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Article: Estimation of all-sky instantaneous surface incident shortwave radiation from Moderate Resolution Imaging Spectroradiometer data using optimization method

TitleEstimation of all-sky instantaneous surface incident shortwave radiation from Moderate Resolution Imaging Spectroradiometer data using optimization method
Authors
KeywordsAerosol optical depth
Cloud optical depth
Incident shortwave radiation
Optimization
Issue Date2018
Citation
Remote Sensing of Environment, 2018, v. 209, p. 468-479 How to Cite?
AbstractSurface incident shortwave radiation (ISR) is a crucial parameter in the land surface radiation budget. Many reanalysis, observation-based, and satellite-derived global radiation products have been developed but often have insufficient accuracy and spatial resolution for many applications. In this paper, we propose a method based on a radiative transfer model for estimating surface ISR from Moderate Resolution Imaging Spectroradiometer (MODIS) Top of Atmosphere (TOA) observations by optimizing the surface and atmospheric variables with a cost function. This approach consisted of two steps: retrieving surface bidirectional reflectance distribution function parameters, aerosol optical depth (AOD), and cloud optical depth (COD); and subsequently calculating surface ISR. Validation against measurements at seven Surface Radiation Budget Network (SURFRAD) sites resulted in an R2 of 0.91, a bias of −6.47 W/m2, and a root mean square error (RMSE) of 84.17 W/m2 (15.12%) for the instantaneous results. Validation at eight high-latitude snow-covered Greenland Climate Network (GC-Net) sites resulted in an R2 of 0.86, a bias of −21.40 W/m2, and an RMSE of 84.77 W/m2 (20.96%). These validation results show that the proposed method is much more accurate than the previous studies (usually with RMSEs of 80-150 W/m2). We further investigated whether incorporating additional satellite products, such as the MODIS surface broadband albedo (MCD43), aerosol (MOD/MYD04), and cloud products (MOD/MYD06), as constraints in the cost function would improve the accuracy. When the AOD and COD estimates were constrained, RMSEs were reduced to 62.19 W/m2 (12.12%) and 71.70 W/m2 (17.74%) at the SURFRAD and GC-Net sites, respectively. This algorithm could estimate surface ISR with MODIS TOA observations over both snow-free and seasonal/permanent snow-covered surfaces. The algorithm performed well at high-latitude sites, which is very useful for radiation budget research in the polar regions.
Persistent Identifierhttp://hdl.handle.net/10722/322047
ISSN
2021 Impact Factor: 13.850
2020 SCImago Journal Rankings: 3.611
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Yi-
dc.contributor.authorHe, Tao-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorWang, Dongdong-
dc.contributor.authorYu, Yunyue-
dc.date.accessioned2022-11-03T02:23:14Z-
dc.date.available2022-11-03T02:23:14Z-
dc.date.issued2018-
dc.identifier.citationRemote Sensing of Environment, 2018, v. 209, p. 468-479-
dc.identifier.issn0034-4257-
dc.identifier.urihttp://hdl.handle.net/10722/322047-
dc.description.abstractSurface incident shortwave radiation (ISR) is a crucial parameter in the land surface radiation budget. Many reanalysis, observation-based, and satellite-derived global radiation products have been developed but often have insufficient accuracy and spatial resolution for many applications. In this paper, we propose a method based on a radiative transfer model for estimating surface ISR from Moderate Resolution Imaging Spectroradiometer (MODIS) Top of Atmosphere (TOA) observations by optimizing the surface and atmospheric variables with a cost function. This approach consisted of two steps: retrieving surface bidirectional reflectance distribution function parameters, aerosol optical depth (AOD), and cloud optical depth (COD); and subsequently calculating surface ISR. Validation against measurements at seven Surface Radiation Budget Network (SURFRAD) sites resulted in an R2 of 0.91, a bias of −6.47 W/m2, and a root mean square error (RMSE) of 84.17 W/m2 (15.12%) for the instantaneous results. Validation at eight high-latitude snow-covered Greenland Climate Network (GC-Net) sites resulted in an R2 of 0.86, a bias of −21.40 W/m2, and an RMSE of 84.77 W/m2 (20.96%). These validation results show that the proposed method is much more accurate than the previous studies (usually with RMSEs of 80-150 W/m2). We further investigated whether incorporating additional satellite products, such as the MODIS surface broadband albedo (MCD43), aerosol (MOD/MYD04), and cloud products (MOD/MYD06), as constraints in the cost function would improve the accuracy. When the AOD and COD estimates were constrained, RMSEs were reduced to 62.19 W/m2 (12.12%) and 71.70 W/m2 (17.74%) at the SURFRAD and GC-Net sites, respectively. This algorithm could estimate surface ISR with MODIS TOA observations over both snow-free and seasonal/permanent snow-covered surfaces. The algorithm performed well at high-latitude sites, which is very useful for radiation budget research in the polar regions.-
dc.languageeng-
dc.relation.ispartofRemote Sensing of Environment-
dc.subjectAerosol optical depth-
dc.subjectCloud optical depth-
dc.subjectIncident shortwave radiation-
dc.subjectOptimization-
dc.titleEstimation of all-sky instantaneous surface incident shortwave radiation from Moderate Resolution Imaging Spectroradiometer data using optimization method-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rse.2018.02.052-
dc.identifier.scopuseid_2-s2.0-85042935832-
dc.identifier.volume209-
dc.identifier.spage468-
dc.identifier.epage479-
dc.identifier.isiWOS:000430897300034-

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