Uncertainty of Coupled Model Intercomparison Projects 6 (CMIP6) in Indonesia’s maritime continental region for the historical period

Abstract

Climate Model is a tool for studying climate and climate change, In climate models there is uncertainty that occurs due to the inability of the model to simulate climate in an area. This study aims to find the best CMIP6 model in the IMC and look at the uncertainty of the model. The data used in this study are precipitation data on the CMIP6 model, as well as the use of CRU data as reference data and observation data. Uncertainty is calculated for historical periods using CDF to see random values from the model. Validation of historical CRU and CMIP6 data is performed by performing statistical calculations that include Pearson correlation, standard deviation, RMSE, KGE, TSS, and relative bias. CRU model testing in Indonesia shows quite good performance at all points, the CRU model has a pattern that follows observational data based on correlation values. the uncertainty of CMIP6 is large in high precipitation and low in moderate precipitation, and there is moderate uncertainty in low precipitation, The analysis of historical data indicates that the EC-Earth3-Veg-LR model has greater performance in simulating precipitation within the IMC region, closely aligning with the values and patterns observed in the CRU model. Furthermore, the EC-Earth3-Veg-LR model displays a strong correlation, as well as good values for the KGE and relative Bias, measuring at 0.33, 0.175, and 1.101% respectively.