Stratospheric modulation of Arctic Oscillation extremes as represented by extended-range ensemble forecasts

• Published in: Weather and Climate Dynamics
• Main Authors: J. Spaeth, T. Birner
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2022
• Subjects: Meteorology. Climatology; QC851-999; Arctic
• Online Access: https://doi.org/10.5194/wcd-3-883-2022; https://doaj.org/article/8adea8a7cf704e06a78ed866dc27d7a9

The Arctic Oscillation (AO) describes a seesaw pattern of variations in atmospheric mass over the polar cap. It is by now well established that the AO pattern is in part determined by the state of the stratosphere. In particular, sudden stratospheric warmings (SSWs) are known to nudge the tropospheric circulation toward a more negative phase of the AO, which is associated with a more equatorward-shifted jet and enhanced likelihood for blocking and cold air outbreaks in mid-latitudes. SSWs are also thought to contribute to the occurrence of extreme AO events. However, statistically robust results about such extremes are difficult to obtain from observations or meteorological (re-)analyses due to the limited sample size of SSW events in the observational record (roughly six SSWs per decade). Here we exploit a large set of extended-range ensemble forecasts within the subseasonal-to-seasonal (S2S) framework to obtain an improved characterization of the modulation of AO extremes due to stratosphere–troposphere coupling. Specifically, we greatly boost the sample size of stratospheric events by using potential SSWs (p-SSWs), i.e., SSWs that are predicted to occur in individual forecast ensemble members regardless of whether they actually occurred in the real atmosphere. For example, the S2S ensemble of the European Centre for Medium-Range Weather Forecasts gives us a total of 6101 p-SSW events for the period 1997–2021. A standard lag-composite analysis around these p-SSWs validates our approach; i.e., the associated composite evolution of stratosphere–troposphere coupling matches the known evolution based on reanalysis data around real SSW events. Our statistical analyses further reveal that following p-SSWs, relative to climatology, (1) persistently negative AO states ( >1 week duration) are 16 % more likely; (2) the likelihood for extremely negative AO states ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" ...