Decadal Variation of the Impact of La Nina on the Winter Arctic Stratosphere

The impact of La Ni?a on the winter Arctic stratosphere has thus far been an ambiguous topic of research. Contradictory results have been reported depending on the La Ni?a events considered. This study shows that this is mainly due to the decadal variation of La Ni?a’s impact on the winter Arctic stratosphere since the late 1970 s. Specifically,during the period1951–78,the tropospheric La Ni?a teleconnection exhibits a typical negative Pacific–North America pattern,which strongly inhibits the propagation of the planetary waves from the extratropical troposphere to the stratosphere,and leads to a significantly strengthened stratospheric polar vortex. In contrast,during 1979–2015,the La Ni?a teleconnection shifts eastwards,with an anomalous high concentrated in the northeastern Pacific. The destructive interference of the La Ni?a teleconnection with climatological stationary waves seen in the earlier period reduces greatly,which prevents the drastic reduction of planetary wave activities in the extratropical stratosphere. Correspondingly,the stratospheric response shows a less disturbed stratospheric polar vortex in winter.

Intraseasonal Variability of Summertime Surface Air Temperature over Mid-High-Latitude Eurasia and Its Prediction Skill in S2S Models

Features of the dominant modes of surface air temperature(SAT)on the intraseasonal timescale over the mid-highlatitude Eurasia(MHE)during boreal summer(June-September)are investigated based on the ERA5 reanalysis data from 1979 to 2016.The intraseasonal variability(ISV)of SAT over MHE is primarily characterized by an eastward propagation along 60°N,which is found to impact the regional weather in China,including summertime extreme hot and cool events.The forecast skill and potential predictability of the ISV of SAT over MHE are assessed for 5 dynamical models that have participated in the subseasonal-to-seasonal(S2 S)prediction project,by analyzing12 years’(1999-2010)model reforecast/hindcast data.By using the principal component(PC)index of the leading intraseasonal SAT modes as a predictand,we found that the forecast skill for ISV of SAT can reach out to 11-17 days,and the ECMWF model exhibits the best score.All the S2 S models tend to show 1)a relatively higher skill for strong intraseasonal oscillation(ISO)cases,2)a systematic underestimate of the amplitude of the SAT ISV signal,and 3)different skills during different phases of ISO cases.Analysis of potential predictability based on the perfectmodel assumption reveals a 4-6-day skill gap for most models,and the skill gap also varies among different phases of ISO events.The results imply the need for continued development of operational forecasting systems to improve the actual prediction skills for the ISV of SAT over MHE.