Future Changes in Day-to-Day Precipitation Variability in Europe

Ondřej Lhotka aInstitute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic
bGlobal Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

Search for other papers by Ondřej Lhotka in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0001-5129-1272
,
Eva Plavcová aInstitute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic

Search for other papers by Eva Plavcová in
Current site
Google Scholar
PubMed
Close
, and
Romana Beranová aInstitute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic

Search for other papers by Romana Beranová in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

We analyzed regional patterns of day-to-day precipitation variability across Europe and assessed their future changes using Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate models. A discrete Markov chain process was employed to calculate transition probabilities from wet and dry states, and the precipitation variability was quantified using the proposed variability index (IVAR, the sum of wet-to-dry and dry-to-wet transitions divided by the total number of transitions). The IVAR is, in general, lowest in southern Europe and gradually increases northward in the observed data. Performance of the regional climate models is season dependent: They capture IVAR reasonably well in summer, but higher simulated variability was found for the winter season. The IVAR trends computed for the 2006–95 period suggest decreasing day-to-day precipitation variability over southern Europe, especially in summer under the high-concentration RCP8.5 pathway. By contrast, increased variability is projected in northern Europe. Between these two regions, future IVAR trends are less clear because they strongly depend on the selection of driving global model, hinting of an uncertain future hydroclimate in the central European region.

Significance Statement

In a warming world, water availability will play a key role in ecosystem productivity. Although future changes in rainfall amounts have been studied extensively, much less attention has been given to changes in their temporal distribution and variability. Because grouping wet or dry days into sequences vitally contributes to characterizing floods or droughts, we aimed to study future changes in these tendencies. We found that although future changes in wet or dry days grouping tendencies are mostly driven solely by change in their frequency, climate models do not agree on the change in the frequency of wet days over large parts of continental Europe. This leaves major uncertainties in a future European hydroclimate and implications for impact modeling.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ondřej Lhotka, ondrej.lhotka@ufa.cas.cz

Abstract

We analyzed regional patterns of day-to-day precipitation variability across Europe and assessed their future changes using Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate models. A discrete Markov chain process was employed to calculate transition probabilities from wet and dry states, and the precipitation variability was quantified using the proposed variability index (IVAR, the sum of wet-to-dry and dry-to-wet transitions divided by the total number of transitions). The IVAR is, in general, lowest in southern Europe and gradually increases northward in the observed data. Performance of the regional climate models is season dependent: They capture IVAR reasonably well in summer, but higher simulated variability was found for the winter season. The IVAR trends computed for the 2006–95 period suggest decreasing day-to-day precipitation variability over southern Europe, especially in summer under the high-concentration RCP8.5 pathway. By contrast, increased variability is projected in northern Europe. Between these two regions, future IVAR trends are less clear because they strongly depend on the selection of driving global model, hinting of an uncertain future hydroclimate in the central European region.

Significance Statement

In a warming world, water availability will play a key role in ecosystem productivity. Although future changes in rainfall amounts have been studied extensively, much less attention has been given to changes in their temporal distribution and variability. Because grouping wet or dry days into sequences vitally contributes to characterizing floods or droughts, we aimed to study future changes in these tendencies. We found that although future changes in wet or dry days grouping tendencies are mostly driven solely by change in their frequency, climate models do not agree on the change in the frequency of wet days over large parts of continental Europe. This leaves major uncertainties in a future European hydroclimate and implications for impact modeling.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ondřej Lhotka, ondrej.lhotka@ufa.cas.cz

Supplementary Materials

    • Supplemental Materials (PDF 2.7788 MB)
Save
  • Berkovic, S., and S. Raveh-Rubin, 2022: Persistent warm and dry extremes over the eastern Mediterranean during winter: The role of North Atlantic blocking and central Mediterranean cyclones. Quart. J. Roy. Meteor. Soc., 148, 23842409, https://doi.org/10.1002/qj.4308.

