Performance Analysis of CMIP6 Climate Models for the Precipitation of Indonesia Region

Climate model projections are widely used to investigate the potential impact of climate change on the future climate, studies on the agricultural sector, water resources, human health, global economy, etc. This study aims to evaluate the performance of CMIP6 climate models in simulating the historical precipitation data in Indonesia. The results of this study will be used to select the best appropriate CMIP6 model before the downscaling process. The Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) was used as its reference dataset. This research is oriented toward assessing the skills of the 26 CMIP6 models in simulating precipitation on various scales of climate variables (daily, monthly, seasonal, and annual). The determination of the appropriate model was carried out based on the provisions of Taylor’s diagram. The statistical analysis conducted includes calculations for standard deviation (SD), Pearson correlation coefficient (PCC), BIAS, and root mean square error (RMSE). The results of the processing and analysis indicated that the most suitable models to use were ACCESS-ESM1-5, IPSL-CM6A-LR, CNRM-CM6-1, and CNRM-ESM2-1, as they exhibited a high level of agreement with the observations. The correlation coefficients of the four models range from 0.398 (CNRM-ESM2-1) to 0.446 (IPSL-CM6A-LR). The results of the analysis indicate that the spatial and temporal variations of rainfall in the ACCESS model are closer to the CHIRPS model. The implications of these analysis results are expected to be applied in monitoring monthly water availability fluctuations, facilitating the management of regional water resources, and scheduling planting seasons in the agricultural sector.