{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:14:38Z","timestamp":1774037678936,"version":"3.50.1"},"reference-count":48,"publisher":"Copernicus GmbH","issue":"19","license":[{"start":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T00:00:00Z","timestamp":1602201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biogeosciences"],"abstract":"<jats:p>Abstract. The interaction between co-occurring drought and hot conditions is often particularly damaging to crop's health and may cause crop failure. Climate change exacerbates such risks due to an increase in the intensity and frequency of dry and hot events in many land regions. Hence, here we model the trivariate dependence between spring maximum temperature and spring precipitation and wheat and barley yields over two province regions in Spain with nested copulas. Based on the full trivariate joint distribution, we (i)\u00a0estimate the impact of compound hot and dry conditions on wheat and barley loss and (ii)\u00a0estimate the additional impact due to\ncompound hazards compared to individual hazards. We find that crop loss increases when drought or\nheat stress is aggravated to form compound dry and hot conditions and that an increase in the severity of\ncompound conditions leads to larger damage. For instance, compared to moderate drought only,\nmoderate compound dry and hot conditions increase the likelihood of crop loss by 8\u2009% to\n11\u2009%, while when starting with moderate heat, the increase is between 19\u2009% to 29\u2009%\n(depending on the cereal and region). These findings suggest that the likelihood of crop loss is\ndriven primarily by drought stress rather than by heat stress, suggesting that drought plays the dominant\nrole in the compound event; that is, drought stress is not required to be as extreme as heat\nstress to cause similar damage. Furthermore, when compound dry and hot conditions aggravate stress from\nmoderate to severe or extreme levels, crop loss probabilities increase 5\u2009% to 6\u2009% and\n6\u2009% to 8\u2009%, respectively (depending on the cereal and region). Our results highlight the\nadditional value of a trivariate approach for estimating the compounding effects of dry and\nhot extremes on crop failure risk. Therefore, this approach can effectively contribute to design\nmanagement options and guide the decision-making process in agricultural practices.<\/jats:p>","DOI":"10.5194\/bg-17-4815-2020","type":"journal-article","created":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T08:50:34Z","timestamp":1602233434000},"page":"4815-4830","source":"Crossref","is-referenced-by-count":144,"title":["Risk of crop failure due to compound dry and hot extremes estimated with nested copulas"],"prefix":"10.5194","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0481-0337","authenticated-orcid":false,"given":"Andreia Filipa Silva","family":"Ribeiro","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0042-2441","authenticated-orcid":false,"given":"Ana","family":"Russo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3147-5696","authenticated-orcid":false,"given":"C\u00e9lia