Statistical Characteristics of the Long-term Variations in Major Sudden Stratospheric Warming Events

+ Author Affiliations + Find other works by these authors
  • Corresponding author: Yuli ZHANG, zhangyuli@mail.iap.ac.cn
  • Funds:

    Supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA17010105) and Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO-2019-01)

  • doi: 10.1007/s13351-021-0166-3
  • Note: This paper has been peer-reviewed and is just accepted by J. Meteor. Res. Professional editing and proof reading are underway. Please use with caution.

PDF

  • Using NCEP/NCAR reanalysis data, we investigate the statistical characteristics and the long-term variations of major sudden stratospheric warming (SSW) events in the Northern Hemisphere. We find that the strength and duration of major SSW events has increased from 1958 to 2019 and that this is due to the strengthening of the winter planetary wave activity. We find that the frequency of displacement and split SSW events differs between early, middle and late winter. Early and middle winter are dominated by displacement and split SSW events, respectively, but the frequency of the two types of event is almost equal in late winter. This is due to the differences in the relative strength of wavenumber-1 and wavenumnber-2 planetary wave activity in the three winter periods. As a result of the increase in upward planetary wave activity and the decrease in westerly winds around the polar vortex in middle winter, a shift in the timing of SSW events toward middle winter is detected. In addition, we revealed the influence of the downward propagation of different types of SSW event on the surface temperature anomaly. There were surface cold centers in Russia and northern China after the middle split SSW events; by contrast, there were more cold events in North America after the middle split SSW events.
  • 加载中
  • Fig. 7.  The distribution of the mean E–P flux (colored arrows) and its divergence (black contours) within 1 month (±15 lag days) around the central day of two types of SSW event: (a) wavenumber-1 for displacement SSW events, (b) wavenumber-2 for split SSW events, (c) wavenumber-1 for split SSW events and (d) wavenumber-2 for SSW events.

    Fig. 1.  (a) The mean temperature anomalies in the polar region (60–90°N) at 10 hPa for each SSW event (grey lines) and the average of all SSW events (black line). The lag day 0 is the central day of SSW. (b) The maximum of mean temperature anomalies in the polar region within 1 month (±15 lag days) around the central day of the SSW event (black dots). The black line indicates the long-term trend of the maximum of mean temperature anomaly. The trends with “*” passed the 95% significance criterion.

    Fig. 2.  (a) The duration of SSW events. (b) The duration of SSW events (black dots) and its long-term trend (black line). The trends with “*” passed the 95% significance criterion.

    Fig. 3.  (a) The mean eddy heat flux in 1 month (±15 lag days) around the central day of SSW events within 45–70°N at 100 hPa. (b) The mean zonal-mean zonal wind in 1 month (±15 lag days) around the central day of SSW events at 60°N, 10 hPa. The long-term trends are shown as black lines.

    Fig. 4.  The locations of the polar vortex at 10 hPa (blue lines are geopotential height equal to 29.8 km) for (a–e) displacement and (f–j) split SSW events.

    Fig. 5.  The locations of vertical upward wave activity equal to 0.2 m2 s−2 at 100 hPa (red lines) for (a–e) displacement and (f–j) split SSW events.

    Fig. 6.  The dates of all SSW events. The blue and red dots are the central day of displacement and split SSW events, respectively. The blue and red solid lines are the averages of the central day of displacement and split SSW events, respectively. The whole winter period covering all SSW events is evenly divided into three periods (early, middle, and late winter) by the four black dashed lines.

    Fig. 8.  The mean eddy heat flux within 50–65°N at 100 hPa for (a) all wavenumbers and (b) wavenumber-1 (blue line) and wavenumber-2 (red lines). The whole winter covering all SSW events is evenly divided into three periods (early, middle and late winter) by the four black dashed lines. The horizontal solid lines represent the mean values during the three winter periods.

    Fig. 9.  The NAM index (contours, blue for negative; red for positive) for six types of SSW event: (a) early displacement, (b) early split, (c) middle displacement, (d) middle split, (e) late displacement and (f) late split SSW events. The color shading indicates statistical significance at the 95% confidence level based on a t-test.

    Fig. 10.  The location of the surface cold center for six types of SSW event: (a) early displacement, (b) middle displacement, (c) late displacement, (d) early split, (e) middle split and (f) late split SSW events. Blue lines are the mean surface temperature anomalies for the 30 days after the central day of the SSW events equal to −4 K.

    Table 1.  The central dates and the types of SSW events identified in the NCEP/NCAR datasets

    Early
    (before 4th JAN)
    Middle(5th JAN–
    12th FEB)
    Late
    (after 13th FEB)
    Displacement30 Nov 195816 Jan 196022 Feb 2008
    8 Dec 196523 Jan 198713 Mar 1969
    27 Nov 19687 Jan 200420 Mar 1971
    2 Jan 197028 Jan 201729 Feb 1980
    4 Dec 198124 Feb 1984
    15 Dec 199820 Mar 2000
    16 Dec 200024 Feb 2007
    2 Jan 200226 Feb 2017
    Split2 Jan 198530 Jan 195823 Mar 1965
    8 Dec 19878 Jan 196824 Feb 1966
    17 Jan 197122 Feb 1979
    2 Feb 197314 Mar 1988
    11 Feb 200122 Feb 1989
    18 Jan 200325 Feb 1999
    21 Jan 200614 Feb 2018
    24 Jan 2009
    9 Feb 2010
    10 Jan 2013
    Download: Download as CSV

    Table 2.  The long-term trends of (a) mean eddy heat flux within 50–65°N at 100 hPa and (b) mean zonal wind at 60°N and 10 hPa in early, middle and late winter. The trends with “*” passed the 95% significance criterion

    Early winterMiddle winterLate winter
    (a) Mean eddy heat flux
     (K ms−1 year−1)
    0.05*0.08 0.01
    (b) Mean zonal wind
     (ms−1 year−1)
    0.11−0.08−0.01
    Download: Download as CSV
  • [1]

    Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle Atmosphere Dynamics. Academic Press, London, 489 pp.
    [2]

    Ayarzagüena, B., U. Langematz, S. Meul, et al., 2013: The role of climate change and ozone recovery for the future timing of major stratospheric warmings. Geophys. Res. Lett., 40, 2460–2465. doi: 10.1002/grl.50477.
    [3]

    Baldwin, M. P., and T. J. Dunkerton, 1999: Propagation of the Arctic Oscillation from the stratosphere to the troposphere. J. Geophys. Res. Atmos., 104, 30937–30946. doi: 10.1029/1999JD900445.
    [4]

    Baldwin, M. P., and T. J. Dunkerton, 2001: Stratospheric harbingers of anomalous weather regimes. Science, 294, 581–584. doi: 10.1126/science.1063315.
    [5]

    Bell, C. J., L. J. Gray, and J. Kettleborough, 2010: Changes in Northern Hemisphere stratospheric variability under increased CO2 concentrations. Quart. J. Roy. Meteor. Soc., 136, 1181–1190. doi: 10.1002/qj.633.
    [6]

    Butler, A. H., and L. M. Polvani, 2011: El Niño, La Niña, and stratospheric sudden warmings: A reevaluation in light of the observational record. Geophys. Res. Lett., 38, L13807. doi: 10.1029/2011GL048084.
    [7]

    Butler, A. H., D. J. Seidel, S. C. Hardiman, et al., 2015: Defining sudden stratospheric warmings. Bull. Amer. Meteor. Soc., 96, 1913–1928. doi: 10.1175/BAMS-D-13-00173.1.
    [8]

    Charlton, A. J., and L. M. Polvani, 2007: A new look at stratospheric sudden warmings. Part I: Climatology and modeling benchmarks. J. Climate, 20, 449–469. doi: 10.1175/JCLI3996.1.
    [9]

    Cohen, J., and J. Jones, 2011: Tropospheric precursors and stratospheric warmings. J. Climate, 24, 6562–6572. doi: 10.1175/2011JCLI4160.1.
    [10]

    Coy, L., S. Eckermann, and K. Hoppel, 2009: Planetary wave breaking and tropospheric forcing as seen in the stratospheric sudden warming of 2006. J. Atmos. Sci., 66, 495–507. doi: 10.1175/2008JAS2784.1.
    [11]

    Domeisen, D. I. V., 2019: Estimating the frequency of sudden stratospheric warming events from surface observations of the North Atlantic Oscillation. J. Geophys. Res. Atmos., 124, 3180–3194. doi: 10.1029/2018JD030077.
    [12]

    Edmon, H. J. Jr., B. J. Hoskins, and M. E. McIntyre, 1980: Eliassen-Palm cross sections for the troposphere. J. Atmos. Sci., 37, 2600–2616. doi: 10.1175/1520-0469(1980)037<2600:EPCSFT>2.0.CO;2.
    [13]

    Eliassen, A., and E. Palm, 1961: On the transfer of energy in stationary mountain waves. Geofys. Publ., 22, 1–23.
    [14]

    Garfinkel, C. I., A. H. Butler, D. W. Waugh, et al., 2012: Why might stratospheric sudden warmings occur with similar frequency in El Niño and La Niña winters? J. Geophys. Res. Atmos., 117, D19106. doi: 10.1029/2012JD017777.
    [15]

    Garfinkel, C. I., S. W. Son, K. Song, et al., 2017: Stratospheric variability contributed to and sustained the recent hiatus in Eurasian winter warming. Geophys. Res. Lett., 44, 374–382. doi: 10.1002/2016GL072035.
    [16]

    Gerber, E. P., C. Orbe, and L. M. Polvani, 2009: Stratospheric influence on the tropospheric circulation revealed by idealized ensemble forecasts. Geophys. Res. Lett., 36, L24801. doi: 10.1029/2009GL040913.
    [17]

    Horan, M. F., and T. Reichler, 2017: Modeling seasonal sudden stratospheric warming climatology based on polar vortex statistics. J. Climate, 30, 10101–10116. doi: 10.1175/JCLI-D-17-0257.1.
    [18]

    Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–471. doi: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.
    [19]

    Karpechko, A. Y., A. Charlton‐Perez, M. Balmaseda, et al., 2018: Predicting sudden stratospheric warming 2018 and its climate impacts with a multimodel ensemble. Geophys. Res. Lett., 45, 13538–513546. doi: 10.1029/2018GL081091.
    [20]

    Li, Y. P., and W. S. Tian, 2017: Different impact of central Pacific and eastern Pacific El Niño on the duration of sudden stratospheric warming. Adv. Atmos. Sci., 34, 771–782. doi: 10.1007/s00376-017-6286-0.
    [21]

    Matsuno, T., 1971: A dynamical model of the stratospheric sudden warming. J. Atmos. Sci., 28, 1479–1494. doi: 10.1175/1520-0469(1971)028<1479:admots>2.0.co;2.
    [22]

    Maury, P., C. Claud, E. Manzini, et al., 2016: Characteristics of stratospheric warming events during Northern winter. J. Geophys. Res. Atmos., 121, 5368–5380. doi: 10.1002/2015JD024226.
    [23]

    McLandress, C., and T. G. Shepherd, 2009: Impact of climate change on stratospheric sudden warmings as simulated by the Canadian Middle Atmosphere Model. J. Climate, 22, 5449–5463. doi: 10.1175/2009JCLI3069.1.
    [24]

    Mitchell, D. M., M. Osprey, S., L. J., Gray, et al, 2012a: The effect of climate change on the variability of the Northern Hemisphere stratospheric polar vortex. J. Atmos. Sci., 69, 2608–2618. doi: 10.1175/JAS-D-12-021.1.
    [25]

    Mitchell, D. M., J. Charlton-Perez, A., L. J., Gray, et al, 2012b: The nature of Arctic polar vortices in chemistry–climate models. Quart. J. Roy. Meteor. Soc., 138, 1681–1691. doi: 10.1002/qj.1909.
    [26]

