Removal of the MCSST MODIS SST Bias During Upwelling Events Along the Southeastern Coast of Brazil - Pimentel, Gilberto R.; Franca, Gutemberg B.; Peres, Leonardo F. (IEEE transactions on geoscience and remote sensing, 2019)
Remotely sensed sea-surface temperature (SST) retrievals with a significant positive bias during the occurrence of upwelling phenomena along the southeastern coast of Brazil were reported in our companion paper. As a result, this paper proposes an automated bias correction algorithm to improve the MODIS long-wave multichannel SST (MCSST) retrievals during the abovementioned conditions in this region. In this paper, MODIS daytime SST data (SST MODIS ) and differences between brightness temperatures in MODIS channels 31 and 32 (BT31 − BT32) are analyzed simultaneously with hourly wind surface conditions, in situ SST at 0.3 and 10 m in depth (SST buoy03 and SST buoy10 ), and sensible and latent heat fluxes from the Cabo Frio buoy data (at 23° S, 42° W) during 2014. The obtained results show that some upwelling events present air temperature ( T_{air} ) greater than SSTbuoy03 and low-atmospheric water vapor content. A simultaneous occurrence of these factors during upwelling conditions may lead to a warm-skin layer effect and may cause BT31 to be greater than SST buoy03 and BT31 − BT32 to be small (−0.18 °C ± 0.22 °C), affecting the MCSST performance. The proposed bias correction algorithm uses a least-squares curve between SST buoy03 and SST MODIS retrievals when BT31 − BT32 ≤ 0.5 °C (i.e., dry atmospheric conditions). The bias correction algorithm has significantly improved the SSTMODIS bias (RMSE) from 1.43 °C to −0.2 °C (1.60 °C to 0.58 °C) when applied to 22 cloud-free pixels of MODIS during January-March of 2015.