34 research outputs found

    The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: Evaluation of precipitation

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    Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∌ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∌ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∌ −40% at 12 km to ∌ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.Fil: Ban, Nikolina. Universidad de Innsbruck; AustriaFil: Caillaud, CĂ©cile. UniversitĂ© de Toulouse; FranciaFil: Coppola, Erika. The Abdus Salam. International Centre for Theoretical Physics; Italia. The Abdus Salam; ItaliaFil: Pichelli, Emanuela. The Abdus Salam; Italia. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Sobolowski, Stefan. Norwegian Research Centre; NoruegaFil: Adinolfi, Marianna. Fondazione Centro Euro-Mediterraneo sui cambiamenti climatici; ItaliaFil: Ahrens, Bodo. Goethe Universitat Frankfurt; AlemaniaFil: Alias, Antoinette. UniversitĂ© de Toulouse; FranciaFil: Anders, Ivonne. German Climate Computing Center; AlemaniaFil: Bastin, Sophie. Universite Paris-Saclay;Fil: BeluĆĄić, Danijel. Swedish Meteorological and Hydrological Institute; SuizaFil: Berthou, SĂ©golĂšne. Met Office Hadley Centre; Reino UnidoFil: Brisson, Erwan. UniversitĂ© de Toulouse; FranciaFil: Cardoso, Rita M.. Universidade Nova de Lisboa; PortugalFil: Chan, Steven C.. University of Newcastle; Reino UnidoFil: Christensen, Ole BĂžssing. Danish Meteorological Institute; DinamarcaFil: FernĂĄndez, JesĂșs. Universidad de Cantabria; EspañaFil: Fita Borrell, LluĂ­s. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la AtmĂłsfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la AtmĂłsfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Frisius, Thomas. Helmholtz Gemeinschaft; AlemaniaFil: Gaparac, Goran. Croatia Control Ltd.; CroaciaFil: Giorgi, Filippo. The Abdus Salam. International Centre for Theoretical Physics; Italia. The Abdus Salam; ItaliaFil: Goergen, Klaus. Centre for High-Performance Scientific Computing in Terrestrial Systems; Alemania. Helmholtz Gemeinschaft. Forschungszentrum JĂŒlich; AlemaniaFil: Haugen, Jan Erik. Norwegian Meteorological Institute; NoruegaFil: Hodnebrog, Øivind. Center for International Climate and Environmental Research-Oslo; NoruegaFil: Kartsios, Stergios. Aristotle University Of Thessaloniki; GreciaFil: Katragkou, Eleni. Aristotle University Of Thessaloniki; GreciaFil: Kendon, Elizabeth J.. Met Office Hadley Centre; Reino UnidoFil: Keuler, Klaus. Brandenburg University of Technology Cottbus-Senftenberg; AlemaniaFil: Lavin Gullon, Alvaro. Universidad de Cantabria; EspañaFil: Lenderink, Geert. Royal Netherlands Meteorological Institute; PaĂ­ses Bajo

    The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas

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    peer reviewedAbstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of Regional Climate Model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)

    Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

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    International audienceOwing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynam-ical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981-2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanaly-ses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs

    Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections with respect to control run

