1. Introduction
Low-frequency atmospheric variability has been of particular interest for meteorologists during the last decades considering its potential promise for medium- and extended-range weather forecasting and its profound societal and economic impacts. Early observational studies suggest that a surprisingly large portion of variance in the low-frequency variability can be well explained by a few recurring patterns (Horel 1981; Wallace and Gutzler 1981; Barnston and Livezey 1987). Later studies found diverse causes for the occurrence of these patterns such as the atmospheric response to slowly varying thermal forcing from oceans (e.g., Horel and Wallace 1981; Shukla and Wallace 1983; Branstator 1985; Geisler et al. 1985; Wang et al. 2018), interactions with the climatological stationary waves (Hoskins et al. 1983; Simmons et al. 1983; Branstator 1990, 1992), forcing by anomalous fluxes from high-frequency transients (Lau and Holopainen 1984; Lau 1988; Held et al. 1989; Cai and Mak 1990; Lau and Nath 1991; Branstator 1992, 1995; Liu et al. 2014), and transition between different climatic regimes (Charney and DeVore 1979; Charney and Straus 1980; Yang et al. 2010). Recently, the role of quasi resonance of forced and free waves in exciting the summertime teleconnection patterns was also proposed (Petoukhov et al. 2013; Coumou et al. 2014; Screen and Simmonds 2014; Kornhuber et al. 2017; Mann et al. 2017).
A new type of teleconnection pattern was identified by Hsu and Lin (1992) through diagnosing the 250-hPa streamfunction field. This pattern propagates along the upper-tropospheric subtropical jet and shows a meridionally confined and zonally oriented feature, both of which are very different from the canonical patterns that are characterized by arching structures with pronounced meridional group velocity due to the spherical effect (Hoskins et al. 1977). Hoskins and Ambrizzi (1993) found that this teleconnection pattern can be well simulated by subjecting a barotropic model to a localized forcing when linearized about the realistic climatological mean flow. They suggested that the zonally oriented character can be well explained by the fact that Rossby wave tends to propagate toward the region with a larger value of refractive index in the light of Wenzel–Kramer–Brillouin (WKB) approximation (Hoskins and Karoly 1981; Karoly and Hoskins 1982), which means that the Rossby wave will be trapped in the latitudes of local maximum refractive index where the tropospheric jet generally resides. Therefore, the jet stream can act as a waveguide and facilitate the zonal propagation of Rossby wave if the longitudinally confined jet has sufficient zonal extent (Branstator 1983, 2002; Branstator and Teng 2017) and has the possibility to allow wave resonance in certain background conditions (Manola et al. 2013; Petoukhov et al. 2013; Kornhuber et al. 2017). Later studies investigated the dynamics of the waveguide under more complicated circumstances, such as in basic flows that are baroclinic (Ambrizzi and Hoskins 1997), zonally varying (Naoe et al. 1997), or time-varying (Terao 1998; Branstator and Teng 2017). Overreflection and nonlinear effects within the waveguide are also studied in Branstator (1983) and Naoe and Matsuda (1998, 2002), respectively.
The concept of the waveguide was initially proposed for the background state in boreal winter, but it also applies to the situation in the boreal summer (Ambrizzi et al. 1995) when the subtropical waveguide is located approximately 10° northward compared with that in winter. By analyzing one-point correlation maps of the 200-hPa meridional wind, Lu et al. (2002) identified a wavelike teleconnection pattern along the upper-tropospheric subtropical jet over the Eurasia. Enomoto et al. (2003) further confirmed its nature as a stationary Rossby wave train trapped in the jet and named it the Silk Road pattern (SRP). It is suggested that sometimes the trapped energy can be (re)generated or enhanced by the local perturbations downstream, forming a circumglobal teleconnection (CGT; Ding and Wang 2005, 2007; Ding et al. 2011) without energy being much dispersed over a broad region.
(a) The standard deviation of the summer mean 250-hPa meridional wind during the period 1979–2015 [shading interval (SI) = 1 m s−1]. The red box indicates the region to perform EOF analysis. (b) The meridional gradient of the climatological summer mean 250-hPa potential vorticity (PV) (SI = 0.5 × 10−12 m−1 s−1). (c) The zonal gradient of the climatological summer mean 250-hPa zonal wind (SI = 2 × 10−6 s−1).
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
Although there are some studies on the summertime teleconnections over northern Eurasia, most of them focus not on the teleconnection pattern itself but on the observed climate anomalies. For example, many studies investigated the atmospheric anomalies associated with anomalous behaviors of the Okhotsk high (Wang 1992; Wang and Yasunari 1994; Nakamura and Fukamachi 2004; Sato and Takahashi 2007) because a strong Okhotsk high often induces strengthened northeasterly to the northeastern Japan, leading to devastating influence on the local rice crops (Ninomiya and Mizuno 1985a,b; Kodama 1997). Fukutomi et al. (2003) also discussed the atmospheric pattern that is related to the water balance in Siberia. On the other hand, there are indeed some studies that define teleconnection patterns in northern Eurasia, but the wavelike structure in these studies is not very clear or shows a large zonal symmetric component (Wakabayashi and Kawamura 2004; Lin 2014). According to Branstator (2002), such a zonal symmetric component to a large extent is actually temporally independent of the wavy component and tends to mask the downstream and upstream negative centers. Thus, the symmetric component should be avoided when attempting to extract such trapped mode along the waveguide. Iwao and Takahashi (2008) also investigated the dominant summertime teleconnection pattern over Eurasia. However, they focused on the covariations between the quasi-stationary Rossby waves along the subtropical jet and PFJ, and did not investigate the dominant pattern along the PFJ itself. In addition, the dynamical nature of the leading teleconnection pattern along the PFJ, such as its excitation and maintenance mechanisms, is still not clear. Hence, it is necessary and meaningful to investigate the leading teleconnection pattern along the summertime PFJ in northern Eurasia thoroughly.
