Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations

文献类型： 外文期刊

第一作者： Yao, Yunjun

作者： Yao, Yunjun;Liang, Shunlin;Li, Xianglan;Cheng, Jie;Zhang, Xiaotong;Jiang, Bo;Jia, Kun;Feng, Fei;Liang, Shunlin;Hong, Yang;Hong, Yang;Hong, Yang;Fisher, Joshua B.;Zhang, Nannan;Chen, Jiquan;Zhao, Shaohua;Sun, Liang;Wang, Kaicun;Chen, Yang;Mu, Qiaozhen

作者机构：

关键词： latent heat flux;evapotranspiration;Bayesian model averaging method;simple model averaging method

期刊名称：JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES （ 影响因子：4.261； 五年影响因子：4.626 ）

ISSN： 2169-897X

年卷期： 2014 年 119 卷 8 期

页码：

收录情况： SCI

摘要： Accurate estimation of the satellite-based global terrestrial latent heat flux (LE) at high spatial and temporal scales remains a major challenge. In this study, we introduce a Bayesian model averaging (BMA) method to improve satellite-based global terrestrial LE estimation by merging five process-based algorithms. These are the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product algorithm, the revised remote-sensing-based Penman-Monteith LE algorithm, the Priestley-Taylor-based LE algorithm, the modified satellite-based Priestley-Taylor LE algorithm, and the semi-empirical Penman LE algorithm. We validated the BMA method using data for 2000-2009 and by comparison with a simple model averaging (SA) method and five process-based algorithms. Validation data were collected for 240 globally distributed eddy covariance tower sites provided by FLUXNET projects. The validation results demonstrate that the five process-based algorithms used have variable uncertainty and the BMA method enhances the daily LE estimates, with smaller root mean square errors (RMSEs) than the SA method and the individual algorithms driven by tower-specific meteorology and Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological data provided by the NASA Global Modeling and Assimilation Office (GMAO), respectively. The average RMSE for the BMA method driven by daily tower-specific meteorology decreased by more than 5 W/m(2) for crop and grass sites, and by more than 6 W/m(2) for forest, shrub, and savanna sites. The average coefficients of determination (R-2) increased by approximately 0.05 for most sites. To test the BMA method for regional mapping, we applied it for MODIS data and GMAO-MERRA meteorology to map annual global terrestrial LE averaged over 2001-2004 for spatial resolution of 0.05 degrees. The BMA method provides a basis for generating a long-term global terrestrial LE product for characterizing global energy, hydrological, and carbon cycles.

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