摘要: |
FY-3B TOU臭氧总量产品空间分辨率为50 km,在开展小区域或精细化的臭氧研究时,需要获得更高分辨率、更具有准确和可靠性的臭氧插值数据。常规的数据插值方法没有考虑TOU臭氧总量受短波辐射、海拔高度的影响,所得到的插值数据参考性不强。文中介绍TOU多元回归插值方法,方法采用程序设计方式,动态分析TOU与短波辐射、海拔高度之间的相关性,建立一元回归模型,并根据一元回归模型结构建立多元回归模型,再通过多元回归模型对TOU进行插值。使用OMI臭氧总量数据对插值结果开展验证,验证结果表明采用多元回归算法的插值具有较好的可行性。且该插值方法及程序设计对其他类似的数据插值、分析具有一定的借鉴和参考意义。 |
关键词: 臭氧总量;短波辐射;高程;OMI;多元回归模型;插值 |
DOI: |
投稿时间:2022-06-20修订日期:2023-01-02 |
基金项目:风云三号03批气象卫星工程地面应用系统2021年区域特色应用项目“山地生态气象遥感应用系统”(项目编号:FY-3(03)-AS-12.13) |
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Multivariate Regression Interpolation and Verification of FY-3B TOU Total Ozone |
tang hong xiang,hua meng ying,liao yao,hu feng,huang lin feng |
(Guizhou Provincial Center for Ecological Meteorology and Satellite Remote Sensing;Guizhou Food Engineering Vocational College) |
Abstract: |
The spatial resolution of FY-3B TOU total ozone product is 50 km,and it is necessary to obtain high-resolution, more accuracy and reliability total ozone interpolation data, when carrying out small area or refined ozone studies.Conventional data interpolation methods do not consider the influence of short wave radiation and altitude on the total ozone amount of TOU, and the interpolation data obtained are not highly referential. This paper introduces the multiple regression interpolation method of TOU. The method adopts the programming method to dynamically analyze the correlation between TOU and shortwave radiation, altitude, establish a single regression model, establish a multiple regression model according to the structure of the single regression model, and then interpolate TOU through the multiple regression model. The OMI ozone total data was used to verify the interpolation results, and the verification results showed that the interpolation using multiple regression algorithm was feasible. And the interpolation method and program design have certain reference significance for other similar data interpolation and analysis. |
Key words: total ozone; shortwave radiation; elevation; OMI; multiple regression model; interpolation |