In-Orbit Calibration Uncertainty of the Microwave Radiation Imager on board Fengyun-3C

This study evaluates the in-orbit calibration uncertainty(CU)for the microwave radiation imager(MWRI)on board the Chinese polar-orbiting meteorological satellite Fengyun-3 C(FY-3 C).Uncertainty analysis of the MWRI provides a direct link to the calibration system of the sensor and quantifies the calibration confidence based on the prelaunch and postlaunch measurements.The unique design of the sensor makes the uncertainty in the calibration of the sensor highly correlate to the uncertainty in the brightness temperature(TB)measured at the hot view,while the cold view has negligible impacts on the calibration confidence.Lack of knowledge on the emission of the hot-load reflector hampers the MWRI calibration accuracy significantly in the descending passes of the orbits when the hotload reflector is heated nonuniformly by the solar illumination.Radiance contamination originating from the satellite and in-orbit environments could enter the primary reflector via the hot view and further impinge on the CU,especially at the 10.65-GHz channels where the main-beam width is much broader than that of higher-frequency channels.The monthly-mean CU is lower than 2 K at all channels,depending on the observed earth scenes and in-orbit environments,and the month-to-month variation of CU is also noticed for all channels.Due to the uncertainty in the emissive hot-load reflector,CU in the descending passes is generally larger than that in the ascending orbits.Moreover,up to 1-K CU difference between the ocean and land scenes is found for the 10.65-GHz channels,while this difference is less than 0.1 K at the 89-GHz channels.

Impact of FY-3D MWRI Radiance Assimilation in GRAPES 4DVar on Forecasts of Typhoon Shanshan

In this study, Fengyun-3 D(FY-3 D) Micro Wave Radiation Imager(MWRI) radiance data were directly assimilated into the Global/Regional Assimilation and Pr Ediction System(GRAPES) four-dimensional variational(4 DVar) system. Quality control procedures were developed for MWRI applications by using algorithms from similar microwave instruments. Compared with the FY-3 C MWRI, the bias of FY-3 D MWRI observations did not show a clear node-dependent difference from the numerical weather prediction background simulation. A conventional bias correction approach can therefore be used to remove systematic biases before the assimilation of data. After assimilating the MWRI radiance data into GRAPES, the geopotential height and humidity analysis fields were improved relative to the control experiment. There was a positive impact on the location of the subtropical high, which led to improvements in forecasts of the track of Typhoon Shanshan.