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The Canadian Climate Impacts Scenarios (CCIS) Project. A collaborative project sponsored by the Climate Change Action Fund. Project Aims. To encourage the use of a consistent set of climate change scenarios by the VIA research community in Canada. By:
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The Canadian Climate Impacts Scenarios (CCIS) Project A collaborative project sponsored by the Climate Change Action Fund
Project Aims To encourage the use of a consistent set of climate change scenarios by the VIA research community in Canada • By: • providing basic national climate change scenarios • developing a nationally-consistent framework within which sector- and region-specific climate change scenarios can be developed • developing and maintaining a capacity to support climate impacts and adaptation research and assessments http://www.cics.uvic.ca/scenarios • involving the university research community and scenario users in the further development of climate change scenarios
Project conforms to IPCC-TGCIA recommendations: Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment (Download from: http://ipcc-ddc.cru.uea.ac.uk) Current focus is on climate change scenario construction using GCM output: • Warm start experiments • IS92a, and now SRES emissions scenarios • GCMs which have been involved in model intercomparison exercises
IPCC-TGCIA Recommendation “Users should design and apply multiple scenarios in impacts assessments, where these scenarios span a range of possible future climates, rather than designing and applying a single ‘best guess’ scenario” http://ipcc-ddc.cru.uea.ac.uk
What’s available from CCIS... • Climate change scenarios for Canada and North America • At original GCM resolution; (0.5° latitude/longitude) • Mean changes wrt 1961-1990 for the 2020s, 2050s and 2080s; also monthly time series, anomaly time series • Monthly, seasonal and annual values • Climate variables, minimum data set: mean, minimum and maximum temperature, precipitation, a radiation variable, a humidity variable, wind speed • Advice on scenario construction, downscaling, applications, limitations and uncertainties http://www.cics.uvic.ca/scenarios
Scenarios from ... • Canadian Centre for Climate Modelling and Analysis (CGCM1, CGCM2) • Hadley Centre for Climate Prediction and Research (HadCM2, HadCM3) • Australian Commonwealth Scientific and Industrial Research Organisation (CSIROMk2b) • German Climate Research Centre (ECHAM4) • Geophysical Fluid Dynamics Laboratory (GFDL-R15, GFDL-R30) • Japanese Centre for Climate Research Studies (CCSR/NIES) • US National Centre for Atmospheric Research (NCAR-PCM)
IS92a CGCM1, CGCM2 HadCM2, HadCM3 ECHAM4 GFDL-R15 CSIROMk2b CCSR/NIES NCAR-PCM Total 26, + 4 means SRES CGCM2 HadCM3 CSIROMk2b ECHAM4 CCSR/NIES GFDL-R30 NCAR-PCM Total 29, + 3 means Available Scenarios
How do you use this information? Simplest method: apply monthly or seasonal scenario changes from appropriate grid box to observed data (either daily, monthly or seasonal).
You can produce synthetic weather data using a stochastic weather generator - statistical characteristics will be similar to observed, but day-to-day values will be different Results … • A time series which has the same statistical characteristics as the observed data, but with the mean values perturbed by the scenario amount
2020s PRISM: 1961-90 Normals 2050s Scenario Application Present and Future Precipitation in British Columbia 2080s [Supplied by Bill Taylor, Environment Canada, Pacific and Yukon Region]
Scenario Tools • Scatter plots to assist with scenario selection • Access to downscaling tools
Scatter Plots Cooler, wetter Warmer, wetter Warmer, drier Cooler, drier
LARS-WG: stochastic weather generator Access to SDSM and predictor variables for North America (soon global) Downscaling Tools
In Progress ... • Major revisions to web site content and development of additional tools • Major updates to bioclimate profiles • Predictor datasets for use with SDSM
What’s planned ... • Interpretation of scenarios • descriptive indices, such as degree days, a drought index … • Scenarios of changes in climate variability and extremes; significance of scenario changes • Further work on downscaling
Scenario Significance CGCM1 GAX: Winter precipitation change (%)
Climate Change versus Climate Variability [Source: Nigel Arnell, in Hulme et al. (1999), Nature 397]
Significance of the Effect of Climate Change: Runoff [Source: Nigel Arnell, in Hulme et al. (1999), Nature 397]
GCMs and Extreme Events ‘Hot’ summer