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Report of the CCSM Climate Change and Assessment Working Group


Fifth Annual Community Climate System Model Workshop
Co-chairs: W. Washington, G. Meehl, and K. Taylor
The Village at Breckenridge, 29 June 2000


The Climate Change and Assessment Working Group (CCAWG) met for the first time at the 2000 CCSM Workshop in Breckenridge, Colorado. W. Washington presented an overview of climate change simulations carried out to date by CSM and PCM. These simulations used carbon dioxide, other greenhouse gases, sulfate aerosols, and solar variability forcing. A description of the CSM simulations can be found at www.cesm.ucar.edu/ and the PCM simulations can be found at www.pcmdi.llnl.gov and at NCAR at www.cgd.ucar.edu/pcm/.

It was noted that the CSM and PCM would be merged over the next year or so. The name of the new merged model will be the Community Climate System Model (CCSM). An interim model with the new sea ice model and ocean model coupled to the existing atmospheric model is currently being tested as a lead-in to the merged model. This model version is sometimes being referred to as "PCM2" or "interim model." Though the ocean and sea ice components are predecessors to the versions that will be included in the CCSM, the interim version still uses the PCM coupler and PCM version of the CCM3. The new merged model (CCSM) will use the new sea ice and ocean components, along with the Community Atmosphere Model (CAM-1), which is the name of the next version of CCM3, and the new flux coupler currently being configured.

Three scientific presentations were given during the CCAWG meeting and G. Meehl gave another in the plenary session. The talk given by G. Meehl documented reasons for the improvements in El Niño amplitude in recent versions of CSM and PCM (Meehl et al., 2000a), showed that these recent versions compare favorably with observations while many other current global coupled models simulate less El Niño variability than observed, and then described results from 2XCO2 and 4XCO2 stabilization simulations with PCM where there was no significant change in El Niño amplitude in those future climate states (Washington et al., 2000). He noted that CSM and PCM simulations make prominent contributions in the upcoming IPCC Third Assessment Report. He then examined the range of responses between members of an ensemble of climate change simulations with a single model (the PCM) and the range of responses from a multi-model ensemble (from Chapter 9 of the IPCC Third Assessment Report, which includes CSM and PCM). Since the multi-model ensemble range at the year 2100 was roughly an order of magnitude larger than the multi-member ensemble range from a single model (the PCM), it was stressed that an urgent research issue is to sort out why different models respond in different ways. Meehl gave an example of this type of analysis of the "El Niño-like response" and sea ice response differences between two versions of global coupled models at NCAR (the original CSM and the predecessor to the PCM, the DOE coupled model; Meehl et al., 2000b). It is only through such analyses of processes and feedbacks in different models that we can understand their different responses and eventually reduce uncertainty.

Continuing this theme, K. Taylor discussed the development of a new methodology for quantifying how various feedbacks play a role in climate change simulations in different models (Taylor et al., 2000). A. Dai then showed climate change results from both the CSM and PCM simulations. He also identified the model biases compared to observational data. The final talk was given by M. Wehner, who discussed the establishment of statistical criteria for how many members of an ensemble are needed for statistically significant responses from different climate variables. He also described how PCMDI would archive and make available PCM climate change data.

Since the understanding of processes and how they contribute to model responses is recognized as a research priority for the CCAWG, it was noted that a principal activity of the working group over the next year would be to analyze the many existing climate change simulations with CSM and PCM. CCAWG members were encouraged to perform such analyses either on their own or in collaboration with other working group members. This is the first time in the United States that a significant number of ensemble members have been run with difference forcing scenarios for projections of future climate, and then have been made generally available to the community. Access to the simulations is as follows:

CSM: Contact Lawrence Buja  (southern@ucar.edu) or check the CSM web page at www.cesm.ucar.edu/.

PCM: Contact Mike Wehner (mwehner@llnl.gov) or check the web page: www-pcmdi.llnl.gov and click on "model data."

In the open discussion several suggestions and recommendations were made:

Chuck Hakkarinen offered to make available an email mailing address for participants who are interested in climate change issues. The address is ccsmccawg@pcmecca.epri.com. Chuck asked that interested scientists send him suggestions for additions to the mailing list.

It was agreed that correspondence would be sent out on a monthly basis to interested scientists via email about new runs and data sets. W. Washington would take on this responsibility along with the other co-chairs. As part of this communication process, before significant new runs are started, the community will be asked if they want specific quantities saved. This should avoid having to do re-runs later if quantities of interest are set up to be saved before the run starts.

There was a consensus that it would be useful to have daily output of climate variables for some of the simulations. Most of the PCM 20th and 21st century runs have saved key daily quantities, and these are in the process of being transferred to PCMDI.

