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Cited by 344

The DOI matches its Crossref record; 115 of the 115 references it cites were found in a registry or an index.

MJO Simulation Diagnostics

Open access
·2009·Journal of Climate
DOI 10.1175/2008jcli2731.1
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Abstract

The Madden–Julian oscillation (MJO) interacts with and influences a wide range of weather and climate phenomena (e.g., monsoons, ENSO, tropical storms, midlatitude weather), and represents an important, and as yet unexploited, source of predictability at the subseasonal time scale. Despite the important role of the MJO in climate and weather systems, current global circulation models (GCMs) exhibit considerable shortcomings in representing this phenomenon. These shortcomings have been documented in a number of multimodel comparison studies over the last decade. However, diagnosis of model performance has been challenging, and model progress has been difficult to track, because of the lack of a coherent and standardized set of MJO diagnostics. One of the chief objectives of the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group is the development of observation-based diagnostics for objectively evaluating global model simulations of the MJO in a consistent framework. Motivation for this activity is reviewed, and the intent and justification for a set of diagnostics is provided, along with specification for their calculation, and illustrations of their application. The diagnostics range from relatively simple analyses of variance and correlation to more sophisticated space–time spectral and empirical orthogonal function analyses. These diagnostic techniques are used to detect MJO signals, to construct composite life cycles, to identify associations of MJO activity with the mean state, and to describe interannual variability of the MJO.

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Metadata

Venue
Journal of Climate
Publisher
American Meteorological Society
Published
2009-06-01
Volume
22
Issue
11
Pages
3006-3030
ISSN
  • 0894-8755 (ISSN-L)
  • 1520-0442
DOI
10.1175/2008jcli2731.1
OpenAlex
W2102827053
Cited by
344
References
115
FWCI
12.05
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.