Marina","family":"Gouveia","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6874-0599","authenticated-orcid":false,"given":"Patr\u00edcia","family":"P\u00e1scoa","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6045-1629","authenticated-orcid":false,"given":"Jakob","family":"Zscheischler","sequence":"additional","affiliation":[]}],"member":"3145","published-online":{"date-parts":[[2020,10,9]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","unstructured":"Balla,\nK., Rakszegi, M., Li, Z., Bekes, F., Bencze, S., and Veisz, O.: Quality of winter wheat in\nrelation to heat and drought shock after anthesis, Czech J. Food Sci., 29, 117\u2013128, 2011.\u2002a","DOI":"10.17221\/227\/2010-CJFS"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Bastos, A.,\nGouveia, C. M., Trigo, R. M., and Running, S. W.: Analysing the spatio-temporal impacts of the\n2003 and 2010 extreme heatwaves on plant productivity in Europe, Biogeosciences, 11, 3421\u20133435,\nhttps:\/\/doi.org\/10.5194\/bg-11-3421-2014, 2014.\u2002a","DOI":"10.5194\/bg-11-3421-2014"},{"key":"ref3","doi-asserted-by":"crossref","unstructured":"Ben-Ari, T., Adrian, J., Klein, T., Calanca, P., Van\u00a0der\nVelde, M., and Makowski, D.: Identifying indicators for extreme wheat and maize yield losses,\nAgr. Forest Meteorol., 220, 130\u2013140, https:\/\/doi.org\/10.1016\/j.agrformet.2016.01.009, 2016.\u2002a, b","DOI":"10.1016\/j.agrformet.2016.01.009"},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"Bevacqua, E., Maraun, D., Hob\u00e6k Haff, I., Widmann, M., and\nVrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions:\nanalysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701\u20132723,\nhttps:\/\/doi.org\/10.5194\/hess-21-2701-2017, 2017.\u2002a","DOI":"10.5194\/hess-21-2701-2017"},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"Bokusheva, R., Kogan, F., Vitkovskaya, I., Conradt,\nS., and Batyrbayeva, M.: Satellite-based vegetation health indices as a criteria for insuring\nagainst drought-related yield losses, Agr. Forest Meteorol., 220, 200\u2013206,\nhttps:\/\/doi.org\/10.1016\/j.agrformet.2015.12.066, 2016.\u2002a","DOI":"10.1016\/j.agrformet.2015.12.066"},{"key":"ref6","doi-asserted-by":"crossref","unstructured":"Buras, A., Rammig, A., and Zang,\nC. S.: Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003,\nBiogeosciences, 17, 1655\u20131672, https:\/\/doi.org\/10.5194\/bg-17-1655-2020, 2020.\u2002a, b","DOI":"10.5194\/bg-17-1655-2020"},{"key":"ref7","unstructured":"CGLS (Copernicus Global Land service): CORINE Land Cover (CLC) inventory, available at: https:\/\/land.copernicus.eu\/pan-european\/corine-land-cover, last access: 9\u00a0November 2019.\u2002a"},{"key":"ref8","unstructured":"COPA-COGECA: Assessment of the impact of\nthe heat wave and drought of the summer 2003 on agriculture and forestry, Committee of\nAgricultural Organisations in the European Union General Committee for Agricultural Cooperation in\nthe European Union, Brussels, p.\u00a015, 2003.\u2002a, b, c"},{"key":"ref9","doi-asserted-by":"crossref","unstructured":"Del\u00a0Moral, L.\u00a0G., Rharrabti, Y., Villegas, D., and Royo, C.: Evaluation of grain yield and its\ncomponents in durum wheat under Mediterranean conditions: an ontogenic approach, Agron. J., 95,\n266\u2013274, 2003.\u2002a","DOI":"10.2134\/agronj2003.2660"},{"key":"ref10","doi-asserted-by":"crossref","unstructured":"Durante, F. and Sempi, C.: Principles of\nCopula Theory, Taylor and Francis, New York, https:\/\/doi.org\/10.1201\/b18674, 2015.