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A bias correction method for FY-3C VIRR SST data
- Liao, Zhihong, Dong, Qing, Xue, Cunjin
- Remote sensing letters 2017 v.8 no.5 pp. 429-437
- algorithms, probability distribution, remote sensing, surface water temperature
- 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.