This figure depicts a short simulation from the Parallel Climate Model (PCM). For the atmosphere, the figure shows vectors depicting the winds in the lowest model layer, and shows the sea level pressure as lines of constant pressure. The surface temperatures are shown in color, and the sea ice is shown in grayscale

Warren Washington and Gerald Meehl, National Center for Atmospheric Researchz
Albert Semtner, Naval Postgraduate School
John Weatherly, U.S. Army Cold Regions Research and Engineering Laboratory

Research Objectives
The main purpose of this research is to use the Parallel Climate Model (PCM) for studies of anthropogenically forced climate change simulations with higher resolution and more detailed model components. Because it is difficult to separate anthropogenic climate change from natural climate variability, it is necessary to carry out ensembles of simulations in order to statistically find the climate change signal.

Computational Approach
Ocean model component: Through collaboration among LANL, NPS, and NCAR, we have developed an ocean component that uses the finite difference Parallel Ocean Program (POP) with a displaced north pole. This model was modified from the original average resolution of 2/3° latitude and longitude to allow increased latitudinal resolution near the equator of approximately 1/2°. Also, because of the displaced pole, there is high horizontal resolution in the eastern North Pacific, in the Arctic Straits near northern Canada and Greenland, and the Gulf Stream area. The continents and bottom topography were carefully modified so as to obtain the correct volume transport flow in many regions through the globe. The model in its present form yields an extraordinary simulation of the Arctic Ocean, tropical Pacific, and boundary currents such as the Gulf Steam, with eddies. POP has recently been reformulated in terms of data structures and the use of memory and cache for enhanced performance in a message passing environment. Also, many additional model physics options have been added to improve the model's fidelity.

Sea ice model component: This model component is entirely new. The thermodynamic part of the model uses the physics from the C. Bitz University of Washington ice model, which allows an unusually high level of detail, including five or more ice thickness categories and elaborate surface treatment of snow and sea ice melt physics. Recently, an option for using elastic-viscous-plastic physics has been added, using the E. Hunke and J. Dukowicz approach to the solution of the ice dynamics.

Atmospheric model component: The atmospheric component is the massively parallel version of the NCAR Community Climate Model version 3 (CCM3). This state-of-the-art model includes the latest versions of radiation, boundary physics, and precipitation physics. We use a T42 version (approximately 2.5°) for most of the simulations and will run a single simulation at T85 (approximately 1.25°) — the highest resolution climate change simulation ever attempted.

Flux Coupler: The method of tying the components together and allowing the exchange of fluxes and variables is the flux coupler. Since the component grids are different, there is an interpolation scheme for passing information between the atmosphere component grid and the ocean/sea ice grid that has been developed by P. Jones of LANL. The interpolation algorithm has been designed to run efficiently on distributed memory architectures. Recently, Chris Ding and collaborators at NERSC have improved the performance of the flux coupler on parallel computers.

Higher resolution atmosphere, ocean, and sea-ice models give more realistic simulations, but the computer time required for climate change scenarios prohibits conducting many experiments at higher resolution. We anticipate that the component interfacing through the flux coupler will be sufficiently flexible to handle a large range of resolutions. Therefore, the ongoing DOE-supported high resolution models can use the same structure as lower resolution models.

Accomplishments
Over the past year we have accomplished a large ensemble set of simulations, showing the global climate changes due to increased greenhouse gases and changes in sulfate aerosols, for the years 1870—2100. We believe this is the largest set of climate change simulations with state-of-the-art models in the United States. We have continued to develop improved versions of the coupled model that include better sea ice and ocean components and a river transport component. Because of the importance of regional aspects of climate change, we have developed a higher resolution atmosphere model component that has a better definition of the continents-ocean boundaries as well as an improved treatment of mountains.

The archive of PCM simulation data sets has been made available to a wide community, including the Intergovernmental Panel on Climate Change (IPCC), the U.S. National Assessment of the Potential Consequences of Climate Variability and Change, and various model intercomparison projects, including the DOE Program for Climate Model Diagnosis and Intercomparison (PCMDI).

Significance
The DOE Climate Change Prediction Program is focused on developing, testing and applying climate simulation and prediction models that stay at the leading edge of scientific knowledge and computational technology. The intent is to increase dramatically both the accuracy and throughput of computer model-based predictions of future climate system response to the increased concentrations of greenhouse gases on decadal and longer time scales. In the Kyoto protocol, there are several climate change scenarios with emissions of greenhouse gases and sulfate aerosols that must be completed for the U.S. National Assessment.

Publications
A. J. Semtner, "Ocean and climate modeling on advanced parallel computers: Progress and prospects," Communications of the ACM (in press).

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

http://www.cgd.ucar.edu/pcm/