Articles | Volume 14, issue 4
https://doi.org/10.5194/esd-14-797-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-797-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Aug 2023
Research article |
| 16 Aug 2023
| 16 Aug 2023
Role of mean and variability change in changes in European annual and seasonal extreme precipitation events
Department of Geography, Ludwig-Maximilians-Universität
München, 80333 Munich, Germany
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Short summary
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To study floods and droughts that are likely to change in the future, we use climate projections from climate models. However, we first need to adjust the systematic biases of these projections at the catchment scale before using them in hydrological models. Our study compares statistical methods that can adjust these biases but specifically for climate projections that enable a quantification of internal climate variability. We provide recommendations on the most appropriate methods.
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Hydrol. Earth Syst. Sci., 29, 4153–4178, https://doi.org/10.5194/hess-29-4153-2025, https://doi.org/10.5194/hess-29-4153-2025, 2025
Short summary
Short summary
Continuous and high-quality meteorological datasets are crucial to study extreme hydro-climatic events. We here conduct a comprehensive spatio-temporal evaluation of precipitation and temperature for four climate reanalysis datasets, focusing on mean and extreme metrics, variability, trends, and the representation of droughts and floods over Switzerland. Our analysis shows that all datasets have some merit when limitations are considered, and that one dataset performs better than the others.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2864, https://doi.org/10.5194/egusphere-2024-2864, 2024
Preprint archived
Short summary
Short summary
We applied a biogeochemical model on grasslands in the pre-Alpine Ammer region in Germany and analyzed the influence of soil and climate on annual yields. In drought affected years, total yields were decreased by 4 %. Overall, yields decrease with rising elevation, but less so in drier and hotter years, whereas soil organic carbon has a positive impact on yields, especially in drier years. Our findings imply, that adapted management in the region allows to mitigate yield losses from drought.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
David Gampe, Clemens Schwingshackl, Andrea Böhnisch, Magdalena Mittermeier, Marit Sandstad, and Raul R. Wood
Earth Syst. Dynam., 15, 589–605, https://doi.org/10.5194/esd-15-589-2024, https://doi.org/10.5194/esd-15-589-2024, 2024
Short summary
Short summary
Using a special suite of climate simulations, we determine if and when climate change is detectable and translate this to the global warming prevalent in the corresponding year. Our results show that, at 1.5°C warming, >85 % of the global population (>95 % at 2.0° warming) is already exposed to nighttime temperatures altered by climate change beyond natural variability. Furthermore, even incremental changes in global warming levels result in increased human exposure to emerged climate signals.
Cited articles
Aalbers, E. E., Lenderink, G., van Meijgaard, E., and van den Hurk, B. J. J.
M.: Local-scale changes in mean and heavy precipitation in Western Europe,
climate change or internal variability?, Clim. Dynam., 50, 4745–4766,
https://doi.org/10.1007/s00382-017-3901-9, 2018.
Aalbers, E. E., van Meijgaard, E., Lenderink, G., de Vries, H., and van den Hurk, B. J. J. M.: The 2018 west-central European drought projected in a warmer climate: how much drier can it get?, Nat. Hazards Earth Syst. Sci., 23, 1921–1946, https://doi.org/10.5194/nhess-23-1921-2023, 2023.
Addor, N. and Fischer, E. M.: The influence of natural variability and
interpolation errors on bias characterization in RCM simulations, J.
Geophys. Res.-Atmos., 120, 10180–10195, https://doi.org/10.1002/2014JD022824, 2015.
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and
the hydrologic cycle, Nature, 419, 224–232,
https://doi.org/10.1038/nature01092, 2002.
Arora, V. K., Scinocca, J. F., Boer, G. J., Christian, J. R., Denman, K. L.,
Flato, G. M., Kharin, V. V., Lee, W. G., and Merryfield, W. J.: Carbon
emission limits required to satisfy future representative concentration
pathways of greenhouse gases, Geophys. Res. Lett., 38, L05805, https://doi.org/10.1029/2010GL046270, 2011.
Bador, M. and Alexander, L. V.: Future Seasonal Changes in Extreme
Precipitation Scale With Changes in the Mean, Earth's Future, 10, e2022EF002979,
https://doi.org/10.1029/2022EF002979, 2022.
