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KNN不同距离度量对FY-4A/AGRI红外亮温反演降水的影响研究
投稿时间:2020-03-30  修订日期:2020-04-11  点此下载全文
引用本文:王根,陆雅君,王悦,吴瑞姣,丁从慧.KNN不同距离度量对FY-4A/AGRI红外亮温反演降水的影响研究[J].红外,2020,41(6):33~40
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作者单位E-mail
王根 中亚大气科学研究中心
安徽省气象台 
203wanggen@163.com 
陆雅君 安徽省气象台 强天气集合分析和预报重点实验室  
王悦 安徽省气象台 强天气集合分析和预报重点实验室  
吴瑞姣 安徽省气象台 强天气集合分析和预报重点实验室  
丁从慧 安徽省气象台 强天气集合分析和预报重点实验室  
基金项目:中亚大气科学研究基金项目(CAAS202003);国家自然科学基金项目(41805080);上海台风研究基金项目(TFJJ201909) ;安徽省气象局项目(KM201902)
中文摘要:静止卫星的高时空分辨率对高影响灾害性天气的监测和预报有显著优势。开展了基于风云四号A星多通道扫描成像辐射计(Advanced Geosynchronous Radiation Imager,AGRI)红外光谱亮温的台风降水反演研究。探讨了正则化反问题方法中K-最邻近(K-Nearest Neighbor,KNN)不同距离度量对降水反演精度的影响。降水反演共分两步:一是降水视场点识别,主要基于训练字典样本,利用KNN识别待反演的亮温“降水”和“非降水”信号;二是降水视场点反演,即在判识视场点有降水的基础上采用正则化反问题方法进行红外亮温降水反演。KNN距离度量分别采用欧氏、标准化欧氏、马氏和布洛克距离。以台风“安比(2018)”为例,开展了降水反演试验。试验表明,反演结果与GPM的相似度较高,且不同距离度量在反演“极端降水”时各有优势。
中文关键词:FY-4A/AGRI  台风“安比”  降水反演  距离度量  正则化反问题
 
Different Distance Measurements of KNN on Precipitation Retrieval by AGRI Infrared Bright Temperatures of FY-4A
Abstract:The high spatial and temporal resolution of geostationary satellite has significant advantages in monitoring and forecasting disastrous weather with high impact. A typhoon precipitation retrieval study based on infrared spectrum bright temperatures of the advanced geosynchronous radiation imager (AGRI) in FY-4A satellite is conducted. The influences on precipitation retrieval accuracy of different distance measurements of K-nearest neighbor (KNN) in the inverse problem of regularization method are discussed. The precipitation retrieval consists of two steps: (1) the identification of precipitation field of view, which uses KNN to identify the “precipitation” and “non-precipitation” signals of brightness temperatures to be retrieved mainly based on the training dictionary samples;(2) the retrieval of the precipitation field of view, which uses inverse problem of regularization method to retrieve the infrared brightness temperatures precipitation on the basis of identifying the precipitation field of view. KNN distance measurement adopts Euclidean, normalized Euclidean, Mahalanobis and Cityblock respectively. Taking typhoon “Ampil (2018)”as an example, the precipitation retrieval experiment is carried out. The experiment shows that the retrieval result has a high similarity with GPM, and different distance measurements have their own advantages in the retrieval of "extreme precipitation".
keywords:FY-4A/AGRI  typhoon Ampil  precipitation retrieval  distance measurement  inverse problem of regularization
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