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A recently launched project under the auspices of the World Climate Research Program’s (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both “weather-like” (WL, initialized just before the event in question) and “climate” (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes.

In the framework of the EURO-CORDEX initiative an ensemble of European-wide high-resolution regional climate simulations on a 0 . 11 ∘ ( ∼ 12.5 km ) grid has been generated. This study investigates whether the fine-gridded regional climate models are found to add value to the simulated mean and extreme daily and sub-daily precipitation compared to their coarser-gridded 0 . 44 ∘ ( ∼ 50 km ) counterparts. Therefore, pairs of fine- and coarse-gridded simulations of eight reanalysis-driven models are compared to fine-gridded observations in the Alps, Germany, Sweden, Norway, France, the Carpathians, and Spain. A clear result is that the 0 . 11 ∘ simulations are found to better reproduce mean and extreme precipitation for almost all regions and seasons, even on the scale of the coarser-gridded simulations (50 km). This is primarily caused by the improved representation of orography in the 0 . 11 ∘ simulations and therefore largest improvements can be found in regions with substantial orographic features. Improvements in reproducing precipitation in the summer season appear also due to the fact that in the fine-gridded simulations the larger scales of convection are captured by the resolved-scale dynamics . The 0 . 11 ∘ simulations reduce biases in large areas of the investigated regions, have an improved representation of spatial precipitation patterns, and precipitation distributions are improved for daily and in particular for 3 hourly precipitation sums in Switzerland. When the evaluation is conducted on the fine (12.5 km) grid, the added value of the 0 . 11 ∘ models becomes even more obvious.

In this study the added value of a ensemble of convection permitting climate simulations (CPCSs) compared to coarser gridded simulations is investigated. The ensemble consists of three non hydrostatic regional climate models providing five simulations with ~10 and ~3 km (CPCS) horizontal grid spacing each. The simulated temperature, precipitation, relative humidity, and global radiation fields are evaluated within two seasons (JJA 2007 and DJF 2007–2008) in the eastern part of the European Alps. Spatial variability, diurnal cycles, temporal correlations, and distributions with focus on extreme events are analyzed and specific methods (FSS and SAL) are used for in-depth analysis of precipitation fields. The most important added value of CPCSs are found in the diurnal cycle improved timing of summer convective precipitation, the intensity of most extreme precipitation, and the size and shape of precipitation objects. These improvements are not caused by the higher resolved orography but by the explicit treatment of deep convection and the more realistic model dynamics. In contrary improvements in summer temperature fields can be fully attributed to the higher resolved orography. Generally, added value of CPCSs is predominantly found in summer, in complex terrain, on small spatial and temporal scales, and for high precipitation intensities.

This study investigates the role of physical parameterization in regional climate model simulations. The authors also present a comprehensive assessment of errors arising from use of physical parameterization schemes, and their consequent impact on model performance in a region of complex topography. An error range related to the choice of physical parameterization is provided for 2-m air temperatureT 2mand precipitation. Two state-of-the-art nonhydrostatic mesoscale regional climate models, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) model, are used to dynamically downscale the 40-yr ECMWF Re-Analysis (ERA-40) to a spatial resolution of 10 km × 10 km in the European alpine region. SimulatedT 2mand precipitation are compared with gridded observational datasets. The model performance on regional and subregional scales is evaluated on daily, monthly, seasonal, and annual time scales. The results are based on a mixed physics ensemble of twenty-nine 1-yr-long hindcast simulations generated by choosing different model configurations. These results indicate that performance of both models is sensitive to the choice of physical parameterization and WRF is more sensitive than MM5. This sensitivity is higher during summer than during winter. The cumulus and microphysics scheme have the dominant effect on model performance during summer while boundary layer and radiation schemes affect the results during all seasons. It is found that annual mean error in the alpine region forT 2mand precipitation lies between −2.75° and −1.08°C (−1.12° and 1.33°C) and 0.27 and 0.80 mm day−1(0.13 and 1.51 mm day−1) for MM5 (WRF), respectively. The authors also found that the error range during winter for subregional scales is higher than the regional-scale error range, while during the other seasons the subregional error ranges are higher only in case of precipitation but not forT 2m. These results suggest that significant reductions of errors can be achieved by choosing a suitable model configuration for the region of interest. The other outcome of these experiments is a suitable setup, which can be used to conduct further long-term high-resolution climate simulations.

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study \"Convective Phenomena over Europe and the Mediterranean\" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results.

