The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0

Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias correction approach into the Community Land Model vers...

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Autores principales:	Dayang Wang, Dagang Wang, Chongxun Mo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	remote sensing evapotranspiration community land model bias correction Science Q
Acceso en línea:	https://doaj.org/article/bda2198d134646fe9754d65845d480d4
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spelling	oai:doaj.org-article:bda2198d134646fe9754d65845d480d42021-11-11T18:58:06ZThe Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.010.3390/rs132144602072-4292https://doaj.org/article/bda2198d134646fe9754d65845d480d42021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4460https://doaj.org/toc/2072-4292Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias correction approach into the Community Land Model version 5.0 (CLM5) globally by utilizing the remote sensing-based ET dataset. Results reveal that the correction approach can alleviate both overestimation and underestimation of ET by CLM5 over the globe. The adjustment to overestimation is generally effective, whereas the effectiveness for underestimation is determined by the ET regime, namely water-limited or energy-limited. In the areas with abundant precipitation, the underestimation is effectively corrected by increasing ET without the water supply limit. In areas with rare precipitation, however, increasing ET is limited by water supply, which leads to an undesirable correction effect. Compared with the ET simulated by CLM5, the bias correction approach can reduce the global-averaged relative bias (RB) and the root mean square error (RMSE) by 51.8% and 65.9% against Global Land Evaporation Amsterdam Model (GLEAM) ET data, respectively. Meanwhile, the correlation coefficient (CC) can also be improved from 0.93 to 0.98. Continentally, the most substantial ET improvement occurs in Asia, with the RB and RMSE decreased by 69.7% (from 7.04% to 2.14%) and 70.2% (from 0.312 mm day<sup>−1</sup> to 0.093 mm day<sup>−1</sup>, equivalent to from 114 mm year<sup>−1</sup> to 34 mm year<sup>−1</sup>), and the CC increased from 0.92 to 0.99, respectively. Consequently, benefiting from the improvement of ET, the simulations of runoff and soil moisture are also improved over the globe and each of the six continents, and the improvement varies with region. This study demonstrates that the use of satellite-based ET products is beneficial to hydrological simulations in land surface models over the globe.Dayang WangDagang WangChongxun MoMDPI AGarticleremote sensingevapotranspirationcommunity land modelbias correctionScienceQENRemote Sensing, Vol 13, Iss 4460, p 4460 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	remote sensing evapotranspiration community land model bias correction Science Q
spellingShingle	remote sensing evapotranspiration community land model bias correction Science Q Dayang Wang Dagang Wang Chongxun Mo The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
description	Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias correction approach into the Community Land Model version 5.0 (CLM5) globally by utilizing the remote sensing-based ET dataset. Results reveal that the correction approach can alleviate both overestimation and underestimation of ET by CLM5 over the globe. The adjustment to overestimation is generally effective, whereas the effectiveness for underestimation is determined by the ET regime, namely water-limited or energy-limited. In the areas with abundant precipitation, the underestimation is effectively corrected by increasing ET without the water supply limit. In areas with rare precipitation, however, increasing ET is limited by water supply, which leads to an undesirable correction effect. Compared with the ET simulated by CLM5, the bias correction approach can reduce the global-averaged relative bias (RB) and the root mean square error (RMSE) by 51.8% and 65.9% against Global Land Evaporation Amsterdam Model (GLEAM) ET data, respectively. Meanwhile, the correlation coefficient (CC) can also be improved from 0.93 to 0.98. Continentally, the most substantial ET improvement occurs in Asia, with the RB and RMSE decreased by 69.7% (from 7.04% to 2.14%) and 70.2% (from 0.312 mm day<sup>−1</sup> to 0.093 mm day<sup>−1</sup>, equivalent to from 114 mm year<sup>−1</sup> to 34 mm year<sup>−1</sup>), and the CC increased from 0.92 to 0.99, respectively. Consequently, benefiting from the improvement of ET, the simulations of runoff and soil moisture are also improved over the globe and each of the six continents, and the improvement varies with region. This study demonstrates that the use of satellite-based ET products is beneficial to hydrological simulations in land surface models over the globe.
format	article
author	Dayang Wang Dagang Wang Chongxun Mo
author_facet	Dayang Wang Dagang Wang Chongxun Mo
author_sort	Dayang Wang
title	The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
title_short	The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
title_full	The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
title_fullStr	The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
title_full_unstemmed	The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0
title_sort	use of remote sensing-based et estimates to improve global hydrological simulations in the community land model version 5.0
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bda2198d134646fe9754d65845d480d4
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The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0

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