Abstract
In this review, we provide guidance on the construction of climate scenarios for stress tests—scenarios that represent disruptive climatic events and can be used to assess the impacts of climate and weather risks at the level of detail that is necessary to identify specific adaptation actions or strategies. While there is a wealth of guidance on scenario-based climate adaptation planning, this guidance typically assumes the selection and use of decadal to century-long time segments of downscaled climate model projections, rather than the creation of a customized scenario depicting a specific extreme event. We address this gap by synthesizing a variety of data sources and analytical techniques for constructing climate scenarios for stress tests that are customized to address specific end-users’ needs. We then illustrate the development and application of climate scenarios with a case study that explores water sustainability under changing climate in the Truckee and Carson River basins of California and Nevada. Finally, we assess the potential advantages and disadvantages of the different data sources and analytical techniques described to provide guidance on which are best suited for an intended application based on the system of study, the stakeholders involved, and the resources available. Ultimately, this work is intended to provide the building blocks with which scientist-stakeholder teams can produce their own stress test scenarios to explore place-based weather and climate risks.
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References
Abatzoglou JT, Brown TJ (2012) A comparison of statistical downscaling methods suited for wildfire applications. Int J Climatol 32:772–780. https://doi.org/10.1002/joc.2312
Albano CM, Dettinger MD, McCarthy MI et al (2016) Application of an extreme winter storm scenario to identify vulnerabilities, mitigation options, and science needs in the Sierra Nevada mountains, USA. Nat Hazards 80:879–900. https://doi.org/10.1007/s11069-015-2003-4
Alexander D (2000) Scenario methodology for teaching principles of emergency management. Disaster Prev Manag An Int J 9:89–97
Amoroso M, Daniels L, Baker P, Camarero J (2017) Dendroecology:tree-ring analyses applied to ecological studies. Springer, Berlin Heidelberg
Anandhi A, Frei A, Pierson DC et al (2011) Examination of change factor methodologies for climate change impact assessment. Water Resour Res 47:1–11. https://doi.org/10.1029/2010WR009104
Ballesteros-Canovas JA, Stoffel M, St George S, Hirschboeck K (2015) A review of flood records from tree rings. Prog Phys Geogr 39. https://doi.org/10.1177/0309133315608758
Boyer WO (2018) A dynamic decision support system for drought resiliency and climate change. University of Nevada, Thesis
Breinl K, Di Baldassarre G, Girons Lopez M et al (2017) Can weather generation capture precipitation patterns across different climates, spatial scales and under data scarcity? Sci Rep 7:5449. https://doi.org/10.1038/s41598-017-05822-y
Brewer GD (2007) Inventing the future: scenarios, imagination, mastery and control. Sustain Sci 2:159–177. https://doi.org/10.1007/s11625-007-0028-7
Brown C, Ghile Y, Laverty M, Li K (2012) Decision scaling: linking bottom-up vulnerability analysis with climate projections in the water sector. Water Resour Res 48:1–12. https://doi.org/10.1029/2011WR011212
Brown C, Wilby RL (2012) An alternate approach to assessing climate risks. EOS Trans Am Geophys Union 93:401–412. https://doi.org/10.1029/2012EO410001
Bryant BP, Lempert RJ (2010) Thinking inside the box: a participatory, computer-assisted approach to scenario discovery. Technol Forecast Soc Change 77:34–49. https://doi.org/10.1016/j.techfore.2009.08.002
Bureau of Reclamation (2015) Truckee basin study. Basin study report. https://www.usbr.gov/watersmart/bsp/docs/finalreport/truckee/tbsbasinstudy.pdf
Chatfield C (2004) The analysis of time series: an introduction, 6th edn. Chapman and Hall/CRC Texts in Statistical Science Ser
Chen J, Brissette FP (2014) Stochastic generation of daily precipitation amounts: review and evaluation of different models. Clim Res 59:189–206. https://doi.org/10.3354/cr01214
