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Title: Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

Abstract

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetationmore » and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Authors:
 [1];  [2];  [2];  [3];  [3];  [3]
  1. Univ. of Wisconsin, Madison, WI (United States). Nelson Inst. Center for Climatic Research; California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.
  2. Univ. of Wisconsin, Madison, WI (United States). Nelson Inst. Center for Climatic Research
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division. Climate Change Science Inst.
Publication Date:
Research Org.:
Univ. of Wisconsin, Madison, WI (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF)
OSTI Identifier:
1422596
Alternate Identifier(s):
OSTI ID: 1419613
Grant/Contract Number:  
AC05-00OR22725; SC0012534; AGS-1343904
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 31; Journal Issue: 4; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; Africa; hydrology; statistical techniques; atmosphere-land interaction; vegetation-atmosphere interactions

Citation Formats

Yu, Yan, Notaro, Michael, Wang, Fuyao, Mao, Jiafu, Shi, Xiaoying, and Wei, Yaxing. Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model. United States: N. p., 2018. Web. doi:10.1175/JCLI-D-17-0220.1.
Yu, Yan, Notaro, Michael, Wang, Fuyao, Mao, Jiafu, Shi, Xiaoying, & Wei, Yaxing. Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model. United States. doi:10.1175/JCLI-D-17-0220.1.
Yu, Yan, Notaro, Michael, Wang, Fuyao, Mao, Jiafu, Shi, Xiaoying, and Wei, Yaxing. Mon . "Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model". United States. doi:10.1175/JCLI-D-17-0220.1.
@article{osti_1422596,
title = {Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model},
author = {Yu, Yan and Notaro, Michael and Wang, Fuyao and Mao, Jiafu and Shi, Xiaoying and Wei, Yaxing},
abstractNote = {Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.},
doi = {10.1175/JCLI-D-17-0220.1},
journal = {Journal of Climate},
number = 4,
volume = 31,
place = {United States},
year = {Mon Feb 05 00:00:00 EST 2018},
month = {Mon Feb 05 00:00:00 EST 2018}
}

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