In this study, the dominant mode along the summertime PFJ will be defined from quantitative considerations. Its structure, climate influence, and dynamics are analyzed in detail. Its potential predictability on the interannual time scale is also discussed. The remainder of this paper is organized as follows. Section 2 describes the datasets and methods used in this study. Section 3 defines the teleconnection pattern and investigates its structure and associated climate anomalies. Section 4 analyzes the dynamics of the teleconnection pattern in detail. Section 5 discusses the potential predictability of the teleconnection pattern including the excitation mechanism and relation to external forcing. Finally, section 6 gives a brief summary and section 7 discusses some remaining issues.
2. Data and methods
Monthly mean atmospheric reanalysis data used in this study are from the ERA-Interim dataset (Dee et al. 2011) from the European Centre for Medium-Range Weather Forecasts (ECMWF) on a 2.5° × 2.5° grid. The monthly mean precipitation and surface air temperature datasets employed here are the Climatic Research Unit (CRU) high-resolution gridded datasets, version 4.00 with 0.5° × 0.5° resolution (CRU TSv4.00; Harris et al. 2014). The Global Precipitation Climatology Project (GPCP) monthly data provided by the NOAA/OAR/ESRL PSD with 2.5° × 2.5° resolution are also used to check the uncertainty in the precipitation data (Adler et al. 2003). The interpolated monthly mean outgoing longwave radiation (OLR) data on a 2.5° × 2.5° grid for the period of 1979–2015 from the National Oceanic and Atmospheric Administration (NOAA) are employed to serve as a proxy for convection (Liebmann and Smith 1996). Monthly mean precipitation and surface air temperature of 160 stations in China provided by the National Climate Center (NCC) of the China Meteorological Administration (CMA) are used to check the climate anomalies in China. The oceanic data are from the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset (Rayner et al. 2003). The snow cover data are available after October 1966 and obtained from the National Snow and Ice Data Center (NSIDC) (Brodzik and Armstrong 2013). The monthly North Atlantic Oscillation (NAO) index is downloaded from http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml. In addition to the monthly mean atmospheric reanalysis, we also employ the daily mean and 6-h mean ERA-Interim datasets to calculate the feedbacks of the high-frequency transients on the low-frequency flow and the apparent heat source defined in Yanai et al. (1973). Since the ERA-Interim reanalysis dataset used in this study only covers the limited period of 1979–2015, we have employed other longer datasets to check the robustness of the results. These reanalysis datasets include the Japanese 55-Year Reanalysis (JRA-55) dataset (Kobayashi et al. 2015), the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis dataset (Kalnay et al. 1996), and the ECMWF Twentieth Century Reanalysis (ERA-20C) dataset (Poli et al. 2016). Because the results are insensitive to the concerned periods and highly consistent among datasets, only the results based on the ERA-Interim dataset are presented unless otherwise stated.
This study focuses on the boreal summer mean, which is defined as the mean of June, July, and August (JJA). The empirical orthogonal function (EOF) analysis was employed to extract the leading modes along the summertime PFJ. The corresponding normalized leading principal component (PC) is regarded as an index. Various meteorological variables are then regressed against the index to show the associated spatial structure. The statistical significance test of linear regression is evaluated by the two-tailed Student’s t test. To obtain the disturbance with synoptic time scales, a 2–10-day Lanczos bandpass filter has been applied to the daily data (Duchon 1979), and the wave activity and eddy flux associated with transients are then evaluated using the bandpass filtered data.
3. The British–Baikal Corridor pattern along the summertime PFJ
To extract the leading teleconnection pattern along the PFJ, EOF analysis was applied to the 250-hPa meridional wind over the domain 50°–80°N, 20°W–150°E, depicted by the red box in Fig. 1a. There are several reasons for us to use this definition. First, Branstator (2002) suggested that defining wave trains using meridional wind can intrinsically put more emphasis on a shorter zonal scale and filter out the zonal symmetric component that is temporally independent of the wavy component. Thus, it is preferentially able to extract the waveguide mode compared to using streamfunction or geopotential height. Second, considering that the waveguide along the PFJ is most distinct at the tropopause where the separation with the subtropical waveguide is clear (Iwao and Takahashi 2008), the level of 250 hPa is used to define the pattern. Third, the domain 50°–80°N, 20°W–150°E corresponds to the maximum interannual variability of meridional wind over northern Eurasia and to a large extent reflects the validity of the waveguide along the PFJ (Fig. 1). Hence, this domain is used for the EOF analysis.
