Does ERA5 outperform satellite products in estimating atmospheric downward longwave radiation at the surface?
Does ERA5 outperform satellite products in estimating atmospheric downward longwave radiation at the surface?
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ERA5 在估算地表大气向下长波辐射方面是否优于卫星产品？
DOI：
10.1016/j.atmosres.2021.105453
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发表时间：
2021-04
影响因子：
5.5
通讯作者：
Xu Zhou
中科院分区：
文献类型：
--
作者：
Wenjun Tang;Jun Qin;Kun Yang;Fuxin Zhu;Xu Zhou
大气向下长波辐射(DLR)是地球系统地表能量收支的重要组成部分。卫星反演和大气再分析估算是获得时空连续DLR产品的两种典型方法。在这项研究中，我们对最新的ERA5大气再分析和著名的云和地球辐射能量系统(CERES)卫星反演的DLR产品进行了评估，并与46个地面基线地面辐射网络(BSRN)站和9个全球热带系泊浮标阵列(GTMBA)浮标站收集的高质量观测结果进行了对比。在每小时到每月的时间尺度上，ERA5 DLR产品在陆地上的平均精度高于CERES。相反，在估计海洋表面的DLR时，ERA5的表现略逊于CERES-SYN。这是大气再分析首次在估计陆地表面的DLR方面优于卫星反演，显示了ERA5潜在的广泛应用前景，同时也为定量遥感研究提出了新的挑战。
Atmospheric downward longwave radiation (DLR) is a key component of the surface energy budget in the Earth system. Satellite retrievals and atmospheric reanalysis estimates are the two typical approaches to obtaining a spatio-temporally continuous DLR product. In this study, we evaluated the DLR product from the latest ERA5 atmospheric reanalysis and the well-known Clouds and Earth's Radiant Energy System (CERES) satellite retrievals, against high-quality observations collected at 46 Baseline Surface Radiation Network (BSRN) stations over land surfaces and at 9 Global Tropical Moored Buoy Array (GTMBA) buoy stations. The accuracy of the ERA5 DLR product over land was found to be higher on average than that of CERES at hourly to monthly time scales. Conversely, ERA5 performed slightly worse than CERES-SYN when estimating DLR over the ocean surface. This is the first time that atmospheric reanalysis has performed better than satellite retrievals in estimating DLR over the land surface, demonstrating the potentially extensive application prospects for ERA5 as well as setting new challenges for quantitative remote sensing research.
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影响因子：
3
作者：
Shashi K. Gupta;D. Kratz;P. Stackhouse;A. C. Wilber;Taiping Zhang;Victor E. Sothcott
通讯作者：
Shashi K. Gupta;D. Kratz;P. Stackhouse;A. C. Wilber;Taiping Zhang;Victor E. Sothcott
根据导出的主动和被动云属性参数估计多云天空表面向下长波辐射的框架
影响因子：
13.5
作者：
Yang Feng;Cheng Jie
通讯作者：
Cheng Jie
DOI：
10.1002/joc.6408
发表时间：
2019-12
期刊：
International Journal of Climatology
影响因子：
--
作者：
Zhigao Zhou;A. Lin;Lunche Wang;Wenmin Qin;Yang Zhong;Lijie He
通讯作者：
Zhigao Zhou;A. Lin;Lunche Wang;Wenmin Qin;Yang Zhong;Lijie He
影响因子：
--
作者：
Kaicun Wang;S. Liang
通讯作者：
Kaicun Wang;S. Liang
影响因子：
4.9
作者：
Shashi K. Gupta
通讯作者：
Shashi K. Gupta