    • Search Google Scholar
    • Export Citation
  • Casanueva, A., and Coauthors, 2016: Daily precipitation statistics in a EURO-CORDEX RCM ensemble: Added value of raw and bias-corrected high-resolution simulations. Climate Dyn., 47, 719737, https://doi.org/10.1007/s00382-015-2865-x.

    • Search Google Scholar
    • Export Citation
  • Chen, D., A. Dai, and A. Hall, 2021: The convective-to-total precipitation ratio and the “drizzling” bias in climate models. J. Geophys. Res. Atmos., 126, e2020JD034198, https://doi.org/10.1029/2020JD034198.

    • Search Google Scholar
    • Export Citation
  • Chernokulsky, A., F. Kozlov, O. Zolina, O. Bulygina, I. I. Mokhov, and V. A. Semenov, 2019: Observed changes in convective and stratiform precipitation in northern Eurasia over the last five decades. Environ. Res. Lett., 14, 045001, https://doi.org/10.1088/1748-9326/aafb82.

    • Search Google Scholar
    • Export Citation
  • Clarke, B., F. Otto, R. Stuart-Smith, and L. Harrington, 2022: Extreme weather impacts of climate change: An attribution perspective. Environ. Res., 1, 012001, https://doi.org/10.1088/2752-5295/ac6e7d.

    • Search Google Scholar
    • Export Citation
  • Coppola, E., and Coauthors, 2021: Assessment of the European climate projections as simulated by the large EURO-CORDEX regional and global climate model ensemble. J. Geophys. Res. Atmos., 126, e2019JD032356, https://doi.org/10.1029/2019JD032356.

    • Search Google Scholar
    • Export Citation
  • Cornes, R. C., G. van der Schrier, E. J. M. van den Besselaar, and P. D. Jones, 2018: An ensemble version of the E-OBS temperature and precipitation data sets. J. Geophys. Res. Atmos., 123, 93919409, https://doi.org/10.1029/2017JD028200.

    • Search Google Scholar
    • Export Citation
  • Cornwall, W., 2021: Europe’s deadly floods leave scientists stunned. Science, 373, 372373, https://doi.org/10.1126/science.373.6553.372.

    • Search Google Scholar
    • Export Citation
  • Cos, J., F. Doblas-Reyes, M. Jury, R. Marcos, P.-A. Bretonnière, and M. Samsó, 2022: The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections. Earth Syst. Dyn., 13, 321340, https://doi.org/10.5194/esd-13-321-2022.

    • Search Google Scholar
    • Export Citation
  • Da Silva, N. A., and J. O. Haerter, 2023: The precipitation characteristics of mesoscale convective systems over Europe. J. Geophys. Res. Atmos., 128, e2023JD039045, https://doi.org/10.1029/2023JD039045.

    • Search Google Scholar
    • Export Citation
  • Déqué, M., S. Somot, E. Sanchez-Gomez, C. M. Goodess, D. Jacob, G. Lenderink, and O. B. Christensen, 2012: The spread amongst ENSEMBLES regional scenarios: Regional climate models, driving general circulation models and interannual variability. Climate Dyn., 38, 951964, https://doi.org/10.1007/s00382-011-1053-x.

    • Search Google Scholar
    • Export Citation
  • Di Sante, F., E. Coppola, and F. Giorgi, 2021: Projections of river floods in Europe using EURO-CORDEX, CMIP5 and CMIP6 simulations. Int. J. Climatol., 41, 32033221, https://doi.org/10.1002/joc.7014.

    • Search Google Scholar
    • Export Citation
  • ECA&D, 2022: E-OBS Gridded data set, version 24.0e. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 24 March 2022, https://doi.org/10.24381/cds.151d3ec6.

  • Fdez-Arroyabe Hernáez, P., and J. Martin-Vide, 2012: Regionalization of the probability of wet spells and rainfall persistence in the Basque Country (northern Spain). Int. J. Climatol., 32, 19091920, https://doi.org/10.1002/joc.2405.

