Abstract ID: 012
Precursory Signals in the Stratospheric Meridional Mass Circulation for Mid-Latitude Cold Air Outbreak Events of High and Low Sub-Seasonal Predictability
Lead Author: Yueyue Y
Nanjing University of Information Science and Technology, China
Keywords: cold air outbreak event, stratosphere
Abstract: Using the NCEP reforecast data (1999–2010) and NCEP’s CFSv2 real-time forecast data (2012–2019) from the S2S (Sub-seasonal to Seasonal) project, we evaluated the sub-seasonal skill by the CFSv2 model with respect to mid-latitude cold air outbreak events (CAOs) in winter (November–February) and investigated the distinct features of the anomalies of surface temperature, stratospheric mass circulation, and wave activities between the top 11 “high-skill” CAO events and the top 10 “low-skill” events. Results show that the predictability limit tends to be longer for wide-impact and long-lasting CAOs occurred in Eurasia or both continents, but such tendency is not very robust. The model possesses a better sub-seasonal skill when there is generally stronger and longer-lasting equatorward cold air branch of isentropic meridional mass circulation, which is coupled with a stronger stratospheric poleward warm branch in the 3 weeks prior to the peak time of “high-skill” CAOs. The largest contrast between “high-skill” and “low-skill” CAOs lies in the wavenumber-1 component of stratospheric poleward warm branch. Both the amplitude in the middle stratosphere and vertically westward-tilting of wavenumber-1 waves in the lower stratosphere tend to be stronger (weaker) prior to “high-skill” (“low-skill”) CAOs, collaboratively contributing to the stronger (weaker) stratospheric poleward warm branch. The temporal evolution of intensity of stratospheric poleward warm branch, wave amplitude, and westward-tilting are better captured by CFSv2 model at sub-seasonal scale in the month before “high-skill” CAOs. These results reveal the important role of stratosphere–troposphere connection in determining the windows of opportunity for skillful sub-seasonal forecasts of CAOs.