{"title":"Probabilistic projections of temperature and rainfall for climate risk assessment in Vietnam","authors":"Quan Tran-Anh, T. Ngo‐Duc","doi":"10.2166/wcc.2024.461","DOIUrl":null,"url":null,"abstract":"\n \n In this study, we developed a probabilistic model using the surrogate/model mixed 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.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"51 9","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/wcc.2024.461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we developed a probabilistic model using the surrogate/model mixed 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.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.