Stratospheric Modulation of Arctic Oscillation Extremes as Represented by Extended-Range Ensemble Forecasts

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 6 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, for the ECMWF S2S ensemble this 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 reanalyses 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 (< −3σ) is enhanced by at least 35 %, while that for extremely positive AO states (> +3σ) is reduced to almost zero, 3) a p-SSW preceding an extremely negative AO state within 4 weeks is causal for this AO extreme (in a statistical sense) up to a degree of 27 %. A corresponding analysis relative to strong stratospheric vortex events reveals similar insights into the stratospheric modulation of positive AO extremes.

Influence of the Madden–Julian Oscillation on the Arctic Oscillation Prediction in S2S Operational Models

The connections between the Madden–Julian Oscillation (MJO) and the Arctic Oscillation (AO) are examined in both observations and model forecasts. In the observations, the time-lag composites are carried out for AO indices and anomalies of 1,000-hPa geopotential height after an active or inactive initial MJO. The results show that when the AO is in its positive (negative) phase at the initial time, the AO activity is generally enhanced (weakened) after an active MJO. Reforecast data of the 11 operational global circulation models from the Sub-seasonal to Seasonal (S2S) Prediction Project are further used to examine the relationship between MJO activity and AO prediction. When the AO is in its positive phase on the initial day of the S2S prediction, an initial active MJO can generally improve the AO prediction skill in most of the models. This is consistent with results found in the observations that a leading MJO can enhance the AO activity. However, when the AO is in its negative phase, the relationship between the MJO and AO prediction is not consistent among the 11 models. Only a few S2S models provide results that agree with the observations. Furthermore, the S2S prediction skill of the AO is examined in different MJO phases. There is a significantly positive relationship between the MJO-related AO activity and the AO prediction skill. When the AO activity is strong (weak) in an MJO phase, including the inactive MJO, the models tend to have a high (low) AO prediction skill. For example, no matter what phase the initial AO is in, the AO prediction skill is generally high in MJO phase 7, in which the AO activity is generally strong. Thus, the MJO is an important predictability source for the AO forecast in the S2S models.

The Impact of Spatial Variation of Westerlies On Comprehensive And Extreme Precipitation Over Iran

This study analyzed the impact of spatial variation in westerlies on widespread and heavy precipitation over Iran using the sinuosity index. Four groups of datasets were used for the period from 1979 to 2020, containing the gridded geopotential height, specific humidity, precipitation data, and the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) teleconnection patterns. The results demonstrate that the trend in sinuosity variation has been decreased during the 1979-1999 sub period but increased from 2000 to 2020. The analysis of the trend in cumulative sinuosity for the above two sub periods indicates that sinuosity rate has been greater in the latter than in the former all over the year except in October. The overall trend in sinuosity variation exhibits an increase by 0.0018, significantly. Maximum sinuosity can be observed in January, March, and December, and minimum sinuosity is seen in October. The relationship between heavy precipitation and sinuosity suggests that daily precipitation has increased by 3 mm with a rise of 0.2 in the value of sinuosity, monthly precipitation by 10 mm, and the annual value by 38 mm. Thus, the rate of correlation between sinuosity and precipitation over Iran equals to 0.74. Sinuosity increase in the 0-70° E range indicates an increase in wave depth and the occurrence of a cut off low. The most important factor in the persistence of widespread extreme precipitation has been the formation of these lows in the 20-40°E and 20-35°N ranges.

The Effect of the Arctic Oscillation on the Predictability of Mid-High Latitude Circulation in December

The impact of the Arctic Oscillation (AO) on the predictability of mid-high latitude circulation in December is analysed using a full set of hindcasts generated form the Beijing Climate Center Atmospheric General Circulation Model version 2.2 (BCC_AGCM2.2). The results showed that there is a relationship between the predictability of the model on the Eurasian mid-high latitude circulation and the phase of AO, with the highest predictability in the negative AO phase and the lowest predictability in the normal AO phase. Moreover, the difference of predictability exists at different lead times. The potential sources of the high predictability in the negative AO phase in the BCC_AGCM2.2 model were further diagnosed. It was found that the differences of predictability on the Eurasian mid-high latitude circulation also exist in different Arctic sea ice anomalies, and the model performs well in reproducing the response of Arctic sea ice on the AO. The predictability is higher when sudden stratospheric warming (SSW) events occur, and strong SSW events tend to form a negative AO phase distribution in the Eurasian mid-high latitudes both in the observation and model. In addition, the model captured the blocking over the mid-high latitudes well, it may be related to the relatively long duration of the blocking. Changes in the AO will affect the blocking circulations over the mid-high latitudes, which partly explains the high predictability of the model in negative AO phases from the aspect of the internal atmospheric dynamics.

