scholarly journals The European Space Agency’s Earth Explorer Mission CryoSat: measuring variability in the cryosphere

2004 ◽  
Vol 39 ◽  
pp. 313-320 ◽  
Author(s):  
Mark R. Drinkwater ◽  
Richard Francis ◽  
Guy Ratier ◽  
Duncan J. Wingham

AbstractCryoSat is currently being prepared for a 2005 launch as the first European Space Agency Earth Explorer Opportunity mission. It is a dedicated cryospheric mission equipped with a Ku-band SIRAL (SAR/Interferometric Radar ALtimeter), whose primary objectives are to measure the variability and trends in the mass of the Arctic sea-ice cover and large terrestrial ice sheets. In this paper, an overview is provided of the mission and of the measurement characteristics of the new SIRAL instrument. Examples of data acquired on recent preparatory campaigns are presented, illustrating the operating characteristics of the key SIRAL modes. Preparatory plans for calibration and validation of CryoSat data are described.

2013 ◽  
Vol 7 (4) ◽  
pp. 1315-1324 ◽  
Author(s):  
M. Zygmuntowska ◽  
K. Khvorostovsky ◽  
V. Helm ◽  
S. Sandven

Abstract. Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat-2 was launched in 2010 carrying a Ku-band radar altimeter (SIRAL) designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300 m along track. In this study, airborne Ku-band radar altimeter data over different sea ice types have been analyzed. A set of parameters has been defined to characterize the differences in strength and width of the returned power waveforms. With a Bayesian-based method, it is possible to classify about 80% of the waveforms from three parameters: maximum of the returned power waveform, the trailing edge width and pulse peakiness. Furthermore, the maximum of the power waveform can be used to reduce the number of false detections of leads, compared to the widely used pulse peakiness parameter. For the pulse peakiness the false classification rate is 12.6% while for the power maximum it is reduced to 6.5%. The ability to distinguish between different ice types and leads allows us to improve the freeboard retrieval and the conversion from freeboard into sea ice thickness, where surface type dependent values for the sea ice density and snow load can be used.


2010 ◽  
Vol 4 (2) ◽  
pp. 641-661 ◽  
Author(s):  
V. Alexandrov ◽  
S. Sandven ◽  
J. Wahlin ◽  
O. M. Johannessen

Abstract. Retrieval of Arctic sea ice thickness from radar altimeter freeboard data, to be provided by CryoSat-2, requires observational data to verify the relation between the two variables. In this study in-situ ice and snow data from 689 observation sites obtained during the Sever expeditions in the 1980s have been used to establish an empirical relation between ice thickness and freeboard. Estimates of mean and variability of snow depth, snow density and ice density were produced based on many field observations, and have been used in the isostatic equilibrium equation to estimate ice thickness as a function of ice freeboard, snow depth and snow/ice density. The accuracy of the ice thickness retrieval has been calculated from the estimated variability in ice and snow parameters and error of ice freeboard measurements. It is found that uncertainties of ice density and freeboard are the major sources of error in ice thickness calculation. For FY ice, retrieval of ≈1.0 m (2.0 m) thickness has an uncertainty of 60% (41%). For MY ice the main uncertainty is ice density error, since the freeboard error is relatively smaller than for FY ice. Retrieval of 2.4 m (3.0 m) thick MY ice has an error of 24% (21%). The freeboard error is ±0.05 m for both the FY and MY ice. If the freeboard error can be reduced to 0.01 m by averaging a large number of measurements from CryoSat, the error in thickness retrieval is reduced to about 32% for a 1.0 m thick FY floe and to about 18% for a 2.3 m thick MY floe. The remaining error is dominated by uncertainty in ice density. Provision of improved ice density data is therefore important for accurate retrieval of ice thickness from CryoSat data.


2011 ◽  
Vol 52 (57) ◽  
pp. 197-205 ◽  
Author(s):  
Rosemary Willatt ◽  
Seymour Laxon ◽  
Katharine Giles ◽  
Robert Cullen ◽  
Christian Haas ◽  
...  

