Deficient precipitation sensitivity to Sahel land surface forcings among CMIP5 models

Journal Article · 08 June 2022 · International Journal of Climatology

DOI: https://doi.org/10.1002/joc.7737 · OSTI ID:1871853

Wang, Fuyao  ^[1]; Notaro, Michael ^[1]; Yu, Yan ^[2]; Mao, Jiafu ^[3]

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1. Nelson Institute Center for Climatic Research University of Wisconsin‐Madison 1225 W Dayton St, Madison Wisconsin USA
2. Department of Atmospheric and Oceanic Sciences School of Physics, Peking University Beijing China
3. Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory Oak Ridge Tennessee USA

Abstract The overall performance of the simulated seasonal precipitation response to local terrestrial forcings, namely vegetation abundance and soil moisture, in the Sahel among the Coupled Model Intercomparison Project Phase Five (CMIP5) Earth System Models (ESMs) is systematically investigated and compared with its observational counterpart using a multivariate statistical method. The observed seasonal precipitation response is evaluated against a large ensemble of observational, reanalysis, and satellite data sets to provide quantification of uncertainties. The behaviour of models with and without a Dynamic Global Vegetation Model (DGVM) component is also explored, along with the mechanisms responsible for terrestrial feedback on rainfall. In general, the CMIP5 models can reasonably capture the seasonal evolution of Sahel precipitation and soil moisture, albeit with wet biases during the pre‐monsoon period and dry biases during the peak monsoon period. The non‐DGVM ESMs simulate comparable leaf area indices (LAIs) with observations, while DGVM‐enabled ESMs simulate too much year‐round LAI. The variance of precipitation that is attributed to oceanic forcings in CMIP5 is comparable with observations; however, the variance of precipitation that is attributed to terrestrial forcings is smaller in CMIP5 models than observed, especially for non‐DGVM ESMs. CMIP5 models, especially those without DGVMs, undervalue precipitation's observed response strength to soil moisture anomalies. In both observations and CMIP5 models, none of the atmospheric variables show significant responses to direct vegetation forcing, except for the response in transpiration. Although vegetation has minimal direct effect on the atmospheric state, it can affect the atmosphere by modifying soil moisture and transpiration rate indirectly, which helps explain the more realistic simulation of rainfall in DGVM‐enabled ESMs than non‐DGVM ESMs. Coupling of an ESM to a DGVM is critical in generating reasonable land–atmosphere feedback and examining future ecological and climatic changes over the Sahel.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: AC05-00OR22725; SC0012534
• OSTI ID: 1871853
• Journal Information: International Journal of Climatology, Journal Name: International Journal of Climatology Journal Issue: 1 Vol. 43; ISSN 0899-8418
• Publisher: Wiley Blackwell (John Wiley & Sons)Copyright Statement
• Country of Publication: United Kingdom
• Language: English