Removal of the MCSST MODIS SST Bias During Upwelling Events Along the Southeastern Coast of Brazil

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 M...

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Veröffentlicht in:IEEE transactions on geoscience and remote sensing Jg. 57; H. 6; S. 3566 - 3573
Hauptverfasser: Pimentel, Gilberto R., Franca, Gutemberg B., Peres, Leonardo F.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Air temperature
Algorithms
Atmospheric conditions
Atmospheric water
Bias
Bias correction
Buoys
Coastal environments
Heat flux
Heat transfer
Latent heat
Meteorological satellites
Meteorology
MODIS
Ocean circulation
Ocean temperature
Remote sensing
Sea measurements
Sea surface
Sea surface temperature
sea-surface temperature (SST)
Temperature sensors
Upwelling
Water vapor
Water vapour
Brazil
ISSN:0196-2892, 1558-0644
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Zusammenfassung: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 (<inline-formula> <tex-math notation="LaTeX">T_{\mathrm {air}} </tex-math></inline-formula>) 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.
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ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2018.2885759