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MAGICC/SCENGEN Hands On Tutorial

MAGICC/SCENGEN Hands On Tutorial. By Joel B. Smith Stratus Consulting Inc. Jsmith@stratusconsulting.com NCAR Summer 2006 Colloquium on Climate and Health July 18, 2006. Outline. Brief Introduction on Climate Change Scenarios

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MAGICC/SCENGEN Hands On Tutorial

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  1. MAGICC/SCENGEN Hands On Tutorial By Joel B. Smith Stratus Consulting Inc. Jsmith@stratusconsulting.com NCAR Summer 2006 Colloquium on Climate and Health July 18, 2006

  2. Outline • Brief Introduction on Climate Change Scenarios • Then, we’ll spend most of the time on the tutorial on MAGICC/SCENGEN

  3. Why Use Climate Change Scenarios? • We are unsure exactly how regional climate will change • Scenarios are plausible combinations of variables consistent with what we know about human-induced climate change • One can think of them as the prediction of a model, contingent upon the greenhouse gas emissions scenario • Since estimates of regional change by models differ substantially, an individual model estimate should be treated more as a scenario

  4. What Are Reasonable Scenarios? • Scenarios should be: • Consistent with our understanding of the anthropogenic effects on climate • Internally consistent • e.g., clouds, temperature, precipitation • Scenarios are a communication tool about what is known and not known about climate change • Should reflect plausible range for key variables

  5. Scenarios for Impacts Analysis • Need to be at a scale necessary for analysis • Spatial • e.g., to watershed or farm level • Temporal • Monthly • Daily • Sub-daily

  6. Regional Climate Change Scenarios • Present range of possible regional changes in climate • Two roles • Use ranges of climate changes to help understand sensitivity of affected systems • Use ranges to communicate what is known and not known about regional climate change • Temperature rise and range of precipitation changes

  7. Tools for Assessing Regional Model Output • We’ll learn how to use a tool that enables us to examine output from a number of climate models • Can see degree to which models agree and disagree about regional changes

  8. Sources of Uncertainty on Regional Climate Change • GHG Emissions • Greenhouse Gas Concentrations • Climate Sensitivity, e.g., 2xCO2 • Regional pattern of climate change • Distribution of changes in temperature and precipitation • Climate Variability

  9. GHG Emissions and Concentrations Projections Source: Houghton et al., 2001.

  10. Projections of Global Mean Temperature Change Source: Houghton et al., 2001.

  11. Normalized Annual-Mean Temperature Changes in CMIP2 Greenhouse Warming Experiments

  12. MAGICC/SCENGEN • User can: • Select GHG emission scenarios e.g., from IPCC SRES • Can select CO2 concentration • Select climate sensitivity • Select GCMs to examine • Regional pattern is hard wired in • Can examine change in seasonal variability • Not interannual or daily

  13. MAGICC/SCENGEN • MAGICC is a simple model of global T and SLR • Used in IPCC TAR • SCENGEN uses pattern scaling for 17 GCMs • Yield • Model by model changes • Mean change • Intermodel SD • Interannual variability changes • Current and future climate on 5 x 5°grid

  14. Using MAGICC/SCENGEN

  15. MAGICC: Selecting Scenarios

  16. SO2 Scenarios

  17. MAGICC: Selecting Scenarios (continued)

  18. MAGICC: Selecting Forcings

  19. MAGICC: Displaying Results

  20. MAGICC: Displaying Results (continued)

  21. SCENGEN

  22. Normalizing GCM Output • Expresses regional change relative to an increase of 1°C in mean global temperature • This is a way to avoid high sensitivity models dominating results • It allows us to compare GCM output based on relative regional change • Normalized temperature change = ΔTRGCM/ΔTGMTGCM • Normalized precipitation change = ΔPRGCM/ΔTGMTGCM