The first three EOFs and corresponding PCs are presented in Fig. 2. These EOFs are all well separated from other counterparts according to the criteria of North et al. (1982). Broadening or narrowing the domain yields similar patterns, although the explained variance increases or decreases as the domain changes. The leading EOF (EOF1) and second EOF (EOF2) explain 27.9% and 19.5% of the total variance, respectively. The two EOFs share similar spatial structure although the phases are longitudinally shifted due to the orthogonality. EOF2 actually is the pattern documented by Iwao and Takahashi (2008) when investigating the covariation relationship between the precipitation in northeastern Asia and Siberia. The third EOF (EOF3) explains the 10.6% of the total variance and its spatial pattern shows distinct discrepancy with EOF1 and EOF2. In this study, we will focus on EOF1, which explains the largest fraction of variance along the summertime PFJ.
(a),(c),(e) The first three EOFs of summer mean 250 hPa meridional wind over the region 50°–80°N, 20°W–150°E for the period 1979–2015 (unit: m s−1). (b),(d),(f) The corresponding normalized PC time series. The percentage of explained variance by each EOF is indicated in the upper right of (a), (c), and (e).
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
Figure 3 shows the three-dimensional structure associated with EOF1, which features a wavelike structure in the upper troposphere (Fig. 3a). The wavelike structure consists of four geographically fixed lobes with centers being located over the west of Britain, the Baltic Sea, western Siberia, and Lake Baikal. It has a zonal wavenumber 5, which is consistent with the deduced stationary Rossby wavenumber under the WKB approximation (Iwao and Takahashi 2008). The horizontal wave activity flux (Takaya and Nakamura 2001) emanates from the center near Britain and propagates eastward continuously, confirming its nature as a stationary Rossby wave train. The zonally oriented and meridionally confined structure suggests that this wave train tends to be trapped by the waveguide of the PFJ. The vertical cross section along the major centers of action (blue lines in Fig. 3a) shows that the wave train is equivalent-barotropic and tilts westward with height in the lower-to-middle troposphere (Fig. 3b). The center of the anomalous temperature field is located slightly westward to that of the anomalous geopotential field. It indicates efficient meridional eddy heat flux, which can also be interpreted from the strong upward wave activity fluxes. A closer examination suggests that the baroclinicity of the center near the British Isles is weaker than other three centers, probably due to the larger meridional gradient of climatological temperature over the Eurasian continent in the lower troposphere (also see Fig. 8b). The spatial pattern presented in Fig. 3 indicates that the PFJ acts like an expressway to facilitate disturbance near the British Isles to propagate downstream to the Lake Baikal. Thus, this teleconnection is named the British–Baikal Corridor (BBC) pattern to reflect the nature of this waveguide mode. Accordingly, the PC1 time series shown in Fig. 1b is defined as the BBC index. Compared with previously documented teleconnection patterns that are defined more or less arbitrary or include a large zonal symmetric component, the BBC pattern has a clearer wavy structure and is defined with more quantitative considerations.
(a) The regressed summer mean 250-hPa geopotential height [black contour; contour interval (CI) = 10 gpm] onto the BBC index and associated horizontal component of the wave activity flux (arrow; unit: m2 s−2). The 20 m s−1 contour of climatological 250-hPa summer mean zonal wind is indicated with a purple contour. The major action centers that are labeled with letters A–F are connected by the thick blue lines. (b) The vertical cross sections of regressed summer mean geopotential height (black contour; CI = 5 gpm), air temperature (blue contour; CI = 0.3°C), and wave activity flux (vector; unit: m2 s−2) along the blue solid line in (a). The horizontal component of wave activity flux in (b) is calculated as the mean square of the zonal and meridional components of wave activity flux. The vertical component has been multiplied by a factor of 120 for visual purposes. Zero contours have been omitted and negative contours are dashed. The light and dark shading indicate the 95% and 99% confidence levels based on a two-tailed Student’s t test, respectively.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
Like the SRP pattern that could affect the climate in Europe, Mongolia, China, and Japan (Enomoto et al. 2003; Iwasaki and Nii 2006; Saeed et al. 2014; Huang et al. 2012; Wang et al. 2017), the BBC pattern can also affect the local climate significantly along its route. Figure 4 shows that anomalous ascending (descending) motion is located between the front of anomalous cyclone (anticyclone) and rear of anomalous anticyclone (cyclone) over Eurasia (Fig. 4a), consistent with the constraint of the omega equation under the quasigeostrophic framework. Corresponding to the anomalous vertical motion, enhanced (suppressed) precipitation can be observed over northeast Europe and northeast Asia (central Siberia) (Figs. 4b,c). Large-scale warming and cooling can also be observed right below the anomalous anticyclonic and cyclonic circulation centers (Fig. 4d). In addition to the prominent climate anomalies over northern Eurasia, there is also a significant increase of precipitation in northern China. Repeating the regression but using the station data provided by CMA yields a similar result (figure not shown). This influence can be easily explained by the circulation pattern associated with the BBC pattern. Referring to Fig. 3, an anomalous barotropic low is located above Lake Baikal. To its western flank, this anomalous low will favor anomalous northerlies near the surface (figure not shown). As a result, the confluence of the cold/dry and warm/wet air masses over northern China facilitates the cyclogenesis and enhances precipitation.