    • Search Google Scholar
    • Export Citation
  • Gagniuc, P. A., 2017: Markov Chains: From Theory to Implementation and Experimentation. John Wiley and Sons, 256 pp.

  • Giorgi, F., C. Torma, E. Coppola, N. Ban, C. Schär, and S. Somot, 2016: Enhanced summer convective rainfall at Alpine high elevations in response to climate warming. Nat. Geosci., 9, 584589, https://doi.org/10.1038/ngeo2761.

    • Search Google Scholar
    • Export Citation
  • Guilbert, J., A. K. Betts, D. M. Rizzo, B. Beckage, and A. Bomblies, 2015: Characterization of increased persistence and intensity of precipitation in the northeastern United States. Geophys. Res. Lett., 42, 18881893, https://doi.org/10.1002/2015GL063124.

    • Search Google Scholar
    • Export Citation
  • Hajani, E., and G. Sarma, 2023: Generation of rainfall data series by using the Markov Chain model in three selected sites in the Kurdistan Region, Iraq. AI Civ. Eng., 2, 5, https://doi.org/10.1007/s43503-023-00014-2.

    • Search Google Scholar
    • Export Citation
  • Hatzaki, M., H. A. Flocas, I. Simmonds, J. Kouroutzoglou, K. Keay, and I. Rudeva, 2014: Seasonal aspects of an objective climatology of anticyclones affecting the Mediterranean. J. Climate, 27, 92729289, https://doi.org/10.1175/JCLI-D-14-00186.1.

    • Search Google Scholar
    • Export Citation
  • Huntingford, C., M. S. Williamson, and F. J. M. M. Nijsse, 2020: CMIP6 climate models imply high committed warming. Climatic Change, 162, 15151520, https://doi.org/10.1007/s10584-020-02849-5.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2023: Summary for policymakers. Climate Change 2023: Synthesis Report, H. Lee and J. Romero, Eds., IPCC, 1–34.

  • Jacob, D., and Coauthors, 2014: EURO-CORDEX: New high-resolution climate change projections for European impact research. Reg. Environ. Change, 14, 563578, https://doi.rog/10.1007/s10113-013-0499-2.

    • Search Google Scholar
    • Export Citation
  • Jacob, D., and Coauthors, 2020: Regional climate downscaling over Europe: Perspectives from the EURO-CORDEX community. Reg. Environ. Change, 20, 51, https://doi.org/10.1007/s10113-020-01606-9.

    • Search Google Scholar
    • Export Citation
  • Kjellström, E., L. Bärring, G. Nikulin, C. Nilsson, G. Persson, and G. Strandberg, 2016: Production and use of regional climate model projections – A Swedish perspective on building climate services. Climate Serv., 23, 1529, https://doi.org/10.1016/j.cliser.2016.06.004.

    • Search Google Scholar
    • Export Citation
  • Kotlarski, S., and Coauthors, 2014: Regional climate modeling on European scales: A joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci. Model Dev., 7, 12971333, https://doi.org/10.5194/gmd-7-1297-2014.

    • Search Google Scholar
    • Export Citation
  • Kottegoda, N. T., L. Natale, and E. Raiteri, 2004: Some considerations of periodicity and persistence in daily rainfalls. J. Hydrol., 296, 2337, https://doi.org/10.1016/j.jhydrol.2004.03.001.

    • Search Google Scholar
    • Export Citation
  • Kučerová, M., C. Beck, A. Philipp, and R. Huth, 2016: Trends in frequency and persistence of atmospheric circulation types over Europe derived from a multitude of classifications. Int. J. Climatol., 37, 25022521, https://doi.org/10.1002/joc.4861.

