Preprints
https://doi.org/10.5194/gmd-2020-228
https://doi.org/10.5194/gmd-2020-228
Submitted as: model experiment description paper
 | 
05 Aug 2020
Submitted as: model experiment description paper |  | 05 Aug 2020
Status: this preprint has been withdrawn by the authors.

System identification techniques for detection of teleconnections within climate models

Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang

Abstract. Quantifying teleconnections and discovering new ones is a complex, difficult process. Using transfer functions, we introduce a new method of identifying teleconnections in climate models on arbitrary timescales. We validate this method by perturbing temperature in the Nino3.4 region in a climate model. Temperature and precipitation responses in the model match known El Nino-Southern Oscillation (ENSO)-like teleconnection features, consistent with modes of tropical variability. Perturbing the Nino3.4 region results in temperature responses consistent with the Pacific Meridional Mode, the Pacific Decadal Oscillation, and the Indian Ocean Dipole, all of which have strong ties to ENSO. Some precipitation features are also consistent with these modes of variability, although because precipitation is noisier than temperature, obtaining robust responses is more difficult. While much work remains to develop this method further, transfer functions show promise in quantifying teleconnections or, perhaps, identifying new ones.

This preprint has been withdrawn.

Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang

Interactive discussion

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Status: closed
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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang
Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang

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This preprint has been withdrawn.

Short summary
Through a cascade of physical mechanisms, a change in one location can trigger a response in a different location. These responses and the mechanisms that cause them are difficult to detect. Here we propose a method, using global climate models, to detect possible relationships between changes in one region and responses throughout the globe caused by that change. A change in the Pacific ocean is used as a test case to determine the effectiveness of the method.