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Article: Estimating high spatial resolution clear-sky land surface upwelling longwave radiation from MODIS data

TitleEstimating high spatial resolution clear-sky land surface upwelling longwave radiation from MODIS data
Authors
KeywordsModerate Resolution Imaging Spectroradiometer (MODIS)
Neural networks
Remote sensing
Satellite applications
Surface radiation budget (SRB)
Surface upwelling longwave radiation (LWUP)
Issue Date2009
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2009, v. 47, n. 5, p. 1559-1570 How to Cite?
AbstractSurface upwelling longwave radiation (LWUP) is an important component in the surface radiation budget. Existing satellite-derived LWUP data sets are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this paper, we evaluate three methods for estimating clear-sky land LWUP from the Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1-km spatial resolution. The three methods are as follows: 1) the temperature-emissivity method; 2) the linear model method; and 3) the artificial neural network (ANN) model method. Methods 2 and 3 are new methods based on extensive radiative transfer simulations and statistical analysis. We explicitly considered surface emissivity effects by incorporating the University of California Santa Barbara emissivity library in the radiative transfer simulation. The three methods were evaluated using ground-measured LWUP from six SURFRAD sites. Although methods 2 and 3 were developed using MODIS Terra atmospheric profiles, they were applied to both Terra and Aqua data because the designs of the two sensors are similar. The root mean squared errors (rmses) of the ANN model method are smaller than that of the other two methods at all sites. The averaged rmses of the ANN model method are 15.89 W/m2 (Terra) and 14.57 W/m2 (Aqua); the averaged biases are -8.67 W/m 2 (Terra) and -7.21 W/m2 (Aqua). The biases and rmses for Aqua are sim1.3 W/m2 smaller than that of Terra. The biases and rmses of the ANN model method are sim5 W/m2 smaller than that of the temperature-emissivity method and sim2.5 W/m2 smaller than that of the linear model method. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/321372
ISSN
2021 Impact Factor: 8.125
2020 SCImago Journal Rankings: 2.141

 

DC FieldValueLanguage
dc.contributor.authorWang, Wenhui-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorAugustine, John A.-
dc.date.accessioned2022-11-03T02:18:28Z-
dc.date.available2022-11-03T02:18:28Z-
dc.date.issued2009-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2009, v. 47, n. 5, p. 1559-1570-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/321372-
dc.description.abstractSurface upwelling longwave radiation (LWUP) is an important component in the surface radiation budget. Existing satellite-derived LWUP data sets are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this paper, we evaluate three methods for estimating clear-sky land LWUP from the Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1-km spatial resolution. The three methods are as follows: 1) the temperature-emissivity method; 2) the linear model method; and 3) the artificial neural network (ANN) model method. Methods 2 and 3 are new methods based on extensive radiative transfer simulations and statistical analysis. We explicitly considered surface emissivity effects by incorporating the University of California Santa Barbara emissivity library in the radiative transfer simulation. The three methods were evaluated using ground-measured LWUP from six SURFRAD sites. Although methods 2 and 3 were developed using MODIS Terra atmospheric profiles, they were applied to both Terra and Aqua data because the designs of the two sensors are similar. The root mean squared errors (rmses) of the ANN model method are smaller than that of the other two methods at all sites. The averaged rmses of the ANN model method are 15.89 W/m2 (Terra) and 14.57 W/m2 (Aqua); the averaged biases are -8.67 W/m 2 (Terra) and -7.21 W/m2 (Aqua). The biases and rmses for Aqua are sim1.3 W/m2 smaller than that of Terra. The biases and rmses of the ANN model method are sim5 W/m2 smaller than that of the temperature-emissivity method and sim2.5 W/m2 smaller than that of the linear model method. © 2006 IEEE.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectModerate Resolution Imaging Spectroradiometer (MODIS)-
dc.subjectNeural networks-
dc.subjectRemote sensing-
dc.subjectSatellite applications-
dc.subjectSurface radiation budget (SRB)-
dc.subjectSurface upwelling longwave radiation (LWUP)-
dc.titleEstimating high spatial resolution clear-sky land surface upwelling longwave radiation from MODIS data-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2008.2005206-
dc.identifier.scopuseid_2-s2.0-67349183337-
dc.identifier.volume47-
dc.identifier.issue5-
dc.identifier.spage1559-
dc.identifier.epage1570-

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