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Report on CCSM Atmosphere Model Working Group Meeting

Seventh Annual CCSM Workshop, The Village at Breckenridge

Co-Chairs: Bill Collins, Leo Donner and Dave Randall

26 June 2002

The CCSM Atmosphere Model Working Group (AMWG) breakout session was held on the second day of the June 2002 CCSM Workshop. The ten oral and twelve poster presentations addressed various aspects of the new Community Atmosphere Model (CAM2) released with the rest of CCSM-2 on May 17, 2002. One of the primary objectives of the AMWG breakout session was to introduce the new atmospheric model to the scientific community. This model incorporates enhancements to the dynamics, physics, and boundary data sets, including:

The improvements in the climate simulation include more realistic tropical precipitable water, clear-sky longwave fluxes in polar regions, and more realistic forcing in the tropical Pacific.

The oral talks addressed analysis of systematic errors in the simulated climate, proposals for ameliorating or eliminating these biases, and new methods for diagnosing the model. The systematic errors include:

The manifestations of these biases were demonstrated in uncoupled and coupled simulations and in whole-atmosphere simulations with interactive stratospheric chemistry.

At the April AMWG meeting, the Scientific Steering Committee (SSC) requested that we give highest priority to research on reducing or eliminating these systematic errors. This request was discussed during our meeting in June and has been accepted by the AMWG. The group agreed to pursue this research in close collaboration with other working groups. The AMWG co-chairs have agreed to coordinate the experiments and experimental strategy.

The group also presented plans for longer-range development once the significant model biases have been addressed. These include:

Oral presentations:

Model diagnostics

Dave Williamson described a new, ARM-funded initiative to characterize errors in CAM and other GCMs by running short forecasts and comparing the model simulations against observations. The idea is to use state-of-the-art operational analyses to initialize the model state, preferably in regions where the analyses can be evaluated against extensive in situ data. Short-term forecasts from climate models initialized with the analyses will then be compared against observations from, for example, ARM sites. Errors in the short-term forecasts should be dominated by errors in physics parameterizations assuming the errors in the analyzed fields are sufficiently small. Dave presented preliminary results from his efforts to run CAM in forecast mode.

Model characteristics:

Chris Bretherton discussed the simulation of the eastern tropical Pacific. He showed that while the simulation of shortwave cloud forcing had improved, the warm bias in SSTs persists in CCSM2. The net energy flux at the ocean surface actually increases in CAM2 relative to CCM3. Chris attributed this increase to an underestimation of the latent heat flux compared to NCEP analyses. The cause appears to be an excessively moist PBL with mixing ratios under stratocumuli as large as 1 g/kg. His conclusion was that the PBL is not entraining enough air from the free troposphere.

Jeff Kiehl presented an analysis of cloud forcing response to SST anomalies from CAM and observational data sets. The analysis was based on a composite of warm and cold events. The model reproduces the changes in precipitation, total cloud amount, and outgoing longwave radiation. However, the sign of the response in absorbed shortwave radiation is incorrect in CAM relative to ERBE. Since the observed cloud response is strongly correlated with changes in high cloud amount, Jeff concluded that the high-cloud ice water concentrations are too low. He recommended moving to prognosing the phase of condensed water as well as its total amount.

Byron Boville addressed the issue of the cold tropopause bias in CAM. He showed that the cold bias of 6K is independent of dynamical core and is present in January and July. He used a radiative equilibrium model to infer the changes in radiative heating required to eliminate the bias and found that an increase of 0.1 K/day between 80-300mb would be sufficient. He also found that increases in condensed water path by 0.2 g/m^2 in high cloud would warm the tropopause by 3K. Based upon these sensitivity studies, he recommended that future modifications include the latent heat of fusion, better continuity of stratiform cloudiness, and explicit prognostic treatment of cloud phase.