Regression of the summer mean (a) 500-hPa vertical velocity (SI = 0.002 Pa s−1), (b) OLR (SI = 2 W m−2), (c) precipitation (SI = 2 mm month−1), and (d) surface air temperature (SI = 0.2°C) onto the BBC index for the period of 1979–2015. Gray and black dots indicate the 95% and 99% confidence levels based on a two-tailed Student’s t test, respectively.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
4. Dynamics of the BBC pattern
a. Vorticity budget
Figure 5 suggests that S, ZA, and Beta are the dominant terms in the linearized vorticity equation. The term S is located upstream of the BBC pattern with one-quarter of a wavelength. Further decomposition of term S shows that it is primarily contributed by the stretching term (figure not shown), indicating that the RWS is closely related to the convergence and divergence in the upper troposphere. A close comparison between Figs. 5a and 4c reveals a high resemblance between term S and the anomalous precipitation field associated with the BBC pattern. This is not surprising because the anomalous latent heat release induced by precipitation anomalies can lead to divergence or convergence and thereby contribute to the generation of RWS in the upper troposphere.
Vorticity budget of the BBC pattern at 250 hPa (SI = 2 × 10−11 s−2) using Eq. (2): (a) the RWS term, (b) the zonal advection term (ZA), (c) the meridional advection term (MA), (d) the beta effect term (Beta), and (e) the residual term (Res).
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
The term ZA is located slightly downstream to the major centers of actions of the BBC pattern, indicating that the perturbed vorticity is advected downstream by the climatological rotational westerly. The term Beta is located upstream to the BBC pattern, consistent with the traditional notion that the advection of the climatological vorticity tends to shift the wave pattern westward. Therefore, the above analysis of vorticity equation reveals a clear picture of the BBC pattern as follows. The Rossby wave source S associated with the BBC pattern is mainly caused by the latent heating released by the precipitation anomalies, and it is primarily balanced with the zonal advection of anomalous vorticity by the climatological rotational flow (ZA) that tends to move the BBC pattern downstream and the advection of the climatological mean vorticity by anomalous rotational flow (Beta) that tends to move the BBC pattern upstream. The term Res does not organize itself into any well-defined pattern that shows comparable amplitude to terms S or ZA, so its possible role is not explicitly investigated. But the nonnegligible magnitude of the term Res indicates that other effects such as dissipation or nonlinear effect may play some role in the balance of the vorticity budget. Nevertheless, the vorticity budget shown here can reveal the primary maintenance mechanism associated the BBC pattern at least qualitatively.
b. Temperature budget
Surface-to-850 hPa-integrated temperature budget (SI = 2 × 10−4 K s−1) of the BBC pattern using Eq. (4). (a) Zonal advection of anomalous temperature by basic flow, (b) zonal advection of mean temperature by anomalous wind, (c) meridional advection of anomalous temperature by basic flow, (d) meridional advection of mean temperature by anomalous wind, (e) vertical advection of anomalous temperature by basic flow, (f) vertical advection of mean temperature by anomalous vertical motion, (g) diabatic heating, and (h) the residuals. Subscripts A and B indicate the anomalous and the climatological mean quantities.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
c. Water vapor budget
Surface-to-100 hPa-integrated water vapor budget (SI = 10−1 g m2 s−1) using Eq. (5). Divergence of water vapor caused by (a) the divergence of anomalous specific humid in the zonal direction, (b) the divergence of anomalous specific humid in the meridional direction, (c) the divergence of anomalous zonal wind, (d) the divergence of anomalous meridional wind, and (e) the sum of all terms in (a)–(d). Subscripts A and B indicate the anomalous and the climatological mean quantities.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
The term 
d. Energetics budget
Previous studies suggested that the SRP is a dynamical mode inherent in the subtropical jet because it can extract energy efficiently from basic flow via barotropic (Sato and Takahashi 2006) and baroclinic processes (Kosaka et al. 2009; Chen et al. 2013). As the counterpart teleconnection along the summertime PFJ, it is possible that the BBC pattern may also owe its dominance and geographically fixed nature to the interactions with basic flow. This issue will be investigated in this section.
The BBC pattern-associated (a) barotropic energy conversion (contours; CI = 0.4 × 10−2 W m−2), (b) baroclinic energy conversion (contours; CI = 0.4 × 10−2 W m−2), and (c) perturbed APE generation due to diabatic heating (contours; CI = 0.4 × 10−2 W m−2). The energy conversion terms are integrated vertically from surface to 100 hPa. Negative contours are dashed. Shading in (a) represents the region where 250-hPa climatological zonal wind velocity is larger than 20 m s−1. Red contours in (b) represent the climatological temperature at the 950 hPa (CI = 3 K). Shading in (c) indicates the regressed summertime precipitation onto the BBC index based on CRU TS v4.00 dataset.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
The efficiency of various conversion terms can be quantitatively evaluated by the time scale with which the eddy energy associated with the BBC pattern could be replenished by a particular conversion term. Various characteristic time scales, which are denoted as τCK, τCP, τCQ, τDry, and τTotal, represent the efficiency of the conversions by CK, CP, CQ, dry energy conversion (CK and CP), and total energy conversion (CK, CP, and CQ), respectively. See Kosaka and Nakamura (2010) for more details. The eddy energy and conversion term are both integrated horizontally between 5° and 85°N over the entire Northern Hemisphere and then integrated vertically from 1000 to 100 hPa. Choosing other integrated domains and levels also yields qualitatively similar conclusion. If the conversion time scale is shorter (longer) than a season, then the associated term is considered to be efficient to fuel (damp) the pattern.
