Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 472

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

ENSO and Extreme Rainfall Events in South America

Grimm, Alice M., Tedeschi, Renata G.·2009·Journal of Climate

Abstract

The influence of the opposite phases of ENSO on the frequency of extreme rainfall events over South America is analyzed for each month of the ENSO cycle on the basis of a large set of daily station rainfall data and compared with the influence of ENSO on the monthly total rainfall. The analysis is carried out with station data and their gridded version and the results are consistent. Extreme events are defined as 3-day mean precipitation above the 90th percentile. The mean frequencies of extreme events are determined for each month and for each category of year (El Niño, La Niña, and neutral), and the differences between El Niño and neutral years and La Niña and neutral years are computed. Changes in the mean intensity of extreme events are also investigated. Significant ENSO signals in the frequency of extreme events are found over extensive regions of South America during different periods of the ENSO cycle. Although ENSO-related changes in intensity show less significance and spatial coherence, there are some robust changes in several regions, especially in southeastern South America. The ENSO-related changes in the frequency of extreme rainfall events are generally coherent with changes in total monthly rainfall quantities. However, significant changes in extremes are much more extensive than the corresponding changes in monthly rainfall because the highest sensitivity to ENSO seems to be in the extreme range of daily precipitation. This is important, since the most dramatic consequences of climate variability result from changes in extreme events. The pattern of frequency changes produced by El Niño and La Niña episodes with respect to neutral years is roughly symmetric, but there are several examples of nonlinearity in the ENSO regional teleconnections.

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 · 10.1175/2008jcli2429.1

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Cited by

See all 472

Metadata

Authors
Grimm, A. M., & Tedeschi, R. G.
Venue
Journal of Climate
Published
2009-04-01
Volume
22
Issue
7
Pages
1589-1609
ISSN
  • 0894-8755 (ISSN-L)
  • 1520-0442
OpenAlex
W2006265919
Cited by
472
References
1
FWCI
7.64
Type
journal article
Language
en
Open access
closed

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

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.