    Mitchell, D. M., L. J. Gray, J. Anstey, et al., 2013: The influence of stratospheric vortex displacements and splits on surface climate. J. Climate, 26, 2668–2682. doi: 10.1175/JCLI-D-12-00030.1.
    [27]

    Nakagawa, K. I., and K. Yamazaki, 2006: What kind of stratospheric sudden warming propagates to the troposphere? Geophys. Res. Lett., 33, L04801. doi: 10.1029/2005GL024784.
    [28]

    O’Callaghan, A., M. M. Joshi, D. Stevens, et al., 2014: The effects of different sudden stratospheric warming types on the ocean. Geophys. Res. Lett., 41, 7739–7745. doi: 10.1002/2014GL062179.
    [29]

    O’Neill, A., 2003: Stratospheric sudden warmings. Encyclopedia of Atmospheric Sciences, J. R. Holton, J. A. Pyle, and J. A. Curry, Eds., Elsevier, New York, 1342–1353. (本条文献在正文中未被引用).
    [30]

    Plumb, R. A., 1985: On the three-dimensional propagation of stationary waves. J. Atmos. Sci., 42, 217–229. doi: 10.1175/1520-0469(1985)042<0217:OTTDPO>2.0.CO;2.
    [31]

    Polvani, L. M., and D. W. Waugh, 2004: Upward wave activity flux as a precursor to extreme stratospheric events and subsequent anomalous surface weather regimes. J. Climate, 17, 3548–3554. doi: 10.1175/1520-0442(2004)017<3548:UWAFAA>2.0.CO;2.
    [32]

    Rao, J., C. I. Garfinkel, and I. P. White, 2020: Predicting the downward and surface influence of the February 2018 and January 2019 sudden stratospheric warming events in subseasonal to seasonal (S2S) models. J. Geophys. Res. Atmos., 125, e2019JD031919. doi: 10.1029/2019JD031919.
    [33]

    Scott, R. K., and L. M. Polvani, 2006: Internal variability of the winter stratosphere. Part I: Time-independent forcing. J. Atmos. Sci., 63, 2758–2776. doi: 10.1175/JAS3797.1.
    [34]

    Seviour, W. J. M., D. M. Mitchell, and L. J. Gray, 2013: A practical method to identify displaced and split stratospheric polar vortex events. Geophys. Res. Lett., 40, 5268–5273. doi: 10.1002/grl.50927.
    [35]

    Sigmond, M., J. F. Scinocca, V. V. Kharin, et al., 2013: Enhanced seasonal forecast skill following stratospheric sudden warmings. Nat. Geosci., 6, 98–102. doi: 10.1038/NGEO1698.
    [36]

    WMO CAS, 1978: Abridged Final Report of the Seventh Session, Manila, 27 February–10 March 1978. Secretariat of the WMO Rep. WMO-509, 113 pp.
    [37]

    Xie, F., J. P. Li, W. S. Tian, et al., 2016: A connection from Arctic stratospheric ozone to El Niño-Southern oscillation. Environ. Res. Lett., 11, 124026. doi: 10.1088/1748-9326/11/12/124026.
    [38]

    Xie, F., J. P. Li, J. K. Zhang, et al., 2017: Variations in North Pacific Sea surface temperature caused by arctic stratospheric ozone anomalies. Environ. Res. Lett., 12, 114023. doi: 10.1088/1748-9326/aa9005.
    [39]

    Yu, Y. Y., R. C. Ren, and M. Cai, 2015: Dynamic linkage between cold air outbreaks and intensity variations of the meridional mass circulation. J. Atmos. Sci., 72, 3214–3232. doi: 10.1175/JAS-D-14-0390.1.
    [40]

    Zhang, L. D., and Q. L. Chen, 2019: Analysis of the variations in the strength and position of stratospheric sudden warming in the past three decades. Atmos. Oceanic Sci. Lett., 12, 147–154. doi: 10.1080/16742834.2019.1586267.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Statistical Characteristics of the Long-term Variations in Major Sudden Stratospheric Warming Events

    Corresponding author: Yuli ZHANG, zhangyuli@mail.iap.ac.cn
  • Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
Funds: Supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA17010105) and Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO-2019-01)

Abstract: Using NCEP/NCAR reanalysis data, we investigate the statistical characteristics and the long-term variations of major sudden stratospheric warming (SSW) events in the Northern Hemisphere. We find that the strength and duration of major SSW events has increased from 1958 to 2019 and that this is due to the strengthening of the winter planetary wave activity. We find that the frequency of displacement and split SSW events differs between early, middle and late winter. Early and middle winter are dominated by displacement and split SSW events, respectively, but the frequency of the two types of event is almost equal in late winter. This is due to the differences in the relative strength of wavenumber-1 and wavenumnber-2 planetary wave activity in the three winter periods. As a result of the increase in upward planetary wave activity and the decrease in westerly winds around the polar vortex in middle winter, a shift in the timing of SSW events toward middle winter is detected. In addition, we revealed the influence of the downward propagation of different types of SSW event on the surface temperature anomaly. There were surface cold centers in Russia and northern China after the middle split SSW events; by contrast, there were more cold events in North America after the middle split SSW events.

1.   Introduction
  • Sudden stratospheric warming (SSW) has been known as the most dramatic disturbance in the stratosphere during winter since it was first found by Scherhag (1952 本条文献在文后文献中未体现). It is characterized by a rapid temperature increase in the stratospheric polar region (Andrews et al., 1987). It is important to reveal the characteristics and variations of SSW since it can modify stratospheric circulation, which in turn can affect tropospheric climate (Baldwin and Dunkerton, 2001; Xie et al., 2016, 2017). SSW events can be divided into major and minor events according to the definition of World Meteorological Organization (WMO; WMO CAS, 1978). Here we focus on the major SSW events in the Northern Hemisphere. During these events, not only an increase in temperature but also a reversal of circulation around the polar vortex are observed.