Volcanic activity sparks the Arctic Oscillation

The parasol effect of volcanic dust and aerosol caused by volcanic eruption results in the deepening and strengthening of the Arctic vortex system, thus stimulating or strengthening the Arctic Oscillation (AO). Three of the strongest AOs in more than a century have been linked to volcanic eruptions. Every significant fluctuation of the AO index (AOI = ΔH_middle latitudes − ΔH_Arctic) for many years has been associated with a volcanic eruption. Volcanic activity occurring at different locations in the Arctic vortex circulation will exert different effects on the polar vortex.

Influence of the Arctic Oscillation on the Formation of Water Circulation Regimes in the Sector of the North, Norwegian and Barents Seas

The article studies the influence of wind forcing associated with the Arctic Oscillation on the water circulation regimes in the sector of the World Ocean (65–81.5 N, 0–70 E), which consolidates the North, Norwegian and Barents Seas. The study aims at establishing quantitative patterns of variability of the ocean level and surface geostrophic current velocities depending on the value of the Arctic Oscillation index. In general, the response of the sea level averaged over the ocean sector under consideration is in an antiphase with this index. However, there are periods of mismatch between antiphase fluctuations of the sea level and the Arctic Oscillation index. After 2009, an increase in the amplitude and a decrease in the duration of the phases of the Arctic Oscillation index are noted. The difference between the areas of positive and negative values of sea level anomalies creates a pressure gradient that causes surface geostrophic currents carrying Atlantic waters along the shelf edge eastward in a cyclonic regime (the Arctic Oscillation index is greater than 0) and westward in an anticyclonic regime (the index is less than 0). The article provides estimates of the linear regression coefficients: for the sea level they are ~ 2 cm in the shelf zone and about minus 1 cm in the deep-water part of the sector. Thus, the level difference between the shelf and the deeper part of the considered water area is ~ 3 cm per 1 unit of the Arctic Oscillation index. Estimates of the linear regression coefficients for anomalies of the geostrophic currents velocity were ~ 0.5 cm/s per 1 unit of the index. Analysis of the longterm variability of the steric component of the ocean level showed a better relationship with the interannual variability of the Arctic Oscillation index as compared to the ocean level.

The Impact of the Stratospheric Polar Vortex Shift on the Arctic Oscillation

Using the ERA-Interim reanalysis dataset for the time period 1979–2016, we analyzed the influence of the stratospheric polar vortex shift on the Arctic Oscillation (AO) in winter (December–March). The results show that a shift in the stratospheric polar vortex toward the Eurasian continent is favorable for the occurrence of the negative phase of the AO. The duration of the AO events accompanied by the stratospheric polar vortex shift toward the Eurasian continent (AO-shift events) is longer than that of the remaining negative AO events (AO-noshift events), and the intensity of AO-shift events is greater than that of AO-noshift events from day 4 to day 15 of the life cycle of the events. The enhancement in the AO intensity during AO-shift events is likely due to downward extension of the stratospheric northern annular mode (NAM) signals and more poleward-propagating planetary waves in the troposphere and lower stratosphere and their convergence in the mid-high latitudes. Furthermore, the polar vortex shift can lead to changes in the intensity of the three action centers in the AO spatial pattern at 500 hPa. In general, during AO-shift events, the three action centers are stronger than those during AO-noshift events. There is an overall westward shift of the Arctic action center during AO-shift events, which may be closely related to the changes of Greenland blocking frequency.

Non-Stationary Effects of the Arctic Oscillation and El Niño–Southern Oscillation on January Temperatures in Korea

In recent decades, extremely cold winters have occurred repeatedly throughout the Northern Hemisphere, including the Korean Peninsula (hereafter, Korea). Typically, cold winter temperatures in Korea can be linked to the strengthening of the Siberian High (SH). Although previous studies have investigated the typical relationship between the SH and winter temperatures in Korea, this study uniquely focused on a change in the relationship, which reflects the influence of the Arctic Oscillation (AO) and El Niño–Southern Oscillation (ENSO). A significant change in the 15-year moving correlation between the SH and the surface air temperature average in Korea (K-tas) was observed in January. The correlation changed from −0.80 during 1971–1990 to −0.16 during 1991–2010. The mean sea-level pressure pattern regressed with the temperature, and a singular value decomposition analysis that incorporated the temperature and pressure supports that the negative high correlation during 1971–1990 was largely affected by AO. This connection with AO is substantiated by empirical orthogonal function (EOF) analysis with an upper-level geopotential height at 300 hPa. In the second mode of the EOF, the temperature and pressure patterns were primarily affected by ENSO during 1991–2010. Consequently, the interdecadal change in correlation between K-tas and the SH in January can be attributed to the dominant effect of AO from 1971–1990 and of ENSO from 1991–2010. Our results suggest that the relative importance of these factors in terms of the January climate in Korea has changed on a multidecadal scale.