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Although the surface energy budget is essential to determine Earth's climate, site measurements of various radiative components are still too scarce to properly characterize their spatial and temporal variations. This has led to the development of a growing number of surface radiation products, mainly including remotely sensed data, model reanalysis data, and simulations using General Circulation Models (GCMs). This collection of papers introduces new techniques, including the use of machine learning methods for radiation estimation, and evaluates and compares various radiation products, as well as their spatio-temporal variations. These studies show large discrepancies among various products across nearly all radiative parameters in either accuracy or spatio-temporal variations. However, remotely sensed radiation products perform relatively better than others. Despite this, there is an urgent need for further efforts to address these discrepancies and improve the accuracy of these estimates. Even though the major radiative parameters including downward shortwave radiation, net longwave radiation, and albedo, from most products show insignificant long-term variation trends on a global scale, only specific regions, such as the Yunnan-Kweichow Plateau (YKP) and regions with permafrost (i.e. Qinghai-Tibet Plateau and Arctic) and glaciers (i.e. Altai Mountains) exhibit remarkable trends. [ABSTRACT FROM AUTHOR]

In this paper, we report on the mixing structures and transport properties of the Adriatic Sea surface, as a semi-enclosed basin of the Mediterranean Sea, from October 2006 until December 2011. Lagrangian transport models were used to simulate synthetic trajectories from the mean flow fields obtained by the Massachusetts Institute of Technology general circulation model implemented for the Adriatic. We examine the dispersion properties of numerical pair particles, through the calculation of time-averaged finite-size Lyapunov exponents (FSLEs) in the Adriatic Sea during selected months in each year. The results show the significant effects of river runoff and wind forcing, especially the Bora wind field, on the mixing activities of numerical pair particles by the generation of vortices, which appear as a tangle of filaments on the FSLE maps. The stretch/compression lines, which contain high values of the FSLEs, work as robust transport barriers, most having been detected along boundary currents on the eastern and western flanks of the Adriatic, particularly during winter. Numerical experiments have indicated that stable flows, with less mixing activity, occur in the northern part of the Adriatic in June and September of each year, while the Southern Adriatic Pit has flows with larger seasonal fluctuations and high values of eddy kinetic energy because of the influence of wind and energetic currents entering from the Ionian Sea. [ABSTRACT FROM AUTHOR]

This paper investigates climate change impacts on the hydrology and water quality of Brazilian semi-arid reservoirs. An integrated approach coupling climate, hydrological and water quality models was proposed. Five general circulation models (GCMs) and two future scenarios (SSP2-4.5 and SSP5-8.5) were used for the projections. The simulations showed that uncertainty in climate forecast significantly impacted hydrological and water quality outputs. Some scenarios revealed a strong decrease in streamflow and storage volume. On the other hand, 40% of multi-GCM projections indicated reservoir eutrophication. The impacts on hydrology and water quality under SSP5-8.5 were more significant than those under SSP2-4.5. The results also indicated that drought events may be prolonged under climate change, principally at the end of the 21st century for SSP5-8.5, and may significantly increase the total phosphorus concentration. This suggests that tropical semi-arid reservoirs could be more vulnerable to eutrophication in scenarios of climate change than those in other regions. [ABSTRACT FROM AUTHOR]

The aim of this paper is to estimate the effect that climate change will have on groundwater recharge at the Yucatan Peninsula, Mexico. The groundwater recharge is calculated from a monthly water balance model considering eight methods of potential and actual evapotranspiration. Historical data from 1961–2000 and climate model outputs from five downscaled general circulation models in the near horizon (2015–2039), with representative concentration pathway (RCP) 4.5 and 8.5 are used. The results estimate a recharge of 118 ± 33 mm·year–1 (around 10% of precipitation) in the historical period. Considering the uncertainty from GCMs under different RCP and evapotranspiration scenarios, our monthly water balance model estimates a groundwater recharge of 92 ± 40 mm·year–1 (RCP4.5) and 94 ± 38 mm·year–1 (RCP8.5) which represent a reduction of 23% and 20%, respectively, a result that threatens the socio-ecological balance of the region. [ABSTRACT FROM AUTHOR]

In cold region environments, any alteration in the hydro-climatic regime can have profound impacts on river ice processes. This paper studies the implications of hydro-climatic trends on river ice processes, particularly on the freeze-up and ice-cover breakup along the Athabasca River in Fort McMurray in western Canada, which is an area very prone to ice-jam flooding. Using a stochastic approach in a one-dimensional hydrodynamic river ice model, a relationship between overbank flow and breakup discharge is established. Furthermore, the likelihood of ice-jam flooding in the future (2041–2070 period) is assessed by forcing a hydrological model with meteorological inputs from the Canadian regional climate model driven by two atmospheric–ocean general circulation climate models. Our results show that the probability of ice-jam flooding for the town of Fort McMurray in the future will be lower, but extreme ice-jam flood events are still probable. [ABSTRACT FROM AUTHOR]

