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Improving weather and climate prediction with better representation of fast processes in atmospheric models
Many atmospheric processes that influence Earth's weather and climate occur at spatiotemporal scales that are too small to be resolved in large scale models. They must be parameterized, which means approximately representing them by variables that can be resolved by model grids.
Fast Processes in Large-Scale Atmospheric Models: Progress, Challenges and Opportunities explores ways to better investigate and represent multiple parameterized processes in models and thus improve their ability to make accurate climate and weather predictions.
Volume highlights include:
The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Yangang Liu, Brookhaven National Laboratory, USA.
Pavlos Kollias, Brookhaven National Laboratory and Stony Brook University, USA.
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