Innovations in the Data Processing Algorithm for Chinese FY Meteorological Satellites

This study introduces some innovations in the data processing algorithm for Chinese FY meteorological satellites. Issues about satellite image navigation, radiation calibration, and data assimilation are discussed. A time series of the earth＇s disk center-line count provides information on the orientation of the satellite spin axis. With this information, the altitude parameters of the satellite and then the earth disk location in the south-north direction may be solved. In each spin cycle, the satellite views the sun and the earth. Given the satellite position and altitude, the angle （β） subtended at the satellite by the sun and the earth can be calculated and predicted. Thus, the earth＇s disk location in the east-west direction is fixed. Based on this principle, we derived an automatic image navigation algorithm for FY2 geosynchronous meteorological satellites with an accuracy approaching pixel level. The FY2 meteorological satellite traveling in a geostationary orbit suffers a large amount of radiation from the sun. The radiation varies on both diurnal and annual scales, which causes radiation responses in the thermal infrared （IR） bands wherein the wavelengths greater than 3.5 μm vibrate periodically on scales of hours to years. These vibrations must be precisely calibrated. First, based on the accurate estimation of the radiant contribution from the front-optics, the variation characteristics of the calibration parameters are obtained on a temporal scale of hours from the space-borne inner-blackbody （IBB） measurement results. Second, the in-orbit measured radiation of the lunar surface is referenced and utilized to correct the sys- tematic bias of the IBB calibration from daily to annual scales. By using such algorithms, we achieved a calibration accuracy of the FY2 satellite＇s IR imagery of less than 1 K. The on-orbit satellite instrument parameters play an important role in data quality; however, they may be mis-measured due to limitations in the measurement conditions or may be changed due to the space environment after launch. A satellite instrument parameters on-orbit optimizer （SIPOn-Opt） for a polar orbit meteorological satellite was developed to optimize the true state of the instrument parameters on-orbit with regard to the observation constraints. When applying the SIPOn-Opt to FY3 sounding instruments, the FY3 data quality was much improved, compared to its European and the U.S. polar orbit meteorological satellite counterparts, leading to improved forecast skill of numerical weather prediction.