    The frequency, timing, duration and strength of major SSW events are important metrics of polar stratospheric winter variability. Some modelling studies have predicted an increase in the frequency of major SSW events under future climate (McLandress and Shepherd, 2009; Bell et al., 2010; Butler et al., 2015); however, some studies have shown that the SSW frequency is model dependent (Mitchell et al., 2012b; Ayarzagüena et al., 2013). Domeisen (2019) suggested that the frequency of SSW events can be estimated from the surface conditions of the North Atlantic Oscillation (NAO). The minimum SSW frequency in the 1990s has been found to be coincident with the longest absence of an NAO event, which is defined as an increased persistence of the negative NAO phase and a change from a positive to a negative NAO. Mitchell et al. (2012a) found that there is no statistically significant change in SSW frequency over the twenty-first century, but the monthly distribution of SSW events has shifted toward February. Ayarzagüena et al. (2013) also found a shift in the timing of major SSW events toward midwinter in the future. Although some studies have suggested that the SSW frequency is similar during El Niño and La Niña events (Butler and Polvani, 2011; Garfinkel et al., 2012), Li and Tian (2017) found that the duration of major SSW events during the central Pacific El Niño is shorter than during the eastern Pacific El Niño. Zhang and Chen (2019) found a negative trend in the strength of both major and minor SSW events since 1979. They also showed that the maximum temperature centers are mainly located over Eurasia due to the shift in the polar vortex. By investigating all the major and minor SSW events from mid-November to mid-March, Maury et al. (2016) argued that the amplitude of SSW events shows a distinct seasonal distribution. They found that small-amplitude SSW events mainly occur in early and late winter and that large-amplitude SSW events occur in mid-winter.

    Other studies have shown that an SSW event is followed by a negative Northern Annular Mode (NAM), which propagates from the upper stratosphere to the surface (Baldwin and Dunkerton, 2001; Charlton and Polvani, 2007). However, not all SSW events appear to influence the troposphere and the surface (Gerber et al., 2009). Nakagawa and Yamazaki (2006) found that SSW events with a larger wavenumber-2 flux were more likely to propagate into the troposphere than those with a reduced wavenumber-2 flux. Some studies have shown that different types (displacement and split) of SSW event have different impacts on the surface climate (Mitchell et al., 2013; Seviour et al., 2013; O’Callaghan et al., 2014). Mitchell et al. (2013) found that vortex split events are correlated with more significant surface weather anomalies. Seviour et al. (2013) showed that vortex split events are associated with a negative Arctic Oscillation pattern. O’Callaghan et al. (2014) found that the magnitude of the surface wind stress anomaly is larger for split SSW events in the 0–30 day period after the onset of an SSW event. However, other studies (Charlton and Polvani, 2007; Cohen and Jones, 2011) have argued that the influence of SSW events on the tropospheric state is found to be largely insensitive to the SSW type. Nevertheless, this stratosphere–troposphere coupling still provides opportunities to improve the intraseasonal predictability of surface weather anomalies in winter (e.g. Sigmond et al., 2013; Yu et al., 2015; Garfinkel et al., 2017; Karpechko et al., 2018; Rao et al., 2020).

    In this study, we focus on the statistical characteristics and the long-term variations of major SSW events using historical records. The remainder of this paper is structured as follows. Section 2 describes the data and methods. Section 3 shows the long-term variations of SSW strength and duration. Section 4 provides a classification of SSW events according to the types of polar vortex and the time periods of winter. We analyze the variations in the planetary wave activity and westerly winds around the polar vortex that are responsible for the statistical characteristics and long-term variations. Then, the characteristics of the downward propagation and surface temperature response are shown in Section 5. Finally, Section 6 presents the conclusions and discussion of our findings.

2.   Data and methods
  • We use reanalysis data from the NCEP/NCAR (Kalnay et al., 1996) during the period of 1958–2019 to investigate all major SSW events in the Northern Hemisphere. The daily mean temperature, wind velocity and geopotential height at pressure levels, as well as the temperature at the surface, were used. On the basis of the definition of WMO CAS (1978), 40 major SSW events occurred in the 62 winters during the period of 1958–2019. The details of SSW frequency can be found in the paper by Butler et al. (2015).

  • The strength of a major SSW event is defined as the maximum of the mean temperature anomaly in the polar region (mean temperature in 60–90°N) within 31 days around the central day of the SSW event (central day ± 15 days) at 10 hPa. The central day of an SSW event is defined as the first day on which the daily mean zonal-mean zonal wind at 60°N and 10 hPa is easterly.

    During a major SSW event, the zonal-mean zonal wind at 60°N, 10 hPa reverses from westerly (positive) to easterly (negative). The duration of a major SSW event is defined as the time period around the day on which the minimum of the zonal-mean zonal wind at 60°N, 10 hPa is observed, and all the zonal-mean zonal wind velocities at 60°N, 10 hPa must be equal to or less than 0 m s−1 in this time period.

    For the classification of vortex displacement and split SSW events, we followed the definition of Charlton and Polvani (2007). According to this definition, there were 21 displacement and 19 split SSW events. The central date and the type of each event are shown in Table 1.