Ban, N., Schmidli, J., and Schär, C.: Evaluation of the
convection-resolving regional climate modeling approach in decade-long
simulations, J. Geophys. Res.-Atmos., 119, 7889–7907,
https://doi.org/10.1002/2014JD021478, 2014.
Bélair, S., Mailhot, J., Girard, C., and Vaillancourt, P.: Boundary
Layer and Shallow Cumulus Clouds in a Medium-Range Forecast of a Large-Scale
Weather System, Mon. Weather Rev., 133, 1938–1960,
https://doi.org/10.1175/MWR2958.1, 2005.
Bevacqua, E., Zappa, G., and Shepherd, T. G.: Shorter cyclone clusters
modulate changes in European wintertime precipitation extremes, Environ.
Res. Lett., 15, 124005, https://doi.org/10.1088/1748-9326/abbde7, 2020.
Bintanja, R. and Selten, F. M.: Future increases in Arctic precipitation
linked to local evaporation and sea-ice retreat, Nature, 509, 479–482,
https://doi.org/10.1038/nature13259, 2014.
Bintanja, R., van der Wiel, K., van der Linden, E. C., Reusen, J., Bogerd,
L., Krikken, F., and Selten, F. M.: Strong future increases in Arctic
precipitation variability linked to poleward moisture transport, Sci.
Adv., 6, eaax6869, https://doi.org/10.1126/sciadv.aax6869, 2020.
Böhnisch, A., Ludwig, R., and Leduc, M.: Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe, Earth Syst. Dynam., 11, 617–640, https://doi.org/10.5194/esd-11-617-2020, 2020.
Böhnisch, A., Mittermeier, M., Leduc, M., and Ludwig, R.: Hot Spots and
Climate Trends of Meteorological Droughts in Europe–Assessing the Percent
of Normal Index in a Single-Model Initial-Condition Large Ensemble, Front.
Water, 3, 716621, https://doi.org/10.3389/frwa.2021.716621, 2021.
Brogli, R., Kröner, N., Sørland, S. L., Lüthi, D., and Schär,
C.: The Role of Hadley Circulation and Lapse-Rate Changes for the Future
European Summer Climate, J. Climate, 32, 385–404,
https://doi.org/10.1175/JCLI-D-18-0431.1, 2019.
Brönnimann, S., Rajczak, J., Fischer, E. M., Raible, C. C., Rohrer, M., and Schär, C.: Changing seasonality of moderate and extreme precipitation events in the Alps, Nat. Hazards Earth Syst. Sci., 18, 2047–2056, https://doi.org/10.5194/nhess-18-2047-2018, 2018.
Brunner, M. I., Swain, D. L., Wood, R. R., Willkofer, F., Done, J. M.,
Gilleland, E., and Ludwig, R.: An extremeness threshold determines the
regional response of floods to changes in rainfall extremes, Commun. Earth
Environ., 2, 173, https://doi.org/10.1038/s43247-021-00248-x, 2021.
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century,
Climatic Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Christensen, J. H., Larsen, M. A. D., Christensen, O. B., Drews, M., and
Stendel, M.: Robustness of European climate projections from dynamical
downscaling, Clim. Dynam., 53, 4857–4869,
https://doi.org/10.1007/s00382-019-04831-z, 2019.
Contractor, S., Donat, M. G., and Alexander, L. V.: Changes in Observed
Daily Precipitation over Global Land Areas since 1950, J. Climate, 34,
3–19, https://doi.org/10.1175/JCLI-D-19-0965.1, 2021.
Coppola, E., Sobolowski, S., Pichelli, E., Raffaele, F., Ahrens, B., Anders,
I., Ban, N., Bastin, S., Belda, M., Belusic, D., Caldas-Alvarez, A.,
Cardoso, R. M., Davolio, S., Dobler, A., Fernandez, J., Fita, L., Fumiere,
Q., Giorgi, F., Goergen, K., Güttler, I., Halenka, T., Heinzeller, D.,
Hodnebrog, Ø., Jacob, D., Kartsios, S., Katragkou, E., Kendon, E.,
Khodayar, S., Kunstmann, H., Knist, S., Lavín-Gullón, A., Lind, P.,
Lorenz, T., Maraun, D., Marelle, L., van Meijgaard, E., Milovac, J., Myhre,
G., Panitz, H.-J., Piazza, M., Raffa, M., Raub, T., Rockel, B., Schär,
C., Sieck, K., Soares, P. M. M., Somot, S., Srnec, L., Stocchi, P.,
Tölle, M. H., Truhetz, H., Vautard, R., de Vries, H., and Warrach-Sagi,
K.: A first-of-its-kind multi-model convection permitting ensemble for
investigating convective phenomena over Europe and the Mediterranean, Clim.
