Regional Classes of Sea Ice Cover in the East Antarctic Pack Observed from Satellite and In Situ Data during a Winter Time Period

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.

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Review of "Snow depth on Arctic sea ice from historical in situ data."

10.5194/tc-2017-278-rc3 ◽

2018 ◽

Author(s):

Anonymous

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Arctic Sea Ice ◽

In Situ Data ◽

Arctic Sea

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Freeboard, snow depth and sea-ice roughness in East Antarctica from in situ and multiple satellite data

Annals of Glaciology ◽

10.3189/172756411795931570 ◽

2011 ◽

Vol 52 (57) ◽

pp. 242-248 ◽

Cited By ~ 32

Author(s):

Thorsten Markus ◽

Robert Massom ◽

Anthony Worby ◽

Victoria Lytle ◽

Nathan Kurtz ◽

...

Keyword(s):

Sea Ice ◽

Correlation Coefficient ◽

Satellite Data ◽

Snow Depth ◽

Large Scale ◽

Mean Difference ◽

Laser Altimeter ◽

In Situ Data ◽

Ice Roughness

AbstractIn October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km × 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50–500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. the results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

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GLOBAL CHANGES IN THE SEA ICE COVER AND ASSOCIATED SURFACE TEMPERATURE CHANGES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-469-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 469-479

Author(s):

Josefino C. Comiso

Keyword(s):

Global Warming ◽

Sea Ice ◽

Surface Temperature ◽

Ice Cover ◽

Rate Of Change ◽

The Arctic ◽

Global Changes ◽

Data Set ◽

Time Period ◽

The Antarctic

The trends in the sea ice cover in the two hemispheres have been observed to be asymmetric with the rate of change in the Arctic being negative at −3.8 % per decade while that of the Antarctic is positive at 1.7 % per decade. These observations are confirmed in this study through analyses of a more robust data set that has been enhanced for better consistency and updated for improved statistics. With reports of anthropogenic global warming such phenomenon appears physically counter intuitive but trend studies of surface temperature over the same time period show the occurrence of a similar asymmetry. Satellite surface temperature data show that while global warming is strong and dominant in the Arctic, it is relatively minor in the Antarctic with the trends in sea ice covered areas and surrounding ice free regions observed to be even negative. A strong correlation of ice extent with surface temperature is observed, especially during the growth season, and the observed trends in the sea ice cover are coherent with the trends in surface temperature. The trend of global averages of the ice cover is negative but modest and is consistent and compatible with the positive but modest trend in global surface temperature. A continuation of the trend would mean the disappearance of summer ice by the end of the century but modelling projections indicate that the summer ice could be salvaged if anthropogenic greenhouse gases in the atmosphere are kept constant at the current level.

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Impact of snow cover on CO<sub>2</sub> dynamics in Antarctic pack ice

The Cryosphere Discussions ◽

10.5194/tcd-8-3263-2014 ◽

2014 ◽

Vol 8 (3) ◽

pp. 3263-3295

Author(s):

N.-X. Geilfus ◽

J.-L. Tison ◽

S. F. Ackley ◽

S. Rysgaard ◽

L. A. Miller ◽

...

Keyword(s):

Sea Ice ◽

Snow Cover ◽

Dissolved Inorganic Carbon ◽

Ice Cover ◽

Snow Accumulation ◽

Total Alkalinity ◽

Partial Pressures ◽

Pack Ice ◽

Cold Events

Abstract. Temporal evolution of pCO2 profiles in sea ice in the Bellingshausen Sea, Antarctica, in October 2007 shows that the CO2 system in the ice was primarily controlled by physical and thermodynamic processes. During the survey, a succession of warming and cold events strongly influenced the physical, chemical and thermodynamic properties of the ice cover. Two sampling sites with contrasting characteristics of ice and snow thickness were sampled: one had little snow accumulation (from 8 to 25 cm) and larger temperature and salinity variations than the second site, where the snow cover was up to 38 cm thick and therefore better insulated the underlying sea ice. We confirm that each cooling/warming event was associated with an increase/decrease in the brine salinity, total alkalinity (TA), total dissolved inorganic carbon (TCO2), and in situ brine and bulk ice CO2 partial pressures (pCO2). Thicker snow covers muted these changes, suggesting that snow influences changes in the sea ice carbonate system through its impact on the temperature and salinity of the sea ice cover. During this survey, pCO2 was undersaturated with respect to the atmosphere both in situ, in the bulk ice (from 10 to 193 μatm), and in the brine (from 65 to 293 μatm), and the ice acted as a sink for atmospheric CO2 (up to 2.9 mmol m−2 d−1), despite the underlying supersaturated seawater (up to 462 μatm).

