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A bias correction method for FY-3C VIRR SST data

Author:
Liao, Zhihong, Dong, Qing, Xue, Cunjin
Source:
Remote sensing letters 2017 v.8 no.5 pp. 429-437
ISSN:
2150-7058
Subject:
algorithms, probability distribution, remote sensing, surface water temperature
Abstract:
A bias correction method was proposed for correcting the significant negative sea surface temperature (SST) biases in Fengyun-3C (FY-3C) visible and infrared radiometer (VIRR) products. The multichannel SST algorithm (MCSST) for the daytime SST and night-time SST of VIRR products are modified for estimating the debiased VIRR SSTs, and the optimal local matchup data are selected for each SST observations based on the distance to each parts of regressors in R -space. Compared with the probability density function matching technique for bias correction, the proposed method can better remove the negative biases and decrease the standard deviations of biases.
Agid:
5630893