MAGICC/SCENGEN Hands On Tutorial by techmaster

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									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

• Then, we’ll spend most of the time on the
  tutorial on MAGICC/SCENGEN
           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
              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
              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
     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
   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
      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
          GHG Emissions and
        Concentrations Projections




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




  Source: Houghton et al., 2001.
 Normalized Annual-Mean Temperature
Changes in CMIP2 Greenhouse Warming
             Experiments




            0 .4          0 .8       1 .2

     0 .2          0 .6          1          1 .4
        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
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
Using MAGICC/SCENGEN
MAGICC: Selecting Scenarios
SO2 Scenarios
MAGICC: Selecting Scenarios
           (continued)
MAGICC: Selecting Forcings
MAGICC: Displaying Results
MAGICC: Displaying Results
           (continued)
SCENGEN
     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
           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
Running SCENGEN   (continued)
SCENGEN: Analysis
SCENGEN: Model Selection
SCENGEN: Area of Analysis
SCENGEN: Select Variable
SCENGEN: Scenario
SCENGEN: Global Results
SCENGEN: Map Results
 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 (%)
SCENGEN: Global Analysis
SCENGEN: Error Analysis
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
    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
      Thank You!

I’d be happy to take questions

								
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