1. Introduction
In the context of global warming, surface air temperatures of the Arctic are rising at a rate 2–4 times that of the global average, which is termed the phenomenon of Arctic amplification (Cohen et al. 2014; England et al. 2021; Rantanen et al. 2022; Screen and Simmonds 2010a,b; Serreze et al. 2009). The Arctic near-surface warming, tightly coupled with the accompanying Arctic sea ice loss (Dai et al. 2019; Screen and Simmonds 2010a; Stroeve and Notz 2018; Stroeve et al. 2012), has sparked a growing research interest during recent decades. Multifaceted effects of Arctic warming on the midlatitudes have been revealed, including but not limited to changes in the strength and displacement of the westerly jet, the intensification of the Siberian high, its interplay with atmospheric blockings, and, last but not least, the emergence of midlatitude continent cooling (Cohen et al. 2014; Coumou et al. 2018; Francis and Vavrus 2012, 2015; Honda et al. 2009; Inoue et al. 2012; Kim et al. 2014; Kug et al. 2015; Luo et al. 2016; Mori et al. 2014; Vihma 2014; M. Xu et al. 2021; Yao et al. 2017; Zhang et al. 2018). Although a great endeavor has been made to parse the Arctic-to-midlatitude linkage, a consensus on whether and to what extent Arctic warming is influencing the midlatitudes is still lacking (Cohen et al. 2019; Outten et al. 2022; Overland et al. 2021; Smith et al. 2019; Vavrus 2018). Some argue that the warming or sea ice loss over the Barents–Kara Seas (BKS)—the most severe within the entire Arctic and thus making BKS the hotspot of Arctic warming (Lind et al. 2018; Screen and Simmonds 2010b; Smedsrud et al. 2013)—is responsible for the Eurasian cooling, hence coining the eye-catching term “warm Arctic–cold Eurasia” (WACE) (Cohen et al. 2014; Kug et al. 2015; Mori et al. 2014, 2019; Outten and Esau 2012). But others doubt the causality therein revealed by observational analyses because the simulated Eurasian cooling is much weaker than the observation and even absent (Blackport et al. 2019; Dai and Song 2020; McCusker et al. 2016; Zappa et al. 2021). Lately, evidence is mounting that the vertical profile of Arctic warming possesses an intimate relationship with the Eurasian cooling, which helps enrich our understanding of the WACE pattern, the most representative phenomenon embodying the Arctic-to-midlatitude linkage (He et al. 2020; Kim et al. 2021; Labe et al. 2020; Ogawa et al. 2018; Xu et al. 2019; Zhang et al. 2022).
Although the Arctic warming is strongest at the surface (termed the surface-based or bottom-heavy structure) in observations and reanalysis, the significant warming also extends from the surface into the middle-to-high troposphere, especially in boreal winter (Alexeev et al. 2011; Chung et al. 2013; Cohen et al. 2019; Graversen et al. 2008; Serreze et al. 2009; Tjernström and Graversen 2009). Among recent research on the vertical distribution of Arctic warming, one essential study by He et al. (2020) classified the winters with Arctic warming into deep and shallow warming ones according to whether the BKS-averaged air temperature at 500 hPa is significantly above the normal in the presence of concurrent surface warming. Their statistical results from large ensembles of coupled climate model simulations and atmospheric models forced by prescribed realistic sea surface temperatures (SSTs) and sea ice concentrations (SICs) consistently showed that the Eurasian cooling or WACE anomalies tend to appear in the winters with deep rather than shallow BKS warming. Thus, deep Arctic warming very likely governs the Arctic-to-midlatitude linkage. Also, the fact that deep Arctic warming emerges more readily since the late 1990s has been proposed as the main cause for the interdecadal enhancement of correlations between Arctic warming and changes in the strength of the Siberian high (Xu et al. 2019), the frequency of midlatitude extreme winter weather (Cohen et al. 2018), and haze pollution in North China (Zhang et al. 2022). Ogawa et al. (2018) further elucidated that among large ensemble members forced by realistic SSTs and SICs in six atmospheric general circulation models (AGCMs), a wintertime Eurasian cooling trend similar to the observation can only be reproduced in a few simulations therein, which all happen to be subject to deep Arctic warming (their Fig. 4).
