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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.

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

The performance of the Global Satellite Mapping of Precipitation data Microwave-Infrared Combined Reanalysis Product (GSMaP RNL), version 6, was evaluated, using northern Vietnam as the test area. The Vietnam Gridded Precipitation (VnGP) Dataset was used for comparison purposes. Particular emphasis was placed on the investigation of heavy-rain days (precipitation over 50 mm day −1). Wind data from operational radiosonde observations at Hanoi were also used to examine the effect of interaction between wind and topography, on the GSMaP performance, and the basic relationship between the VnGP precipitation and lower tropospheric wind. Results showed that heavy-rain days generally occurred during May–August. Regions with higher and lower precipitation in the GSMaP, compared to the VnGP, were found to be distributed in a complex manner, at a scale similar to that of tributary basins. The GSMaP and the VnGP showed similar precipitation values when associated with westerly wind in the lower troposphere at Hanoi. Positive influences of westerly wind on estimated precipitation were observed along the northeastern foot of the mountain ranges, whereas negative influences were found along the southeastern foot. The results implied that the GSMaP rainfall estimation algorithm, taking account of orographic effects, may improve the accuracy of rainfall reproducibility, by using a more appropriate wind dataset to evaluate orographic convection.

In this study, simulations over Southeast Asia (15°S–40°N, 80°–145°E) at 36 km resolution were conducted for the period 1989–2007 using the Regional Climate Model version 4.3 (RegCM4.3) under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (or SEACLID/CORDEX-SEA) project. Forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), 18 experiments were carried out using different combinations of cumulus parameterization and ocean flux schemes. Twelve extreme indices for both rainfall and temperature were estimated from the model output. A statistical omega index was used to measure the degree of similarity among the 18 experiments in phase and shape. The results showed relatively high similarities among the experiments over mainland Asia compared to those over the Maritime Continent for both seasonal and inter-annual variability. The extreme rainfall indices had a lower omega compared to that of temperature. Observed daily rainfall and temperature data at 52 meteorological stations over the SEA region were used to validate the simulated extreme indices. The results showed that extreme temperature indices were generally underestimated across the region. Systematic biases for each simulated rainfall index were also identified. A score ranking system was established to compare the relative performance of the 18 experiments over the 52 selected stations objectively. It was shown that the experiments with the Massachusetts Institute of Technology (MIT)-Emanuel scheme performed relatively better than the other convective schemes. The combination of the MIT-Emanuel convective scheme with the Biosphere–Atmosphere Transfer scheme (BATS1e) ocean flux scheme produced the best performance.

To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.

A land process model [the coupled hydrological and biogeochemical model (CHANGE)] is used to quantitatively assess changes in the ice phenology, thickness, and volume of terrestrial Arctic rivers from 1979 to 2009. The CHANGE model was coupled with a river routing and discharge model enabling explicit representation of river ice and water temperature dynamics. Model-simulated river ice phenological dates and thickness were generally consistent with in situ river ice data and landscape freeze–thaw (FT) satellite observations. Climate data indicated an increasing trend in winter surface air temperature (SAT) over the pan-Arctic during the study period. Nevertheless, the river ice thickness simulations exhibited a thickening regional trend independent of SAT warming, and associated with less insulation and cooling of underlying river ice by thinning snow cover. Deeper snow depth (SND) combined with SAT warming decreased simulated ice thickness, especially for Siberian rivers, where ice thickness is more strongly correlated with SND than SAT. Overall, the Arctic river ice simulations indicated regional trends toward later fall freezeup, earlier spring breakup, and consequently a longer annual ice-free period. The simulated ice phenological dates were significantly correlated with seasonal SAT warming. It is found that SND is an important factor for winter river ice growth, while ice phenological timing is dominated by seasonal SAT. The mean total Arctic river ice volume simulated from CHANGE was 54.1 km3 based on the annual maximum ice thickness in individual grid cells, while river ice volume for the pan-Arctic rivers decreased by 2.82 km3 (0.5%) over the 1979–2009 record. Arctic river ice is shrinking as a consequence of regional climate warming and coincident with other cryospheric components, including permafrost, glaciers, and sea ice.

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.