AbstractSatellite radar altimetry provides data to monitor winter Arctic sea-ice thickness variability on interannual, basin-wide scales. When using this technique an assumption is made that the peak of the radar return originates from the snow/ice interface. This has been shown to be true in the laboratory for cold, dry snow as is the case on Arctic sea ice during winter. However, this assumption has not been tested in the field. We use data from an airborne normal-incidence Ku-band radar altimeter and in situ field measurements, collected during the CryoSat Validation Experiment (CryoVEx) Bay of Bothnia, 2006 and 2008 field campaigns, to determine the dominant scattering surface for Arctic snow-covered sea ice. In 2006, when the snow temperatures were close to freezing, the dominant scattering surface in 25% of the radar returns appeared closer to the snow/ice interface than the air/snow interface. However, in 2008, when temperatures were lower, the dominant scattering surface appeared closer to the snow/ice interface than the air/snow interface in 80% of the returns.


2014 ◽  
Vol 8 (2) ◽  
pp. 1831-1871 ◽  
Author(s):  
R. Ricker ◽  
S. Hendricks ◽  
V. Helm ◽  
H. Skourup ◽  
M. Davidson

Abstract. Several studies have shown that there is considerable evidence that the Arctic sea-ice is thinning during the last decades. When combined with the observed rapid reduction of ice-covered area this leads to a decline in sea-ice volume. The only remote sensing technique capable of quantifying this ice volume decrease at global scale is satellite altimetry. In this context the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku-band SAR radar altimeter SIRAL, which we use to derive sea-ice freeboard defined as the height of the ice surface above the local sea level. In the context of quantifying Arctic ice-volume decrease at global scale, the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku-band SAR radar altimeter SIRAL, which we use to derive sea-ice freeboard defined as the height of the ice surface above the sea level. Accurate CryoSat-2 range measurements over open water and the ice surface in the order of centimeters are necessary to achieve the required accuracy of the freeboard to thickness conversion. Besides uncertainties of the actual sea-surface height and limited knowledge of ice and snow properties, the penetration of the radar signal into the snow cover and therefore the interpretation of radar echoes is crucial. This has consequences in the selection of retracker algorithms which are used to track the main scattering horizon and assign a range estimate to each CryoSat measurement. In this paper we apply a retracker algorithm with thresholds of 40%, 50% and 80% of the first maximum of radar echo power, spanning the range of values used in current literature. For the 40% threshold we assume that the main scattering horizon lies at a certain depth between the surface and snow-ice interface as verified through coincident CryoSat-2 and airborne laser altimetry measurements. This contrasts with the 50% and 80% thresholds where we assume the ice-snow interface as the main scattering horizon similar to other published studies. Using the selected retrackers we evaluate the uncertainties of trends in sea-ice freeboard and higher level products that arise from the choice of the retracker threshold only, independently from the uncertainties related to snow and ice properties. Our study shows that the choice of retracker thresholds does have a non-negligible impact on magnitude estimates of sea-ice freeboard, thickness and volume, but that the main trends in these parameters are less affected. Specifically we find declines of Arctic sea-ice volume of 9.7% (40% threshold), 10.9% (50% threshold) and 6.9% (80% threshold) between March 2011 and March 2013. In contrast to that we find increases in Arctic sea-ice volume of 27.88% (40% threshold), 25.71% (50% threshold) and 32.65% (80% threshold) between November 2011 and November 2013. Furthermore we obtain a significant increase of freeboard from March 2013 to November 2013 in the area for multi-seasonal sea-ice north of Greenland and the Canadian Archipelago. Since this is unlikely it gives rise to the assumption that applying different retracker thresholds depending on seasonal properties of the snow load is necessary in the future.


2021 ◽  
Vol 13 (8) ◽  
pp. 1414
Author(s):  
Shengkai Zhang ◽  
Yue Xuan ◽  
Jiaxing Li ◽  
Tong Geng ◽  
Xiao Li ◽  
...  