Bruce Briegleb used results from the CCSM2 polar atmosphere simulation to suggest ways to reduce the warm surface temperature bias at high latitudes during winter. The results indicate that low cloud amount over the arctic is overestimated by 50% compared to Warren's cloud atlas. The downwelling longwave is overestimated by 20 W/m^2 and the downwelling shortwave underestimated by 40 W/m^2 compared to ECMWF analysis for January. Bruce recommended that we attempt to reduce the low cloud amount to eliminate these biases.

New modeling initiatives:

Leo Donner presented evidence that his convection scheme may alter the simulation of the MJO and ITCZ structure. Early results from the GFDL AM2 model indicate that precipitation patterns are changed considerably with the introduction of the Donner scheme, although the ITCZ was not as well-developed as originally hoped. The scheme differs from other cumulus parameterizations in its inclusion of mesoscale circulations, PDFs of entrainment coefficients, and a tendency closure. Leo plans to continue experimentation with the Donner convection scheme in CAM2.

Fabrizio Sassi discussed preliminary simulations with the Whole Atmosphere Community Climate Model (WACCM) with interactive chemistry. The simulations showed clearly that the bias in tropopause temperatures are producing an unrealistic simulation of the water vapor tape recorder and leading to dehydration of the stratosphere and mesosphere. The resulting biases in HOX can make it difficult to reproduce the mesosphere ozone temperature. Cold biases in the arctic stratosphere lead to denitrification, creation of NAD, and the formation of an ozone hole. In discussion, Byron Boville noted that the bias in polar stratospheric temperatures may result from an underestimation of gravity wave drag, which was tuned for a different dynamical core.

Phil Duffy presented results from high-resolution, untuned integrations of CAM at T170 and T239 resolution. He analyzed the changes in the simulations relative to T42 using Taylor diagrams. Generally, increased resolution reduced pattern errors in all twenty quantities he studied, particularly when the model was run at T239. There was significant improvement in DJF precipitation and much more realistic regional distribution of precipitation over the continental U.S.

Xiaoqing Wu concluded the breakout session with a report on his work with cumulus momentum transport (CMT) in CAM. The zonal-mean distribution of precipitation in the Atlantic and Pacific seems to be more realistic with the incorporation of CMT, and the seasonal migration of precipitation across the equator is apparently closer to observations. Xiaoqing concluded with his plan to extend this work to other GCM modeling efforts.