One of the most significant climate change impacts on arctic urban landscapes is the warming and degradation of permafrost, which negatively affects the structural integrity of infrastructure. We estimate potential changes in stability of Russian urban infrastructure built on permafrost in response to the projected climatic changes provided by six preselected General Circulation Models (GCMs) participated in the most recent Climate Model Inter-comparison Project (CMIP5). The analysis was conducted for the entire extent of the Russian permafrost-affected area. According to our analysis a significant (at least 25%) climate-induced reduction in the urban infrastructure stability throughout the Russian permafrost region should be expected by the mid-21st century. However, the high uncertainty, resulting from the GCM-produced climate projections, prohibits definitive conclusion about the rate and magnitude of potential climate impacts on permafrost infrastructure. Results presented in this paper can serve as guidelines for developing adequate adaptation and mitigation strategy for Russian northern cities. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change is one of the most impactful global phenomena, affecting multiple ecosystems, particularly wetlands and water bodies, as well as important species that depend on these areas. Flamingos are unique and distinctive species that live exclusively in these environments and are highly impacted by any changes in their breeding or non-breeding wetlands. To address and measure the direct impact that future climatic changes could have on the distribution of the six extant species of flamingos, I used citizen science data and climatic variables to construct habitat suitability models. These models were used to predict the future gain or loss of climatic suitability areas in the short, medium, and long term, under four different Shared Socioeconomic Pathways and eight Global Circulation Models. The results predicted that five out of the six species of flamingos will experience continued loss of habitat over the next few decades in all scenarios. Dramatic changes in distribution are expected for all species. The data also indicate a higher impact of climate change on more habitat restrictive species and on wetlands along the borders of their distributions. Finally, the research highlights the importance of combined efforts from public communities, scientists, and policymakers to create mitigation and conservation plans that could avoid the intensification of climate change effects on wetlands and prevent the future reduction of flamingo populations. [ABSTRACT FROM AUTHOR]

This paper predicts climate change pattern and outlines suitable adaptation strategies related to irrigated agricultural practices in Hakra Branch Canal Command (HBCC) of Pakistan. Climate change predictions were simulated using models perturbed with climatic data and A2 emission scenario. A biased correction method was applied to the simulated future climatic data. The study site reveals different nature of vulnerabilities to the changing climate based on climate change scenario downscaling. The variation in rainfall patterns, especially the seasonal shifts, would have likely impact on water availability for irrigation and subsequently on the crop growth. A detailed survey was conducted to investigate how farmers in HBCC perceive variations in weather patterns and the proposed adaptation measures. The statistical significance of farmers' perceptions and decisions about adaptation measures are reported with regard to their location along the secondary canals. The literature offers a range of potential climate change adaptation measures to the farming community that sometimes are not coherent with the national policy and the local practice. Farmers generally feel it difficult to pick a suitable adaptation option that suits their particular conditions. This research proposes a simple yet robust criterion to prioritize the potential climate change adaptation measures. This criterion (colloquially known as 3P) is based on three subjective factors – i.e. policy, prevalence and practicability – and it could be scaled out to other areas where results of climate change studies are available. [ABSTRACT FROM AUTHOR]

In this study, a simple polynomial bias correction method is developed to correct the bias in the forecasted streamflow (runoff) derived from a global circulation model (GCM). First, a set of polynomial correction factors was derived comparing observed and GCM-derived runoff for a hindcast period (1961–2000) for each of the 11 selected GCMs. The correction factors are used to correct the GCM-derived streamflow for projected periods (2046–2065 and 2081–2100) for the Intergovernmental Panel on Climate Change scenarios A2 and B1 (CMIP3) for the Murray-Hotham catchment of Western Australia. The assumption is that the correction factors derived for each GCM for the observed period (1961–2000) are valid for the projected periods. Results show the method reduces biases considerably for the projected runoff at a catchment scale. The method developed here uses CMIP3 data but it may be applicable to any GCM data, such as CMIP5/CMIP6. [ABSTRACT FROM AUTHOR]