\u2002a, b","DOI":"10.1201\/b18674"},{"key":"ref11","doi-asserted-by":"crossref","unstructured":"Feng, S., Hao, Z.,\nZhang, X., and Hao, F.: Probabilistic evaluation of the impact of compound dry-hot events on\nglobal maize yields, Sci. Total Environ., 689, 1228\u20131234, https:\/\/doi.org\/10.1016\/j.scitotenv.2019.06.373,\n2019.\u2002a, b","DOI":"10.1016\/j.scitotenv.2019.06.373"},{"key":"ref12","doi-asserted-by":"crossref","unstructured":"Ferrise, R.,\nMoriondo, M., and Bindi, M.: Probabilistic assessments of climate change impacts on durum wheat in\nthe Mediterranean region, Nat. Hazards Earth Syst. Sci., 11, 1293\u20131302,\nhttps:\/\/doi.org\/10.5194\/nhess-11-1293-2011, 2011.\u2002a","DOI":"10.5194\/nhess-11-1293-2011"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"Garcia-Herrera, R., D\u00edaz, J., Trigo, R.\u00a0M., Luterbacher, J.,\nand Fischer, E.\u00a0M.: A review of the european summer heat wave of 2003, Crit. Rev. Environ.\nSci. Technol., 40, 267\u2013306, https:\/\/doi.org\/10.1080\/10643380802238137, 2010.\u2002a","DOI":"10.1080\/10643380802238137"},{"key":"ref14","doi-asserted-by":"crossref","unstructured":"Gaupp,\nF., Hall, J., Hochrainer-stigler, S., and Dadson, S.: Changing risks of simultaneous global\nbreadbasket failure, Nat. Clim. Change, 10, 54\u201357, https:\/\/doi.org\/10.1038\/s41558-019-0600-z, 2019.\n\u2002a","DOI":"10.1038\/s41558-019-0600-z"},{"key":"ref15","doi-asserted-by":"crossref","unstructured":"G\u00f3recki, J., Hofert, M., and Hole\u0148a, M.: On structure, family and parameter estimation\nof hierarchical Archimedean copulas, J. Stat. Comput. Simul., 87, 3261\u20133324, 2017.\u2002a","DOI":"10.1080\/00949655.2017.1365148"},{"key":"ref16","doi-asserted-by":"crossref","unstructured":"Harris, I.,\nJones, P.\u00a0D., Osborn, T.\u00a0J., and Lister, D.\u00a0H.: Updated high-resolution grids of monthly climatic\nobservations \u2013 the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623\u2013642, https:\/\/doi.org\/10.1002\/joc.3711,\n2014.\u2002a, b","DOI":"10.1002\/joc.3711"},{"key":"ref17","doi-asserted-by":"crossref","unstructured":"Iglesias, A. and Quiroga, S.:\nMeasuring the risk of climate variability to cereal production at five sites in Spain, Climate\nRes., 34, 47\u201357, 2007.\u2002a","DOI":"10.3354\/cr034047"},{"key":"ref18","unstructured":"IM and AEMET: Iberian climate atlas. Air Temperature and\nPrecipitation (1971\u20132000), Instituto de Meteorologia Portug\u00eas (IM) and Agencia Estatal de\nMeteorologia Espa\u00f1ola (AEMET), 2011.\u2002a"},{"key":"ref19","unstructured":"IPCC: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, edited by: Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M., and Midgley, P. M., Cambridge University Press, Cambridge, UK, and New York, NY, USA, 582\u00a0pp., 2012.\u2002a"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Kojadinovic, I. and Yan, J.:\nModeling Multivariate Distributions with Continuous Margins Using the copula R Package,\nJ. Stat. Softw., 34, 1\u201320, https:\/\/doi.org\/10.18637\/jss.v034.i09, 2010.