DOI: 10.1007/s00382-015-2596-z
Scopus记录号: 2-s2.0-84955704933
论文题名: On the development of a coupled regional climate–vegetation model RCM–CLM–CN–DV and its validation in Tropical Africa
作者: Wang G. ; Yu M. ; Pal J.S. ; Mei R. ; Bonan G.B. ; Levis S. ; Thornton P.E.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2016
卷: 46, 期: 2017-01-02 起始页码: 515
结束页码: 539
语种: 英语
英文关键词: Biogeochemical cycles
; Biosphere–atmosphere interactions
; Plant phenology
; Regional climate modeling
; Vegetation dynamics
英文摘要: This paper presents a regional climate system model RCM–CLM–CN–DV and its validation over Tropical Africa. The model development involves the initial coupling between the ICTP regional climate model RegCM4.3.4 (RCM) and the Community Land Model version 4 (CLM4) including models of carbon–nitrogen dynamics (CN) and vegetation dynamics (DV), and further improvements of the models. Model improvements derive from the new parameterization from CLM4.5 that addresses the well documented overestimation of gross primary production (GPP), a refinement of stress deciduous phenology scheme in CN that addresses a spurious LAI fluctuation for drought-deciduous plants, and the incorporation of a survival rule into the DV model to prevent tropical broadleaf evergreens trees from growing in areas with a prolonged drought season. The impact of the modifications on model results is documented based on numerical experiments using various subcomponents of the model. The performance of the coupled model is then validated against observational data based on three configurations with increasing capacity: RCM–CLM with prescribed leaf area index and fractional coverage of different plant functional types (PFTs); RCM–CLM–CN with prescribed PFTs coverage but prognostic plant phenology; RCM–CLM–CN–DV in which both the plant phenology and PFTs coverage are simulated by the model. Results from these three models are compared against the FLUXNET up-scaled GPP and ET data, LAI and PFT coverages from remote sensing data including MODIS and GIMMS, University of Delaware precipitation and temperature data, and surface radiation data from MVIRI and SRB. Our results indicate that the models perform well in reproducing the physical climate and surface radiative budgets in the domain of interest. However, PFTs coverage is significantly underestimated by the model over arid and semi-arid regions of Tropical Africa, caused by an underestimation of LAI in these regions by the CN model that gets exacerbated through vegetation dynamics in RCM–CLM–CN–DV. © 2015, Springer-Verlag Berlin Heidelberg. 资助项目: NSF, National Science Foundation
; NSF, National Science Foundation
; NSF, National Science Foundation
; NSF, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/53875
Appears in Collections: 过去全球变化的重建
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作者单位: Department of Civil and Environmental Engineering, Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, United States; Department of Civil Engineering, Loyola Marymount University, Los Angeles, CA, United States; Terrestrial Sciences Division, National Center for Atmospheric Research, Boulder, CO, United States; Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Recommended Citation:
Wang G.,Yu M.,Pal J.S.,et al. On the development of a coupled regional climate–vegetation model RCM–CLM–CN–DV and its validation in Tropical Africa[J]. Climate Dynamics,2016-01-01,46(2017-01-02)