    Early
    (before 4th JAN)
    Middle(5th JAN–
    12th FEB)
    Late
    (after 13th FEB)
    Displacement30 Nov 195816 Jan 196022 Feb 2008
    8 Dec 196523 Jan 198713 Mar 1969
    27 Nov 19687 Jan 200420 Mar 1971
    2 Jan 197028 Jan 201729 Feb 1980
    4 Dec 198124 Feb 1984
    15 Dec 199820 Mar 2000
    16 Dec 200024 Feb 2007
    2 Jan 200226 Feb 2017
    Split2 Jan 198530 Jan 195823 Mar 1965
    8 Dec 19878 Jan 196824 Feb 1966
    17 Jan 197122 Feb 1979
    2 Feb 197314 Mar 1988
    11 Feb 200122 Feb 1989
    18 Jan 200325 Feb 1999
    21 Jan 200614 Feb 2018
    24 Jan 2009
    9 Feb 2010
    10 Jan 2013

    Table 1.  The central dates and the types of SSW events identified in the NCEP/NCAR datasets

  • The Eliassen–Palm (E–P) flux and its divergence depict planetary wave activity and eddy forcing on the zonal mean flow (Eliassen and Palm, 1961; Edmon et al., 1980). Based on daily NCEP/NCAR data, they were examined to characterize the features of the planetary wave activity during SSW events. The E–P flux, $F \equiv \left({0,{F^{\left(\lambda \right)}},{F^{\left(z \right)}}} \right)$, is composed of meridional $ {F}^{\left(\lambda \right)} $ and vertical $ {F}^{\left(z\right)} $ components. They are defined as

    $${{\rm{F}}^{\left({\rm{\lambda }} \right)}} \equiv {{\rm{\rho }}_{\rm{0}}}\;{\rm{a}}\;{\rm{cos\lambda }}\left({{{{\rm{\bar u}}}_{\rm{z}}}\overline {{\rm{v'}}\Theta '} /{{\bar \Theta }_{\rm{z}}} - \overline {{\rm{v'u'}}} } \right),$$ (1)
    $${{\rm{F}}^{\left({\rm{z}} \right)}} \equiv {{\rm{\rho }}_{\rm{0}}}\;{\rm{a}}\;{\rm{cos\lambda }}\left\{ {\left[ {{\rm{f - }}{{\left({{\rm{a}}\;{\rm{cos\lambda }}} \right)}^{ - 1}}{{\left({{\rm{\bar u}}\;{\rm{cos\lambda }}} \right)}_{\rm{\lambda }}}} \right]\overline {{\rm{v'}}\Theta '} - \overline {{\rm{w}}'{\rm{u}}'} } \right\},$$ (2)

    where Θ and $ \lambda $ refer to the potential temperature and latitude respectively, $ \overline {{\mathrm{v}}'{\mathrm{u}}'} $ refers to the eddy momentum flux and $ \overline {{\mathrm{v}}'\Theta '} $ refers to eddy heat flux. The divergence of the E–P flux is given by

    $$\hspace{-40pt} \nabla \cdot {\rm{F}} \equiv {\left({{\rm{a}}\;{\rm{cos\lambda }}} \right)^{ - 1}}\frac{\partial }{{\partial {\rm{\lambda }}}}\left({{{\rm{F}}^{\left({\rm{\lambda }} \right)}}{\rm{cos\lambda }}} \right) + \frac{{\partial {{\rm{F}}^{\left({\rm{z}} \right)}}}}{{\partial {\rm{z}}}}.$$ (3)

    There are large differences in the magnitude of the E–P flux throughout the troposphere and stratosphere. To clearly show the E–P flux in all levels of the troposphere and stratosphere, the E–P flux below 100 hPa is scaled by 1.0 and the flux between 100 and 10 hPa is scaled by 2.0 in Fig. 7(引用位置太靠前).

    Figure 7.  The distribution of the mean E–P flux (colored arrows) and its divergence (black contours) within 1 month (±15 lag days) around the central day of two types of SSW event: (a) wavenumber-1 for displacement SSW events, (b) wavenumber-2 for split SSW events, (c) wavenumber-1 for split SSW events and (d) wavenumber-2 for SSW events.

    We also use three-dimensional E–P flux (Plumb, 1985) to show the horizontal distributions of upward wave activity on pressure levels.

    $${{\rm{F}}_{3{\rm{D}}}} = \dfrac{{\rm{p}}}{{{{\rm{p}}_0}}}{\rm{cos\varphi }} \times \left[ {\begin{array}{*{20}{c}} {{{\rm{v}}^{'2}} - \dfrac{1}{{2{\rm{\Omega asin}}2{\rm{\varphi }}}}\dfrac{{\partial \left({{\rm{v'}}\Phi '} \right)}}{{\partial {\rm{\lambda }}}}}\\ { - {\rm{u'v'}} + \dfrac{1}{{2{\rm{\Omega asin}}2{\rm{\varphi }}}}\dfrac{{\partial \left({{\rm{v'}}\Phi '} \right)}}{{\partial {\rm{\lambda }}}}}\\ {\dfrac{{2{\rm{\Omega asin\varphi }}}}{{\rm{S}}}\left[ {{\rm{v'T'}} - \dfrac{1}{{2{\rm{\Omega asin}}2{\rm{\varphi }}}}\dfrac{{\partial \left({{\rm{T'}}\Phi '} \right)}}{{\partial {\rm{\lambda }}}}} \right]} \end{array}} \right],$$ (4)

    where φ, λ and Ф are latitude, longitude and geopotential height respectively.

    The meridional eddy heat flux $\overline {{\rm{v*}}T*} $ (Polvani and Waugh, 2004) is proportional to the vertical component of the E–P flux. We also use the eddy heat flux at 100 hPa to quantify the upward-propagating planetary wave activity. The first two zonal wavenumber components (wavenumber-1 and wavenumber-2) are applied to the eddy heat flux to quantify the different wave activity during different types of SSW event (displacement and split, respectively).

3.   Long-term variation of SSW events
  • First, we calculated the daily temperature anomalies (daily temperature minus climatology). The mean value of the temperature anomalies in 60–90°N for each SSW event is shown in Fig. 1a. SSW events are characterized by a rapid increase in polar stratospheric temperature, which reaches a maximum around the central day of the SSW event. On the basis of the definition of SSW strength in Section 2, Fig. 1b shows that the strength of SSW events has increased from 1958 to 2019. The maximum of the mean temperature anomaly in the stratospheric polar region (60–90°N, 10 hPa) increased at a rate of 0.13 K yr−1.

