12 research outputs found

    Climate Change and Weather Extremes in the Eastern Mediterranean and Middle East

    Get PDF
    Observation‐based and modeling studies have identified the Eastern Mediterranean and Middle East (EMME) region as a prominent climate change hotspot. While several initiatives have addressed the impacts of climate change in parts of the EMME, here we present an updated assessment, covering a wide range of timescales, phenomena and future pathways. Our assessment is based on a revised analysis of recent observations and projections and an extensive overview of the recent scientific literature on the causes and effects of regional climate change. Greenhouse gas emissions in the EMME are growing rapidly, surpassing those of the European Union, hence contributing significantly to climate change. Over the past half‐century and especially during recent decades, the EMME has warmed significantly faster than other inhabited regions. At the same time, changes in the hydrological cycle have become evident. The observed recent temperature increase of about 0.45°C per decade is projected to continue, although strong global greenhouse gas emission reductions could moderate this trend. In addition to projected changes in mean climate conditions, we call attention to extreme weather events with potentially disruptive societal impacts. These include the strongly increasing severity and duration of heatwaves, droughts and dust storms, as well as torrential rain events that can trigger flash floods. Our review is complemented by a discussion of atmospheric pollution and land‐use change in the region, including urbanization, desertification and forest fires. Finally, we identify sectors that may be critically affected and formulate adaptation and research recommendations toward greater resilience of the EMME region to climate change. The Eastern Mediterranean and Middle East is warming almost two times faster than the global average and other inhabited parts of the world Climate projections indicate a future warming, strongest in summers. Precipitation will likely decrease, particularly in the Mediterranean Virtually all socio‐economic sectors will be critically affected by the projected changes The Eastern Mediterranean and Middle East is warming almost two times faster than the global average and other inhabited parts of the world Climate projections indicate a future warming, strongest in summers. Precipitation will likely decrease, particularly in the Mediterranean Virtually all socio‐economic sectors will be critically affected by the projected change

    Climate Change and Weather Extremes in the Eastern Mediterranean and Middle East

    Get PDF
    Observation-based and modeling studies have identified the Eastern Mediterranean and Middle East (EMME) region as a prominent climate change hotspot. While several initiatives have addressed the impacts of climate change in parts of the EMME, here we present an updated assessment, covering a wide range of timescales, phenomena and future pathways. Our assessment is based on a revised analysis of recent observations and projections and an extensive overview of the recent scientific literature on the causes and effects of regional climate change. Greenhouse gas emissions in the EMME are growing rapidly, surpassing those of the European Union, hence contributing significantly to climate change. Over the past half-century and especially during recent decades, the EMME has warmed significantly faster than other inhabited regions. At the same time, changes in the hydrological cycle have become evident. The observed recent temperature increase of about 0.45 degrees C per decade is projected to continue, although strong global greenhouse gas emission reductions could moderate this trend. In addition to projected changes in mean climate conditions, we call attention to extreme weather events with potentially disruptive societal impacts. These include the strongly increasing severity and duration of heatwaves, droughts and dust storms, as well as torrential rain events that can trigger flash floods. Our review is complemented by a discussion of atmospheric pollution and land-use change in the region, including urbanization, desertification and forest fires. Finally, we identify sectors that may be critically affected and formulate adaptation and research recommendations toward greater resilience of the EMME region to climate change.Peer reviewe

    When will extreme heat events become part of the new climate normal?

    No full text
    As a result of global warming, extreme heat events have become more frequent and severe. This will likely continue or accelerate in the future, particularly under high radiative forcing scenarios. In the present study, based on an ensemble of global climate model simulations, we identify the absolute historical extremes expressed by several temperature indices. Considering projections under two future pathways (SSP1-2.6, SSP5-8.5), we investigate to what extent extreme heat events will become predominant during the rest of the century. The timing of a transition to prevailing hot weather extremes is critical for the development of mitigation and adaptation strategies, therefore, we also identify the projected first year of such a transition, as well as the persistence in subsequent decades. Different aspects of heat extremes are investigated, including both maximum and minimum temperature. For some climate zones, our results highlight that regardless of mitigation efforts, hot weather conditions will be at least similar but likely more extreme compared to historical events within the following decades. By the end of the century, under a business-as-usual pathway, successive years will be much more extreme than the most severe conditions in the recent past virtually everywhere

    TIN-Copula bias-correction method for model-derived maximum temperature in the MENA region

    No full text
    Global and regional climate models' prediction accuracy is limited, often with systematic biases between the model output and observed conditions. The present research aims to minimize the biases between the maximum temperature simulated by a global (HadGEM3) and a regional (WRF) climate model for the period of 2006–2014, based on the ERA5 reanalysis data, used as a proxy for observations (calibration period 1981–2000). For the bias correction, a new approach with the TIN-Copula method (combination of Triangular Irregular Networks-TINs and Copulas), suitable for gridded datasets is used. The methodology applies TINs to define the grids to which the corrections are made, and copulas for analysing the dependence between the reanalysis and simulated data during the calibration period. The dependence structure is then used for the bias adjustment. Our methodology is applied to the Middle East and North Africa MENA-CORDEX domain, where extreme heat conditions prevail, which are projected to accelerate during the 21st century. Besides to the entire area, a detailed analysis was performed for six subregions. Our results indicate that the maximum temperature output of both models diverges from the ERA5 reanalysis, especially during summer. In several subregions and seasons, discrepancies are highest for the HadGEM3 model, which has a much coarser resolution than WRF. The effectiveness of the TIN-Copula method was tested spatially, temporally and based on two relevant climate indices [daily maximum temperature (TXx) and warm spell duration index (WSDI]), showing that it minimizes model biases

