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Retrieval of Arctic Sea Ice Motion from FY-3D/MWRI Brightness Temperature Data.

Authors :
Chen, Haihua
Ni, Kun
Liu, Jun
Li, Lele
Source :
Remote Sensing; Sep2023, Vol. 15 Issue 17, p4191, 22p
Publication Year :
2023

Abstract

Sea ice motion (SIM) has significant implications for sea–air interactions, thermohaline circulation, and the development of the Arctic passage. This research proposes an improved SIM retrieval method from Fengyun-3D's (FY-3D) microwave radiometer imager's (MWRI) brightness temperature (T<subscript>b</subscript>) data based on the modified classical maximum cross-correlation (MCC) method and the multisource data merging method. This study utilized buoy data to establish the search area range, applied distinct thresholds across various Arctic regions, and merged the buoy data, reanalysis wind data, and SIM retrieved from FY-3D/MWRI T<subscript>b</subscript> data. In 2019, for the final Arctic SIM results retrieved from the MWRI 89 GHz and 36.5 GHz T<subscript>b</subscript> data, the root-mean-square error (RMSE) and the mean average error (MAE) in the east–west direction were 2.07 cm/s and 1.38 cm/s and those in the north–south direction were 1.96 cm/s and 1.15 cm/s, compared to the ice-tethered profiler (ITP) data. Compared with the daily average data of the National Snow and Ice Data Center (NSIDC), the RMSE and MAE of the SIM results obtained in this study were 0.74 cm/s and 0.93 cm/s in the east–west direction, and 0.56 cm/s and 0.72 cm/s in the north–south direction, respectively. The monthly average of the SIM retrieved from the MWRI T<subscript>b</subscript> data in this research also showed a good agreement with the monthly average of the NSIDC SIM product. The comparison showed that the MWRI T<subscript>b</subscript> data could be used to retrieve the Arctic SIM, and the Arctic SIM retrieval method presented in this paper was accurate and general. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
17
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
171859107
Full Text :
https://doi.org/10.3390/rs15174191