scholarly journals Satellite-derived sea-ice export and its impact on Arctic ice mass balance

2018 ◽  
Author(s):  
Robert Ricker ◽  
Fanny Girard-Ardhuin ◽  
Thomas Krumpen ◽  
Camille Lique
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
North Atlantic ◽  
Large Scale ◽  
The Arctic ◽  
Fram Strait ◽  
Ice Volume ◽  
Ice Drift ◽  
Ice Mass Balance ◽  
Arctic Ice

Abstract. Ice volume export drives variations of Arctic ice mass balance. It also represents a significant fresh water input to the North Atlantic, which could in turn modulate the intensity of the thermohaline circulation. We present the first estimates of winter sea ice volume export through the Fram Strait using CryoSat-2 sea ice thickness retrievals and three different drift products for the years 2010 to 2017. The export rates vary between −21 and −540 km3/month. We find that ice drift variability is the main driver of annual and interannual ice volume export variability, and that the interannual variations of the ice drift are driven by large scale variability of the atmospheric circulation captured by the Arctic Oscillation and North Atlantic Oscillation indices. On shorter timescale, however, the seasonal cycle is also driven by the mean thickness of exported sea ice, typically peaking in March. Considering Arctic winter multiyear ice volume changes, 54 % of the variability can be explained by the variations of ice volume export through the Fram Strait.

scholarly journals Satellite-derived sea ice export and its impact on Arctic ice mass balance

2018 ◽  
Vol 12 (9) ◽  
pp. 3017-3032 ◽  
Author(s):  
Robert Ricker ◽  
Fanny Girard-Ardhuin ◽  
Thomas Krumpen ◽  
Camille Lique
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
North Atlantic ◽  
Large Scale ◽  
The Arctic ◽  
Fram Strait ◽  
Ice Volume ◽  
Ice Drift ◽  
Ice Mass Balance ◽  
Arctic Ice

Abstract. Sea ice volume export through the Fram Strait represents an important freshwater input to the North Atlantic, which could in turn modulate the intensity of the thermohaline circulation. It also contributes significantly to variations in Arctic ice mass balance. We present the first estimates of winter sea ice volume export through the Fram Strait using CryoSat-2 sea ice thickness retrievals and three different ice drift products for the years 2010 to 2017. The monthly export varies between −21 and −540 km3. We find that ice drift variability is the main driver of annual and interannual ice volume export variability and that the interannual variations in the ice drift are driven by large-scale variability in the atmospheric circulation captured by the Arctic Oscillation and North Atlantic Oscillation indices. On shorter timescale, however, the seasonal cycle is also driven by the mean thickness of exported sea ice, typically peaking in March. Considering Arctic winter multi-year ice volume changes, 54  % of their variability can be explained by the variations in ice volume export through the Fram Strait.

scholarly journals Sea ice volume variability and water temperature in the Greenland Sea

2020 ◽  
Vol 14 (2) ◽  
pp. 477-495 ◽  
Author(s):  
Valeria Selyuzhenok ◽  
Igor Bashmachnikov ◽  
Robert Ricker ◽  
Anna Vesman ◽  
Leonid Bobylev
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Heat Content ◽  
The Arctic ◽  
Fram Strait ◽  
Greenland Sea ◽  
Nordic Seas ◽  
Ice Volume ◽  
Long Term Variations

Abstract. This study explores a link between the long-term variations in the integral sea ice volume (SIV) in the Greenland Sea and oceanic processes. Using the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS, 1979–2016), we show that the increasing sea ice volume flux through Fram Strait goes in parallel with a decrease in SIV in the Greenland Sea. The overall SIV loss in the Greenland Sea is 113 km3 per decade, while the total SIV import through Fram Strait increases by 115 km3 per decade. An analysis of the ocean temperature and the mixed-layer depth (MLD) over the climatic mean area of the winter marginal sea ice zone (MIZ) revealed a doubling of the amount of the upper-ocean heat content available for the sea ice melt from 1993 to 2016. This increase alone can explain the SIV loss in the Greenland Sea over the 24-year study period, even when accounting for the increasing SIV flux from the Arctic. The increase in the oceanic heat content is found to be linked to an increase in temperature of the Atlantic Water along the main currents of the Nordic Seas, following an increase in the oceanic heat flux from the subtropical North Atlantic. We argue that the predominantly positive winter North Atlantic Oscillation (NAO) index during the 4 most recent decades, together with an intensification of the deep convection in the Greenland Sea, is responsible for the intensification of the cyclonic circulation pattern in the Nordic Seas, which results in the observed long-term variations in the SIV.

scholarly journals Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes

2019 ◽  
Author(s):  
Alex West ◽  
Mat Collins ◽  
Ed Blockley
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
The North ◽  
Energy Evaluation ◽  
Ice Mass Balance ◽  
Arctic Ice

