1. Introduction

Viet Nam is among the countries that have been severely impacted by climate change [ MoNRE, 2016 ]. In recent years, the Ministry of Natural Resources and Environment has published several reports on climate change and sea level rise scenarios for Viet Nam [ MoNRE, 2009; 2012; 2016; IMHEN, 2021 ]. These reports provide the latest information on observed and projected trends for climate and sea level rise in Viet Nam; they offer an important scientific basis for ministries, sectors and localities in assessing impacts, vulnerability and risks due to climate change, enabling them to develop and update their action plans as necessary. Building climate change scenarios for Viet Nam involves downscaling global scenarios for various global greenhouse gas (GHG) scenarios. Two methods have been used: statistical downscaling [ MoNRE, 2009; 2012 ] and dynamical downscaling [ MoNRE, 2012; 2016; IMHEN, 2021 ]. The statistical downscaling method has the advantages of being simple and not requiring huge computer resources. Meanwhile, the dynamical downscaling method, which implies the use of regional climate models, has the advantage of being able to provide coherent information among climate variables. Yet the main disadvantage of the dynamical method in the high computing storage capacity it requires. The MoNRE reports published in 2009 and 2012 applied the Special Report on Emission scenarios (SRES) [ Nakicenovic et al., 2000 ], which were used in the Third and the Fourth Assessment Reports of the Intergovernmental Panel on Climate Change [ IPCC, 2001; 2007 ]. Meanwhile, the greenhouse gas (GHG) scenarios used in the latest MoNRE reports [ MoNRE, 2016; IMHEN, 2021 ] are the Representative Concentration Pathways [ RCPs; van Vuuren, 2011 ]. The RCPs were used in the Fifth Assessment Report of IPCC [ IPCC, 2013 ]. According to the various scenarios published by MoNRE, average annual temperatures in Viet Nam at the end of the XXIst century will increase by 1.5–4.2°C, average annual rainfall will increase by 10–40%, and extreme rainfall by 20–40% relative to the baseline period (1980–1999 or 1986–2005 depending on the used GHG scenarios).

The information sourced from these climate change scenarios is an essential input for climate change impact assessment in various socio-economic aspects. Part of this assessment is being implemented within the framework of the GEMMES Viet Nam project sponsored by the French Development Agency (AFD). This chapter summarizes some updated results from the latest technical report on climate change and sea level rise scenarios for Viet Nam [ IMHEN, 2021 ] and developed in parts 2, 3 and 4 of this report. In addition, we implement a new statistical downscaling approach using the Bias Correction Spatial Disaggregation (BCSD) method, applied for 31 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). In this new approach, four RCPs (RCP2.6, 4.5, 6.0 and 8.5) were used. It should be noted that only two RCPs (RCP4.5 and RCP8.5) were used in the 2016 and 2021 reports of MoNRE and IMHEN, respectively. The reason is that because these reports used the dynamical downscaling method, the number of models and GHG scenarios needed to be limited as a result of associated computation times.

In 2015, many countries around the world adopted the Paris Agreement — which aims to limit global warming at the end of XXIst century to well below 2°C in relation to to the pre-industrial era — and endeavoured to limit the increase