Javascript must be enabled to continue!
An Intercomparison of Satellite Derived Arctic Sea Ice Motion Products
View through CrossRef
Arctic sea ice motion information provides an important scientific basis for revealing the changing mechanism of Arctic sea ice and assessing the navigational safety of Arctic waterways. For now, many satellite derived Arctic sea ice motion products have been released but few studies have conducted comparisons of these products. In this study, eleven satellite sea ice motion products from the Ocean and Sea Ice Satellite Application Facility (OSI SAF), the National Snow and Ice Data Center (NSIDC), and the French Research Institute for the Exploitation of the Seas (Ifremer) were systematically evaluated and compared based on buoys from the International Arctic Buoy Program (IABP) and the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) over 2018–2020. The results show that the mean absolute errors (MAEs) of ice speed for these products are 1.15–2.26 km/d and the MAEs of ice motion angle are 14.93–23.19°. Among all products, Ifremer_AMSR2 achieves the best accuracy in terms of speed error, NSIDC_Pathfinder shows the lowest angle error and OSI-405-c_Merged performs best in sea-ice drift trajectory reconstruction. Moreover, season, region, data source, ice drift tracking algorithm, and time interval all influence the accuracy of these products: (1) The sea ice motion bias in the freezing season (1.04–1.96 km/d and 11.93–22.41°) is smaller than that in the melting season (1.13–3.90 km/d and 14.41–27.41°) for most of the products. (2) Most products perform worst in East Greenland, where ice movements are fast and complex. (3) The accuracies of the products derived from AMSR-2 remotely sensed data are better than those from other data sources. (4) The continuous maximum cross-correlation (CMCC) algorithm outperforms the maximum cross-correlation (MCC) algorithm in sea ice drift retrieval. (5) The MAEs of sea ice motion with longer time interval are relatively smaller. Overall, the results indicate that the eleven remote sensing Arctic sea ice drift products are of practical use for data assimilation and model validation if uncertainties are appropriately considered. Furthermore, this study provides some improvement directions for sea ice drift retrieval from satellite data.
Title: An Intercomparison of Satellite Derived Arctic Sea Ice Motion Products
Description:
Arctic sea ice motion information provides an important scientific basis for revealing the changing mechanism of Arctic sea ice and assessing the navigational safety of Arctic waterways.
For now, many satellite derived Arctic sea ice motion products have been released but few studies have conducted comparisons of these products.
In this study, eleven satellite sea ice motion products from the Ocean and Sea Ice Satellite Application Facility (OSI SAF), the National Snow and Ice Data Center (NSIDC), and the French Research Institute for the Exploitation of the Seas (Ifremer) were systematically evaluated and compared based on buoys from the International Arctic Buoy Program (IABP) and the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) over 2018–2020.
The results show that the mean absolute errors (MAEs) of ice speed for these products are 1.
15–2.
26 km/d and the MAEs of ice motion angle are 14.
93–23.
19°.
Among all products, Ifremer_AMSR2 achieves the best accuracy in terms of speed error, NSIDC_Pathfinder shows the lowest angle error and OSI-405-c_Merged performs best in sea-ice drift trajectory reconstruction.
Moreover, season, region, data source, ice drift tracking algorithm, and time interval all influence the accuracy of these products: (1) The sea ice motion bias in the freezing season (1.
04–1.
96 km/d and 11.
93–22.
41°) is smaller than that in the melting season (1.
13–3.
90 km/d and 14.
41–27.
41°) for most of the products.
(2) Most products perform worst in East Greenland, where ice movements are fast and complex.
(3) The accuracies of the products derived from AMSR-2 remotely sensed data are better than those from other data sources.
(4) The continuous maximum cross-correlation (CMCC) algorithm outperforms the maximum cross-correlation (MCC) algorithm in sea ice drift retrieval.
(5) The MAEs of sea ice motion with longer time interval are relatively smaller.
Overall, the results indicate that the eleven remote sensing Arctic sea ice drift products are of practical use for data assimilation and model validation if uncertainties are appropriately considered.
Furthermore, this study provides some improvement directions for sea ice drift retrieval from satellite data.
Related Results
Dissolved Neodymium Isotopes Trace Origin and Spatiotemporal Evolution of Modern Arctic Sea Ice
Dissolved Neodymium Isotopes Trace Origin and Spatiotemporal Evolution of Modern Arctic Sea Ice
<p>The lifetime and thickness of Arctic sea ice have markedly decreased in the recent past. This affects Arctic marine ecosystems and the biological pump, given that ...
Seasonal Arctic sea ice predictability and prediction
Seasonal Arctic sea ice predictability and prediction
Arctic sea ice plays a central role in the Earth’s climate. Changes in the sea ice on seasonal-to-interannual timescales impact ecosystems, populations and a growing number of stak...
Differences in Arctic sea ice simulations from various SODA3 data sets
Differences in Arctic sea ice simulations from various SODA3 data sets
<p>SODA (Simple Ocean Data Assimilation) is one of the ocean reanalysis data widely used in oceanographic research. The SODA3 dataset provides multiple ocean reanalys...
A new HPLC-MS method for fatty acid detection in sea ice
A new HPLC-MS method for fatty acid detection in sea ice
The presence of marine-sourced fatty acids1,2,3, in Antarctic ice cores has been linked to changes in sea ice conditions2,3. It has been proposed that the phytoplankton within and ...
Sea ice deformation and thickness in the Western Ross Sea
Sea ice deformation and thickness in the Western Ross Sea
<p>Sea ice cover is arguably the longest and best observed climate variable from space, with over four decades of highly reliable daily records of extent in both hemi...
Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover
Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover
Abstract. Recent studies based on satellite observations have shown that there is a high statistical connection between the late winter (Feb-May) sea ice export out the Laptev Sea,...
Multiple Sea Ice Type Retrieval Using the HaiYang-2B Scatterometer in the Arctic
Multiple Sea Ice Type Retrieval Using the HaiYang-2B Scatterometer in the Arctic
Sea ice type classification is of great significance for the exploration of waterways, fisheries, and offshore operations in the Arctic. However, to date, there is no multiple remo...
Effect of ocean heat flux on Titan's topography and tectonic stresses
Effect of ocean heat flux on Titan's topography and tectonic stresses
INTRODUCTIONThe thermo-mechanical evolution of Titan's ice shell is primarily controlled by the mode of the heat transfer in the ice shell and the amount of heat coming from the oc...

