Future changes in bias-corrected CMIP6 earth system model’s air temperature and precipitation over the Indian Ocean Region
摘要
The presence of inherent systematic biases in global Earth System Climate models limit their ability to accurately represent oceanic and atmospheric processes at regional scales. Therefore, the available estimates of future changes in air temperature (T2M) and precipitation (PR) from these models, are subject to high uncertainty. This study evaluates the performance of five widely used bias-correction methods using two reanalysis datasets. Among them, Quantile Mapping (QM) and Time-varying Delta (TVD) show comparable performance, with TVD marginally outperforming QM. An ensemble approach combining TVD and QM (ETQM) leverages the strengths of both methods, outperforming other methods. It is then applied to correct biases in T2M and PR from three selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models over the Indian Ocean region. The upper T2M extremes in the historical period (1980–2014) are corrected by approximately 1.5