ClimateChange Assessment Guide.pdf - University of Waterloo

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Guide for Assessment of Hydrologic Effects of Climate Change in Ontarioviiithe future with climate change, is crucial to the validityof this approach. Changes in the variability of weatherin the future and weather extremes are addressed bythis method. Predictors generated by GCMs for futuretime periods reflect future climate variability and thusinfluence the variability of the predictands through theregressions. Guidance is provided on acquiring andapplying the Statistical Downscaling Model (SDSM) togenerate future climates that incorporate changes inclimate variability.Weather generators are statistically-based climatemodels that replicate the statistical attributes (i.e.,mean and variance) of local observed climate variables(Christensen et al., 2007a; Wilby et al., 2004). Weathergenerators do not replicate observed sequences ofevents; they simulate the sequence of wet and dryweather events and the transition from one to another(de Loë and Berg, 2006). Often secondary variables suchas air temperature and solar radiation are modelledconditionally on precipitation conditions, especially thepresence or absence of rain. Since weather generatorsrely on climate statistics, long observation records arerequired to develop robust scenarios. Variability ofclimate is addressed with this method as GCM simulatedfuture climate variance can be incorporated in the futureweather model formulation. The weather generatorLARS-WG is discussed in the Guide with information onacquiring and applying the model.Dynamical downscaling using regional climate models(RCMs) is one of the most promising methods fordownscaling GCM output. RCMs are physically based3-D models capable of representing important physicalfeatures (i.e., topography and water bodies) and climaticprocesses such as the formation of convective stormsand soil moisture storage over small portions of theglobe. RCMs are typically nested within GCMs anduse one-way boundary conditions such as sea-surfacetemperatures and atmospheric circulation patterns fromthe GCMs to drive them (de Loë and Berg, 2006). RCMssimulate smaller scale physical processes involvingthe use of interactive land-surface models. Output isavailable at finer resolution than from GCMs, typicallyin the range of 40 to 50 km spacing; thus, an orderof magnitude more spatially detailed than the GCMsoutput. Because of the smaller scale of the modeldomain, RCMs can simulate individual storms (notsmaller convective events such as thunderstorms) and,therefore, can be used to examine the occurrence offuture storms and extreme events.The following table describes these approaches forgenerating future climates and lists their relativeadvantages and disadvantages.Summary GCM-change field and downscaled climates for use in climate change impact assessmentsTechnique Description Advantages DisadvantagesGCM-change fieldSummary GCM continued next page• Simulated climate at coarsegrid spacing• Use to develop monthly(seasonal or other) changefields• Provides data used instatistical downscaling• Wide variety of GCMsavailable• Several GCMs have beenapplied to long-termsimulations for family ofemission scenarios• Comprehensive physicallybased tools• Several variables available• Good agreement acrossGCMs on temperaturechange• Coarse spatial resolution,unrepresentative of localclimate• Extreme events generallyoccur at a smaller scale thanGCM scales, not represented• Modest agreement acrossGCMs on precipitation• Cannot be used to changeclimate variability
Executive SummaryixSummary GCM continuedTechnique Description Advantages DisadvantagesStatistical Downscalingwith RegressionWeather GeneratorsRegional Climate Models• Climates based uponstatistical relationshipsbetween climate variablesand atmospheric predictors• Weather data generatedbased on statistical attributesof local climate and GCMvariables• Higher resolution physicallybased models oftenembedded in GCMs• Local physiography andwater bodies are included• High spatial and temporalresolution if observationaldata available• Several variables available• Ease of application, thusmany long-term scenarioscan be tested• Good skill demonstrated atsimulating temperature• High spatial and temporalresolution if observationaldata available• Several variables available• Ease of application, thusmany long-term scenarioscan be tested• Good skill demonstrated atsimulating temperature• Good skill at simulatingperiods of drought andextended precipitation• High spatial and temporalresolution output for severalvariables• Improved extreme eventsimulation over GCMs• Physically based andconsistent with GCMs• May account for feedbackfrom anthropogenic ornatural systems• Assumes empiricalrelationships will hold asclimates change• May perpetuate GCM biases• Generally underestimatesextremes• Some models do notsimulated monthly variabilitywell• Poor skill in simulatingprecipitation extremes• Neighbouring stations notcorrelated• Observational data to buildstatistical relationships notavailable in all areas• Assumes empiricalrelationships will hold asclimates change• May perpetuate GCM biases• Generally underestimatesextremes• Some models do notsimulated monthly variabilitywell• Poor skill in simulatingprecipitation extremes• Neighbouring stations notcorrelated• Observational data notavailable in all areas• Few model runs and GHGemission scenarios available• May perpetuate GCM biases• Complex model systemsprecludes non-expert use• Simulation periods aretypically short, thus fewerextremes are representedCritical Hydrologic ProcessesThe Guide discusses critical hydrologic processes andthe influence of climate variables on the function ofthese processes. Evapotranspiration, winter conditions(i.e., snow cover, frozen ground), groundwater recharge,and streamflow are discussed with respect to theirsensitivity to climate change. Recommendations aremade with respect to the selection of appropriateclimate sensitive hydrologic formulations. SeveralOntario-based studies of the impact of climate changein hydrologic systems are highlighted with respect totheir methods and conclusions.Climate Change Impact AssessmentThe final chapter in the Guide provides a step-by-stepprocedure for conducting a hydrologic climate changeimpact assessment. A Step-by-Step Guide to HydrologicAssessment Incorporating Climate Change, presented in
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Appendix A A-1Watershed and Receivi
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Appendix A A-3Watershed and Receivi
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Appendix B B-1GCM Modelling GroupsT
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Appendix CGCM-Based Change FieldAss
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C-2Guide for Assessment of Hydrolog
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C-10Guide for Assessment of Hydrolo
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Appendix DRCM and GCM Data Conversi
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D-2Guide for Assessment of Hydrolog
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Appendix E E-1Subwatershed 19 Case
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