globalchange  > 气候减缓与适应
DOI: 10.1002/2017JD027732
Scopus记录号: 2-s2.0-85042625175
论文题名:
Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework
作者: Xu T.; Bateni S.M.; Neale C.M.U.; Auligne T.; Liu S.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期:5
起始页码: 2409
结束页码: 2423
语种: 英语
英文关键词: data assimilation ; evaporative fraction ; evapotranspiration ; land surface temperature ; neutral bulk heat transfer coefficient ; uncertainty
英文摘要: In different studies, land surface temperature (LST) observations have been assimilated into the variational data assimilation (VDA) approaches to estimate turbulent heat fluxes. The VDA methods yield accurate turbulent heat fluxes, but they need an adjoint model, which is difficult to derive and code. They also cannot directly calculate the uncertainty of their estimates. To overcome the abovementioned drawbacks, this study assimilates LST data from Geostationary Operational Environmental Satellite into the ensemble Kalman smoother (EnKS) data assimilation system to estimate turbulent heat fluxes. EnKS does not need to derive the adjoint term and directly generates statistical information on the accuracy of its predictions. It uses the heat diffusion equation to simulate LST. EnKS with the state augmentation approach finds the optimal values for the unknown parameters (i.e., evaporative fraction and neutral bulk heat transfer coefficient, CHN) by minimizing the misfit between LST observations from Geostationary Operational Environmental Satellite and LST estimations from the heat diffusion equation. The augmented EnKS scheme is tested over six Ameriflux sites with a wide range of hydrological and vegetative conditions. The results show that EnKS can predict not only the model parameters and turbulent heat fluxes but also their uncertainties over a variety of land surface conditions. Compared to the variational method, EnKS yields suboptimal turbulent heat fluxes. However, suboptimality of EnKS is small, and its results are comparable to those of the VDA method. Overall, EnKS is a feasible and reliable method for estimation of turbulent heat fluxes. ©2018. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114288
Appears in Collections:气候减缓与适应

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作者单位: State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China; Department of Civil and Environmental Engineering and Water Resources Research Center, University of Hawai'i at Mānoa, Honolulu, HI, United States; Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE, United States; Joint Center for Satellite Data Assimilation (JCSDA), College ParkMD, United States; University Corporation for Atmospheric Research (UCAR), Boulder, CO, United States

Recommended Citation:
Xu T.,Bateni S.M.,Neale C.M.U.,et al. Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(5)
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