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  • Perspective
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Understanding and managing connected extreme events

Nature Climate Change volume 10, pages 611–621 (2020)Cite this article

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This article has been updated

Abstract

Extreme weather and climate events and their impacts can occur in complex combinations, an interaction shaped by physical drivers and societal forces. In these situations, governance, markets and other decision-making structures—together with population exposure and vulnerability—create nonphysical interconnections among events by linking their impacts, to positive or negative effect. Various anthropogenic actions can also directly affect the severity of events, further complicating these feedback loops. Such relationships are rarely characterized or considered in physical-sciences-based research contexts. Here, we present a multidisciplinary argument for the concept of connected extreme events, and we suggest vantage points and approaches for producing climate information useful in guiding decisions about them.

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Fig. 1: The flow of connected extremes.
Fig. 2: Major losses caused by extreme climate events over 1980–2019 and their connective elements.
Fig. 3: Decisions related to multiscale connected extremes.

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Data availability

Data used in Fig. 2 are available from the corresponding author upon reasonable request. The data are not publicly available as they are part of a commercially proprietary dataset.

Code availability

Code for reproducing Figs. 2 and 3 has been archived at https://doi.org/10.5281/zenodo.3714226.

Change history

  • 22 June 2020

    In the version of this Perspective originally published, ‘Temporal compounding, concurrent’ in Fig. 2 should have read ‘Temporal compounding, concurrence’; this has now been corrected in the online versions.

References

  1. Klotzbach, P. J. et al. The extremely active 2017 North Atlantic hurricane season. Mon. Weather Rev. 146, 3425–3443 (2018).

    Google Scholar 

  2. Murakami, H., Levin, E., Delworth, T. L., Gudgel, R. & Hsu, P.-C. Dominant effect of relative tropical Atlantic warming on major hurricane occurrence. Science 362, 794–799 (2018).

    CAS  Google Scholar 

  3. 2017 Hurricane Season FEMA After-Action Report (FEMA, 2018); https://www.fema.gov/media-library/assets/documents/167249 Details the timeline of actions by the US Federal Emergency Management Agency in the lead-up and aftermath of Hurricanes Harvey and Maria in 2017, including underlying decision-making parameters.

  4. Transformation and Innovation in the Wake of Devastation: An Economic and Disaster Recovery Plan for Puerto Rico (Government of Puerto Rico, 2018); http://www.p3.pr.gov/assets/pr-transformation-innovation-plan-congressional-submission-080818.pdf

  5. Short-term Outlook for EU Agricultural Markets in 2018 and 2019. Report No. 22 (European Commission, 2018); https://ec.europa.eu/info/sites/info/files/food-farming-fisheries/farming/documents/short-term-outlook-autumn-2018_en.pdf

  6. Faust, E. & Strobl, M. Heatwaves, Drought and Forest Fires in Europe: Billions of Dollars in Losses for Agricultural Sector (Munich Re, 2018); https://www.munichre.com/topics-online/en/climate-change-and-natural-disasters/climate-change/heatwaves-and-drought-in-europe.html

  7. Oppenheimer, M. et al. in IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 1039–1099 (IPCC, Cambridge Univ. Press, 2014). Defines the terms ‘hazards’, ‘exposure’ and ‘vulnerability’, and provides a consensus framework for how these factors combine to shape risk, including examples and assessment paradigms.

  8. Zscheischler, J. et al. A typology of compound weather and climate events. Nat. Rev. Earth Env. https://doi.org/10.1038/s43017-020-0060-z (2020). Reviews key concepts and methodologies for compound extreme weather and climate events, and proposes a classification scheme to unite analyses across scales and event types.

  9. Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).

    Google Scholar 

  10. Wahl, T. et al. When environmental forces collide. EOS https://doi.org/10.1029/2018EO099745 (2018).

  11. Leonard, M. et al. A compound event framework for understanding extreme impacts. WIREs Clim. Change 5, 113–128 (2014). Describes the motivation for the concept of compound weather and climate events, and proposes a graphical and statistical analysis framework that hinges upon stakeholder input.

    Google Scholar 

  12. Seneviratne, S. I. et al. in 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 (eds Field, C. B. et al.) 109–230 (IPCC, Cambridge Univ. Press, 2012).

