Probabilistic projections of temperature and rainfall for climate risk assessment in Vietnam

Abstract

In this study, we developed a probabilistic model using the surrogate mixed model ensemble (SMME) method to project temperature and rainfall in Vietnam under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The SMME model combines patterns from 31 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their weighted model surrogates. Testing for the period of 2006–2018 demonstrated the SMME's ability to encompass observed temperature and rainfall changes. By the end of the 21st century, there is a 5% probability of average temperature increase exceeding 6.29 °C, and a 95% probability of minimum temperature increasing by more than 2.21 °C during 2080–2099 under RCP8.5 compared to 1986–2005. Meanwhile, rainfall is projected to slightly increase, with an average rise of 6.12% at the 5% probability level. The study also quantified the contributions of uncertainty sources – unforced, forced, and scenario-related – to the projection results, revealing that unforced uncertainty dominates the total signal at the beginning of the 21st century and gradually decreases, while forced uncertainty remains relatively moderate but increases gradually over time. As we approach the end of the century, scenario uncertainty dominates, accounting for 75–80% of the total signal. HIGHLIGHTS A probabilistic dataset of daily temperature and rainfall in Vietnam has been constructed, providing valuable insights into future changes in Vietnam.; The dataset is accessible online at no cost.; The contributions of three sources of uncertainty, namely, unforced uncertainty, forced uncertainty, and scenario uncertainty to the projection results in Vietnam have been quantified.;

Keywords

• climate extreme
• cmip5
• probabilistic projection
• surrogate mixed model ensemble
• vietnam