1. Introduction and objectives
Polar lows (PLs) are high-latitude mesoscale maritime cyclones, characterized by short lifetimes (typically less than 2 days) and strong surface winds (up to 25–30 m s−1; e.g., Rasmussen and Turner 2003; Heinemann and Claud 1997). Severe conditions associated with PLs, such as large-amplitude ocean waves, heavy snow showers with limited visibility, and strong icing (Claud et al. 1993; Harrold and Browning 1969; Rasmussen and Turner 2003), can pose hazards to coastal communities and marine operations. Efforts to advance the representation of PLs in numerical weather prediction systems, such as the development of a convective-scale atmospheric prediction system for the European Arctic region (AROME-Arctic; Müller et al. 2017) and the Advanced Models and Weather Prediction in the Arctic project (Alertness; https://www.alertness.no/en/project), have contributed to improved PL forecasts, especially for the near-surface wind speed and mesoscale cloud structure (Hallerstig et al. 2021; Stoll et al. 2020). However, most operational models still suffer from insufficient model resolution, inadequate representation of crucial physical processes, and limited observations in the Arctic region (Bourassa et al. 2013; Furevik et al. 2015; Jonassen et al. 2020). Consequently, skillful prediction of PLs thus remains a challenge, especially for extended-range forecasting.
In addition to model improvement, a better understanding of the predictability sources can also help improve forecasts of PL activity. Previous studies have shown that PL development is strongly affected by environmental conditions, including marine cold air outbreaks, the presence of an upper-level trough, weak static stability, and low-level baroclinicity (e.g., Kolstad 2011; Rasmussen and Turner 2003; Stoll et al. 2021). These synoptic conditions are modulated by low-frequency atmospheric variability, such as the North Atlantic Oscillation (NAO; e.g., Rogers 1997; Serreze et al. 1997). Carleton (1985) examined the mesocyclone activity in the North Atlantic sector of the Arctic for two winters, 1974/75 and 1976/77, which are representative of the positive and negative NAO phases, respectively, and found that more mesocyclones developed in 1974/75 east of the Labrador Sea than in 1976/77. Consistently, Mallet et al. (2013) found that PLs are almost absent during the negative phase of NAO in the Labrador Sea. Over the Nordic seas, Harold (1999a,b) reported an increase in the mesocyclone frequency as the NAO index became more positive. However, a different conclusion was drawn by Mallet et al. (2013), who showed that more PLs were observed in the negative phase of the NAO in the Norwegian and Barents Seas. Furthermore, a recent study by Michel et al. (2018) suggested that there is no preference for a specific state of NAO when PLs form. Therefore, the relationship between PL activity and the NAO remains controversial over the Nordic seas.
Sudden stratospheric warmings (SSWs) are another important phenomenon of low-frequency variability in high latitudes (Baldwin et al. 2021). SSWs have widespread effects on weather, atmospheric chemistry (Pedatella et al. 2018), and even the ocean (Kidston et al. 2015; Reichler et al. 2012). SSWs are initiated by upward propagation of planetary-scale waves from the troposphere to the stratosphere, which leads to a weakening of the stratospheric polar vortex (Matsuno 1971). As the polar vortex weakens, adiabatic warming contributes to a rapid increase in the polar stratospheric temperatures. Owing to the dynamical coupling between the troposphere and stratosphere (Kidston et al. 2015), the stratospheric wind and temperature anomalies then descend downward and induce anomalous tropospheric circulations, resembling the negative phase of the NAO or Arctic Oscillation (AO; e.g., Baldwin and Dunkerton 2001; Butler et al. 2017; Domeisen 2019; Kolstad et al. 2010). The negative NAO (or AO) regimes have a profound influence on the occurrence of extreme weather in many regions over the Northern Hemisphere (Kenyon and Hegerl 2008), including cold air outbreaks and heavy snowfall over northern Europe and the eastern United States (e.g., Kidston et al. 2015; Kolstad et al. 2010), as well as unusual warmings over southwest Greenland and Newfoundland (e.g., Thompson et al. 2002). In addition, the tropospheric jet stream and storm tracks displace southward in response to the weakening of the stratospheric polar jet (Baldwin and Dunkerton 2001; Kidston et al. 2015).
The onsets of most SSWs can be predicted by current weather prediction systems (with high model tops) at least 5 days in advance (Tripathi et al. 2015). A better understanding of the connection between SSWs and PL variability has the potential to improve extended-range forecasts of PL activity. This study therefore aims to investigate the following questions:
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Do SSWs modulate PL activity in the North Atlantic?
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What large-scale circulation anomalies associated with SSWs are responsible for the variations of PL activity?
Data and methodology are described in section 2, and PL variability along with the changes of the large-scale circulation related to SSWs are examined in section 3, followed by discussion and conclusions in section 4.