Chen J, Brissette FP, Leconte R (2010) A daily stochastic weather generator for preserving low-frequency of climate variability. J Hydrol 388:480–490. https://doi.org/10.1016/j.jhydrol.2010.05.032
Committee on Homeland Security and Governmental Affairs (2006) Hurricane Katrina: a nation still unprepared. Special Report of the Committee on Homeland Security and Governmental Affairs, S. Rept. 109–322
Cook ER, Krusic P (2004) North American summer PDSI reconstructions. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2004-045. NOAA/NGDC paleoclimatology program. https://www.ncdc.noaa.gov/data-access/paleoclimatology-data
Daly C, Halbleib M, Smith JI et al (2008) Physiographically-sensitive mapping of temperature and precipitation across the conterminous United States. Int J Climatol 28:2031–2064
DeLong J (2015) The drought is relentless ; here’s what it’s affecting. Reno Gaz. Journal. https//www.rgj.com/story/news/2015/06/17/heres-how-the-drought-is-affecting-your-life/28882073/
Department of Homeland Security (2013) Homeland Security Exercise and Evaluation Program (HSEEP). https://preptoolkit.fema.gov/documents/1269813/1269861/HSEEP_Revision_Apr1
Dessai S, Hulme M (2004) Does climate adaptation policy need probabilities? Clim Policy 4:107–128. https://doi.org/10.1080/14693062.2004.9685515
Dettinger MD, Martin Ralph F, Hughes M et al (2012) Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California. Nat Hazards 60:1085–1111. https://doi.org/10.1007/s11069-011-9894-5
Dettinger MD, Sterle K, Simpson K et al (2017) Climate scenarios for the Truckee-Carson River System. University of Nevada Cooperative Extension Special Publication 17-05
Dilling L, Lemos MC (2011) Creating usable science: opportunities and constraints for climate knowledge use and their implications for science policy. Glob Environ Chang 21:680–689. https://doi.org/10.1016/j.gloenvcha.2010.11.006
Dominguez F, Dall’Erba S, Huang S et al (2018) Tracking an atmospheric river in a warmer climate: from water vapor to economic impacts. Earth Syst Dyn 9:249–266. https://doi.org/10.5194/esd-9-249-2018
Fatichi S, Ivanov VY, Caporali E (2011) Simulation of future climate scenarios with a weather generator. Adv Water Resour 34:448–467. https://doi.org/10.1016/j.advwatres.2010.12.013
Ford JD, Keskitalo ECH, Smith T et al (2010) Case study and analogue methodologies in climate change vulnerability research. Wiley Interdiscip Rev Clim Chang 1:374–392. https://doi.org/10.1002/wcc.48
Gangopadhyay S, Harding BL, Rajagopalan B et al (2009) A nonparametric approach for paleohydrologic reconstruction of annual streamflow ensembles. Water Resour Res 45:1–14. https://doi.org/10.1029/2008WR007201
Gangopadhyay S, Mccabe GJ, Woodhouse CA (2015) Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach. Water Resour Res 51:9763–9774. https://doi.org/10.1002/2014WR016259
Garb Y, Pulver S, Vandeveer SD (2008) Scenarios in society, society in scenarios : toward a social scientific analysis of storyline-driven environmental modeling. Environ Res Lett 3:045015. https://doi.org/10.1088/1748-9326/3/4/045015
Ghil M, Allen MR, Dettinger MD et al (2002) Advanceed spectral methods for climatic time series. Rev Geophys:40. https://doi.org/10.1029/2000RG000092
Groves DG, Lempert RJ (2007) A new analytic method for finding policy-relevant scenarios. Glob Environ Chang 17:73–85. https://doi.org/10.1016/j.gloenvcha.2006.11.006
Harbaugh A (2005) MODFLOW-2005, The U.S. Geological Survey modular ground-water model—the ground-water flow process. U.S. Geological Survey techniques and methods 6-A16. 253 p
Hazeleger W, Van Den Hurk BJJM, Min E et al (2015) Tales of future weather. Nat Clim Chang 5:107–113. https://doi.org/10.1038/nclimate2450
Huntington J, McEvoy D (2011) Climatological estimates of open water evaporation from selected Truckee and Carson River basin water bodies, California and Nevada. Desert Research Institute. Publication No. 41254
Intergovernmental Panel on Climate Change (IPCC) (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. Special Report of the Intergovernmental Panel on Climate Change. https://www.ipcc.ch/report/managing-the-risks-of-extreme-events-and-disasters-to-advance-climate-change-adaptation/
Karl T, Nicholls N, Ghazi A (1999) CLIVAR/GCOS/WMO workshop on indices and indicators for climate extremes. Clim Chang 42:3–7
