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Assessment of Arctic Sea Ice Thickness Estimates From ICESat-2 Using IceBird Airborne Measurements

Xiaoyi Shen, Chang‐Qing Ke, Qimao Wang, Jie Zhang, Lijian Shi, Xi Zhang

2020IEEE Transactions on Geoscience and Remote Sensing24 citationsDOI

Abstract

The successful launch of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides a new and advanced tool for sea ice thickness (SIT) estimations in the Arctic. However, the performance of ICESat-2 for SIT estimations still remains unknown. In the present study, SIT estimates derived from ICESat-2 are examined using three retrieval methods, namely, two buoyancy methods with the merged snow depth and empirical snow depth (BMA and BME, respectively) and one empirical estimation method (EEM), and these estimates are compared to near-simultaneous airborne measurements from the IceBird mission in April 2019. Overall, the ICESat-2 total freeboard registers quite well with that from the near-concurrent IceBird mission with a mean bias of 2.5 cm, which demonstrates the high reliability of ICESat-2 data for SIT estimation. However, the much more evident difference between SIT estimations than total freeboard from ICESat-2 and IceBird indicates that other parameters (e.g., snow depth and snow/ice densities) may bring increased uncertainties to the SIT estimation. Overall, BMA is the best method for SIT estimation and has the closest thickness distribution to that of IceBird data with a mean bias of 0.11 m, followed by the BME and EEM methods. The dominate error sources for SIT estimation using the buoyancy method are ice density and snow depth that require further investigation in future studies.

Topics & Concepts

FreeboardSnowRemote sensingEnvironmental scienceSea iceSatelliteArcticElevation (ballistics)Ice cloudMeteorologyGeologyArctic ice packGeodesyClimatologyGeographyOceanographyMathematicsEngineeringWaste managementAerospace engineeringFluidized bedGeometryArctic and Antarctic ice dynamicsCryospheric studies and observationsClimate change and permafrost
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