The values of various time scales are listed in the column labeled as “original” in Table 1. It suggests that the BBC pattern gains energy from the basic state mainly through baroclinic energy conversion. Although barotropic conversion also contributes to the maintenance of the BBC pattern to some extent, its time scale is longer than a season and thus should not be considered as an efficient energy source. CQ actually damps the BBC pattern, although its efficiency is low. The net effect of these energy conversions suggests that the total energy of the BBC pattern can be filled up within 10 days. Therefore, similar to the SRP pattern, the BBC pattern is also an intrinsic dynamical mode inherent in the basic flow. The dominance of baroclinic conversion over other conversion terms is consistent with the fact that the BBC pattern is a waveguide mode formed from the large meridional gradient of stratification.
Time scales (days) when the spatially integrated energy associated with the BBC pattern could be replenished through a particular energy conversion term. The replenished time is also evaluated after the anomaly pattern has been shifted zonally relative to the basic flow as indicated. Here, τCK, τCP, τCQ, τDry, and τTotal represent the efficiency of the conversions by, respectively, barotropic energy conversion, baroclinic energy conversion, diabatic generation, dry energy conversion (barotropic plus baroclinic energy conversions), and total energy conversion (dry energy conversion plus diabatic generation). The eddy energy and conversion terms have been integrated horizontally between 5° and 85°N over the Northern Hemisphere and vertically from 1000 to 100 hPa. The conversion time scale, which is positive (negative) and shorter than a season, is considered as the efficient fueling (damping) term.
As shown in previous sections, the BBC pattern is a stationary Rossby wave train with geographically fixed centers. From an energetic view, this phase-locked nature may possibly imply preferred region(s) where local energy extraction from the basic flow is particularly efficient for the maintenance against dissipation. To investigate this issue, the above energetic analyses were repeated by shifting the BBC pattern westward or eastward relative to the basic flow, like in Kosaka and Nakamura (2010) and Hu et al. (2018). The purpose of such an “experiment” is to find out whether the original phase is the optimal configuration for energy conversion. The shifted longitudes relative to the basic flow are indicated as the label in Table 1. This reveals that although CK contributes little to the maintenance of the BBC pattern in its original configuration, it decreases rapidly and even becomes an efficient damping term when the pattern shifts 20° zonally. The efficiency of CP also decreases when the pattern shifts either eastward or westward, but CP is not as sensitive to the longitudinal shift of basic flow as CK. This is because CP is mainly determined by the vertically averaged distribution of climatological meridional gradient of temperature in the troposphere (Kosaka et al. 2009). The absolute value of τCQ is always considerably larger than a season regardless of longitudinal shifting, indicating a negligible role of CQ in anchoring the phase of the BBC pattern. To summarize, the energetics analyses suggests that the BBC pattern is an optimal pattern for energy conversion. Although CK is not as efficient as CP to maintain the BBC pattern, it tends to anchor the phase of the BBC pattern geographically because it is highly sensitive to subtle configuration of the basic flow. In contrast, other terms like CP or CQ only play a very limited role in this aspect.
5. Potential predictability of the BBC pattern
a. Excitation mechanism
Previous studies suggested that current numerical models exhibit some predict skills for the waveguide mode along the subtropical jet (Teng et al. 2013; Wang et al. 2014; Schroeder et al. 2017). As the dominant mode along the summertime PFJ on the interannual time scale, it is possible that the interannual variability of the BBC pattern may be linked to some concurrent external forcing and thereby exhibits some potential predictability (Arai and Kimoto 2005). However, no immediate tropical sea surface temperature (SST) or convections were found to be significantly correlated with the BBC pattern either in simultaneous winter or in preceding seasons (figure not shown), in contrast to the SRP, which shows close relation to certain forcing in low latitudes (Krishnan and Sugi 2001; Wu 2002; Enomoto et al. 2003; Enomoto 2004; Ding and Wang 2005; Ding et al. 2011; Yim et al. 2014). This is possible because the BBC pattern is located at higher latitudes than the SRP. Moreover, no significant relations were found with the sea ice, snow cover, and SST in the middle and high latitudes (figure not shown). The weak immediate relation to external forcing indicates that the BBC pattern is very likely an atmospheric internal mode, and that its phase on interannual time scale is very likely unpredictable due to the dominance of its chaotic nature.
