scholarly journals A model-based assessment of the effects of projected climate change on the water resources of Jordan

2010 ◽  
Vol 368 (1931) ◽  
pp. 5151-5172 ◽  
Author(s):  
A. J. Wade ◽  
E. Black ◽  
D. J. Brayshaw ◽  
M. El-Bastawesy ◽  
P. A. C. Holmes ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Model ◽  
Regional Climate ◽  
Water Security ◽  
Annual Rainfall ◽  
Near Surface ◽  
Modelling Framework ◽  
Air Temperatures ◽  
Extreme Flood

This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

scholarly journals Uncertainties in climate change projections and regional downscaling in the tropical Andes: implications for water resources management

2010 ◽  
Vol 14 (7) ◽  
pp. 1247-1258 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Tropical Andes ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

Climate Change Impacts on Jordan River Flow: Downscaling Application from a Regional Climate Model

2010 ◽  
Vol 11 (4) ◽  
pp. 860-879 ◽  
Author(s):  
Rana Samuels ◽  
Alon Rimmer ◽  
Andreas Hartmann ◽  
Simon Krichak ◽  
Pinhas Alpert
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Local Level ◽  
Regional Climate ◽  
Resource Planning ◽  
Annual Rainfall ◽  
Future Climate Change ◽  
Jordan River ◽  
Response Models

Abstract The integration of climate change projections into hydrological and other response models used for water resource planning and management is challenging given the varying spatial resolutions of the different models. In general, climate models are generated at spatial ranges of hundreds of kilometers, while hydrological models are generally watershed specific and based on input at the station or local level. This paper focuses on techniques applied to downscale large-scale climate model simulations to the spatial scale required by local response models (hydrological, agricultural, soil). Specifically, results were extracted from a regional climate model (RegCM) simulation focused on the Middle East, which was downscaled to a scale appropriate for input into a local watershed model [the Hydrological Model for Karst Environment (HYMKE)] calibrated for the upper Jordan River catchment. With this application, the authors evaluated the effect of future climate change on the amount and form of precipitation (rain or snow) and its effect on streamflow in the Jordan River and its tributaries—the major water resources in the region. They found that the expected changes in the form of precipitation are nearly insignificant in terms of changing the timing of streamflow. Additionally, the results suggest a future increase in evaporation and decrease in average annual rainfall, supporting expected changes based on global models in this region.

Evaluation of the impacts of climate change and land-use dynamics on water resources: The case of the Lobo River watershed: Central-Western Côte d'Ivoire

2021 ◽  
Author(s):  
Berenger Koffi ◽  
Zilé Alex Kouadio ◽  
Affoué Berthe Yao ◽  
Kouakou Hervé Kouassi ◽  
Martin Sanchez Angulo ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Water Resource Management ◽  
Climate Model ◽  
Regional Climate ◽  
Mean Annual Temperature ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Impacts Of Climate Change

<p>Meeting growing water needs in a context of increasing scarcity of resources due to climate change and changes in land use is a major challenge for developing countries in the coming years. The watershed of the Lobo river in Nibéhibé does not escape this dilemma. The water retention of the Lobo River and its watershed play an important role in the subsistence of the inhabitants of the region. However, the watershed is currently subject to strong human pressures mainly associated with the constant increase in human population and intensification of agricultural activities. The main objective of this study is to assess the impacts of climate change on the water resources of the Lobo River watershed at Nibéhibé in the central-western part of Côte d'Ivoire. Two climate change scenarios (RCP4.5 and RCP8.5) were established using the regional climate model RCA4 (Rossby Centre atmospheric model 4) and the flows under these scenarios were simulated by the hydrological model CEQUEAU with respect to a reference period (1986-2005). The RCA4 regional model predicts an increase of 1.27° C; 2.58° C in the horizon 2021-2040 and 2051-2070 in mean annual temperature. Rainfall would also experience a significant average annual decrease of about 6.51% and 11.15% over the period 2021-2040 and 2041-2070. As for the evolution of flows, the Cequeau model predicts a decrease in the runoff and infiltration of water on the horizon 2021-2040 and an increase in evapotranspiration over time according to the RCP4.5 scenario. However, the model predicts an increase in runoff at the expense of a decrease in REE and infiltration at the horizon 2040-2070 according to scenario RCP8.5. It appears from this study that surface flows and infiltrations, which constitute the water resources available to meet the water needs of the basin's populations, will be the most affected. The results obtained in this study are important and could contribute to guide decision making for sustainable water resource management.</p>

scholarly journals Adaptability of Mediterranean Agricultural Systems to Climate Change: The Example of the Sierra Mágina Olive-Growing Region (Andalusia, Spain). Part II: The Future

2014 ◽  
Vol 6 (4) ◽  
pp. 451-467 ◽  
Author(s):  
Josyane Ronchail ◽  
Marianne Cohen ◽  
María Alonso-Roldán ◽  
Hélène Garcin ◽  
Benjamin Sultan ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Model ◽  
Rainfall Variability ◽  
Regional Climate ◽  
Interdisciplinary Approach ◽  
Olive Tree ◽  
Adaptation To Climate Change ◽  
Surface Water Resources ◽  
Annual Reduction

