Articles | Volume 5, issue 1
https://doi.org/10.5194/wcd-5-211-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-5-211-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of climate change on persistent cold-air pools in an alpine valley during the 21st century
Univ. Grenoble Alpes, CNRS, Grenoble INP, LEGI, 38000 Grenoble, France
Julien Beaumet
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Atmo Auvergne-Rhône-Alpes, 38400 Grenoble, France
Martin Ménégoz
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Hubert Gallée
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Enzo Le Bouëdec
Univ. Grenoble Alpes, CNRS, Grenoble INP, LEGI, 38000 Grenoble, France
Chantal Staquet
Univ. Grenoble Alpes, CNRS, Grenoble INP, LEGI, 38000 Grenoble, France
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
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Simon F. Reifenberg, Anna Martin, Matthias Kohl, Sara Bacer, Zaneta Hamryszczak, Ivan Tadic, Lenard Röder, Daniel J. Crowley, Horst Fischer, Katharina Kaiser, Johannes Schneider, Raphael Dörich, John N. Crowley, Laura Tomsche, Andreas Marsing, Christiane Voigt, Andreas Zahn, Christopher Pöhlker, Bruna A. Holanda, Ovid Krüger, Ulrich Pöschl, Mira Pöhlker, Patrick Jöckel, Marcel Dorf, Ulrich Schumann, Jonathan Williams, Birger Bohn, Joachim Curtius, Hardwig Harder, Hans Schlager, Jos Lelieveld, and Andrea Pozzer
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Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Sara Bacer, Fatima Jomaa, Julien Beaumet, Hubert Gallée, Enzo Le Bouëdec, Martin Ménégoz, and Chantal Staquet
Weather Clim. Dynam., 3, 377–389, https://doi.org/10.5194/wcd-3-377-2022, https://doi.org/10.5194/wcd-3-377-2022, 2022
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We study the impact of climate change on wintertime atmospheric blocking over Europe. We focus on the frequency, duration, and size of blocking events. The blocking events are identified via the weather type decomposition methodology. We find that blocking frequency, duration, and size are mostly stationary over the 21st century. Additionally, we compare the blocking size results with the size of the blocking events identified via a different approach using a blocking index.
Mickaël Lalande, Martin Ménégoz, Gerhard Krinner, Kathrin Naegeli, and Stefan Wunderle
Earth Syst. Dynam., 12, 1061–1098, https://doi.org/10.5194/esd-12-1061-2021, https://doi.org/10.5194/esd-12-1061-2021, 2021
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Climate change over High Mountain Asia is investigated with CMIP6 climate models. A general cold bias is found in this area, often related to a snow cover overestimation in the models. Ensemble experiments generally encompass the past observed trends, suggesting that even biased models can reproduce the trends. Depending on the future scenario, a warming from 1.9 to 6.5 °C, associated with a snow cover decrease and precipitation increase, is expected at the end of the 21st century.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
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Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Domenico Taraborrelli, David Cabrera-Perez, Sara Bacer, Sergey Gromov, Jos Lelieveld, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 21, 2615–2636, https://doi.org/10.5194/acp-21-2615-2021, https://doi.org/10.5194/acp-21-2615-2021, 2021
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Atmospheric pollutants from anthropogenic activities and biomass burning are usually regarded as ozone precursors. Monocyclic aromatics are no exception. Calculations with a comprehensive atmospheric model are consistent with this view but only for air masses close to pollution source regions. However, the same model predicts that aromatics, when transported to remote areas, may effectively destroy ozone. This loss of tropospheric ozone rivals the one attributed to bromine.
Marion Donat-Magnin, Nicolas C. Jourdain, Christoph Kittel, Cécile Agosta, Charles Amory, Hubert Gallée, Gerhard Krinner, and Mondher Chekki
The Cryosphere, 15, 571–593, https://doi.org/10.5194/tc-15-571-2021, https://doi.org/10.5194/tc-15-571-2021, 2021
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We simulate the West Antarctic climate in 2100 under increasing greenhouse gases. Future accumulation over the ice sheet increases, which reduces sea level changing rate. Surface ice-shelf melt rates increase until 2100. Some ice shelves experience a lot of liquid water at their surface, which indicates potential ice-shelf collapse. In contrast, no liquid water is found over other ice shelves due to huge amounts of snowfall that bury liquid water, favouring refreezing and ice-shelf stability.
Sara Bacer, Sylvia C. Sullivan, Odran Sourdeval, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Atmos. Chem. Phys., 21, 1485–1505, https://doi.org/10.5194/acp-21-1485-2021, https://doi.org/10.5194/acp-21-1485-2021, 2021
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We investigate the relative importance of the rates of both microphysical processes and unphysical correction terms that act as sources or sinks of ice crystals in cold clouds. By means of numerical simulations performed with a global chemistry–climate model, we assess the relevance of these rates at global and regional scales. This estimation is of fundamental importance to assign priority to the development of microphysics parameterizations and compare model output with observations.
