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Article: MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley-Taylor algorithm

TitleMODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley-Taylor algorithm
Authors
KeywordsChina
Evapotranspiration
Latent heat flux
MODIS
Priestley-Taylor
Issue Date2013
Citation
Agricultural and Forest Meteorology, 2013, v. 171-172, p. 187-202 How to Cite?
AbstractBecause of China's large size, satellite observations are necessary for estimation of the land surface latent heat flux (LE). We describe here a satellite-driven Priestley-Taylor (PT)-based algorithm constrained by the Normalized Difference Vegetation Index (NDVI) and Apparent Thermal Inertia (ATI) derived from temperature change over time. We compare to the satellite-driven PT-based approach, PT-JPL, and validate both models using data collected from 16 eddy covariance flux towers in China. Like PT-JPL, our proposed algorithm avoids the computational complexities of aerodynamic resistance parameters. We run the algorithms with monthly Moderate Resolution Imaging Spectroradiometer (MODIS) products (0.05° resolution), including albedo, Land Surface Temperature (LST), surface emissivity, and NDVI; and, Insolation from the Japan Aerospace Exploration Agency (JAXA). We find good agreement between our estimates of monthly LE and field-measured LE, with respective Root Mean Square Error (RMSE) and bias differences of 12.5Wm-2 and -6.4Wm-2. As compared with PT-JPL, our proposed algorithm has higher correlations with ground-measurements. Between 2001 and 2010, LE shows generally negative trends in most regions of China, though positive LE trends occur over 39% of the region, primarily in Northeast, North and South China. Our results indicate that the variations of terrestrial LE are responding to large-scale droughts and afforestation caused by human activity with direct links to terrestrial energy exchange, both spatially and temporally. © 2012 Elsevier B.V.
Persistent Identifierhttp://hdl.handle.net/10722/321507
ISSN
2023 Impact Factor: 5.6
2023 SCImago Journal Rankings: 1.677
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYao, Yunjun-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorCheng, Jie-
dc.contributor.authorLiu, Shaomin-
dc.contributor.authorFisher, Joshua B.-
dc.contributor.authorZhang, Xudong-
dc.contributor.authorJia, Kun-
dc.contributor.authorZhao, Xiang-
dc.contributor.authorQin, Qiming-
dc.contributor.authorZhao, Bin-
dc.contributor.authorHan, Shijie-
dc.contributor.authorZhou, Guangsheng-
dc.contributor.authorZhou, Guoyi-
dc.contributor.authorLi, Yuelin-
dc.contributor.authorZhao, Shaohua-
dc.date.accessioned2022-11-03T02:19:22Z-
dc.date.available2022-11-03T02:19:22Z-
dc.date.issued2013-
dc.identifier.citationAgricultural and Forest Meteorology, 2013, v. 171-172, p. 187-202-
dc.identifier.issn0168-1923-
dc.identifier.urihttp://hdl.handle.net/10722/321507-
dc.description.abstractBecause of China's large size, satellite observations are necessary for estimation of the land surface latent heat flux (LE). We describe here a satellite-driven Priestley-Taylor (PT)-based algorithm constrained by the Normalized Difference Vegetation Index (NDVI) and Apparent Thermal Inertia (ATI) derived from temperature change over time. We compare to the satellite-driven PT-based approach, PT-JPL, and validate both models using data collected from 16 eddy covariance flux towers in China. Like PT-JPL, our proposed algorithm avoids the computational complexities of aerodynamic resistance parameters. We run the algorithms with monthly Moderate Resolution Imaging Spectroradiometer (MODIS) products (0.05° resolution), including albedo, Land Surface Temperature (LST), surface emissivity, and NDVI; and, Insolation from the Japan Aerospace Exploration Agency (JAXA). We find good agreement between our estimates of monthly LE and field-measured LE, with respective Root Mean Square Error (RMSE) and bias differences of 12.5Wm-2 and -6.4Wm-2. As compared with PT-JPL, our proposed algorithm has higher correlations with ground-measurements. Between 2001 and 2010, LE shows generally negative trends in most regions of China, though positive LE trends occur over 39% of the region, primarily in Northeast, North and South China. Our results indicate that the variations of terrestrial LE are responding to large-scale droughts and afforestation caused by human activity with direct links to terrestrial energy exchange, both spatially and temporally. © 2012 Elsevier B.V.-
dc.languageeng-
dc.relation.ispartofAgricultural and Forest Meteorology-
dc.subjectChina-
dc.subjectEvapotranspiration-
dc.subjectLatent heat flux-
dc.subjectMODIS-
dc.subjectPriestley-Taylor-
dc.titleMODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley-Taylor algorithm-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.agrformet.2012.11.016-
dc.identifier.scopuseid_2-s2.0-84874249456-
dc.identifier.volume171-172-
dc.identifier.spage187-
dc.identifier.epage202-
dc.identifier.isiWOS:000316513000018-

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