2. Data and methodology
a. ERA-5
We use the European Centre for Medium-Range Weather Forecasts (ECMWF) state-of-the-art reanalysis version 5 (ERA5; Hersbach et al. 2020) for the detection of SSW events, PLs, and the composite analyses. The hourly data are available at a grid spacing of 0.25° × 0.25° from 1950 to the near-present, and we focus on the Northern Hemisphere PL season, November–April, from 1979 to 2016 (the PL season includes January–April in 1979 and November–December in 2016). Daily anomalies are defined as the departures from the long-term (1979–2016) daily mean.
b. Identifying SSW events
The stratospheric zonal wind reversal has been used to identify “major” SSWs (e.g., McInturff 1978), which often have strong influences on surface weather conditions (Palmeiro et al. 2015). A commonly used definition for major SSWs (Charlton and Polvani 2007) is based on the reversal of the zonal-mean 10-hPa zonal wind along 60°N. However, this definition is sensitive to the meridional extent of the polar vortex. The latitudinal average of 10-hPa zonal wind has been suggested as a more robust measure to identify SSWs (Butler et al. 2015). We therefore follow the approach by Butler et al. (2015) in this study, except that some additional thresholds are applied to exclude six weak and short-lived SSWs. An SSW event is identified when the 10-hPa daily mean zonal wind, cosine weighed and averaged over 60°–90°N (U6090), falls below 0 m s−1 during November to March (Butler et al. 2015). We also require that U6090 remains westerly for at least 20 consecutive days between two SSW events, or that U6090 returns to westerly for at least 10 consecutive days after the final warming event prior to 30 April. The average frequency of SSWs (1.03 yr−1) obtained here is slightly higher than those identified in previous studies using different reanalysis datasets (Butler et al. 2015) owing to several short-lived events. To exclude such events, we further applied duration and intensity thresholds. The duration of an SSW event is defined as the number of days when U6090 remains below 0 m s−1, and the intensity of an SSW event is measured by the magnitude of the strongest U6090 anomaly during its duration. The averaged intensity and standard deviation of 39 SSW events are 36.64 and 9.66 m s−1, respectively. If the duration of an SSW event is less than 6 days and the intensity is less than 27 m s−1, which is one standard deviation below the mean intensity for all SSW events, this event is regarded as a minor SSW and is excluded from the composite analysis. Six minor SSW events are excluded, and the remaining 33 SSW events mainly occur during January to March. About 92% (22 out of 24) of the SSW events identified by Butler et al. (2017) using the ERA-Interim during 1979–2014 are included in our study (see Table S1 in the online supplemental material).
The mature day (day 0) of an SSW event is defined as the day when the U6090 anomaly reaches its maximum amplitude. The zonal-mean temperature and zonal wind anomalies in the Arctic region (60°–90°N) propagate downward in a manner consistent with what was reported in previous studies (Fig. S1; Baldwin and Dunkerton 2001; Limpasuvan et al. 2004). Since the stratospheric temperature and wind anomalies are relatively weak before day 0 or after day 20, our analyses focus on the period from day 1 to day 20.
c. Polar low dataset
Stoll’s (2021) PL track dataset based on ERA5 for 1979–2020 is used in this study, based on the following methodology. The 850-hPa relative vorticity is first smoothed by a uniform filter of 60-km radius, and cyclones are identified as local maxima of smoothed 850-hPa relative vorticity exceeding 1.5 × 10−4 s−1 between 30° and 80°N over ice-free water. Four criteria are then applied to separate PLs from other cyclones: 1) The potential temperature (θ) at tropopause must be less than 300.8 K (i.e., the cyclone occurs poleward of the polar front); 2) the θ difference between the sea surface and the 500-hPa level must be less than 11 K (i.e., low static stability); 3) the smoothed 850-hPa relative vorticity must exceed 2 × 10−4 s−1 (an intensity criterion); and 4) the vortex diameter must be less than 430 km (mesoscale-size criterion). If the averaged tropopause θ during a cyclone lifetime satisfies the threshold (criterion 1), and criteria 2–4 are satisfied at one time step (can be non-simultaneous), the vortex is classified as a PL. Comparisons of PL database developed by Stoll (2021) to different satellite-derived PL lists show reasonable agreement over the North Atlantic.
Since a PL track in Stoll (2021) may include the stage when the vortex is a weak marine mesocyclone, we only consider the track segments when the intensity criterion is met. The resultant climatological PL track densities are slightly reduced over the Labrador Sea, Denmark Strait, and the Nordic seas (cf. Figs. S2a and S2c). Applying the intensity threshold has no qualitative influence on the obtained results as it does not change the pattern of PL anomalies during SSWs (Figs. S2b and S2d).
d. Statistical significance
If not specified otherwise, a two-sample Student’s t test is used to determine whether the composite differences of 33 SSW events and the Pearson correlation coefficients are significant at the 95% (p value < 0.05) confidence level.
3. Variations in polar low activity and environmental conditions
a. Polar low activity
Figures 1a shows the climatological (1979–2016) PL track density from November to April. The highest PL track density occurs along the coastal regions of Scandinavia in the Norwegian and Barents Seas (together referred to as the Nordic seas), and a second maximum is found southeast of Greenland in the Irminger Sea. Figure 1b shows the anomaly in the PL track density during days 1–20 of all SSW events compared to the climatological value for the same 20 calendar days of each SSW. Although significant long-term trends of PL activity have been observed by Stoll (2021) over the Labrador Sea and Nordic seas, removing the trends does not affect the pattern of PL anomalies (not shown). A significant reduction in PL activity during the 20 days following an SSW is observed over the Labrador Sea and the southern tip of Greenland, while the negative anomalies are rather scattered and mixed with insignificant positive anomalies in the Nordic seas (Fig. 1b). Over the Labrador Sea [50°–65°N, 65°–45°W; a domain defined in Parker (1997)], the PL track density declines ∼40%–50% compared to climatological conditions. Using a one-sample Student’s t test, the reduction is above the 95% confidence level (p value = 0.039). In contrast, over the northern Nordic seas [65°–80°N, 20°E–55°W; a domain defined in Noer et al. (2011)], the increase in the areal-mean PL track density is not significant (p value = 0.614).
