基于K 最近邻模型的青藏高原CMORPH日降水数据的订正研究

doi:10.11873/j.issn.1004-0323.2016.3.0607

遥感技术与应用

2016, Vol. 31

Issue (3): 607-616 DOI: 10.11873/j.issn.1004-0323.2016.3.0607

遥感应用

基于K 最近邻模型的青藏高原CMORPH日降水数据的订正研究

王玉丹^１,２,南卓铜^３,陈浩^４,吴小波^１

(１．中国科学院寒区旱区环境与工程研究所,甘肃兰州　７３００００;２．中国科学院大学,北京　１０００４９;
３．南京师范大学地理科学学院,江苏南京　２１００２３;４．宝鸡文理学院,陕西宝鸡　７２１０１３)

Correction of CMORPH Daily Precipitation Data over the Qinghai-Tibetan Plateau with K-Nearest Neighbor Model

Wang Yudan^1,2,Nan Zhuotong³,Chen Hao⁴,Wu Xiaobo¹

(1.Cold and Arid Regions Environmental and Engineering Research Institute,
Chinese Academy of Sciences,Lanzhou 730000,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China;
3.School of Geography Science,Nanjing Normal University,Nanjing 210023,China;
4.Baoji University of Science and Art,Baoji 721013,China)

全文: PDF(11395 KB)

摘要：

青藏高原的降水数据主要由遥感产品和多源观测数据融合产生,由于青藏高原的观测站点分布稀疏不均,遥感数据误差较大,因此常用的CMORPH(ClimatePredictionCenter Morphing Technique)等降水数据集精度有限.通过K 最近邻(KＧNearestNeighbor,简称KNN)模型,可以建立环境(海拔、坡度、坡向、植被)、气象因子(气温、湿度、风速)和日降水量的关系,从而订正青藏高原的CMORPH 日降水数据集,提高数据精度.对CMORPH 日降水数据的误差分析表明,采用KNN 模型订正后的CMORPH 降水数据优于原始数据和采用PDF(ProbabilityDensityFunctionMatchingMethod)法订正的CMORPH 数据,且空间分布较好地符合青藏高原的降水分布特征.

关键词： 最近邻模型; 降水数据; CMORPH; 青藏高原

Abstract:

Precipitation data of the Qinghai\|Tibetan Plateau(QTP)are generally fused from multiple source remote sensing products and observation data.While the meteorological observations on the QTP are scarcely and unevenly distributed,the commonly used precipitation datasets,such as CMORPH(Climate Prediction Center Morphing Technique)bear fairly large errors.In this paper the K\|Nearest Neighbor(KNN)model was applied for correcting CMORPH daily precipitation over the QTP by establishing the relationship between daily precipitation and environmental,such as elevation,slope,aspect,and vegetation,and meteorological factors such as air temperature,humidity,and wind speed.The results show that the KNN\|corrected CMORPH precipitation is more accurate than both the original CMORPH precipitation and the PDF\|corrected results which were processed with a probability density function matching method and are available for downloading on the official Web site of Chinese Meteorological Administration.Examination of typical regions shows the KNN\|corrected results well represent the characteristics of precipitation distribution over the QTP.

Key words: KNN model;Precipitation data;CMORPH;The Qinghai\ Tibetan Plateau

收稿日期: 2016-01-15 出版日期: 2016-07-19

TP７９　

基金资助:

国家自然科学基金面上项目(４１４７１０５９),宝鸡文理学院博士启动费项目(ZK１６０６５).

通讯作者: 南卓铜(１９７７－),男,浙江乐清人,教授,主要从事陆表过程集成建模、科学数据共享等研究.Email:nanzt＠njnu．edu．cn.

作者简介: 王玉丹(１９８９－),女,河南洛阳人,硕士研究生,主要从事遥感与地理信息研究.Email:wydan＠lzb．ac．cn.

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引用本文:

王玉丹,南卓铜,陈浩,吴小波. 基于K 最近邻模型的青藏高原CMORPH日降水数据的订正研究[J]. 遥感技术与应用, 2016, 31(3): 607-616.

Wang Yudan,Nan Zhuotong,Chen Hao,Wu Xiaobo. Correction of CMORPH Daily Precipitation Data over the Qinghai-Tibetan Plateau with K-Nearest Neighbor Model. Remote Sensing Technology and Application, 2016, 31(3): 607-616.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.3.0607 或 http://www.rsta.ac.cn/CN/Y2016/V31/I3/607

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