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Summary of achievements

Peter spent the large majority of his time over the last year as Chairman of the CCSM Science Steering Committee. The CCSM project is in the middle of development of the next version of the model, CCSM4. This version will have many improvements in the physical components of the model. In addition, it will have an explicit carbon-nitrogen cycle component, a chemistry component, an upper atmosphere version, and a very early version of a land ice component. The CCSM is supposed to be ready by the end of 2008. It is Peter's and the steering comittee's job to oversee this development, and to assure that it is completed on time.

Publications

Danabasoglu, G. and P. Gent, 2009: Equilibrium Climate Sensitivity: Is It Accurate to Use a Slab Ocean Model? Journal of Climate, 22, 2494–2499, doi:doi:10.1175/2008JCLI2596.1..

Figure 1: High resolution figure

Abstract: The equilibrium climate sensitivity of a climate model is usually defined as the globally averaged equilibrium surface temperature response to a doubling of carbon dioxide. This is virtually always estimated in a version with a slab model for the upper ocean. The question is whether this estimate is accurate for the full climate model version, which includes a full-depth ocean component. This question has been answered for the low-resolution version of the Community Climate System Model, version 3 (CCSM3). The answer is that the equilibrium climate sensitivity using the full-depth ocean model is 0.14°C higher than that using the slab ocean model, which is a small increase. In addition, these sensitivity estimates have a standard deviation of nearly 0.1°C because of interannual variability. These results indicate that the standard practice of using a slab ocean model does give a good estimate of the equilibrium climate sensitivity of the full CCSM3. Another question addressed is whether the effective climate sensitivity is an accurate estimate of the equilibrium climate sensitivity. Again the answer is yes, provided that at least 150 yr of data from the doubled carbon dioxide run are used.

Figure Caption: Surface temperature from the end of runs for (a) SOM control and (b) full-depth ocean control, and difference in surface temperature for (c) SOM 2 × CO₂ - control and (d) full-depth ocean 2 × CO₂ - control.

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Gent, P.R., S.G. Yeager, R.B. Neale, S. Levis and D.A. Bailey. 2009: Improvements in a half degree atmosphere/land version of the CCSM. Climate Dynamics, 79, 25-58, doi:10.1007/s00382-009-0614-8.

Figure 2: High resolution figure

Abstract: A decadal climate projection between 1980 and 2030 using a nominal 0.5° resolution in the atmosphere and land components has been performed using the Community Climate System Model, version 3.5. The mean climate is compared to a companion simulation using a nominal 2° resolution in the atmosphere and land components. The increased atmosphere resolution has several benefits, and produces a significantly better mean climate. The maximum sea surface temperature biases in the major upwelling regions, including the West Coast of the USA, are reduced by more than 60%. Precipitation patterns are improved in the summer Asian monsoon, mostly due to the better resolved orography, and in the eastern tropical Pacific Ocean south of the equator. The improved precipitation patterns lead to better river flows in many rivers worldwide. The atmospheric circulation in the Arctic also improves, which leads to a better regional sea ice thickness distribution in the Arctic Ocean.

Figure caption: Annual mean Arctic sea ice thickness in meter from (a) 0.5° run, and (b) 2° run.

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Washington, W.M., J. Drake, L. Buja, D. Anderson, D. Bader, R. Dickinson, D. Erickson, P. Gent, S. Ghan, P. Jones and R. Jacob. 2008: SciDac 2008, the use of the Climate-science Computational end Station (CCES) development and grand challenge team for the next IPCC assessment: an operational plan. Journal of Physics Conference Series 125 012023, doi:10.1088/1742-6596/125/1/012024.

Figure 3: High resolution figure

Abstract: The grand challenge of climate change science is to predict future climates based on scenarios of anthropogenic emissions and other changes resulting from options in energy and development policies. Addressing this challenge requires a Climate Science Computational End Station consisting of a sustained climate model research, development, and application program combined with world-class DOE leadership computing resources to enable advanced computational simulation of the Earth system. This project provides the primary computer allocations for the DOE SciDAC and Climate Change Prediction Program. It builds on the successful interagency collaboration of the National Science and the U.S. Department of Energy in developing and applying the Community Climate System Model (CCSM) for climate change science. It also includes collaboration with the National Aeronautics and Space Administration in carbon data assimilation and university partners with expertise in high-end computational climate research.

Figure caption: Operational timeline.