The European CORDEX (EURO-CORDEX) initiative is a large voluntary effort that seeks to advance regional climate and Earth system science in Europe. As part of the World Climate Research Programme (WCRP)-Coordinated Regional Downscaling Experiment (CORDEX), it shares the broader goals of providing a model evaluation and climate projection framework and improving communication with both the General Circulation Model (GCM) and climate data user communities. EURO-CORDEX oversees the design and coordination of ongoing ensembles of regional climate projections of unprecedented size and resolution (0.11 • EUR-11 and 0.44 • EUR-44 domains). Additionally, the inclusion of empiricalstatistical downscaling allows investigation of much larger multi-model ensembles. These complementary approaches provide a foundation for scientific studies within the climate research community and others. The value of the EURO-CORDEX ensemble is shown via numerous peer-reviewed studies and its use in the development of climate services. Evaluations of the EUR-44 and EUR-11 ensembles also show the benefits of higher resolution. However, significant challenges remain. To further advance scientific understanding, two flagship pilot studies (FPS) were initiated. The first investigates local-regional phenomena at convection-permitting scales over central Europe and the Mediterranean in collaboration with the Med-CORDEX community. The second investigates the impacts of land cover changes on European climate across spatial and temporal scales. Over the coming years, the EURO-CORDEX community looks forward to closer collaboration with other communities, new advances, supporting international initiatives such as the IPCC reports, and continuing to provide the basis for research on regional climate impacts and adaptation in Europe.
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.
Two Regional Climate Model (RCM) projections of changes in extreme precipitation over Europe are assessed and compared. This provides insight into the importance of RCM formulation in representing changes in climate extremes at high spatial resolution. The models concerned are two recent Hadley Centre RCMs, HadRM2 and HadRM3, and are applied at a horizontal resolution of approximately 50 km over Europe, nested within the Hadley Centre coupled Atmosphere Ocean General Circulation Model (AOGCM), HadCM2. The simulation periods are thirty years with fixed concentrations of greenhouse gases representing the climate of 1961-1990 and twenty years representing transient climate change for 2080-2100. The use of common boundary conditions to drive the two RCMs allows us to determine whether their different formulations significantly alter the downscaled projections.The RCM simulations of precipitation extremes are compared with observations from a dense rain-gauge network over Great Britain, aggregated to the grid used by the RCMs. Both RCMs simulate realistically extreme precipitation occurring over timescales of one to thirty days and for return periods of two to twenty years. In particular, relative errors in the magnitude of extreme precipitation are generally no larger than those in the mean. The two regional models show different patterns of errors for daily precipitation extremes, with the main difference in the western and upland areas of Great Britain where they are underestimated in HadRM2 and overestimated in HadRM3. Change in extremes over all land areas in the domain show increases in intensity everywhere (except for the Iberian peninsula and Mediterranean coast) with most of these significant at the 5% level. Projected increases are greatest for those extremes which are the rarest and shortest duration (i.e. the most intense), both in relative and thus absolute terms. The large-scale patterns of these changes are very similar in the two RCMs implying they are generally robust to the RCM formulation changes. Given the demonstrated quality of the models this enhances our confidence in the projected changes and suggests that they are mainly conditioned by the large-scale response in the driving GCM. Crown
Reliable projections of future changes in local precipitation extremes are essential for informing policy decisions regarding mitigation and adaptation to climate change. In this paper, the extent to which the natural variability of the climate affects one's ability to project the anthropogenically forced component of change in daily precipitation extremes across Europe is examined. A three-member ensemble of the Hadley Centre Regional Climate Model (HadRM3H) is used and a statistical framework is applied to estimate the uncertainty due to the full spectrum of climate variability. In particular, the results and understanding presented here suggest that annual to multidecadal natural variability may contribute significant uncertainty. For this ensemble projection, extreme precipitation changes at the grid-box level are found to be discernible above climate noise over much of northern and central Europe in winter, and parts of northern and southern Europe in summer. The ability to quantify the change to a reasonable level of accuracy is largely limited to regions in northern Europe. In general, where climate noise has a significant component varying on decadal time scales, single 30-yr climate change projections are insufficient to infer changes in the extreme tail of the underlying precipitation distribution. In this context, the need for ensembles of integrations is demonstrated and the relative effectiveness of spatial pooling and averaging for generating robust signals of extreme precipitation change is also explored. The key conclusions are expected to apply more generally to other models and forcing scenarios.
