Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 278

The DOI matches its Crossref record.

A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

Open access
Schubert, Siegfried, Gutzler, David, Wang, Hailan, Dai, Aiguo, Delworth, Tom, Deser, Clara, Findell, Kirsten, Fu, Rong, Higgins, Wayne, Hoerling, Martin, Kirtman, Ben, Koster, Randal, Kumar, Arun, Legler, David, Lettenmaier, Dennis, Lyon, Bradfield, Magana, Victor, Mo, Kingtse, Nigam, Sumant, Pegion, Philip, Phillips, Adam, Pulwarty, Roger, Rind, David, Ruiz-Barradas, Alfredo, Schemm, Jae, Seager, Richard, Stewart, Ronald, Suarez, Max, Syktus, Jozef, Ting, Mingfang, Wang, Chunzai, Weaver, Scott, Zeng, Ning·2009·Journal of Climate

Abstract

The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models. It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1175/2009jcli3060.1

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 278

Metadata

Authors
Schubert, S., Gutzler, D., Wang, H., Dai, A., Delworth, T., Deser, C., Findell, K., Fu, R., Higgins, W., Hoerling, M., Kirtman, B., Koster, R., Kumar, A., Legler, D., Lettenmaier, D., Lyon, B., Magana, V., Mo, K., Nigam, S., Pegion, P., Phillips, A., Pulwarty, R., Rind, D., Ruiz-Barradas, A., Schemm, J., Seager, R., Stewart, R., Suarez, M., Syktus, J., Ting, M., Wang, C., Weaver, S., & Zeng, N.
Venue
Journal of Climate
Published
2009-10-01
Volume
22
Issue
19
Pages
5251-5272
ISSN
  • 0894-8755 (ISSN-L)
  • 1520-0442
OpenAlex
W2026413132
Cited by
278
References
0
FWCI
17.68
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results. https://app.cochat.ai/papers/10.1175/2009jcli3060.1
The paper
Schubert, S., Gutzler, D., Wang, H., Dai, A., Delworth, T., Deser, C., Findell, K., Fu, R., Higgins, W., Hoerling, M., Kirtman, B., Koster, R., Kumar, A., Legler, D., Lettenmaier, D., Lyon, B., Magana, V., Mo, K., Nigam, S., . . . Zeng, N. (2009). A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results. Journal of Climate. https://doi.org/10.1175/2009jcli3060.1

Data sources

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.