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Computational science / Climate forcing / Global climate model / Global warming / Atmospheric model / Climate model / National Center for Atmospheric Research / Simulation / Atmospheric sciences / Climatology / Meteorology


Decadal Climate Simulations Using Accurate and Fast Neural Network Emulation of Full, Long- and Short Wave, Radiation
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Document Date: 2007-12-19 12:34:37


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File Size: 1,17 MB

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Company

SAIC / /

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Event

Environmental Issue / /

Facility

University of Maryland Michael S. Fox-Rabinovitz / /

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IndustryTerm

last decade new emerging neural network / neural networks / satellite retrieval procedures / generic tool / numerical algorithms / multi-scale systems / /

Organization

University of Maryland / Earth System Science Interdisciplinary Center / University of Maryland Corresponding / National Center for Atmospheric Research / National Oceanic and Atmospheric Administration / European Centre for Medium-range Weather Forecasting / /

Person

Camp Springs / Michael S. Fox-Rabinovitz / Vladimir M. Krasnopolsky / /

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Position

author / Bishop / representative data sets / representative / General / /

Product

NNs / /

ProvinceOrState

Maryland / /

PublishedMedium

Journal of Climate / Atmospheric Research / /

Technology

Radiation / Neural Network / machine learning / alternative numerical algorithms / simulation / /

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