MAGICC/SCENGEN Hands On Tutorial

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MAGICC/SCENGEN Hands On Tutorial

• By
• Joel B. Smith
• Stratus Consulting Inc.
• Jsmith_at_stratusconsulting.com
• NCAR Summer 2006 Colloquium on Climate and Health
• July 18, 2006

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Outline

• Brief Introduction on Climate Change Scenarios
• Then, well spend most of the time on the
  tutorial on MAGICC/SCENGEN

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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

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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

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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

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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

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Tools for Assessing Regional Model Output

• Well 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

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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

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GHG Emissions and Concentrations Projections
Source Houghton et al., 2001.
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Projections of Global Mean Temperature Change
Source Houghton et al., 2001.
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Normalized Annual-Mean Temperature Changes in
CMIP2 Greenhouse Warming Experiments
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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

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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 5grid

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Using MAGICC/SCENGEN
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MAGICC Selecting Scenarios
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SO2 Scenarios
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MAGICC Selecting Scenarios (continued)
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MAGICC Selecting Forcings
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MAGICC Displaying Results
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MAGICC Displaying Results (continued)
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SCENGEN
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Normalizing GCM Output

• Expresses regional change relative to an increase
  of 1C 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 ?TRGCM/?TGMTGCM
• Normalized precipitation change ?PRGCM/?TGMTGCM

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Pattern Scaling

• Is a technique for estimating change in regional
  climate using normalized patterns of change and
  changes in GMT
• Pattern scaled temperature change
• ?TR?GMT (?TRGCM/?TGMTGCM) x ?GMT
• Pattern scaled precipitation
• ?PR?GMT (?PRGCM/?TGMTGCM) x ?GMT

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Running SCENGEN (continued)
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SCENGEN Analysis
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SCENGEN Model Selection
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SCENGEN Area of Analysis
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SCENGEN Select Variable
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SCENGEN Scenario
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SCENGEN Global Results
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SCENGEN Map Results
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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
()
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SCENGEN Global Analysis
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SCENGEN Error Analysis
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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
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Whats 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

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Thank You!

• Id be happy to take questions