File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Estimation of high-spatial resolution clear-sky longwave downward and net radiation over land surfaces from MODIS data

TitleEstimation of high-spatial resolution clear-sky longwave downward and net radiation over land surfaces from MODIS data
Authors
KeywordsMODIS
Remote sensing
Surface downwelling longwave radiation
Surface net longwave radiation
Surface radiation budget
Issue Date2009
Citation
Remote Sensing of Environment, 2009, v. 113, n. 4, p. 745-754 How to Cite?
AbstractSurface downwelling longwave radiation (LWDN) and surface net longwave radiation (LWNT) are two components in the surface radiation budget. In this study, we developed new linear and nonlinear models using a hybrid method to derive instantaneous clear-sky LWDN over land from the Moderate Resolution Imaging Spectroradiometer (MODIS) TOA radiance at 1 km spatial resolution. The hybrid method is based on extensive radiative transfer simulation (physical) and statistical analysis (statistical). Linear and nonlinear models were derived at 5 sensor view zenith angles (0°, 15°, 30°, 45°, and 60°) to estimated LWDN using channels 27-29 and 31-34. Separate models were developed for daytime and nighttime observations. Surface pressure effect was considered by incorporating elevation in the models. The linear LWDN models account for more than 92% of variations of the simulated data sets, with standard errors less than 16.27 W/m2 for all sensor view zenith angles. The nonlinear LWDN models explain more than 93% of variations, with standard errors less than 15.20 W/m2. The linear and nonlinear LWDN models were applied to both Terra and Aqua TOA radiance and validated using ground data from six SURFRAD sites. The nonlinear models outperform the linear models at five sites. The averaged root mean squared errors (RMSE) of the nonlinear models are 17.60 W/m2 (Terra) and 16.17 W/m2 (Aqua), with averaged RMSE ~ 2.5 W/m2 smaller than that of the linear models. LWNT was estimated using the nonlinear LWDN models and the artificial neural network (ANN) model method that predicts surface upwelling longwave radiation. LWNT was also validated using the same six SURFRAD sites. The averaged RMSEs are 17.72 (Terra) and 16.88 (Aqua) W/m2; the averaged biases are - 2.08 (Terra) and 1.99 (Aqua) W/m2. The LWNT RMSEs are less than 20 W/m2 for both Terra and Aqua observations at all sites. © 2008 Elsevier Inc.
Persistent Identifierhttp://hdl.handle.net/10722/321367
ISSN
2021 Impact Factor: 13.850
2020 SCImago Journal Rankings: 3.611

 

DC FieldValueLanguage
dc.contributor.authorWang, Wenhui-
dc.contributor.authorLiang, Shunlin-
dc.date.accessioned2022-11-03T02:18:26Z-
dc.date.available2022-11-03T02:18:26Z-
dc.date.issued2009-
dc.identifier.citationRemote Sensing of Environment, 2009, v. 113, n. 4, p. 745-754-
dc.identifier.issn0034-4257-
dc.identifier.urihttp://hdl.handle.net/10722/321367-
dc.description.abstractSurface downwelling longwave radiation (LWDN) and surface net longwave radiation (LWNT) are two components in the surface radiation budget. In this study, we developed new linear and nonlinear models using a hybrid method to derive instantaneous clear-sky LWDN over land from the Moderate Resolution Imaging Spectroradiometer (MODIS) TOA radiance at 1 km spatial resolution. The hybrid method is based on extensive radiative transfer simulation (physical) and statistical analysis (statistical). Linear and nonlinear models were derived at 5 sensor view zenith angles (0°, 15°, 30°, 45°, and 60°) to estimated LWDN using channels 27-29 and 31-34. Separate models were developed for daytime and nighttime observations. Surface pressure effect was considered by incorporating elevation in the models. The linear LWDN models account for more than 92% of variations of the simulated data sets, with standard errors less than 16.27 W/m2 for all sensor view zenith angles. The nonlinear LWDN models explain more than 93% of variations, with standard errors less than 15.20 W/m2. The linear and nonlinear LWDN models were applied to both Terra and Aqua TOA radiance and validated using ground data from six SURFRAD sites. The nonlinear models outperform the linear models at five sites. The averaged root mean squared errors (RMSE) of the nonlinear models are 17.60 W/m2 (Terra) and 16.17 W/m2 (Aqua), with averaged RMSE ~ 2.5 W/m2 smaller than that of the linear models. LWNT was estimated using the nonlinear LWDN models and the artificial neural network (ANN) model method that predicts surface upwelling longwave radiation. LWNT was also validated using the same six SURFRAD sites. The averaged RMSEs are 17.72 (Terra) and 16.88 (Aqua) W/m2; the averaged biases are - 2.08 (Terra) and 1.99 (Aqua) W/m2. The LWNT RMSEs are less than 20 W/m2 for both Terra and Aqua observations at all sites. © 2008 Elsevier Inc.-
dc.languageeng-
dc.relation.ispartofRemote Sensing of Environment-
dc.subjectMODIS-
dc.subjectRemote sensing-
dc.subjectSurface downwelling longwave radiation-
dc.subjectSurface net longwave radiation-
dc.subjectSurface radiation budget-
dc.titleEstimation of high-spatial resolution clear-sky longwave downward and net radiation over land surfaces from MODIS data-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rse.2008.12.004-
dc.identifier.scopuseid_2-s2.0-60749097764-
dc.identifier.volume113-
dc.identifier.issue4-
dc.identifier.spage745-
dc.identifier.epage754-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats