Implementation Plan for CCSM 4 CCSM 4 needs to be ready by the end of 2008 for AR5 in early 2013.

Most important items to address for CCSM 4 Physical biases in CCSM 3. Double ITCZ, ENSO frequency, continental precipitation, high latitude land temperatures, too large windstress, and too much Arctic low cloud. CCSM 4 should have some form of carbon cycle. The indirect effects of aerosols should be included, which were omitted in CCSM 3.

HadiSST data set

B Changes to FV deep convection scheme and momentum transport due to convection

Strategy Preliminary carbon cycle run in CSM 1. Updated carbon cycle now in CCSM 3. Biggest possibility of severe failure is combining updated carbon cycle with the new physical components in CCSM 4. This process needs to be done in stages, and not left until sometime in Propose a three stage strategy.

Stage 1 – starts on 1 March 2007 BGC land is CLM-CN; results of C-LAMP Aerosol indirect effect scheme: NOT NOW. Atmosphere: updated version of the FV Land: Community Hydrology Project Ocean: POP 2 base code plus updates Sea Ice: merged CICE4 and CSIM4 codes Resolution: FV 1.9x2.5, ocean x1 Significant advance on current BGC control runs in the T31x3 CCSM 3

Stage 2 – complete by end of 2007 Developments in all components designed to reduce the significant CCSM 3 biases. Include in prognostic mode the land ice component being worked on by Lipscomb. Why so early? I’m afraid if we say June 2008, then won’t be ready by end of CAM should just include the troposphere. Not include interactive chemistry. This was controversial – include time slices?

Stage 3 – complete by end of is year to validate and understand CCSM 4 that includes BGC, indirect aerosol effects, and land ice component. Target resolution? FV 1.9x2.5 for carbon cycle – higher resolution for short-term simulations: FV 1x1.25, x1 Ocean? Many questions: eg. should CCSM 4 have a dynamic biogeography component? Low resolution Paleo version also in 2008; this might still be the T31x3 version?

Potential Failure Points Not ready for Stage 1 by 1 March If slippage is only few months, then proceed. Timeline for Stage 2 slips. Again, if only a few months, then it’s probably okay. Timeline for Stage 2 slips by > 6 months. Then, a backup is to use the Stage 1 version for CCSM 4 with possible updates. If the IPCC AR5 schedule slips, then the Stage 2 & 3 timelines can slip by the same amount. This would be nice, but unlikely?

Verification and IPCC AR5 Runs CCSM 3 defined by present day control run. Should change to verify CCSM 4 by how well it simulates the climate of the 20 th Century? If so, then we should definitely radiatively balance a 1870, not present day, control run. This requires more runs for verification. Vary the time interval between starting the 20 th century runs from the 1870 control run. Number of scenarios versus ensemble size?

Resources Needed Computer resources: NCAR resources planned to be x3 larger by end of Oak Ridge plans to upgrade the Cray XT3 to a 250 TF system by the end of I estimate the computer cost of proposed CCSM 4 is times the CCSM 3. If chemistry component not included for AR5, then computer resources seem okay. However, need more software engineers; restore CSEG to level at the end of 2004.

Short-Term Simulations Using the Community Climate System Model Background Discussed at several past CAB meetings, especially by Eric Sundquist and Tom Crowley at CAB meeting February The issue came up again at the SSC/CAB/ WG Cochairs meeting in Breckenridge. There was extensive discussion of short -term climate simulations at the Aspen WGCM/AIMES Workshop held in August. CGD discussion on Monday, 6 Nov 2006.

Short-Term Simulations: Proposed Form Start in about 1980, then run in pure simulation or simulation/assimilation mode until The short-term simulation would be from 2006 to Need an ensemble size of >10 to address extremes. Does it make an important difference if the CCSM is initialized to the actual climate of 2005? This requires data assimilation into the ocean, and possibly sea ice extent. Do we need to initialize the tropical Pacific for ENSO and N Atlantic for MOC?

Blue: T85,  1 Red: T42,  1 Black: T31,  3 CCSM3: Present Day Control Runs Maximum MOC in North Atlantic

Increases in Global Ocean Temps (Results from CCSM3 Ensemble) Gent et al, J Climate 11, CCSM3 Special Issue, 2006 L = Levitus et al (2005) Ensemble Members

Advantages of Short-Term Simulations Because the runs are short, the atmosphere model can be run at higher resolution: produces relevant regional information for the relatively near-term. Most of the climate change is already committed, so the projections are much less dependent on the highly uncertain future greenhouse gas scenarios. There is a much smaller range between models in their transient climate response, so that the multi- model ensemble is less dependent on the quite wide range of sensitivities among climate models.

Projections for Arctic Land Temp

Challenges of Short-Term Simulations No experience so far with assimilating data into the CCSM ocean and sea ice components, or with coupled model assimilation as at Hadley Centre. Should run chemistry in prognostic mode or with time slices? Should carbon cycle be included? This increases the CCSM project workload as these S-T simulations would be in addition to the more familiar, long future scenario runs planned for CCSM4 that includes a form of carbon cycle.

Scientific Opportunities Runs without and with data assimilation between could be used to address the decadal timescale predictability of the climate system. Stimulus for multi-scale modeling activities, eg very high resolution one-way downscaling over the U.S.A. What is impact on SST biases in the upwelling regions? Changes in extremes, eg heat waves, floods, droughts. Atmospheric chemistry component added; simulations of air pollution (aerosols, ozone) in major urban areas.

Scientific Opportunities II Assessment of aerosol forcing compared with ongoing observations may allow a better understanding of aerosol climate forcing, and hence climate sensitivity. Better representation of soil, topographic, vegetation controls of carbon cycle; different permafrost classes. S-t runs emphasize human-induced land use changes, which requires use of the dynamic vegetation module. Mineral aerosols might help sort out the importance of human versus natural controls of dust emissions.