Various mechanisms have been proposed to explain how Arctic warming might drive Eurasian cooling (Cohen et al. 2014; Outten et al. 2022). Specifically, Arctic warming can contribute to Eurasian cooling by enhancing the anticyclone over Eurasia via triggering a Rossby wave train (Honda et al. 2009; Kug et al. 2015) or weakening the stratospheric polar vortex (Kim et al. 2014; Zhang et al. 2018) or by inducing more atmospheric blockings owing to the decelerated jet stream associated with the weakened poleward temperature gradient (Francis and Vavrus 2012, 2015; Mori et al. 2014). These proposed mechanisms reasonably apply to the deep Arctic warming, but there is a caveat that near-surface Arctic warming appears insufficient to generate comparable remote impacts through the same pathways (He et al. 2020; Wu 2017). To explore this question, several studies have evaluated the atmospheric circulation responses to distinct vertical structures of Arctic warming imposed in AGCMs of different complexity. An earlier study using an idealized linear stationary wave model stated that significant midlatitude circulation responses are excited only if the idealized heating penetrates up to the tropopause, alluding to a pathway for establishing the Arctic-to-midlatitude teleconnection under specific conditions (Sellevold et al. 2016). Kim et al. (2021) subsequently examined the atmospheric circulation sensitivity to various vertical levels of Arctic warming using aquaplanet slab-ocean AGCM simulations. They found that the imposed warming far away from the surface can induce stronger effects on the midlatitude jet than the near-surface warming, whereby Eurasian cooling might be more likely. The behaviors of the Siberian high (Labe et al. 2020) and Ural blockings (Chen et al. 2021), which have significant implications for Eurasian temperature prediction, also turn out to be dependent on the vertical extents of Arctic heating artificially added into the AGCM simulations. Simply put, a similar result yielded by hierarchical models is that the strength of Arctic-to-midlatitude linkage in models greatly hinges on how realistically climate models can simulate the vertical structure of the observed Arctic warming—in other words, whether the simulated warming is sufficiently deep.
Despite the significance of the vertical structure of Arctic warming, less attention has been paid to the intraseasonal variability of the Arctic warming profile. Most of the aforementioned studies concerning vertical distributions of Arctic warming have focused on either the winter mean in each year (He et al. 2020; Kim et al. 2021; Labe et al. 2020) or longer time scales (Ogawa et al. 2018; Sellevold et al. 2016; Xu et al. 2019; Zhang et al. 2022). Also, possible drivers of midtropospheric warming in the Arctic have been previously investigated on these time scales. The direct cause for the Arctic aloft warming is the poleward atmospheric energy (dominated by latent and internal energy) transport into the Arctic (Graversen et al. 2008; X. Xu et al. 2021), which has been further attributed to atmospheric internal dynamics (He et al. 2020; Ogawa et al. 2018), SSTs at low latitudes (Blackport and Kushner 2017; Park et al. 2018), or ocean–atmosphere interactions (Deser et al. 2015). This stands in striking contrast to the Arctic surface warming on the same time scale that is largely caused by the local sea ice loss (Dai et al. 2019; Kumar et al. 2010; Perlwitz et al. 2015; Screen et al. 2012). On the other hand, short time scale Arctic warming events receive increasing attention and can be easily analyzed in recent years (Graham et al. 2017; Moore 2016; Yu et al. 2021). Besides, Rossby waves and their associated energy propagation, one of the potential dynamical pathways linking the Arctic warming and midlatitude weather, function specifically on the intraseasonal time scale (Cohen et al. 2014; Gong et al. 2020), which reasonably becomes our priority of time scale to be examined.