The use of regional climate model (RCM)‐based projections for providing regional climate information in a research and climate service contexts is currently expanding very fast. This has been possible thanks to a considerable effort in developing comprehensive ensembles of RCM projections, especially for Europe, in the EURO‐CORDEX community (Jacob et al., 2014, 2020). As of end of 2019, EURO‐CORDEX has developed a set of 55 historical and scenario projections (RCP8.5) using 8 driving global climate models (GCMs) and 11 RCMs. This article presents the ensemble including its design. We target the analysis to better characterize the quality of the RCMs by providing an evaluation of these RCM simulations over a number of classical climate variables and extreme and impact‐oriented indices for the period 1981–2010. For the main variables, the model simulations generally agree with observations and reanalyses. However, several systematic biases are found as well, with shared responsibilities among RCMs and GCMs: Simulations are overall too cold, too wet, and too windy compared to available observations or reanalyses. Some simulations show strong systematic biases on temperature, others on precipitation or dynamical variables, but none of the models/simulations can be defined as the best or the worst on all criteria. The article aims at supporting a proper use of these simulations within a climate services context.
International audienceMedicanes are cyclones over the Mediterranean Sea having a tropical-like structure but a rather small size, that can produce significant damage due to the combination of intense winds and heavy precipitation. Future climate projections, performed generally with individual atmospheric climate models, indicate that the intensity of the medicanes could increase under climate change conditions. The availability of large ensembles of high resolution and ocean–atmosphere coupled regional climate model (RCM) simulations, performed in MedCORDEX and EURO-CORDEX projects, represents an opportunity to improve the assessment of the impact of climate change on medicanes. As a first step towards such an improved assessment, we analyze the ability of the RCMs used in these projects to reproduce the observed characteristics of medicanes, and the impact of increased resolution and air-sea coupling on their simulation. In these storms, air-sea interaction plays a fundamental role in their formation and intensification, a different mechanism from that of extra-tropical cyclones, where the baroclinic instability mechanism prevails. An observational database, based on satellite images combined with high resolution simulations (Miglietta et al. in Geophys Res Lett 40:2400–2405, 2013), is used as a reference for evaluating the simulations. In general, the simulated medicanes do not coincide on a case-by-case basis with the observed medicanes. However, observed medicanes with a high intensity and relatively long duration of tropical characteristics are better replicated in simulations. The observed spatial distribution of medicanes is generally well simulated, while the monthly distribution reveals the difficulty of simulating the medicanes that first appear in September after the summer minimum in occurrence. Increasing the horizontal resolution has a systematic and generally positive impact on the frequency of simulated medicanes, while the general underestimation of their intensity is not corrected in most cases. The capacity of a few models to better simulate the medicane intensity suggests that the model formulation is more important than reducing the grid spacing alone. A negative intensity feedback is frequently the result of air-sea interaction for tropical cyclones in other basins. The introduction of air-sea coupling in the present simulations has an overall limited impact on medicane frequency and intensity, but it produces an interesting seasonal shift of the simulated medicanes from autumn to winter. This fact, together with the analysis of two contrasting particular cases, indicates that the negative feedback could be limited or even absent in certain situations. We suggest that the effects of air-sea interaction on medicanes may depend on the oceanic mixed layer depth, thus increasing the applicability of ocean–atmosphere coupled RCMs for climate change analysis of this kind of cyclones
The Philippines is one of the most exposed countries in the world to tropical cyclones. In order to provide information to help the country build resilience and plan for a future under a warmer climate, we build on previous research to investigate implications of future climate change on tropical cyclone activity in the Philippines. Experiments were conducted using three regional climate models with horizontal resolutions of approximately 12 km (HadGEM3‐RA) and 25 km (HadRM3P and RegCM4). The simulations are driven by boundary data from a subset of global climate model simulations from the CMIP5 ensemble. Here we present the experimental design, the methodology for selecting CMIP5 models, the results of the model validation, and future projections of changes to tropical cyclone frequency and intensity by the mid‐21st century. The models used are shown to represent the key climatological features of tropical cyclones across the domain, including the seasonality and general distribution of intensities, but issues remain in resolving very intense tropical cyclones and simulating realistic trajectories across their life‐cycles. Acknowledging model inadequacies and uncertainties associated with future climate model projections, the results show a range of plausible changes with a tendency for fewer but slightly more intense tropical cyclones. These results are consistent with the basin‐wide results reported in the IPCC AR5 and provide clear evidence that the findings from these previous studies are applicable in the Philippines region.
Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.