The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Stratosphere–Troposphere Coupling and Links with Eurasian Land Surface Variability
Open accessAbstract
A diagnostic of Northern Hemisphere winter extratropical stratosphere–troposphere interactions is presented to facilitate the study of stratosphere–troposphere coupling and to examine what might influence these interactions. The diagnostic is a multivariate EOF combining lower-stratospheric planetary wave activity flux in December with sea level pressure in January. This EOF analysis captures a strong linkage between the vertical component of lower-stratospheric wave activity over Eurasia and the subsequent development of hemisphere-wide surface circulation anomalies, which are strongly related to the Arctic Oscillation. Wintertime stratosphere–troposphere events picked out by this diagnostic often have a precursor in autumn: years with large October snow extent over Eurasia feature strong wintertime upward-propagating planetary wave pulses, a weaker wintertime polar vortex, and high geopotential heights in the wintertime polar troposphere. This provides further evidence for predictability of wintertime circulation based on autumnal snow extent over Eurasia. These results also raise the question of how the atmosphere will respond to a modified snow cover in a changing climate.
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Cites
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Cited by
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Metadata
- Authors
- Cohen, J., Barlow, M., Kushner, P. J., & Saito, K.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2007-11-01
- Volume
- 20
- Issue
- 21
- Pages
- 5335-5343
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2099424815
- Cited by
- 339
- References
- 20
- FWCI
- 7.44
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