Kawase H, Yoshikane T, Hara M et al (2009) Intermodel variability of future changes in the Baiu rainband estimated by the pseudo global warming downscaling method. J Geophys Res 114:1–14. https://doi.org/10.1029/2009JD011803
Kirsch BR, Characklis GW, Zeff HB (2013) Evaluating the impact of alternative hydro-climate scenarios on transfer agreements: practical improvement for generating synthetic streamflows. J Water Resour Plan Manag 139:396–406. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000287
Lemos MC, Kirchhoff CJ, Ramprasad V (2012) Narrowing the climate information usability gap. Nat Clim Chang 2:789
Lempert R (2013) Scenarios that illuminate vulnerabilities and robust responses. Clim Chang 117:627–646. https://doi.org/10.1007/s10584-012-0574-6
Lempert RJ, Popper SW, Bankes SC (2003) Shaping the next one hundred years: new methods for quantitative, long-term policy analysis. RAND, Santa Monica, CA
Livneh B, Rosenberg EA, Lin C et al (2013) A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: update and extensions. J Clim 26:9384–9392. https://doi.org/10.1175/JCLI-D-12-00508.1
Mahmoud M, Liu Y, Hartmann H et al (2009) A formal framework for scenario development in support of environmental decision-making. Environ Model Softw 24:798–808. https://doi.org/10.1016/j.envsoft.2008.11.010
Mahmoud MI, Gupta HV, Rajagopal S (2011) Scenario development for water resources planning and watershed management: methodology and semi-arid region case study. Environ Model Softw 26:873–885. https://doi.org/10.1016/j.envsoft.2011.02.003
Mahoney K, Swales D, Mueller MJ et al (2018) An examination of an inland-penetrating atmospheric river flood event under potential future thermodynamic conditions. J Clim 31:6281–6297. https://doi.org/10.1175/JCLI-D-18-0118.1
Maraun D, Shepherd TG, Widmann M et al (2017) Towards process-informed bias correction of climate change simulations. Nat Clim Chang 7:764–773. https://doi.org/10.1038/nclimate3418
Markstrom SL, Niswonger RG, Regan RS et al (2008) GSFLOW-coupled ground-water and surface-water flow model based on the integration of the precipitation-runoff modeling system (PRMS) and the modular ground-water flow model (MODFLOW-2005). U.S. Geological Survey techniques and methods 6-D1
Marx SM, Weber EU, Orlove BS et al (2007) Communication and mental processes: experiential and analytic processing of uncertain climate information. Glob Environ Chang 17:47–58. https://doi.org/10.1016/j.gloenvcha.2006.10.004
Mckenzie E, Rosenthal A, Bernhardt J et al (2012) Developing scenarios to assess ecosystem service tradeoffs : guidance and case studies for InVEST users. World Wildlife Fund, Washington D.C
Mearns LOO, Hulme M, Carter TR et al (2001) Climate scenario development. In: Houghton J, Ding Y, Griggs D et al (eds) Climate change 2001: the scientific basis, contribution of working group 1 to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 739–768
Meko D, Graybill DA (1995) Tree-ring reconstruction of upper Gila River discharge. Water Resour Bull 31:605–616. https://doi.org/10.1111/j.1752-1688.1995.tb03388.x
Miller BW, Symstad AJ, Frid L et al (2017) Co-producing simulation models to inform resource management: a case study from southwest South Dakota. Ecosphere 8. https://doi.org/10.1002/ecs2.2020
Mote PW, Brekke LD, Duffy PB, Maurer EP (2011) Guidelines for constructing climate scenarios. EOS Trans Am Geophys Union 92:2010–2012
National Research Council (2013) Climate and social stress: implications for security analysis. The National Academies Press, Washington D.C
Norton-Smith K, Lynn K, Chief K et al (2016) Climate change and indigenous peoples : a synthesis of current impacts and experiences. Gen. Tech. Rep. PNW-GTR-944, Department of Agriculture, Forest Service, Pacific Northwest Research Station. 1–142
Pierce DW, Cayan DR, Thrasher BL (2014) Statistical downscaling using localized constructed analogs (LOCA). J Hydrometeorol 15:2558–2585. https://doi.org/10.1175/JHM-D-14-0082.1
Rowland E, Cross M, Hartmann H (2014) Considering multiple futures : scenario planning to address uncertainty in natural resource conservation. U.S. Fish and Wildlife Service, Washington D.C.