Cited articles
Arduini, G., Chemel, C., and Staquet, C.: Local and non-local controls on a persistent cold-air pool in the Arve River Valley, Q. J. Roy. Meteorol. Soc., 146, 2497–2521, https://doi.org/10.1002/qj.3776, 2020. a, b
Bacer, S., Jomaa, F., Beaumet, J., Gallée, H., Le Bouëdec, E., Ménégoz, M., and Staquet, C.: Impact of climate change on wintertime European atmospheric blocking, Weather Clim. Dynam., 3, 377–389, https://doi.org/10.5194/wcd-3-377-2022, 2022. a, b
Beaumet, J., Ménégoz, M., Morin, S., Gallée, H., Fettweis, X., Six, D., Vincent, C., Wilhelm, B., and Anquetin, S.: Twentieth century temperature and snow cover changes in the French Alps, Reg. Environ. Change, 21, 1–13, https://doi.org/10.1007/s10113-021-01830-x, 2021. a, b
Beaumet, J., Ménégoz, M., and Gallée, H.: MAR-MPI-ESM1-2-HR SSP585 European Alps (2015–2100), Zenodo [data set], https://doi.org/10.5281/zenodo.5834376, 2022a. a
Beaumet, J., Ménégoz, M., and Gallée, H.: MAR-MPI-ESM1-2-HR HIST (1961–2014) and SSP245 European Alps (2015–2100), Zenodo [data set], https://doi.org/10.5281/zenodo.5834221, 2022b. a
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992. a
Cannon, A. J.: Reductions in daily continental-scale atmospheric circulation biases between generations of global climate models: CMIP5 to CMIP6, Environ. Res. Lett., 15, 064006, https://doi.org/10.1088/1748-9326/ab7e4f, 2020. a
Caserini, S., Giani, P., Cacciamani, C., Ozgen, S., and Lonati, G.: Influence of climate change on the frequency of daytime temperature inversions and stagnation events in the Po Valley: historical trend and future projections, Atmos. Res., 184, 15–23, https://doi.org/10.1016/j.atmosres.2016.09.018, 2017. a, b, c, d, e
Chemel, C., Arduini, G., Staquet, C., Largeron, Y., Legain, D., Tzanos, D., and Paci, A.: Valley heat deficit as a bulk measure of wintertime particulate air pollution in the Arve River Valley, Atmos. Environ., 128, 208–215, https://doi.org/10.1016/j.atmosenv.2015.12.058, 2016. a
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity, Mon. Weather Rev. 129, 569–585, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a
Connolly, A., Chow, F., and Hoch, S.: Nested Large-Eddy Simulations of the Displacement of a Cold-Air Pool by Lee Vortices, Bound.-Lay. Meteorol., 178, 91–118, https://doi.org/10.1007/s10546-020-00561-6, 2021. a
Crosman, E. T. and Horel, J. D.: Large-eddy simulations of a Salt Lake Valley cold-air pool, Atmosp. Res., 193, 10–25, https://doi.org/10.1016/j.atmosres.2017.04.010, 2017. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Fernandez-Granja, J., Casanueva, A., Bedia, J., and Fernandez, J.: Improved atmospheric circulation over Europe by the new generation of CMIP6 earth system models, Clim. Dynam., 56, 3527–3540, https://doi.org/10.1007/s00382-021-05652-9, 2021. a
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a
Gallée, H. and Schayes, G.: Development of a three-dimensional meso-gamma primitive equations model, katabatic winds simulation in the area of Terra Nova Bay, Antarctica, Mon. Weather Rev., 122, 671–685, 1994. a
Gallée, H., Pettré, P., and Schayes, G.: Sudden Cessation of Katabatic Winds in Adélie Land, Antarctica, J. Appl. Meteorol. Clim., 35, 1142–1152, https://doi.org/10.1175/1520-0450(1996)035<1142:SCOKWI>2.0.CO;2, 1996. a
Gallée, H., Peyaud, V., and Goodwin, I.: Simulation of the net snow accumulation along the Wilkes Land transect, Antarctica, with a regional climate model, Ann. Glaciol., 41, 17–22, https://doi.org/10.3189/172756405781813230, 2005. a
Hong, S.-Y., Noh, Y., and Dudhia, J.: A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/MWR3199.1, 2006. a
Hou, P. and Wu, S.: Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality, Sci. Rep., 6, 23792, https://doi.org/10.1038/srep23792, 2016. a
Iacobellis, S. F., Norris, J. R., Kanamitsu, M., Tyree, M., and Cayan, D. C.: Climate variability and California low-level temperature inversions, Publication no. CEC-500-2009-020-F, California Climate Change Center, http://www.energy.ca.gov/2009publications/CEC-500-2009-020/CEC-500-2009-020-F.PDF (last access: 16 May 2023), 2009. a