Dynam., 55, 3–34, https://doi.org/10.1007/s00382-018-4521-8, 2020.
Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio,
P. N., Fiore, A., Frankignoul, C., Fyfe, J. C., Horton, D. E., Kay, J. E.,
Knutti, R., Lovenduski, N. S., Marotzke, J., McKinnon, K. A., Minobe, S.,
Randerson, J., Screen, J. A., Simpson, I. R., and Ting, M.: Insights from
Earth system model initial-condition large ensembles and future prospects,
Nat. Clim. Change, 10, 277–286, https://doi.org/10.1038/s41558-020-0731-2,
2020.
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate
change projections: the role of internal variability, Clim. Dynam., 38,
527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012.
de Vries, H., Lenderink, G., van der Wiel, K., and van Meijgaard, E.:
Quantifying the role of the large-scale circulation on European summer
precipitation change, Clim. Dynam., 59, 2871–2886,
https://doi.org/10.1007/s00382-022-06250-z, 2022.
Donat, M. G., Lowry, A. L., Alexander, L. V., O'Gorman, P. A., and Maher,
N.: More extreme precipitation in the world's dry and wet regions, Nat.
Clim. Change, 6, 508–513, https://doi.org/10.1038/nclimate2941, 2016.
Findell, K. L., Keys, P. W., van der Ent, R. J., Lintner, B. R., Berg, A.,
and Krasting, J. P.: Rising Temperatures Increase Importance of Oceanic
Evaporation as a Source for Continental Precipitation, J. Climate, 32,
7713–7726, https://doi.org/10.1175/JCLI-D-19-0145.1, 2019.
Fischer, E. M. and Knutti, R.: Observed heavy precipitation increase
confirms theory and early models, Nat. Clim. Change, 6, 986–991,
https://doi.org/10.1038/NCLIMATE3110, 2016.
Fowler, H. J., Lenderink, G., Prein, A. F., Westra, S., Allan, R. P., Ban,
N., Barbero, R., Berg, P., Blenkinsop, S., Do, H. X., Guerreiro, S.,
Haerter, J. O., Kendon, E. J., Lewis, E., Schaer, C., Sharma, A., Villarini,
G., Wasko, C., and Zhang, X.: Anthropogenic intensification of
short-duration rainfall extremes, Nat. Rev. Earth Environ., 2, 107–122,
https://doi.org/10.1038/s43017-020-00128-6, 2021.
Fyfe, J. C., Derksen, C., Mudryk, L., Flato, G. M., Santer, B. D., Swart, N.
C., Molotch, N. P., Zhang, X., Wan, H., Arora, V. K., Scinocca, J., and
Jiao, Y.: Large near-term projected snowpack loss over the western United
States, Nat. Commun., 8, 14996,
https://doi.org/10.1038/ncomms14996, 2017.
Giorgi, F., Torma, C., Coppola, E., Ban, N., Schär, C., and Somot, S.:
Enhanced summer convective rainfall at Alpine high elevations in response to
climate warming, Nat. Geosci., 9, 584–589,
https://doi.org/10.1038/ngeo2761, 2016.
Guerreiro, S. B., Fowler, H. J., Barbero, R., Westra, S., Lenderink, G.,
Blenkinsop, S., Lewis, E., and Li, X.-F.: Detection of continental-scale
intensification of hourly rainfall extremes, Nat. Clim. Change, 8,
803–807, https://doi.org/10.1038/s41558-018-0245-3, 2018.
Hawcroft, M., Walsh, E., Hodges, K., and Zappa, G.: Significantly increased
extreme precipitation expected in Europe and North America from
extratropical cyclones, Environ. Res. Lett., 13, 124006,
https://doi.org/10.1088/1748-9326/aaed59, 2018.
Hawkins, E. and Sutton, R.: The Potential to Narrow Uncertainty in Regional
Climate Predictions, B. Am. Meteorol. Soc., 90, 1095–1108,
https://doi.org/10.1175/2009BAMS2607.1, 2009.
