Transcript THE CLIMATE SEVERITY INDEX FOR CANADA

Global Climate Model (GCM) Scenarios for
Climate Change Impacts Research
Trevor Murdock, M.Sc. [email protected]
Canadian Institute for Climate Studies www.cics.uvic.ca
14 Sep 2004
Outline
1.
2.
Context & definitions
Global Climate Models (GCMs)
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3.
Applying scenarios to impacts studies
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4.
5.
Scenarios
Uncertainty
Emissions
Vegetation
Downscaling: RCMs & other approaches
Climate normals
Scenarios for BC
Summary
Context and definitions
• Identify Vulnerabilities - what aspects of
climate change is a community / region
susceptible to?
• Study potential Impacts of climate change;
projections of future climate are required; use
a range of Scenarios from Global Climate
Models (GCMs) to deal with uncertainty
• Adaptation strategies involve managing for
current and potential future climate (change
and variability) impacts
What are Global Climate Models?
• GCMs compute
global weather
patterns several
times per day
projected over the
next century
• GCMs are the
“…only credible
tools currently
available for
simulating the
physical processes
that determine
global climate...”
[IPCC]
Sources of Uncertainty
[Source: Hadley Centre for Climate Prediction and Research, UK Met. Office]
Emissions Scenarios
– Emissions scenarios
based on different
assumptions about
how the global
economy will
evolve and emit
fossil fuels over
the next century
– SRES recommended
– IS92a gg & ga also available
– Naming convention also denotes members of ensembles
with numbers and ensemble averages with x (i.e. CGCM2
A11, A12, A13, A1x)
Emissions & Concentrations
GCMs
Each GCM has different parameterizations of physics
of the Atmosphere, Ocean, Cryosphere & Biosphere
CGCM1
Canadian Centre for Climate Modelling and Analysis Global Coupled Model 1
CGCM2
Canadian Centre for Climate Modelling and Analysis Global Coupled Model 2
HadCM2
Hadley Centre Coupled Model 2
HadCM3
Hadley Centre Coupled Model 3
GFDLR15
Geophysical Fluid Dynamics Laboratory R15
GFDLR30
Geophysical Fluid Dynamics Laboratory R30
ECHAM4
European Centre/Hamburg Model 4
CSIROMk2b
Commonwealth Scientific Industrial Research Organization Mk2b
CCSRNIES
Center for Climate Research - National Institute for Environmental Studies
NCARPCM
National Center for Atmospheric Research
Vegetation in GCMs
• GCMs typically ignore climate/vegetation feedbacks:
• CCCMa (Canada)
– CGCM2 - no vegetation
– CGCM3 - simple CLASS scheme
– CGCM4 - will include more sophisticated vegetation and
biophysical processes
• Hadley Center (UK)
– HadCM3 includes representation of freezing and melting of
soil moisture and evaporation includes the stomatal
resistance on temperature, vapour pressure, and CO2
concentration (Cox et al., 1998)
Applying Scenarios: Downscaling
• GCM scenarios coarse resolution (100s of kms / monthly)
• Dynamic methods
• retain internal physical consistency
• high resolution AGCMs, Regional Climate Models (RCMs)
• Statistical methods
• less costly/less complicated
• Weather generators – LARS-WG, Multiple linear regression - SDSM
• Best solution often not to downscale at all
• interpolate (introduces false geographical precision)
• apply change fields from larger spatial scale to working scale
Regional Climate Models
1. Account for sub-grid
scale forcings such
as topography and
land cover in a
physically-based
way
2. Note: more physics
can mean more
uncertainty
Applying Scenarios: Climate Normals
- “Baseline Climates”
- Usually 1961-1990
- Good baseline data needed for 2 reasons:
- GCM scenario differences need to be applied to an observed
baseline (to remove model bias).
- Impacts assessment should include analysis of recent climate
- Types of observational baselines:
-
Individual station data (raw, homogenized)
Gridded station data (interpolated)
Gridded satellite data
Gridded reanalysis data (statistical/dynamical/modeling)
PRISM 4km x 4km ( or resampled to 2km x 2 km ) grid –
Temperature, Rainfall, Snowfall
CCIS – Custom Regions
http://www.cics.uvic.ca/scenarios/data/select.cgi
• Predefined regions or create by clicking on map
• Control panel interface (rather than steps)
• Dynamic map creation allows for user customization
of many features (legend, decimal places, grid, etc.)
• Meta-information about full map and region (min,
max, median, area-weighted mean, stddev)
http://www.cics.uvic.ca/scenarios/data/select.cgi
Summary
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Impacts work most effective in the context of
Vulnerability, Impacts, and Adaptation
GCM based scenarios used to represent range of
plausible future climates for impacts studies
Vegetation beginning to be included explicitly in GCMs
Downscaling may be used to overcome differences in
scale between GCMs and impacts analysis
GCM change fields are applied to climate normals
Scenarios for BC – see www.cics.uvic.ca/scenarios for
more tools, scenarios, and data