The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity fr...The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity(SMOS) satellite data. Based on the principal component regression(PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea(in the area of 4?–25?N, 105?–125?E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu(practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.展开更多
Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. ...Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. The results suggest a highly positive linear correlation between freshwater flux and SSS in the Arabian Sea (correlation coefficient, R=0.74) and the western equatorial Indian Ocean (R=0.73), whereas the linear relationships are relatively weaker in the Bay of Bengal (R=0.50) and the eastern equatorial Indian Ocean (R=0.40). Additionally, the interannual variations of freshwater flux and SSS and their mutual relationship are investigated in four sub- regions for pre-monsoon, monsoon, and post-monsoon seasons separately. The satellite retrievals of SSS from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions can provide continuous and consistent SSS fields for a better understanding of its variability and the differences between the freshwater flux and SSS signals, which are commonly thought to be linearly related.展开更多
基金supported by the National Natural Science Foundation of China under project 41275013the National High-Tech Research and development program of China under project 2013AA09A506-4the National Basic Research Program under project 2009CB723903
文摘The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity(SMOS) satellite data. Based on the principal component regression(PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea(in the area of 4?–25?N, 105?–125?E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu(practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.
文摘Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. The results suggest a highly positive linear correlation between freshwater flux and SSS in the Arabian Sea (correlation coefficient, R=0.74) and the western equatorial Indian Ocean (R=0.73), whereas the linear relationships are relatively weaker in the Bay of Bengal (R=0.50) and the eastern equatorial Indian Ocean (R=0.40). Additionally, the interannual variations of freshwater flux and SSS and their mutual relationship are investigated in four sub- regions for pre-monsoon, monsoon, and post-monsoon seasons separately. The satellite retrievals of SSS from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions can provide continuous and consistent SSS fields for a better understanding of its variability and the differences between the freshwater flux and SSS signals, which are commonly thought to be linearly related.