Held, I. M. and Soden, B. J.: Robust Responses of the Hydrological Cycle to
Global Warming, J. Climate, 19, 5686–5699,
https://doi.org/10.1175/JCLI3990.1, 2006.
Hodnebrog, Ø., Marelle, L., Alterskjær, K., Wood, R. R., Ludwig, R.,
Fischer, E. M., Richardson, T. B., Forster, P. M., Sillmann, J., and Myhre,
G.: Intensification of summer precipitation with shorter time-scales in
Europe, Environ. Res. Lett., 14, 124050,
https://doi.org/10.1088/1748-9326/ab549c, 2019.
Innocenti, S., Mailhot, A., Frigon, A., Cannon, A. J., and Leduc, M.:
Observed and Simulated Precipitation over Northeastern North America: How Do
Daily and Subdaily Extremes Scale in Space and Time?, J. Climate,
32, 8563–8582, https://doi.org/10.1175/JCLI-D-19-0021.1, 2019.
Kain, J. S. and Fritsch, J. M.: A One-Dimensional Entraining/Detraining
Plume Model and Its Application in Convective Parameterization, J. Atmos.
Sci., 47, 2784–2802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2, 1990.
Kautz, L.-A., Martius, O., Pfahl, S., Pinto, J. G., Ramos, A. M., Sousa, P.
M., and Woollings, T.: Atmospheric blocking and weather extremes over the
Euro-Atlantic sector – a review, Weather Clim. Dynam., 3, 305–336,
https://doi.org/10.5194/wcd-3-305-2022, 2022.
Kelder, T., Wanders, N., van der Wiel, K., Marjoribanks, T. I., Slater, L.
J., Wilby, R. L., and Prudhomme, C.: Interpreting extreme climate impacts
from large ensemble simulations – are they unseen or unrealistic?, Environ.
Res. Lett., 17, 44052, https://doi.org/10.1088/1748-9326/ac5cf4, 2022.
Kendon, E. J., Ban, N., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan,
S. C., Evans, J. P., Fosser, G., and Wilkinson, J. M.: Do
Convection-Permitting Regional Climate Models Improve Projections of Future
Precipitation Change?, B. Am. Meteorol. Soc., 98, 79–93,
https://doi.org/10.1175/BAMS-D-15-0004.1, 2017.
Kirchmeier-Young, M. C., Zwiers, F. W., and Gillett, N. P.: Attribution of
Extreme Events in Arctic Sea Ice Extent, J. Climate, 30, 553–571,
https://doi.org/10.1175/JCLI-D-16-0412.1, 2017.
Kirchmeier-Young, M. C., Gillett, N. P., Zwiers, F. W., Cannon, A. J., and
Anslow, F. S.: Attribution of the Influence of Human-Induced Climate Change
on an Extreme Fire Season, Earth's Future, 7, 2–10,
https://doi.org/10.1029/2018EF001050, 2019a.
Kirchmeier-Young, M. C., Wan, H., Zhang, X., and Seneviratne, S. I.:
Importance of Framing for Extreme Event Attribution: The Role of Spatial and
Temporal Scales, Earth's Future, 7, 1192–1204,
https://doi.org/10.1029/2019EF001253, 2019b.
Kreienkamp, F., Philip, S. Y., Tradowsky, J. S., Kew, S. F., Lorenz, P.,
Arrighi, J., Belleflamme, A., Bettmann, T., Caluwaerts, S., Chan, S. C.,
Ciavarella, A., de Cruz, L., de Vries, H., Demuth, N., Ferrone, A., Fischer,
r. M., Fowler, H. J., Goergen, K., Heinrich, D., Henrichs, Y., Lenderink,
G., Kaspar, F., Nilson, E., Otto, F. E. L., Ragone, F., Seneviratne, S. I.,
Singh, R. K., Skålevåg, A., Termonia, P., Thalheimer, L., van Aalst,
M., van den Bergh, J., van de Vyver, H., Vannitsem, S., van Oldenborgh, G.
J., van Schaeybroeck, B., Vautard, R., Vonk, D., and Wanders, N.: Rapid
attribution of heavy rainfall events leading to the severe flooding in
Western Europe during July 2021, https://www.worldweatherattribution.org/heavy-rainfall-which-led-to-severe-flooding-in-western-europe-made-more-likely-by-climate-change/
(last access: 25 February 2022), 2021.
