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China Meteorological Administration National Satellite Meteorological Center

CMA Working Papers for CGMS-41. China Meteorological Administration National Satellite Meteorological Center. Training Course on Satellite Meteorology 2012 ） Oct.22-Nov.2 Beijing China. List of CMA Working Papers for CGMS-41 Workgroup II.

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China Meteorological Administration National Satellite Meteorological Center

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  1. CMA Working Papers for CGMS-41 China Meteorological Administration National Satellite Meteorological Center Training Course on Satellite Meteorology 2012 ）Oct.22-Nov.2 Beijing China

  2. List of CMA Working Papers for CGMS-41 Workgroup II

  3. The National Satellite Meteorological Center (NSMC) currently uses the Nonlinear Sea Surface Temperature (NLSST) algorithms to estimate the sea surface temperature (SST) with the FY-3B satellite Visible and Infrared Radiometer (VIRR) data. Based on the match-up database(MDB), the standard deviation between the FY-3B VIRR SST and the in-situ is less than 0.5 ° C. Comparing with Daily OISST, the standard deviation is about 1.5 ° C. Validation of FY-3B Sea Surface Temperature CGMS-41, CMA-WP-07 Prepared by CMA Agenda Item: II/9 Discussed in WGII

  4. Introduction NSMC/CMA currently uses NLSST algorithms to estimate sea surface temperature (SST) from FY-3B VIRR data. In this study, we created a month by month database of global sea surface temperature derived from FY-3B VIRR data paired with coincident SST measurements from buoys (so called the SST matchup database) from August 2012 to March 2013. The satellite derived SST and buoy SST pairs were included in the database while they were coincident within 1.1km and 1 hour. A regression analysis of the data in this matchup database was used to derive the coefficients for the NLSST equations applicable to FY-3B VIRR sensor data.

  5. Comparison Validate FY3B VIRR SST against in situ data Quality controlled in situ data from iQUAM was used. The month by month matchup database(MDB) was used to assess the accuracy of these day and night NLSST algorithms. The bias was found to be 0.02°C and 0.04° C for the day and night algorithms, respectively. The standard deviation was< 0.5° C Time series of global bias and STD with respect to in situ SST from August 2012 to March 2013.Matchup window was set to 1.1KM in space and 1hour in time.

  6. ComparisonCompare SST against the global grid L4 SST The coefficient derived from 2013 March MDB was used for 2013 April L2 SST retrival. Daily OISST(0.25º x 0.25º) is bilinear interpolated to FY-3B VIRR sensor’s pixels, L2 SST analysis is based on the 5-minute granule of FY3B SST minus OISST. comparison between FY-3B VIRR NLSST and Global gridded daily OISST, the global accuracy of FY3B VIRR NLSST is -0.62°C±1.45°C (Day ),-0.43°C±1.5°C (Night). If chose the absolute difference between FY-3B VIRR SST and OISST within 2°C, the global accuracy is -0.24°C±0.82°C (Day),0.04°C±0.84°C (Night).

  7. Summary The standard deviation between FY-3B VIRR SST and in situ data was< 0.5° C. Compare with Daily OISST, the global accuracy of FY3B VIRR SST is -0.62°C±1.45°C (Day),-0.43°C±1.5°C (Night).

  8. The End Thanks for your attention

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