February 28, 2007
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FROM VOLUME 5, NUMBER 9, SEPTEMBER 1992
Computer Hardware, Advanced Mathematics and Model Physics [CHAMMP]:
Pilot Project Final Report (DOE/ER-0541T), U.S. Dept. Energy Off. Energy
Res., 122 pp., May 1992. Available to DOE and its contractors from Off. Sci.
Tech. Info., POB 62, Oak Ridge TN 37831 (615-576-8401; inquire for price), to
others from NTIS.
CHAMMP was launched in 1990 to utilize the emerging capabilities of
massively parallel scientific computers for regional-scale predictions of
decade-to-century climate change. This report is a compilation of 15 papers
describing pilot CHAMMP projects that were carried out to identify the principal
challenges and to involve new scientific computing expertise.
Implementation and Validation of Improved Landsurface Hydrology in an
Atmospheric General Circulation Model (NASA-CR-189488), K.D. Johnson (Mass.
Inst. Technol., Cambridge, Mass.), D. Entekhabi, P.S. Eagleson, 193 pp., Oct.
1991. NTIS: N92-13476/6; $26.
Two types of improvements in landsurface hydrological parameterization were
implemented in the NASA-GISS GCM, and tested. Runoff rate, especially in the
tropics, was improved with the new schemes, and the remaining components of the
heat and moisture balance showed comparable improvements when compared to
observations. The model performance was validated at a range of scales from
global down to smaller river basins.
Regional Climate Change Predictions from the Goddard Institute for
Space Studies High Resolution GCM (NASA-CR-190037), R.G. Crane (Penn. State
Univ., Univ. Park, Penn.), B.C. Hewitson, 54 pp., 1991. NTIS:
Describes a new diagnostic tool for examining relationships between the
synoptic-scale circulation and regional temperature distributions in GCMs.
Transfer function relationships are derived between observed synoptic
circulation and surface temperatures using principal components analysis and
multivariate regression models. Application of these functions to GCM
simulations indicates that there is considerable spatial bias present in the GCM
temperature distributions. The functions are also used to estimate the change in
regional temperatures expected in a doubled CO2 scenario.
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