Kröner, N., Kotlarski, S., Fischer, E., Lüthi, D., Zubler, E., and
Schär, C.: Separating climate change signals into thermodynamic,
lapse-rate and circulation effects: theory and application to the European
summer climate, Clim. Dynam., 48, 3425–3440,
https://doi.org/10.1007/s00382-016-3276-3, 2017.
Kuo, H. L.: On Formation and Intensification of Tropical Cyclones Through
Latent Heat Release by Cumulus Convection, J. Atmos. Sci., 22, 40–63,
https://doi.org/10.1175/1520-0469(1965)022<0040:OFAIOT>2.0.CO;2, 1965.
Leduc, M., Mailhot, A., Frigon, A., Martel, J.-L., Ludwig, R., Brietzke, G.
B., Giguère, M., Brissette, F., Turcotte, R., Braun, M., and Scinocca,
J.: The ClimEx Project: A 50-Member Ensemble of Climate Change Projections
at 12-km Resolution over Europe and Northeastern North America with the
Canadian Regional Climate Model (CRCM5), J. Appl. Meteorol.
Clim., 58, 663–693, https://doi.org/10.1175/JAMC-D-18-0021.1, 2019.
Lehner, F., Deser, C., Maher, N., Marotzke, J., Fischer, E. M., Brunner, L., Knutti, R., and Hawkins, E.: Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6, Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, 2020.
Lenderink, G. and van Meijgaard, E.: Increase in hourly precipitation
extremes beyond expectations from temperature changes, Nat. Geosci., 1,
511–514, https://doi.org/10.1038/ngeo262, 2008.
Lenderink, G., Barbero, R., Loriaux, J. M., and Fowler, H. J.:
Super-Clausius–Clapeyron Scaling of Extreme Hourly Convective Precipitation
and Its Relation to Large-Scale Atmospheric Conditions, J. Climate, 30,
6037–6052, https://doi.org/10.1175/JCLI-D-16-0808.1, 2017.
Lenggenhager, S. and Martius, O.: Atmospheric blocks modulate the odds of
heavy precipitation events in Europe, Clim. Dynam., 53, 4155–4171,
https://doi.org/10.1007/s00382-019-04779-0, 2019.
Maher, N., Matei, D., Milinski, S., and Marotzke, J.: ENSO Change in Climate
Projections: Forced Response or Internal Variability?, Geophys. Res. Lett., 45, 11390–11398, https://doi.org/10.1029/2018GL079764, 2018.
Maher, N., Milinski, S., and Ludwig, R.: Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble, Earth Syst. Dynam., 12, 401–418, https://doi.org/10.5194/esd-12-401-2021, 2021a.
Maher, N., Power, S. B., and Marotzke, J.: More accurate quantification of
model-to-model agreement in externally forced climatic responses over the
coming century, Nat. Commun., 12, 788,
https://doi.org/10.1038/s41467-020-20635-w, 2021b.
Martel, J.-L., Mailhot, A., and Brissette, F.: Global and Regional Projected
Changes in 100-yr Subdaily, Daily, and Multiday Precipitation Extremes
Estimated from Three Large Ensembles of Climate Simulations, J.
Climate, 33, 1089–1103, https://doi.org/10.1175/JCLI-D-18-0764.1, 2020.
Martel, J.-L., Brissette, F. P., Lucas-Picher, P., Troin, M., and Arsenault,
R.: Climate Change and Rainfall Intensity–Duration–Frequency Curves:
Overview of Science and Guidelines for Adaptation, J. Hydrol. Eng., 26,
3121001, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002122, 2021.
Martynov, A., Laprise, R., Sushama, L., Winger, K., Šeparović, L.,
and Dugas, B.: Reanalysis-driven climate simulation over CORDEX North
America domain using the Canadian Regional Climate Model, version 5: model
performance evaluation, Clim. Dynam., 41, 2973–3005,
https://doi.org/10.1007/s00382-013-1778-9, 2013.
Matte, D., Larsen, M. A. D., Christensen, O. B., and Christensen, J. H.:
Robustness and Scalability of Regional Climate Projections Over Europe,
Front. Environ. Sci., 6, 163, https://doi.org/10.3389/fenvs.2018.00163, 2019.
McKenna, C. M. and Maycock, A. C.: Sources of Uncertainty in Multimodel
Large Ensemble Projections of the Winter North Atlantic Oscillation, Geophys.