Ji, F., Evans, J., Di Luca, A., Jiang, N., Olson, R., Fita, L., Argüeso, D., Chang, L.-C., Scorgie, Y., and Riley, M.: Projected change in characteristics of near surface temperature inversions for southeast Australia, Clim. Dynam., 52, 1487–1503, https://doi.org/10.1007/s00382-018-4214-3, 2019. a, b
Jiménez, P. A., Dudhia, J., Gonzalez-Rouco, J. F., Navarro, J., Montavez, J. P., and Garcia-Bustamante, E.: A Revised Scheme for the WRF Surface Layer Formulation, Mon. Weather Rev., 140, 898–918, https://doi.org/10.1175/MWR-D-11-00056.1, 2012. a
Jungclaus, J., Bittner, M., Wieners, K.-H., Wachsmann, F., Schupfner, M., Legutke, S., Giorgetta, M., Reick, C., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Esch, M., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP historical, WCRP, https://doi.org/10.22033/ESGF/CMIP6.6594, 2019. a
Largeron, Y. and Staquet, C.: The atmospheric boundary layer during wintertime persistent inversions in the Grenoble valleys, Front. Earth Sci., 4, 70, https://doi.org/10.3389/feart.2016.00070, 2016b. a, b, c, d
Le Bouëdec, E.: Wintertime characteristic atmospheric circulation in the Grenoble basin and impact on air pollution, PhD thesis, Université Grenoble Alpes, Grenoble, https://theses.hal.science/tel-04148049 (last access: 1 April 2023), 2021. a
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S., Fläschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T., Jimenéz-de-la Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S., Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B., Müller, W. A., Nabel, J. E. M. S., Nam, C. C. W., Notz, D., Nyawira, S.-S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M., Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider, T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D., Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt, A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst., 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019. a
Ménégoz, M., Gallée, H., and Jacobi, H. W.: Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations, Hydrol. Earth Syst. Sci., 17, 3921–3936, https://doi.org/10.5194/hess-17-3921-2013, 2013. a
Ménégoz, M., Valla, E., Jourdain, N. C., Blanchet, J., Beaumet, J., Wilhelm, B., Gallée, H., Fettweis, X., Morin, S., and Anquetin, S.: Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010, Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, 2020. a
Michelangeli, P.-A., Vautard, R., and Legras, B.: Weather regimes: Recurrence and quasi stationarity, J. Atmos. Sci., 52, 1237–1256, 1995. a
Milionis, A. E. and Davies, T. D.: The effect of the prevailing weather on the statistics of atmospheric temperature inversions, Int. J. Climatol., 28, 1385–1397, https://doi.org/10.1002/joc.1613, 2008. a
Monteiro, D. and Morin, S.: Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets, The Cryosphere, 17, 3617–3660, https://doi.org/10.5194/tc-17-3617-2023, 2023. a
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M., Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., Ilyina, T., Kleine, T., Kornblueh, L., Li, H., Modali, K., Notz, D., Pohlmann, H., Roeckner, E., Stemmler, I., Tian, F., and Marotzke, J.: A Higher-resolution Version of the Max Planck Institute Earth System Model (MPI-ESM1.2-HR), J. Adv. Model. Earth Syst., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018. a
Neemann, E. M., Crosman, E. T., Horel, J. D., and Avey, L.: Simulations of a cold-air pool associated with elevated wintertime ozone in the Uintah Basin, Utah, Atmos. Chem. Phys., 15, 135–151, https://doi.org/10.5194/acp-15-135-2015, 2015. a
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016. a
Philipona, R.: Greenhouse warming and solar brightening in and around the Alps, Int. J. Climatol., 33, 1530–1537, https://doi.org/10.1002/joc.3531, 2013. a, b
Quimbayo-Duarte, J., Chemel, C., Staquet, C., Troude, F., and Arduini, G.: Drivers of severe air pollution events in a deep valley during wintertime: A case study from the Arve river valley, France, Atmos. Environ., 247, 118030, https://doi.org/10.1016/j.atmosenv.2020.118030, 2021. a, b