\u2002a, b","DOI":"10.18637\/jss.v034.i09"},{"key":"ref21","doi-asserted-by":"crossref","unstructured":"Leonard, M., Westra, S., Phatak, A.,\nLambert, M., van\u00a0den Hurk, B., Mcinnes, K., Risbey, J., Schuster, S., Jakob, D., and\nStafford-Smith, M.: A compound event framework for understanding extreme impacts, WIRES\nClim. Change, 5, 113\u2013128, https:\/\/doi.org\/10.1002\/wcc.252, 2014.\u2002a","DOI":"10.1002\/wcc.252"},{"key":"ref22","doi-asserted-by":"crossref","unstructured":"Loboda, T., Krankina, O., Savin, I., Kurbanov, E., and Hall, J.: Land management and the impact of the 2010 extreme drought event on the agricultural and ecological systems of European Russia, in: Land-Cover and Land-Use Changes in Eastern Europe after the Collapse of the Soviet Union in 1991, Springer, Cham, 173\u2013192, 2017.\u2002a","DOI":"10.1007\/978-3-319-42638-9_8"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Madadgar, S., AghaKouchak, A., Farahmand, A., and Davis,\nS.\u00a0J.: Probabilistic estimates of drought impacts on agricultural production, Geophys. Res. Lett.,\n44, 7799\u20137807, https:\/\/doi.org\/10.1002\/2017GL073606, 2017.\u2002a","DOI":"10.1002\/2017GL073606"},{"key":"ref24","doi-asserted-by":"crossref","unstructured":"Nelsen, R.\u00a0B.: An Introduction to Copulas, in: Springer Series in Statistics, 2nd edn., Springer-Verlag New York, https:\/\/doi.org\/10.1007\/0-387-28678-0, 2006.\u2002a, b","DOI":"10.1007\/0-387-28678-0"},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"Nicolas, M.\u00a0E.,\nGleadow, R.\u00a0M., and Dalling, M.\u00a0J.: Effects of drought and high temperature on grain growth in\nwheat, Funct. Plant Biol., 11, 553\u2013566, 1984.\u2002a","DOI":"10.1071\/PP9840553"},{"key":"ref26","doi-asserted-by":"crossref","unstructured":"Okhrin, O. and Ristig, A.: Hierarchical\narchimedean copulae: The HAC package, J. Stat. Softw., 58, 1\u201320, https:\/\/doi.org\/10.18637\/jss.v058.i04,\n2014.\u2002a, b, c, d, e, f, g, h, i","DOI":"10.18637\/jss.v058.i04"},{"key":"ref27","doi-asserted-by":"crossref","unstructured":"Pe\u00f1a-Gallardo, M., Vicente-Serrano, S.\u00a0M.,\nDom\u00ednguez-Castro, F., and Beguer\u00eda, S.: The impact of drought on the productivity of two\nrainfed crops in Spain, Nat. Hazards Earth Syst. Sci., 19, 1215\u20131234,\nhttps:\/\/doi.org\/10.5194\/nhess-19-1215-2019, 2019.\u2002a","DOI":"10.5194\/nhess-19-1215-2019"},{"key":"ref28","doi-asserted-by":"crossref","unstructured":"Qaseem, M.\u00a0F.,\nQureshi, R., and Shaheen, H.: Effects of pre-anthesis drought, heat and their combination on the\ngrowth, yield and physiology of diverse wheat (Triticum aestivum L.) genotypes varying in\nsensitivity to heat and drought stress, Sci. Rep., 9, 1\u201312, 2019. \u2002a","DOI":"10.1038\/s41598-019-43477-z"},{"key":"ref29","doi-asserted-by":"crossref","unstructured":"Ribeiro, A.\u00a0F., Russo, A., Gouveia, C.\u00a0M., and P\u00e1scoa, P.:\nCopula-based agricultural drought risk of rainfed cropping systems, Agric. Water Manage., 223,\nhttps:\/\/doi.org\/10.1016\/j.agwat.2019.105689, 2019a.\u2002a, b, c, d, e","DOI":"10.1016\/j.agwat.2019.105689"},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Ribeiro, A. F. S., Russo, A., Gouveia, C. M., P\u00e1scoa, P., and\nPires, C. A. L.: Probabilistic modelling of the dependence between rainfed crops and drought\nhazard, Nat. Hazards Earth Syst. Sci., 19, 2795\u20132809, https:\/\/doi.org\/10.5194\/nhess-19-2795-2019,\n2019b.