Development of localized climate projections for Vietnam’s Mekong Delta using univariate and multivariate bias corrections of CMIP6 simulations

Abstract Vietnam’s Mekong Delta plays a pivotal role in national and global food security. However, agriculture-based livelihoods in the delta are highly susceptible to climate extremes, highlighting the need for more localized climate change information. Hence, this study applied univariate and multivariate bias correction methods to raw climate model simulations from the Coupled Model Intercomparison Project Phase 6 under eight Shared Socioeconomic Pathways (SSP) to develop localized climate projections. The univariate method employed is the Quantile Delta Mapping (QDM) algorithm, whereas the multivariate approaches include the N -dimensional probability density function transform (MBCn) and the Rank Resampling for Distributions and Dependences (R 2 D 2 ). The performance of these bias correction techniques was evaluated based on their ability to reduce model biases in marginal distributions and to reproduce multidimensional characteristics, including inter-variable, inter-site, and temporal dependence structures. Successive cross-validation results indicate that the bias-corrected fields exhibit substantial improvements in marginal distributions, even at high quantile values. Moreover, multivariate methods demonstrate superior performance in capturing multivariate characteristics compared to their univariate counterpart. For future projections, this study combined the trend-preserving feature of the QDM algorithm with sliding window settings to better preserve the underlying climate change signals from raw climate model outputs. At the annual scale, projections for the near to far future consistently indicate a warmer and wetter response relative to the baseline period across most SSP-based scenarios. However, rainfall during the dry season (months) is projected to decrease with considerable uncertainty. The findings provide valuable insights for climate-sensitive planning and decision-making in the delta.