Estimating future daily pan evaporation for Qatar using the Hargreaves model and statistically downscaled global climate model projections under RCP climate change scenarios

2020 ◽  
Vol 13 (18) ◽  
Author(s):  
Xiaohui Yan ◽  
Abdolmajid Mohammadian
2013 ◽  
Vol 17 (12) ◽  
pp. 4941-4956 ◽  
Author(s):  
V. Mahat ◽  
A. Anderson

Abstract. Rivers in Southern Alberta are vulnerable to climate change because much of the river water originates as snow in the eastern slopes of the Rocky Mountains. Changes in likelihood of forest disturbance (wildfire, insects, logging, etc.) may also have impacts that are compounded by climate change. This study evaluates the impacts of climate and forest changes on streamflow in the upper parts of the Oldman River in Southern Alberta using a conceptual hydrological model, HBV-EC (Hydrologiska Byråns attenbalansavdelning, Environment Canada), in combination with a stochastic weather generator (LARS-WG) driven by GCM (global climate model) output climate data. Three climate change scenarios (A1B, A2 and B1) are selected to cover the range of possible future climate conditions (2020s, 2050s, and 2080s). The GCM projected less than a 10% increase in precipitation in winter and a similar amount of precipitation decrease in summer. These changes in projected precipitation resulted in up to a 200% (9.3 mm) increase in winter streamflow in February and up to a 63% (31.2 mm) decrease in summer flow in June. Flow also decreased in July and August, when irrigation is important; these reduced river flows during this season could impact agriculture production. The amplification in the streamflow is mostly driven by the projected increase in temperature that is predicted to melt winter snow earlier, resulting in lower water availability during the summer. Uncertainty analysis was completed using a guided GLUE (generalized likelihood uncertainty estimation) approach to obtain the best 100 parameter sets and associated ranges of streamflows. The impacts of uncertainty in streamflows were higher in spring and summer than in winter and fall. Forest change compounded the climate change impact by increasing the winter flow; however, it did not reduce the summer flow.


2013 ◽  
Vol 10 (7) ◽  
pp. 8503-8536 ◽  
Author(s):  
V. Mahat ◽  
A. Anderson

Abstract. Rivers in Southern Alberta are vulnerable to climate change because much of the river water originates as snow in the eastern slopes of the Rocky Mountains. Changes in likelihood of forest disturbance (wildfire, insects, logging, etc.) may also have impacts that are compounded by climate change. This study evaluates the impacts of climate and forest changes on streamflow in the upper parts of the Oldman River in Southern Alberta using a conceptual hydrological model, HBV-EC in combination with a stochastic weather generator (LARS-WG) driven by GCM (Global Climate Model) output climate data. Three climate change scenarios (A1B, A2 and B1) are selected to cover the range of possible future climate conditions (2020s, 2050s, and 2080s). GCM projected less than a 10% increase in precipitation in winter and a similar amount of precipitation decrease in summer. These changes in projected precipitation resulted in up to a 200% (9.3 mm) increase in winter streamflow in February and up to a 63% (31.2 mm) decrease in summer flow in June. This amplification is mostly driven by the projected increase in temperature that is predicted to melt winter snow earlier, possibly resulting in lower water availability in the snowmelt dominated regions during the summer. Uncertainty analysis was completed using a guided GLUE (generalized likelihood uncertainty estimation) approach to obtain the best 100 parameter sets and associated ranges of streamflows. The impacts of uncertainty were higher in spring and summer flows than in winter and fall flows. Forest change compounded the climate change impact by increasing winter flow; however, it did not reduce the summer flow.


2018 ◽  
Vol 15 ◽  
pp. 217-230
Author(s):  
María Pilar Amblar-Francés ◽  
María Asunción Pastor-Saavedra ◽  
María Jesús Casado-Calle ◽  
Petra Ramos-Calzado ◽  
Ernesto Rodríguez-Camino

Abstract. Over the past decades, the successive Coupled Model Intercomparison Projects (CMIPs) have produced a huge amount of global climate model simulations. Along these years, the climate models have advanced and can thus provide credible evolution of climate at least at continental or global scales since they are better representing physical processes and feedbacks in the climate system. Nevertheless, due to the coarse horizontal resolution of global climate models, it is necessary to downscale these results for their use to assess possible future impacts of climate change in climate sensitive ecosystems and sectors and to adopt adaptation strategies at local and national level. In this vein, the Spanish State Meteorological Agency (AEMET) has been producing since 2006 a set of reference downscaled climate change projections over Spain either applying statistical downscaling techniques to the outputs of the Global Climate Models (GCMs) or making use of the information generated by dynamical downscaling techniques through European projects or international initiatives such as PRUDENCE, ENSEMBLES and EURO-CORDEX. The AEMET strategy aims at exploiting all the available sources of information on climate change projections. The generalized use of statistical and dynamical downscaling approaches allow us to encompass a great number of global models and therefore to provide a better estimation of uncertainty. Most impact climate change studies over Spain make use of this reference downscaled projections emphasizing the estimation of uncertainties. Additionally to the rationale and history behind the AEMET generation of climate change scenarios, we focus on some preliminary analysis of the dependency of estimated uncertainties on the different sources of data.


2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.


2019 ◽  
Vol 11 (4) ◽  
pp. 1370-1382 ◽  
Author(s):  
Asma Hanif ◽  
Ashwin Dhanasekar ◽  
Anthony Keene ◽  
Huishu Li ◽  
Kenneth Carlson

Abstract Projected climate change impacts on the hydrological regime and corresponding flood risks were examined for the years 2030 (near-term) and 2050 (long-term), under representative concentration pathways (RCP) 4.5 (moderate) and 8.5 (high) emission scenarios. The United States Army Corps of Engineers' (USACE) Hydrologic Engineering Center's Hydrologic Modeling System was used to simulate the complete hydrologic processes of the various dendritic watershed systems and USACEs' Hydrologic Engineering Center's River Analysis System hydraulic model was used for the two-dimensional unsteady flow flood calculations. Climate projections are based on recent global climate model simulations developed for the International Panel on Climate Change, Coupled Model Inter-comparison Project Phase 5. Hydrographs for frequent (high-recurrence interval) storms were derived from 30-year historical daily precipitation data and decadal projections for both time frames and RCP scenarios. Since the climate projections for each scenario only represented ten years of data, 100-year or 500-year storms cannot be derived. Hence, this novel approach of identifying frequent storms is used as an indicator to compare across the various time frames and climate scenarios. Hydrographs were used to generate inundation maps and results are used to identify vulnerabilities and formulate adaptation strategies to flooding at 43 locations worldwide.


2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.


2016 ◽  
Vol 16 (7) ◽  
pp. 1617-1622 ◽  
Author(s):  
Fred Fokko Hattermann ◽  
Shaochun Huang ◽  
Olaf Burghoff ◽  
Peter Hoffmann ◽  
Zbigniew W. Kundzewicz

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.


Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.


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