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Developing Climate Scenarios for Climate Change I, A & V Assessments

Developing Climate Scenarios for Climate Change I, A & V Assessments An introduction to the resources on scenario development and application available for AIACC study teams By Dr Xianfu Lu, Tyndall Centre for Climate Change Research At AIACC Training Workshop on

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Developing Climate Scenarios for Climate Change I, A & V Assessments

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  1. Developing Climate Scenarios for Climate Change I, A & V Assessments An introduction to the resources on scenario development and application available for AIACC study teams By Dr Xianfu Lu, Tyndall Centre for Climate Change Research At AIACC Training Workshop on Vulnerability & Adaptation Assessment Methods 3~14 June, Trieste, Italy

  2. Next 30 minutes… • Why do we need climate scenarios? • What technical support is available? • Why developing climate scenarios are so problematic? 4. What should be considered while developing scenarios? 5. What data are currently available in public domain? 6. What’s new from the technical support group?

  3. Global socio-economic assumptions Emissions scenarios Concentration projections Radiative forcing projections Sea level projections Climate projections National Policy responses: adaptation and mitigation Interactions and feedbacks Climate and Sea Level Scenarios National integrated scenarios (socio-economic & environmental) National impacts 1. Why do we need climate scenarios? Conceptual framework for conducting integrated assessment of climate change for policy applications. Source: IPCC (2001)

  4. 2. What support resource is available? • Tyndall Centre • Advising on scenario design; • Providing technical support for scenario development and application; • Preparing technical notes on particular scenario development techniques; • Conducting diagnostic analysis of climate model experiment results while appropriate; • Updating study teams on the newly available information/data • Regional mentors • Latin America: Jose Marengo • Asia: Roger Jones • Africa: Bruce Hewittson

  5. 3. Why developing climate scenarios are so problematic? Problem 1. Models are not accurate …. … so we ‘cannot’ use data from climate models directly in environmental or social simulation models … add model changes to baseline – mean and variability … use a weather generator

  6. 3. Why developing climate scenarios are so problematic? Problem 2. Different climate models give different results … … so we have difficulty knowing which climate model(s) to use … select on basis of validation, age, representativeness, accessibility – or use them all! …

  7. 3. Why developing climate scenarios are so problematic? Problem 3.It is expensive to run many (global/regional) climate model experiments for many future emissions …. .… so we often have to make choices about which emissions scenarios from which we build our climate scenarios … may not matter much for 2020s, but will make a real difference by 2080s … pattern-scaling methods may help if we only have results from only one emissions scenario

  8. 3. Why developing climate scenarios are so problematic? Problem 4. Climate models give us results at the ‘wrong’ spatial scale … … so we have to develop and apply one or more downscaling methods … these may be simple (interpolation) or complex (statistical downscaling, weather generators) … RCMs may get you so far, but probably not far enough

  9. 4. What should be considered while developing scenarios? How many scenarios do you need? Which uncertainties are you going to explore? What non-climate information do you need in your scenario(s)? Do you need local data for case studies/sites, or national/regional coverage? What spatial resolution in your climate model output do you really need – 300k, 100k, 50k, 10k, 1k? Can you justify this choice? Do you need changes in average climate, or in variability? Do you need changes in daily weather, or just monthly totals? What climate variables are essential for your study?

  10. 5. What data are currently available? • Data Sources • Climate reconstruction data • Observed climatology • Climate model outputs World Data Centre for Palaeo-climatology (www.ngdc.noaa.gov/paleo/data.html) Climatic Research Unit, UEA (www.cru.uea.ac.uk/cru/data) NCDC(lwf.ncdc.noaa.gov/oa/ncdc.html) NCEP/NCAR reanalysis (www.cdc.noaa.gov/cdc/data.nmc.reanalysis.html) IPCC-DDC GCM data (ipcc-ddc.cru.uea.ac.uk; ipcc-ddc.cru.uea.ac.uk/dkrz/dkrz_index.html) Hadley Centre data (www.cru.uea.ac.uk/link/) Canadian data (www.cccma.bc.ec.gc.ca/data.html)

  11. 5. What data are currently available? • SRES driving GCM experiments • DDC YELLOW pages (ipcc-ddc.cru.uea.ac.uk/dkrz/dkrz_index.html) • Monthly time series (1960~2100); • A set of core surface variables and a set of optional upper-air indices; • Currently available for A2 and B2 runs from HadCM3, CSIRO-Mk2, NCAR-PCM, CGCM2); A1 and B1 from CSIRO-Mk2. • DDC GREEN pages (ipcc-ddc.cru.uea.ac.uk) • 30-year monthly average (1961~90, 2020s, 2050s, 2080s); • A set of core surface variables and a set of optional upper-air indices; • No data available yet

  12. 6. What’s new from the technical support group? • Technical note on pattern-scaling GCM outputs

  13. 6. What’s new from the technical support group? • Diagnostic analysis of the IPCC TAR reviewed GCM experiments • 1961~1990 climatologies against 0.5 degree observed climatologies; • Seasonal (DJF and JJA) anomalies of precipitation and temperature from 9 GCM experiments for the time slice of 2080s

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