Transcript The role of climate models in IPCC

The role of climate models in IPCC
Reto Knutti
NCAR / CGD
[email protected]
With contributions from thousands of people around the world…
NCAR Summer School: The art of climate modeling
Overview
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What is IPCC? And AR4?
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Types of models used in IPCC reports
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Highlights: a few examples
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Benefits and problems in coordinated model efforts
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Benefits and problems of IPCC for the modeling community
What is IPCC
The Intergovernmental Panel on Climate Change (IPCC) was established
in 1988 by WMO and UNEP and consists of about 190 governments that
commission assessments performed by the international climate science
community on the state of human knowledge of climate and climate
change.
Role of the IPCC
The role of the IPCC is to assess on a comprehensive, objective, open
and transparent basis the scientific, technical and socio-economic
information relevant to understanding the scientific basis of risk of
human-induced climate change, its potential impacts and options for
adaptation and mitigation. Review by experts and governments is an
essential part of the IPCC process. The Panel does not conduct new
research, monitor climate-related data or recommend policies. It is open
to all member countries of WMO and UNEP
(From http://www.ipcc.ch/about/anniversarybrochure.pdf)
What is IPCC
Role of the IPCC
The role of the IPCC is to assess on a comprehensive, objective, open
and transparent basis the scientific, technical and socio-economic
information relevant to understanding the scientific basis of risk of
human-induced climate change, its potential impacts and options for
adaptation and mitigation. Review by experts and governments is an
essential part of the IPCC process. The Panel does not conduct new
research, monitor climate-related data or recommend policies. It is
open to all member countries of WMO and UNEP.
IPCC is policy relevant, but not policy prescriptive!
Although the reports are supposed to be objective and purely
scientific, the process is to some degree political (plenary, open for
all countries, topics covered, criticism on process and authors).
UNFCCC
United Nations Framework Convention on Climate Change
(UNFCCC)
“…to achieve stabilization of greenhouse gas concentrations in the
atmosphere at a low enough level to prevent dangerous anthropogenic
interference with the climate system. “
The IPCC first assessment report was important in creating the
UNFCCC.
What is IPCC
Structure of AR4
Working Group I: The physical science basis
Working Group II: Climate impacts, adaptation and vulnerability
Working Group III: Mitigation
Organization: Chair, Co-chairs, Coordinating lead authors, lead authors,
contributing authors, review editors, expert and government reviewers
1990:
1995:
2001:
2007:
~ 2013:
First assessment report (FAR)
Second assessment report (SAR)
Third assessment report (TAR)
Fourth assessment report (AR4)
Fifth assessment report (AR5)
Special reports on emission scenarios (SRES), CO2 capture and storage,
safeguarding the ozone layer (CFC, HFC, PCF,…), land use change,
aviation, etc.
Timetable
Apr 2003
1st Scoping meeting
Sep 2003
2nd Scoping meeting
Nov 2003
IPCC approval of outline
…….
Climate sensitivity workshop
(July, 2004, Paris)
Sep 2004
1st LA meeting (Italy)
……
Zero order draft, internal review
Mar 2005
May 2005
Model analysis wkshp, IPRC, Hawaii Documentation needed (papers
submitted to journals) by May 31
2nd LA meeting (Beijing)
……
1st draft due Aug. 12; expert review, 17’000 comments!
Dec 2005
3rd LA meeting (New Zealand)
……
2nd draft due Mar. 3, Govt/expert rev
Jun 2006
4th LA meeting (Norway)
……
3rd draft due Sep 15; review of SPM
Jan 2007
IPCC WG1 approval
All new model runs needed for WGI
All papers/documentation in press
or appeared by December 15
WG I structure
AR4 WG I: Climate Change 2007: The Physical Science Basis
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Historical Overview of Climate Change Science
Changes in Atmospheric Constituents and in Radiative Forcing
Observations: Surface and Atmospheric Climate Change #
Observations: Changes in Snow, Ice and Frozen Ground
Observations: Oceanic Climate Change and Sea Level
Paleoclimate *
Couplings Between Changes in the Climate System and
Biogeochemistry *
Climate Models and their Evaluation
Understanding and Attributing Climate Change
Global Climate Projections #**
Regional Climate Projections *
#NCAR coordinating lead author
*NCAR lead author
WG I structure
AR4 WG I: Climate Change 2007: The Physical Science Basis
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Historical Overview of Climate Change Science
Changes in Atmospheric Constituents and in Radiative Forcing
Observations: Surface and Atmospheric Climate Change #
Observations: Changes in Snow, Ice and Frozen Ground
Observations: Oceanic Climate Change and Sea Level
Paleoclimate *
Couplings Between Changes in the Climate System and
Biogeochemistry *
Climate Models and their Evaluation
Understanding and Attributing Climate Change
Global Climate Projections #**
Regional Climate Projections *
#NCAR coordinating lead author
*NCAR lead author
Types of models used in IPCC
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Simple models to run many scenarios
Intermediate complexity models (EMICs) for probabilistic
projections, long-term projections, sensitivity studies, long-term
carbon cycle projections, climate sensitivity estimates,
paleoclimate, etc.
