Research progress and prospect of remote sensing with passive microwave from snow

Research progress of the passive microwave remote sensing for snow cover at home and abroad in recent years was overviewed, and common passive microwave sensors SMMR（Scanning Multichannel Microwave Radiometer）, SSM/I（Special Sensor Microwave/Imager）, AMSRE (Advanced Microwave Scanning RadiometerEOS) and MWRI（Microwave Radiation Imager）were compared for each other. Some problems were found as follows: 1) The discriminant threshold of dry snow and wet snow is influenced by many factors that do not determined still. 2) The measured value of snow depth can not by reflected by meteorological situation. 3) The resolution is not high enough to used in monitoring the shallow snow zone information. 4) It seems to be overestimated for range and depth of snow and so on. In addition, the accuracy of the inversion results was affected by snow density, particle size, precipitation, cold desert, vegetation, permafrost and other factors. Aim to further study intensively, passive microwave remote sensing of snow cover was prospected as follows: 1) To operational monitoring, visible light and passive microwave data should be integrated; 2) Combination of remote sensing and geographic information systems would improve the accuracy and application breadth; 3) Improvements of the algorithm, higher spatial resolution data of passive microwave AMSRE, and passive microwave radiation imaginer MWRI of our FY3 satellite with the snow model would enhance importance of snow monitoring; 4) Range of snow monitoring is more consistent with passive microwave remote sensing and MODIS visible light.The passive microwave remote sensing can play an alternative role when visible light images can not be obtained satisfactorly due to more clouds; and 5) Passive microwave remote sensing still have more issues in operational snow monitoring, continuous monitoring of ground operations and Algorithm improvement. Its validation is an important guarantee to improve the technology, which need to be verified in snow storms.