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Here are the current Papers & Articles under the research topic Arctic Oscillation. Click on the title of a paper you are interested in to go straight to the full paper. Papers and articles covering the basics (ideal for learning) are shown in Green. A new index for more accurate winter predictions (SCE - Snow Cover Extent and SAI - Snow Advance Index) 2011 paper. Abstract: Seasonal climate prediction remains a challenge. During Northern Hemisphere (NH) winter the large‐scale teleconnection pattern the Arctic Oscillation (AO) explains the largest fraction of temperature variance of any other known climate mode. However the Arctic Oscillation is considered to be a result of intrinsic atmospheric dynamics or chaotic behavior and therefore is unpredictable. Here we develop a snow advance index (SAI) derived from antecedent observed snow cover that explains a large fraction of the variance of the winter AO. The high correlation between the SAI and the winter AO demonstrates that the AO is most likely predictable and that this index can be exploited for skillful seasonal climate predictions. Arctic Oscillation (AO) - A Simple Guide Global Patterns: Arctic & North Atlantic Oscillations Dynamical Link between the Barents–Kara Sea Ice and the Arctic Oscillation 2016 paper. Abstract: The recent accelerated Arctic sea ice decline has been proposed as a possible forcing factor for midlatitude circulation changes, which can be projected onto the Arctic Oscillation (AO) and/or North Atlantic Oscillation (NAO) mode. However, the timing and physical mechanisms linking AO responses to the Arctic sea ice forcing are not entirely understood. In this study, the authors suggest a connection between November sea ice extent in the Barents and Kara Seas and the following winter’s atmospheric circulation in terms of the fast sea ice retreat and the subsequent modification of local air–sea heat fluxes. In particular, the dynamical processes that link November sea ice in the Barents and Kara Seas with the development of AO anomalies in February is explored. In response to the lower-tropospheric warming associated with the initial thermal effect of the sea ice loss, the large-scale atmospheric circulation goes through a series of dynamical adjustment processes: The decelerated zonal-mean zonal wind anomalies propagate gradually from the subarctic to midlatitudes in about one month. The equivalent barotropic AO dipole pattern develops in January because of wave–mean flow interaction and firmly establishes itself in February following the weakening and warming of the stratospheric polar vortex. This connection between sea ice loss and the AO mode is robust on time scales ranging from interannual to decadal. Therefore, the recent winter AO weakening and the corresponding midlatitude climate change may be partly associated with the early winter sea ice loss in the Barents and Kara Seas. Hindcasting the January 2009 Arctic Sudden Stratospheric Warming and Its Influence on the Arctic Oscillation with Unified Parameterization of Orographic Drag in NOGAPS. Part I: Extended-Range Stand-Alone Forecast 2009 paper. Abstract: A very strong Arctic major sudden stratospheric warming (SSW) event occurred in late January 2009. The stratospheric temperature climbed abruptly and the zonal winds reversed direction, completely splitting the polar stratospheric vortex. A hindcast of this event is attempted by using the Navy Operational Global Atmospheric Prediction System (NOGAPS), which includes the full stratosphere with its top at around 65 km. As Part I of this study, extended-range (3 week) forecast experiments are performed using NOGAPS without the aid of data assimilation. A unified parameterization of orographic drag is designed by combining two parameterization schemes; one by Webster et al., and the other by Kim and Arakawa and Kim and Doyle. With the new unified orographic drag scheme implemented, NOGAPS is able to reproduce the salient features of this Arctic SSW event owing to enhanced planetary wave activity induced by more comprehensive subgrid-scale orographic drag processes. The impact of the SSW on the tropospheric circulation is also investigated in view of the Arctic Oscillation (AO) index, which calculated using 1000-hPa geopotential height. The NOGAPS with upgraded orographic drag physics better simulates the trend of the AO index as verified by the Met Office analysis, demonstrating its improved stratosphere–troposphere coupling. It is argued that the new model is more suitable for forecasting SSW events in the future and can serve as a tool for studying various stratospheric phenomena. How Predictable Are the Arctic and North Atlantic Oscillations? Exploring the Variability and Predictability of the Northern Hemisphere 2018 paper. Abstract: The North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) describe the domi- nant part of the variability in the Northern Hemisphere extratropical troposphere. Due to the strong connection of these patterns with surface climate, recent years have shown an increased interest and an increasing skill in forecasting them. However, it is unclear what the intrinsic limits of short-term predictability for the NAO and AO patterns are. This study compares the variability and predictability of both patterns, using a range of data and index computation methods for the daily NAO/AO indices. Small