    Bias Correction of RCM Precipitation by TIN-Copula Method: A Case Study for Historical and Future Simulations in Cyprus

    No full text
    Numerical models are being used for the simulation of recent climate conditions as well as future projections. Due to the complexity of the Earth’s climate system and processes occurring at sub-grid scales, model results often diverge from the observed values. Different methods have been developed to minimize such biases. In the present study, the recently introduced “triangular irregular networks (TIN)-Copula” method was used for the bias correction of modelled monthly total and extreme precipitation in Cyprus. The method was applied to a 15-year historical period and two future periods of the same duration. Precipitation time-series were derived from a 12-km resolution EURO-CORDEX regional climate simulation. The results show that the TIN-Copula method significantly reduces the positive biases between the model results and observations during the historical period of 1986–2000, for both total and extreme precipitation (>80%). However, the level of improvement differs temporally and spatially. For future periods, the model tends to project significantly higher total precipitation rates prior to bias correction, while for extremes the differences are smaller. The adjustments slightly affect the overall climate change signal, which tends to be enhanced after bias correction, especially for total precipitation and for the autumn period

    Minimizing the uncertainties of RCMs climate data by using spatio-temporal geostatistical modeling

    No full text
    The spatio-temporal Κriging approach by using five different covariance models, has been applied into Regional Climate Model (RCM) simulated precipitation and temperature dataset in a coastal area. The results of the spatio-temporal technique were evaluated against the ERA-Interim reanalysis data during the period from 1981 to 2000. The reliability of the spatio-temporal interpolation results were estimated by using both the judgment of the wireframe plots, between the sample and the fitted covariance models, and the statistic metrics. Thus, Taylor diagrams were used and the Mean Square Error (MSE) was calculated. The analysis demonstrates that the sum-metric covariance model is highly superior to the other four covariance models as it is closer to the reanalysis data, having the highest correlation coefficient, as well as, the smallest standard deviation, resulting in the smallest Root Mean Square Error. The spatio-temporal interpolation approach improved the MPI and HadGEM2 climate model dataset. The largest enhancement is pointed out in the interpolated RCM precipitation during winter and autumn. Concerning the temperature, the interpolated MPI temperature data is negligibly improved, whereas the interpolated HadGEM2 temperature is particularly optimized during winter and autumn. The spatio-temporal interpolation technique led to the minimization of the uncertainties of the Regional Climate Models, (RCMs) simulations, and also to the best agreement between them and the ERA-Interim reanalysis data during the period from 1981 to 2000. Nevertheless, the MPI climate model is more reasonable compared to the HADGEM2 for the research area. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature

    Climate Change and Weather Extremes in the Eastern Mediterranean and Middle East

    No full text
    Observation‐based and modeling studies have identified the Eastern Mediterranean and Middle East (EMME) region as a prominent climate change hotspot. While several initiatives have addressed the impacts of climate change in parts of the EMME, here we present an updated assessment, covering a wide range of timescales, phenomena and future pathways. Our assessment is based on a revised analysis of recent observations and projections and an extensive overview of the recent scientific literature on the causes and effects of regional climate change. Greenhouse gas emissions in the EMME are growing rapidly, surpassing those of the European Union, hence contributing significantly to climate change. Over the past half‐century and especially during recent decades, the EMME has warmed significantly faster than other inhabited regions. At the same time, changes in the hydrological cycle have become evident. The observed recent temperature increase of about 0.45°C per decade is projected to continue, although strong global greenhouse gas emission reductions could moderate this trend. In addition to projected changes in mean climate conditions, we call attention to extreme weather events with potentially disruptive societal impacts. These include the strongly increasing severity and duration of heatwaves, droughts and dust storms, as well as torrential rain events that can trigger flash floods. Our review is complemented by a discussion of atmospheric pollution and land‐use change in the region, including urbanization, desertification and forest fires. Finally, we identify sectors that may be critically affected and formulate adaptation and research recommendations toward greater resilience of the EMME region to climate change.Key Points: The Eastern Mediterranean and Middle East is warming almost two times faster than the global average and other inhabited parts of the world. Climate projections indicate a future warming, strongest in summers. Precipitation will likely decrease, particularly in the Mediterranean. Virtually all socio‐economic sectors will be critically affected by the projected changes.European Union Horizon 2020https://esg-dn1.nsc.liu.se/search/esgf-liu

    A Semantic Approach to Constraint-Based Reasoning in Geographical Domains

    No full text
    Various models have been developed to manage geographic data but most of them integrate heterogeneous techniques to support knowledge representation and reasoning. This is far from optimal because it requires mapping data between different representation formats; moreover, as it fragments knowledge, it limits the possibility to use complete information about the problem to be solved for the execution of inferences. In order to address this issue, we adopt a unified approach, in which we use Semantic Web techniques to manage both knowledge representation and reasoning rules with particular attention to constraint verification that is central to several geographic reasoning tasks. Our model exploits an ontological description of spatial constraints which supports the specification of their properties, facilitating the automated selection of the relevant ones to be applied to a given problem. The model supports different types of inferences, such as checking the compliance of a given geographical area to a set of constraints, or suggesting a suitable aggregation of land patches that satisfy them. We test our model by applying it to the management of Ecological Networks, which describe the structure of existing real ecosystems and help planning their expansion, conservation and improvement by introducing constraints on land use
    corecore