  13. Tilloy, A., Malamud, B. D., Winter, H. & Joly-Laugel, A. A review of quantification methodologies for multi-hazard interrelationships. Earth-Sci. Rev. 196, 102881 (2019).

    Google Scholar 

  14. Pescaroli, G. & Alexander, D. Understanding compound, interconnected, interacting, and cascading risks: a holistic framework. Risk Anal. 38, 2245–2257 (2018). Differentiates among four types of complex risk related to physical systems and describes some of the key challenges that these pose for the goals of the Sendai Framework for Disaster Risk Reduction.

    Google Scholar 

  15. Sadegh, M. et al. Multihazard scenarios for analysis of compound extreme events. Geophys. Res. Lett. 45, 5470–5480 (2018).

    Google Scholar 

  16. Gallina, V. et al. A review of multi-risk methodologies for natural hazards: consequences and challenges for a climate change impact assessment. J. Env. Manag. 168, 123–132 (2016).

    Google Scholar 

  17. Sendai Framework for Disaster Risk Reduction 2015–2030 Report No. UNISDR/GE/2015 ICLUX EN5000 (United Nations, 2015).

  18. Gill, J. C. & Malamud, B. D. Reviewing and visualizing the interactions of natural hazards. Rev. Geophys. 52, 680–722 (2014).

    Google Scholar 

  19. Renn, O., Lucas, K., Haas, A. & Jaeger, C. Things are different today: the challenge of global systemic risks. J. Risk Res. 22, 401–415 (2017). Proposes that systemic risks—whether financial, climatic or otherwise—share the characteristics of being global, interconnected, nonlinear and stochastic, and have multiple scales of interaction that can lead to catastrophe.

    Google Scholar 

  20. Lloréns, H. Ruin nation. NACLA Report on the Americas 50, 154–159 (2018).

    Google Scholar 

  21. Schwartz, E. The facts: Hurricane Maria’s effect on Puerto Rico. MercyCorps https://www.mercycorps.org/articles/united-states/hurricane-maria-puerto-rico (2019).

  22. Mazzei, P. & Robles, F. Former FEMA official accused of taking bribes in Hurricane Maria recovery. New York Times (2019); https://www.nytimes.com/2019/09/10/us/puerto-rico-fema-arrests-corruption.html

  23. Clement, S., Zezima, K., Guskin, E., Leaming, W. & Ribas, J. Puerto Rico after Maria: residents see a failure at all levels of government. Washington Post (2018); https://www.washingtonpost.com/news/national/wp/2018/09/12/feature/residents-see-a-failure-at-all-levels-of-government/

  24. Santos-Burgoa, C. et al. Differential and persistent risk of excess mortality from Hurricane Maria in Puerto Rico: a time-series analysis. Lancet Planet. Health 2, e478–e488 (2018).

    Google Scholar 

  25. Rodriguez, H. in Hurricanes: Climate and Socioeconomic Impacts (eds H. F. Diaz, H. F. & Pulwarty, R. S.) 121–146 (Springer, 1997).

  26. Levermann, A. Make supply chains climate-smart. Nature 506, 27–29 (2014).

    CAS  Google Scholar 

  27. Johnson, J. & Gheorghe, A. V. Antifragility analysis and measurement framework for systems of systems. Int. J. Disaster Risk Sci. 4, 159–168 (2013).

    Google Scholar 

  28. Helbing, D. Globally networked risks and how to respond. Nature 497, 51–59 (2013).

    CAS  Google Scholar 

  29. Dilling, L. et al. Is adaptation success a flawed concept? Nat. Clim. Change 9, 570–574 (2019).

    Google Scholar 

  30. Introduction to the IRGC Risk Governance Framework, Revised Version (International Risk Governance Center, 2017).

  31. Treverton, G. F. et al. Global Food System Stability and Risk: At the Nexus of Defense and Development (Thomson Reuters, 2018).

  32. Deryng, D., Conway, D., Ramankutty, N., Price, J. & Warren, R. Global crop yield response to extreme heat stress under multiple climate change futures. Env. Res. Lett. 9, 034011 (2014).

    Google Scholar 

  33. Lucas, R. A. I., Epstein, Y. & Kjellstrom, T. Excessive occupational heat exposure: a significant ergonomic challenge and health risk for current and future workers. Extr. Physiol. Med. 3, 14 (2014).