The weak immediate relation to external forcing raises an intriguing question on how the atmospheric internal dynamics regulates the excitation of the BBC pattern. Referring to Fig. 3a, it shows that the center of action near the British Isles is a key center that the zonally oriented wave train emanates from. Note this center also resides in the exit region of the North Atlantic jet where the interannual variability of meridional wind is particularly strong (Fig. 1a). Simmons et al. (1983) pointed out that the flow tends to be barotropically unstable in the jet exit region where the zonal shear of the basic zonal wind is strong. The low-frequency variability, once being excited there by certain remote forcing that is not confined to a particular location, could develop readily through deriving barotropic energy from the basic flow. On the other hand, the presence of low-frequency circulation anomalies will also modify the activity of high-frequency transients by barotropically steering the disturbance or inducing local instability (Robertson and Metz 1989; Cai and Mak 1990; Robertson and Metz 1990; Cai and van den Dool 1991, 1992; Branstator 1995), which may further reinforce the low-frequency circulation anomalies through eddy vorticity and heat fluxes (Shutts 1983; Illari 1984; Lau and Holopainen 1984; Mullen 1987; Lau 1988; Lau and Nath 1991; Branstator 1992). Therefore, it is possible that the excitation of the BBC pattern may involve the barotropic instability and the interactions between the low-frequency circulation anomalies and high-frequency synoptic-scale transients in the exit region of the Atlantic jet stream.
Section 4d suggests that the vertically integrated barotropic energy conversion only has a limited contribution to the maintenance of the BBC pattern. In contrast, Fig. 9a suggests that the barotropic energy conversion has large value in the upper troposphere. Note that positive CK can be observed near the southeastern flank of the Atlantic jet. It indicates that the BBC pattern can gain barotropic energy there that is closely linked to the barotropic instability in the exit region of the summertime Atlantic jet. On the other hand, the low-frequency circulation can also modulate the activity of storm tracks. Figure 9b presents the composite storm track represented by the variance of bandpass-filtered 250-hPa meridional wind in positive (red contours) and negative phases of the BBC pattern (blue contours). The positive (negative) phases are defined as summers that the BBC index is larger (less) than 0.5 (−0.5) standard deviation. The North Atlantic storm track tends to migrate northward when the BBC pattern is positive and southward when the BBC pattern is negative. The regressed storm track onto the BBC index (Fig. 9c) confirms the above composite results, with a zonally elongated meridional dipole straddling the climatological storm track axis (Fig. 9c). In addition, significant changes of transient eddy activities can also be observed over eastern Europe, central Siberia, and the coast of the Laptev Sea, which may be related to changes of the local westerlies.
(a) As Fig. 8a, but for the barotropic energy conversion at 250 hPa. (b) The composite of storm track when the BBC index is larger than 0.5 (red; CI = 30 m2 s−2 starting from 75 m2 s−2) and smaller than −0.5 (blue; CI = 30 m2 s−2 starting from 75 m2 s−2) standard deviation. (c) Regression of storm track onto the BBC index (CI = 4 m2 s−2). (d) Geopotential height tendency induced by high-frequency transient eddies (CI = 1 gpm day−1). The light and dark shading in (c) and (d) indicate the 95% and 99% confidence levels based on a two-tailed Student’s t test, respectively.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
The BBC-related positive barotropic energy conversion is located near the southeastern flank of the North Atlantic jet (Fig. 9a), and the high-frequency transient eddy-induced positive geopotential height tendency is also located near the North Atlantic jet (Fig. 9d). Both of them are near the first center of action of the BBC pattern over the west of Britain (Figs. 9b,c). These coincidences imply that the multiscale interactions between the climatological mean flow, the low-frequency flow, and the synoptic-scale transient eddies in the exit region of North Atlantic jet stream may play a crucial role in the excitation of the BBC pattern as summarized below. In the exit region of the North Atlantic jet, the climatological flow tends to be barotropically unstable due to the large horizontal gradient of basic wind. Any random disturbance with small amplitude tends to grow readily through extracting energy barotropically from the background state. The resultant amplified disturbance can modify the transient eddy activities via change the meridional position of the North Atlantic storm track on one hand, and be further reinforced by the feedback forcing of synoptic-scale transient eddies on the other hand. Meanwhile, the energy of the low-frequency anomalies can propagate downstream along the PFJ and emerge as the BBC pattern.
The phase-locked nature of the BBC pattern was attributed to the high sensitivity of CK to the subtle configuration of the basic flow based on analyses of energetics in section 4d. In addition, it can also be attributed to the multiscale interactions between the eddies and basic flow near the exit region of the North Atlantic jet stream. On one hand, the flow near the exit region of the North Atlantic jet has the strong tendency to be barotropic unstable due to the strong zonal variations of the zonal wind (Fig. 1c). On the other hand, the Atlantic storm track can provide sufficient high-frequency disturbances for the low-frequency anomalies to redistribute, which could in turn result in more significant low-frequency flow anomalies. These two advantages make the multiscale interaction mechanism work particularly efficiently in the exit region of the North Atlantic jet where the first center of the BBC pattern is located. As a result, the multiscale interaction mechanism may act as certain kinds of natural selection to preferentially determine where to excite the BBC pattern. Hence, the multiscale interaction processes can suggest a preferred upstream forcing that acts to anchor the BBC pattern geographically.
