ClimateChange Assessment Guide.pdf - University of Waterloo

Executive Summaryviiwatering needs may shift earlier in the year and mayrequire more water if drought becomes more frequent.In addition to the Drinking Water Source Protectionprogram and the Permit-to-Take-Water program, severalother water related programs in Ontario are affected byclimate change. These include subwatershed studies,environmental monitoring programs, stormwatermanagement and dam/reservoir management.Hydrologic assessments can also support ecosystemand resource productivity studies in several disciplines(i.e., agriculture, forestry etc.). In all cases climate changecan cause significant changes in hydrology and waterquality that must be recognized as part of adaptivemanagement planning.Global Climate ModelsGCMs are coupled ocean-atmosphere models thatattempt to simulate future climate under alternate GHGforcing scenarios. These tools have evolved since the1970s to their present level of sophistication. Numerousmodelling centres around the world have developedGCMs that are used for long-term simulations (i.e.,250 year) to characterize the evolution of temperature,precipitation, solar radiation, winds and otherparameters well into the future. GCMs produce globalscale output at grid point spacings of 250 to 400 km.Simulations are designed to characterize future climateon an annual, seasonal and monthly basis at relativelycoarse spatial scales. GCMs do not simulate small scalestorms (i.e., thunderstorms) and therefore cannot reflectextreme events at the local scale.Greenhouse Gas Emission ScenariosA standard set of GHG emission scenarios have beendeveloped by the IPCC. These scenarios representfuture storylines based on alternative directionsfor humanity in terms of economies, technology,demographics and governance. Each scenario resultsin a different rate and timing of GHG emissions that,in turn, are developed into GHG concentrations thatdrive the GCMs to simulate a unique future climate.The different GCMs forced by alternate GHG emissionscenarios results in a large number of possible futureclimates. Since each future climate is considered equallyplausible, the IPCC recommends that climate changeimpact assessments use as many of these scenarios aspossible.Developing Future Local Climates as Input toModelling AssessmentsFuture local climates must be developed to be used asinput to hydrologic models for climate change impactassessments. Currently, all climate scenario-generatingapproaches rely upon the GCM simulations.The most established methodology for estimatingfuture local climates uses the GCM simulations toestimate annual, seasonal or monthly changes for eachclimate variable for a future time period relative to abaseline climate period. These relative changes, termedchange fields, are used to adjust the observed climatestation data time series to reflect future conditions.This approach results in an altered input climate timeseries that reflects the average relative change in eachparameter and, through the use of local observations,the local climate. The change field method is a simpleapproach to develop future local climates that reflectlarge scale average features and allows the use of allGCM and GHG emission scenarios. It is also importantto recognize the limitations of this approach; it doesnot alter the sequence of wet and dry days nor does italter the patterns of intense precipitation events. GCMslack the local scale parameterization and feedback fromlocally significant features (i.e., topography and surfacewater) to reflect local scale conditions directly in modeloutput.Climate downscaling methods have been developedto reflect local conditions and address climatevariability. Two different approaches include statisticaldownscaling and dynamical downscaling. Statisticaldownscaling methods can be further divided intoregression type models and weather generators.Statistical regression models are conceptually simpleapproaches to climate scenario generation. Resolvedatmospheric conditions at the GCM scale are linkedto climatic features or parameters at the local scalethrough statistical relationships. These tools rely uponpredictors selected from large scale (i.e., GCMs) climatemodelling output (e.g., upper atmosphere water-vapourcontent, barometric pressure or geopotential thickness).Predictors must be selected for the strength of theirinfluence on important local scale predictands, such asair temperature, precipitation, wind speed and radiation,as required in hydrologic modelling. The assumption ofstationarity, that these relationships will hold true into