ClimateChange Assessment Guide.pdf - University of Waterloo

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Guide for Assessment of Hydrologic Effects of Climate Change in Ontario66A list of all 57 candidate GCMs and associated GHGemission scenarios is provided in Appendix C.Since the focus of this application is to understandthe impacts of climate change on hydrology andimplications for water resources management, thecriteria for further screening were based on climatedrivers important to hydrology, namely temperature andprecipitation. The climate scenarios were subsequentlyused in a hydrologic model (HSP-F) in a simplified formand for a subwatershed in the Credit River Watershed.These future climate simulations illustrated the potentialrange of outcomes obtained from applying varyingnumbers of climate scenarios and provided insight intothe “reasonable” number of scenarios to use for climatechange hydrologic impact assessments.The proposed approaches for short-listing climatechange scenarios address the shortcomings found inhydrologic impact assessments that were completedusing only two climate change scenarios, amongpotentially many, due to resource limitations. In theseassessments, the two climate change scenarios gavewidely divergent outcomes (e.g., one an increase inrunoff and the other a decrease in runoff), that limitedthe usefulness of the assessment results for planning anddecision making (see Section 5.1).Guidance:Use a scatter plot of temperature change andprecipitation change (annual at minimum) todisplay, understand and communicate the rangeof potential changes in future climates.A scatter plot is a valuable tool in presenting therange of future climates from GCM-GHG runs andcommunicating this information in conjunction withthe climate change impact assessment results. Figure6.3, the scatter plot of GCM-based mean annualtemperature change versus mean annual precipitationchange, presents the full suite of candidate futureclimates and identifies those that were selected usingthe two screening approaches, which are discussed inthe following subsections.6.4.3.1 Scatter Plot Method - ‘Bounding theUncertainty’The intent of the scatter plot method is to ‘bound theuncertainty’ that is, to select four future climates thatreflect the extreme range of changes projected fortemperature and precipitation conditions. In doing so,the hydrological assessment should also “capture”these extreme future conditions and provide a range ofconditions for planning and decision making with theeffort of using only four scenarios.Four future climates were selected by identifying theGCM runs that were in the extreme four corners of ascatter plot where the mean annual temperature changewas plotted versus the mean annual precipitationchange (Figure 6.3). In this case, the future climates aredefined by four different GCMs and two GHG emissionscenarios (Table 6.3). It is recommended that at leasttwo different GCMs be used when using this approach.These four scenarios were modelled using HSP-F whichwas setup to model three hydrologic response units.The hydrologic response units are unit areas of typicalsurficial soils in Ontario with vegetated surface cover andmodest slopes (i.e., sand, silt and clay areas with varyingland cover).Table 6‐3 Scenarios from the Scatter Plot MethodIDIPCCAssessmentModelGHGEmissionScenario11 AR4 CNRMCM3 SR-B150 AR4 HADCM3 SR-A1B29 AR4 INMCM3.0 SR-B131 AR4 IPSLCM4 SR-A1B6.4.3.2 Percentiles MethodThe objective of the Percentile Method is to provide astatistically-based, reproducible method of selectingGCM – GHG scenarios to provide a broader rangeof future climates for the climate change impactassessment process. The temperature component ofthe selection process relates to the potential impacts onevapotranspiration while the precipitation componentrelates to potential impacts on runoff.
Climate Change Assessment67The mean annual temperature change fields and themean annual precipitation change fields were calculated,as shown in Table 6.4, for each of the 57 climatescenarios. Each scenario was ranked in ascending orderbased on their mean annual temperature change field(left) and mean annual precipitation change field (right).A percentile was assigned to each climate scenario,representing the order of the scenario divided by thetotal number of scenarios (i.e., 1/57, 2/57, 3/57, etc. forthe first three scenarios). For this analysis, the 90th, 75th,50th, 25th, and 10th percentiles (i.e., rank) for both themean annual temperature change fields and the meanannual precipitation change fields were selected andare shown in bold on Table 6.4. However, based on theanalysis of results (Section 6.4.3.3), the 95th and 5thpercentiles are recommended for the Percentile Method,rather than the 90th and 10th. See Section 6.4.3.3 and6.4.3.4 for more information.Five climate scenarios were selected for their range inmean annual temperature change (Table 6.5) and five fortheir range in mean annual precipitation change (Table6.6). Two future climates were selected under both atemperature and precipitation percentile scenario (i.e.,MIROC3.2 medres - SR-A2 (ID 35) and NCARCCSM3 -SR-A2 (ID 53)). As a result there were eight unique futureclimates (see Figure 6.3). These eight future climateswere modelled with HSP-F on generic hydrologicresponse units.Table 6.4 Climate scenarios and rank of mean annual change in temperature and precipitation for thePercentile MethodIDClimate Scenario42 CSIROMk3 - SR-B1Mean AnnualTemperatureChange (ºC)Percentile (%) ID Climate Scenario1.29 2 28 INMCM3.0 - SR-A1BMean AnnualPrecipitation Percentile (%)Change (%)-6.14 224 GISSE-R - SR-B1 1.38 4 27 INMCM3.0 - SR- -6.00 4A216 FGOALS-g1.0 -SR-B11.67 5 30 IPSLCM4 - SR-A2 -5.44 539 MRI CGCM2.3.2a- SR-B156 NCARPCM - SR-A221 GISSAOM - SR-B157 NCARPCM - SR-A1B11 CNRMCM3 - SR-B114 ECHAM5OM -SR-B11.79 7 31 IPSLCM4 - SR--3.00 7A1B1.85 9 45 ECHO-G - SR-B1 -2.97 91.87 11 35 MIROC3.2-1.97 11medres - SR-A21.92 12 32 IPSLCM4 - SR-B1 -1.62 121.96 14 29 INMCM3.0 - SR-B12.01 16 34 MIROC3.2 hires -SR-B1-1.48 14-0.74 1623 GISSE-R - SR-A2 2.06 18 43 ECHO-G - SR-A2 -0.38 183 BCM2.0 - SR-B1 2.11 19 52 MIROC3.20.16 19medres - SR-A1B41 CSIROMk3 - SR- 2.13 21 55 NCARCCSM3 - 1.33 21A1BSR-B137 MRI CGCM2.3.2a 2.14 23 51 HADCM3 - SR-B1 1.75 23- SR-A222 GISSE-H - SR-A1B 2.21 24 41 CSIROMk3 - SR-A1B1.77 24Table 6.4 continued on next page
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Guide for Assessment of HydrologicE
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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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Appendix DRCM and GCM Data Conversi
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Appendix E E-1Subwatershed 19 Case
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