[ACG51-06] The Inversion and Quality Validation of FY3 MWRI Sea Surface Temperature
Keywords:FY-3, microwave imager, sea surface temperature
Objective :Sea surface temperature (SST) is an important physical parameter in the field of marine and climate research. Passive microwave remote sensing has the advantage of completing all weather observations ignoring the clouds interference, which has received more and more attention. The Fengyun (FY)-3 satellites carry the microwave imager (MWRI) on board. So using the FY3 MWRI to retrieval SST is of important significance.
Method:FY3 MWRI SST product uses statistical algorithms. Firstly, MWRI precipitation and sea ice products were used to remove the data containing precipitation and sea ice. Then using the temporal window of 0.2 hour and spatial window of 0.2°, the MWRI brightness temperature is matched with the buoy SST, and the matchup having land within 100km were excluded. Then being divided into four latitudes, 12 months, the descending and ascending statistical relationship between the buoy SST observation and MWRI bright temperature is established respectively. A total of 4 x 12 x 2 regression coefficients were obtained and corresponding regression coefficients were used respectively in the estimation of SST. The daily SST product were obtained using a 0.25°*0.25° equal latitude and longitude projections. The quality flag is set to 51 when FY3 MWRI SST minus 30 years monthly mean SST greater than 2.5K, and it showed that these pixels basically distribute on the edge of the land and high wind speed region.
Result:After excluding the pixels with quality flag of 51 , the quality validation of FY3 MWRI SST show that, compared with the global buoy data, the precision of the ascending orbit SST product is -0.02±1.22 K, and the precision of the descending orbit SST product is -0.15±1.28 K; compared with global analysis field OISST, the precision of the ascending daily SST product is 0.00±1.03K, and the precision of the descending daily SST product is -0.09±1.08K. The accuracy of the ascending orbit is better than that of the descending orbit, this is due to the non-uniform heating of the ocean surface during the day (the descending orbit). From the monthly SST product, we can see the kuroshio current, Gulf stream, western Pacific warm pool and La Nina clearly, which suggest that this SST product can also be well applied to the climatology investigation.
Conclusion:The results of the quality validation of FY3 MWRI SST consist with the FY3 product quality control system, and the SST precision is influenced by the performance of MWRI, its calibration and positioning accuracy, the precipitation and sea ice detection accuracy, the land interference and high wind speed. How to improve the precision of SST with wind speed greater than 12 m/s is the emphasis of the next step. The buoy SST and the global analysis field OISST can’t be referred as a completely true value, therefore, in the future, we will use the method of triple collocation to make a more comprehensive analysis of the error characteristics of the SST products.
Method:FY3 MWRI SST product uses statistical algorithms. Firstly, MWRI precipitation and sea ice products were used to remove the data containing precipitation and sea ice. Then using the temporal window of 0.2 hour and spatial window of 0.2°, the MWRI brightness temperature is matched with the buoy SST, and the matchup having land within 100km were excluded. Then being divided into four latitudes, 12 months, the descending and ascending statistical relationship between the buoy SST observation and MWRI bright temperature is established respectively. A total of 4 x 12 x 2 regression coefficients were obtained and corresponding regression coefficients were used respectively in the estimation of SST. The daily SST product were obtained using a 0.25°*0.25° equal latitude and longitude projections. The quality flag is set to 51 when FY3 MWRI SST minus 30 years monthly mean SST greater than 2.5K, and it showed that these pixels basically distribute on the edge of the land and high wind speed region.
Result:After excluding the pixels with quality flag of 51 , the quality validation of FY3 MWRI SST show that, compared with the global buoy data, the precision of the ascending orbit SST product is -0.02±1.22 K, and the precision of the descending orbit SST product is -0.15±1.28 K; compared with global analysis field OISST, the precision of the ascending daily SST product is 0.00±1.03K, and the precision of the descending daily SST product is -0.09±1.08K. The accuracy of the ascending orbit is better than that of the descending orbit, this is due to the non-uniform heating of the ocean surface during the day (the descending orbit). From the monthly SST product, we can see the kuroshio current, Gulf stream, western Pacific warm pool and La Nina clearly, which suggest that this SST product can also be well applied to the climatology investigation.
Conclusion:The results of the quality validation of FY3 MWRI SST consist with the FY3 product quality control system, and the SST precision is influenced by the performance of MWRI, its calibration and positioning accuracy, the precipitation and sea ice detection accuracy, the land interference and high wind speed. How to improve the precision of SST with wind speed greater than 12 m/s is the emphasis of the next step. The buoy SST and the global analysis field OISST can’t be referred as a completely true value, therefore, in the future, we will use the method of triple collocation to make a more comprehensive analysis of the error characteristics of the SST products.