    Google Scholar 

  34. Iizumi, T. & Ramankutty, N. How do weather and climate influence cropping area and intensity? Glob. Food Secur. 4, 46–50 (2015).

    Google Scholar 

  35. Ben-Ari, T. et al. Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France. Nat. Commun. 9, 1627 (2018).

    Google Scholar 

  36. Gaupp, F., Hall, J., Mitchell, D. & Dadson, S. Increasing risks of multiple breadbasket failure under 1.5 and 2°C global warming. Agr. Syst. 175, 34–45 (2019).

    Google Scholar 

  37. Kornhuber, K. et al. Amplified Rossby waves enhance risk of concurrent heatwaves in major breadbasket regions. Nat. Clim. Change 10, 48–53 (2020).

    Google Scholar 

  38. Singh, D. et al. Climate and the global famine of 1876–78. J. Clim. 31, 9445–9467 (2018).

    Google Scholar 

  39. Anderson, W. B., Seager, R., Baethgen, W., Cane, M. & You, L. Synchronous crop failures and climate-forced production variability. Sci. Adv. 5, eeaw1976 (2019).

    Google Scholar 

  40. Tigchelaar, M., Battisti, D. S., Naylor, R. L. & Ray, D. K. Future warming increases probability of globally synchronized maize production shocks. Proc. Natl Acad. Sci. USA 115, 6644–6649 (2018).

    Google Scholar 

  41. Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J. & Kirchner, J. W. The relative importance of different flood-generating mechanisms across Europe. Water Resour. Res. 55, 4582–4593 (2019).

    Google Scholar 

  42. Namias, J. Some meteorological aspects of drought, with special reference to the summers of 1952–54 over the United States. Mon. Weather Rev. 83, 199–205 (1955).

    Google Scholar 

  43. Bender, J., Wahl, T., Müller, A. & Jensen, J. A multivariate design framework for river confluences. Hydrol. Sci. J. 61, 471–482 (2015).

    Google Scholar 

  44. Ward, P. J. et al. Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries. Environ. Res. Lett. 13, 084012 (2018).

    Google Scholar 

  45. Moftakhari, H. R., Salvadori, G., AghaKouchak, A., Sanders, B. F. & Matthew, R. A. Compounding effects of sea level rise and fluvial flooding. Proc. Natl Acad. Sci. USA 114, 9785–9790 (2017).

    CAS  Google Scholar 

  46. Serinaldi, F. & Kilsby, C. G. A blueprint for full collective flood risk estimation: demonstration for European river flooding. Risk Anal. 37, 1958–1976 (2017).

    Google Scholar 

  47. Rhee, G., Salazar, J. & Grigg, C. How long does a 15-year drought last? On the correlation of rare events. J. Clim. 32, 1345–1359 (2019).

    Google Scholar 

  48. Bagley, J. E., Desai, A. R., Harding, K. J., Snyder, P. K. & Foley, J. A. Drought and deforestation: has land cover change influenced recent precipitation extremes in the Amazon? J. Clim. 27, 345–361 (2014).

    Google Scholar 

  49. Cook, B. I., Miller, R. L. & Seager, R. Amplification of the North American “Dust Bowl” drought through human-induced land degradation. Proc. Natl Acad. Sci. USA 106, 4997–5001 (2009).

    CAS  Google Scholar 

  50. Otkin, J. A. et al. Flash droughts: A review and assessment of the challenges imposed by rapid-onset droughts in the United States. Bull. Amer. Meteorol. Soc. 99, 911–920 (2018).

    Google Scholar 

  51. Overpeck, J. T. The challenge of hot drought. Nature 503, 350–351 (2013).

    CAS  Google Scholar 

  52. Vogel, M. M. et al. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. J. Geophys. Res. Atmos. 44, 1511–1519 (2017).

    Google Scholar 

  53. Salvadori, G. & de Michele, C. Multivariate multiparameter extreme value models and return periods: A copula approach. Water Resour. Res. 46, w10501 (2010).

    Google Scholar 

  54. Wahl, T., Jain, S., Bender, J., Meyers, S. & Luther, M. Increasing risk of compound flooding from storm surge and rainfall for major US cities. Nat. Clim. Change 5, 1093–1097 (2015).

