The role of climate models in IPCC Reto Knutti NCAR / CGD knutti@ucar.edu With contributions from thousands of people around the world… NCAR Summer School: The art of climate modeling

Overview What is IPCC? And AR4? Types of models used in IPCC reports Highlights: a few examples Benefits and problems in coordinated model efforts 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: First assessment report (FAR) 1995: Second assessment report (SAR) 2001: Third assessment report (TAR) 2007: Fourth assessment report (AR4) ~ 2013: 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 All new model runs needed for WGI IPCC WG1 approval Jan 2007 3rd draft due Sep 15; review of SPM …… 4th LA meeting (Norway) Jun 2006 2nd draft due Mar. 3, Govt/expert rev 3rd LA meeting (New Zealand) Dec 2005 1st draft due Aug. 12; expert review, 17’000 comments! Model analysis wkshp, IPRC, Hawaii 2nd LA meeting (Beijing) Mar 2005 May 2005 Zero order draft, internal review 1st LA meeting (Italy) Sep 2004 Climate sensitivity workshop (July, 2004, Paris) ……. IPCC approval of outline Nov 2003 2nd Scoping meeting Sep 2003 1st Scoping meeting Apr 2003 All new model runs needed for WGI Documentation needed (papers submitted to journals) by May 31 All papers/documentation in press or appeared by December 15

WG I structure AR4 WG I: Climate Change 2007: The Physical Science Basis 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 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 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. Observed changes are unlikely to be due to internal variability (detection); Observed changes are consistent with the calculated responses from best-guess estimates of anthropogenic and natural forcing (attribution) Observed changes are not consistent with alternative, physically plausible explanations of recent climate 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…

The problem of combining results from multiple models… Model evaluation The problem of combining results from multiple models… 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… How much do we learn from intercomparisons? Is IPCC worth the effort? Purely science driven models vs. operational forecast? What is interesting vs. what IPCC or WG II/III wants “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. 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.