(a) Long-term-mean (1979–2016) PL track density function (TDF; unit: h day−1 in a 5° × 5° grid cell) from November to April. (b) Composite differences in the PL TDF from day 1 to day 20 of SSW events. Black dots highlight the regions where the difference exceeds the 95% confidence level. Note that the TDF is normalized by 1/cos(latitude).
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
In the following analyses, we explore the factors responsible for the significantly suppressed PL activity in the Labrador Sea and discuss why the changes in PL activity are less coherent over the Nordic seas. Variations of PL activity along the southeast coast of Greenland, however, are not further investigated because the anomalies in this region are mainly along the coast (Fig. 1b) and may be strongly modulated by the interaction between Greenland topography and synoptic flows (Bromwich 1991; Klein and Heinemann 2002).
b. Environmental conditions for PL development modulated by SSWs
Figure 2a illustrates the climatological SLP during November–April, as well as anomalies of 10-m winds and SLP following SSWs. The climatological mean is characterized by relatively high SLP over land and the ice-covered Arctic, the Aleutian low over the North Pacific, and the Icelandic low over the North Atlantic. Following SSWs, we observe a clear negative AO pattern (e.g., Baldwin and Dunkerton 2001). The significant anomalies include increased SLP over the Arctic, reduced SLP over the midlatitude North Atlantic and western Europe, anomalous northerly/northeasterly flow over the Nordic seas, and anomalous southeasterly flow over the Labrador Sea. The SLP anomalies over the North Atlantic sector exhibit a meridional dipole pattern, resembling the negative phase of the NAO. The anomalies over the North Pacific are relatively weak. It is worth noting that the positive SLP anomalies north of ∼65°N (Fig. 2a) differ from the dipolar SLP distribution noted by Zahn and von Storch (2008). They found that the increased PL occurrence over the Norwegian Sea can be linked to a pressure difference of around 2–3 hPa in the zonal direction between the Barents Sea and the Denmark Strait (see Fig. 3a in Zahn and von Storch 2008), and the enhanced northerly winds favor marine cold-air outbreaks (MCAOs; Kolstad et al. 2009). The weak northeasterly wind anomalies shown in Fig. 2a, however, have a large component parallel to the mean isotherms and thus are not optimal in producing strong cold advection.
(a) Long-term (1979–2016) mean of SLP (black contours; hPa) during November–April, and composite differences in 10-m winds (m s−1; only differences exceeding the 95% confidence level are shown) and SLP (shading; hPa) averaged from day 1 to day 20. White contours highlight SLP anomalies above the 95% confidence level. Blue contour denotes the climatological (1979–2016) sea ice edge (defined by sea ice coverage ≥ 15%). (b) 850-hPa temperatures (contours; °C) over the oceanic regions, composite differences in 850-hPa winds (vectors; only differences exceeding the 95% confidence level are shown), and anomalies in temperature advection (shading; only differences exceeding the 95% confidence level are shown; K day−1) averaged during days 1–20 following SSWs.
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
The frequency of MCAOs is strongly modulated by SSWs on the subseasonal time scale (Afargan-Gerstman et al. 2020). To better evaluate how MCAOs are influenced by SSWs, we examined the temperature advection anomalies following SSWs. The 850-hPa temperatures averaged during days 1–20 (i.e., T), anomalous winds (V′), and anomalous temperature advection [i.e.,
PLs tend to develop within marine polar air masses, which are characterized by a low static stability in the troposphere. A criterion for low static stability is a difference between sea surface temperature (SST) and 500-hPa air temperature (SST − T500) larger than 43 K (e.g., Yanase et al. 2016; Zahn and von Storch 2008; Zappa et al. 2014). The composite differences in the daily frequency (h day−1) of SST − T500 exceeding 43 K averaged from day 1 to day 20 (Fig. 3a) show positive anomalies over the Nordic seas and negative anomalies over the Labrador Sea and Denmark Strait. In both cases, the magnitudes of the anomalies approach 1.5 h day−1. The positive frequency anomalies of SST − T500 ≥ 43 K are generally insignificant over the Nordic seas; in contrast, the significant negative anomalies over the Labrador Sea are coherent and represent a 40%–50% reduction of the long-term mean in some regions (Fig. S3a), contributing to the suppressed PL activity (Fig. 1b). Further analyses show that the sea ice edge (defined by sea ice coverage ≥ 15%; Fig. S3a) and SST (Fig. S3c) do not differ significantly from their climatological states. The significant anomalies of SST − T500 for the Labrador Sea can be primarily attributed to anomalous warming aloft centered over the Baffin Bay and Davis Strait (Fig. S3b).