A new shallow layer laboratory model of global atmospheric circulation is realised and studied by experiments and numerical simulations. A shallow rotating cylindrical fluid layer of 30 mm thickness and 690 mm diameter, with a localised heater at the bottom periphery and localised cooler in the central part of the upper boundary is considered. The rim heater imitates the equator heating and disc cooler – the North pole cooling. The flow transforms from the Hadley-like regime to the baroclinic wave regime through transitional states. The decrease in the thermal Rossby number for the fixed value of Taylor number results in the regularisation of the baroclinic waves. All wave regimes, even with regular wave structures, are characterised by strong non-periodic fluctuations. The observed baroclinic wave structures are a combination of temporarily evolving different baroclinic modes. The important outcome of the shallow layer model is a realisation of the Earth-like meridional three-cell structure. It is shown that the three-cell structure with analogs of polar, Ferrel and Hadley cells exist only in a limited range of parameters. A comparison of the results for the water and silicon oil demonstrated that the physical properties of the fluid can have a strong impact on the baroclinic wave structure. [ABSTRACT FROM AUTHOR]

Stable water isotopes in ground-level vapour are key to estimating water exchange between geospheres. Their sampling, however, is limited to laser-absorption spectrometers and satellite observations, having inherent shortcomings. This study investigates diffusive kinetic fractionation during liquid condensation under supersaturated environment, providing a cost-effective, reliable way of sampling ground-level vapour isotopes (18O, 2H). Experiments were undertaken at three locations in India with 'liquid' samples collected from condensation of ambient air at 0°C. Simultaneously, pristine 'vapour' was sampled via cryogenic-trapping using liquid nitrogen–alcohol slush at –78°C. The 'liquid' condensed under supersaturation was progressively more depleted in 18O, and less enriched in 2H than expected under equilibrium fractionation, with an increasing degree of supersaturation expressed as saturation index (Si). This study revealed: (1) Si, molecular density, Rh, T together control the extent of isotopic kinetic fractionation. (2) The presence of diffusive concentration gradient inhibits the flow of heavier isotopes during liquid condensation. (3) The stochastic nature of the process cannot be explained using a physics-based model alone. The artificial neural network model is hence deployed to sample δ18O (δ2H) within –0.24 ± 1.79‰ (0.53 ± 11.23 ‰) of true value. (4) The approach can be extended to ground-validate isotope-enabled general circulation models and satellite observations. [ABSTRACT FROM AUTHOR]

A global eddy-resolving forecast system LFS is developed based on a primitive ocean general circulation model. The system's configuration, forecast experiments, and a preliminary evaluation of the preoperational system are shown. In the preoperational stage, since the full data assimilation has not yet been set up for LFS, the initial state is obtained by nudging the ocean temperature and salinity from an ocean analysis dataset. Despite this, the LFS demonstrates a generally good performance in short-term oceanography forecasting, except for sea level anomaly (SLA). The median values of the 1-day forecast leading root mean square error (RMSE) for the sea surface temperature (SST), SLA, upper 2000 m temperature, and salinity are approximately 0.52°C, 0.10 m, 0.57°C and 0.13 psu, respectively. Although there are slight warm biases in the forecasted SST, the forecasts of temperature and salinity in the thermocline by the LFS are comparable with the results of operational oceanography systems under the framework of the Intercomparison and Validation Task Team. However, the forecast SLA has a relatively large RMSE related to the absence of direct observational constraints in the initial state. Further investigations are needed to improve the performance of LFS. [ABSTRACT FROM AUTHOR]

Surface incident shortwave radiation (Rs) can promote the circulation of substance and energy, and the accuracy of its estimation is of great significance for climate studies. The Rs can be acquired from satellite retrievals, reanalysis predictions and general circulation model (GCM) simulations. Although Rs estimates have been evaluated and compared in previous studies, most of them focus on evaluating the Rs estimates over specific regions using ground measurements from limited stations. Therefore, it is essential to comprehensively validate Rs estimates from multiple data sources. In this study, ground measurements of 690 stations from BSRN, GEBA, CMA, GC-NET and buoys were employed to validate the Rs estimates from seven representative products (GLASS, GEWEX-SRB, CERES-EBAF, ERA5, MERRA2, CFSR and CMIP6). The validation results indicated that the selected products overestimated Rs globally, with biases ranged from 0.48 to 21.27 W/m2. The satellite retrievals showed relatively better accuracy among seven datasets compared to ground measurements at the selected stations. Moreover, the selected seven products were all in poor accuracy at high-latitude regions with RMSEs greater than 50 W/m2. The long-term variation trends were also analyzed in this study. [ABSTRACT FROM AUTHOR]

