ClimateChange Assessment Guide.pdf - University of Waterloo

Guide for Assessment of Hydrologic Effects of Climate Change in Ontario78• GCM-based change fields;• Statistically downscaling climate data;• Downscaling with a weather generator tool; and• Dynamical downscaling using RCM scenario output.The GCM based change field method allows for theinvestigation of multiple scenarios from the availablesuite of future climate scenarios. By analyzing manyscenarios, an understanding of uncertainty emerges asdoes a basis for identifying prevailing trends common toall or most of the scenarios. By identifying these trends,modellers are able to extract the most valuable andconsistent information regarding future direction andthe influence of climate change on their study areas. TheGCM based change field method is therefore the mostvaluable method proposed for climate change impactassessments.The GCM based change field method has shortcomings;in particular, the inability of the change field method toaddress future climate variability, especially in terms ofprecipitation. To gain some understanding of climatevariability, the inclusion of downscaling methods are alsoproposed. The three downscaling methods incorporatefuture climate variability while reflecting local conditions.It is not possible, at this time, to develop largenumbers of downscaled climates based on differentGCM scenarios due to the limited availability of highresolution future climate data. Downscaled climatesare, therefore, best used to examine potential climatevariability; whereas, the GCM change field climates areused to identify common responses and trends.For climate change impact assessments using bothGCM-based and statistical downscaling methods todevelop climate change scenarios, the results of thedownscaling climate runs should be compared withGCM scenarios with the same emission and modelorigin. If the downscaling climate scenario does notcorrespond to an existing GCM-based change fieldscenario (i.e., those selected using the PercentileMethod), then the corresponding GCM change fieldscenario should also be assessed. The output from thedownscaled climates should not be lumped with theGCM scenario change field output as this would biasthe collective result towards the emission scenarios andGCMs common to both methods.Guidance:For comprehensive hydrologic investigations,it is recommended that in addition to the GCMchange field scenarios selected using thePercentile Method (Section 6.4), that downscalingbe conducted using three methods, namely astatistical method, a weather generator and onebased upon RCM output. This combination ofapproaches will provide the best examination ofprevailing trends and variability in outcomes.Guidance:If statistical downscaling is going to be used, thecomparable GCM-based change field scenarioshould also be assessed.Considering the currently available downscalinginformation at daily time steps or better on EnvironmentCanada websites, only three SRES scenarios arerepresented, namely, A1B, A2 and B2. The maximumnumber of scenarios available for processing is two RCMoutputs and four statistical downscaling scenarios.The following sections outline the steps to acquire andapply climate change information in water resourceassessments using each of four methods discussedabove.6.5.2 GCM Change FieldsGCM outputs are not of sufficient resolution or reliabilityto be input directly to hydrological models to representa changed climate. Instead, a climate change scenariois developed by applying a change field based on GCMoutput to the climatological baseline data. GCM changefields represent both the easiest method to representfuture climates and the best method to establish awide base of scenarios covering the full spectrum ofGCMs and emission scenarios. These change fields arecalculated based on the difference or ratio betweenaverages for the 2020s (2011-2040), 2050s (2041-2070)and 2080s (2071-2100) and the baseline climate (1961-1990) from the GCM runs. Annual, seasonal or monthly