Rasilla, D. F., Martilli, A., Allende, F., and Fernández, F.: Long-term evolution of cold air pools over the Madrid basin, Int. J. Climatol., 43, 38–56, https://doi.org/10.1002/joc.7700, 2022. a, b, c
Reeves, H. D. and Stensrud, D. J.: Synoptic-scale flow and valley cold pool evolution in the Western United States, Weather Forecast., 24, 1625–1643, 2009. a
Sabatier, T., Largeron, Y., Paci, A., Lac, C., Rodier, Q., Canut, G., and Masson, V.: Semi-idealized simulations of wintertime flows and pollutant transport in an Alpine valley. Part II: Passive tracer tracking, Q. J. Roy. Meteorol. Soc., 146, 827–845, https://doi.org/10.1002/qj.3710, 2020. a
Schmidli, J., Böing, S., and Fuhrer, O.: Accuracy of Simulated Diurnal Valley Winds in the Swiss Alps: Influence of Grid Resolution, Topography Filtering, and Land Surface Datasets, Atmosphere, 9, 196, https://doi.org/10.3390/atmos9050196, 2018. a
Schupfner, M., Wieners, K.-H., Wachsmann, F., Steger, C., Bittner, M., Jungclaus, J., Früh, B., Pankatz, K., Giorgetta, M., Reick, C., Legutke, S., Esch, M., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: CMIP6 ScenarioMIP DKRZ MPI-ESM1-2-HR ssp245 – RCM-forcing data, WCD Climate, https://doi.org/10.26050/WDCC/RCM_CMIP6_SSP245-HR, 2020a. a
Schupfner, M., Wieners, K.-H., Wachsmann, F., Steger, C., Bittner, M., Jungclaus, J., Früh, B., Pankatz, K., Giorgetta, M., Reick, C., Legutke, S., Esch, M., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: CMIP6 ScenarioMIP DKRZ MPI-ESM1-2-HR ssp585_r1i1p1f1 – RCM-forcing data, WCD Climate, https://doi.org/10.26050/WDCC/RCM_CMIP6_SSP585-HR_r1i1p1f1, 2020b. a
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Liu, Z., Berner, J., Wang, W., Powers, J., Duda, M., Barker, D., and Huang, X.: A Description of the Advanced Research WRF Model Version 4, ncar technical notes – ncar/tn-556+str Edn., University Corporation for Atmospheric Research, NCAR, https://www2.mmm.ucar.edu/wrf/users/docs/technote/v4_technote.pdf (last access: 2 March 2023), 2019. a
Tomasi, E., Giovannini, L., Falocchi, M., Antonacci, G., Jiménez, P. A., Kosovic, B., Alessandrini, S., Zardi, D., Delle Monache, L., and Ferrero, E.: Turbulence parameterizations for dispersion in sub-kilometer horizontally non-homogeneous flows, Atmos. Res., 228, 122–136, https://doi.org/10.1016/j.atmosres.2019.05.018, 2019. a
Umek, L., Gohm, A., Haid, M., Ward, H. C., and Rotach, M. W.: Large-eddy simulation of foehn–cold pool interactions in the Inn Valley during PIANO IOP 2, Q. J. Roy. Meteorol. Soc., 147, 944–982, https://doi.org/10.1002/qj.3954, 2021. a
Whiteman, C. and Doran, J.: The Relationship between Overlying Synoptic-Scale Flows and Winds within a Valley, J. Appl. Meteorol., 32, 1669–1682, https://doi.org/10.1175/1520-0450(1993)032<1669:TRBOSS>2.0.CO;2, 1993. a
Whiteman, C. and McKee, T.: Breakup of Temperature Inversions in Deep Mountain Valleys: Part II. Thermodynamic Model, J. Appl. Meteorol., 21, 290–302, https://doi.org/10.1175/1520-0450(1982)021<0290:BOTIID>2.0.CO;2, 1982. a
Whiteman, C. D., Bian, X., and Zhong, S.: Wintertime Evolution of the Temperature Inversion in the Colorado Plateau Basin, J. Appl. Meteorol., 38, 1103–1117, https://doi.org/10.1175/1520-0450(1999)038<1103:WEOTTI>2.0.CO;2, 1999a. a
Yu, L., Zhong, S., and Bian, X.: Multi-day valley cold-air pools in the western United States as derived from NARR, Int. J. Climatol., 37, 2466–2476, https://doi.org/10.1002/joc.4858, 2017. a, b
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020. a
Short summary
A model chain is used to downscale outputs from a climate model to the Grenoble valley atmosphere over the 21st century in order to study the impact of climate change on persistent cold-air pool episodes. We find that the atmosphere in the Grenoble valleys during these episodes tends to be slightly less stable in the future under the SSP5–8.5 scenario, and statistically unchanged under the SSP2–4.5 scenario but that very stable persistent cold-air pool episodes can still form.
A model chain is used to downscale outputs from a climate model to the Grenoble valley...