A 10-km CMIP6 downscaled dataset of temperature and precipitation for historical and future Vietnam climate.

High-resolution climate projections are mandatory for many applications and impact assessments in environmental and management studies. In response to the needs in Vietnam, this study constructs a new precipitation and temperature daily dataset for Vietnam, at a high spatial resolution of 0.1° × 0.1°, based on the outputs of 35 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The Bias Correction and Spatial Disaggregation (BCSD) method is adopted to bias-correct monthly GCM simulations using observation data, then subsequently temporally disaggregate them into daily data. The new dataset is called CMIP6-VN, covering the present-time period 1980-2014 and future projections for 2015-2099 from both CMIP6 tier-1 (Shared Socioeconomic Pathways (SSPs) 1-1.26, 2-4.5, 3-7.0, and 5-8.5) and tier-2 (SSPs 1-1.9, 4-3.4, 4-6.0) experiments. Results indicated the good performance of CMIP6-VN for the historical period, suggesting that the dataset could be used for studies on climate change assessment and impacts in Vietnam.

Climate change and health in Southeast Asia - defining research priorities and the role of the Wellcome Trust Africa Asia Programmes.

This article summarises a recent virtual meeting organised by the Oxford University Clinical Research Unit in Vietnam on the topic of climate change and health, bringing local partners, faculty and external collaborators together from across the Wellcome and Oxford networks. Attendees included invited local and global climate scientists, clinicians, modelers, epidemiologists and community engagement practitioners, with a view to setting priorities, identifying synergies and fostering collaborations to help define the regional climate and health research agenda. In this summary paper, we outline the major themes and topics that were identified and what will be needed to take forward this research for the next decade. We aim to take a broad, collaborative approach to including climate science in our current portfolio where it touches on infectious diseases now, and more broadly in our future research directions. We will focus on strengthening our research portfolio on climate-sensitive diseases, and supplement this with high quality data obtained from internal studies and external collaborations, obtained by multiple methods, ranging from traditional epidemiology to innovative technology and artificial intelligence and community-led research. Through timely agenda setting and involvement of local stakeholders, we aim to help support and shape research into global heating and health in the region.

Multi-model projections of precipitation extremes in Southeast Asia based on CORDEX-Southeast Asia simulations.

This study examines the projected precipitation extremes for the end of 21st century (2081-2100) over Southeast Asia (SEA) using the output of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment - Southeast Asia (SEACLID/CORDEX-SEA). Eight ensemble members, representing a subset of archived CORDEX-SEA simulations at 25 km spatial resolution, were examined for emission scenarios of RCP4.5 and RCP8.5. The study utilised four different indicators of rainfall extreme, i.e. the annual/seasonal rainfall total (PRCPTOT), consecutive dry days (CDD), frequency of extremely heavy rainfall (R50mm) and annual/seasonal maximum of daily rainfall (RX1day). In general, changes in extreme indices are more pronounced and covering wider area under RCP8.5 than RCP4.5. The decrease in annual PRCPTOT is projected over most of SEA region, except for Myanmar and Northern Thailand, with magnitude as much as 20% (30%) under RCP4.5 (RCP8.5) scenario. The most significant and robust changes were noted in CDD, which is projected to increase by as much as 30% under RCP4.5 and 60% under RCP8.5, particularly over Maritime Continent (MC). The projected decrease in PRCPTOT over MC is significant and robust during June to August (JJA) and September to November (SON). During March to May (MAM) under RCP8.5, significant and robust PRCPTOT decreases are also projected over Indochina. The CDD changes during JJA and SON over MC are even higher, more robust and significant compared to the annual changes. At the same time, a wetting tendency is also projected over Indochina. The R50mm and RX1day are projected to increase, during all seasons with significant and robust signal of RX1day during JJA and SON.

Flood inundation assessment for the Hanoi Central Area, Vietnam under historical and extreme rainfall conditions.

Flash floods have long been common in Asian cities, with recent increases in urbanization and extreme rainfall driving increasingly severe and frequent events. Floods in urban areas cause significant damage to infrastructure, communities and the environment. Numerical modelling of flood inundation offers detailed information necessary for managing flood risk in such contexts. This study presents a calibrated flood inundation model using referenced photos, an assessment of the influence of four extreme rainfall events on water depth and inundation area in the Hanoi central area. Four types of historical and extreme rainfall were input into the inundation model. The modeled results for a 2008 flood event with 9 referenced stations resulted in an R2 of 0.6 compared to observations. The water depth at the different locations was simulated under the four extreme rainfall types. The flood inundation under the Probable Maximum Precipitation presents the highest risk in terms of water depth and inundation area. These results provide insights into managing flood risk, designing flood prevention measures, and appropriately locating pump stations.