Arctic sea ice variations are sensitive to Arctic environmental changes and global changes. Freeboard and thickness are two important parameters in sea ice change research. Satellite altimetry can provide long-time and large-scale sea ice monitoring. We estimated the Arctic sea ice freeboard and its variations for the period from 2002 to 2012 from Envisat satellite altimetry data. To remove geoid undulations, we reprocessed the Envisat data using a newly developed mean sea surface (MSS) model, named DTU18. Residuals in the static geoid were removed by using the moving average technique. We then determined the local sea surface height and sea ice freeboard from the Envisat elevation profiles. We validated our freeboard estimates using two radar freeboard products from the European Space Agency (ESA) Climate Change Initiative (CCI) and the Alfred Wegener Institute (AWI), as well as the Operation IceBridge (OIB) sea ice freeboard product. The overall differences between our estimates and the CCI and AWI data were 0.11 ± 0.14 m and 0.12 ± 0.14 m, respectively. Our estimates show good agreement with the three products for areas of freeboard larger than 0.2 m and smaller than 0.3 m. For areas of freeboard larger than 0.3 m, our estimates correlate better with OIB freeboard than with CCI and AWI. The variations in the Arctic sea ice thickness are discussed. The ice freeboard reached its minimum in 2008 during the research period. Sharp decreases were found in the winters of 2005 and 2007.


2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.


2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.


2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mats Brockstedt Olsen Huserbråten ◽  
Elena Eriksen ◽  
Harald Gjøsæter ◽  
Frode Vikebø

Abstract The Arctic amplification of global warming is causing the Arctic-Atlantic ice edge to retreat at unprecedented rates. Here we show how variability and change in sea ice cover in the Barents Sea, the largest shelf sea of the Arctic, affect the population dynamics of a keystone species of the ice-associated food web, the polar cod (Boreogadus saida). The data-driven biophysical model of polar cod early life stages assembled here predicts a strong mechanistic link between survival and variation in ice cover and temperature, suggesting imminent recruitment collapse should the observed ice-reduction and heating continue. Backtracking of drifting eggs and larvae from observations also demonstrates a northward retreat of one of two clearly defined spawning assemblages, possibly in response to warming. With annual to decadal ice-predictions under development the mechanistic physical-biological links presented here represent a powerful tool for making long-term predictions for the propagation of polar cod stocks.


2016 ◽  
Vol 16 (3) ◽  
pp. 1773-1788 ◽  
Author(s):  
A.-M. Blechschmidt ◽  
A. Richter ◽  
J. P. Burrows ◽  
L. Kaleschke ◽  
K. Strong ◽  
...  

Abstract. Intense, cyclone-like shaped plumes of tropospheric bromine monoxide (BrO) are regularly observed by GOME-2 on board the MetOp-A satellite over Arctic sea ice in polar spring. These plumes are often transported by high-latitude cyclones, sometimes over several days despite the short atmospheric lifetime of BrO. However, only few studies have focused on the role of polar weather systems in the development, duration and transport of tropospheric BrO plumes during bromine explosion events. The latter are caused by an autocatalytic chemical chain reaction associated with tropospheric ozone depletion and initiated by the release of bromine from cold brine-covered ice or snow to the atmosphere. In this manuscript, a case study investigating a comma-shaped BrO plume which developed over the Beaufort Sea and was observed by GOME-2 for several days is presented. By making combined use of satellite data and numerical models, it is shown that the occurrence of the plume was closely linked to frontal lifting in a polar cyclone and that it most likely resided in the lowest 3 km of the troposphere. In contrast to previous case studies, we demonstrate that the dry conveyor belt, a potentially bromine-rich stratospheric air stream which can complicate interpretation of satellite retrieved tropospheric BrO, is spatially separated from the observed BrO plume. It is concluded that weather conditions associated with the polar cyclone favoured the bromine activation cycle and blowing snow production, which may have acted as a bromine source during the bromine explosion event.


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