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Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Published on: December 12, 2013
Stratospheric memory and skill of extended-range weather forecasts
Mark P Baldwin1, David B Stephenson, David W J Thompson
1Northwest Research Associates, 14508 NE 20th Street, Bellevue, WA, 98007, USA.
Science (New York, N.Y.)
|August 2, 2003
Summary
We developed a statistical model for extended-range Arctic Oscillation (AO) forecasts. Forecast skill, especially in winter, relies on persistent stratospheric circulation anomalies influencing the troposphere.
Area of Science:
- Atmospheric Science
- Climate Dynamics
- Meteorology
Background:
- The Arctic Oscillation (AO) is a key climate pattern influencing Northern Hemisphere weather.
- Predicting the AO on extended ranges remains a challenge.
Purpose of the Study:
- To demonstrate skill in extended-range forecasting of the monthly-mean Arctic Oscillation (AO).
- To identify the mechanisms driving AO predictability.
Main Methods:
- Utilized an empirical statistical model.
- Analyzed persistent circulation anomalies in the lowermost stratosphere.
- Compared Arctic and Southern Hemisphere predictability.
Main Results:
- Significant skill was demonstrated in extended-range AO forecasts.
- Forecast skill is greatest during boreal winter.
- Predictability depends on persistent circulation anomalies above the tropopause.
Conclusions:
- Persistent stratospheric anomalies are crucial for AO predictability.
- These anomalies likely influence the troposphere via upper-troposphere wave changes.
- The findings enhance understanding of atmospheric teleconnections and climate prediction.
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