deviations from Gaussianity are found and characteristic decorrelation time scales of around one week. In the analysis of the Lyapunov spectrum it is found that predictability is not significantly different between the AO and NAO or between reanalysis products. Differences exist however between the indices based on EOF analysis, which exhibit predictability time scales around 12 - 16 days, and the station-based indices, exhibiting a longer predictability of 18 - 20 days. Both of these time scales indicate predictability beyond that currently obtained in ensemble prediction models for short-term predictability. Additional longer-term predictability for these patterns may be gained through local feedbacks and remote forcing mechanisms for particular atmospheric conditions. Observed and Simulated Teleconnections Between the Stratospheric Quasi‐Biennial Oscillation and Northern Hemisphere Winter Atmospheric Circulation 2019 paper. Abstract: The Quasi‐Biennial Oscillation (QBO) is the dominant mode of interannual variability in the tropical stratosphere, with easterly and westerly zonal wind regimes alternating over a period of about28 months. It appears to influence the Northern Hemisphere winter stratospheric polar vortex and atmospheric circulation near the Earth's surface. However, the short observational record makes unequivocal identification of these surface connections challenging. To overcome this, we use a multi century control simulation of a climate model with a realistic, spontaneously generated QBO to examine teleconnections with extratropical winter surface pressure patterns. Using a 30‐hPa index of the QBO, we demonstrate that the observed teleconnection with the Arctic Oscillation (AO) is likely to be real,and a teleconnection with the North Atlantic Oscillation (NAO) is probable, but not certain. Simulated QBO‐AO teleconnections are robust, but appear weaker than in observations. Despite this, inconsistency with the observational record cannot be formally demonstrated. To assess the robustness of our results, weuse an alternative measure of the QBO, which selects QBO phases with westerly or easterly winds extending over a wider range of altitudes than phases selected by the single‐level index. We find increased strength and significance for both the AO and NAO responses, and better reproduction of the observed surface teleconnection patterns. Further, this QBO metric reveals that the simulated AO response is indeed likely to be weaker than observed. We conclude that the QBO can potentially provide another source of skill for Northern Hemisphere winter prediction, if its surface teleconnections can be accurately simulated. October circulation precursors of the wintertime Arctic Oscillation 2014 paper. Abstract: Investigation into atmospheric processes preceding winters of different Arctic Oscillation index (AOI) polarity, based on empirical data analysis, has revealed highly statistically significant relationships between the wintertime AOI and preceding October circulation. The wintertime AOI strongly covaries with an October circulation anomaly barotropically spanning the depth of the troposphere over the Taymyr Peninsula (Taymyr circulation anomaly, TCA), with the anticyclonic (cyclonic) TCA preceding winters of the negative (positive) AOI polarity. The October TCA affects the wintertime AOI polarity mainly via its impact on air temperature over the Arctic and North‐East Asia. Anticyclonic (cyclonic) TCA leads to the positive (negative) temperature anomaly over the Arctic and a corresponding increase (decrease) of geopotential heights, and to the negative (positive) temperature anomaly over North‐East Asia and so to enhancement (weakening) of the climatological trough associated with long planetary waves and corresponding enhancement (weakening) of the upward wave activity flux. To characterize temporal variability of the TCA, a Taymyr circulation index (TCI) is suggested. Correlation coefficient between the (inverted) wintertime AOI and the October TCI is 0.58 for the 1958–2012 period, with correlations being stable in time. The anticyclonic (cyclonic) TCA is associated with smaller (larger) number of cyclones coming to the region of the eastern Barents Sea–Taymyr Peninsula–Laptev Sea. Statistical relationships between the October TCA, wintertime AOI and September/October sea surface temperature in the northern Barents Sea are shown. Winter 2009–2010: A case study of an extreme Arctic Oscillation event 2010 paper. Abstract: Winter 2009–2010 made headlines for extreme cold and snow in most of the major population centers of the industrialized countries of the Northern Hemisphere (NH). The major teleconnection patterns of the Northern Hemisphere,El Niño/Southern Oscillation (ENSO) and the Arctic Oscillation (AO) were of moderate to strong amplitude, making both potentially key players during the winter of 2009–2010.The dominant NH winter circulation pattern can be shown to have originated with a two‐way stratosphere‐troposphere interaction forced by Eurasian land surface and lower tropospheric atmospheric conditions during autumn. This cycle occurred twice in relatively quick succession contributing to the record low values of the AO observed. Using a skillful winter temperature forecast, it is shown that the AO explained a greater variance of the observed temperature pattern across the extratropical landmasses of the NH than did ENSO.