\u2002a, b, c, d, e, f","DOI":"10.5194\/nhess-19-2795-2019"},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Ribeiro, A. F.\u00a0S., Russo, A., Gouveia, C.\u00a0M., and P\u00e1scoa, P.: Modelling drought-related yield losses in Iberia using remote sensing and multiscalar indices, Theor. Appl. Climatol., 136, 203\u2013220, https:\/\/doi.org\/10.1007\/s00704-018-2478-5, 2019c.\u2002a, b, c","DOI":"10.1007\/s00704-018-2478-5"},{"key":"ref32","doi-asserted-by":"crossref","unstructured":"Ribeiro, A. F. S., Russo, A., Gouveia, C. M., P\u00e1scoa, P., and Zscheischler, J.: Rcode for risk of crop failure due to compound dry and hot extremes estimated with nested copulas, IMPECAF, available at:\nhttp:\/\/impecaf.rd.ciencias.ulisboa.pt\/Rcode_BGpaper.html (last access: 24 September 2020).\u2002a","DOI":"10.5194\/bg-2020-116"},{"key":"ref33","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez\u00a0D\u00edaz, J.\u00a0A., Weatherhead, E.\u00a0K., Knox,\nJ.\u00a0W., and Camacho, E.: Climate change impacts on irrigation water requirements in the\nGuadalquivir river basin in Spain, Regio. Environ. Change, 7, 149\u2013159,\nhttps:\/\/doi.org\/10.1007\/s10113-007-0035-3, 2007.\u2002a","DOI":"10.1007\/s10113-007-0035-3"},{"key":"ref34","doi-asserted-by":"crossref","unstructured":"Salvadori, G. and De\u00a0Michele, C.: On the\nUse of Copulas in Hydrology: Theory and Practice, J. Hydrol. Eng., 12, 369\u2013380,\nhttps:\/\/doi.org\/10.1061\/(ASCE)1084-0699(2007)12:4(369), 2007.\u2002a, b","DOI":"10.1061\/(ASCE)1084-0699(2007)12:4(369)"},{"key":"ref35","doi-asserted-by":"crossref","unstructured":"Salvadori, G., Durante, F., De Michele, C., Bernardi, M., and\nPetrella, L.: A multivariate copula-based framework for dealing with hazard scenarios and failure\nprobabilities, Water Resour. Res., 52, 3701\u20133721, https:\/\/doi.org\/10.1002\/2015WR017225, 2016.\u2002a","DOI":"10.1002\/2015WR017225"},{"key":"ref36","doi-asserted-by":"crossref","unstructured":"Schumacher, D.\u00a0L., Keune, J., Van\u00a0Heerwaarden, C.\u00a0C.,\nde\u00a0Arellano, J. V.-G., Teuling, A.\u00a0J., and Miralles, D.\u00a0G.: Amplification of mega-heatwaves\nthrough heat torrents fuelled by upwind drought, Nat. Geosci., 12, 712\u2013717, 2019.\u2002a, b","DOI":"10.1038\/s41561-019-0431-6"},{"key":"ref37","doi-asserted-by":"crossref","unstructured":"Serinaldi, F.: An uncertain journey around the tails of\nmultivariate hydrological distributions, Water Resour. Res., 49, 6527\u20136547,\nhttps:\/\/doi.org\/10.1002\/wrcr.20531, 2013.\u2002a","DOI":"10.1002\/wrcr.20531"},{"key":"ref38","doi-asserted-by":"crossref","unstructured":"Serinaldi, F.: Can we tell more than we can know? The\nlimits of bivariate drought analyses in the United States, Stoch. Environ. Res. Risk A., 30,\n1691\u20131704, https:\/\/doi.org\/10.1007\/s00477-015-1124-3, 2016.\u2002a","DOI":"10.1007\/s00477-015-1124-3"},{"key":"ref39","unstructured":"Sklar, A.: Fonctions de R\u00e9partition \u00e0 n\nDimensions et Leurs Marges, Institut Statistique de l'Universit\u00e9 de Paris, 8, 229\u2013231, 1959.