(a) Composite differences in the daily frequency (h day−1) of SST−T500 exceeding 43 K averaged from day 1 to day 20. Purple lines highlight the anomalies above the 95% confidence level. (b),(c) As in (a), but for composite differences of surface fluxes (sum of sensible heat and latent heat fluxes; W m−2), and daily frequency (h day−1) of |∇hT850| exceeding 2 K (100 km)−1, respectively. Note that the land and sea ice regions are masked out, and the thick black contours represent the climatological sea ice edge (defined by sea ice coverage ≥ 15%) during November–April.
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
Previous studies have suggested that strong surface heat fluxes contribute to the convective development of PLs (e.g., Emanuel and Rotunno 1989; Kolstad et al. 2016; Kolstad and Bracegirdle 2017). Air masses flowing from cold land or sea ice over a warmer water surface often experience intense diabatic warming by extracting sensible and latent heat from the ocean, thereby modulating static stability and baroclinicity (Hartmann et al. 1997; Papritz and Spengler 2017). Figure 3b shows that the surface turbulent heat fluxes (i.e., sum of sensible heat and latent heat fluxes) are enhanced over the northern Nordic seas but reduced south of Iceland and over the Labrador Sea. The latter is mainly due to the reduced surface wind speed, while the former can be attributed to enhanced temperature contrast between the ocean and atmosphere (not shown). Consistent with a reduced frequency of low static stability (Fig. 3a), significant anomalies of the surface turbulent heat fluxes are most coherent over the Labrador Sea, consistent with the suppressed PL activity there (Fig. 1b). Additionally, the reduced surface wind speed and air–sea fluxes can modify the ocean mixed layer heat budget (O’Callaghan et al. 2014) and affect deep-water formation, suggesting a stratospheric connection to the Atlantic meridional overturning circulation (AMOC; Reichler et al. 2012).
Moist baroclinic growth has been suggested as an important mechanism for PL development (e.g., Mak 1982; Sardie and Warner 1985; Montgomery and Farrell 1992), and this mechanism was also emphasized by some recent studies (e.g., Terpstra et al. 2015; Stoll et al. 2021). The Eady growth rate was examined but significant anomalies are largely absent over either the Labrador Sea or the Nordic seas (not shown). Stoll et al. (2021) suggested that the 850-hPa horizontal temperature gradient (|∇hT850|) exceeding 2 K (100 km)−1 is a favorable condition for the cyclogenesis and subsequent intensification of PLs by baroclinic instability. We thus examine the frequency of |∇hT850| ≥ 2 K 100 km−1. Figure 3c shows significant negative anomalies over the Labrador Sea (Fig. 3c), which are consistent with the suppressed PL activity over this area.
Simultaneous occurrences of weak static stability, high baroclinicity, and strong surface fluxes form favorable condition for PL development (Stoll et al. 2021). For 55% of the SSW events (18 out of 33; Table S1), we observe a simultaneous reduction in the areal-mean frequencies of SST − T500 exceeding 43 K, |∇hT850| larger than 2 K (100 km)−1 as well as the averaged surface fluxes over the Labrador Sea. In contrast, over the northern Nordic seas, only 21% of SSWs (7 of 33; Table S1) undergo a concurrent decrease of these conditions. These environmental conditions synchronously increase following 24% of SSWs (8 out of 33; Table S1), consistent with the largely insignificant anomalies over this area (Fig. 3). Such differences help to explain the significantly suppressed PL activity over the Labrador Sea and the mixed PL anomalies over the Nordic seas.
We also examined the upper-tropospheric potential vorticity (PV) anomalies. Montgomery and Farrell (1992) suggested that the initial spinup of the surface vortex may benefit from the positive interaction between an upper-level trough and a weak lower tropospheric PV anomaly (Hoskins et al. 1985). The role of upper-tropospheric PV anomalies or tropopause polar vortices (Cavallo and Hakim 2012; 2013) in triggering the cyclogenesis of PLs was also supported by recent studies (e.g., Kolstad 2011; Mallet et al. 2013). Following Kolstad (2011), variations in the dynamical tropopause pressure were used as an indicator of the upper-tropospheric forcing. It was found that the tropopause significantly displaces downward north of 70°N following SSWs (Fig. S4a). The increased upper-level PV can be mainly attributed to the enhanced static stability near the tropopause associated with stratospheric warming (Fig. S4b) instead of changes in tropopause relative vorticity (Fig. S4c). The changes of the tropopause pressure are insignificant over the Labrador Sea and the southeast coast of Greenland, and may not strongly contribute to the anomalies of PL activity in those regions. In summary, the suppressed PL activity over the Labrador Sea can be attributed to reduced occurrence of low static stability, weaker environmental baroclinicity, and weaker surface turbulent fluxes.
