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Remote Sens. 2018, 10(1), 36; https://doi.org/10.3390/rs10010036

Inter-Calibration of Passive Microwave Satellite Brightness Temperatures Observed by F13 SSM/I and F17 SSMIS for the Retrieval of Snow Depth on Arctic First-Year Sea Ice

1
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
2
Key Laboratory of Polar Surveying and Mapping, National Administration of Surveying, Mapping and Geoinformation, Wuhan 430079, China
3
School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
4
Key Laboratory for Polar Science of the State Oceanic Administration, Polar Research Institute of China, Shanghai 200136, China
*
Author to whom correspondence should be addressed.
Received: 6 November 2017 / Revised: 12 December 2017 / Accepted: 23 December 2017 / Published: 26 December 2017
(This article belongs to the Special Issue Snow Remote Sensing)
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Abstract

Passive microwave satellite brightness temperatures (TB) that were observed by the F13 Special Sensor Microwave/Imager (SSM/I) and the subsequent F17 Special Sensor Microwave Imager/Sounder (SSMIS) were inter-calibrated using empirical relationship models during their overlap period. Snow depth (SD) on the Arctic first-year sea ice was further retrieved. The SDs derived from F17 TB and F13C TB which were calibrated F17 TB using F13 TB as the baseline were then compared and evaluated against in situ SD measurements based on the Operational IceBridge (OIB) airborne observations from 2009 to 2013. Results show that Cavalieri inter-calibration models (CA models) perform smaller root mean square error (RMSE) than Dai inter-calibration models (DA models), and the standard deviation of OIB SDs in the 25 km pixels is around 6 cm on first-year sea ice. Moreover, the SDs derived from the calibrated F17 TB using F13 TB as the baseline were in better agreement than the F17 SDs as compared with OIB SDs, with the biases of −2 cm (RMSE of 5 cm) and −9 cm (RMSE of 10 cm), respectively. We conclude that TB observations from F17 SSMIS calibrated to F13 SSM/I as the baseline should be recommended when performing the sensors’ biases correction for SD purpose based on the existing algorithm. These findings could serve as a reference for generating more consistent and reliable TB, which could help to improve the retrieval and analysis of long-term snow depth on the Arctic first-year sea ice. View Full-Text
Keywords: snow depth; SSM/I; SSMIS; Operation IceBridge; Arctic snow depth; SSM/I; SSMIS; Operation IceBridge; Arctic
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Liu, Q.; Ji, Q.; Pang, X.; Gao, X.; Zhao, X.; Lei, R. Inter-Calibration of Passive Microwave Satellite Brightness Temperatures Observed by F13 SSM/I and F17 SSMIS for the Retrieval of Snow Depth on Arctic First-Year Sea Ice. Remote Sens. 2018, 10, 36.

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