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1. Structural fluctuations of the Arctic Oscillation tied to the Atlantic Multidecadal Oscillation

   https://doi.org/10.1038/s41612-024-00805-z  

   Gong, Hainan; Ma, Kangjie; Liu, Bo; Cohen, Judah; Wang, Lin (December 2024, npj Climate and Atmospheric Science)

   The Arctic Oscillation (AO) has been observed to undergo distinct decadal structural fluctuations that significantly influence regional weather and climate. Understanding the drivers and mechanisms behind the AO’s spatial nonstationarity is critical for improving climate predictions related to the AO. Wepresent evidence that the Atlantic Multidecadal Oscillation (AMO) plays a pivotal role in modulating AO’s Pacific center in recent decades. The poleward amplified cooling associated with negative AMO enhances the north-south temperature gradient and results the strengthened westerly winds and stratospheric polar vortex (SPV) responses, which reflects more planetary waves from the North Pacific to the North Atlantic. This enhances the atmospheric coupling between these regions and leads to amore pronounced Pacific center within theAOpattern.Numerical simulations fromECHAM5 and 35 CMIP6 models further corroborate the essential role of the AMO. These findings advance our understanding of the mechanisms driving the variability of the AO pattern. 

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2. Decoupling of the Arctic Oscillation and North Atlantic Oscillation in a warmer climate

   https://doi.org/10.1038/s41558-020-00966-8  

   Hamouda, Mostafa E.; Pasquero, Claudia; Tziperman, Eli (February 2021, Nature Climate Change)

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3. The Impact of the Madden–Julian Oscillation on High-Latitude Winter Blocking during El Niño–Southern Oscillation Events

   https://doi.org/10.1175/JCLI-D-17-0721.1  

   Henderson, Stephanie A.; Maloney, Eric D. (July 2018, Journal of Climate)
4. Carrier density oscillation in the photoexcited semiconductor

   https://doi.org/10.1088/1361-6463/abd1a4  

   Najafi, Ebrahim; Jafari, Amir; Liao, Bolin (January 2021, Journal of Physics D: Applied Physics)
5. Subseasonal predictability of the North Atlantic Oscillation

   https://doi.org/10.1088/1748-9326/abe781  

   Albers, John R.; Newman, Matthew (March 2021, Environmental Research Letters)

   Abstract Skillfully predicting the North Atlantic Oscillation (NAO), and the closely related northern annular mode (NAM), on ‘subseasonal’ (weeks to less than a season) timescales is a high priority for operational forecasting centers, because of the NAO’s association with high-impact weather events, particularly during winter. Unfortunately, the relatively fast, weather-related processes dominating total NAO variability are unpredictable beyond about two weeks. On longer timescales, the tropical troposphere and the stratosphere provide some predictability, but they contribute relatively little to total NAO variance. Moreover, subseasonal forecasts are only sporadically skillful, suggesting the practical need to identify the fewer potentially predictable events at the time of forecast. Here we construct an observationally based linear inverse model (LIM) that predicts when, and diagnoses why, subseasonal NAO forecasts will be most skillful. We use the LIM to identify those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. Our method has broad applicability because both the LIM and the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS) have higher (and comparable) skill for the same set of predicted high skill forecast events, suggesting that the low-dimensional predictable subspace identified by the LIM is relevant to real-world subseasonal NAO predictions. 

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