There were recommendations for additional climate change simulations. One is to continue business-as-usual simulations to the year 2200. The purpose of this simulation is to show a larger climate change difference from a greenhouse gas stabilization simulation that stopped at year 2100. However, the time evolution of the various forcings needs to be configured from 2100 to 2200 before this run can be performed. Another suggestion was to perform a land-surface change simulation. Most climate change simulations have involved greenhouse gases and sulfate aerosols. However, it is expected that land-surface changes will be a major component of future climate change. Over the next year, research will have to be done to develop data sets of present and expected future land-surface modifications. Part of the effort will be to specify changes in vegetation types. Another simulation that was suggested by the CCAWG was to put in a time series of volcanic aerosols. The Paleoclimate Working Group is expected to use the C. Ammann data set, which will be available in the fall, when he finishes his Ph.D. thesis. K. Trenberth suggested that we use other volcanic data sets as well because of the high uncertainty of the forcing. Use of several volcanic data sets will provide a range of uncertainty. It was suggested that some tests be performed with recent eruptions to help calibrate the model response. To carry out this research will require coordination with the Land and Paleoclimate Working Groups. On a longer time scale than a year, the working group will need to work with the Biogeochemistry Working Group on including interactions with the carbon cycle, other greenhouse gas cycles, and several types of aerosol-chemistry cycles. The CCAWG noted that the option of an anthropogenic sulfate aerosol cycle is important for CAM1.

A simulation with a T85 version of CCM3 in the current version of PCM is planned to test the effects of resolution on climate change simulations. Up to the present, most climate change simulations have used a T42 or lower horizontal resolution. A lead-in to this coupled simulation will be an AMIP run with the T85 CCM3. It was agreed to make the T85 AMIP run data and the fully coupled test run available to the Polar Climate and Climate Variability Working Groups.

There was discussion of new tools that are being developed by PCMDI, NCAR/SCD, and NCAR/CGD that would make both the CSM and PCM data available in a more convenient manner. The idea is to make obtaining the data as easy as possible and to avoid transferring the data archive across the Internet as much as possible. This is especially important to this working group because of the size of the data sets.

References:

Dai, A., T.M.L. Wigley, B.A. Boville, J.T. Kiehl, and L.E. Buja, 2000: Climates of the 20th and 21st centuries simulated by the NCAR Climate System Model. Journal of Climate, in press.

Meehl, G.A., P. Gent, J.M. Arblaster, B.L. Otto-Bliesner, E. Brady, and A. Craig, 2000a: Factors that affect amplitude of El Niño in global coupled climate models. Climate Dynamics, accepted.

Meehl, G.A., W.D. Collins, B. Boville, J.T. Kiehl, T.M.L Wigley, and J.M. Arblaster, 2000b: Response of the NCAR Climate System Model to increased CO2 and the role of physical processes. Journal of Climate, 13, 1879-1898.

Taylor, K.E., C.D. Hewitt, P. Braconnot, A.J. Broccoli, C. Doutriaux, and J.F.B. Mitchell, 2000: Analysis of forcing, response and feedbacks in a paleoclimate modeling experiment. Proc. Third PMIP Workshop, WCRP Report WCRP-111, in press.

Washington, W.M., J.W. Weatherly, G.A. Meehl, A.J. Semtner, Jr., T.W. Bettge, A.P. Craig, W.G. Strand, Jr., J.M. Arblaster, V.B. Wayland, R. James, Y. Zhang, 2000: Parallel Climate Model (PCM) control and transient simulations. Climate Dynamics, in press.

Participant List

First Name

 Last Name

 E-mail

Julie

 Arblaster

 jma@ucar.edu

Anjuli

 Bamzai 

 abamzai@nsf.gov

Jason

 Bell

jbell@es.ucsc.edu

Aiguo

 Dai

adai@ucar.edu

Dmitriy

 Dukhovskoy

dmitri@ims.uaf.edu

Johannes

 Feddema

feddema@ukans.edu

Arthur

 Few

few@rice.edu

Lydia

 Gates

LGates@lbl.gov

Charles

 Hakkarinen

chakk@epri.com

Danny

 Harvey

harvey@ucar.edu

Justin

 Hnilo

hnilo@pcmdi.llnl.gov

Qi

 Hu

qhu@unlnotes.unl.edu

Elizabeth

 Hunke

eclare@lanl.gov

Steven

 Jayne

surje@ucar.edu

JoAnn

 Lysne

lysne@ucar.edu

Roland

 Madden

ram@ucar.edu

Robert Malone rcm@lanl.gov

Lawrence

 Marx

marx@cola.iges.org

Jerry

 Meehl

meehl@ncar.ucar.edu

Richard

 Moritz

dickm@apl.washington.edu

Norikazu

 Nakashiki

nakasiki@criepi.denken.or.jp

David

 Pierce

dpierce@ucsd.edu

Gerald

 Potter

gpotter@llnl.gov

Andrew

 Robertson

andy@atmos.ucla.edu

Edward

 Sarachik

sarachik@atmos.washington.edu

Frank

 Selten

selten@ucar.edu

Albert

 Semtner

sbert@ucar.edu

Dezheng

 Sun

ds@cdc.noaa.gov

Karl

 Taylor

taylor13@llnl.gov

Starley

 Thompson

thompson59@llnl.gov

Robin

 Tokmakian

robint@ucar.edu

Kevin

 Trenberth

trenbert@ucar.edu

Warren

 Washington

wmw@ucar.edu

Michael

 Wehner

mwehner@llnl.gov

Fanglin

 Yang

fyang@ncep.noaa.gov

Rucong

 Yu

yrc@lasgsg18.jap.ac.cn

Yuxia

 Zhang

zhangy@ucar.edu