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气象:2018,44(6):844-849
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改进的FY-3B/VIRR OLR反演模式及其应用效果
吴晓,白文广,张婉春
(中国气象局中国遥感卫星辐射测量和定标重点开放实验室,北京 100081; 国家卫星气象中心, 北京 100081)
Improved FY-3B OLR Retrieval Model and Its Application Effect
WU Xiao,BAI Wenguang,ZHANG Wanchun
(Department of Statistics, College of Economics, Jinan University, Guangzhou 510632)
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投稿时间:2017-11-07    修订日期:2018-02-11
中文摘要: FY-3B卫星VIRR仪器的向外长波辐射(outgoing long wave radiation,OLR)产品处理采用与NOAA/AVHRR相同的算法模型,即用窗区通道亮温 通量等效亮度温度的回归关系式计算OLR,但两星的OLR业务产品与目前国际质量最好的云和地球辐射能量系统(cloud and earth’s radiant energy system,CERES)仪器观测OLR产品相比,存在约10 W·m-2的系统负偏差。FY-3B的原因在于OLR反演模式建立过程中红外辐射传输计算软件的精度不够。鉴于此,本文采用美国21世纪开发的逐线辐射传输模型计算软件(LBLRTM),模拟计算了全球2521条大气廓线的大气顶辐射率光谱,在此基础上计算了每条廓线的OLR和FY-3B/VIRR窗区通道亮温,应用最小二乘法统计回归模拟数据,重新建立了由FY 3B/VIRR窗区通道亮温计算OLR的回归关系式及系数。模式应用于FY-3B L1级数据,处理2016年1,3,7和10月的FY-3B逐日全球OLR资料,该资料与AQUA-TERRA卫星的CERES仪器OLR观测产品相比,得到日平均OLR:RMSE=9~15 W·m-2,R=0.9834,Bias=-0.3 W·m-2;月平均OLR:RMSE=4~7 W·m-2,R=0.9915,Bias=-0.3 W·m-2,表明改进的模式能处理出无系统偏差的、精度基本与CERES观测相当的OLR产品,尽管单通道反演算法有着固有的模式回归误差。
Abstract:The outgoing longwave radiation (OLR) product processing of FY 3B/VIRR adopts the same method as that used in NOAA/AVHRR, that is, the regression equation relating flux equivalent brightness temperature with window channel brightness temperature is used to calculate OLR. But the OLR products of the two satellites have a negative bias of 10 W·m-2 when compared with the clouds and earth’s radiant energy system (CERES) observed OLR product, which is considered the best OLR product in quality in the world. The cause for the FY 3B OLR bias is the lower accuracy of the software used in infrared radiative transfer model during the process of developing OLR retrieval model. Herein, with American line-by-line radiative transfer model software (LBLRTM) developed in 21st century, the spectral radiances at the top of atmosphere (TOA) for 2521 global atmospheric profiles are simulated, and then the OLR and window channel radiance of FY-3B/VIRR are calculated. By applying the least square method to sum up and regress the simulated data, this paper rebuilds the regression equation and coefficient of OLR, which are calculated by the FY 3B/VIRR window channel 5 brightness temperature. The FY-3B L1 data are applied to the model and the daily global OLR data in January, March, July, October of 2016 are processed out. Comparing the processed data with the CERES OLR products, the following results are obtained: daily averaged OLR: RMSE=9-15 W·m-2, R=0.9834, Bias=-0.3 W·m-2, monthly averaged OLR: RMSE=4-7 W·m-2, R=0.9915, Bias=-0.3 W·m-2. The validation results indicate that the improved model can work out the OLR data without systematic bias and the accuracy is basically similar with the CERES〖JP〗 observation although the inherent model regression error might exist in the single channel retrieval method.
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基金项目:中国气象局气象资料质量控制与多源数据融合与再分析攻关项目(GMAGGTD003-5)资助
引用文本:
吴晓,白文广,张婉春,2018.改进的FY-3B/VIRR OLR反演模式及其应用效果[J].气象,44(6):844-849.
WU Xiao,BAI Wenguang,ZHANG Wanchun,2018.Improved FY-3B OLR Retrieval Model and Its Application Effect[J].Meteor Mon,44(6):844-849.