Search Results (7)

The temperature-based indicators heating and cooling degree days, are frequently utilized to quantitatively link indoor energy demand and outdoor thermal conditions, especially in the context of climate change. We present a comprehensive study of the heating and cooling degree-days and the degree-days categories for the near past (1976–2005), and the AR5 RCP4.5 and RCP8.5 scenario-driven future (2066–2095) over Southeast Europe based on an elaborated methodology and performed using a 19 combinations of driving global and regional climate models from EURO-CORDEX with horizontal resolution of 0.11°. Alongside the explicit focus of the degree-days categories and the finer grid resolution, the study benefits substantially from the consideration of the monthly, rather than annual, time scale, which allows the assessment of the intra-annual variations of all analyzed parameters. We provide evidences that the EURO-CORDEX ensemble is capable of simulating the spatiotemporal patterns of the degree-days and degree-day categories for the near past period. Generally, we demonstrate also a steady growth in cooling and a decrease in heating degree-days, where the change of the former is larger in relative terms. Additionally, we show an overall shift toward warmer degree-day categories as well as prolongation of the cooling season and shortening of the heating season. As a whole, the magnitude of the projected long-term changes is significantly stronger for the ’pessimistic’ scenario RCP8.5 than the ’realistic’ scenario RCP4.5. These outcomes are consistent with the well-documented general temperature trend in the gradually warming climate of Southeast Europe. The patterns of the projected long-term changes, however, exhibit essential heterogeneity, both in time and space, as well as among the analyzed parameters. This finding is manifested, in particular, in the coexistence of opposite tendencies for some degree-day categories over neighboring parts of the domain and non-negligible month-to-month variations. Most importantly, the present study unequivocally affirms the significance of the anticipated long-term changes of the considered parameters over Southeast Europe in the RCP scenario-driven future with all subsequent and far-reaching effects on the heating, cooling, and ventilation industry. Full article

Climate change increasingly is affecting every aspect of human life on the earth. Many regional climate models (RCMs) have so far been developed to carefully assess this important phenomenon on specific regions. In this study, ten RCMs captured from the European Coordinated Downscaling Experiment (EURO CORDEX) platform are evaluated on the river Chiese catchment located in the northeast of Italy. The models’ ensembles are assessed in terms of the uncertainty and error calculated through different statistical and error indices. The uncertainties are investigated in terms of signal (increase, decrease, or neutral changes in the variables) and value uncertainties. Together with the spatial analysis of the data over the catchment, the weighted averaged values are used for the models’ evaluations and data projections. Using weighted catchment variables, climate change impacts are assessed on 10 different hydro-climatological variables showing the changes in the temperature, precipitation, rainfall events’ features, and the hydrological variables of the Chiese catchment between historical (1991–2000) and future (2071–2080) decades under RCP (Representative Concentration Path for increasing greenhouse gas emissions) scenario 4.5. The results show that, even though the multi-model ensemble mean (MMEM) could cover the outputs’ uncertainty of the models, it increases the error of the outputs. On the other hand, the RCM with the least error could cause high signal and value uncertainties for the results. Hence, different multi-model subsets of ensembles (MMEM-s) of 10 RCMs are obtained through a proposed algorithm for different impact models’ calculations and projections, making tradeoffs between two important shortcomings of model outputs, which are error and uncertainty. The single model (SM) and multi-model (MM) outputs imply that catchment warming is obvious in all cases and, therefore, evapotranspiration will be intensified in the future where there are about 1.28% and 6% value uncertainties for monthly temperature increase and the decadal relative balance of evapotranspiration, respectively. While rainfall events feature higher intensity and shorter duration in the SM, there are no significant differences for the mentioned features in the MM, showing high signal uncertainties in this regard. The unchanged catchment rainfall events’ depth can be observed in two SM and MM approaches, implying good signal certainty for the depth feature trend; there is still high uncertainty about the depth values. As a result of climate change, the percolation component change is negligible, with low signal and value uncertainties, while decadal evapotranspiration and discharge uncertainties show the same signal and value. While extreme events and their anomalous outcomes direct the uncertainties in rainfall events’ features’ values towards zero, they remain critical for yearly maximum catchment discharge in 2071–2080 as the highest value uncertainty is observed for this variable. Full article

Future drought-hazard assessments using standardized indices depend on the period used to calibrate the probability distributions. This appears to be particularly important in a changing climate with significant trends in drought-related variables. This study explores the effect of using different approaches to project droughts, with a focus on changes in drought characteristics (frequency, duration, time spent in drought, and spatial extent), estimated with a calibration period covering recent past and future conditions (self-calibrated indices), and another one that only applies recent-past records (relative indices). The analysis focused on the Iberian Peninsula (IP), a hot-spot region where climate projections indicate significant changes by the end of this century. To do this, a EURO-CORDEX multi-model ensemble under RCP8.5 was used to calculate the Standardized Precipitation-Evapotranspiration Index (SPEI) at both 3- and 12-month timescales. The results suggest that projections of drought characteristics strongly depend on the period used to calibrate the SPEI, particularly at a 12-month timescale. Overall, differences were larger for the near future when relative indices indicated more severe droughts. For the distant future, changes were more similar, although self-calibrated indices revealed more frequent and longer-lasting droughts and the relative ones a drought worsening associated with extremely prolonged drought events. Full article