Abstract. Arctic sea ice has declined rapidly over recent decades. Models predict that the Arctic will be nearly ice-free by mid-century, but the spread in predictions of sea ice extent is currently large. The reasons for this spread are poorly understood, partly due to a lack of observations with which the processes by which Arctic atmospheric and oceanic forcing affect sea ice state can be examined. In this study, a method of estimating fluxes of top melt, top conduction, basal conduction and ocean heat flux from Arctic ice mass balance buoy elevation and temperature data is presented. The derived fluxes are used to evaluate modelled fluxes from the coupled climate model HadGEM2-ES in two densely sampled regions of the Arctic, the North Pole and Beaufort Sea. The evaluation shows the model to overestimate the magnitude of summer top melting fluxes, and winter conductive fluxes, results which are physically consistent with an independent sea ice and surface energy evaluation of the same model.

scholarly journals From points to Poles: extrapolating point measurements of sea-ice mass balance

2006 ◽  
Vol 44 ◽  
pp. 188-192 ◽  
Author(s):  
Don Perovich ◽  
Jacqueline A. Richter-Menge
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Large Scale ◽  
Heat Budget ◽  
Ice Cover ◽  
The Arctic ◽  
Bottom Surface ◽  
Ice Thickness ◽  
Ice Mass Balance ◽  
Remote Sensing Techniques

AbstractThe amount of ice growth and ablation are key measures of the thermodynamic state of the ice cover. While ice extent and even ice thickness can be determined using remote-sensing techniques, this is not the case for the mass balance. Mass-balance measurements require an ability to attribute the change, establishing whether a change in the thickness of the ice cover occurs at the top or bottom surface and whether it is a result of growth or ablation. We have developed and implemented a tool that can be used to measure thermodynamic changes in sea-ice mass balance at individual locations: the ice mass-balance buoy (IMB). The primary limitation of the IMB is that it provides a point measurement of the ice mass balance, defined by a particular combination of snow and ice conditions. Determining if, and how, such point measurements can be extrapolated is critical to understanding the large-scale mass balance of the sea-ice cover. We explore the potential for extrapolation using mass-balance observations from the Surface Heat Budget of the Arctic (SHEBA) field experiment. During SHEBA, mass-balance measurements were made at over 100 sites covering a 100 km2 area. Results indicate that individual point measurements can provide reasonable estimates for undeformed and unponded multi-year ice, which represented more than two-thirds of the ice cover at SHEBA and is the dominant ice type in the perennial pack. A key is carefully selecting a representative location for the instrument package. The contribution of these point measurements can be amplified by integrating them with other tools designed to measure ice thickness and assimilating these combined data into sea-ice models.

scholarly journals Satellite-based estimates of sea-ice volume flux through Fram Strait

2006 ◽  
Vol 44 ◽  
pp. 321-328 ◽  
Author(s):  
Gunnar Spreen ◽  
Stefan Kern ◽  
Detlef Stammer ◽  
Rene Forsberg ◽  
Jörg Haarpaintner
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Thickness Distribution ◽  
The Arctic ◽  
Ice Thickness ◽  
Fram Strait ◽  
Model Errors ◽  
Geoid Model ◽  
Ice Volume ◽  
Ice Drift

AbstractSea-ice volume fluxes through Fram Strait, Arctic Ocean, are estimated for the two Icesat measurement periods in February/March and October/November 2003 by combining Sea-ice area fluxes, determined from Space-borne microwave observations, with estimates of the Sea-ice thickness distribution, inferred from measurements of Icesat’s Geoscience Laser Altimeter System (GLAs) instrument. The thickness is derived from Icesat data by converting its Surface elevation measurements into an ice freeboard estimate. Combined with prior information about ice density and Snow depth and density, the freeboard is converted into ice thickness. Uncertainties in freeboard estimates due to geoid model errors are reduced through the use of the recent geoid from the Arctic Gravity Project. Missing information about the ocean circulation and ocean tides is approximated locally by interpolating the Sea Surface height linearly between open leads. Meridional ice volume fluxes estimated for 79˚N using ice drift observed by AMSR-E (QuiksCAT) amount to 168 km3 (236km3) and 62 km3 (77 km3) for 30 day periods in February/March and October/November 2003, respectively. These values lie in the range of previous results from Similar Studies, but are considerably Smaller than the average ice flux during the 1990s, most likely because of a Smaller ice-drift Speed during 2003.

