Work

Future rainfall projections for the Lower Mekong Basin using CMIP6 dynamical downscaling

Year: 2025

Type: article

Abstract: ABSTRACT Reliable rainfall projections for the Lower Mekong River Basin (LMB) are crucial for effective water resource management and disaster risk reduction in the context of global warming. This study analyzes the outputs of two experiments over the LMB using the RegCM4-NH to dynamically downscale simulations from two global climate models (CNRM-CM6-1 and NorESM2-MM) at a spatial resolution of 25 km. The results indicate that the downscaled experiments accurately capture spatial rainfall patterns and their seasonal cycles during the evaluation period (2000–2014), though biases remain, particularly where rainfall is overestimated. Quantile mapping bias correction improves model mean values, increasing the correlations for the average seasonal rainfall cycle from 0.71 (0.78) to 0.92 (0.95) for the downscaled CNRM-CM6-1 (NorESM2-MM) outputs. Both scenarios SSP2-4.5 and SSP5-8.5 project increasing mean annual rainfall, maximum daily rainfall (Rx1day), and rainfall intensity (SDII) toward the century's end, with SSP5-8.5 showing more significant increases. A pronounced amplification of the seasonal cycle is noted, with wetter summers (up to a 70 mm/month increase) and drier winters (a 5–30 mm/month decrease), especially in midstream to downstream areas under SSP5-8.5. These changes are expected to heighten flood risks during wetter months and exacerbate drought conditions in dry season.

Source: Journal of Water and Climate Change

DOI: 10.2166/wcc.2025.793