Future precipitation projection in Bangladesh using SimCLIM climate model: A multi-model ensemble approach

Abstract

Appraisal of the long-term precipitation trends and variability is crucial for sustainable water resources management. This research intended to evaluate Bangladesh's monthly, seasonal, and annual spatiotemporal rainfall variability using 40 global climate models for two representative concentration pathways (RCPs), RCP4.5 and RCP8.5. Statistical downscaling climate model (SimCLIM) was used for downscaling and ensemble projection of rainfall in near (2011–2040), middle (2041–2070), and far (2071–2100) futures. Modified Mann–Kendall test was applied to detect future rainfall trends. The results revealed a significant increasing trend in rainfall in near and middle futures for RCP4.5 and in all three future periods for RCP8.5 at all meteorological stations of Bangladesh during significant rainfall months (May–October). The results also showed a decreasing trend in rainfall in dry months (December–January) at many stations. The highest increase in rainfall was projected in June at a rate of 0.10–1.11 mm·year−1 for RCP4.5 and 3.34–4.98 mm·year−1 for RCP8.5 in different future periods. Monsoon rainfall showed the highest increase, and winter rainfall the lowest increase for all RCPs and future periods. The increase in annual precipitation over Bangladesh was projected 2.76–5.98% in three future periods for RCP4.5 and 6.98–26.44% for RCP8.5. These outcomes indicate a possible increase in floods severity and frequency in Bangladesh in the future.