Sub-Grid Representation of Vegetation Cover in Land Surface Schemes Improves the Modeling of How Climate Responds to Deforestation

Yingzuo Qin; Dashan Wang; Ye’er Cao; Xitian Cai; Shijing Liang; Hylke Beck; Zhenzhong Zeng

doi:10.1029/2023gl104164

Sub-Grid Representation of Vegetation Cover in Land Surface Schemes Improves the Modeling of How Climate Responds to Deforestation

Yingzuo Qin, Dashan Wang, Ye’er Cao, Xitian Cai, Shijing Liang, Hylke Beck, Zhenzhong Zeng

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Understanding the regional climate response to land cover change requires a realistic sub-grid representation of vegetation cover in the land surface scheme (LSS) of climate models. The Community Land Model (CLM) is considered one of the most advanced LSSs; however, when coupled with the Weather Research and Forecasting (WRF) model, the tiling vegetation cover approach was deactivated. Here, we reactivated the theoretical sub-grid vegetation cover representation in WRF-CLM and applied it to assess the impacts of deforestation on regional climate in the Southeast Asian Massif region. We found that CLM-tiling performs more accurate simulations of surface air temperature and precipitation compared to other LSSs using the in situ observations. Importantly, CLM-tiling successfully captures the theoretical sensitivity of evapotranspiration (ET) and temperature to sub-grid deforestation, aligning with Noah-mosaic, and it substantially improves the spatial pattern responses of simulated ET and temperature to regional deforestation.

Original language	English (US)
Journal	Geophysical Research Letters
Volume	50
Issue number	15
DOIs	https://doi.org/10.1029/2023gl104164
State	Published - Aug 2 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-08-07
Acknowledgements: This study was supported by the National Natural Science Foundation of China (42071022, 42001321) and the startup fund provided by the Southern University of Science and Technology (29/Y01296002, 29/Y01296122, 29/Y01296222). We thank the Center for Computational Science and Engineering at the Southern University of Science and Technology for providing computing resources. We acknowledge the anonymous reviewers for their detailed and helpful comments on the original manuscript. We thank the editor Guiling Wang for her valuable guidance and input, which greatly improved this manuscript.

ASJC Scopus subject areas

Geophysics
General Earth and Planetary Sciences

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1029/2023gl104164

https://repository.kaust.edu.sa/bitstream/10754/693473/1/Geophysical%20Research%20Letters%20-%202023%20-%20Qin.pdf

Cite this

@article{35dde6c5375f4ea88ed1ca290941ccf2,

title = "Sub-Grid Representation of Vegetation Cover in Land Surface Schemes Improves the Modeling of How Climate Responds to Deforestation",

abstract = "Understanding the regional climate response to land cover change requires a realistic sub-grid representation of vegetation cover in the land surface scheme (LSS) of climate models. The Community Land Model (CLM) is considered one of the most advanced LSSs; however, when coupled with the Weather Research and Forecasting (WRF) model, the tiling vegetation cover approach was deactivated. Here, we reactivated the theoretical sub-grid vegetation cover representation in WRF-CLM and applied it to assess the impacts of deforestation on regional climate in the Southeast Asian Massif region. We found that CLM-tiling performs more accurate simulations of surface air temperature and precipitation compared to other LSSs using the in situ observations. Importantly, CLM-tiling successfully captures the theoretical sensitivity of evapotranspiration (ET) and temperature to sub-grid deforestation, aligning with Noah-mosaic, and it substantially improves the spatial pattern responses of simulated ET and temperature to regional deforestation.",

author = "Yingzuo Qin and Dashan Wang and Ye{\textquoteright}er Cao and Xitian Cai and Shijing Liang and Hylke Beck and Zhenzhong Zeng",

note = "KAUST Repository Item: Exported on 2023-08-07 Acknowledgements: This study was supported by the National Natural Science Foundation of China (42071022, 42001321) and the startup fund provided by the Southern University of Science and Technology (29/Y01296002, 29/Y01296122, 29/Y01296222). We thank the Center for Computational Science and Engineering at the Southern University of Science and Technology for providing computing resources. We acknowledge the anonymous reviewers for their detailed and helpful comments on the original manuscript. We thank the editor Guiling Wang for her valuable guidance and input, which greatly improved this manuscript.",

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doi = "10.1029/2023gl104164",

language = "English (US)",

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T1 - Sub-Grid Representation of Vegetation Cover in Land Surface Schemes Improves the Modeling of How Climate Responds to Deforestation

AU - Qin, Yingzuo

AU - Wang, Dashan

AU - Cao, Ye’er

AU - Cai, Xitian

AU - Liang, Shijing

AU - Beck, Hylke

AU - Zeng, Zhenzhong

N1 - KAUST Repository Item: Exported on 2023-08-07 Acknowledgements: This study was supported by the National Natural Science Foundation of China (42071022, 42001321) and the startup fund provided by the Southern University of Science and Technology (29/Y01296002, 29/Y01296122, 29/Y01296222). We thank the Center for Computational Science and Engineering at the Southern University of Science and Technology for providing computing resources. We acknowledge the anonymous reviewers for their detailed and helpful comments on the original manuscript. We thank the editor Guiling Wang for her valuable guidance and input, which greatly improved this manuscript.

PY - 2023/8/2

Y1 - 2023/8/2

N2 - Understanding the regional climate response to land cover change requires a realistic sub-grid representation of vegetation cover in the land surface scheme (LSS) of climate models. The Community Land Model (CLM) is considered one of the most advanced LSSs; however, when coupled with the Weather Research and Forecasting (WRF) model, the tiling vegetation cover approach was deactivated. Here, we reactivated the theoretical sub-grid vegetation cover representation in WRF-CLM and applied it to assess the impacts of deforestation on regional climate in the Southeast Asian Massif region. We found that CLM-tiling performs more accurate simulations of surface air temperature and precipitation compared to other LSSs using the in situ observations. Importantly, CLM-tiling successfully captures the theoretical sensitivity of evapotranspiration (ET) and temperature to sub-grid deforestation, aligning with Noah-mosaic, and it substantially improves the spatial pattern responses of simulated ET and temperature to regional deforestation.

AB - Understanding the regional climate response to land cover change requires a realistic sub-grid representation of vegetation cover in the land surface scheme (LSS) of climate models. The Community Land Model (CLM) is considered one of the most advanced LSSs; however, when coupled with the Weather Research and Forecasting (WRF) model, the tiling vegetation cover approach was deactivated. Here, we reactivated the theoretical sub-grid vegetation cover representation in WRF-CLM and applied it to assess the impacts of deforestation on regional climate in the Southeast Asian Massif region. We found that CLM-tiling performs more accurate simulations of surface air temperature and precipitation compared to other LSSs using the in situ observations. Importantly, CLM-tiling successfully captures the theoretical sensitivity of evapotranspiration (ET) and temperature to sub-grid deforestation, aligning with Noah-mosaic, and it substantially improves the spatial pattern responses of simulated ET and temperature to regional deforestation.

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DO - 10.1029/2023gl104164

M3 - Article

SN - 0094-8276

VL - 50

JO - Geophysical Research Letters

JF - Geophysical Research Letters

IS - 15

ER -

Sub-Grid Representation of Vegetation Cover in Land Surface Schemes Improves the Modeling of How Climate Responds to Deforestation

Abstract

Bibliographical note

ASJC Scopus subject areas

UN SDGs

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