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Title: Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model‐Simulated Leaf Area Index

Abstract

Abstract Parameterizations of fractional vegetation cover (FVC) in land surface models have important effects on simulations of surface energy budget, especially in arid and semiarid regions. This study uses a FVC scheme in which FVC is derived from leaf area index and a remotely sensed clumping index. The performance of the new scheme (SMFVC) is evaluated against Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and in situ soil temperature observations, together with two other FVC schemes, a general FVC scheme (CTL) based on land cover map and a climatology‐based FVC scheme (RSFVC) that uses long‐term remotely sensed Normalized Difference Vegetation Index of MODIS. The three FVC schemes were implemented in the Common Land Model (CoLM) and applied in the Tibetan Plateau using the same forcing data and default parameters. Our results demonstrate that FVC schemes have significant influence on the CoLM performance: (1) the RSFVC and SMFVC schemes significantly reduce the LST biases found in CTL, particularly in grassland and during summer; (2) soil temperature evaluation by in situ observations from three networks on the Tibetan Plateau corroborates the LST results; and (3) the improvements are mainly related to representing temporal (seasonal) variability and subgrid heterogeneity of FVC,more » which improves surface albedo and surface energy balance. In other words, by including more vegetation characteristics, such as using a clumping index, land surface models may better simulate surface vegetation condition and further better represent the land surface energy budget over the Tibetan Plateau.« less

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [5]; ORCiD logo [6];  [7]; ORCiD logo [8]
  1. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China, State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing China
  2. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China, Joint Center for Global Change Studies Beijing China
  3. Pacific Northwest National Laboratory Richland WA USA
  4. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China, Joint Center for Global Change Studies Beijing China, Key Laboratory of Tibetan Environment Changes and Land Surface Processes Institute of Tibetan Plateau Research, Chinese Academy of Sciences Beijing China, CAS Center for Excellence in Tibetan Plateau Earth Sciences Beijing China
  5. Now at Department of Civil and Environmental Engineering University of Houston Houston TX USA, Department of Land Resources and Environmental Sciences and Institute on Ecosystems Montana State University Bozeman MT USA
  6. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China, Changjiang Institute of Survey, Planning, Design and Research Wuhan China
  7. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science Tsinghua University Beijing China
  8. Key Laboratory of Tibetan Environment Changes and Land Surface Processes Institute of Tibetan Plateau Research, Chinese Academy of Sciences Beijing China, CAS Center for Excellence in Tibetan Plateau Earth Sciences Beijing China
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1499217
Grant/Contract Number:  
DE‐AC05‐76RL01830
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Name: Journal of Geophysical Research: Atmospheres Journal Volume: 124 Journal Issue: 5; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English

Citation Formats

Li, Chengwei, Lu, Hui, Leung, L. Ruby, Yang, Kun, Li, Hongyi, Wang, Wei, Han, Menglei, and Chen, Yingying. Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model‐Simulated Leaf Area Index. United States: N. p., 2019. Web. doi:10.1029/2018JD028640.
Li, Chengwei, Lu, Hui, Leung, L. Ruby, Yang, Kun, Li, Hongyi, Wang, Wei, Han, Menglei, & Chen, Yingying. Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model‐Simulated Leaf Area Index. United States. https://doi.org/10.1029/2018JD028640
Li, Chengwei, Lu, Hui, Leung, L. Ruby, Yang, Kun, Li, Hongyi, Wang, Wei, Han, Menglei, and Chen, Yingying. 2019. "Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model‐Simulated Leaf Area Index". United States. https://doi.org/10.1029/2018JD028640.
@article{osti_1499217,
title = {Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model‐Simulated Leaf Area Index},
author = {Li, Chengwei and Lu, Hui and Leung, L. Ruby and Yang, Kun and Li, Hongyi and Wang, Wei and Han, Menglei and Chen, Yingying},
abstractNote = {Abstract Parameterizations of fractional vegetation cover (FVC) in land surface models have important effects on simulations of surface energy budget, especially in arid and semiarid regions. This study uses a FVC scheme in which FVC is derived from leaf area index and a remotely sensed clumping index. The performance of the new scheme (SMFVC) is evaluated against Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and in situ soil temperature observations, together with two other FVC schemes, a general FVC scheme (CTL) based on land cover map and a climatology‐based FVC scheme (RSFVC) that uses long‐term remotely sensed Normalized Difference Vegetation Index of MODIS. The three FVC schemes were implemented in the Common Land Model (CoLM) and applied in the Tibetan Plateau using the same forcing data and default parameters. Our results demonstrate that FVC schemes have significant influence on the CoLM performance: (1) the RSFVC and SMFVC schemes significantly reduce the LST biases found in CTL, particularly in grassland and during summer; (2) soil temperature evaluation by in situ observations from three networks on the Tibetan Plateau corroborates the LST results; and (3) the improvements are mainly related to representing temporal (seasonal) variability and subgrid heterogeneity of FVC, which improves surface albedo and surface energy balance. In other words, by including more vegetation characteristics, such as using a clumping index, land surface models may better simulate surface vegetation condition and further better represent the land surface energy budget over the Tibetan Plateau.},
doi = {10.1029/2018JD028640},
url = {https://www.osti.gov/biblio/1499217}, journal = {Journal of Geophysical Research: Atmospheres},
issn = {2169-897X},
number = 5,
volume = 124,
place = {United States},
year = {Wed Mar 13 00:00:00 EDT 2019},
month = {Wed Mar 13 00:00:00 EDT 2019}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at https://doi.org/10.1029/2018JD028640

Citation Metrics:
Cited by: 13 works
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