Abstract The adaptability of olive-growing systems to climate change is studied in the Sierra Mágina region (Andalusia) using an interdisciplinary approach that evaluates and makes associations across climate, water resources, and socioeconomic strategies. First, the evolution of rainfall and temperature during the twenty-first century is assessed at the local scale using 17 regional climate model (RCM) simulations. A 15%–30% rainfall reduction is expected in the fall combined with a 7%–9% annual reduction by 2030–50. Based on a regression model relating yields to rainfall, residual yields (independent of the increasing trend in the present period and from the biennial fruit bearing of the olive tree) are projected to decrease by 7% and 3.5% by 2030–50 for rainfed and irrigated olive groves, respectively. Substantial uncertainties in these results are discussed. A GIS analysis shows a reduction of ground and surface water resources, which are the basis of the present adaptation to rainfall variability, and an uneven potential for adaptation to climate change in the Sierra Mágina region. Despite the important challenges faced by this rural region, there is no consensus among the local key actors regarding adaptation strategies. This is due in part to the diversity among farmers, but also to the different levels of awareness about climate change among all the stakeholders and farmers. Since the projected decline in medium-range future yields is not very high, there might be time and possibilities, especially in the northern part of the Sierra Mágina, to build a local adaptability strategy within the next 20 years that would take into account improved methods of water management and a better economic valorization of olive oil. But at longer time scales, the adaptability of the olive-growing system to yield and water resource declines seems to be threatened.

scholarly journals Assessment of Local Climate Change: Historical Trends and RCM Multi-Model Projections Over the Salento Area (Italy)

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 978 ◽  
Author(s):  
Marco D’Oria ◽  
Maria Tanda ◽  
Valeria Todaro
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
Warm Season ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Local Climate

This study provides an up-to-date analysis of climate change over the Salento area (southeast Italy) using both historical data and multi-model projections of Regional Climate Models (RCMs). The accumulated anomalies of monthly precipitation and temperature records were analyzed and the trends in the climate variables were identified and quantified for two historical periods. The precipitation trends are in almost all cases not significant while the temperature shows statistically significant increasing tendencies especially in summer. A clear changing point around the 80s and at the end of the 90s was identified by the accumulated anomalies of the minimum and maximum temperature, respectively. The gradual increase of the temperature over the area is confirmed by the climate model projections, at short—(2016–2035), medium—(2046–2065) and long-term (2081–2100), provided by an ensemble of 13 RCMs, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). All the models agree that the mean temperature will rise over this century, with the highest increases in the warm season. The total annual rainfall is not expected to significantly vary in the future although systematic changes are present in some months: a decrease in April and July and an increase in November. The daily temperature projections of the RCMs were used to identify potential variations in the characteristics of the heat waves; an increase of their frequency is expected over this century.

scholarly journals Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach

2013 ◽  
Vol 26 (10) ◽  
pp. 3394-3414 ◽  
Author(s):  
C. Adam Schlosser ◽  
Xiang Gao ◽  
Kenneth Strzepek ◽  
Andrei Sokolov ◽  
Chris E. Forest ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Projections ◽  
Massachusetts Institute Of Technology ◽  
Adaptation To Climate Change ◽  
Intergovernmental Panel ◽  
Near Surface ◽  
Institute Of Technology

Abstract The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: specifically, the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, the authors present a technique that extends the latitudinal projections of the 2D atmospheric model of the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and this approach is demonstrated in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, the authors characterize the climate models’ spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of metaensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate model projections. This hybridization of the climate model longitudinal projections with the global and latitudinal patterns projected by the IGSM can, in principle, be applied to any given state or flux variable that has the sufficient observational and model-based information.

scholarly journals Modelling the Impacts of Climate Change on Shallow Groundwater Conditions in Hungary

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 668
Author(s):  
Attila Kovács ◽  
András Jakab
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Groundwater Resources ◽  
Regional Climate ◽  
Shallow Groundwater ◽  
Predictive Modelling ◽  
Climate Impacts ◽  
Annual Rainfall ◽  
Groundwater Levels

The purpose of the present study was to develop a methodology for the evaluation of direct climate impacts on shallow groundwater resources and its country-scale application in Hungary. A modular methodology was applied. It comprised the definition of climate zones and recharge zones, recharge calculation by hydrological models, and the numerical modelling of the groundwater table. Projections of regional climate models for three different time intervals were applied for the simulation of predictive scenarios. The investigated regional climate model projections predict rising annual average temperature and generally dropping annual rainfall rates throughout the following decades. Based on predictive modelling, recharge rates and groundwater levels are expected to drop in elevated geographic areas such as the Alpokalja, the Eastern parts of the Transdanubian Mountains, the Mecsek, and Northern Mountain Ranges. Less significant groundwater level drops are predicted in foothill areas, and across the Western part of the Tiszántúl, the Duna-Tisza Interfluve, and the Szigetköz areas. Slightly increasing recharge and groundwater levels are predicted in the Transdanubian Hills and the Western part of the Transdanubian Mountains. Simulation results represent groundwater conditions at the country scale. However, the applied methodology is suitable for simulating climate change impacts at various scales.

scholarly journals Uncertainties in climate change projections and regional downscaling: implications for water resources management

2010 ◽  
Vol 7 (2) ◽  
pp. 1821-1848 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Regional Climate Model ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

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