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Improving the Effectiveness of U.S. Climate Modeling (2001)

Chapter: Color Plates

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Suggested Citation:"Color Plates." National Research Council. 2001. Improving the Effectiveness of U.S. Climate Modeling. Washington, DC: The National Academies Press. doi: 10.17226/10087.
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PLATE 1 Amdahl’s Law: Impact of the number of processors (axis labeled p) on the parallel efficiency (vertical axis) for a range of code parallelization (axis labeled x), between 90% and the ideal but unattainable 100%. a) Multiprocessing system with a number of processors between 1 and 32. Note that the greenish area, representing practically attainable efficiencies, ranges from over 20% for low parallelization to well over 50% for high parallelization. b) Massively parallel processor, with 40 to 1024 processors. Note that the attainable ranges of efficiency are well below 10% except for the hard-to-reach highest ranges of code parallelization (over 99%).

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Suggested Citation:"Color Plates." National Research Council. 2001. Improving the Effectiveness of U.S. Climate Modeling. Washington, DC: The National Academies Press. doi: 10.17226/10087.
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PLATE 2 a. Terrain over North America on a model grid at 240 km horizontal resolution. b. Terrain over North America on a model grid at 30 km horizontal resolution. (Provided by M. Blackmon)

Page 129 Cite
Suggested Citation:"Color Plates." National Research Council. 2001. Improving the Effectiveness of U.S. Climate Modeling. Washington, DC: The National Academies Press. doi: 10.17226/10087.
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Page 130 Cite
Suggested Citation:"Color Plates." National Research Council. 2001. Improving the Effectiveness of U.S. Climate Modeling. Washington, DC: The National Academies Press. doi: 10.17226/10087.
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Information derived from climate modeling has become increasingly important in recent years. More and more we understand that climate variability and change impacts society and that dealing with climate-related disasters, conflicts, and opportunities requires the best possible information about the past, present, and future of the climate system. To this end, Improving the Effectiveness of U.S. Climate Modeling describes ways to improve the efficacy of the U.S. climate modeling enterprise, given the current needs and resources. It discusses enhanced and stable resources for modeling activities, focused and centralized operational activities, how to give researchers access to the best computing facilities, the creation of a common modeling and data infrastructure, and research studies on the socioeconomic aspects of climate and climate modeling.

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