4.5 Article

Assessment of the unified model in reproducing West African precipitation and temperature climatology

Journal

THEORETICAL AND APPLIED CLIMATOLOGY
Volume 148, Issue 1-2, Pages 779-794

Publisher

SPRINGER WIEN
DOI: 10.1007/s00704-022-03973-1

Keywords

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Funding

  1. Natural Environment Research Council (NERC)-Department for International Development (DFID)-funded Improving Model Processes for African Climate (IMPALA) project [NE/M017206/1]

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This study evaluates the performance of the Global Coupled configuration 2 (GC2) of the Unified Model (UM) in reproducing climate variables over West Africa. The results show that UM performs relatively well in simulating temperature and precipitation, with larger biases in precipitation. The overall performance of UM is better than the 4 CMIP6 GCMs, and the simulation is more accurate in the southern parts of the region. It is recommended to further investigate how the model reproduces precipitation and temperature-based processes and to use the model for future climate research in West Africa.
The ability of any climate model to reproduce present-day climate fields is very important for the confidence in the projections of the future state of the same fields. It is against this background that the performance of the Global Coupled configuration 2 (GC2) of the Unified Model (UM), a Global Climate Model (GCM), was evaluated over the West African region (a climate-sensitive region) for two periods on 3 climatological time scales for precipitation (using the Global Precipitation Climatology Center data) and 2-m temperature where the Climate Research Unit Time Series dataset was used. The GC2's performance is also compared with 4 Coupled Model Intercomparison Project phase 6 (CMIP6) GCMs. Results indicate that spatial biases are of similar patterns across the domain for the two study periods for both variables, demonstrating the consistency of the model in reproducing the two climate variables over West Africa (WA). The simulation of temperature by the UM is better than precipitation. Biases are larger in the UM and the CMIP6 GCMs than the levels of observational uncertainties for precipitation, but for temperature, biases in all the models are within the levels of uncertainties found in the observations. Also, the holistic performance of the UM in the two fields is relatively better than the 4 CMIP6 GCMs. The two variables are also simulated better in the southern parts of the region than the northern parts of the domain by the UM. The analysis of the UM suggests a strong linkage between the two variables and therefore, a detailed investigation in how the model reproduces precipitation and temperature-based processes over WA is recommended in order to enhance the model's simulations of these climate variables. Also, the model is recommended for future investigations of precipitation and temperature climatologies over WA.

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