Res. Lett., 48, e2021GL093258, https://doi.org/10.1029/2021GL093258, 2021.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T.,
Lamarque, J.-F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K.,
Thomson, A., Velders, G. J. M., and van Vuuren, D. P.: The RCP greenhouse
gas concentrations and their extensions from 1765 to 2300, Climatic Change,
109, 213–241, https://doi.org/10.1007/s10584-011-0156-z, 2011.
Mittermeier, M., Braun, M., Hofstätter, M., Wang, Y., and Ludwig, R.:
Detecting Climate Change Effects on Vb Cyclones in a 50-Member Single-Model
Ensemble Using Machine Learning, Geophys. Res. Lett., 46, 14653–14661,
https://doi.org/10.1029/2019GL084969, 2019.
Mittermeier, M., Weigert, M., Rügamer, D., Küchenhoff, H., and
Ludwig, R.: A deep learning based classification of atmospheric circulation
types over Europe: projection of future changes in a CMIP6 large ensemble,
Environ. Res. Lett., 17, 84021, https://doi.org/10.1088/1748-9326/ac8068,
2022.
Myhre, G., Alterskjær, K., Stjern, C. W., Hodnebrog, Ø., Marelle, L.,
Samset, B. H., Sillmann, J., Schaller, N., Fischer, E., Schulz, M., and
Stohl, A.: Frequency of extreme precipitation increases extensively with
event rareness under global warming, Sci. Rep., 9, 16063,
https://doi.org/10.1038/s41598-019-52277-4, 2019.
Norris, J., Chen, G., and Neelin, J. D.: Thermodynamic versus Dynamic
Controls on Extreme Precipitation in a Warming Climate from the Community
Earth System Model Large Ensemble, J. Climate, 32, 1025–1045,
https://doi.org/10.1175/JCLI-D-18-0302.1, 2019.
O'Gorman, P. A. and Schneider, T.: Scaling of Precipitation Extremes over a
Wide Range of Climates Simulated with an Idealized GCM, J. Climate, 22,
5676–5685, https://doi.org/10.1175/2009JCLI2701.1, 2009.
Otto, F. E. L., van der Wiel, K., van Oldenborgh, G. J., Philip, S., Kew, S.
F., Uhe, P., and Cullen, H.: Climate change increases the probability of
heavy rains in Northern England/Southern Scotland like those of storm
Desmond – a real-time event attribution revisited, Environ. Res. Lett., 13,
24006, https://doi.org/10.1088/1748-9326/aa9663, 2018a.
Otto, F. E. L., Philip, S., Kew, S., Li, S., King, A., and Cullen, H.:
Attributing high-impact extreme events across timescales – a case study of
four different types of events, Climatic Change, 149, 399–412,
https://doi.org/10.1007/s10584-018-2258-3, 2018b.
Ouranos: CRCM5-LE ClimEx, https://www.climex-project.org/en/data-access (last access: 14 August 2023), 2020.
Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C., and Sanderson, B. M.:
Precipitation variability increases in a warmer climate, Sci. Rep.,
7, 17966, https://doi.org/10.1038/s41598-017-17966-y, 2017.
Pfahl, S., O'Gorman, P. A., and Fischer, E. M.: Understanding the regional
pattern of projected future changes in extreme precipitation, Nat. Clim.
Change, 7, 423–427, https://doi.org/10.1038/nclimate3287, 2017.
Philip, S. Y., Kew, S. F., van Oldenborgh, G. J., Anslow, F. S., Seneviratne, S. I., Vautard, R., Coumou, D., Ebi, K. L., Arrighi, J., Singh, R., van Aalst, M., Pereira Marghidan, C., Wehner, M., Yang, W., Li, S., Schumacher, D. L., Hauser, M., Bonnet, R., Luu, L. N., Lehner, F., Gillett, N., Tradowsky, J. S., Vecchi, G. A., Rodell, C., Stull, R. B., Howard, R., and Otto, F. E. L.: Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021, Earth Syst. Dynam., 13, 1689–1713, https://doi.org/10.5194/esd-13-1689-2022, 2022.
