flaw and coastal polynyas. The large seasonal cycle of sea-ice area in the entire Laptev Sea varies from a summer minimum of about 190 103 km2 to a winter maximum of roughly 610 103 km2. Our results indicate a high interannual variability of summer seaice coverage. The minima of the daily mean summer ice areas have been shown to vary between 9.3 103 km2 (1995) and 339 103 km2 (1996). (2) The time series of ice area data suggest negative trends in all the areas of the Laptev Sea studied. However, the trend is statistically significant at the 95% level in only one of the regions. The 24 years of satellite derived ice observations reveal a decrease in sea-ice area by 5.5% decade 1 in August or more than 4.5% decade 1 in September and October. Regionally, the western Laptev Sea exhibits largest negative trends in August at 6.9% decade 1 and the eastern Laptev Sea at 5.0% decade 1 in October. In the southeastern Laptev Sea the decrease in fast-ice area are more pronounced in July ( 6.4% decade 1) and October ( 4.6% decade 1). In addition, an increase in polynya activity in late winter/early spring, a shift towards earlier snowmelt-onset, and an increase in open-water area during early fall, indicating an extension of the length of the summer melt period, has been observed. (3) None of the dynamic and thermodynamic factors alone can explain the large interannual
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variability and retreat of sea-ice coverage during summer and early fall as observed in the 1990s. Despite the preliminary understanding of driving processes, there is still a large degree of uncertainty about the role of each factor and coupled mechanisms. Fully coupled regional climate models accurately treating land, ocean, sea-ice and atmospheric processes and giving only a small number of external boundary conditions will provide valuable insight in these couplings and may help to understand sea-ice response to changes of forcing (Maslanik et al., 2000; Rinke et al., 2003). Our analysis support earlier research concluding that ice conditions in the study region are influenced by a combination of dynamic and thermodynamic factors operating over a variety of spatial and temporal scales between climate subsystems. No clear and direct link to large-scale atmospheric modes such as the AO is obvious. (4) In all regions of the southern Laptev Sea the impact of river water on fast-ice retreat is clearly evident. In fast-ice areas exposed to surface flooding coastal polynyas develop after 4 weeks on average, whereas adjacent fast ice melts after 8 weeks. According to our model results, the net fluxes of atmospheric and riverine heat contribute with 53% and 47%, respectively, to the melt of nearshore fast ice. This is to a significant part due to the sharp decrease in surface albedo and greater solar heating of the flooded or sediment-covered upper ice surface. For the melting of offshore fast ice 90% of the energy is derived from the atmosphere and only 10% from river water.
Acknowledgements
We very much appreciate the comments and suggestions of C. Haas from the Alfred-WegenerInstitute for Polar and Marine Science (Bremerhaven, Germany) and H. Eicken from the Geophysical Institute of the University of Alaska Fairbanks. SMMR and SSM/I passive-microwave and ice drift data were provided by the National Snow and Ice data Center, Boulder (CO, U.S.A.). NCEP/NCAR reanalysis data were obtained from the NOAA-CIRES Climate Diagnostics Center, Boulder (CO, U.S.A.) and ECMWF re-analysis data from the European
Centre for Medium-Range Weather Forecasts (Reading, U.K.). Computational resources and software were provided by the German High Performance Computing Centre for Climate- and Earth System Research (Hamburg, Germany). This study was partly financially supported by the German Research Foundation (DFG) under contract He 1929/3-1. Two anonymous reviewers provided valuable suggestions to improve the manuscript.
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