The advancement of computational resources has allowed researchers to run convection-permitting regional climate model (CPRCM) simulations. A pioneering effort promoting a multimodel ensemble of such simulations is the CORDEX Flagship Pilot Studies (FPS) on “Convective Phenomena over Europe and the Mediterranean” over an extended Alps region. In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast simulations for the daily mean near-surface wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as the reference. The use of a normalized metric allows for spatial comparison among the different regions (coast and inland), altitudes and seasons. This approach permits a direct assessment of the added value between the CPRCM simulations against their global driving reanalysis (ERA-Interim) and respective coarser resolution regional model counterparts. In general, the results show that CPRCMs add value to their global driving reanalysis or forcing regional model, due to better-resolved topography or through better representation of ocean-land contrasts. However, the nature and magnitude of the improvement in the wind speed representation vary depending on the model, the season, the altitude, or the region. Among seasons, the improvement is usually larger in summer than winter. CPRCMs generally display gains at low and medium-range altitudes. In addition, despite some shortcomings in comparison to ERA-Interim, which can be attributed to the assimilation of wind observations on the coast, the CPRCMs outperform the coarser regional climate models, both along the coast and inland.

Mountain forests provide a multitude of services beyond timber production. In a large European project (ARANGE—Advanced multifunctional forest management in European mountain RANGEs), the impacts of climate change and forest management on ecosystem services (ES) were assessed. Here, we provide background information about the concept that was underlying the ARANGE project, and its main objectives, research questions, and methodological approaches are presented. The project focused on synergies and trade-offs among four key ES that are relevant in European mountain ranges: timber production, carbon storage, biodiversity conservation, and protection from gravitational natural hazards. We introduce the concept and selection of case study areas (CSAs) that were used in the project; we describe the concept of representative stand types thatwere developed to provide a harmonized representation of forest stands and forest management in the CSAs; we explain and discuss the climate data and climate change scenarios that were applied across the seven CSAs; and we introduce the linker functions that were developed to relate stand- and landscape-scale forest features from model simulations to ES provisioning in mountain forests. Finally, we provide a brief overview of the Special Feature, with an attempt to synthesize emerging response patterns across the CSAs.

Small-scale floods are a consequence of high precipitation rates in small areas that can occur along frontal activity and convective storms. This situation is expected to become more severe due to a warming climate, when single precipitation events resulting from deep convection become more intense (super Clausius–Clapeyron effect). Regional climate model (RCM) evaluations and inter-comparisons have shown that there is evidence that an increase in RCM resolution and, in particular, at the convection-permitting scale will lead to a better representation of the spatial and temporal characteristics of heavy precipitation at small and medium scales. In this paper, the benefits of grid size reduction and bias correction in climate models are evaluated in their ability to properly represent flood generation in small- and medium-sized catchments. The climate models are sequentially coupled with a distributed hydrological model. The study area is the Eastern Alps, where small-scale storms often occur along with heterogeneous rainfall distributions leading to a very local flash flood generation. The work is carried out in a small multi-model framework using two different RCMs (CCLM and WRF) in different grid sizes. Bias correction is performed by the use of the novel scaled distribution mapping (SDM), which is similar to the usual quantile mapping (QM) method. The results show that, in the investigated RCM ensemble, no clear added value of the usage of convection-permitting RCMs for the purpose of flood modelling can be found. This is based on the fact that flood events are the consequence of an interplay between the total precipitation amount per event and the temporal distribution of rainfall intensities on a sub-daily scale. The RCM ensemble is lacking in one and/or the other. In the small catchment (<100 km2), a favourable superposition of the errors leads to seemingly good CCLM 3 km results both for flood statistics and seasonal occurrence. This is, however, not systematic across the catchments. The applied bias correction only corrects total event rainfall amounts in an attempt to reduce systematic errors on a seasonal basis. It does not account for errors in the temporal dynamics and deteriorates the results in the small catchment. Therefore, it cannot be recommended for flood modelling.

The quality of regional climate model (RCM) simulations is strongly dependent on the quality of data provided as lateral boundary conditions (LBCs). Frequently, the quality of near-surface variables of general circulation model (GCM) simulations like those from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is analyzed in the region of interest. However, such analysis does not necessarily lead to the selection of high-quality LBCs, as demonstrated in this study. The study region is the European domain of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX), where a model performance index (MPI) is used to evaluate the skill of CMIP5 GCMs to reproduce near-surface variables within the EURO-CORDEX domain and free atmosphere variables along its lateral boundaries as a proxy for LBCs used in regional climate modeling. The results suggest that a GCM’s skill in simulating near-surface variables is correlated with 0.62 (Spearman’sr) to its skill in simulating LBCs for regional climate simulations. However, there is hardly any correlation between the performances of different variables, implying that a GCM evaluation solely based on surface parameters or a few variables is inadequate to select suitable driving data for regional climate models. The selection should include the evaluation of all variables passed to the RCM as LBCs in the lateral boundary zone (LBZ) on at least one midtropospheric level.