Retrieval of Daily Mean VIIRS SST Products in China Seas

Sea surface temperature (SST) is one of the most important factors in regulating air-sea heat flux and, thus, climate change. Most of current global daily SST products are derived from one or two transient measurements of polar-orbiting satellites, which are not the same to daily mean SST values. In...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2021-12, Vol.13 (24), p.5158
Main Authors: Li, Qianmei, He, Qingyou, Chen, Chuqun
Format: Article
Language:English
Subjects:
Accuracy
Air temperature
Atmosphere
Calibration
Climate change
Control algorithms
daily mean SST
diurnal variation
Diurnal variations
Emergency communications systems
FY–4A
Heat
Heat flux
Imaging radiometers
Infrared imaging
Infrared radiometers
Meteorological satellites
Polar orbiting satellites
Quality control
Radiation
Remote sensing
Retrieval
Satellites
Sea surface temperature
Simulation
Synchronous satellites
VIIRS
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Summary:Sea surface temperature (SST) is one of the most important factors in regulating air-sea heat flux and, thus, climate change. Most of current global daily SST products are derived from one or two transient measurements of polar-orbiting satellites, which are not the same to daily mean SST values. In this study, high-temporal-resolution SST measurements (32–40 snapshots per day) from a geostationary satellite, FengYun-4A (FY–4A), are used to analyze the diurnal variation of SST in China seas. The results present a sinusoidal pattern of the diurnal variability in SST, with the maximum value at 13:00–15:00 CST and the minimum at 06:00–08:00 CST. Based on the diurnal variation of SST, a retrieval method for daily mean SST products from polar-orbiting satellites is established and applied to 7716 visible infrared imaging radiometer (VIIRS) data in China seas. The results suggest that it is feasible and practical for the retrieval of daily mean SST with an average RMSE of 0.133 °C. This retrieval method can also be utilized to other polar-orbiting satellites and obtain more daily mean satellite SST products, which will contribute to more accurate estimation and prediction between atmosphere and ocean in the future.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13245158