    Google Scholar 

  55. Zscheischler, J. & Seneviratne, S. I. Dependence of drivers affects risks associated with compound events. Sci. Adv. 3, e1700263 (2017).

    Google Scholar 

  56. Di Baldassarre, G. et al. Water shortages worsened by reservoir effects. Nat. Sustain. 1, 617–622 (2018).

    Google Scholar 

  57. Greve, P. et al. Global assessment of water challenges under uncertainty in water scarcity projections. Nat. Sustain. 1, 486–494 (2018).

    Google Scholar 

  58. Welch, H. L. & Barnes, K. K. Streamflow Characterization and Summary of Water-quality Data Collection During the Mississippi River flood, April through July 2011. Report No. 2013–1106 (U. S. Department of the Interior and U. S. Geological Survey, 2013); http://pubs.usgs.gov/of/2013/1106/

  59. Torres, J. M. et al. Characterizing the hydraulic interactions of hurricane storm surge and rainfall-runoff for the Houston-Galveston region. Coast Eng. 106, 7–19 (2015).

    Google Scholar 

  60. Di Baldassarre, G. et al. Sociohydrology: scientific challenges in addressing the sustainable development goals. Water Resour. Res. 55, 6327–6355 (2019). Defines ‘sociohydrology’ as linking physical and technical approaches to water management with societal dimensions such as power dynamics, culture and psychology, and describes how the latter result in suboptimal decision-making for a wide spectrum of hydrological challenges.

    Google Scholar 

  61. Schulz, A. & Northridge, M. E. Social determinants of health: implications for environmental health promotion. Health Educ. Behav. 31, 455–71 (2004).

    Google Scholar 

  62. Gasparrini, A. et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 386, 369–375 (2015).

    Google Scholar 

  63. English, P. B. & Richardson, M. Components of population vulnerability and their relationship with climate-sensitive health threats. Curr. Env. Health Rep. 3, 91–98 (2016).

    CAS  Google Scholar 

  64. Schnell, J. L. & Prather, M. P. Co-occurrence of extremes in surface ozone, particulate matter, and temperature over eastern North America. Proc. Natl Acad. Sci. USA 114, 2854–2859 (2017).

    CAS  Google Scholar 

  65. Baldwin, J. W., Dessy, J. B., Vecchi, G. A. & Oppenheimer, M. Temporally compound heat wave events and global warming: an emerging hazard. Earth’s Future 7, 411–427 (2019).

    Google Scholar 

  66. Matthews, T., Wilby, R. L. & Murphy, C. An emerging tropical cyclone-deadly heat compound hazard. Nat. Clim. Change 9, 602–606 (2019).

    Google Scholar 

  67. Storm, I., den Hertog, F., Van Oers, H. & Schuit, A. J. How to improve collaboration between the public health sector and other policy sectors to reduce health inequalities? – a study in sixteen municipalities in the Netherlands. Int. J. Equity Health 15, 97 (2016).

    Google Scholar 

  68. Sisco, S. et al. The role and function of the Liaison Officer: lessons learned and applied after Superstorm Sandy. Health Secur. 17, 109–116 (2019).

    Google Scholar 

  69. Abramson, D. M. & Redlener, I. Hurricane Sandy: lessons learned. Disast. Med. Publ. Health Prepared. 6, 328–330 (2012).

    Google Scholar 

  70. Ebi, K. et al. Stress testing the capacity of health systems to manage climate change-related shocks and stresses. Int. J. Env. Res. Public Health 15, 2370 (2018).

    Google Scholar 

  71. Woo, G. Counterfactual disaster risk analysis. Variance 10, 279–291 (2016).

    Google Scholar 

  72. Moftakhari, H. & AghaKouchak, A. Increasing exposure of energy infrastructure to compound hazards: cascading wildfires and extreme rainfall. Env. Res. Lett. 14, 104018 (2019).

    CAS  Google Scholar 

  73. Litman, T. Lessons from Katrina and Rita: what major disasters can teach transportation planners. J. Transport. Eng. 132, 11–21 (2006).

    Google Scholar 

  74. Marks, D. The urban political ecology of the 2011 floods in Bangkok: the creation of uneven vulnerabilities. Pacific Affairs 88, 623–652 (2015).