Pichelli, E., Coppola, E., Sobolowski, S., Ban, N., Giorgi, F., Stocchi, P.,
Alias, A., Belušić, D., Berthou, S., Caillaud, C., Cardoso, R. M.,
Chan, S., Christensen, O. B., Dobler, A., de Vries, H., Goergen, K., Kendon,
E. J., Keuler, K., Lenderink, G., Lorenz, T., Mishra, A. N., Panitz, H.-J.,
Schär, C., Soares, P. M. M., Truhetz, H., and Vergara-Temprado, J.: The
first multi-model ensemble of regional climate simulations at
kilometer-scale resolution part 2: historical and future simulations of
precipitation, Clim. Dynam., 56, 3581–3602,
https://doi.org/10.1007/s00382-021-05657-4, 2021.
Poschlod, B.: Using high-resolution regional climate models to estimate return levels of daily extreme precipitation over Bavaria, Nat. Hazards Earth Syst. Sci., 21, 3573–3598, https://doi.org/10.5194/nhess-21-3573-2021, 2021.
Poschlod, B. and Ludwig, R.: Internal variability and temperature scaling of
future sub-daily rainfall return levels over Europe, Environ. Res. Lett.,
16, 64097, https://doi.org/10.1088/1748-9326/ac0849, 2021.
Poschlod, B., Ludwig, R., and Sillmann, J.: Ten-year return levels of sub-daily extreme precipitation over Europe, Earth Syst. Sci. Data, 13, 983–1003, https://doi.org/10.5194/essd-13-983-2021, 2021.
Prein, A. F., Gobiet, A., Truhetz, H., Keuler, K., Goergen, K., Teichmann,
C., Fox Maule, C., van Meijgaard, E., Déqué, M., Nikulin, G.,
Vautard, R., Colette, A., Kjellström, E., and Jacob, D.: Precipitation
in the EURO-CORDEX 0.11∘ and 0.44∘ simulations: high
resolution, high benefits?, Clim. Dynam., 46, 383–412,
https://doi.org/10.1007/s00382-015-2589-y, 2016.
Rajczak, J. and Schär, C.: Projections of Future Precipitation Extremes
Over Europe: A Multimodel Assessment of Climate Simulations, J. Geophys.
Res.-Atmos., 122, 10773–10800, https://doi.org/10.1002/2017JD027176, 2017.
Rajczak, J., Pall, P., and Schär, C.: Projections of extreme
precipitation events in regional climate simulations for Europe and the
Alpine Region, J. Geophys. Res.-Atmos., 118, 3610–3626,
https://doi.org/10.1002/jgrd.50297, 2013.
Ritzhaupt, N. and Maraun, D.: Consistency of Seasonal Mean and Extreme
Precipitation Projections Over Europe Across a Range of Climate Model
Ensembles, J. Geophys. Res.-Atmos., 128, e2022JD037845,
https://doi.org/10.1029/2022JD037845, 2023.
Rutgersson, A., Kjellström, E., Haapala, J., Stendel, M., Danilovich, I., Drews, M., Jylhä, K., Kujala, P., Larsén, X. G., Halsnæs, K., Lehtonen, I., Luomaranta, A., Nilsson, E., Olsson, T., Särkkä, J., Tuomi, L., and Wasmund, N.: Natural hazards and extreme events in the Baltic Sea region, Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, 2022.
Schemm, S., Sprenger, M., Martius, O., Wernli, H., and Zimmer, M.: Increase
in the number of extremely strong fronts over Europe? A study based on
ERA-Interim reanalysis (1979–2014), Geophys. Res. Lett., 44, 553–561,
https://doi.org/10.1002/2016GL071451, 2017.
Šeparović, L., Alexandru, A., Laprise, R., Martynov, A., Sushama,
L., Winger, K., Tete, K., and Valin, M.: Present climate and climate change
over North America as simulated by the fifth-generation Canadian regional
climate model, Clim. Dynam., 41, 3167–3201,
https://doi.org/10.1007/s00382-013-1737-5, 2013.
Sippel, S., Zscheischler, J., Heimann, M., Lange, H., Mahecha, M. D., van Oldenborgh, G. J., Otto, F. E. L., and Reichstein, M.: Have precipitation extremes and annual totals been increasing in the world's dry regions over the last 60 years?, Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, 2017.
Sippel, S., Meinshausen, N., Fischer, E. M., Székely, E., and Knutti,
R.: Climate change now detectable from any single day of weather at global
scale, Nat. Clim Change, 10, 35–41,
https://doi.org/10.1038/s41558-019-0666-7, 2020.