Runyon AN, Carlson AR, Gross J et al (2020) Repeatable approaches to work with scientific uncertainty and advance climate change adaptation in US national parks. Park Steward Forum 36. https://doi.org/10.5070/p536146402
Sauchyn D, Ilich N (2017) Nine hundred years of weekly streamflows: stochastic downscaling of ensemble tree-ring reconstructions. Water Resour Res 53:9266–9283. https://doi.org/10.1002/2017WR021585
Schwarz A, Ray P, Wi S et al (2018) Climate change risk faced by the California Central Valley water resource system. California’s fourth climate change assessment. Publication number:CCCA4-EXT-2018-001
Seager R, Cane M, Henderson N et al (2019) Strengthening tropical Pacific zonal sea surface temperature gradient consistent with rising greenhouse gases. Nat Clim Chang 9:517–522. https://doi.org/10.1038/s41558-019-0505-x
Shepherd TG, Boyd E, Calel RA et al (2018) Storylines: an alternative approach to representing uncertainty in physical aspects of climate change. Clim Chang:555–571. https://doi.org/10.1007/s10584-018-2317-9
Singletary L, Sterle K (2017) Collaborative modeling to assess drought resiliency of snow-fed river dependent communities in the Western United States: a case study in the Truckee-Carson river system. Water (Switzerland) 9:1–19. https://doi.org/10.3390/w9020099
Singletary L, Sterle K, Simpson K (2016) Assessing and enhancing the climate resiliency and adaptive capacity of the Truckee-Carson River System: results of a survey of local organizations. Spec Publ 16-03:1–48
Skamarock WC, Klemp JB, Dudhia J et al (2008) Description of the advanced research WRF version 3. CAR Technical Note, NCAR/TN-475+STR
Snover AK, Mantua NJ, Littell JS et al (2013) Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions. Conserv Biol 27:1147–1157. https://doi.org/10.1111/cobi.12163
Sofaer HR, Barsugli JJ, Jarnevich CS et al (2017) Designing ecological climate change impact assessments to reflect key climatic drivers. Glob Chang Biol 23:2537–2553. https://doi.org/10.1111/gcb.13653
Sorooshian S, Martinson DG (1995) Proxy indicators of climate: an essay. In: Natural climate variability on decade-to-century time scales. The National Academies Press, Washington D.C., pp 489–494
Star J, Rowland EL, Black ME et al (2016) Supporting adaptation decisions through scenario planning: enabling the effective use of multiple methods. Clim Risk Manag 13:88–94. https://doi.org/10.1016/j.crm.2016.08.001
Sterle K, Jose L, Coors S et al (2020a) Collaboratively modeling reservoir reoperation to adapt to earlier snowmelt runoff. J Water Resour Plan Manag 146. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001136
Sterle K, Singletary L (2017) Adapting to variable water supply in the Truckee-Carson River System : results of focus groups conducted in 2016 with local water managers. Univ Nevada Coop Ext Spec Publ 17-15
Sterle K, Singletary L, Lee G et al (2020b) Water sustainability and climate in the Truckee-Carson River System , western United States 10 key takeaways from the Water for the Seasons collaborative research program. University of Nevada, Reno Extension Special Publication SP-20-02
Stern PC, Ebi KL, Leichenko R et al (2013) Managing risk with climate vulnerability science. Nat Clim Chang 3:607–609. https://doi.org/10.1038/nclimate1929
Stoner AMK, Hayhoe K, Wuebbles DJ (2013) An asynchronous regional regression model for statistical downscaling of daily climate variables. Int J Climatol 33:2473–2494. https://doi.org/10.1002/joc.3603
Swain DL, Langenbrunner B, Neelin JD, Hall A (2018) Increasing precipitation volatility in twenty-first-century California. Nat Clim Chang 8:427–433. https://doi.org/10.1038/s41558-018-0140-y
Symstad AJ, Fisichelli NA, Miller BW et al (2017) Multiple methods for multiple futures: integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making. Clim Risk Manag 17:78–91. https://doi.org/10.1016/j.crm.2017.07.002