General circulation climate models (GCMs)
Carbon cycle models to estimate carbon cycle feedbacks
Chemistry models, radiation codes, ice sheet models, etc.
AR4 multi-model effort
The IPCC AR4 has motivated the formulation of the largest international
global coupled climate model experiment and multi-model analysis effort
ever attempted, and is being coordinated by the Working Group on
Coupled Modeling (WGCM) Climate Simulation Panel.
Fourteen modeling groups from around the world are participating with 23
models; considerable resources have been devoted to this project;
PCMDI has archived ~30 TB of model data so far.
CCSM Version 3 was released in time to run the requested simulations.
CCSM3 has made the largest contribution from any single model to the
multi-model dataset (about 30%) being assessed for the AR4, with eight
ensemble members of all experiments (five for A2). Model runs at NCAR,
Oak Ridge National Laboratory (ORNL), and the National Energy
Research Scientific Computing Center (NERSC) and the Earth Simulator.
Total amount of data generated at NCAR: >100 TB
SRES projections
SRES projections
A1B zonal average of projected warming
SRES projections
SRES A1B 2080-2100, relative to 1980-2000
SRES projections
Sea ice concentration (in %)
SRES projections
Extreme events: overall tendency to increase in precipitation intensity,
dry days, heat waves, growing season length, decrease in frost days
Detection attribution
Anthropogenic and
natural forcings
Only natural forcings
Detection and attribution
Global temperature, for all forcings (red) and natural forcing only (blue),
and observations (black)
Detection and attribution
We cannot conclude with high confidence that the total forcing was
indeed positive due to the uncertainties of the forcing components. Thus,
attribution of the observed warming does not rest very securely on the
straightforward argument that a significantly positive anthropogenic
radiative forcing caused the observed warming. Rather, attribution is
demonstrated indirectly by the following arguments.
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Observed changes are unlikely to be due to internal variability
(detection);
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Observed changes are consistent with the calculated responses from
best-guess estimates of anthropogenic and natural forcing
(attribution)
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Observed changes are not consistent with alternative, physically
plausible explanations of recent climate
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The difference between the observations and the attribution patterns,
i.e., the part of the observed signal which is not explained by the
assumed forcing, must be consistent with internal unforced climate
variability.
Detection and attribution
Run model with certain forcing (e.g. GHG) and project observations on
model response, calculate scaling factor , estimate uncertainty in  from
model control runs
Detection:  inconsistent with zero at given significance level
Attribution:  consistent with unity
Detection attribution
Detection and
attribution is now
possible for global
surface temperature,
the vertical profile of
temperature in the
atmosphere, for
changes in the ocean
temperature, for
continental to regional
temperature changes,
and for changes in the
tropopause height.
(Santer et al. 2000)
Detection attribution
FAR 1990: little observational evidence of a detectable anthropogenic
influence on climate
SAR 1995: “The balance of evidence suggests a discernible human
influence on the climate of the 20th century.“
TAR 2001: “There is new and stronger evidence that most of the warming
observed over the last 50 years is attributable to human activities.”
Proposed for AR4 2007: It is very likely that greenhouse gas forcing has
been the dominant cause of the observed warming of globally averaged
temperatures in the last 50 years. An increasing body of evidence
suggests a discernible influence on other aspects of climate, including
sea ice, heat waves and other extremes, circulation, storm tracks, and
precipitation. Second order draft, subject to change!!!
Regional projections
Annual precipitation for the Alps
Observations
Regional climate model (RCM) 50km
RCM 25km
RCM 12km
Regional projections
A1B regional changes in temperature for Asia
Model evaluation
RMS error over all
longitudes and
Seasons
No single best
model for all
diagnostics.
Multi-model mean
Is better than
Individual models.
But…
Model evaluation
The problem of combining results from multiple models…
Model evaluation
The problem of combining results from multiple models…
Model evaluation
The problem of combining results from multiple models…
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no verification, therefore skill undefined, no unique metric
dependence, uncertainty does not decrease with 1/n2
average biases, with known or unknown effects
not designed to span the uncertainty range, ensemble of
opportunity, distribution arbitrary within that range, unknown prior
tuning with the same datasets as used to define skill, right result
for the wrong reason
Averaging blindly across models doesn’t seem to be ideal. Models
are highly dependent, and some are much worse than others. But
reaching an agreement on a set of metrics to evaluate and weight
models is difficult for both scientific and political reasons.
Should we rather have fewer but better models?
Probabilistic projections
Simple climate models
Carbon cycle EMICs
Zero emission commitment
A critical look at it…
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How much do we learn from intercomparisons?
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Is IPCC worth the effort?
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Purely science driven models vs. operational forecast? What is
interesting vs. what IPCC or WG II/III wants
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“IPCC is just an assessment of published literature” vs. “IPCC is
driving the development in climate modeling”.
NCAR CCSM Version 4 probably must be released in 2009,
production will be in 2010, simulations need to be done by end of
2010 in order to go into IPCC AR5 in 2013. Pressure is large, and the
effort and costs are huge.
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Has climate modeling lost its innocence?
Funding into climate modeling has increased because of IPCC.
Political decisions determine funding, drive model development, and
therefore influence scientific questions.