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Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days—90pWET, contribution of the very wet days to total precipitation—R95pTOT and number of consecutive dry days—CDD). As reference for model evaluation high resolution gridded observational data over continental Spain (Spain011/044) and the Alpine region (EURO4M-APGD) are used. The assessment and comparison of the two resolutions is accomplished not only on their original horizontal grids (approximately 12 and 50 km), but the high-resolution RCMs are additionally regridded onto the coarse 50 km grid by grid cell aggregation for the direct comparison with the low resolution simulations. The direct application of RCMs e.g. in many impact modelling studies is hampered by model biases. Therefore bias correction (BC) techniques are needed at both resolutions to ensure a better agreement between models and observations. In this work, the added value of the high resolution (before and after the bias correction) is assessed and the suitability of these BC methods is also discussed. Three basic BC methods are applied to isolate the effect of biases in mean precipitation, wet-day intensity and wet-day frequency on the derived indicators. Daily precipitation percentiles are strongly affected by biases in the wet-day intensity, whereas the dry spells are better represented when the simulated precipitation frequency is adjusted to the observed one. This confirms that there is no single optimal way to correct for RCM biases, since correcting some distributional features typically leads to an improvement of some aspects but to a deterioration of others. Regarding mean seasonal biases before the BC, we find only limited evidence for an added value of the higher resolution in the precipitation intensity and frequency or in the derived indicators. Thereby, evaluation results considerably depend on the RCM, season and indicator considered. High resolution simulations better reproduce the indicators’ spatial patterns, especially in terms of spatial correlation. However, this improvement is not statistically significant after applying specific BC methods.
Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits?
(2016)
In the framework of the EURO-CORDEX initiative an ensemble of European-wide high-resolution regional climate simulations on a 0.11∘(∼12.5km) 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∘(∼50km) 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.
Interactions between the land surface and the atmosphere play a fundamental role in the weather and climate system. Here we present a comparison of summertime land-atmosphere coupling strength found in a subset of the ERA-Interim-driven European domain Coordinated Regional Climate Downscaling Experiment
(EURO-CORDEX) model ensemble (1989 – 2008). Most of the regional climate models (RCMs) reproduce the overall soil moisture interannual variability, spatial patterns, and annual cycles of surface exchange fluxes for the different European climate zones suggested by the observational Global Land Evaporation Amsterdam Model (GLEAM) and FLUXNET data sets. However, some RCMs differ substantially from FLUXNET observations for some regions. The coupling strength is quantified by the correlation between the surface sensible and the latent heat flux, and by the correlation between the latent heat flux and 2 m temperature. The first
correlation is compared to its estimate from the few available long-term European high-quality FLUXNET
observations, and the latter to results from gridded GLEAM data. The RCM simulations agree with both
observational datasets in the large-scale pattern characterized by strong coupling in southern Europe and weak
coupling in northern Europe. However, in the transition zone from strong to weak coupling covering large parts of central Europe many of the RCMs tend to overestimate the coupling strength in comparison to both FLUXNET and GLEAM. The RCM ensemble spread is caused primarily by the different land surface models applied, and by the model-specific weather conditions resulting from different atmospheric parameterizations
A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. The first set of simulations with a horizontal resolution of 12.5 km was completed for the new emission scenarios RCP4.5 and RCP8.5 with more simulations expected to follow. The aim of this paper is to present this data set to the different communities active in regional climate modelling, impact assessment and adaptation. The EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The large-scale patterns of changes in mean temperature and precipitation are similar in all three scenarios, but they differ in regional details, which can partly be related to the higher resolution in EURO-CORDEX. The results strengthen those obtained in ENSEMBLES, but need further investigations. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities.
Erratum to: EURO-CORDEX: new high-resolution climate change projections for European impact research
(2014)
We used the regional climate model CCLM 4 to reconstruct the climate over the CADSES regions for the period 1961-2000. This most recent model version is currently still in a test phase. The simulation quality for this part of the entire simulation area is exemplarily analyzed by using a small but representative subset of model variables. Mean sea level pressure is chosen as an indicator for the behavior of the near-surface dynamics. Furthermore, the two regional variables 2 m temperature and precipitation are evaluated, which are of relevance for hydrological applications. For additional analyses to identify sources of uncertainty, we used soil moisture and cloudiness. Altogether, the accuracy of the simulation results can be judged as being in good agreement with the results of similar simulations by other regional climate models over Europe. Area-averaged monthly mean 2 m temperatures during winter show a cold bias of about -2 K. The simulated mean sea level pressure is with a bias of about 2 hPa slightly too high compared to the used reference data set. Although cloud cover evaluation hints at insufficiencies in the corresponding parameterization, further analyses are required to unambiguously identify the causes for this cold bias. During summer, higher 2 m temperatures linked to reduced precipitation are identified in nearly identical regions over southern and southeastern Europe. Further analyses of soil moisture evolution and cloud cover give evidence for a source of uncertainty in the surface hydrological scheme. Altogether, the detected differences do not exceed the typical ranges of uncertainty in comparable regional climate simulations over Europe. For input in hydrological applications, however, the uncertainties produced by the CCLM simulation described here have to be reduced in the medium term.