This study presents an approach for modelling and mapping fluvial flooding, considering both land use/land cover (LULC) change and climate change, and applies it to the Brahmani River Basin in eastern India. Climate change projections were obtained from the Coupled Model Intercomparison Project Phase 6 (CMIP6), and their impacts on the hydrology of the catchment were investigated using HEC-HMS and HEC-RAS software. Results reveal that changes in LULC types, specifically an increase in proportions of agricultural and built-up areas and a decrease in forest cover, as undergone between years 1985 and 2018, have increased peak discharge following a storm, thereby causing an increase in spatial extent of floods of different return periods. Moreover, downscaled climate change scenarios from two General Circulation Models were used to determine potential changes in river discharge according to two GHG emission scenarios from the latest IPCC: SSP245 and SSP585. The projections indicate that peak discharge and the spatial extent of flooded areas will increase for floods with return periods ranging from two to 100 years. This study demonstrates the important influence that changes in LULC have had on the susceptibility of the BRB to flooding, with climate change projected to further enhance the risk of flooding as the century progresses. [ABSTRACT FROM AUTHOR]

In this study, the Hydrologic Evaluation of Landfill Performance (HELP3.8D) model was developed to evaluate the spatiotemporal distribution of potential groundwater recharge (GWR) in Tasuj aquifer, northwestern Iran. High-resolution future climatic data from second-generation Canadian Earth System Model (CanESM2) general circulation models (GCMs) was produced under different scenarios of Representative Concentration Pathways (RCP2.6, RCP4.5, and RCP8.5). The analysis of climate parameters demonstrated that under RCP2.6, climatic variation will be substantially similar to that of the observed period (1961–2005), while moderate and severe droughts are anticipated under scenarios RCP4.5 and RCP8.5, respectively, over 2017–2030. The projection results showed that GWR will be altered by climate change, on average, from 31 mm/year at baseline to 32 (+3%), 28.5 (−8%) and 11.5 (−63%) mm/year under the RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively. This approach can be easily replicated by other researchers and could be beneficial for monitoring water security and managing groundwater resources in other catchment areas. [ABSTRACT FROM AUTHOR]

The impact of climate change on the agricultural and water resources sectors cannot be overemphasized since West Africa is prone to drought as a result of high variability in rainfall and temperature. In this study, an assessment on the impact of climate change in the Sahel Region of Nigeria (SRN) on drought was carried out between 1971 and 2060. Gridded temperature and rainfall datasets from Climate Research Unit (CRU) and seven Global Climate Models (GCMs) using regional climate model (RCA-4) under Representative Concentration Pathway (RCP) 8.5 scenario were used. Standardized Precipitation and Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) at 3- and 12-month time steps were used for drought characterization. The RCA-4 ensemble of the 7 GCMs was able to pattern the seasonal cycle of the maximum and minimum temperatures of SRN well as most of the climatic features were captured as indicated by the CRU observation. Furthermore, the results indicated by the RCA-4 ensemble median of SPEI-3 and SPEI-12 show more drought intensity changes than SPI-3 and SPI-12 as the twenty-first century progresses. An awareness that can help policymakers know the impact climate change may have on the agricultural and hydrological sectors of SRN was created. [ABSTRACT FROM AUTHOR]

Studies to understand the role of future climate on transportation infrastructure may use climate multiple models and interpret the results based on the statistical variation in simulated outcomes. Unfortunately, specific guidance on the models to choose that ensure results span the breadth of possible outcomes is limited, and the solution involves running simulations using as many models as possible. The objective of this study is to provide guidance on which models from the Coupled Intercomparison Project 5 (CMIP5) dataset to use for pavement studies in the United States and in so doing provide a framework for selecting models from other datasets and locations. Effective temperature functions are derived and used to select individual models from the CMIP5 dataset that represent the maximum, median, and minimum outcomes of the whole ensemble. The results are clustered based on region and represent relatively hot, cold, and median future assumptions. The model selection process is verified using detailed pavement analyses with all models at individual pavement sites in four states. The models chosen using the effective temperature approach are found to align with the extremes and the median, with further improvements to median estimates obtained by averaging all three (maximum, minimum, and median) models. [ABSTRACT FROM AUTHOR]

A spatio-temporal analysis of representative concentration pathways (RCPs)-based projections of surface air temperatures under different combinations of global circulation models (GCMs) and RCPs for Satluj River Basin has been presented. The projections of temperature anomalies have been obtained for several meteorological stations in the basin using 16 different combinations of emission scenarios and global climate models (GCMs). For each combination, the projections of temperature anomalies have been analysed for two future time periods centred at 2030 and 2050. The results of the analysis conducted herein clearly indicate that the temperature will rise for all the future time scales with the maximum increase being projected under RCP8.5 compared to the baseline 1986–2005. However, there is large inter-model variability in the projections of temperature anomalies under different RCPs. Under RCP 8.5, the average temperature in Satluj basin is projected to rise by around 4°C by mid of the twenty-first century. The projections of temperature anomalies analysed herein could be potentially used for the evaluation of hydrological impacts of climate change in Satluj River Basin—a key basin in the Himalayan region from the view point of global warming. [ABSTRACT FROM AUTHOR]

