The predictors and forecast skill of Northern Hemisphere teleconnection patterns for lead times of 3-4 weeks

Jiaxin Black, Nathaniel C. Johnson, Stephen Baxter, Steven B. Feldstein, Daniel S. Harnos, Michelle L. L'Heureux

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The Pacific-North American pattern (PNA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are three dominant teleconnection patterns known to strongly affect December-February surface weather in the Northern Hemisphere. A partial least squares regression (PLSR) method is adopted in this study to generate wintertime two-week statistical forecasts of these three teleconnection pattern indices for lead times of up to five weeks over the 1980-2013 period. The PLSR approach generates forecasts for the teleconnection pattern indices by maximizing the variance explained by predictor indices determined as linear combinations of predictor fields, which include gridded outgoing longwave radiation (OLR), 300-hPa geopotential height (Z300), and 50-hPa geopotential height (Z50). Overall, the PLSR models yield statistically significant skill at all lead times up to five weeks. In particular, cross-validated correlations between the combined weeks 3-4 PLSR forecasts and verification for the PNA, NAO, and AO indices are 0.34, 0.28, and 0.41, respectively. The PLSR approach also allows the authors to isolate a small number of predictor patterns that help shed light on the sources of prediction skill for each teleconnection pattern. As expected, the results reveal the importance of tropical convection (OLR) for forecast skill in weeks 3-4, but the initial atmospheric flow (Z300) accounts for a substantial fraction of the skill as well. Overall, the results of this study provide promise for improving subseasonal-to-seasonal (S2S) forecasts and the physical understanding of predictability on these time scales.

Original languageEnglish (US)
Pages (from-to)2855-2877
Number of pages23
JournalMonthly Weather Review
Volume145
Issue number7
DOIs
StatePublished - Jul 1 2017

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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