Retrieval of Microwave Surface Emissivities at TMI Frequencies in Shouxian

Using a microwave radiative transfer model, atmospheric sounding profiles, satellite brightness temperatures, and some surface observed measurements under cloud-free conditions, surface emissivities at the frequencies of TRMM/TMI (Tropical Rainfall Measuring Mission Microwave Imager) at Shouxian in HUBEX (Huaihe River Basin Energy and Water Cycle Experiment) are retrieved. Compared to the microwave surface emissivities with changing conditions of the surface, it is found that the microwave emissivities have some sensitive variability with the conditions of the surface, and the variability is reasonable. In the calculation, the surface air temperatures are assumed to equal the surface skin temperatures, and only the emissivity at Shouxian is calculated; the calculation of the emissivities over the region of HUBEX needs more measurements.

Spatiotemporal Variations of Microwave Land Surface Emissivity(MLSE)over China Derived from Four-Year Recalibrated Fengyun 3B MWRI Data

Microwave Land Surface Emissivity(MLSE)over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures(Tbs)from Fengyun-3B Microwave Radiation Imager(FY-3B MWRI),combined with cloud properties derived from Himawari-8 Advanced Himawari Imager(AHI)observations.The contributions from cloud particles and atmospheric gases to the upwelling Tbs at the top of atmosphere were calculated and removed in radiative transfer.The MLSEs at horizontal polarizations at 10.65,18.7,and 36.5 GHz during 7 July 2015 to 30 June 2019 over China showed high values in the southeast vegetated area and low values in the northwest barren,or sparsely vegetated,area.The maximum values were found in the belt area of the Qinling-Taihang Mountains and the eastern edge of the Qinghai-Tibet Plateau,which is highly consistent with MLSEs derived from AMSR-E.It demonstrates that the measurements of FY-3B MWRI Tbs,including its calibration and validation,are reliable,and the retrieval algorithm developed in this study works well.Seasonal variations of MLSE in China are mainly driven by the combined effects of vegetation,rainfall,and snow cover.In tropical and southern forest regions,the seasonal variation of MLSE is small due to the enhancement from vegetation and the suppression from rainfall.In the boreal area,snow causes a significant decrease of MLSE at 36.5 GHz in winter.Meanwhile,the MLSE at lower frequencies experiences less suppression.In the desert region in Xinjiang,increases of MLSEs at all frequencies are observed with increasing snow cover.

Influence of Surface Temperature and Emissivity on AMSU-A Assimilation over Land

AMSU-A （Advanced Microwave Sounding Unit-A） measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction （NWP） models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting （WRF） model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation （WRF-VAR） system, the surface parameters from the operational Microwave Surface and Precipitation Products System （MSPPS） are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error （RMSE） and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction （NCEP） global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.