Improved Teleconnection-Based Dynamical Seasonal Predictions of Boreal Winter
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Date
2018-04-28
Publication Type
Journal Article
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Abstract
Climate and weather variability in the North Atlantic region is determined largely by the North Atlantic Oscillation (NAO). The potential for skillful seasonal forecasts of the winter NAO using an ensemble‐based dynamical prediction system has only recently been demonstrated. Here we show that the winter predictability can be significantly improved by refining a dynamical ensemble through subsampling. We enhance prediction skill of surface temperature, precipitation, and sea level pressure over essential parts of the Northern Hemisphere by retaining only the ensemble members whose NAO state is close to a “first guess” NAO prediction based on a statistical analysis of the initial autumn state of the ocean, sea ice, land, and stratosphere. The correlation coefficient between the reforecasted and observation‐based winter NAO is significantly increased from 0.49 to 0.83 over a reforecast period from 1982 to 2016, and from 0.42 to 0.86 for a forecast period from 2001 to 2017. Our novel approach represents a successful and robust alternative to further increasing the ensemble size, and potentially can be used in operational seasonal prediction systems.
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published
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Journal / series
Volume
45 (8)
Pages / Article No.
3605 - 3614
Publisher
American Geophysical Union
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Organisational unit
09612 - Domeisen, Daniela / Domeisen, Daniela
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Funding
170523 - Improving the Prediction of Sub-seasonal to Seasonal Weather and Climate – From Theory to Application (SNF)