    Figure 1.  (a) The mean temperature anomalies in the polar region (60–90°N) at 10 hPa for each SSW event (grey lines) and the average of all SSW events (black line). The lag day 0 is the central day of SSW. (b) The maximum of mean temperature anomalies in the polar region within 1 month (±15 lag days) around the central day of the SSW event (black dots). The black line indicates the long-term trend of the maximum of mean temperature anomaly. The trends with “*” passed the 95% significance criterion.

    SSW events with shorter durations occur in any period of winter; however, the events with longer durations tend to occur in mid-winter (Fig. 2a). The long-term variation of SSW duration (Fig. 2b) shows that there were more SSW events with longer durations in the most recent two decades. Since 1998, 44% of events were longer than 15 days, but only 11% of events were longer than 15 days in 1979–1990. There were two SSW events longer than 30 days at the end of the 2010s. Although there were still SSW events with shorter durations in recent years, the duration generally increased at a rate of 0.21 days per year from 1958 to 2019.

    Figure 2.  (a) The duration of SSW events. (b) The duration of SSW events (black dots) and its long-term trend (black line). The trends with “*” passed the 95% significance criterion.

    Driven by strong upward-propagating planetary wave activity (Matsuno, 1971; Polvani and Waugh, 2004; Coy et al., 2009), SSW events are known to occur under a relatively weak stratospheric polar vortex (Scott and Polvani, 2006; Horan and Reichler, 2017). Therefore, we further analyzed the long-term variations of the upward-propagating planetary wave activity and the strength of the stratospheric polar vortex during SSW events. The upward-propagating planetary wave activity can be represented by the 100 hPa mean eddy heat flux within 45–70°N, which is where the strongest upward-propagating planetary wave activity is always observed (Fig. 7引用位置太靠前). Figure 3a shows the long-term variation of the mean value of this eddy heat flux during the SSW event. The eddy heat flux shows an increasing trend (0.06 K m s−1 yr−1), indicating enhancement of the upward-propagating planetary wave activity during SSW from 1958 to 2019. The mean zonal-mean zonal wind at the edge of the stratospheric polar vortex (60°N, 10 hPa), which represents the strength of stratospheric polar vortex, shows a decreasing trend of −0.03 m s−1 yr−1 (Fig. 3b). The enhancement in upward-propagating wave activity and decrease in polar vortex might be responsible for the increasing strength and duration of SSW events.

    Figure 3.  (a) The mean eddy heat flux in 1 month (±15 lag days) around the central day of SSW events within 45–70°N at 100 hPa. (b) The mean zonal-mean zonal wind in 1 month (±15 lag days) around the central day of SSW events at 60°N, 10 hPa. The long-term trends are shown as black lines.

4.   SSW classification and characteristics
  • According to the shape of the stratospheric polar vortex, SSW events can be divided into two types: vortex split SSW events, in which the polar vortex divides into two separate vortices; and vortex displacement SSW events, in which the polar vortex moves far away from the pole. On the basis of the definition of Charlton and Polvani (2007), there were 21 displacement and 19 split SSW events during the period of 1958–2019.

    Figure 4 shows the evolution of the polar vortex location at 10 hPa in the period of the SSW central day ± 8 days during displacement (Figs. 4ae) and split (Figs. 4fj) SSW events. The polar vortex is characterized by low geopotential height at a given pressure level. Therefore, the polar vortex locations can be represented by an area surrounded by a blue line for regions with geopotential heights less than 29.8 km at 10 hPa (Fig. 4). The polar vortices for 21 displacement SSW events were overlaid on a polar stereographic map. For displacement SSW events, the polar vortices are located over northern Europe and the North Atlantic Ocean before the central day (Figs. 4a, b). After the central day (Figs. 4ce), the polar vortices move farther from the pole (located south of 75°N) with much weaker strength (smaller areas of the polar vortices). Compared with displacement SSW events, the polar vortices before split SSW events are located not only over northern Europe and the North Atlantic Ocean but also over North America before the central day (Figs. 4f, g). On the central day of split SSW events, the polar vortices are clearly split and located over two regions: northern Europe and North America (Fig. 4h). The polar vortices weaken quickly after the central day of split SSW events (Figs. 4i, j). On the basis of the three-dimensional E–P flux (Plumb, 1985), Fig. 5 compares the corresponding upward-propagating planetary wave activity between displacement and split SSW events. During displacement SSW events, strong upward propagating planetary wave activities are observed over the north of Eurasia and the North Pacific (Figs. 5ae). However, during split SSW events, the strong upward-propagating planetary wave activities cover almost all of the high latitudes of the Northern Hemisphere. Compared with displacement SSW events, there are strong upward-propagating planetary wave activities over North America.

    Figure 4.  The locations of the polar vortex at 10 hPa (blue lines are geopotential height equal to 29.8 km) for (a–e) displacement and (f–j) split SSW events.

    Figure 5.  The locations of vertical upward wave activity equal to 0.2 m2 s−2 at 100 hPa (red lines) for (a–e) displacement and (f–j) split SSW events.

    The time distribution of the central date of the two types of SSW event are compared in Fig. 6. The mean date of displacement (late January, shown as the blue solid line) and split (early February, shown as the red solid line) SSW events did not show much difference. All SSW events occurred within the period of late November to late March. The earliest one is the 1968–1969 SSW event with the central day on 27 November 1968, and the latest one is the 1964–1965 SSW event with the central day on 23 March 1965. Therefore, we evenly divided the period from 27 November to 23 March into three parts: early winter (from 27 November to 4 January), middle winter (from 5 January to 12 February) and late winter (from 13 February to 23 March). On the basis of this division, two characteristics can be found in Fig. 6.

    Figure 6.  The dates of all SSW events. The blue and red dots are the central day of displacement and split SSW events, respectively. The blue and red solid lines are the averages of the central day of displacement and split SSW events, respectively. The whole winter period covering all SSW events is evenly divided into three periods (early, middle, and late winter) by the four black dashed lines.

