On the development of a coupled regional climate–vegetation model RCM–CLM–CN–DV and its validation in Tropical Africa

• Published in: Climate dynamics Vol. 46; no. 1-2; pp. 515 - 539
• Main Authors: Wang, Guiling, Yu, Miao, Pal, Jeremy S., Mei, Rui, Bonan, Gordon B., Levis, Samuel, Thornton, Peter E.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2016; Springer; Springer Nature B.V; Springer-Verlag
• Subjects: Arid zones; Biogeochemical cycles; Biosphere-atmosphere interactions; CARBON-CYCLE FEEDBACKS; Climate models; Climate science; Climate system; Climatology; Deciduous trees; Drought; DYNAMIC VEGETATION; Earth and Environmental Science; Earth Sciences; ENVIRONMENTAL SCIENCES; Geophysics/Geodesy; GLOBAL VE; LAND-USE CHANGES; LARGE-SCALE MODELS; LATERAL BOUNDARY-CONDITIONS; Oceanography; Phenology; Plant phenology; Plant-soil relationships; Primary production; Rainforests; Regional climate modeling; Regions; Remote sensing; Semiarid lands; Soil carbon; Soil nitrogen; Validation studies; Vegetation; Vegetation dynamics; WEST-AFRICA; Africa; USA, Delaware; Regional climate modeling; Biosphere–atmosphere interactions; Vegetation dynamics; Biogeochemical cycles; Plant phenology
• DOI: 10.1007/s00382-015-2596-z
• ISSN: 0930-7575

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.