c. Linkage to synoptic cyclones and the NAO
Previous studies have indicated that PLs tend to form west of synoptic cyclones (Businger 1985; Condron et al. 2006; Yanase et al. 2016; Watanabe et al. 2017). The northerly flow associated with the synoptic low can induce an MCAO, and the convergence zone between cold dry continental air mass and warm moist maritime air mass west of the synoptic cyclone provides favorable conditions for mesocyclone development (Afargan-Gerstman et al. 2020; Bond and Shapiro 1991). Previous studies also suggested that the North Atlantic storm track displaces equatorward following SSWs (Baldwin and Dunkerton 2001; Kidston et al. 2015), and this may introduce an additional factor into PL variability. The Pearson correlation coefficient between PL and synoptic cyclone numbers calculated over 37 winters are shown in Fig. 4 for the Labrador Sea and the northern Nordic seas separately. Here the synoptic cyclones are detected using a tracking algorithm based on the 6-hourly SLP from the ERA5 (Zhang et al. 2004; see more information in the online supplemental material), and the cyclone number is measured by the cyclone trajectories detected over a certain region (i.e., northern Nordic seas), regardless of its genesis location and lifetime. For the northern Nordic seas, a significant positive correlation is found between the seasonal PL and synoptic-scale cyclone frequencies (Fig. 4a; r = 0.39; above the 95% confidence level) during November–April 1979 to 2016. However, for the Labrador Sea, the correlation between the PL and synoptic cyclone frequencies is insignificant (Fig. 4b; r = 0.27; below the 95% confidence level). Kolstad et al. (2009) suggested that synoptic lows west of Iceland can advect cold air masses from the northwest into the Labrador Sea. Accordingly, we find a significant positive correlation between synoptic cyclones southeast of Greenland (50°–65°N, 45°–25°W; position marked in Fig. 4d) and PLs over the Labrador Sea (Fig. 4c; r = 0.37; above the 95% confidence level).
(a) The standardized anomalies of the November–April synoptic cyclone frequency (blue line) and PL (red line) frequency over the Nordic seas, and (b) over the Labrador Sea from 1979/80 to 2015/16. (c) The standardized anomalies of the November–April synoptic cyclone frequency over the southeast Greenland and PL frequency over the Labrador Sea. (d) Composite differences in the synoptic cyclone density activity from day 1 to day 20 of SSW events. Black dots highlight the regions where the difference exceeds the 95% confidence level. Note that the density function is normalized by 1/cos(latitude).
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
The influences of SSWs on synoptic storm activity are also examined. Variations of synoptic cyclone activity are mixed, and there is a lack of coherent spatial changes (Fig. 4d). Furthermore, the areal-mean cyclone frequency anomalies are insignificant over the Nordic seas, suggesting that the indirect impacts of SSWs on PL activity via synoptic storms are limited over this area. Although an increase in synoptic cyclones is observed southeast of Greenland (Fig. 4d), which could lead to increased PL activity in the Labrador Sea, the environmental conditions after SSWs are less favorable than normal for PL development in this region, as explained earlier. This finding is consistent with Afargan-Gerstman and Domeisen (2020), but may not have been anticipated considering the modulation of the storm track by SSWs suggested by previous studies (Baldwin and Dunkerton 2001; Kidston et al. 2015).
The surface response to SSWs often projects onto the negative phase of the NAO (Charlton-Perez et al. 2018; Domeisen 2019). It is thus instructive to examine the relationship between the NAO and PL variability. The correlation coefficient between the seasonal NAO index and the PL frequency is found to be low during 1979–2016 (r = 0.17; below the 95% confidence level) over the Nordic seas. In contrast, the PL frequency over the Labrador Sea is strongly correlated to the NAO index (r = 0.48; above the 99% confidence level). The 21-yr running correlations between the NAO and PL activity over the Nordic seas during 1979–2016 (Fig. S5a) reveals a significant correlation to the NAO index from 1992 to 1998 but the correlation becomes weaker after 1999. The significant relationship between PL and NAO from the 1990s to early 2000s is consistent with Harold (1999a,b), but not with Mallet et al. (2013) and Michel et al. (2018). The difference may be attributable to the use of different PL datasets. In addition, we focus on the NAO index here, while Mallet et al. (2013) distinguished four weather regimes in their analysis.
Further analysis shows a similar nonstationary relationship between the NAO and synoptic cyclone activity (Fig. S5b). Over the Nordic seas, the nonstationary relationship between the NAO and PLs (Fig. S5a) may be partly attributed to the nonstationary relationship between the NAO and synoptic cyclones (Fig. S5b), given the significant connection between synoptic cyclones and PLs over this area (Fig. 4a). The changing impacts of NAO on intense synoptic cyclone activity near Scandinavia has been reported by previous studies (e.g., Jung et al. 2003) and could be attributed to interdecadal shifts in the location of the NAO pressure centers (e.g., Lu and Greatbatch 2002; Vicente‐Serrano and López‐Moreno 2008).
In contrast to the Nordic seas, the strong linkage between the NAO index and PL frequency over the Labrador Sea (Fig. S5c) indicates that the PL development over this region is strongly modulated by the phase of NAO, possibly owing to the NAO’s impacts on the frequency of MACOs over the Labrador Sea (Kolstad et al. 2009). Additionally, the significant running correlations between synoptic cyclone frequency and the NAO index (Fig. S5d) suggest that recurrent synoptic lows southeast of Greenland during the positive NAO phase could be an important contributor to cold air outbreaks over the Labrador Sea.