It has been demonstrated that intraseasonal Arctic warming events are typically accompanied by a Ural blocking or an anomalous anticyclone over northern Eurasia and that there exists a strong coupling among this positive pressure anomaly, Arctic warming, Eurasian cooling, and sea ice variability (Luo et al. 2016; Messori et al. 2018; Tyrlis et al. 2020; Yao et al. 2017; Ye and Messori 2020). Nevertheless, only the Arctic surface warming was concerned in all these findings. A recent and relevant study by Cardinale and Rose (2022) attached great importance to vertical structures of the tropospheric energy flux into the Arctic. Although the surface energy budget was the focus, their results also indicated the relationship between atmospheric energy fluxes and the vertical structure of Arctic temperature anomalies (their Figs. 5 and 10). To date, whether there are distinctions of vertical extent (e.g., deep and shallow warming) among intraseasonal Arctic warming events and, if yes, how the different warming profiles generate remains unclear. Moreover, do the existing mechanisms for Arctic warming on longer time scales also apply to intraseasonal Arctic warming events? To address these questions, a detailed investigation of intraseasonal deep and shallow Arctic warming events is necessary, which also helps improve the understanding of the Arctic-to-midlatitude connection.
In this study, we identify deep and shallow Arctic warming events in winter on the intraseasonal time scale, and also contrast their spatiotemporal evolutions, potential causes, and associations with Eurasian cooling. The rest of the paper is organized as follows. The adopted datasets and methods are described in section 2. Section 3 delineates the definition of deep and shallow Arctic warming events and displays their spatiotemporal variations, respectively. Detailed thermodynamic diagnoses of how both kinds of Arctic warming events develop and differ from each other are revealed in section 4. Section 5 explores the relationship between deep Arctic warming events and preceding convection in the upstream region, which is followed by a discussion and summary in section 6.
2. Data and methodology
For this study, we use 4-times daily data (sampling at 0000, 0600, 1200, and 1800 UTC per day) on a 1° × 1° grid in extended winter months from November to March (NDJFM) during 1979–2020 from two sets of global reanalysis archives both provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), namely ERA5 (Hersbach et al. 2020) and ERA-Interim (Dee et al. 2011). We specify the winter of 1979 as the five months from November 1979 to March 1980 with the rest done in the same manner. Several commonly used atmospheric fields are accessed from ERA5, including air temperature at 2 m (T2m) and at multiple pressure levels (T), horizontal and vertical wind (u, υ, and ω), geopotential height (H), sea level pressure (SLP), vertically integrated moisture flux (including water vapor as well as cloud frozen and liquid water), sea ice concentration (SIC), and surface heat fluxes. Additionally, the hourly ERA5 total precipitation (24 times per day) is utilized. Diabatic heating variables (interpolated from the hybrid sigma pressure to pressure coordinate), including the longwave (QLW) and shortwave (QSW) radiational heating as well as the total diabatic heating (QTOTAL), are available in ERA-Interim. Note that the sum of latent and sensible heating (QLH+SH) is obtained by subtracting both QLW and QSW from QTOTAL, namely QLH+SH = QTOTAL − QLW − QSW (Clark and Feldstein 2020a). For comparison with the ERA5 precipitation, the station data of daily accumulated precipitation available during 1958–2013 at Tasiilaq (situated in southeast Greenland: 65.60°N, 37.63°W) is obtained from the Danish Meteorological Institute (Cappelen 2014).
All variables are preprocessed through the following steps before being analyzed unless otherwise stated. First, we acquire daily data by averaging the hourly data every four values with those on 29 February in all leap years skipped. The ERA5 hourly precipitation is summed up to get the daily accumulated precipitation, and the Tasiilaq daily precipitation is directly obtained from the Danish Meteorological Institute. Afterward, daily anomalies are computed as departures from the 1979–2020 mean of each corresponding calendar day. The anomalies are further detrended using the least squares method. Last, we apply a 5-day low-pass Lanczos filter to the detrended daily anomalies. Note that the primary conclusions show little disparity with and without filtering, but the filtered results feature smoother evolutions and higher readability.
We perform a Monte Carlo approach to assess the statistical significance of composite results of deep and shallow warming events, respectively. Specifically, a total of 1000 random composites with the same number of corresponding event types are generated, and the resultant 5th and 95th percentiles are used to test the confidence level of 95%. The two-tailed Student’s t test is also employed to estimate significant differences between deep and shallow events.