    • Search Google Scholar
    • Export Citation
  • Lee, J.-Y., and Coauthors, 2021: Future global climate: Scenario-based projections and near-term information. Climate Change 2021: The Physical Science Basis, V. Masson-Delmotte et al., Eds., Cambridge University Press, 553–672.

  • Lhotka, O., and J. Kyselý, 2022: The 2021 European heat wave in the context of past major heat waves. Earth Space Sci., 9, e2022EA002567, https://doi.org/10.1029/2022EA002567.

    • Search Google Scholar
    • Export Citation
  • Li, C., F. Zwiers, X. Zhang, G. Li, Y. Sun, and M. Wehner, 2021: Changes in annual extremes of daily temperature and precipitation in CMIP6 models. J. Climate, 34, 34413460, https://doi.org/10.1175/JCLI-D-19-1013.1.

    • Search Google Scholar
    • Export Citation
  • Lucas-Picher, P., D. Argüeso, E. Brisson, Y. Tramblay, P. Berg, A. Lemonsu, S. Kotlarski, and C. Caillaud, 2021: Convection-permitting modeling with regional climate models: Latest developments and next steps. Wiley Interdiscip. Rev.: Climate, 12, e731, https://doi.org/10.1002/wcc.731.

    • Search Google Scholar
    • Export Citation
  • McErlich, C., A. McDonald, A. Schuddeboom, G. Vishwanathan, J. Renwick, and S. Rana, 2023: Positive correlation between wet-day frequency and intensity linked to universal precipitation drivers. Nat. Geosci., 16, 410415, https://doi.org/10.1038/s41561-023-01177-4.

    • Search Google Scholar
    • Export Citation
  • Moghim, S., A. J. Teuling, and R. Uijlenhoet, 2022: A probabilistic climate change assessment for Europe. Int. J. Climatol., 42, 66996715, https://doi.org/10.1002/joc.7604.

    • Search Google Scholar
    • Export Citation
  • Moss, R. H., and Coauthors, 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747756, https://doi.org/10.1038/nature08823.

    • Search Google Scholar
    • Export Citation
  • Pendergrass, A. G., R. Knutti, F. Lehner, C. Deser, and B. M. Sanderson, 2017: Precipitation variability increases in a warmer climate. Sci. Rep., 7, 17966, https://doi.org/10.1038/s41598-017-17966-y.

    • Search Google Scholar
    • Export Citation
  • Rakovec, O., L. Samaniego, V. Hari, Y. Markonis, V. Moravec, S. Thober, M. Hanel, and R. Kumar, 2022: The 2018–2020 multi-year drought sets a new benchmark in Europe. Earth’s Future, 10, e2021EF002394, https://doi.org/10.1029/2021EF002394.

    • Search Google Scholar
    • Export Citation
  • Raymond, F., A. Ullmann, Y. Tramblay, P. Drobinski, and P. Camberlin, 2019: Evolution of Mediterranean extreme dry spells during the wet season under climate change. Reg. Environ. Change, 19, 23392351, https://doi.org/10.1007/s10113-019-01526-3.

    • Search Google Scholar
    • Export Citation
  • Riahi, K., and Coauthors, 2011: RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109, 3357, https://doi.org/10.1007/s10584-011-0149-y.

    • Search Google Scholar
    • Export Citation
  • Roudier, P., J. C. M. Andersson, C. Donnelly, L. Feyen, W. Greuell, and F. Ludwig, 2016: Projections of future floods and hydrological droughts in Europe under a +2°C global warming. Climatic Change, 135, 341355, https://doi.org/10.1007/s10584-015-1570-4.

    • Search Google Scholar
    • Export Citation
  • Rulfová, Z., R. Beranová, and J. Kyselý, 2017: Climate change scenarios of convective and large-scale precipitation in the Czech Republic based on EURO-CORDEX data. Int. J. Climatol., 37, 24512465, https://doi.org/10.1002/joc.4857.

