Future climate of Brussels and Paris for the 2050s under the A1B scenario

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Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEXv5

Dynamical downscaling in a continuous approach using initial and boundary conditions from a reanalysis or a global climate model is a common method for simulating the regional climate. The simulation potential can be improved by applying an alternative approach of reinitialising the atmosphere, combined with either a daily reinitialised or a continuous land surface. We evaluated the dependence of the simulation potential on the running mode of the regional climate model ALARO coupled to the land surface model Meteo-France SURFace EXternalisee (SUR-FEX), and driven by the ERA-Interim reanalysis. Three types of downscaling simulations were carried out for a 10-year period from 1991 to 2000, over a western European domain at 20 km horizontal resolution: (1) a continuous simulation of both the atmosphere and the land surface, (2) a simulation with daily reinitialisations for both the atmosphere and the land surface and (3) a simulation with daily reinitialisations of the atmosphere while the land surface is kept continuous. The results showed that the daily reinitialisation of the atmosphere improved the simulation of the 2m temperature for all seasons. It revealed a neutral impact on the daily precipitation totals during winter, but the results were improved for the summer when the land surface was kept continuous. The behaviour of the three model configurations varied among different climatic regimes. Their seasonal cycle for the 2m temperature and daily precipitation totals was very similar for a Mediterranean climate, but more variable for temperate and continental climate regimes. Commonly, the summer climate is characterised by strong interactions between the atmosphere and the land surface. The results for summer demonstrated that the use of a daily reinitialised atmosphere improved the representation of the partitioning of the surface energy fluxes. Therefore, we recommend using the alternative approach of the daily reinitialisation of the atmosphere for the simulation of the regional climate

Modeling the scaling of short‐duration precipitation extremes with temperature

The Clausius-Clapeyron (CC) relation expresses the exponential increase in the moisture-holding capacity of air of approximately 7%/degrees C. Earlier studies show that extreme hourly precipitation increases with daily mean temperature, consistent with the CC relation. Recent studies at specific locations found that for temperatures higher than around 12 degrees C, hourly precipitation extremes scale at rates higher than the CC scaling, a phenomenon that is often referred to as "super-CC scaling." These scalings are typically estimated by collecting rainfall data in temperature bins, followed by a linear fit or a visual inspection of the precipitation quantiles in each bin. In this study, a piecewise linear quantile regression model is presented for a more flexible, and robust estimation of the scaling parameters, and their associated uncertainties. Moreover, we use associated information criteria to prove statistically whether or not a pronounced super-CC scaling exists. The techniques were tested on stochastically simulated data and, when applied to hourly station data across Western Europe and Scandinavia, revealed large uncertainties in the scaling rates. Finally, goodness-of-fit measures indicated that the dew point temperature is a better scaling predictor than temperature

Multiscale performance of the ALARO-0 model for simulating extreme summer precipitation climatology in Belgium

Daily summer precipitation over Belgium from the Aire Limitée Adaptation Dynamique Développement International (ALADIN) model and a version of the model that has been updated with physical parameterizations, the so-called ALARO-0 model [ALADIN and AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) combined model, first baseline version released in 1998], are compared with respect to station observations for the period 1961–90. The 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) is dynamically downscaled using both models on a horizontal resolution of 40 km, followed by a one-way nesting on high spatial resolutions of 10 and 4 km. This setup allows us to explore the relative importance of spatial resolution versus parameterization formulation on the model skill to correctly simulate extreme daily precipitation. Model performances are assessed through standard statistical errors and density, frequency, and quantile distributions as well as extreme value analysis, using the peak-over-threshold method and generalized Pareto distribution. The 40-km simulations of ALADIN and ALARO-0 show similar results, both reproducing the observations reasonably well. For the high-resolution simulations, ALARO-0 at both 10 and 4 km is in better agreement with the observations than ALADIN. The ALADIN model consistently produces too high precipitation rates. The findings demonstrate that the new parameterizations within the ALARO-0 model are responsible for a correct simulation of extreme summer precipitation at various horizontal resolutions. Moreover, this study shows that ALARO-0 is a good candidate model for regional climate modeling

Local impact analysis of climate change on precipitation extremes : are high-resolution climate models needed for realistic simulations?

This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3-4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensityduration-frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local subdaily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models

The responses of the ecosystems in the Tianshan North Slope under multiple representative concentration pathway scenarios in the middle of the 21st Century

The arid ecosystem is fragile and sensitive to the changes in climate and CO2 concentration. Exploring the responses of the arid ecosystem to the changes under different representative concentration pathways (RCPs) is of particular significance for the sustainable development of the ecosystem. In this study, the dynamics of net primary productivity (NPP), evapotranspiration (ET), and water use efficiency (WUE) for arid ecosystems in Tianshan North Slope are explored by running the arid ecosystem model at 25 km resolution under RCP2.6, RCP4.5, and RCP8.5. The climate in Tianshan North Slope presents a wet-warming trend during 2006-2055 under each RCP scenario with temporal and spatial heterogeneity. In response to the changes in climate and CO2, the regional annual NPP and ET increased during 2006-2055 by a respectively maximum rate of 2.15 g C m(-2) year(-1) and 0.52 mm year(-1) under RCP8.5. Both the NPP and ET share a similar temporal and spatial heterogeneity with climate change. Different vegetation types respond differently to the changes under different RCP scenarios with increasing WUE. Under each RCP, the non-phreatophyte, phreatophyte, and grass are more sensitive to the changes than in the others, and the broadleaf forest and cropland are less sensitive to the changes