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This work evaluates the daily precipitation and mean temperature of eight CORDEX‐EUR11 ERA‐Interim‐driven simulations of EURO‐CORDEX over the Iberian Peninsula (IP) for the period 1989–2008. To this aim, three observational data sets (Iberia01, E‐OBS‐v19e, and MESAN‐0.11) were considered as reference and compared with the models by means of several indices reflecting the mean and extreme regimes over the IP. For precipitation the Lamb weather types were considered to identify synoptic conditions related with higher observational uncertainty. RCMs are able to reproduce the spatial pattern and the variability observed in the IP. However, there is a higher agreement between models and observations for mean temperature than for precipitation, decreasing when extremes are analyzed. For the observational uncertainty analysis, also extreme daily temperatures were considered to obtain a wider picture of this topic. A higher dependence on the observational data set has been found for precipitation than for temperature. This uncertainty is particularly significant when the 50‐year return value is considered for which the observational uncertainty doubles the model uncertainty. Only the wet‐day frequency presents values lower than 0.5 for all seasons, with most of the rest of values reflecting a similar contribution of both components to the uncertainty. In the case of temperatures, the main contribution of the observations has been found when the lower (MAE01) and upper (MAE99) extremes are considered, with values lower than 0.5. For precipitation the observational uncertainty increases when synoptic patterns affecting the Mediterranean Basin are considered, reflecting the difficulty to properly capture the Mediterranean precipitation regimes. Key Points: EURO‐CORDEX verication over Iberian PeninsulaObservational uncertainty analysis of the evaluation of the EURO‐CORDEX RCMsSynoptic patterns and observational uncertainty of precipitation regimes [ABSTRACT FROM AUTHOR]

The application of climate change impact assessment (CCIA) studies in general and especially the linkages between different actor groups typically involved is often not trivial and subject to many limitations and uncertainties. Disciplinary issues like competing downscaling approaches, imperfect climate and impact model data and uncertainty propagation as well as the selection of appropriate data sets are only one part of the story. Interdisciplinary and transdisciplinary challenges add to these, as climate data and impact model data provision and their usage require at least a minimum of common work and shared understanding among actors. Here, we provide the VALUE perspective on current disciplinary challenges and limitations at the downscaling interface and elaborate transdisciplinary issues that hamper a proper working downscaling interface. The perspective is partly based on a survey on user needs of downscaled data that was distributed among 62 participants across Europe involving 22 sectors. Partly, it is based on the exchanges and experiences gained during the lifetime of VALUE that brought together different actor groups of different disciplines: climate modellers, impact modellers, statisticians and stakeholders. We outline a sketch that summarizes the linkages between the main identified actor groups: climate model data providers, impact modellers and societal users. We summarize review and structure current actors groups, needs and issues. We argue that this structuring enables involved actors to tackle these issues in a more organized and hence effective way. A key solution to several difficulties at the downscaling interface is to our understanding the development of guidelines based on benchmark tests like the VALUE framework. In addition, fostering communication between actor groups—and financing this communication—is essential to obtain the best possible CCIA as a prerequisite for robust adaptation. [ABSTRACT FROM AUTHOR]

In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell-Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max -2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40-60 %) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (-2.8 °C); this location suggests that land-atmosphere rather than cloud-radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain-Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement. [ABSTRACT FROM AUTHOR]

In the current work we present six hindcast Weather Research and Forecasting (WRF) simulations for the EURO-CORDEX domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic biases in both temperature and precipitation linked to different physical mechanisms for the summer and winter season. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly when using Grell-Devenyi convection and the CAM radiation scheme, intensifies the negative summer temperature bias in northern Europe (max -2.5 °C). Conversely, a strong positive downward shortwave summer bias in central (40-60 %) and southern Europe mitigates the systematic cold bias in WRF over these regions, signifying a typical case of error compensation. Maximum winter cold bias is over north-eastern Europe (-2.8 °C); this location is indicative of land-atmosphere rather than cloud-radiation interactions. Precipitation is systematically overestimated in summer by all model configurations, especially the higher quantiles, which are associated with summertime deep cumulus convection. The Kain-Fritsch convection scheme produces the larger summertime precipitation biases over the Mediterranean. Winter precipitation is reproduced with lower biases by all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature-precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest methodologies for model improvement. [ABSTRACT FROM AUTHOR]

ABSTRACT In this study precipitation from a high resolution WRF climate simulation is presented and evaluated against daily gridded observations in the Iberian Peninsula. The simulation corresponds to a dynamical downscaling of ERA-Interim, in the period 1989-2009, performed with two nested grids, at 27 and 9 km horizontal resolution. The higher resolution simulation indicates a significantly improved representation of Iberian precipitation fields, at all timescales, with emphasis on the representation of variability and of extreme weather statistics. Results compare well with recent studies with other models and/or for other regions, further supporting the use of WRF as a regional climate model. [ABSTRACT FROM AUTHOR]

Soil moisture is one of the most important variables of the climate system as it constrains evapotranspiration, affecting the surface energy and water balance. It is of particular importance over transition regions between humid and dry climates as lower evapotranspiration rates lead to higher surface air temperatures thought strong soil moisture‐temperature coupling. A new and more extensive evaluation of the surface energy balance, for the Africa Coordinated Regional Downscaling Experiment, is performed for hindcast simulations, where different Regional Climate Models are driven by ERA‐Interim reanalysis (1990–2008). A new validation is carried out, with Regional Climate Models displaying a good agreement with observations. However, large biases are found over the Sahel and southern Africa for precipitation. All models tend to underestimate maximum temperature, whereas minimum temperature is overestimated for large regions. A multimodel mean ensemble is found to outperform individual models in almost all situations, representing the best estimate of present climate. The seasonal coupling strength as determined by a correlation between latent and sensible heat fluxes indicates Sahel and western Africa as strong coupling for boreal and austral summer, respectively. Also, the strong coupling areas match the transition regions identified by the intermediate values of the evaporative fraction, varying in the spatial extent. Additionally, a new soil moisture‐temperature coupling metric is introduced, which highlights the regions where higher temperatures are influenced by evaporative stress. Therefore, this metric relates extreme daily maximum temperature with latent heat flux and is computed for monthly time scales, incorporating information from the recent past. Key Points: Models are able to capture the main climate patterns within Africa, with some deviations for specific regionsAfrica's transition regions between humid and dry environments are identified as strong soil moisture‐temperature couplingA new soil moisture-temperature coupling metric is introduced allowing the detection of extreme phenomena [ABSTRACT FROM AUTHOR]