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    International audienceAbstract. In this study, we use run-time bias correction to correct for the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) atmospheric model systematic errors on large-scale atmospheric circulation. The bias-correction terms are built using the climatological mean of the adjustment terms on tendency errors in an ARPEGE simulation relaxed towards ERA-Interim reanalyses. The bias reduction with respect to the Atmospheric Model Intercomparison Project (AMIP)-style uncorrected control run for the general atmospheric circulation in the Southern Hemisphere is significant for mean state and daily variability. Comparisons for the Antarctic Ice Sheet with the polar-oriented regional atmospheric models MAR and RACMO2 and in situ observations also suggest substantial bias reduction for near-surface temperature and precipitation in coastal areas. Applying the method to climate projections for the late 21st century (2071–2100) leads to large differences in the projected changes of the atmospheric circulation in the southern high latitudes and of the Antarctic surface climate. The projected poleward shift and strengthening of the southern westerly winds are greatly reduced. These changes result in a significant 0.7 to 0.9 K additional warming and a 6 % to 9 % additional increase in precipitation over the grounded ice sheet. The sensitivity of precipitation increase to temperature increase (+7.7 % K−1 and +9 % K−1) found is also higher than previous estimates. The highest additional warming rates are found over East Antarctica in summer. In winter, there is a dipole of weaker warming and weaker precipitation increase over West Antarctica, contrasted by a stronger warming and a concomitant stronger precipitation increase from Victoria to AdĂ©lie Land, associated with a weaker intensification of the Amundsen Sea Low

    Mediterranean Extreme Precipitation: Amplification by Warmer Sea Surface Temperatures in a Kilometer-Scale Regional Model

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    International audienceWe employ convection-permitting regional climate modeling to analyze the intense Mediterranean Heavy Precipitation Event (HPE) in October 2020 in the southeastern French Alps and northwestern Italian Alps regions, post passage of extra-tropical storm Alex. Exploring the event's sensitivity to warmer sea surface temperatures (SSTs), we conduct modeling experiments for September-October 2020 in western Europe. An ensemble-based approach is adopted to comprehensively assess local uncertainties purely driven by internal variability. Using the CNRM-AROME model, we accurately reproduce the HPE and precursor storm Alex characteristics, including the observed sequence of extreme events and related regional to local impacts. Sensitivity experiments are then conducted with idealized and uniform 2K warming and cooling patterns added to the SSTs over the entire domain and the Mediterranean Sea solely, all other forcings kept identical and representative of the 2020 observed conditions. SST warming intensifies the HPE's extremeness and accumulated precipitation amounts over the Alps. This is accompanied by a shift of the most intense precipitation eastward. In contrast, the strengthening of storm Alex with SST warming has limited impact on the Mediterranean HPE. Our findings underscore the crucial role of Mediterranean warming, enhancing moisture and instability upstream, and fostering deep atmospheric convection over the mountainous coastal region. A plausible worst-case scenario testing warmer SSTs in 2022 on HPE and storm Alex suggests milder precipitation-related impacts in the French Alpes-Maritimes region but increased damage in Italy

    Mediterranean Extreme Precipitation: Amplification by Warmer Sea Surface Temperatures in a Kilometer-Scale Regional Model

    No full text
    International audienceWe employ convection-permitting regional climate modeling to analyze the intense Mediterranean Heavy Precipitation Event (HPE) in October 2020 in the southeastern French Alps and northwestern Italian Alps regions, post passage of extra-tropical storm Alex. Exploring the event's sensitivity to warmer sea surface temperatures (SSTs), we conduct modeling experiments for September-October 2020 in western Europe. An ensemble-based approach is adopted to comprehensively assess local uncertainties purely driven by internal variability. Using the CNRM-AROME model, we accurately reproduce the HPE and precursor storm Alex characteristics, including the observed sequence of extreme events and related regional to local impacts. Sensitivity experiments are then conducted with idealized and uniform 2K warming and cooling patterns added to the SSTs over the entire domain and the Mediterranean Sea solely, all other forcings kept identical and representative of the 2020 observed conditions. SST warming intensifies the HPE's extremeness and accumulated precipitation amounts over the Alps. This is accompanied by a shift of the most intense precipitation eastward. In contrast, the strengthening of storm Alex with SST warming has limited impact on the Mediterranean HPE. Our findings underscore the crucial role of Mediterranean warming, enhancing moisture and instability upstream, and fostering deep atmospheric convection over the mountainous coastal region. A plausible worst-case scenario testing warmer SSTs in 2022 on HPE and storm Alex suggests milder precipitation-related impacts in the French Alpes-Maritimes region but increased damage in Italy
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