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Cited by 232

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PRUDENCE employs new methods to assess European climate change

Open access
Christensen, Jens Hesselbjerg, Carter, Timothy R., Giorgi, Filippo·2002·Eos, Transactions American Geophysical Union

Abstract

Both decision‐makers and the general public need detailed information on future climate to evaluate the risks associated with possible climate change due to anthropogenic emissions of greenhouse gases. Projections of future climate change already exist, but they are deficient, in terms of both the characterization of their uncertainties and their regional detail. To date, the assessment of potential impacts of climate change has generally relied on projections from simple climate models or coarse resolution coupled Atmosphere‐Ocean General Circulation Models (AOGCMs). The former include, at best, only a limited physical representation of the climate system. The latter are unable to resolve processes occurring at scales of less than ∼300 km. This resolution limitation precludes the simulation of realistic extreme events and the detailed spatial structure of variables like temperature and precipitation over regions characterized by heterogeneous surfaces. Typical examples of such regions are mountainous areas such as the Alps or Scandinavia or coastal zones, and areas surrounding inland seas, such as the Mediterranean and Baltic.

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Metadata

Authors
Christensen, J. H., Carter, T. R., & Giorgi, F.
Venue
Eos, Transactions American Geophysical Union
Published
2002-03-26
Volume
83
Issue
13
Pages
147-147
ISSN
  • 0096-3941 (ISSN-L)
  • 2324-9250
OpenAlex
W2106250023
Cited by
232
References
0
FWCI
10.90
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: PRUDENCE employs new methods to assess European climate change. https://app.cochat.ai/papers/10.1029/2002eo000094
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Christensen, J. H., Carter, T. R., & Giorgi, F. (2002). PRUDENCE employs new methods to assess European climate change. Eos, Transactions American Geophysical Union. https://doi.org/10.1029/2002eo000094

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.