@article{li2020spatiotemporal,title={Spatiotemporal variations of satellite microwave emissivity difference vegetation index in China under clear and cloudy skies},author={Li, Rui and Wang, Yipu and Hu, Jiheng and Wang, Yu and Min, Qilong and Bergeron, Yves and Valeria, Osvaldo and Gao, Zongting and Liu, Jinjun and Fu, Yuyun},journal={Earth and Space Science},volume={7},number={5},pages={e2020EA001145},year={2020},publisher={Wiley Online Library},url={https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020EA001145}}
The microwave at low and moderate frequencies (e. g., 18.7 and 36.5 GHz) has good transmittance through the atmosphere, therefor in most algorithms for satellite passive microwave (PMW) remote sensing snow parameters, ignoring the effect of atmosphere and the upwelling microwave brightness temperature at the top of atmosphere (TOA) were directly used to retrieve snow parameters on ground. There are few systematic analysis on the errors introduced by ignoring atmosphere effects. In this paper, we investigated the influences of atmosphere to the PMW retrieval of snow depth over Qinghai-Tibetan Plateau (QTP). We used the upwelling brightness temperature on TOA (TB_TOA) measured by the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) as the main input data. The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product (MYD06_L2) and National Centers for Environmental Prediction (NCEP) FNL reanalysis data (including atmosphere water vapor, atmosphere component and land surface temperature) were used as the ancillary data. The effect of water vapor and non-rainy cloud were corrected and the upwelling brightness temperature at the plateau surface (TB_SRF) were derived based on microwave radiation transfer model (MWRT) calculation. We then estimated the snow depths of SD_TOA and SD_SRF over QTP using these two TBs, respectively. By comparing the two TBs and two SDs, the effect of atmosphere and cloud on PMW remote sensing snow depth were investigated. Through case analysis and nearly 10 years of statistics, we found that:the atmosphere effect on TBs at low frequency microwave 18.7 GHz is weak while TB_TOA at 36.5 GHz are significantly warmer than TBSRF. Without considering such effect, the snow depth over QTP would be underestimated (SD_TOA < SD_SRF). The underestimations are common in multiple cases and significant at multi-year mean scales, therefore should not be neglected. The absolute error (SD_TOA-SD_SRF) is approximately 2 3 cm. In the region with relative shallow snow, the relative error is up to 50% 80%. While in the region with relative deep snow, the relative error is 10% 20%. The error has strong negative correlation with liquid cloud water path (R=-0.45) with sensitivity of -0.047 cm·(g·m-2)-1. The error is not sensitive to ice cloud and even weaker to column water vapor. Snow extent retrieved from MODIS (MYD10CM product) has better correlation to SD_SRF than that to SD_TOA. This imply that corrections of the influence of atmosphere can improve the accuracy of satellite PMW retrieval of snow depth over QTP.
@article{liu2018plateau,title={The Influence of Atmosphere to Passive Microwave Retrieval of Snow Depth over Qinghai-Tibetan Plateau},author={Liu, Jinjun and Fu, Yunfei and Li, Rui and Wang, Yu and Fu, Yuyun and Hu, Jiheng},journal={Plateau Meteorology},volume={37},number={2},pages={305--316},year={2018},url={http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2017.00050}}