Abstract
The present study evaluates the performance of high-resolution global climate models derived from Coupled Model Intercomparison Project Phase 6 (CMIP6 HighResMIP), in simulating rainfall characteristics over Madagascar on an annual and seasonal scales for the period 1981-2014. The models and their ensemble mean are assessed based on two observational datasets sourced from Climate Hazards Group Infrared Precipitation with Station data version 2 (CHIRPS v2.0) data and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis fifth generation-Land dataset (ERA5) as the references throughout the diverse analyses.
A Taylor diagram, accompanied by the Taylor skill score (TSS), is used for the annual and seasonal model-rankings and the overall performance of the models. The best-performing models are EC-Earth3P-HR, ECMWF-IFS-HR, ECMWF-IFS-LR and HadGEM3-GC31-MM.
The least-recommended models with remarkable biases are BCC-CSM2-HR, CAMS-CSM1-0, FGOALS-f3-H, MPI-ESM1-2-HR and MPI-ESM1-2-XR. It is worth mentioning that FGOALS-f3-H tends to overestimate rainfall in most analyses, while MPI-ESM1-2-HR and MPI-ESM1-2-XR underestimate it.
The findings of this study are of great importance to climatologists and present an opportunity for further investigation of underlying processes responsible for the observed wet/dry biases in order to improve the forecast skills in the models over the study area.