Winter Arctic sea ice freeboard, snow depth and thickness variability from ICESat-2 and NESOSIM

2021 ◽  
Author(s):  
Alek Petty ◽  
Nicole Keeney ◽  
Alex Cabaj ◽  
Paul Kushner ◽  
Nathan Kurtz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Cloud ◽  
Ice Drift ◽  
Thickness Variability ◽  
Arctic Ice

<div> <div> <div> <div> <p>National Aeronautics and Space Administration's (NASA's) Ice, Cloud, and land Elevation Satellite‐ 2 (ICESat‐2) mission was launched in September 2018 and is now providing routine, very high‐resolution estimates of surface height/type (the ATL07 product) and freeboard (the ATL10 product) across the Arctic and Southern Oceans. In recent work we used snow depth and density estimates from the NASA Eulerian Snow on Sea Ice Model (NESOSIM) together with ATL10 freeboard data to estimate sea ice thickness across the entire Arctic Ocean. Here we provide an overview of updates made to both the underlying ATL10 freeboard product and the NESOSIM model, and the subsequent impacts on our estimates of sea ice thickness including updated comparisons to the original ICESat mission and ESA’s CryoSat-2. Finally we compare our Arctic ice thickness estimates from the 2018-2019 and 2019-2020 winters and discuss possible causes of these differences based on an analysis of atmospheric data (ERA5), ice drift (NSIDC) and ice type (OSI SAF).</p> </div> </div> </div> </div>

scholarly journals Impacts of large-scale atmospheric circulation changes due to winter sea-ice retreat on Black Carbon transport and deposition to the Arctic

2016 ◽  
Author(s):  
Luca Pozzoli ◽  
Srdan Dobricic ◽  
Simone Russo ◽  
Elisabetta Vignati
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
The Arctic ◽  
The North ◽  
Ice Retreat ◽  
The North Atlantic Oscillation ◽  
Sea Ice Retreat

Abstract. Winter warming and sea ice retreat observed in the Arctic in the last decades determine changes of large scale atmospheric circulation pattern that may impact as well the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a new statistical algorithm, based on the Maximum Likelihood Estimate approach, to determine how the changes of three large scale weather patterns (the North Atlantic Oscillation, the Scandinavian Blocking, and the El Nino-Southern Oscillation), associated with winter increasing temperatures and sea ice retreat in the Arctic, impact the transport of BC to the Arctic and its deposition. We found that the three atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the Eastern Arctic while they increase BC deposition in the Western Arctic. The increasing trend is mainly due to the more frequent occurrences of stable high pressure systems (atmospheric blocking) near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. The North Atlantic Oscillation has a smaller impact on BC deposition in the Arctic, but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The El Nino-Southern Oscillation does not influence significantly the transport and deposition of BC to the Arctic. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.

Winter Arctic sea ice bottom evolution detected by thermistor string-based ice mass balance buoys (SIMBA)

2020 ◽  
Author(s):  
Bin Cheng ◽  
Timo Vihma ◽  
Zeling Liao ◽  
Ruibo Lei ◽  
Mario Hoppmann ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Mass Balance ◽  
Arctic Sea Ice ◽  
Heating Element ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Ice Mass Balance ◽  
Snow And Ice

<p>A thermistor-string-based Snow and Ice Mass Balance Array (SIMBA) has been developed in recent years and used for monitoring snow and ice mass balance in the Arctic Ocean. SIMBA measures vertical environment temperature (ET) profiles through the air-snow-sea ice-ocean column using a thermistor string (5 m long, sensor spacing 2cm). Each thermistor sensor equipped with a small identical heating element. A small voltage was applied to the heating element so that the heat energy liberated in the vicinity of each sensor is the same. The heating time intervals lasted 60 s and 120 s, respectively. The heating temperatures (HT) after these two intervals were recorded. The ET was measured 4 times a day and once per day for the HT.</p><p>A total 15 SIMBA buoys have been deployed in the Arctic Ocean during the Chinese National Arctic Research Expedition (CHINARE) 2018 and the Nansen and Amundsen Basins Observational System (NABOS) 2018 field expeditions in late autumn. We applied a recently developed SIMBA algorithm to retrieve snow and ice thickness using SIMBA ET and HT temperature data. We focus particularly on sea ice bottom evolution during Arctic winter.</p><p>In mid-September 2018, 5 SIMBA buoys were deployed in the East Siberian Sea (NABOS2018) where snow was in practical zero cm and ice thickness ranged between 1.8 m – 2.6 m. By the end of May, those SIMBA buoys were drifted in the central Arctic where snow and ice thicknesses were around 0.05m - 0.2m and 2.6m – 3.2m, respectively. For those 10 SIMBA buoys deployed by the CHINARE2018 in the Chukchi Sea and Canadian Basin, the initial snow and ice thickness were ranged between 0.05m – 0.1cm and 1.5m – 2.5m, respectively.  By the end of May, those SIMBA buoys were drifted toward the north of Greenland where snow and ice thicknesses were around 0.2m - 0.3m and 2.0m – 3.5m, respectively. The ice bottom evolution derived by SIMBA algorithm agrees well with SIMBA HT identified ice-ocean interfaces. We also perform a preliminary investigation of sea ice bottom evolution measured by several SIMBA buoys deployed during the MOSAiC leg1 field campaign in winter 2019/2020.  </p>

Sign in / Sign up

Export Citation Format

Share Document