  23. Pattern Scaling • Is a technique for estimating change in regional climate using normalized patterns of change and changes in GMT • Pattern scaled temperature change: • ΔTRΔGMT = (ΔTRGCM/ΔTGMTGCM) x ΔGMT • Pattern scaled precipitation • ΔPRΔGMT = (ΔPRGCM/ΔTGMTGCM) x ΔGMT

  24. Running SCENGEN (continued)

  25. SCENGEN: Analysis

  26. SCENGEN: Model Selection

  27. SCENGEN: Area of Analysis

  28. SCENGEN: Select Variable

  29. SCENGEN: Scenario

  30. SCENGEN: Global Results

  31. SCENGEN: Map Results

  32. SCENGEN: Quantitative Results INTER-MOD S.D. : AREA AVERAGE = 5.186 % (FOR NORMALIZED GHG DATA) INTER-MOD SNR : AREA AVERAGE = -.067 (FOR NORMALIZED GHG DATA) PROB OF INCREASE : AREA AVERAGE = .473 (FOR NORMALIZED GHG DATA) GHG ONLY : AREA AVERAGE = -.411 % (FOR SCALED DATA) AEROSOL ONLY : AREA AVERAGE = -.277 % (FOR SCALED DATA) GHG AND AEROSOL : AREA AVERAGE = -.687 % (FOR SCALED DATA) *** SCALED AREA AVERAGE RESULTS FOR INDIVIDUAL MODELS *** (AEROSOLS INCLUDED) MODEL = BMRCD2 : AREA AVE = 2.404 (%) MODEL = CCC1D2 : AREA AVE = -5.384 (%) MODEL = CCSRD2 : AREA AVE = 6.250 (%) MODEL = CERFD2 : AREA AVE = -2.094 (%) MODEL = CSI2D2 : AREA AVE = 6.058 (%) MODEL = CSM_D2 : AREA AVE = 1.245 (%) MODEL = ECH3D2 : AREA AVE = .151 (%) MODEL = ECH4D2 : AREA AVE = -1.133 (%) MODEL = GFDLD2 : AREA AVE = 1.298 (%) MODEL = GISSD2 : AREA AVE = -3.874 (%) MODEL = HAD2D2 : AREA AVE = -5.442 (%) MODEL = HAD3D2 : AREA AVE = -.459 (%) MODEL = IAP_D2 : AREA AVE = -.088 (%) MODEL = LMD_D2 : AREA AVE = -6.548 (%) MODEL = MRI_D2 : AREA AVE = .065 (%) MODEL = PCM_D2 : AREA AVE = -3.451 (%) MODEL = MODBAR : AREA AVE = -.687 (%)

  33. SCENGEN: Global Analysis

  34. SCENGEN: Error Analysis

  35. SCENGEN Error Analysis (continued) UNWEIGHTED STATISTICS MODEL CORREL RMSE MEAN DIFF NUM PTS mm/day mm/day BMRCTR .632 1.312 1.026 20 CCC1TR .572 1.160 -.207 20 CCSRTR .587 .989 .322 20 CERFTR .634 1.421 -1.167 20 CSI2TR .553 1.112 -.306 20 CSM_TR .801 1.044 -.785 20 ECH3TR .174 1.501 -.649 20 ECH4TR .767 1.121 -.881 20 GFDLTR .719 .954 -.553 20 GISSTR .688 .799 .123 20 HAD2TR .920 .743 -.598 20 HAD3TR .923 .974 -.883 20 IAP_TR .599 1.408 -.734 20 LMD_TR .432 2.977 -2.103 20 MRI_TR .216 2.895 -2.026 20 PCM_TR .740 1.372 -1.041 20 MODBAR .813 .879 -.654 20

  36. What’s New (and Exciting) • SCENGEN is being updated • Have IPCC AR4 models • 2.5o resolution • May have other bells and whistles • Another very useful tool are the NCAR created PDFs

  37. Thank You! I’d be happy to take questions

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