In previous projects that focused on dynamical downscaling over Europe, e.g., PRUDENCE and ENSEMBLES, many regional climate models (RCMs) tended to overestimate summer air temperature and underestimate precipitation in this season in Southern and Southeastern Europe, leading to the so-called summer drying problem. This bias pattern occurred not only in the RCM results but also in the global climate model (GCM) results, so knowledge of the model uncertainties and their cascade is crucial for understanding and interpreting future climate. Our intention with this study was to examine whether a warm-and-dry bias is also present in the state-of-the-art EURO-CORDEX multi-model ensemble results in the summer season over the Pannonian Basin. Verification of EURO-CORDEX RCMs was carried out by using the E-OBS gridded dataset of daily mean, minimum, and maximum near-surface air temperature and total precipitation amount with a horizontal resolution of 0.1 degrees (approximately 12 km × 12 km) over the 1971–2000 time period. The model skill for selected period was expressed in terms of four verification scores: bias, centered root mean square error (RMSE), spatial correlation coefficient, and standard deviation. The main findings led us to conclude that most of the RCMs that overestimate temperature also underestimate precipitation. For some models, the positive temperature and negative precipitation bias were more emphasized, which led us to conclude that the problem was still present in most of the analyzed simulations. Full article

To support the development of national adaptation policies and measures addressing climate change impacts over Italy, this work aims to analyze projected changes in mean temperatures and precipitations, and extreme events such as droughts and floods, highlighting some local trends in the different Italian regions that have been little considered to date. The investigations are made on the basis of a set of high-resolution Euro-CORDEX models (horizontal resolution 0.11°, about 12 km) to infer quantitative assessments about the danger of climate changes under three different Representative Concentration Pathways (RCPs): business as usual scenario, i.e., without a reduction in green-house gas emissions (RCP 8.5), medium stabilization scenario (RCP 4.5) and mitigation scenario (RCP 2.6). After filtering the models with limited performances in reconstructing the current climate, the multi-model climate change scenarios were characterized by comparing the ensemble mean values computed for the base-line period (1971–2000) with those elaborated for the short- (2021–2050), medium- (2041–2070) and long-term (2071–2100). Two WMO ETCCDI indices were considered to investigate climate extremes: Consecutive Dry Days and extreme precipitations. Despite some uncertainties (related to discrepancies among the models), drought conditions and extreme precipitations will likely exacerbate in the coming decades without mitigation (RCP 8.5). Such conditions will be less critical if partial mitigation actions will be undertaken (RCP 4.5) and are expected to be significantly reduced with decarbonization policies (RCP 2.6). Full article

Climate change will impact urban areas. Decision makers need useful climate information to adapt adequately. This research aims to improve understanding of changes in moisture and temperature projected under climate change in Berlin compared to its surroundings. Simulations for the Representative Concentration Pathway (RCP) 8.5 scenario from the European Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) 0.11° are analyzed, showing a difference in moisture and temperature variables between Berlin and its surroundings. The running mean over 30 years shows a divergence throughout the twenty-first century for relative humidity between Berlin and its surroundings. Under this scenario, Berlin gets drier over time. The Mann-Kendall test quantifies a robust decreasing trend in relative humidity for the multi-model ensemble throughout the twenty-first century. The Mann-Whitney-Wilcoxon test for relative humidity indicates a robust climate change signal in Berlin. It is drier and warmer in Berlin compared to its surroundings for all months with the largest difference existing in summer. Additionally, the change in humidity for the period 2070–2099 compared to 1971–2000 is larger in the summer months. This study presents results to better understand near surface moisture change and related variables under long-term climate change in urban areas compared to their rural surroundings using a regional climate multi-model ensemble. Full article

There is considerable concern that the water resources of Central and Eastern Europe region can be adversely affected by climate change. Projections of future water balance and streamflow conditions can be obtained by forcing hydrological models with the output from climate models. In this study, we employed the SWAT hydrological model driven with an ensemble of nine bias-corrected EURO-CORDEX climate simulations to generate future hydrological projections for the Vistula and Odra basins in two future horizons (2024–2050 and 2074–2100) under two Representative Concentration Pathways (RCPs). The data set consists of three parts: (1) model inputs; (2) raw model outputs; (3) aggregated model outputs. The first one allows the users to reproduce the outputs or to create the new ones. The second one contains the simulated time series of 10 variables simulated by SWAT: precipitation, snow melt, potential evapotranspiration, actual evapotranspiration, soil water content, percolation, surface runoff, baseflow, water yield and streamflow. The third one consists of the multi-model ensemble statistics of the relative changes in mean seasonal and annual variables developed in a GIS format. The data set should be of interest of climate impact scientists, water managers and water-sector policy makers. In any case, it should be noted that projections included in this data set are associated with high uncertainties explained in this data descriptor paper. Full article