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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of socio-hydrological data. The benchmark dataset comprises: 1) detailed review style reports about the events and key processes between the two events of a pair; 2) the key data table containing variables that assess the indicators which characterise management shortcomings, hazard, exposure, vulnerability and impacts of all events; 3) a table of the indicators-of-change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators-of-change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses e.g. focused on causal links between risk management, changes in hazard, exposure and vulnerability and flood or drought impacts. The data can also be used for the development, calibration and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2023, link for review: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/).

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.

In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.

This study examines the characteristics and trends of extreme rainfall in Northern Vietnam from 1961 to 2018, using daily rainfall data collected from 37 meteorological stations. The study reveals that the average annual rainfall varies significantly across stations, ranging from 1140 mm to 4758 mm. The rainy season accounts for 73% to 92% of the total annual rainfall. Most stations show a declining trend in the annual total rainfall during wet days (PRCPTOT) and the number of wet days (WDAY), while rainfall intensity (SDII) has increased in most stations, particularly during the dry season. This can be attributed to an increase in PRCPTOT and a decrease in WDAY in the dry season. The study also finds a general decreasing trend in the annual maximum 1-day precipitation (RX1day) and consecutive 5-day precipitation (RX5day), as well as for the number of moderate (R16mm) and heavy (R50mm) rainfall days. However, most stations in Northern Vietnam demonstrate no trend in the annual maximum number of consecutive dry days (CDD) and the annual maximum number of consecutive wet days (CWD). Furthermore, the frequency of extreme rainfall events in Northern Vietnam exceeding the 5-year and 10-year return values of 1961-2018 has decreased in recent decades at many stations. Overall, the findings of this study provide insights into the changing patterns of extreme rainfall in Northern Vietnam, with significant implications for climate change adaptation and disaster risk reduction efforts in the region.

In recent decades, changes in temperature, wind, and rainfall patterns of Southeast Asia induced by climate warming in the Tibetan Plateau result in many environmental changes that have serious impacts on the lower reach of the Mekong River basin, a region already battling severe water-related environmental problems such as pollution, saltwater intrusion, and intensified flooding. In the densely populated Mekong Delta located at the mouth of the Mekong River basin in southern Vietnam, the hydrogeological systems have been transformed from an almost undisturbed to a human-impacted state and saltwater intrusion into surface water and groundwater systems has grown to be a detrimental issue recently, seriously threatening freshwater supply and degrading the eco-environment. In this article, the impacts of human activities and climate change (e.g., groundwater over-exploitation, relative sea-level rise, storm surge, changing precipitation and temperature regimes, uncontrolled drainage canals, operation of hydropower dams, and rapid development of aquaculture) on saltwater intrusion into groundwater systems in the Mekong Delta are briefly reviewed. Based on current status of research findings regarding saltwater intrusion and the subsequent groundwater quality degradation under the impacts of human activities and climate change, major knowledge gaps and challenges are identified and discussed, including thickness and permeability of the silt and clay aquitard, present-day highly heterogeneous 3D distribution of saline groundwater zones, dynamic variation of saltwater/freshwater transition zone, and the most effective and economical control measure. To bridge these gaps, future work should: 1) apply environmental isotope techniques in combination with borehole tests to gain detailed hydrogeological information regarding spatial variation of permeability and thickness of the silt and clay aquitard; 2) intensify regular groundwater monitoring and collect as much groundwater samples from multiple hydro-stratigraphic units at different depths as possible to visualize the present-day highly heterogeneous 3D distribution of saline groundwater; 3) develop a series of variable-density coupled groundwater flow and salt transport models representing various scenarios of human activities and climate change for predicting future extent of saltwater intrusion; and 4) identify the dominant factor causing saltwater intrusion and determine the most effective and economical engineering technique to address saltwater intrusion problems in the Mekong Delta.

Remote influences on extreme anomalous rainfall over North and South Vietnam during extended summer (May-October) are explored using a 38-year (1979-2016) ERAi global dataset. Composite WET and DRY events with lags of up to two weeks are assembled for rainfall indices over subregions of Vietnam. The large-scale dynamical precursors to these events are explored through diagnostics of the extratropical flow. Rainfall extremes of opposing signs show asymmetrical large scale precursors and different pathways of influence. Both WET and DRY events over North Vietnam are seen to originate from Europe and propagate either at high latitudes or along the Asian Jet. A persistent Siberian High is linked with WET events over North Vietnam. Anomalies also develop along the Asian Jet for both regions, but only for DRY events over South Vietnam. Events over South Vietnam are also much more influenced by tropical precursors. The Dynamical Research Empirical Atmospheric Model (DREAM) was used to examine pathways of influence to the circulation over Vietnam sub-regions in the medium range. A set of stationary wave experiments was conducted with artificial heat sources in different locations around the world, using ERAi summer climatology as a basic state. Influence functions with respect to upper-level divergent flow over the target regions of North and South Vietnam indicate two different pathways: extratropical wave-trains and tropical waves. For North Vietnam, heat sources over Europe give the most influence after 15 days. For South Vietnam, the influence is much weaker and significant precursors are more likely to be tropical Kelvin wave sources.