THIS ARTICLE PROVIDES detailed information on projected changes in annual precipitation extremes over Southeast Asia under global warming of 2°C based on the multi-model simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment Southeast Asia (SEACLID/CORDEX-SEA). Four indices of extreme precipitation are considered: annual total precipitation (PRCPTOT), consecutive dry days (CDD), frequency of rainfall exceeding 50 mm/day (R50mm), and intensity of extreme precipitation (RX1day). The ensemble mean of 10 simulations showed reasonable performance in simulating observed characteristics of extreme precipitation during the historical period of 1986–2005. The year 2041 was taken as the year when global mean temperature reaches 2°C above pre-industrial levels under unmitigated climate change scenario based on Karmalkar and Bradley (2017). Results indicate that the most prominent changes during the period of 2031–2051 were largely significant. Robust increases in CDD imply impending drier conditions over Indonesia, while increases in RX1day suggest more intense rainfall events over most of Indochina under 2°C global warming scenario. Furthermore, northern Myanmar is projected to experience increases in CDD, R50mm and RX1day, suggesting that the area may face more serious repercussions than other areas in Southeast Asia.

This study investigates the ability to apply National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) products and their downscaling by using the Regional Climate Model version 4.2 (RegCM4.2) on seasonal rainfall forecasts over Vietnam. First, the CFS hindcasts (CFS_Rfc) from 1982 to 2009 are used to assess the ability of the CFS to predict the overall circulation and precipitation patterns at forecast lead times of up to 6 months. Second, the operational CFS forecasts (CFS_Ope) and its RegCM4.2 downscaling (RegCM_CFS) for the period 2012–14 are used to derive seasonal rainfall forecasts over Vietnam. The CFS_Rfc and CFS_Ope are validated against the ECMWF interim reanalysis, the Global Precipitation Climatology Centre (GPCC) analyzed rainfall, and observations from 150 meteorological stations across Vietnam. The results show that the CFS_Rfc can capture the seasonal variability of the Asian monsoon circulation and rainfall distribution. The higher-resolution RegCM_CFS product is advantageous over the raw CFS in specific climatic subregions during the transitional, dry, and rainy seasons, particularly in the northern part of Vietnam in January and in the country’s central highlands during July.

A global river routing scheme coupled to the ECMWF land surface model is implemented and tested within the framework of the Global Soil Wetness Project II, to evaluate the feasibility of modelling global river runoff at a daily time scale. The exercise is designed to provide benchmark river runoff predictions needed to verify the land surface model. Ten years of daily runoff produced by the HTESSEL land surface scheme is input into the TRIP2 river routing scheme in order to generate daily river runoff. These are then compared to river runoff observations from the Global Runoff Data Centre (GRDC) in order to evaluate the potential and the limitations. A notable source of inaccuracy is bias between observed and modelled discharges which is not primarily due to the modelling system but instead of to the forcing and quality of observations and seems uncorrelated to the river catchment size. A global sensitivity analysis and Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty analysis are applied to the global routing model. The ground water delay parameter is identified as being the most sensitive calibration parameter. Significant uncertainties are found in results, and those due to parameterisation of the routing model are quantified. The difficulty involved in parameterising global river discharge models is discussed. Detailed river runoff simulations are shown for the river Danube, which match well observed river runoff in upstream river transects. Results show that although there are errors in runoff predictions, model results are encouraging and certainly indicative of useful runoff predictions, particularly for the purpose of verifying the land surface scheme hydrologicly. Potential of this modelling system on future applications such as river runoff forecasting and climate impact studies is highlighted. Copyright © 2009 Royal Meteorological Society.

[1] The Gravity Recovery and Climate Experiment (GRACE) mission provides measurements of spatiotemporal change in land water storage that may improve simulation results of land surface models (LSMs). We show that a transfer scheme recently developed within the Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) LSM significantly improves the simulated land water storage. Over large tropical rivers basins, model results without the transfer scheme provide significantly smaller amplitudes of water storage than observed by GRACE. Including the transfer scheme that accounts for water stored in the river systems and aquifers during its transfer to the oceans leads to predicted land water storage that are comparable to GRACE observations. Water stored in aquifers contributes about half the seasonal variation of water storage over large basins such as the Amazon, Congo, Yangtze, Ganges, Brahmaputra, and Mekong.

