A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation

He, Xinlei; Xu, Tongren; Xia, Youlong; Bateni, Sayed M.; Guo, Zhixia; Liu, Shaomin; Mao, Kebiao; Zhang, Yuan; Feng, Huaize; Zhao, Jingxue

doi:10.3390/rs12050878

i

A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation

2020
By He, Xinlei ; Xu, Tongren ; Xia, Youlong ; ...

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Journal Title:

Remote Sensing
Personal Author:

He, Xinlei ; Xu, Tongren ; Xia, Youlong ; Bateni, Sayed M. ; Guo, Zhixia ; Liu, Shaomin ; Mao, Kebiao ; Zhang, Yuan ; Feng, Huaize ; Zhao, Jingxue
NOAA Program & Office:

NCEP (National Centers for Environmental Prediction) ; NWS (National Weather Service)
Description:

In this study, a Bayesian-based three-cornered hat (BTCH) method is developed to improve the estimation of terrestrial evapotranspiration (ET) by integrating multisource ET products without using any a priori knowledge. Ten long-term (30 years) gridded ET datasets from statistical or empirical, remotely-sensed, and land surface models over contiguous United States (CONUS) are integrated by the BTCH and ensemble mean (EM) methods. ET observations from eddy covariance towers (ETEC) at AmeriFlux sites and ET values from the water balance method (ETWB) are used to evaluate the BTCH- and EM-integrated ET estimates. Results indicate that BTCH performs better than EM and all the individual parent products. Moreover, the trend of BTCH-integrated ET estimates, and their influential factors (e.g., air temperature, normalized differential vegetation index, and precipitation) from 1982 to 2011 are analyzed by the Mann–Kendall method. Finally, the 30-year (1982 to 2011) total water storage anomaly (TWSA) in the Mississippi River Basin (MRB) is retrieved based on the BTCH-integrated ET estimates. The TWSA retrievals in this study agree well with those from the Gravity Recovery and Climate Experiment (GRACE).
Keywords:

General Earth and Planetary Sciences
Source:

Remote Sensing, 12(5), 878
DOI:

https://doi.org/10.3390/rs12050878
ISSN:

2072-4292
Format:

PDF
Publisher:

MDPI AG
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha-512:c47b142572f463309d371fc2b73bb3d8b82e79f58d38942b8bac18863c62d8e1b534ce54bc901b1880f1c893021d1ccbc00a5949ba87817c7832920e65a43483
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https://repository.library.noaa.gov/view/noaa/63719/noaa_63719_DS1.pdf
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[PDF - 9.22 MB ]

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