摘要
为减轻强降水带来的洪涝灾害风险,该文利用风云三号D星(FY-3D)微波成像仪的一级亮温数据,结合与之匹配的二级降水产品,基于极化订正温度(polarization-corrected temperature,PCT)及散射指数(scatter index,SI),建立湖南地区陆面强降水降水率反演模型,进而通过个例对所建立的反演模型进行验证。结果表明,FY-3D卫星一级亮温数据反演的降水率与二级产品所获降水结果基本一致;反演所得降水率在降水量低值区略偏大,而在高值区中心区域偏小;升轨反演模型的相关系数(R)、平均绝对误差(mean absolute evror,MAE)和均方根误差(root mean square evror,RMSE)分别为0.8761,0.7711 mm/h和1.1514 mm/h,降轨反演模型的R、MAE和RMSE分别为0.9113,1.1304 mm/h和1.8322 mm/h;反演得到的降水分布范围比二级产品的分布范围有所增大;相较于二级产品,该模型反演结果在与站点实测值的对比中体现出更高的精度。该研究比较成功地反演了湖南地区陆面强降水的分布区域,可为研究微波亮温与降水的关系,以及陆面强降水降水率估算提供参考。
Using level-1(L1)brightness temperature data from the Microwave Radiation Imager(MWRI)on board Fengyun-3D(FY-3D)satellite and the corresponding Level-2(L2)precipitation products,this study established a precipitation rate inversion model for land surface heavy precipitation in Hunan Province based the polarization corrected temperature(PCT)and scatter index(SI).The proposed model was validated using individual examples.The results indicate that the precipitation rates retrieved from the L1 brightness temperature data of the FY-3D satellite were generally consistent with the results obtained from the L2 precipitation products.Compared to actual data,the retrieved precipitation rates were slightly higher in low precipitation areas but smaller in centers of high precipitation areas.The ascending orbit-based inversion model exhibited a correlation coefficient,mean absolute error(MAE),and root mean square error(RMSE)of 0.8761,0.7711,and 1.1514 mm/h,respectively.Conversely,the descending orbit-based inversion model presented a correlation coefficient,MAE,and RMSE of 0.9113,1.1304,and 1.8322 mm/h,respectively.The inversion results showed a larger precipitation distribution range than that of L2 products.Compared to the measurements at ground meteorological stations,the inversion model demonstrated higher accuracy than L2 products.This study successfully determined the distribution of land surface heavy precipitation in Hunan through inversion.The results of this study can provide a reference for investigating the relationship between microwave brightness temperature and precipitation and estimating land surface heavy precipitation.
作者
王陶然
吴莹
马靖雯
黄媛媛
付琪嘉
WANG Taoran;WU Ying;MA Jingwen;HUANG Yuanyuan;FU Qijia(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science&Technology,Nanjing 210044,China;Meteorological Bureau of Yiyang City,Hunan Province,Yiyang 413099,China)
出处
《自然资源遥感》
北大核心
2025年第4期212-219,共8页
Remote Sensing for Natural Resources
基金
国家自然科学基金联合基金项目“风云卫星产品对数值预报同化应用支撑的关键技术及应用效益评估研究”(编号:U2242212)资助。