    • Search Google Scholar
    • Export Citation
  • Smiatek, G., H. Kunstmann, and A. Senatore, 2016: EURO-CORDEX regional climate model analysis for the Greater Alpine region: Performance and expected future change. J. Geophys. Res. Atmos., 121, 77107728, https://doi.org/10.1002/2015JD024727.

    • Search Google Scholar
    • Export Citation
  • Soares, P. M. M., and R. M. Cardoso, 2018: A simple method to assess the added value using high-resolution climate distributions: Application to the EURO-CORDEX daily precipitation. Int. J. Climatol., 38, 14841498, https://doi.org/10.1002/joc.5261.

    • Search Google Scholar
    • Export Citation
  • Sørland, S. L., and Coauthors, 2021: COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: A review. Geosci. Model Dev., 14, 51255515, https://doi.org/10.5194/gmd-14-5125-2021.

    • Search Google Scholar
    • Export Citation
  • Stowasser, M., 2011: Modelling rain risk: A multi‐order Markov chain model approach. J. Risk Finance, 13, 4560, https://doi.org/10.1108/15265941211191930.

    • Search Google Scholar
    • Export Citation
  • Stryhal, J., and R. Huth, 2019: Classifications of winter atmospheric circulation patterns: Validation of CMIP5 GCMs over Europe and the North Atlantic. Climate Dyn., 52, 35753598, https://doi.org/10.1007/s00382-018-4344-7.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Search Google Scholar
    • Export Citation
  • Teichmann, C., and Coauthors, 2021: Assessing mean climate change signals in the global CORDEX-CORE ensemble. Climate Dyn., 57, 12691292, https://doi.org/10.1007/s00382-020-05494-x.

    • Search Google Scholar
    • Export Citation
  • Thomson, A. M., and Coauthors, 2011: RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109, 7794, https://doi.org/10.1007/s10584-011-0151-4.

    • Search Google Scholar
    • Export Citation
  • van Meijgaard, E., L. H. van Ulft, W. J. van de Berg, F. C. Bosveld, B. J. J. M. van den Hurk, G. Lenderink, and A. P. Siebesma, 2008: The KNMI regional atmospheric climate model RACMO, version 2.1. KNMI Tech. Rep. 302, 50 pp., https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR302.pdf.

  • Vautard, R., and Coauthors, 2013: The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project. Climate Dyn., 41, 25552575, https://doi.org/10.1007/s00382-013-1714-z.

    • Search Google Scholar
    • Export Citation
  • Vautard, R., and Coauthors, 2021: Evaluation of the large EURO-CORDEX regional climate model ensemble. J. Geophys. Res. Atmos., 126, e2019JD032344, https://doi.org/10.1029/2019JD032344.

    • Search Google Scholar
    • Export Citation
  • WCRP, 2022: Coordinated Regional Climate Downscaling Experiment (CORDEX). Earth System Grid Federation (ESGF) nodes, accessed 11 August 2022, https://esgf.github.io/nodes.html.

  • Wehrli, K., B. P. Guillod, M. Hauser, M. Leclair, and S. I. Seneviratne, 2018: Assessing the dynamic versus thermodynamic origin of climate model biases. Geophys. Res. Lett., 45, 84718479, https://doi.org/10.1029/2018GL079220.

    • Search Google Scholar
    • Export Citation
  • Wypych, A., B. Bochenek, and M. Różycki, 2018: Atmospheric moisture content over Europe and the northern Atlantic. Atmosphere, 9, 18, https://doi.org/10.3390/atmos9010018.

    • Search Google Scholar
    • Export Citation
  • Yeh, H.-F., and H.-L. Hsu, 2019: Using the Markov Chain to analyze precipitation and groundwater drought characteristics and linkage with atmospheric circulation. Sustainability, 11, 1817, https://doi.org/10.3390/su11061817.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 469 469 191
Full Text Views 83 83 43
PDF Downloads 101 101 52