b. Linkage to preceding precursors
Although the BBC pattern shows no significant relations to immediate external forcing, there is still possibility that some preceding factors may help to provide some plausible prediction potentials through regulating the background flow. Figure 10 shows the regressed sea level pressure (SLP) field in the preceding winter onto the BBC index. A clear dipole structure is observed over the North Atlantic, resembling the wintertime NAO to some extent. However, the correlation between the BBC index and preceding winter NAO index is low, with a correlation coefficient of 0.28 for 37 years (Fig. 11a). Although the linear correlation is insignificant at the 90% confidence level, Fig. 11a implies that the BBC pattern tends to exhibit an in-phase relationship with the winter NAO. To further confirm this possibility, we apply the Monte Carlo bootstrapping technique (Efron and Tibshirani 1994) to estimate the probability density function (PDF) of the BBC index during positive and negative phases of the winter NAO. The resampling procedure was repeated 10 000 times. The result shows that the two PDFs are well separated from each other and are also significantly different from zero at the 90% confidence level as estimated using the percentile method (Fig. 11b). This indicates that although the linear relationship between the winter NAO and BBC pattern is weak, the preceding winter NAO may preferentially facilitate the occurrence of a particular phase of the BBC pattern. Considering that the sample numbers used to estimate the PDF are relatively small, the relationship between the NAO and the BBC pattern was further checked in the longer dataset ERA-20C for the period 1920–2010. Their temporal correlation coefficient is 0.23 for the 91 years, and the bootstrapping technique also indicates that the PDFs are well separated at the 90% confidence level in different preceding NAO phases (Fig. 11c). This suggests that the NAO–BBC pattern relationship is statistically robust and is not sensitive to datasets or the sample size.
The regression of SLP in preceding winter (December–February) onto the BBC index (CI = 0.5 hPa). The light and dark shading indicate the 90% and 95% confidence levels based on a two-tailed Student’s t test, respectively.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
(a) The time series of the normalized BBC index (solid line) and the normalized NAO index of the preceding winter (blue bar) for the period 1979–2015. The correlation coefficient between the two time series is indicated on the upper right corner. (b) PDF (curve) and median (vertical solid line) of the BBC index estimates from 10 000 bootstrapped samples in the positive (red) and negative (blue) phase of the winter mean NAO index. Vertical dashed lines indicate the 10% and 90% confidence levels estimated using the percentile method. (c) As in (b), but based on the ERA-20C dataset for the period of 1920–2010.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
Ogi et al. (2004) also found that the winter NAO can regulate the interannual variability of the summertime Okhotsk high through a propagating Rossby wave train along the coast of the Arctic Sea. However, the wave train documented in their study originates from the Barents Sea (see their Fig. 4), and the significant relationship they found with springtime snow cover and sea ice cannot be obtained in this study. It is speculated that the inconsistency between their results and those reported in this study may be caused by the different studied months and objects. Ogi et al. (2004) focused on the possible influence of the preceding winter NAO on the circulation only in the following June. In any case, the significant relation between the preceding NAO and the BBC pattern shown here only indicates certain statistical associations, not a physically based cause-and-effect relation. More comprehensive investigations are needed in the future to investigate the physical mechanisms of how the preceding NAO affects the summertime BBC pattern.
6. Conclusions
In this study, a new teleconnection referred to as the British–Baikal Corridor (BBC) pattern is investigated based on observational and reanalysis datasets. Its spatial structure and associated climate anomalies are shown by a schematic diagram in Fig. 12. The BBC pattern is the dominant mode along the upper-tropospheric polar front jet (PFJ) in boreal summer. It has a zonally oriented and meridionally confined wave structure with a zonal wavenumber 5. This distinct structure is formed due to the trapped effect of waveguide arising from the strong meridional gradient of stratification, and it is different from the canonical teleconnection patterns that feature prominent arching structure and meridional group velocity. The BBC pattern consists of four equivalent-barotropic and geographically fixed centers over the Eurasian Continent. Its positive phase features anomalous anticyclones (cyclones) over the west of the British Isles and western Siberia (the Baltic Sea and Lake Baikal), resulting in local warm and wet (cool and dry) anomalies over central Siberia (northeast Europe and northeast Asia) by inducing atmospheric circulation anomalies.
Schematic diagram illustrating the spatial structure of the BBC pattern and associated climate anomalies. The red and blue contours represent the cyclonic and anticyclonic centers of the BBC pattern. Shading and hatches indicate the associated surface air temperature (positive in red and negative in blue) and precipitation (positive in green and negative in brown) anomalies, respectively. The black line represents the waveguide formed from the large meridional gradient of climatological potential vorticity. The purple line indicates the subtropical jet stream.
Citation: Journal of Climate 32, 3; 10.1175/JCLI-D-18-0343.1
The internal dynamics of the BBC pattern can be understood from two aspects. From the perspective of vorticity balance, the maintenance of the BBC pattern is primarily the balance among the Rossby wave source, which is closely related to precipitation anomalies; the zonal advection of perturbed vorticity by the climatological rotational flow, which tends to shift the pattern downstream; and the advection of the climatological vorticity by the perturbed rotational flow, which tends to shift the pattern upstream. From the perspective of energetics, the BBC pattern is a dynamical mode inherent in the summertime PFJ because it can efficiently extract baroclinic energy from the basic flow to maintain itself against dissipation. The dominance of baroclinic energy conversion over other energy conversions is also consistent with the baroclinic nature of the PFJ waveguide. Although the barotropic energy conversion cannot maintain the BBC pattern efficiently, it can help to fix the phase of the BBC pattern geographically because of its high sensitivity to the subtle asymmetry of the basic flow.