Southeast Asia (SEA) climate shows a large range of variability scales, from extreme events to interannual variability. Understanding its answer to climate change is of primary scientific and socio-economic importance. IPCC 5th assessment report however pointed the lack of knowledge in regional climate change and its impact in SEA. In particular little is known about the answer of wind to climate change. The impact of climate change on sea surface wind speed is investigated here, examining changes in daily and extreme event scales, interannual variability and climatological average between the twentieth and twenty-first centuries. For that the RegCM4 regional model was used to perform a dynamical downscaling of CMIP5 simulations done with CNRM-CM5 global climate model under RCP4.5 and RCP8.5 hypothesis. Comparisons with QuikSCAT satellite data show that the downscaled simulations perform overall better than the global simulations. Both models produce regionally and seasonally contrasted results in terms of daily wind speed answer to climate change. Global simulations produce mostly weak and non-significant changes, only suggesting an intensification of northeast winter monsoon in the northern SEA. Conversely regional downscaled simulations suggest from March to November in the northern South China Sea and Pacific regions a significant weakening of wind speed from climatological to daily scales (summer monsoon to extreme values), for regions and periods of initially strong values, associated with a 40–50% decrease of tropical cyclones frequency. These changes result from the increase of mean meridional south to north sea level pressure gradient and decrease its daily variability.

This study first evaluates the performance of three model experiments in representing rainfall over part of Vietnam and the Lower Mekong Basin for the historical period 1986-2005. The three experiments include the Coupled Model Intercomparison Project Phase 5 (CMIP5) EC-EARTH Global Climate Model (GCM) and two downscaling runs based on a regional climate model at 25km resolution with the GCM forcing (RCM-25km) and at 5km resolution with the RCM-25km forcing (RCM-5km). Verifications against observations show that the experiments generally capture the spatial distribution of climatological rainfall. While the GCM well represents the observed average rainfall cycles, its coarse resolution limits its capability in reproducing extreme rainfall values. The downscaling experiments do not clearly show their advantage in simulating average rainfall but exhibit significant added values when representing extreme rainfall in the study region. The RCM-5km does not outperform its driving 25km experiment in representing the mean and extreme rainfall values, suggesting that having a better resolution may not compensate for having a good model configuration with appropriate physical schemes. Analysis of climate projection for the far future period 2080-2099 under two representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5, reveals that the downscaling experiments can modify the change direction of future rainfall obtained with the GCM. While the EC-EARTH GCM generally projects wetter tendencies of up to 50%, the downscaling experiments project a general decrease of down to -50% under both scenarios over the study domain. Regarding extreme rainfall, the annual maximum 1-day rainfall amount (RX1day) is projected to increase for the three experiments. The simple daily intensity index (SDII) future changes follow those of the annual rainfall values.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Understanding the future offshore wind energy is crucial for making an appropriate energy strategy. Yet how offshore wind energy will respond to the rapidly intensifying global warming remains inconclusive. Focusing on a tropical sea in Vietnam, this study assesses the climatic impact of global warming on the local offshore wind potential. Dynamically downscaled wind data obtained by an edge-cutting fine-resolution regional climate model with two greenhouse-gases Representative Concentration Pathway (RCP) scenarios 8.5 and 4.5 were biased-corrected with a quantile mapping method before using for assessment. Results revealed a changing trend of the annual-mean offshore wind speed and power potential in Vietnam under both scenarios. However, the change is seasonally asymmetric with decreases of about 2 – 10% in September-October-November and slight increases of about 2 – 4% in December-January-February. The turbine-based assessment showed that the cumulative annual energy obtained from the 12 MW and 8 MW turbines could reach the highest about 50.9 GWh and 30.7 GWh (2080–2099 average under scenario RCP8.5) but the difference in their capacity factor is much smaller, suggesting that turbine 8 MW should be considered in the sense of cost-effectiveness in some areas.