Rainwater tanks or cisterns are a low impact development infrastructure used to control stormwater runoff and reduce water demand. However, climate change may affect its performance due to increased rainfall intensities. This study evaluates the uncertainty on the effectiveness of cisterns to reduce peak runoff under climate change in an urban watershed in Brazil. Twelve updated intensity-duration-frequency curves, based on six Global Circulation Models and two Representative Concentration Pathways (RCP 4.5 and RCP 8.5) from the Coupled Model Inter-comparison Project 5, were used to yield hyetographs for 2 h-storm events with different recurrence intervals. Peak runoff reduction ranged between 0.4% and 5.5% for RCP 4.5 and 0.4% and 6.3% for RCP 8.5. Under climate change, a reasonable runoff control could be reached if at least 20% of the buildings installed a 5 m3 cistern. Uncertainty in future climate should be addressed in rainfall-runoff modelling to guide stormwater management decisions. [ABSTRACT FROM AUTHOR]

A downscaling model capable of explaining the temporal and spatial variability of regional hydroclimatic variables is essential for reliable climate change studies and impact assessments. This study proposes a novel statistical approach based on generalized hierarchical linear model (GHLM) to downscale precipitation from the outputs of general circulation models (GCMs) at multiple sites. GHLM partitions the total variance of precipitation into within- and between-site variability allowing for transferring information between sites to develop a regional downscaling model. The methodology is demonstrated by downscaling precipitation using the outputs of eight GCMs in Lake Urmia basin in northwestern Iran. Multi-model ensemble simulations are merged and bias-corrected using Bayesian model averaging and equidistant quantile mapping, respectively. The results of this study show projected declining trends in precipitation resulting in approximately 11.2% and 15.3% decrease during 2060–2080 compared to the historical period of 1985–2005 considering representative concentration pathways (RCPs) 4.5 and 8.5, respectively. [ABSTRACT FROM AUTHOR]

This study investigated the impacts of changes in land cover and climate on runoff and sediment yield in a river basin in India. Land Change Modeler was used to derive the future land cover and its changes using the Sankey diagram approach. The future climatic parameters were derived from five general circulation models for two emission scenarios with representative concentration pathways (RCPs) 4.5 and 8.5. The land cover and climate change impacts on runoff and sediment yield were estimated using SWAT model. The results show important changes in land cover and indicate that urban and agricultural areas strongly influence the runoff and sediment yield. Among the land cover and climate change impacts, climate has more predominant (70%–95%) impact. Runoff and sediment yield are likely to decrease in both RCP scenarios in the future period. The impacts of land cover changes are more prominent on sediment yield than runoff. [ABSTRACT FROM AUTHOR]

Uncertainty in climate change impacts on river discharge in the Upper Awash Basin, Ethiopia, is assessed using five MIKE SHE hydrological models, six CMIP5 general circulation models (GCMs) and two representative concentration pathways (RCP) scenarios for the period 2071–2100. Hydrological models vary in their spatial distribution and process representations of unsaturated and saturated zones. Very good performance is achieved for 1975–1999 (NSE: 0.65–0.8; r: 0.79–0.93). GCM-related uncertainty dominates variability in projections of high and mean discharges (mean: –34% to +55% for RCP4.5, – 2% to +195% for RCP8.5). Although GCMs dominate uncertainty in projected low flows, inter-hydrological model uncertainty is considerable (RCP4.5: –60% to +228%, RCP8.5: –86% to +337%). Analysis of variance uncertainty attribution reveals that GCM-related uncertainty occupies, on average, 68% of total uncertainty for median and high flows and hydrological models no more than 1%. For low flows, hydrological model uncertainty occupies, on average, 18% of total uncertainty; GCM-related uncertainty remains substantial (average: 28%). [ABSTRACT FROM AUTHOR]

In this study, three representative concentration pathways (RCPs) and 15 general circulation models of the Coupled Model Intercomparison Project Phase 5 were used to assess the behaviour of precipitation (P) and surface air temperature (SAT) over part of the Songhua River Basin. The Water Evaluation and Planning (WEAP) model linked with SAT and P was used for monthly simulation of streamflow to assess the influence of land use/land cover and climate change on the streamflow. The results suggest that, under RCP2.6, RCP4.5 and RCP8.5, the SAT over the study area may increase in the 21st century by 1.12, 2.44 and 5.82°C, respectively. Moreover, by the middle of the 21st century, streamflow in the basin may have decreased by 19%. The decrease in streamflow may be due to changed land use conditions and water withdrawal, having critical implications for management and future planning of water resources in the basin. [ABSTRACT FROM AUTHOR]