    Google Scholar 

  75. Martius, O., Pfahl, S. & Chevalier, C. A global quantification of compound precipitation and wind extremes. Geophys. Res. Lett. 43, 7709–7717 (2016).

    Google Scholar 

  76. Jongman, B. et al. Increasing stress on disaster-risk finance due to large floods. Nat. Clim. Change 4, 264–268 (2014).

    Google Scholar 

  77. Holzheu, T. & Turner, G. The natural catastrophe protection gap: measurement, root causes and ways of addressing underinsurance for extreme events. The Geneva Papers on Risk and Assurance 43, 37–71 (2018).

    Google Scholar 

  78. Weather, Climate and Catastrophe Insight: 2019 Annual Report (Aon, 2020); http://thoughtleadership.aon.com/Documents/20200122-if-natcat2020.pdf

  79. Golnaraghi, M. et al. Managing Physical Climate Risk: Leveraging Innovations in Catastrophe Risk Modelling (The Geneva Association, 2018). Describes the state of the art in assessing risks from climate hazards from the perspective of the insurance sector, including an overview of current initiatives and future objectives.

  80. Haasnoot, M., Kwakkel, J. H., Walker, W. E. & ter Maat, J. Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world. Glob. Environ. Change 23, 485–498 (2013).

    Google Scholar 

  81. Hall, J. W., Lempert, R. J., Keller, K., Hackbarth, A., Mijere, C. & McInerney, D. J. Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods. Risk Anal. 32, 1657–1673 (2012).

    Google Scholar 

  82. Shepherd, T. G. et al. Storylines: an alternative approach to representing uncertainty in physical aspects of climate change. Clim. Change 151, 555–571 (2012). Advocates for the usage of a non-quantitative ‘storyline’ approach for analysing very rare or unprecedented event sequences to aid in pinpointing sources of uncertainty and in deepening understanding of climate risks in light of specific decision parameters.

    Google Scholar 

  83. Brönnimann, S., Martius, O., Rohr, C., Bresch, D. N. & Lin, K. E. Historical weather data for climate risk assessment. Ann. NY Acad. Sci. 1436, 121–137 (2019).

    Google Scholar 

  84. Wilby, R. L., Dawson, C. W., Murphy, C., O’Connor, P. & Hawkins, E. The statistical down-scaling model – decision centric (SDSM-DC): conceptual basis and applications. Clim. Res. 61, 259–276 (2014).

    Google Scholar 

  85. Prudhomme, C., Wilby, R. L., Crooks, S., Kay, A. L. & Reynard, N. S. Scenario-neutral approach to climate change impact studies: application to flood risk. J. Hydrol. 390, 198–209 (2010).

    Google Scholar 

  86. Moss, R. H. et al. Hell and high water: practice-relevant adaptation science. Science 342, 696–698 (2013).

    CAS  Google Scholar 

  87. Meadow, A. M. et al. Moving toward the deliberate coproduction of climate science knowledge. Weather Clim. Soc. 7, 179–191 (2015).

    Google Scholar 

  88. Weaver, C. P. et al. From global change science to action with social sciences. Nat. Clim. Change 4, 656–660 (2014).

    Google Scholar 

  89. Sanders, B. F. et al. Collaborative modeling with fine-resolution data enhances flood awareness, minimizes differences in flood perception, and produces actionable flood maps. Earth’s Future 7, e2019ef001391 (2020).

    Google Scholar 

  90. Purdy, A. J. et al. Designing drought indicators. Bull. Amer. Meteorol. Soc. 100, 2327–2342 (2019). Highlights a project to reimagine metrics for the multi-variable hazard of drought through detailed decision-maker engagement and iterative co-production of knowledge.

    Google Scholar 

  91. Thonicke, K. et al. Advancing the understanding of adaptive capacity of socio-ecological systems to absorb climate extremes. Earth’s Future 8, e2019ef001221 (2020).

    Google Scholar 

  92. Beckage, B. et al. Linking models of human behaviour and climate alters projected climate change. Nat. Clim. Change 8, 79–84 (2018).

    Google Scholar 

  93. Burger, M., Wentz, J. & Horton, R. The law and science of climate change attribution. Columbia J. Environ. Law 45, 57–240 (2020).