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Advances in altimetric snow depth estimates using bi-frequency SARAL/CryoSat-2 Ka/Ku measurements

10.5194/tc-2021-79 ◽

2021 ◽

Author(s):

Florent Garnier ◽

Sara Fleury ◽

Gilles Garric ◽

Jérôme Bouffard ◽

Michel Tsamados ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Ocean Modeling ◽

The Arctic ◽

Validation Data ◽

Band Frequency ◽

In Situ Data ◽

Wide Range ◽

Assimilation System

Abstract. Although snow depth on sea ice is a key parameter for Sea Ice Thickness (SIT), there currently does not exist reliable estimations. In Arctic, nearly all SIT products use a snow depth climatology (the Warren-99 modified climatology, W99m) constructed from in-situ data obtained prior to the first significant impacts of climate change. In Antarctica, the lack of information on snow depth remains a major obstacle in the development of reliable SIT products. In this study, we present the latest version of the Altimetric Snow Depth (ASD) product computed over both hemispheres from the difference of the radar penetration into the snow pack between the CryoSat-2 Ku-band and the SARAL Ka-band frequency radars. The ASD solution is compared against a wide range of snow depth products including model data (Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) or its equivalent in Antarctica the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), the MERCATOR model and NASA's Eulerian Snow On Sea Ice Model (NESOSIM, only in Arctic)), the Advanced Microwave Scanning Radiometer 2 (AMSR-2) passive radiometer data, and the Dual-altimeter Snow Thickness (DuST) Ka-Ku product (only in Arctic). It is validated in the Arctic against in-situ and airborne validation data. These comparisons demonstrate that ASD provide a consistent snow depth solution, with space and time patterns comparable with those of the alternative Ka-Ku DuST product, but with a mean bias of about 6.5 cm. We also demonstrate that ASD is consistent with the validation data. Comparisons with Operation Ice Bridge's (OIB) airborne snow radar in Arctic during the period of 2014–2018 show a correlation of 0.66 and a RMSE of about 6 cm. Furthermore, a first-guess monthly climatology has been constructed in Arctic from the ASD product, which shows a good agreement with OIB during 2009–2012. This climatology is shown to provide a better solution than the W99m climatology when compared with validation data. Finally, we have characterised the SIT uncertainty due to the snow depth from an ensemble of SIT solutions computed for the Arctic by using the different snow depth products previously used in the comparison with the ASD product. During the period of 2013–2019, we found a spatially averaged SIT mean standard deviation of 20 cm. Deviations between SIT estimations due to different snow depths can reach up to 77 cm. Using the ASD data instead of W99m to estimate SIT over this time period leads to a reduction of the average SIT of about 30 cm.

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Phytoplankton distribution in unusually low sea ice cover over the Pacific Arctic

Biogeosciences Discussions ◽

10.5194/bgd-9-2055-2012 ◽

2012 ◽

Vol 9 (2) ◽

pp. 2055-2093 ◽

Cited By ~ 7

Author(s):

P. Coupel ◽

H. Y. Jin ◽

M. Joo ◽

R. Horner ◽

H. A. Bouvet ◽

...

Keyword(s):

Sea Ice ◽

Arctic Basin ◽

Ice Cover ◽

The Arctic ◽

In Situ Data ◽

Phytoplankton Distribution ◽

The Pacific ◽

Phytoplankton Communities ◽

Ice Retreat ◽

The Impact

Abstract. A large part of the Pacific Arctic basin experiences ice-free conditions in summer as a result of sea ice cover steadily decreasing over the last decades. To evaluate the impact of ice retreat on the Arctic ecosystem, we investigated phytoplankton communities from coastal sites (Chukchi shelf) to northern deep basins (up to 86° N), during year 2008 of high melting. Pigment and taxonomy in situ data were acquired under different ice regime: the ice -free basins (IFB, 74°–77° N), the marginal ice zone (MIZ, 77°–80° N) and the heavy ice covered basins (HIB, >80° N). Our results suggest that extensive ice melting provided favorable conditions to chrysophytes and prymnesiophytes growth and more hinospitable to pico-sized prasinophytes and micro-sized dinoflagellates. Larger cell diatoms were less abundant in the IFB while dominant in the MIZ of the deep Canadian basin. Our data were compared to those obtained during more icy years, 1994 and to a lesser extent, 2002. Freshening, stratification, light and nutrient availability are discussed as possible causes for observed phytoplankton communities under high and low sea ice cover.

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Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer

The Cryosphere ◽

10.5194/tc-9-255-2015 ◽

2015 ◽

Vol 9 (1) ◽

pp. 255-268 ◽

Cited By ~ 13

Author(s):

D. V. Divine ◽

M. A. Granskog ◽

S. R. Hudson ◽

C. A. Pedersen ◽

T. I. Karlsen ◽

...

Keyword(s):

Sea Ice ◽

Open Water ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

First Year ◽

Surface Type ◽

Melt Pond ◽

Melt Ponds

Abstract. The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.

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