Clustering of tracers floating on the ocean surface and evolving due to combined velocity fields consisting of a deterministic mesoscale component and a kinematic random component is analysed. The random component represents the influence of submesoscale motions. A theory of exponential clustering in random velocity fields is applied to characterise the obtained clustering scenarios in both steady and unsteady time-dependent mesoscale flows, as simulated by a comprehensive realistic, eddy-resolving, general circulation model for the Japan/East Sea. The mesoscale flow field abounds in transient eddy-like patterns modulating and branching the main currents, and the underlying time-mean flow component features closed recirculation zones that can entrap the tracer. The submesoscale flow component is modelled kinematically, as a divergent random velocity field with a prescribed correlation radius and variance. The combined flow induces tracer clustering, that is, the exponential growth of tracer density in patches with vanishing areas. The statistical topography methodology, which provides integral characteristics to quantify the emerging clusters, uncovers drastic dependence of the clustering rates on whether the mesoscale flow component is taken to be steady or time-dependent. The former situation favours robust exponential clustering, similar to the theoretically understood case of purely divergent and zero-mean random velocity. The latter situation, on the contrary, hinders exponential clustering due to significant advection of the tracer out of the nearly enclosed eddies, at the rate faster than the clustering rate. [ABSTRACT FROM AUTHOR]

Rainfall events largely control hydrological processes occurring on and in the ground, but the performance of climate models in reproducing rainfall events has not been investigated enough to guide selection among the models when making hydrological projections. We proposed to compare the durations, intensities, and pause periods, as well as depths of rainfall events when assessing the accuracy of general circulation models (GCMs) in reproducing the hydrological characteristics of observed rainfall. We also compared the sizes of design storm events and the frequency and severity of drought to demonstrate the consequences of GCM selection. The results show that rainfall and extreme hydrological event projections could significantly vary depending on climate model selection and weather stations, suggesting the need for a careful and comprehensive evaluation of GCM in the hydrological analysis of climate change. The proposed methods are expected to help to improve the accuracy of future hydrological projections for water resources planning. [ABSTRACT FROM AUTHOR]

Riparian depressional wetlands (haors) in the Upper Meghna River Basin of Bangladesh are invaluable agricultural resources. They are completely flooded between June and November and planted with Boro rice when floodwater recedes in December. However, early harvest period (April/May) floods frequently damage ripening rice. A calibrated/validated Soil and Water Assessment Tool for riparian wetland (SWATrw) model is perturbed with bias free (using an improved quantile mapping approach) climate projections from 17 general circulation models (GCMs) for the period 2031–2050. Projected mean annual rainfall increases (200–500 mm or 7–10%). However, during the harvest period lower rainfall (21–75%) and higher evapotranspiration (1–8%) reduces river discharge (5–18%) and wetland inundation (inundation fraction declines of 0.005–0.14). Flooding risk for Boro rice consequently declines (rationalized flood risk reductions of 0.02–0.12). However, the loss of cultivable land (15.3%) to increases in permanent haor inundation represents a major threat to regional food security. [ABSTRACT FROM AUTHOR]

The possible changes in precipitation of Syrian due to climate change are projected in this study. The symmetrical uncertainty (SU) and multi-criteria decision-analysis (MCDA) methods are used to identify the best general circulation models (GCMs) for precipitation projections. The effectiveness of four bias correction methods, linear scaling (LS), power transformation (PT), general quantile mapping (GEQM), and gamma quantile mapping (GAQM) is assessed in downscaling GCM simulated precipitation. A random forest (RF) model is performed to generate the multi model ensemble (MME) of precipitation projections for four representative concentration pathways (RCPs) 2.6, 4.5, 6.0, and 8.5. The results showed that the best suited GCMs for climate projection of Syria are HadGEM2-AO, CSIRO-Mk3-6-0, NorESM1-M, and CESM1-CAM5. The LS demonstrated the highest capability for precipitation downscaling. Annual changes in precipitation is projected to decrease by −30 to −85.2% for RCPs 4.5, 6.0, and 8.5, while by < 0.0 to −30% for RCP 2.6. The precipitation is projected to decrease in the entire country for RCP 6.0, while increase in some parts for other RCPs during wet season. The dry season of precipitation is simulated to decrease by −12 to −93%, which indicated a drier climate for the country in the future. [ABSTRACT FROM AUTHOR]

