Climate Dynamics

, Volume 16, Issue 10, pp 755–774

Parallel climate model (PCM) control and transient simulations

Authors

  • W. M. Washington
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • J. W. Weatherly
    • US Army Cold Regions Research and Engineering Laboratory (CRREL), USA
  • G. A. Meehl
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • A. J. Semtner Jr.
    • US Naval Postgraduate School (NPS), USA
  • T. W. Bettge
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • A. P. Craig
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • W. G. Strand Jr.
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • J. Arblaster
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • V. B. Wayland
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • R. James
    • National Center for Atmospheric Research (NCAR), 1850 Table Mesa Drive, Boulder, CO 80307, USA E-mail: wmw@ucar.edu
  • Y. Zhang
    • US Naval Postgraduate School (NPS), USA

DOI: 10.1007/s003820000079

Cite this article as:
Washington, W., Weatherly, J., Meehl, G. et al. Climate Dynamics (2000) 16: 755. doi:10.1007/s003820000079

Abstract

 The Department of Energy (DOE) supported Parallel Climate Model (PCM) makes use of the NCAR Community Climate Model (CCM3) and Land Surface Model (LSM) for the atmospheric and land surface components, respectively, the DOE Los Alamos National Laboratory Parallel Ocean Program (POP) for the ocean component, and the Naval Postgraduate School sea-ice model. The PCM executes on several distributed and shared memory computer systems. The coupling method is similar to that used in the NCAR Climate System Model (CSM) in that a flux coupler ties the components together, with interpolations between the different grids of the component models. Flux adjustments are not used in the PCM. The ocean component has 2/3° average horizontal grid spacing with 32 vertical levels and a free surface that allows calculation of sea level changes. Near the equator, the grid spacing is approximately 1/2° in latitude to better capture the ocean equatorial dynamics. The North Pole is rotated over northern North America thus producing resolution smaller than 2/3° in the North Atlantic where the sinking part of the world conveyor circulation largely takes place. Because this ocean model component does not have a computational point at the North Pole, the Arctic Ocean circulation systems are more realistic and similar to the observed. The elastic viscous plastic sea ice model has a grid spacing of 27 km to represent small-scale features such as ice transport through the Canadian Archipelago and the East Greenland current region. Results from a 300 year present-day coupled climate control simulation are presented, as well as for a transient 1% per year compound CO2 increase experiment which shows a global warming of 1.27 °C for a 10 year average at the doubling point of CO2 and 2.89 °C at the quadrupling point. There is a gradual warming beyond the doubling and quadrupling points with CO2 held constant. Globally averaged sea level rise at the time of CO2 doubling is approximately 7 cm and at the time of quadrupling it is 23 cm. Some of the regional sea level changes are larger and reflect the adjustments in the temperature, salinity, internal ocean dynamics, surface heat flux, and wind stress on the ocean. A 0.5% per year CO2 increase experiment also was performed showing a global warming of 1.5 °C around the time of CO2 doubling and a similar warming pattern to the 1% CO2 per year increase experiment. El Niño and La Niña events in the tropical Pacific show approximately the observed frequency distribution and amplitude, which leads to near observed levels of variability on interannual time scales.

Copyright information

© Springer-Verlag Berlin Heidelberg 2000