Tariq A, Lempert RJ, Riverson J et al (2017) A climate stress test of Los Angeles’ water quality plans. Clim Chang 144:625–639. https://doi.org/10.1007/s10584-017-2062-5
Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498
Ullrich PA, Xu Z, Rhoades AM et al (2018) California’s drought of the future: a midcentury recreation of the exceptional conditions of 2012–2017. Earth’s Futur 6:1568–1587. https://doi.org/10.1029/2018EF001007
Van Der Merwe L (2008) Scenario-based strategy in practice: a framework. Adv Dev Hum Resour 10:216–239. https://doi.org/10.1177/1523422307313321
Van Der Wiel K, Selten FM, Bintanja R et al (2020) Ensemble climate-impact modelling: extreme impacts from moderate meteorological conditions. Environ Res Lett 15. https://doi.org/10.1088/1748-9326/ab7668
Vano JA, Kim JB, Rupp DE, Mote PW (2015) Selecting climate change scenarios using impact-relevant sensitivities. Geophys Res Lett 42:5516–5525. https://doi.org/10.1002/2015GL063208
Vasileiadou E, Botzen WJW (2014) Communicating adaptation with emotions: the role of intense experiences in raising concern about extreme weather. Ecol Soc 19. https://doi.org/10.5751/ES-06474-190236
Weaver CP, Lempert RJ, Brown C et al (2013) Improving the contribution of climate model information to decision making: the value and demands of robust decision frameworks. Wiley Interdiscip Rev Clim Chang 4:39–60. https://doi.org/10.1002/wcc.202
Weaver CP, Moss RH, Ebi KL et al (2017) Reframing climate change assessments around risk: recommendations for the U.S. National Climate Assessment. Environ Res Lett 12:
Werner AT, Cannon AJ (2016) Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods. Hydrol Earth Syst Sci 20:1483–1508. https://doi.org/10.5194/hess-20-1483-2016
Whateley S, Walker JD, Brown C (2015) A web-based screening model for climate risk to water supply systems in the northeastern United States. Environ Model Softw 73:64–75. https://doi.org/10.1016/j.envsoft.2015.08.001
Wilks DS, Wilby RL (1999) The weather generation game: a review of stochastic weather models. Prog Phys Geogr 23:329–357. https://doi.org/10.1191/030913399666525256
Wilsey CB, Lawler JJ, Maurer EP et al (2013) Tools for assessing climate impacts on fish and wildlife. J Fish Wildl Manag 4:220–240. https://doi.org/10.3996/062012-JFWM-055
Woodhouse CA, Lukas JJ (2006) Multi-century tree-ring reconstructions of Colorado streamflow for water resource planning. Clim Chang 78:293–315. https://doi.org/10.1007/s10584-006-9055-0
Acknowledgments
This work could not have been accomplished without conversation and insights from Dale Cox (U.S. Geological Survey) and Michael Anderson (California Division of Water Resources) and the contributions from the Stakeholder Advisory Group and research team members of the Water for the Seasons project. We also wish to thank Katherine Hepworth, Erin Delapena Lucas, Shelby Hockaday, Trina Kleist, and Sudhiti Naskar for graphic design support and two anonymous reviewers for feedback that helped to improve this manuscript.
Funding
This material is based upon work supported by the Science Applications for Risk Reduction (SAFRR) program in the U.S. Geological Survey’s Natural Hazards Mission Area under Grant Nos. G16AC00304 and G18-00405 and through a Water Sustainability and Climate program grant from the National Science Foundation and the U.S. Department of Agriculture (#1360505/1360506).
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Albano, C.M., McCarthy, M.I., Dettinger, M.D. et al. Techniques for constructing climate scenarios for stress test applications. Climatic Change 164, 33 (2021). https://doi.org/10.1007/s10584-021-02985-6
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DOI: https://doi.org/10.1007/s10584-021-02985-6