    Google Scholar 

  94. Norström, A. V. et al. Principles for knowledge co-production in sustainability research. Nat. Sustain. 3, 182–190 (2020).

    Google Scholar 

  95. Hartley, K., Kuecker, G. & Woo, J. J. Practicing public policy in an age of disruption. Policy Design Pract. 2, 163–181 (2019).

    Google Scholar 

  96. Kumar, R. et al. Dominant control of agriculture and irrigation on urban heat island in India. Sci. Rep. 7, 14054 (2017).

    Google Scholar 

  97. Balch, J. K. et al. Switching on the big burn of 2017. Fire 1, 17 (2018). Summarizes the mix of anthropogenic and natural factors that contributed to the severe 2017 Western US fire season and concludes that the combination of physical preconditions with increasing societal exposure call for a well-thought-through set of policy changes.

    Google Scholar 

  98. Marlon, J. R. et al. Long-term perspective on wildfires in the western USA. Proc. Natl Acad. Sci. USA 109, E535–E543 (2017).

    Google Scholar 

  99. Zhong, S. et al. Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China. Atm. Chem. Phys. 17, 5439–5457 (2017).

    CAS  Google Scholar 

  100. Lentz, E. E. et al. Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood. Nat. Clim. Change 6, 696–701 (2016).

    Google Scholar 

  101. Temmerman, S. et al. Ecosystem-based coastal defence in the face of global change. Nature 504, 79–84 (2013).

    CAS  Google Scholar 

  102. Sadegh, M., Ragno, E. & AghaKouchak, A. Multivariate copula analysis toolbox (MvCAT): describing dependence and underlying uncertainty using a Bayesian framework. Water Resour. Res. 53, 5166–5183 (2017).

    Google Scholar 

  103. Donges, J. F., Schleussner, C.-F., Siegmund, J. F. & Donner, R. V. Event coincidence analysis for quantifying statistical interrelationships between event time series. Eur. Phys. J. Special Topics 225, 471–487 (2016).

    Google Scholar 

  104. Boers, N. et al. Complex networks reveal global pattern of extreme-rainfall teleconnections. Nature 566, 373–390 (2019).

    Google Scholar 

  105. Maher, N. et al. The Max Planck Institute Grand Ensemble: enabling the exploration of climate system variability. J. Adv. Model. Earth Syst. 11, 2050–2069 (2019).

    Google Scholar 

  106. Lee, C.-Y., Tippett, M. K., Sobel, A. H. & Camargo, S. J. An environmentally forced tropical cyclone hazard model. J. Adv. Model. Earth Sys. 10, 233–241 (2018).

    Google Scholar 

  107. Emanuel, K. Climate and tropical cyclone activity: a new model downscaling approach. J. Clim. 19, 4797–4802 (2006).

    Google Scholar 

  108. Lemoine, D. & Kapnick, S. A top-down approach to projecting market impacts of climate change. Nat. Clim. Change 6, 51–57 (2016).

    Google Scholar 

  109. Zeff, H. B., Herman, J. D., Reed, P. M. & Characklis, G. W. Cooperative drought adaptation: integrating infrastructure development, conservation, and water transfers into adaptive policy pathways. Water Resour. Res. 52, 7327–7346 (2016).

    Google Scholar 

  110. Rivera, F. I. Cultural mechanisms in the exchange of social support among Puerto Ricans after a natural disaster. Qual. Health Res. 22, 801–809 (2012).

    Google Scholar 

  111. Emanuel, K. Assessing the present and future probability of Hurricane Harvey’s rainfall. Proc. Natl Acad. Sci. USA 114, 12681–12684 (2017).

    CAS  Google Scholar 

  112. Biesbroek, R. et al. Opening up the black box of adaptation decision-making. Nat. Clim. Change 5, 493–494 (2015). Emphasizes that decision-making is properly understood as a messy, iterative process, and that collaboration-building efforts must first recognize the diverse mandates and incentives of all actors involved.

    Google Scholar 

  113. Wong-Parodi, G., Krishnamurti, T., Davis, A., Schwartz, D. & Fischhoff, B. A decision science approach for integrating social science in climate and energy solutions. Nat. Clim. Change 6, 563–570 (2016).