Further analysis shows that SSWs during 1979–99 are characterized by stronger surface response and more negative PL anomalies than 2000–16 (Fig. S6) over the northern Nordic seas and the Labrador Sea. More investigation is needed to clarify the physical causes of decadal shifts in the SSW–PL relationship.
d. Diverging impacts of SSWs over the Nordic seas
Although on average the downward impacts of SSWs on the troposphere are robust, not every SSW event influences the lower troposphere. About two-thirds of SSWs have a detectable downward impact (Charlton‐Perez et al. 2018; Domeisen 2019; White et al. 2019). The surface response varies considerably between different SSW events and may be complicated by the tropospheric state (including the NAO or AO) prior to the SSW (Domeisen et al. 2020a). Stronger and persistent SSWs likely cause significant, long-lasting impacts on the troposphere (Karpechko et al. 2017; Rao et al. 2020; Runde et al. 2016). Additionally, Mitchell et al. (2013) suggested that the circulation anomalies descend faster and the surface response is stronger when the stratospheric polar vortex splits into two (split events) than when the polar vortex simply gets displaced away from the pole (displacement events).
To investigate why the Nordic seas are characterized by mixed signals of PL anomalies after SSW events, we separate SSWs into two groups based on the areal-mean changes of PL activity over the Nordic seas. We also examined the tropospheric circulation anomalies in these two groups to help better understand the diverging influences of SSWs on PLs. The 17 SSWs leading to decreased areal-mean PL activity are referred as PL(−), whereas the 16 SSWs leading to increased areal-mean PL activity are referred to as PL(+) (Table S2). PLs are significantly suppressed over the Nordic seas in the PL(−) group, while the PL(+) group is characterized by positive anomalies of PL activity over the Norwegian and Barents Seas (Figs. 5a,c). Meanwhile, significant reduction of PL activity occurs over the Labrador Sea in both groups. Composite analysis shows that the PL(−) group is characterized by reduced frequency of SST − T500 > 43 K (Fig. 5b), while the probability of SST − T500 exceeding 43 K significantly increases in the PL(+) group (Fig. 5d), consistent with the anomalies of PL activity. The composite anomalies of geopotential height at 200 and 850 hPa (Fig. 6a) reveal an east–west elongated anomalous high extending from Greenland to the Norwegian Sea in the PL(−) group. The PL(+) group is characterized by a strong east–west dipole pattern with an anomalous high centered over the North Pole ranging over Greenland and an anomalous low over Scandinavia (Fig. 6c). The anomalous height pattern in the PL(+) group is similar to the Greenland blocking regime, a recurrent weather state during the winters with weak stratospheric vortex (Papritz and Grams 2018). For both groups, the height anomalies have an equivalent barotropic structure from the lower stratosphere to the lower troposphere (Figs. 6a,c), and are linked to different anomalous low-level winds (Figs. 6b,d). The PL(−) group is associated with easterly wind anomalies southeast of Greenland and largely insignificant temperature advection anomalies (Fig. 6b); in contrast, the PL(+) group is characterized by northeasterly wind anomalies and enhanced cold air advection over the Nordic seas (Fig. 6d), which contributes to reduced static stability (Fig. 5d) and creates a favorable condition for PL development (Fig. 5c). The dipole flow configuration in the PL(+) group thus facilitates the development of PLs (Mallet et al. 2013; Zahn and von Storch 2008).
(a) Composite differences in the PL activity from day 1 to day 20 of 17 SSW events in the PL(−) group. Black dots denote the regions with difference significant at 95% confidence level. Note that the density function is normalized by a 1/cos(latitude) factor. (b) Composite differences in the daily frequency (h day−1) of SST−T500 exceeding 43 K averaged from day 1 to day 20 of 17 SSW events in the PL(−) group. (c),(d) As in (a),(b), but for 16 SSW events in the PL(+) group. Note that the land and sea ice regions are masked out, and the thick black contours represent the climatological sea ice edge (defined by sea ice coverage ≥ 15%) during November–April.
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
(a) Composite differences in 850-hPa geopotential height (shaded; m) and 200-hPa geopotential height (contours; m) from day 1 to day 20 of 17 SSWs in the PL(−) group. Purple and green contours highlight 850- and 200-hPa geopotential height anomalies above the 95% confidence level, respectively. (b) 850-hPa temperatures (contours; °C), composite differences in 850-hPa winds (vectors; only differences exceeding the 95% confidence level are shown), and anomalies in temperature advection (shaded; only differences exceeding the 95% confidence level are shown; K day−1) averaged from day 1 to day 20 of 17 SSWs in the PL(−) group. (c),(d) As in (a) and (b), but for 16 SSW events in the PL(+) group.
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
The contrasting tropospheric response between PL(+) and PL(−) groups could be linked to differences in the strength and duration of the stratospheric perturbations (Karpechko et al. 2017; Rao et al. 2020; Runde et al. 2016). The stratospheric warming occurs over a broader area, and the 10-hPa PV and geopotential height anomalies have a greater extension over Siberia and are slightly stronger in the PL(−) group (Figs. 7a,c). In comparison, positive 10-hPa geopotential height anomalies centered close to northern Greenland are characterized by strong symmetry, and negative PV anomalies are mostly confined within the Arctic Ocean in the PL(+) group (Fig. 7b). To further illustrate the differences of SSW events between PL(−) and PL(+) groups, the downward propagation of zonal-mean wind and temperature anomalies in the Arctic region (60°–90°N) are examined (Fig. S7). Significant easterly wind anomalies do not extend below 500 hPa in the PL(−) group prior to day 10 (Fig. S7a) but are visible in the PL(+) group during days 1–5 (Fig. S7b). In addition, despite the weaker warming in the mid- to upper stratosphere (Fig. S7f), the PL(+) group is characterized by slightly enhanced warming between 100 and 300 hPa from day −10 to day 10. The differences between the two groups, however, are all below the 95% confidence level.