    (1) The frequency of the two types of SSW event differs between the three winter periods. In early winter, there were nine displacement SSW events and only two split SSW events. However, in middle winter, there were ten split SSW events and only four displacement SSW events. The number of displacement and split SSW events were almost equal (eight displacement and seven split SSW events) in late winter. Comparing early winter with middle winter, it is interesting that displacement SSW events are dominant in early winter whereas split SSW events are dominant in middle winter.

    (2) There was a shift in the timing of SSW events toward middle winter. Most of the SSW events occurred in middle winter in the most recent two decades instead of being evenly distributed throughout the winter period, as they were before the 1990s. Given the result that SSW events with a longer duration occur in middle winter (Fig. 2a), the shift of SSW timing further explains the increase in SSW duration (Fig. 2b). Using a coupled chemistry–climate model, Ayarzagüena et al. (2013) also predicted a shift in the timing of major SSW events toward midwinter in the future.

    To further explain the frequency differences, we first show the distribution of the mean E–P flux in one month around the central days of the two types of SSW event (Fig. 7). There is a strong upward wavenumber-1 E–P flux in both displacement and split SSW events. The upward wavenumber-2 E–P flux is much weaker than the upward wavenumber-1 E–P flux in displacement SSW events. However, in split SSW events, there is a strong upward wavenumber-2 E–P flux. Thus, the type of SSW event depends more on wavenumber-2 rather than on wavenumber-1 planetary wave activity. The mean eddy heat flux at 50–65°N at 100 hPa can be used to quantify the upward-propagating planetary wave activity (Fig. 8). In general, the upward-propagating planetary wave activity involving all wavenumbers is strongest in middle winter and weakest in late winter (Fig. 8a). The upward-propagating wavenumber-1 planetary wave activity is strongest in early winter, and then gradually weakens in middle and late winter. The upward-propagating wavenumber-2 planetary wave activity is stronger (about 10 K m s−1) in middle winter than in early and late winter (about 5 K m s−1). The mean upward-propagating wavenumber-1 activity is much stronger than the mean upward-propagating wavenumber-2 activity in early winter, which led to more displacement SSW events than split SSW events. However, the mean wavenumber-2 activity enhanced and slightly exceeded the mean wavenumber-1 activity in middle winter, resulting in more split SSW events than displacement SSW events. In late winter, both wavenumber-1 and wavenumber-2 activity was weakened. The mean wavenumber-2 activity was smaller than the mean wavenumber-1 activity, but the difference between them (about 2.5 K m s−1) was not as large as in early winter (about 5 K m s−1). Therefore, the frequency of displacement and split SSW events is almost the same in late winter.

    Figure 8.  The mean eddy heat flux within 50–65°N at 100 hPa for (a) all wavenumbers and (b) wavenumber-1 (blue line) and wavenumber-2 (red lines). The whole winter covering all SSW events is evenly divided into three periods (early, middle and late winter) by the four black dashed lines. The horizontal solid lines represent the mean values during the three winter periods.

    For the shift in the SSW timing toward middle winter, we calculated the trends of mean eddy heat flux within 50–65°N at 100 hPa and mean zonal-mean zonal wind around the polar vortex in the three winter periods (Table 2), as we did in Fig. 3. The most significant trends occur in middle winter, during which the mean eddy flux is increasing at a rate of 0.08 K m s−1 yr−1 and the mean zonal-mean zonal wind is decreasing at a rate of −0.08 m s−1 yr−1. This means that the planetary wave activity becomes more active and the westerly winds around the stratospheric polar vortex become weaker. In early winter, even though the mean eddy heat flux is increasing, the strengthening of the westerly winds around the polar vortex is still against the onset of SSW events. In late winter, there are small changes in the mean eddy heat flux and mean zonal wind. It becomes easier for the SSW events to occur under the condition of enhancing upward-propagating planetary wave activity and weakening westerly winds around the stratospheric polar vortex, leading to a shift in the SSW timing toward middle winter.

    Early winterMiddle winterLate winter
    (a) Mean eddy heat flux
     (K ms−1 year−1)
    0.05*0.08 0.01
    (b) Mean zonal wind
     (ms−1 year−1)
    0.11−0.08−0.01

    Table 2.  The long-term trends of (a) mean eddy heat flux within 50–65°N at 100 hPa and (b) mean zonal wind at 60°N and 10 hPa in early, middle and late winter. The trends with “*” passed the 95% significance criterion

5.   Downward propagation and surface temperature anomalies
  • As the frequency and wave activity of displacement and split SSW events differ between the three winter periods, we further divided the SSW events into six types: early displacement, early split, middle displacement, middle split, late displacement and late split SSW events. The NAM index for the six types of SSW event were compared (Fig. 9) to study the different characteristics of the downward propagation of SSW events. The NAM index is calculated based on first empirical orthogonal function analysis of the daily mean geopotential height (Baldwin and Dunkerton, 1999). It should be noted that there are only two early split SSWs and four middle displacement SSW events, making the results for these two types of event less reliable than the results for the other four types. A strong negative NAM index occurs around the central day of both early displacement and middle split SSW events. The NAM index for these two types of event indicates downward propagation into the troposphere. Compared with the early displacement SSW events, a strong positive NAM index occurs about 40–80 days after the onset of SSW events after the onset of middle split SSW events. The positive NAM index lasted about 40 days and propagated form 10 hPa to 100 hPa, suggesting the recovery of the stratospheric polar vortex. The negative NAM indices of late displacement and split SSW events are much weaker and of shorter duration than that during the early displacement and middle split SSWs. It is difficult for these relatively weak stratospheric signals to propagate into troposphere. Thus, the influence of the late SSW events on the troposphere is not as significant as the influence of the early displacement and middle split SSWs.

    Figure 9.  The NAM index (contours, blue for negative; red for positive) for six types of SSW event: (a) early displacement, (b) early split, (c) middle displacement, (d) middle split, (e) late displacement and (f) late split SSW events. The color shading indicates statistical significance at the 95% confidence level based on a t-test.

