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Article . 2004 . Peer-reviewed
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Empirical‐statistical downscaling in climate modeling

Authors: R. E. Benestad;

Empirical‐statistical downscaling in climate modeling

Abstract

Research into possible impacts of a climate change requires descriptions of local and regional climate. For instance, the local and regional aspect of a climate change is stressed in the U.S. Strategic Plan for the Climate Change Science Program (CCSP) (http://www.climate‐science.gov/Library/stratplan2003/default.htm). Global climate models (GCMs) are important tools for studying climate change and making projections for the future. Although GCMs provide realistic representations of large‐scale aspects of climate, they generally do not give good descriptions of the local and regional scales. It is nevertheless possible to relate large‐scale climatic features to smaller spatial scales.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
64
Top 10%
Top 10%
Top 10%
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