Mathematical formulas identification is a crucial step in the pipeline of many tasks such as mathematical information retrieval, storing digital science documents, etc. For basic mathematical formulas recognition, all these tasks need to detect the bounding boxes of mathematical expression as a prerequisite step. Currently, deep learning-based object detection methods work well for mathematical formula detection (MFD). These methods are divided into two categories: anchor self-study and anchor not self-study. The anchor self-study method is efficient with large quantity labels but not so well with small quantities, whereas the second type of method works better with small quantities. Therefore, we proposed an algorithm that keeps the good prediction of each type and then merges both into final results. To demonstrate the hypothesis, we select two typical object detection methods: YOLOv5 and Faster RCNN as the representation of two kind approaches to building an MFD framework. Our experiment results on ICDAR2021-MFD1 achieved the F1 score of the whole system is 89.3 while the single detector just reached 74.2, 88.9 (Faster RCNN and YOLOv5 respectively) that proving the effectiveness of the proposal.

Projected future changes in mean precipitation over Thailand based on multi-model regional climate simulations of CORDEX Southeast Asia

The quality of estuarine, coastal and marine environment in the Gulf of Tonkin, in the South China Sea, is an essential issue to the ecosystems’ health and to the living conditions and economy of the Viet Nam population. The stakes are particularly high since the demographic density in the Red River delta is one of the highest in the world. Understanding the physical processes that drive the ocean circulation and its response to anthropic pressure there is therefore of primarily importance for enlightened resource management, as well as for designing adequate monitoring and forecasting systems.As a first step toward a better understanding of the physical coastal and marine environment, we present here a study on the Red river plume variability in the Gulf of Tonkin over the period 2011-2016. The study is based on a numerical simulation, under realistic conditions, using the SYMPHONIE coastal model developed at LEGOS (Marsaleix et al., 2008). Compared with various data sources, the model results show good performances. The river plume is then identified and examined at different time scales. In general, the surface coverage of the river plume is strongly correlated with the runoff but with a 1-month lag. However, in some years, a higher peak in runoff does not create a higher peak of the plume area, suggesting that other forcings need to be taken into account to explain the variability of the river plume.Using K-mean clustering, the main patterns of the plume are identified. The result shows that the plume has a large variability at both seasonal and interannual scales. Each pattern shows the plume under different forcing conditions. Most of the time, the plume is narrow and sticks along the coast due to the downcoast current and northeasterly wind. In the summer, due to monsoon, the wind direction changes to southwesterly and helps the plume to spread offshore. The plume reaches its highest coverage in September after the peak of runoff; then its coverage decreases again when the monsoon reverses.We also analyze events of offshore export of freshwater at daily time scales and show that they can be associated with recurrent coastal eddies during the summer monsoon. We investigate the respective role of wind and runoff in the eddies formation. Comparison with a run without river allows to identify the main impacts of the plume on the ocean states, for example in the current and sea surface elevation.

This chapter reviews the progress in regional climate downscaling simulations (RCDS) over Southeast Asia, both at country and regional levels. The need to advance RCDS stems from the fact that robust climate change projections are needed in decision-making processes involved in adopting climate-resilient pathways, wherein adaptation, mitigation, and sustainable development aspects must also be considered. At the country level, notable variation in the progress in RCDS among countries in Southeast Asia exists wherein some countries have not conducted any RCDS, while others show some levels of activities in both dynamical and statistical downscaling. At the regional level, RCDS activities are also limited. However, the establishment of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia (CORDEX-SEA) and the completion of high-resolution multi-model simulations are game changers. Furthermore, through the establishment of the Southeast Asia Regional Climate Change Information System (SARCCIS), a data portal where CORDEX-SEA simulation outputs are archived and linked to the Earth System Grid Federation (ESGF) for worldwide accessibility, the availability of robust climate change projections is expected to spur the research and development activities in the vulnerability, impact, and adaptation aspects in the region. Lastly, the remaining challenges, such as on bias and uncertainties, are discussed, which indicate the way forward concerning RCDS in Southeast Asia.