    To study the influence of different types of SSW event on surface weather, we compared the composites of the mean surface temperature anomalies for the 30 days after the central day of six types of SSW event. However, the composites were not statistically significant (not shown here). Instead, we show the location of the surface cold center (Fig. 10), which is defined as the area where the mean surface temperature anomalies in the 30 days after the central day of the SSW event are less than or equal to a temperature threshold (−4 K in this paper). The surface temperature anomaly is defined as daily surface temperature minus the climatology. The middle displacement (Fig. 10b) and early split (Fig. 10d) SSW events can be ignored in this discussion due to the few samples. Compared with late SSW events, there are more cold centers after the early displacement and middle split SSW events. The greatest difference between the early displacement and middle split SSW events is that there are more cold centers in Russia and the north of China after the onset of middle split SSW events (Fig. 10e). The other difference is that there are more cold centers in North America and fewer in Canada after the onset of middle split SSW events. The cold centers after the late displacement SSW events are mainly limited to high latitudes. Compared with late displacement SSW events, more cold centers occurred in northern Eurasia after the late split SSW events (Fig. 10f). The area of the surface cold center depends on the temperature threshold we choose, but the patterns are similar to Fig. 10. If we choose a larger threshold (e.g. −3 K), the location of the cold center extends to a lower latitude. When the temperature threshold is smaller (e.g. −5 K), the area of the surface cold center is located at higher latitudes.

    Figure 10.  The location of the surface cold center for six types of SSW event: (a) early displacement, (b) middle displacement, (c) late displacement, (d) early split, (e) middle split and (f) late split SSW events. Blue lines are the mean surface temperature anomalies for the 30 days after the central day of the SSW events equal to −4 K.

6.   Conclusions and discussion
  • Using the NCEP/NCAR reanalysis data, we investigated the characteristics and long-term variations of major SSW events from 1958 to 2019. We found that the strength and the duration of the major SSW events has increased, which manifested as an increase in the maximum temperature in the polar region and an increase in the duration of the easterly winds around the polar vortex during the SSW events. As the upward-propagating planetary wave activity (Matsuno, 1971; Polvani and Waugh, 2004; Coy et al., 2009) and the relatively weak westerly zonal winds around the polar vortex (Scott and Polvani, 2006; Horan and Reichler, 2017) are known as the two conditions for the occurrence of SSW events, we also investigated the long-term variation of the mean zonal wind around the polar vortex. The variations of SSWs can be attributed to the enhancing planetary wave activity, which is shown as an increase in upward eddy heat flux within 50–65°N at 100 hPa.

    On the basis of the definition of SSW types by Charlton and Polvani (2007), 21 displacement and 19 split SSW events were identified from 1958 to 2019. During the displacement SSW events, the polar vortex was located over northern Europe and the North Atlantic Ocean with strong upward-propagating planetary wave activity over the north of Eurasia and the North Pacific. Compared with displacement SSW events, the polar vortex during the split SSW events, which weakens quickly after the central day of SSW events, was located not only over northern Europe and the North Atlantic Ocean but also over North America due to the strong upward-propagating planetary wave activity over North America. We further distinguished all SSW events in early, middle and late winter. Two interesting characteristics were found:

    (1) The frequency of the two types of SSW event differs between the three winter periods. We use the E–P flux and eddy heat flux to show that SW events in early winter are almost always displacement SSW events due to the stronger upward wavenumber-1 activity. However, the wavenumber-2 activity is enhanced and almost equal to wavenumber-1 activity in middle winter, resulting in a greater number of split SSW events (ten events) than displacement SSW events (four events) in this period. In late winter, the frequency of displacement and split SSW events is almost the same. The wavenumber-2 activity was smaller than the wavenumber-1 activity in late winter, but the difference between them was not as significant as in early winter.

    (2) There was a shift in the timing of SSW events toward middle winter. The most significant increase in the mean eddy flux and decrease in the mean zonal wind around the polar vortex was found in the middle winter, indicating enhancing upward-propagating planetary wave activity and weakening westerly winds around the polar vortex. Under these conditions, it became easier for SSW events to occur in middle winter. Given that there were a greater number of split SSW events (ten events) than displacement SSW events (four events) in middle winter, there might be more split SSW than displacement SSW events in the future if the SSW timing continues to shift toward middle winter. Mitchell et al. (2012a) argued that although most SSW events (1960–2000) occur in February, a climate model showed that SSW events will become more evenly distributed throughout winter during the periods of 2010–2050 and 2060–2100. They predicted that there will be more displacement SSW events in the future due to an increase in wavenumber-1 activity. Therefore, whether there will be more split SSW events or displacement SSW events in the future is worth exploring.

    The downward propagation represented by the NAM index shows differences during the six types of SSW event: early displacement, early split, middle displacement, middle split, late displacement and late split SSW events. The composites of the mean surface temperature anomalies for the 30 days after the central day of the six types of SSW event are not as statistically significant as in Mitchell et al. (2013), because of the amplified uncertainty when subdividing displacement and split SSW events into early, middle and late types. However, this does not mean that the tropospheric state is insensitive to the SSW type. We found that there were more surface cold centers in Russia and northern China after the onset of the middle split SSW events than early displacement SSW events. Also, there were more cold events in North America and fewer in Canada after the onset of middle split SSW events than early displacement SSW events. Compared with early and middle SSW events, the surface cold centers after the late SSW events were less significant. It should be noted that the influence of early split and middle displacement SSW events on the surface weather are still unknown due to the limited number of samples. If the SSW timing continues to shift toward middle winter and SSW strength and duration continue to increase in the future, we expect stronger and longer-lasting SSW events in the middle winter, during which the polar vortex split might occur more frequently than the polar vortex displacement. Therefore, we should pay more attention to the surface response to middle split SSW events.

    Acknowledgments. We thank NCEP/NCAR for providing the reanalysis data, which are freely available at https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html.

Reference (40)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return