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Cited by 498

The DOI matches its Crossref record.

Tropical drying trends in global warming models and observations

Open access
Neelin, J. D., Münnich, M., Su, H., Meyerson, J. E., Holloway, C. E.·2006·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.0601798103
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Abstract

Anthropogenic changes in tropical rainfall are evaluated in a multimodel ensemble of global warming simulations. Major discrepancies on the spatial distribution of these precipitation changes remain in the latest-generation models analyzed here. Despite this uncertainty, we find a number of measures, both global and local, on which reasonable agreement is obtained, notably for the regions of drying trend (negative precipitation anomalies). Models agree on the overall amplitude of the precipitation decreases that occur at the margins of the convective zones, with percent error bars of magnitude similar to those for the tropical warming. Similar agreement is found on a precipitation climate sensitivity defined here and on differential moisture increase inside and outside convection zones, a step in a hypothesized causal path leading to precipitation changes. A measure of local intermodel agreement on significant trends indicates consistent predictions for particular regions. Observed rainfall trends in several data sets show a significant summer drying trend in a main region of intermodel agreement: the Caribbean/Central-American region.

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Metadata

Authors
Neelin, J. D., Münnich, M., Su, H., Meyerson, J. E., & Holloway, C. E.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2006-04-18
Volume
103
Issue
16
Pages
6110-6115
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.0601798103
OpenAlex
W2107429431
Cited by
498
References
0
FWCI
14.60
Type
journal article
Language
en
Open access
green

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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.