2012
DOI: 10.1029/2012jd017567
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Estimation of clear‐sky land surface longwave radiation from MODIS data products by merging multiple models

Abstract: [1] The surface longwave radiation budget plays an important role in the Earth's climate system. Remote sensing provides the most practical way to map surface longwave radiation on a large scale and at a high spatial resolution. In this paper, we evaluate both surface downward longwave radiation (DLR) and upwelling longwave radiation (ULR) models under clear-sky conditions from MODIS data products. There are multiple DLR models available with variable uncertainties, and the Bayesian Model Averaging (BMA) metho… Show more

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Cited by 60 publications
(55 citation statements)
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“…Multimodel ensemble approaches have therefore become increasing popular in climate change projections (Tebaldi et al , ; Yang et al , ), land surface component simulation (i.e. soil moisture, Guo et al , ; surface longwave radiation, Wu et al , ), groundwater assessment (Neuman, ), hydrologic streamflow predictions (Duan et al , ; Vrugt and Robinson, ; Zhang et al , ), and terrestrial ET estimation (Ershadi et al , ; Yao et al , ). With the ensemble techniques, the SA approach focused on point predictions, while the BMA approach was mainly concerned with producing bias‐corrected probabilistic forecasts (Diks and Vrugt, ).…”
Section: Discussionmentioning
confidence: 99%
“…Multimodel ensemble approaches have therefore become increasing popular in climate change projections (Tebaldi et al , ; Yang et al , ), land surface component simulation (i.e. soil moisture, Guo et al , ; surface longwave radiation, Wu et al , ), groundwater assessment (Neuman, ), hydrologic streamflow predictions (Duan et al , ; Vrugt and Robinson, ; Zhang et al , ), and terrestrial ET estimation (Ershadi et al , ; Yao et al , ). With the ensemble techniques, the SA approach focused on point predictions, while the BMA approach was mainly concerned with producing bias‐corrected probabilistic forecasts (Diks and Vrugt, ).…”
Section: Discussionmentioning
confidence: 99%
“…RF realizes the concept of ensemble learning from the group of regression trees through processes of boosting and bagging. An additional commonly used method, particularly in multimodel fusion, is Bayesian model averaging (BMA), which was implemented to optimize weights to integrate predictive distributions from multi-models such as the mapping of longwave radiative fluxes from multiple models (Raftery et al, 2005;H. Wu et al, 2012).…”
Section: The Data Fusion Methodsmentioning
confidence: 99%
“…The contribution of each individual model in the BMA method is weighted by its posterior weight of evidence (Ellison, 2004). BMA has been widely used to study the climate change (Duan and Phillips, 2010), improve the predictions accuracy of hydrology (Duan et al, 2007), weather (Raftery et al, 2005;Wu et al, 2012), forest biomass and economics (Fernandez et al, 2001). Previous studies indicated better estimations of BMA than other multi-model ensemble methods (Viallefont et al, 2001;Ellison, 2004;Raftery et al, 2005;Sloughter et al, 2007).…”
Section: Introductionmentioning
confidence: 99%