    Google Scholar 

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Acknowledgements

This paper was developed from ideas discussed at a May 2019 workshop at Columbia University, organized by C.R., R.M.H., J.Z., O.M., A.A., S.J.C., M.O., A.C.R., T.W., N. Diffenbaugh, S. I. Seneviratne and A. Sobel (http://extremeweather.columbia.edu/workshop-on-correlated-extremes/). The workshop drew generous support from the U.S. National Science Foundation’s Prediction of and Resilience against Extreme Events (PREEVENTS) program, Aon, the Columbia University Initiative on Extreme Weather and Climate, NOAA’s Consortium for Climate Risk in the Urban Northeast (CCRUN), the World Climate Research Programme’s (WCRP) Grand Challenge on Weather and Climate Extremes, and the European COST Action ‘Understanding and modeling compound climate and weather events’ (DAMOCLES; CA17109). A portion of C.R.’s work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. R.M.H acknowledges support from the NOAA RISA Program (grant no. NA15OAR4310147). J.Z. acknowledges financial support from the Swiss National Science Foundation (Ambizione grant no. 179876). O.M. acknowledges financial support from the Swiss National Science Foundation (grant no. 178751). T.W. acknowledges financial support from the National Science Foundation (grant no. AGS-1929382).

Author information

Authors and Affiliations

  1. Earth-Science Division, Jet Propulsion Laboratory/California Institute of Technology, Pasadena, CA, USA

    Colin Raymond

  2. Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA

    Colin Raymond

  3. Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA

    Radley M. Horton, Suzana J. Camargo & Kai Kornhuber

  4. Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

    Jakob Zscheischler & Olivia Martius

  5. Climate and Environmental Physics, University of Bern, Bern, Switzerland

    Jakob Zscheischler

  6. Mobiliar Lab for Natural Risks, Institute of Geography, University of Bern, Bern, Switzerland

    Olivia Martius

  7. Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA, USA

    Amir AghaKouchak

  8. Department of Earth System Science, University of California, Irvine, Irvine, CA, USA

    Amir AghaKouchak

  9. Earth Lab, CIRES, University of Colorado-Boulder, Boulder, CO, USA

    Jennifer Balch

  10. Department of Geography, University of Colorado-Boulder, Boulder, CO, USA

    Jennifer Balch

  11. Catastrophe Insight Division, Aon, Chicago, IL, USA

    Steven G. Bowen

  12. School of Public Health, University of Washington, Seattle, WA, USA

    Jeremy Hess

  13. School of Medicine, University of Washington, Seattle, WA, USA

    Jeremy Hess

  14. Earth Institute, Columbia University, New York, NY, USA

    Kai Kornhuber

  15. Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ, USA

    Michael Oppenheimer

  16. School of Geosciences, Princeton University, Princeton, NJ, USA

    Michael Oppenheimer

  17. Goddard Institute for Space Studies, National Aeronautics and Space Administration, New York, NY, USA

    Alex C. Ruane

  18. Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USA

    Thomas Wahl

  19. National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL, USA

    Thomas Wahl

  20. United States Army Corps of Engineers, Washington, DC, USA

    Kathleen White

Authors
  1. Colin Raymond
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  2. Radley M. Horton
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  3. Jakob Zscheischler
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  4. Olivia Martius
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  5. Amir AghaKouchak
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  6. Jennifer Balch
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  7. Steven G. Bowen
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  8. Suzana J. Camargo
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  9. Jeremy Hess
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  10. Kai Kornhuber
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  11. Michael Oppenheimer
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  12. Alex C. Ruane
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  13. Thomas Wahl
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  14. Kathleen White
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Contributions

C.R., R.M.H., J.Z. and O.M. developed the initial concept. C.R. created figures and S.G.B. provided data for Fig. 2. C.R. led the writing of the manuscript, and all authors contributed to writing and editing.

Corresponding author

Correspondence to Colin Raymond.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Franziska Gaupp, Silvia Torresan, Gabrielle Wong-Parodi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Raymond, C., Horton, R.M., Zscheischler, J. et al. Understanding and managing connected extreme events. Nat. Clim. Chang. 10, 611–621 (2020). https://doi.org/10.1038/s41558-020-0790-4

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