Participant List

Jeffrey

Anderson

NOAA-GFDL

jla at ucar.edu

David

Bader

US Department Of Energy

dave.bader at science.doe.gov

Jason

Bell

University of California, Santa Cruz

jbell at es.ucsc.edu

John

Bergman

NOAA

jwb at cdc.noaa.gov

Thomas

Bettge

NCAR

bettge at ucar.edu

Uma

Bhatt

IARC Frontier  U. of Alaska Fairbanks

bhatt at iarc.uaf.edu

Cecilia

Bitz

University of Washington

bitz at apl.washington.edu

Maurice

Blackmon

NCAR

blackmon at cgd.ucar.edu

Byron

Boville

NCAR

boville at ucar.edu

Francis

Bretherton

University of Wisconsin

fbrether at concentric.net

Christopher

Bretherton

University of Washington

breth at atmos.washington.edu

David

Bromwich

The Ohio State University

bromwich.1 at osu.edu

Lawrence

Buja

NCAR

southern at ucar.edu

Julie

Caron

NCAR

jcaron at ucar.edu

Ping

Chang

Texas A & M University

ping at ocean.tamu.edu

Shaoping

Chu

Los Alamos National Laboratory

spchu at lanl.gov

William

Collins

NCAR

wcollins at ucar.edu

Andrew

Conley

NCAR

aconley at ucar.edu

Aiguo

Dai

NCAR

adai at ucar.edu

Cecelia

DeLuca

NCAR

cdeluca at ucar.edu

Leo

Donner

Princeton University

ljd at gfdl.noaa.gov

John

Drake

Oak Ridge National Laboratory

drakejb at ornl.gov

Philip

Duffy

Lawrence Livermore National Lab

pduffy at llnl.gov

Mark

Eakin

NOAA National Geophysical Data Center

mark.eakin at noaa.gov

Brian

Eaton

NCAR

eaton at ucar.edu

David

Erickson

Oak Ridge National Laboratory

ericksondj at ornl.gov

Jay

Fein

National Science Foundation

jfein at nsf.gov

David

Fillmore

NCAR

fillmore at ucar.edu

Balasubramian

Govindasamy

Lawrence Livermore National Lab

bala at llnl.gov

James

Hack

NCAR

jhack at ucar.edu

Andrea

Hahmann

University of Arizona

hahmann at atmo.arizona.edu

Howard

Hanson

Los Alamos National Laboratory

hph at lanl.gov

Isaac

Held

NOAA

ih at gfdl.gov

Matthew

Huber

DCESS Niels Bohr Institute

rop at dcess.ku.dk

James

Hurrell

NCAR

jhurrell at ucar.edu

Michael

Iacono

Atmospheric and Environmental Research Inc.

mike at aer.com

S-J.

Lin

NASA GSFC

lin at dao.gsfc.nasa.gov

Jasmin

John

University of California, Berkeley

jjohn at uclink4.berkeley.edu

Marat

Khairoutdinov

Colorado State University

marat at atmos.colostate.edu

Jeffrey

Kiehl

NCAR

jtkon at ucar.edu

Erik

Kluzek

NCAR

erik at ucar.edu

Zavareh

Kothavala

McMaster University

zav at ucar.edu

Natalie

Mahowald

University of California, Santa Barbara

natalie at bren.ucsb.edu

Philip

Merilees

Naval Research Laboratory

merilees at nrlmry.navy.mil

Arthur

Mirin

Lawrence Livermore National Lab

mirin at llnl.gov

Mitchell

Moncrieff

NCAR

moncrief at ucar.edu

Richard

Moritz

University of Washington

dickm at apl.washington.edu

Joel

Norris

Scripps Institution of Oceanography

jrnorris at ucsd.edu

Keith

Oleson

NCAR

oleson at ucar.edu

Jerry

Olson

NCAR

olson at ncar.ucar.edu

David

Pierce

Scripps Institution of Oceanography

dpierce at ucsd.edu

Gerald

Potter

Lawrence Livermore National Lab

gpotter at llnl.gov

William

Putman

SAIC - NASA GSFC

wputman at dao.gsfc.nasa.gov

David

Randall

Colorado State University

randall at redfish.atmos.colostate.edu

Philip

Rasch

NCAR

pjr at ucar.edu

Todd

Ringler

Colorado State University

todd at atmos.colostate.edu

Raymond

Roble

NCAR

roble at ucar.edu

James

Rosinski

NCAR

rosinski at ucar.edu

Douglas

Rotman

Lawrence Livermore National Lab

drotman at llnl.gov

Fabrizio

Sassi

NCAR

sassi at ncar.ucar.edu

Edwin

Schneider

COLA

schneide at cola.iges.org

Anji

Seth

Columbia University

seth at iri.columbia.edu

Lisa

Sloan

University of California, Santa Cruz

lcsloan at es.ucsc.edu

Mark

Stevens

NCAR

stevens at ucar.edu

Karl

Taylor

Lawrence Livermore National Lab

taylor13 at llnl.gov

Kevin

Trenberth

NCAR

trenbert at ucar.edu

Joseph

Tribbia

NCAR

tribbia at ucar.edu

John

Truesdale

NCAR

jet at ncar.ucar.edu

Michael

Wehner

Lawrence Livermore National Lab

mwehner at llnl.gov

David

Williamson

NCAR

wmson at ucar.edu

Xiaoqing

Wu

NCAR

xiaoqing at ucar.edu

Yoshikatsu

Yoshida

Central Research Institute of Electric Power Industry

yyoshida at criepi.denken.or.jp

Hongbin

Yu

Georgia Institute of Technology

yu at breeze.eas.gatech.edu

Charles

Zender

University of California, Irvine

zender at uci.edu

Xubin

Zeng

University of Arizona

xubin at atmo.arizona.edu

Guang

Zhang

Scripps Institution of Oceanography

gzhang at ucsd.edu