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Mapping potential changes in bioclimatic characteristics are critical for planning mitigation goals and climate change adaptation. Assessment of such changes is particularly important for Southeast Asia (SEA) — home to global largest ecological diversity. Twenty-three global climate models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) were used in this study to evaluate changes in 11 thermal bioclimatic indicators over SEA for two shared socioeconomic pathways (SSPs), 2–4.5 and 5–8.5. Spatial changes in the ensemble mean, 5th, and 95th percentile of each indicator for near (2020–2059) and far (2060–2099) periods were examined in order to understand temporal changes and associated uncertainty. The results indicated large spatial heterogeneity and temporal variability in projected changes of bioclimatic indicators. A higher change was projected for mainland SEA in the far future and less in maritime region during the near future. At the same time, uncertainty in the projected bioclimatic indices was higher for mainland than maritime SEA. Analysis of mean multi-model ensemble revealed a change in mean temperature ranged from − 0.71 to 3.23 °C in near and from 0.00 to 4.07 °C in far futures. The diurnal temperature range was projected to reduce over most of SEA (ranging from − 1.1 to − 2.0 °C), while isothermality is likely to decrease from − 1.1 to − 4.6%. A decrease in isothermality along with narrowing of seasonality indicated a possible shift in climate, particularly in the north of mainland SEA. Maximum temperature in the warmest month/quarter was projected to increase a little more than the coldest month/quarter and the mean temperature in the driest month to increase more than the wettest month. This would cause an increase in the annual temperature range in the future. [ABSTRACT FROM AUTHOR]

A possible shift in climate zones in Southeast Asia (SEA) for different shared socioeconomic pathways (SSPs) is evaluated in this study. The ability of 19 Coupled Model Intercomparison Project (CMIP6) global climate models (GCMs) in reconstructing the Köppen-Geiger climate zones in SEA, estimated using reanalysis data (ERA5) for the period 1979-2014, was analysed using five categorical evaluation metrics. The best-performing models were selected to prepare an ensemble to project possible shifts in climate zones for different SSP scenarios in the future. Besides, future projections in climate variables were evaluated to assess the driving factor of climate shifts in the future. The results showed that three CMIP6 GCMs, EC-Earth3-Veg-LR, CMCC-ESM2 and CanESM5, had a higher skill in classifying the observed climate of SEA. Selected GCMs showed climate shifting in 3.4 to 12.6% of the total area of SEA for different SSPs. The highest geographical shift in climate was projected in the north, from dry winter and hot summer (Cwa) to tropical with dry winter (Aw), followed by Aw to tropical monsoon (Am) in the north and south, and tropical without dry season (Af) to Am in the middle and southwest of SEA. An increase in minimum temperature was the key to climate shifting from Cwa to Aw in the north, while increased rainfall was a reason for Aw to Am transition in the north and south. Overall, climatic shifting was higher for high emission scenarios. The maps of future climate zones generated in this study can help to identify the hotspots of ecologically vulnerable areas in SEA due to climate change. • Up to 12.6% of the SEA area is likely to face a climate shift in the future. • North SEA's climate would shift to tropical with dry winters. • There will be a shift towards a more monsoon-dominated climate. • A rapid rise in Tmin is responsible for the climate shift in the north SEA. • Region-specific adaptation policy is needed for climate resiliency in SEA. [ABSTRACT FROM AUTHOR]

The objective of this research was to assess the difference in historical simulations and future projections of rainfall and temperature of CMIP5 (RCP4.5 and 8.5) and CMIP6 (SSP2–4.5 and 5–8.5) models over Southeast Asia (SEA). Monthly historical rainfall and temperature estimations of 13 global climate models common to both CMIPs were evaluated to assess their capability to reproduce the spatial distribution and seasonality of European Reanalysis (ERA) rainfall and temperature. Models were used to determine uncertainty with spatiotemporal variability of rainfall and temperature projections. The CMIP6 GCMs did not appear to perform better than the older CMIP5 in SEA unlike other parts of the globe, except for rainfall. The CMIP6 models showed Kling-Gupta Efficiency (KGE) values in the range of −0.48-0.6, 0.21‐0.85 and 0.66‐0.91 in simulating historical rainfall, maximum temperature and minimum temperature compared to 0.13‐0.46, 0.3‐0.86 and 0.42‐0.92 for CMIP5. The improvement in CMIP6 models in SEA was in the low uncertainty in ensemble simulation. The projections of CMIP5 and CMIP6 showed a relatively smaller increase in temperature with the CMIP6 ensemble when compared to CMIP5 models, while rainfall appeared to decrease. The geographical distribution of the changes indicated a greater increase in temperature in the cooler region than in the warmer region. In contrast, there was increase in rainfall in the wetter region and a smaller improvement in the drier region. This indicates increased homogeneity in temperature spatial variability, but more heterogeneity in rainfall, in the SEA region under climate warming scenarios. • 13 GCMs from both CMIP simulations are performed. • CMIP6 did not perform better than CMIP5 in SEA, except for rainfall. • Rainfall faces a greater increase while temperature faces reduced increase for CMIP6 compared to CMIP5. • Based to CMIP6, new climate change mitigation policy should be considered in SEA. [ABSTRACT FROM AUTHOR]