The BBC pattern is loosely related to external forcing, indicating that the interannual variability of the BBC pattern is dominated by the atmospheric internal dynamics. It was found that the multiscale interactions among the climatological-mean flow, low-frequency flow, and the high-frequency transient eddies in the exit region of the North Atlantic jet play essential roles in the excitation of the BBC pattern. In addition, the above multiscale interactions may also act as a kind of natural selection to preferentially determine the upstream forcing region and anchor the BBC pattern geographically. The Monte Carlo bootstrapping technique reveals that positive (negative) NAO in winter tends to be followed by the positive (negative) phase of the BBC pattern in the subsequent summer. It suggests that the wintertime NAO may provide some prediction potential for the BBC pattern on the interannual time scales. Nevertheless, the involved physical mechanism remains unclear and deserves investigation in the future.
7. Discussion
This study used a relatively small sample size (~40) to discuss the interannual variability of the BBC pattern. One may doubt whether the BBC pattern can still be extracted in longer datasets, so the analyses were repeated with the JRA-55, NCEP–NCAR, and ERA-20C datasets, which have longer records. This reveals that the BBC pattern still appears as EOF1, indicating the robustness of the BBC pattern as an internal mode in the seasonal mean sense. Interestingly, the BBC pattern appears as the second EOF (EOF2) if monthly-mean or low-pass-filtered daily data are used in analyses. In contrast, the EOF2 defined with the seasonal mean data appears as EOF1 defined with the monthly or daily data. The above discrepancy is because there are more cancelations between the positive and negative phases of the daily EOF1 in a season than in a month, resulting in the BBC pattern as the leading EOF in the summer mean data (figure not shown). This result indicates that it is necessary to further investigate the mechanism of the BBC pattern on daily or intraseasonal time scales, which will be done in our future studies.
Recently, several studies indicated that some recent Northern Hemisphere summers with large planetary Rossby wave activities are caused by the quasi-resonance amplification (QRA) of forced and free wavenumbers 6–8. Usually, the quasi-stationary thermal and orographically forced Rossby waves in those wavenumbers are weak (Petoukhov et al. 2013; Coumou et al. 2014). However, when the free synoptic waves with those wavenumbers are trapped along the midlatitude waveguide under certain conditions, the forced planetary waves in the atmosphere can strongly amplify through quasi-resonance, leading to large summertime anomalies. The occurrence of QRA essentially depends on the shape of the jet stream, and observational analysis found that QRA is more likely to occur during double-jet situations (Kornhuber et al. 2017). To investigate the possible role of the QRA in the amplification of the BBC pattern, a simple composite analysis was conducted by calculating the difference of background zonal wind and PV between the years with large and small amplitude of BBC pattern. The years with large (small) amplitude are defined with the criterion that the absolute value of the BBC index is larger than 1.5 (smaller than 0.5). Results show that although significant zonal wind anomalies and PV anomalies can be detected along the North Atlantic and the North Pacific jet streams, the anomalies over northern Eurasia where the BBC pattern is located are very weak (figure not shown). Therefore, although QRA may sometimes play a crucial role in the amplification of the waveguide mode trapped along the subtropical jet at approximately 40°N, there is no compelling evidence that it contributes essentially to the amplification of the BBC pattern, which is located along the PFJ at higher latitudes. Nevertheless, more comprehensive analysis is needed to investigate the relationship between the QRA and BBC pattern in the future.
Some recent studies show that general circulation models (GCMs) tend to simulate a CGT-like response in the middle latitudes under the global warming scenario (Brandefelt and Körnich 2008; Branstator and Selten 2009; Folland et al. 2009; Wang et al. 2013), and the ensembles of GCM projections also indicate the increasing possibility of QRA-favorable conditions and associated extreme weather in the future (Mann et al. 2017). Considering the unique dynamics and climate importance of the BBC pattern, it remains unclear whether or to what extent the current state-of-the-art models can faithfully simulate the structure of the BBC pattern. Comparing the models that can reasonably reproduce the BBC pattern and those fail to do so may help us to gain some insights about the model performance and find out the limitations where models should be improved. In addition, understanding the uncertainties in modulations of the BBC pattern under global warming may also help to interpret the uncertainties in simulating the future climate over the Eurasia. These issues are currently under investigation and will be reported in a forthcoming paper.
Acknowledgments
We are grateful to the three anonymous reviewers for their helpful comments that led to significant improvement of the manuscript. We also appreciate Dr. Yihua Lin of IAP, Dr. Hao Fu of Stanford University, Dr. Christian Franzke of University of Hamburg, and Drs. Jianhua Lu and Zhenning Li of Sun Yat-sen University for helpful discussions. This work was supported jointly by the National Key R&D Program of China (2016YFA0600604), the National Natural Science Foundation of China (41721004), the Science Fund of Yunnan Province (2018FY001-18), and the Fundamental Research Funds for the Central Universities.
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