Suarez-Gutierrez, L., Müller, W. A., Li, C., and Marotzke, J.: Dynamical
and thermodynamical drivers of variability in European summer heat extremes,
Clim. Dynam,, 54, 4351–4366, https://doi.org/10.1007/s00382-020-05233-2,
2020.
Swain, D. L., Langenbrunner, B., Neelin, J. D., and Hall, A.: Increasing
precipitation volatility in twenty-first-century California, Nat. Clim.
Change, 8, 427–433, https://doi.org/10.1038/s41558-018-0140-y, 2018.
Swain, D. L., Singh, D., Touma, D., and Diffenbaugh, N. S.: Attributing
Extreme Events to Climate Change: A New Frontier in a Warming World, One
Earth, 2, 522–527, https://doi.org/10.1016/j.oneear.2020.05.011, 2020.
Thompson, V., Dunstone, N. J., Scaife, A. A., Smith, D. M., Slingo, J. M.,
Brown, S., and Belcher, S. E.: High risk of unprecedented UK rainfall in the
current climate, Nat. Commun., 8, 107,
https://doi.org/10.1038/s41467-017-00275-3, 2017.
van der Wiel, K. and Bintanja, R.: Contribution of climatic changes in mean
and variability to monthly temperature and precipitation extremes, Commun.
Earth Environ., 2, 1, https://doi.org/10.1038/s43247-020-00077-4, 2021.
van der Wiel, K., Wanders, N., Selten, F. M., and Bierkens, M. F. P.: Added
Value of Large Ensemble Simulations for Assessing Extreme River Discharge in
a 2 ∘C Warmer World, Geophys. Res. Lett., 46, 2093–2102,
https://doi.org/10.1029/2019GL081967, 2019.
van der Wiel, K., Batelaan, T. J., and Wanders, N.: Large increases of
multi-year droughts in north-western Europe in a warmer climate, Clim. Dynam., 60, 1781–1800, https://doi.org/10.1007/s00382-022-06373-3, 2022.
von Trentini, F., Aalbers, E. E., Fischer, E. M., and Ludwig, R.: Comparing interannual variability in three regional single-model initial-condition large ensembles (SMILEs) over Europe, Earth Syst. Dynam., 11, 1013–1031, https://doi.org/10.5194/esd-11-1013-2020, 2020.
Westra, S., Alexander, L. V., and Zwiers, F. W.: Global Increasing Trends in
Annual Maximum Daily Precipitation, J. Climate, 26, 3904–3918,
https://doi.org/10.1175/JCLI-D-12-00502.1, 2013.
Westra, S., Fowler, H. J., Evans, J. P., Alexander, L. V., Berg, P.,
Johnson, F., Kendon, E. J., Lenderink, G., and Roberts, N. M.: Future
changes to the intensity and frequency of short-duration extreme rainfall,
Rev. Geophys., 52, 522–555, https://doi.org/10.1002/2014RG000464, 2014.
Williams, A. I. L. and O'Gorman, P. A.: Summer-Winter Contrast in the
Response of Precipitation Extremes to Climate Change Over Northern
Hemisphere Land, Geophys. Res. Lett., 49, e2021GL096531, https://doi.org/10.1029/2021GL096531,
2022.
Wood, R. R. and Ludwig, R.: Analyzing Internal Variability and Forced
Response of Subdaily and Daily Extreme Precipitation Over Europe, Geophys.
Res. Lett., 47, e2020GL089300, https://doi.org/10.1029/2020GL089300, 2020.
Wood, R. R., Lehner, F., Pendergrass, A. G., and Schlunegger, S.: Changes in
precipitation variability across time scales in multiple global climate
model large ensembles, Environ. Res. Lett., 16, 84022,
https://doi.org/10.1088/1748-9326/ac10dd, 2021.
Zittis, G., Bruggeman, A., and Lelieveld, J.: Revisiting future extreme
precipitation trends in the Mediterranean, Weather and Climate Extremes, 34,
100380, https://doi.org/10.1016/j.wace.2021.100380, 2021.
Short summary
The change in extreme-event occurrence is influenced by both a shift in the mean and a change in variability. How large the individual contributions are remains largely unknown. Large-ensemble climate simulations and probability risk ratio are used to partition the change in extreme precipitation events into contributions from a change in the mean and variability. The results reveal that the change in variability can be equally as important as or even more important than the mean change.
The change in extreme-event occurrence is influenced by both a shift in the mean and a change in...
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