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Historical and real-time estimation of snow depth in Eurasia based on multiple passive microwave data

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摘要 Current snow depth datasets demonstrate large discrepancies in the spatial pattern in Eurasia,and the lagging updates of datasets do not meet the operational requirements of the meteorological service department.This study developed a dynamic retrieval method for daily snow depth over Eurasia based on cross-sensor calibrated microwave brightness temperatures to enhance retrieval accuracy and meet the requirements of operational work.These brightness temperatures were detected by microwave radiometer imager carried on the FengYun 3(FY-3)satellite and the special sensor microwave imager/sounder carried on the USA Defense Meteorological Satellite Program series satellites,which use the fewest sensors to provide the longest data and consequently introduce minimal errors during inter-sensor calibration.Firstly,inter-sensor calibration was conducted amongst brightness temperatures collected by the three sensors.A spatiotemporal dynamic relationship between snow depth and microwave brightness temperature gradient was then established,overcoming the large uncertainties induced by varying snow characteristics.This relationship can be utilised in FY-3 satellite data for operational service to obtain real-time snow depth.The generated daily snow depth dataset from 1988 to 2021 presents similar spatial patterns of snow depth to those observed in situ.Against in situ snow depth,the overall bias and root mean square error are−2.04 and 6.49 cm,respectively,facilitating considerable improvements in accuracy compared with the Advanced Microwave Scanning Radiometer 2 snow depth product,which adopts the static algorithm.Further analysis shows an overall decreasing trend from 1988 to 2021 for annual and monthly mean snow depths,demonstrating a noticeable reduction since around 2000.The reduction in monthly mean snow depth started earlier in shallow snow months than in deep snow months.
出处 《Advances in Climate Change Research》 SCIE CSCD 2023年第4期537-545,共9页 气候变化研究进展(英文版)
基金 funded by the National Natural Science Foundation of China(42125604 and 42171143) Innovative Development Project of China Meteorological Administration(CXFZ 2022J039)and CAS Light of West China Program.The National Oceanic and Atmospheric Administration,USA,provided in situ snow depth data in the Eurasian continent except China and passive microwave brightness temperature data on the DMSP series of satellites.China Meteorological Administration provided FengYun satellite data and in situ snow depth in China,and NASA provided AMSR2 brightness temperature and sea ice concentration data.
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