\u2002a, b"},{"key":"ref40","unstructured":"Spanish Ministry of Agriculture, Fisheries and Food: Statistical Yearbook, available at: https:\/\/www.mapa.gob.es\/es\/estadistica\/temas\/publicaciones\/anuario-de-estadistica\/,\nlast access: 9\u00a0November 2019.\u2002a"},{"key":"ref41","doi-asserted-by":"crossref","unstructured":"Talukder, A., McDonald, G.\u00a0K., and Gill, G.\u00a0S.: Effect of short-term heat stress prior to flowering and early grain set on the grain yield of wheat, Field Crops Res., 160, 54\u201363, 2014.\u2002a","DOI":"10.1016\/j.fcr.2014.01.013"},{"key":"ref42","doi-asserted-by":"crossref","unstructured":"Vicente-Serrano, S.\u00a0M., Cuadrat-Prats, J.\u00a0M., and Romo, A.:\nEarly prediction of crop production using drought indices at different timescales and remote\nsensing data: application in the Ebro Valley (north-east Spain), Int. J. Remote Sens., 27,\n511\u2013518, https:\/\/doi.org\/10.1080\/01431160500296032, 2006.\u2002a","DOI":"10.1080\/01431160500296032"},{"key":"ref43","doi-asserted-by":"crossref","unstructured":"Zscheischler, J. and Fischer, E.: The\nrecord-breaking compound hot and dry 2018 growing season in Germany, Weather Clim. Extr., 29,\n100270, https:\/\/doi.org\/10.1016\/j.wace.2020.100270, 2020.\u2002a","DOI":"10.1016\/j.wace.2020.100270"},{"key":"ref44","doi-asserted-by":"crossref","unstructured":"Zscheischler, J. and\nSeneviratne, S.\u00a0I.: Dependence of drivers affects risks associated with compound events,\nSci. Adv., 3, e1700263, https:\/\/doi.org\/10.1126\/sciadv.1700263, 2017.\u2002a","DOI":"10.1126\/sciadv.1700263"},{"key":"ref45","doi-asserted-by":"crossref","unstructured":"Zscheischler, J., Michalak,\nA.\u00a0M., Schwalm, C., Mahecha, M.\u00a0D., Huntzinger, D.\u00a0N., Reichstein, M., Berthier, G., Ciais, P.,\nCook, R.\u00a0B., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng,\nS., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J.,\nand Zeng, N.: Impact of large-scale climate extremes on biospheric carbon fluxes: An\nintercomparison based on MsTMIP data, Global Biogeochem. Cy., 28, 585\u2013600,\nhttps:\/\/doi.org\/10.1002\/2014GB004826, 2014.\u2002a, b","DOI":"10.1002\/2014GB004826"},{"key":"ref46","doi-asserted-by":"crossref","unstructured":"Zscheischler, J., Orth, R., and Seneviratne, S. I.: Bivariate return periods of temperature and\nprecipitation explain a large fraction of European crop yields, Biogeosciences, 14, 3309\u20133320,\nhttps:\/\/doi.org\/10.5194\/bg-14-3309-2017, 2017.\n\u2002a, b, c, d","DOI":"10.5194\/bg-14-3309-2017"},{"key":"ref47","doi-asserted-by":"crossref","unstructured":"Zscheischler, J.,\nWestra, S., Van Den\u00a0Hurk, B.\u00a0J., Seneviratne, S.\u00a0I., Ward, P.\u00a0J., Pitman, A., Aghakouchak, A.,\nBresch, D.\u00a0N., Leonard, M., Wahl, T., and Zhang, X.: Future climate risk from compound events,\nNat. Clim. Change, 8, 469\u2013477, https:\/\/doi.org\/10.1038\/s41558-018-0156-3, 2018.\u2002a","DOI":"10.1038\/s41558-018-0156-3"},{"key":"ref48","doi-asserted-by":"crossref","unstructured":"Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., R., C.,\nHorton, R.\u00a0M., van\u00a0den Hurk, B., AghaKouchak, A., J\u00e9z\u00e9quel, A., Mahecha, M.\u00a0D., Maraun,\nD., Ramos, A.\u00a0M., Ridder, N., Thiery, W., and Vignotto, E.: A typology of compound weather and\nclimate events, Nat. Rev. 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