(a) Composite differences in 10-hPa geopotential height (contours; m) and PV (shading; PVU) averaged from day 1 to day 20 of 17 SSWs in the PL(−) group. Purple and green contours highlight 10-hPa geopotential height and PV anomalies above the 95% confidence level, respectively. (b) As in (a), but for 16 SSWs in the PL(+) group. (c) Differences in 10-hPa geopotential height (contours; m) and PV (shading; PVU) taken as PL(+) minus PL(−). Purple and green contours highlight the regions where 10-hPa geopotential height and PV differences between the two groups are significant at 95% confidence level, respectively.
Citation: Journal of Climate 35, 13; 10.1175/JCLI-D-21-0905.1
Further investigation indicates that the averaged AO index during days 0–20 becomes more negative in the PL(−) group (−0.88), relative to the PL(+) group (−0.50). This is consistent with the findings in previous studies (e.g., Karpechko et al. 2017; Rao et al. 2020; White et al. 2020) that stronger SSW events tend to be followed by a more negative, long-lasting AO signature in the lower troposphere. The duration of SSWs is also examined based on the number of days when the U6090 remains below 0 m s−1, as Runde et al. (2016) suggested that the persistent stratospheric perturbations tend to be associated with a stronger tropospheric response. Although SSWs in PL(+) group, on average, persist slightly longer (14.4 days) than these in the PL(−) group (13.5 days), the duration difference is insignificant.
The occurrence of the split and displacement types of SSWs in the PL(−) and PL(+) groups are examined as well. Every SSW event is subjectively defined as “displacement,” “split,” or “mixed type” based on 10-day-averaged 10-hPa PV (Table S2). For both groups, 11 SSWs can be classified as displacement type, and 4 SSWs are regarded as vortex splitting events, indicating that the type of SSWs is not the primary explanation for different tropospheric responses (Fig. 6).
Additionally, we caution that the different tropospheric responses may not be completely attributed to the differences in the stratospheric polar vortex. Recent studies suggest that the uncertainties in the tropospheric responses following SSWs are closely associated with tropospheric internal variability, including synoptic events with low predictability (Oehrlein et al. 2021; González-Alemán et al. 2022). For example, the development of a strong extratropical cyclone can significantly modulate the occurrence probability of different weather regimes after SSWs (González-Alemán et al. 2022).
4. Summary and discussion
A better understanding of the connection between SSWs and PL variability has the potential to improve extended-range forecasts of PL activity. Our analysis shows that PL activity decreases significantly over the Labrador Sea following SSWs. Consistent with previous studies, we find that the surface response to SSW events projects onto the negative phase of the NAO. To better understand the factors contributing to suppressed PL activity, various environmental parameters are examined. Surface turbulent fluxes, occurrences of a low static stability (as indicated by SST − T500), and strong environmental baroclinicity decrease significantly over the Labrador Sea, which leads to conditions unfavorable for PL development. Changes in these conditions can be understood by a decreased frequency of MCAOs.
Although this study is based on the statistical analysis of observational data, which makes it challenging to determine causal relationships, the conclusion that SSWs induce changes in PLs over the Labrador Sea is supported by previous studies. First, a negative phase of NAO or AO tends to follow SSW events (e.g., Baldwin and Dunkerton 2001; Butler et al. 2017; Domeisen 2019). Second, the NAO has strong impacts on the frequency of MCAOs, 500-hPa air temperatures, and surface turbulent fluxes over the Labrador Sea (e.g., Claud et al. 2007; Kolstad et al. 2009; Visbeck et al. 2003). These environmental parameters are known to affect PL development (e.g., Claud et al. 2007; Mallet et al. 2013). The direction of causality is further supported by examining the 10-day-averaged PL anomalies before the mature days of SSWs. We find positive but insignificant PL anomalies over Labrador Sea prior to SSWs (not shown).
Differences in stratospheric warming pattern appears to affect PL development over the Nordic seas. When the PL activity is increased in the Nordic seas [i.e., the PL(+) group], the middle-stratospheric (10-hPa) geopotential height and PV anomalies occur over a smaller region and the center shifts toward northern Greenland compared to the SSWs associated with decreased PL activity in the Nordic seas [i.e., the PL(−) group]. For both PL(−) and PL(+) groups, the height anomalies present a barotropic structure extending from the lower stratosphere to the troposphere, and the contrasting PL anomalies can be explained by different tropospheric responses between the two groups. An enhanced east–west surface pressure gradient over the Nordic seas favors stronger northerly winds, more frequent occurrences of MCAOs, and reduced static stability, which facilitate PL development. In contrast, an east–west elongated anomalous high is present over the Nordic seas in the PL(−) group. The anomalies feature a blocking anticyclone above Greenland and the Norwegian Sea. This feature blocks the northerly flow over the Nordic seas, and the lower-tropospheric circulation anomalies are generally weaker. Contrasting tropospheric flow patterns, however, cannot be completely attributed to differences in stratospheric states. The tropospheric internal variability may contribute to the different tropospheric responses as well (González-Alemán et al. 2022; Oehrlein et al. 2021).