The Vietnamese Mekong Delta (VMD) is one of the world's most vulnerable deltas to climate change and sea level rise. Adequate understandings of future hydrological changes are crucial for effective water management and risk-proofing, however, this knowledge body is currently very limited. This study quantifies the responses of the VMD's river flow regime to multiple stimuli, namely future upstream inflow variation, local climate change, and sea level rise. The one-dimensional hydrodynamic model MIKE 11 was used to simulate discharges and water levels across the delta. We developed four scenarios to represent changes in the upstream discharges, precipitation changes and sea level rise, covering the 2036–2065 period. We downscaled climate data and applied three bias-correction methods for five General Circulation Models (GCM), and two Representative Concentration Pathways (RCPs). The climate change projections show similar trends of increasing wet season precipitation and decreasing dry season precipitation. However, cross-scenario variations are sometimes large, depending on the individual GCMs, the RCPs and specific locations. The hydraulic simulation results indicate that, under discharge changes between −20% and +10%, combined with in-delta precipitation variations during the dry season, river discharges at the four representative stations could reduce substantially from −2.5% to −100.2%. During the wet season, the calculated river discharges show increase between 7.3% and 46.7% under four considered scenarios. Substantial changes in the VMD's river flow regime could have potentially serious implications for water management, especially saltwater intrusion, and therefore calling for timely adaptation measures. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Páramos are the high-elevation ecosystems of the humid tropical Andes, characterised by the presence of giant rosettes of the Espeletiinae subtribe (Asteraceae). Forecasted climate change is likely to reduce the extent of the area climatically suitable/occupied currently by Espeletiinae and their elevation distribution patterns. Aims: The aim of this study was to estimate the potential impacts of forecasted climate change on the geographic distribution (extent of area and elevation distribution patterns) of 28 species of Espeletiinae that have been recorded in the Cordillera de Mérida, Venezuela. Methods: Six bioclimatic variables, downscaled to a 90 m × 90 m cell size, were used to construct species distribution models (SDM) for the 28 species to model their current and likely future distribution (2070) by using two general circulation models and four representative concentration pathways (RCP). Results: Nine species were estimated to have potential distribution over less than 1000 km2 and five over less than 500 km2, in current climatic conditions. Fifteen and eight species had elevation spans narrower than 1000 m and 500 m, respectively. No significant differences in modelled areas or spans were detected between north, central and south sections of the Cordillera de Mérida. Mean ± SE future reduction in the extent of area climatically suitable were estimated between 51.3% ± 6.3% (RCP2.6) and 78.1% ± 5.3% (RCP8.5), coupled with upward range retreat of between 277.8 m ± 27.4 m (RCP2.6) and 762.5 m ± 59.8 m (RCP8.5). Conclusions: Our study predicts large reductions in modelled area and important upward shifts in the distribution of Venezuelan Espeletiinae by 2070 compared to their current distribution. [ABSTRACT FROM AUTHOR]

A rainfall–streamflow model is proposed, in which a downscaled rainfall series and its wavelet-based decomposed sub-series at optimum lags were used as covariates in GAMLSS (Generalized Additive Model in Location, Scale and Shape). GAMLSS is applied in climate change impact assessment using CMIP5 general climate model to simulate daily streamflow in three sub-catchments of the Onkaparinga catchment, South Australia. The Spearman correlation and Nash-Sutcliffe efficiency between the observed and median simulated streamflow values were high and comparable for both the calibration and validation periods for each sub-catchment. We show that the GAMLSS has the capability to capture non-stationarity in the rainfall–streamflow process. It was also observed that the use of wavelet-based decomposed rainfall sub-series with optimum lags as covariates in the GAMLSS model captures the underlying physics of the rainfall–streamflow process. The development and application of an empirical rainfall–streamflow model that can be used to assess the impact of catchment-scale climate change on streamflow is demonstrated. [ABSTRACT FROM AUTHOR]

Juniperus procera is the most preferred tree in Ethiopia. It is an endangered tree species enumerated in IUCN red list. Accordingly, this study investigates the future suitable habitat of the J. procera under climate change in northern Ethiopia. Three occurrence districts were visited and 124 presence observations were taken. The records, altitude, and 19 bio-climatic variables were used to run a species distribution model to account for the climate change effect on the species. Maxent, Diva-GIS, and ArcGIS were used to evaluate the outputs. Future suitable habitats were projected into mid and end-century time frames with two Representative Concentration Pathways (RCP2.6 and 8.5) under one General Circulation Model, namely the Climate Community System Model Version-4. Our results showed that minimum temperature of the coldest month and altitude are main predictors of the distribution of the species. Suitable habitats of the species will be decreased by 79.84%, 91.17%, 75.31%, and 96.25% in Mid-century RCP2.6, Mid-century RCP8.5, End-century RCP2.6, and End-century RCP8.5 when compared with current distributions, respectively. This indicates that climate change will affect the future distribution of the species. The results of the study indicate that appropriate management strategies must be taken to ensure the long-term survival of J. procera. [ABSTRACT FROM AUTHOR]