Since its launch in March 2002, the GRACE mission is measuring the global time variations of the Earth's gravity field with a current resolution of ~500 km. Especially over the continents, these measurements represent the integrated land water mass including surface waters (lakes, wetlands and rivers), soil moisture, groundwater and snow cover. In this study, we use the GRACE land water solutions computed by Ramillien et al. (2005a) through an iterative inversion of monthly geoids from April 2002 to May 2004, to estimate time-series of basin-scale regional evapotranspiration rate -and associated uncertainties-. Evapotranspiration is determined by integrating and solving the water mass balance equation, which relates land water storage (from GRACE), precipitation data (from the Global Precipitation Climatology Centre), runoff (from a global land surface model) and evapotranspiration (the unknown). We further examine the sensibility of the computation when using different model runoff. Evapotranspiration results are compared to outputs of four different global land surface models. The overall satisfactory agreement between GRACE-derived and model-based evapotranspiration prove the ability of GRACE to provide realistic estimates of this parameter.

International audience; The output of the ORCHIDEE Land Surface Model, driven by a 53-yr (1948-2000) atmospheric forcing data set, was used to estimate the effects of land water storage on global mean sea level. Over the past half century, no significant trend was detected but there is a strong decadal variability in the land water storage, driven by precipitation and originating principally in the tropics. The land water contribution to sea level change over the past 50 yr appears highly anti-correlated with thermal expansion of the oceans. This result suggests that change in ocean heat content influences the global water cycle. It also shows that, at decadal time scale, there is partial compensation in sea level changes between thermal expansion and ocean water mass change due to changes in land water storage.

International audience; We study the daily to interannual variability of the Red River plume in the Gulf of Tonkin from numerical simulations at high resolution over 6 years (2011–2016). Compared with observational data, the model results show good performance. To identify the plume, passive tracers are used in order to (1) help distinguish the freshwater coming from different continental sources, including the Red River branches, and (2) avoid the low salinity effect due to precipitation. We first consider the buoyant plume formed by the Red River waters and three other nearby rivers along the Vietnamese coast. We show that the temporal evolution of the surface coverage of the plume is correlated with the runoff (within a lag), but that the runoff only cannot explain the variability of the river plume; other processes, such as winds and tides, are involved. Using a K-means unsupervised machine learning algorithm, the main patterns of the plume and their evolution in time are analyzed and linked to different environmental conditions. In winter, the plume is narrow and sticks along the coast most of the time due to the downcoast current and northeasterly wind. In early summer, the southwesterly monsoon wind makes the plume flow offshore. The plume reaches its highest coverage in September after the peak of runoff. Vertically, the plume thickness also shows seasonal variations. In winter, the plume is narrow and mixed over the whole water depth, while in summer, the plume can be detached both from the bottom and the coast. The plume can deepen offshore in summer, due to strong wind (in May, June) or specifically to a recurrent eddy occurring near 19°N (in August). This first analysis of the variability of the Red River plume can be used to provide a general picture of the transport of materials from the river to the ocean, for example in case of anthropogenic chemical substances leaked to the river. For this purpose, we provide maps of the receiving basins for the different river systems in the Gulf of Tonkin.Introduction

0148-0227; International audience; Satellite altimetry from TOPEX/Poseidon (T/P) is used to estimate the variation of the global sea level. This signal, once corrected for steric effects, reflects water mass exchange with the atmosphere and land reservoirs (mainly ice caps, soils and snowpack). It can thus be used to test the capacity of general circulations models (GCMs) to estimate change in land water storage. In this study, we compare the land hydrology contribution to global mean sea level variations during the major 1997-1998 El Nino-Southern Oscillation event from two data sets: (1) the results of the Organizing Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface scheme, developed at the Institute Pierre Simon Laplace, coupled to the Laboratoire de Meteorologie Dynamique Atmospheric General Circulation Model (LMD AGCM) and (2) the T/P-based estimates. We show that the seasonal variation of the continental water storage is well represented in the model. The drastic amplitude change between the two contrasted years, 1997 and 1998, observed from satellite altimetry, is also simulated. We analyze the role of each component of simulated water fluxes (precipitation, evaporation, and runoff) in determining the range of annual continental water mass variation and its interannual variability. The difference between the two years, 1997 and 1998, is, for an essential part, due to land precipitation in the 20° N-20° S domain. This analysis emphasizes the important role of tropical regions in interannual variability of climate.