The variability of stratospheric vortex strength exerts pronounced influences on the North Atlantic weather regimes on the subseasonal to seasonal time scales (Charlton-Perez et al. 2018; Papritz and Grams 2018), but different weather regimes after SSWs could have contrasting effects on environmental conditions and PL development over the Nordic seas (Mallet et al. 2013; Papritz and Grams 2018). Specifically, the frequencies of Scandinavian blocking and Greenland blocking have been suggested to increase for the winters with a weak polar stratospheric vortex (Papritz and Grams 2018). However, Greenland blocking is typically associated with more frequent MCAOs, while the likelihood of cold-air outbreaks substantially decreases during the Scandinavian blocking regimes over the Nordic seas (see Figs. 1f and 1g in Papritz and Grams 2018). The opposite effects of these two regimes on cold air outbreaks could dilute the link between SSWs and PLs over the Nordic seas.
The influences of SSWs on PL activity in this study are mainly inferred through variations in environmental conditions, such as MCAOs. However, MCAOs are not a sufficient condition for PL genesis and the relative importance of static stability in PL formation may be flow-dependent (Michel et al. 2018; Terpstra et al. 2016, 2021). For example, reverse shear PLs are often observed in conditions with SST − T500 exceeding 43 K, but this threshold is not necessary for the PLs forming in a forward shear environment (Michel et al. 2018; Terpstra et al. 2016). Other processes in addition to MCAOs, such as interaction of synoptic flows with orography and the existence of a local convergence zone or shear line, could be important factors contributing to PL genesis as well (Terpstra and Watanabe 2020).
Since SSWs are associated with a weak stratospheric polar vortex, it is interesting to examine the impacts of strong stratospheric polar vortex events (SPVs). SPV events are identified using the approach similar to that developed by Díaz-Durán et al. (2017) (see the supplemental material). An increase of PL track density is observed over the Labrador Sea, southeast of Greenland, and in the Norwegian Sea following 23 SPV events (Fig. S7). Meanwhile, the North Atlantic subpolar gyre region is characterized by anomalous cold advection, reduced static stability, and enhanced surface turbulent fluxes (not shown). Although the pattern is broadly opposite to the impacts of SSWs on PLs, significant PL anomalies only exist over the Denmark Strait (Fig. S7). A comparison of the SPV events with significant increased and decreased PL activity would be an interesting topic for future study.
Our study is based on the PL track dataset from Stoll (2022). Due to the limited direct observations of PLs, previous studies have employed different tracking algorithms to identify PLs, and discrepancies exist between different PL datasets (e.g., Michel et al. 2018; Smirnova et al. 2015; Stoll et al. 2018, 2022; Stoll 2022; Zahn and von Storch 2008). The development of a standard observation-based PL best-track dataset will shed light on the uncertainties of the PL climatology. It is possible that some of our findings are quantitatively sensitive to the choice of the PL dataset. However, testing with a different PL track dataset (Stoll et al. 2018) yields qualitatively same results and confirms the robustness of our findings.
This study suggests the potential to improve the extended-range prediction of regional PL activity, especially over the Labrador Sea, based on the skillful prediction of SSWs. Our ability to predict SSW events on the medium-range to subseasonal time scales has increased considerably due to higher model tops, enhanced vertical resolution in the stratosphere (Marshall and Scaife 2010), and improved representation of stratospheric physical processes, such as gravity wave drag (Domeisen et al. 2020b). In the ECMWF subseasonal forecast system, most of the major SSWs are predictable at lead times of 8–12 days (Karpechko 2018). However, fewer than 50% of SSWs can be predicted at lead times longer than 2 weeks (Domeisen et al. 2020b), probably owing to the limitations in forecasting the key tropospheric drivers leading to stratospheric warming (Karpechko 2018). Furthermore, more work is needed to better understand which SSWs will have a significant downward impact (Baldwin et al. 2021). Skillful prediction of the morphology and duration of an SSW event could provide valuable information for medium-range to subseasonal weather forecasts. Additionally, investigation of other predictability sources on the subseasonal time scale, such as the Madden–Julian oscillation (MJO; Madden and Julian 1971), may also help to advance our understanding and prediction of PL variability. The seminal study by Cassou (2008) suggested that the probability of positive NAO significantly increases in response to MJO-associated anomalous heating over the Indian Ocean, while active MJO convection over the eastern Pacific is linked to frequent occurrences of negative NAO events. The potential connection between MJO and PL variability warrants further investigation.
Acknowledgments.
This work was supported by the Office of Naval Research through Grant N000141812216. John Walsh was also supported by the National Science Foundation through Grant ARC-1602720. We acknowledge the NCAR Computational and Information Systems Laboratory (CISL) for providing the storage space. We thank the anonymous reviewers for their extensive and constructive comments on the manuscript.
Data availability statement.
The ERA5 data are available through the NCAR Research Data Archive (RDA) (https://rda.ucar.edu/datasets/ds630.0/), and the monthly NAO index was downloaded from the Climate Prediction Center (CPC; https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml). The daily AO index is derived from the CPC website (ftp://ftp.cpc.ncep.noaa.gov/cwlinks/). PL tracks for this research are included in Stoll (2022).
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