The Kalu Ganga catchment is one of the largest in Sri Lanka, and is home to 5% of the national population. A first assessment is provided here of the sensitivity of Kalu Ganga runoff to a 2°C increase in global mean temperature – the supposed threshold for “dangerous” climate change. Runoff is simulated using the HBV-Light hydrological model and scenario data from seven general circulation models (GCMs). Precipitation is the strongest cause of change in runoff. Substantial inter-GCM differences in scenario precipitation lead to uncertainty in the direction of change in mean annual runoff from the baseline (range −25% to +19%). Scenario monthly runoff ranges from −41% to +124% of the baseline values at its most extreme (March); June is the only month with a consistent direction of change (range −17% to −65%) – thus indicating that climate change may lead to a substantially different hydrological regime in the Kalu Ganga catchment. [ABSTRACT FROM PUBLISHER]

Climatic and hydrological changes will likely be intensified in the Upper Blue Nile (UBN) basin by the effects of global warming. The extent of such effects for representative concentration pathways (RCP) climate scenarios is unknown. We evaluated projected changes in rainfall and evapotranspiration and related impacts on water availability in the UBN under the RCP4.5 scenario. We used dynamically downscaled outputs from six global circulation models (GCMs) with unprecedented spatial resolution for the UBN. Systematic errors of these outputs were corrected and followed by runoff modelling by the HBV (Hydrologiska ByrånsVattenbalansavdelning) model, which was successfully validated for 17 catchments. Results show that the UBN annual rainfall amount will change by −2.8 to 2.7% with a likely increase in annual potential evapotranspiration (in 2041–2070) for the RCP4.5 scenario. These changes are season dependent and will result in a likely decline in streamflow and an increase in soil moisture deficit in the basin. [ABSTRACT FROM PUBLISHER]

A problem frequently met in engineering hydrology is the forecasting of hydrological variables conditional on their historical observations and the hindcasts and forecasts of a deterministic model. On the contrary, it is a common practice for climatologists to use the output of general circulation models (GCMs) for the prediction of climatic variables despite their inability to quantify the uncertainty of the predictions. Here we apply the well-established Bayesian processor of forecasts (BPF) for forecasting hydroclimatic variables using stochastic models through coupling them with GCMs. We extend the BPF to cases where long-term persistence appears, using the Hurst-Kolmogorov process (HKp, also known as fractional Gaussian noise) and we investigate its properties analytically. We apply the framework to calculate the distributions of the mean annual temperature and precipitation stochastic processes for the time period 2016–2100 in the United States of America conditional on historical observations and the respective output of GCMs. [ABSTRACT FROM PUBLISHER]

We apply a complex hydro-meteorological modelling chain for investigating the impact of climate change on future hydrological extremes in Central Vietnam, a region characterized by limited data availability. The modelling chain consists of six General Circulation Models (GCMs), six Regional Climate Models (RCMs), six bias correction (BC) approaches, the fully distributed Water Flow and Balance Simulation Model (WaSiM), and extreme values analysis. Bias corrected and raw climate data are used as input for WaSiM. To derive hydrological extremes, the generalized extreme value distribution is fitted to the annual maxima/minima discharge. We identify limitations according to the fitting procedure and the BC methods, and suggest the usage of the delta change approach for hydrological decision support. Tendencies towards increased high- and decreased low flows are concluded. Our study stresses the challenges in using current GCMs/RCMs in combination with state-of-the-art BC methods and extreme value statistics for local impact studies. [ABSTRACT FROM AUTHOR]

An attempt is made to assess the future trend of spatio-temporal variation of precipitation over a medium-sized river basin. The Statistical Downscaling Model (SDSM, version 4.2) is used to downscale the outputs from two general circulation models (GCMs) for three future epochs: epoch-1 (2011–2040), epoch-2 (2041–2070) and epoch-3 (2071–2100). Considering the Upper Mahanadi Basin as a test bed, the study results indicate a “wetter” monsoon (June–September) and the annual increase in precipitation is 12% during epoch-3, which is consistent for both GCMs. Monthly analyses indicate that the precipitation totals are likely to increase and the magnitude of increase is greater during monsoon months than non-monsoon months. The number of month-wise daily extremes increases in most months in the year. However, the maximum percentage increase (with respect to baseline period, 1971–2000) in the number of extreme events is found in the non-monsoon months (specifically before and after the monsoon). [ABSTRACT FROM AUTHOR]

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1–4°C and 1–5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$). Implications: Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1–5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$). [ABSTRACT FROM AUTHOR]

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