This paper examines the projected changes in rainfall in Southeast Asia (SEA) in the twenty-first century based on the multi-model simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment–Southeast Asia (SEACLID/CORDEX–SEA). A total of 11 General Circulation Models (GCMs) have been downscaled using 7 Regional Climate Models (RCMs) to a resolution of 25 km × 25 km over the SEA domain (89.5° E–146.5° E, 14.8° S–27.0° N) for two different representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5. The 1976–2005 period is considered as the historical period for evaluating the changes in seasonal precipitation of December–January–February (DJF) and June–July–August (JJA) over future periods of the early (2011–2040), mid (2041–2070) and late twenty-first century (2071–2099). The ensemble mean shows a good reproduction of the SEA climatological mean spatial precipitation pattern with systematic wet biases, which originated largely from simulations using the RegCM4 model. Increases in mean rainfall (10–20%) are projected throughout the twenty-first century over Indochina and eastern Philippines during DJF while a drying tendency prevails over the Maritime Continent. For JJA, projections of both RCPs indicate reductions in mean rainfall (10–30%) over the Maritime Continent, particularly over the Indonesian region by mid and late twenty-first century. However, examination of individual member responses shows prominent inter-model variations, reflecting uncertainty in the projections.

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.

This study examines the simulated temperature over Southeast Asia (SEA) using the Regional Climate Model version 4.3 (RegCM4.3), and its sensitivity to selected cumulus and ocean surface flux schemes. Model simulations were conducted for the SEA domain at 36 km spatial resolution for the period of 1989–2008, as part of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-Southeast Asia) project. A total of 18 sensitivity experiments were conducted with a combination of six cumulus parameterization schemes and three ocean surface flux schemes. The model's skill in representing mean, maximum and minimum temperatures is evaluated against observed gridded data sets. Results indicate a predominant cold bias in all simulations, particularly over mainland SEA (Indochina) during the season of December to February. Nevertheless, the seasonal correlation is highest over this region. The cold bias of the model is also evident in the temperature distributions, such that there are more cold months than observed, which may be associated with the underestimation of the daily maximum temperature. A few simulations also reveal a warm bias over some areas in the Maritime Continent. Further examination shows that both radiative and surface fluxes influence the simulated temperature, which may also have effects that partially offset each other in some areas. Comparison of the sensitivity experiments reveals differences in model performance, and underlines the importance in choosing the appropriate configuration for RegCM4.3 before it is used to downscale climate projections, particularly for the SEA region. This study also shows a strong influence of the choice of cumulus scheme on temperature. Based on performance metrics for temperature among the schemes tested, the Massachusetts Institute of Technology (MIT) Emanuel cumulus scheme and the Biosphere-Atmosphere Transfer Scheme version 1e (BATS1e) ocean surface flux scheme can be used in future simulations for the region.

The daily rainfall data at 13 stations over the Central Highlands (CH) Vietnam were collected for the period 1981–2014. Two different sets of criteria using daily observed rainfall and 850 hPa daily reanalysis wind data were applied to determine the onset (retreat) dates of the summer rainy season (RS) and summer monsoon (SM) season, respectively. Over the study period, the mean RS and SM onset dates were April 20 and May 13 with standard deviations of 17.4 and 17.8 days, respectively. The mean RS and SM retreat dates were November 1 and September 30 with standard deviations of 17.9 and 10.2 days, respectively. The year-to-year variations of the onset dates and the rainfall amount within the RS and SM season were closely linked with the preceding winter and spring sea surface temperature in the central-eastern and western Pacific. It was also found that the onset dates were significantly correlated with the RS and SM rainfall amount.

This study presents an approach to assimilate tropical cyclone (TC) real-time reports and the University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies (CIMSS) Atmospheric Motion Vectors (AMV) data into the Weather Research and Forecasting (WRF) model for TC forecast applications. Unlike current methods in which TC real-time reports are used to either generate a bogus vortex or spin up a model initial vortex, the proposed approach ingests the TC real-time reports through blending a dynamically consistent synthetic vortex structure with the CIMSS-AMV data. The blended dataset is then assimilated into the WRF initial condition, using the local ensemble transform Kalman filter (LETKF) algorithm. Retrospective experiments for a number of TC cases in the northwestern Pacific basin during 2013–2014 demonstrate that this approach could effectively increase both the TC circulation and enhance the large-scale environment that the TCs are embedded in. Further evaluation of track and intensity forecast errors shows that track forecasts benefit more from improvement in the large-scale flow at 4–5-day lead times, whereas the intensity improvement is minimal. While the difference between the track and intensity improvement could be due to a specific model configuration, this result appears to be consistent with the recent reports of insignificant impacts of inner core data assimilation in operational TC models at the long range of 4–5 days. The new approach will be most beneficial for future regional TC models that are directly initialized from very high-resolution global models whose storm initial locations are sufficiently accurate at the initial analysis that there is no need to carry out any artificial vortex removal or filtering steps.