Since atmospheric responses are sensitive to the region where the Arctic forcing is applied (Screen 2017) and the largest winter warming appears near the BKS (Screen and Simmonds 2010b), we focus on the BKS region (70°–80°N, 30°–70°E) in this study, keeping in line with Kug et al. (2015), He et al. (2020), and many other relevant studies. Using the whole Arctic area (north than 65°N) detects similar warming events (not shown), indicating the dominance of BKS in wintertime intraseasonal Arctic temperature variability. Each domain average is weighted by area using the cosine of the corresponding latitude. Specifically, we first compute each term of Eqs. (1)–(3) at each mesh point before calculating the area average. Note that although Cardinale et al. (2021) found unphysical high-frequency noise in the energy transport via a net mass flux into the polar cap, such issues with mass conservation would not impact our results that focus on a small domain, namely the BKS region.
3. Categorization and characteristics of intraseasonal deep and shallow Arctic warming events
Figure 1a displays the daily normalized BKS-averaged T2m surpassing one standard deviation (1.0 SD, equal to 4.52°C). An intraseasonal Arctic warming event is defined when satisfying the requirements that (i) the standardized BKS T2m exceeds 1.0 SD and lasts no less than three consecutive days, and (ii) there is only one peak of BKS T2m within 21 days centering the peak date (marked by stars or triangles). The single-peak limitation prevents the expected overlapping of detected events and results are similar if a lower threshold is used (such as 13 days; not shown). In this way, 104 Arctic warming events in total are identified. Day 0 (0d or peak day) is referred to as the day with maximum BKS T2m anomaly during the event, while day −1 (−1d) is the day just prior to the peak day, and so on.
(a) Standardized daily T2m anomalies averaged over the BKS in NDJFM during 1979–2020, with values smaller than one standard deviation (1.0 SD, equal to 4.52°C) are masked. The stars (triangles) represent the peak day of deep (shallow) Arctic warming events. Time cross sections of composite BKS-averaged T anomalies (°C) in the troposphere from −10d to 10d during (b) deep and (c) shallow Arctic warming events. The black contours denote the 1.0 SD of T at different levels. Event numbers are shown in parentheses. (d) Difference of (b) minus (c). Hatched regions in (b)–(d) indicate temperature anomalies or differences exceeding the 95% confidence level.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
Next, we further classify the 104 Arctic warming events into deep versus shallow groups according to the middle tropospheric temperature. A deep (shallow) warming event is identified when the standardized BKS T at 500 hPa (T500hPa) averaged from −1d to +1d is above (below) 1.0 SD. In consequence, 66 deep (marked by stars in Fig. 1a) and 38 shallow (marked by triangles in Fig. 1a) Arctic warming events are picked out of 41 winters during 1979–2020, respectively accounting for 63% and 37% of all warming events. As exhibited in Figs. 1b and 1c, the time-evolving distributions of deep and shallow Arctic warming events stand in stark contrast to each other in terms of the vertical extension, with the significant warming (larger than 1.0 SD; black contours) developing into 300 hPa for deep events while barely reaching 700 hPa for shallow events. Their difference shown in Fig. 1d highlights the extra warming of deep events in the middle troposphere, which reaches its maximum at 500 hPa. Compared with salient temperature differences between deep and shallow events in the middle-to-upper troposphere, those in the near-surface levels are slight throughout the entire life cycle. This implies that a deep warming event should not be considered as a stronger or amplified shallow warming event, as the two kinds have comparable intensity in the lower troposphere but distinct vertical structures.
Figures 2 and 3 display three-dimensional evolutions of deep and shallow warming events in the troposphere from −4d to +4d. In addition to the great differences in BKS warming, associated H anomalies as well as Eurasian cooling also differ substantially between deep and shallow warming events. For deep warming events (Fig. 2), the BKS warming is accompanied by a dipole pattern of H anomalies, with the positive anomalies located over northern Eurasia and the negative anomalies enveloping Greenland. This dipole pattern bears a quasi-barotropic structure with a slight northward tilt from the surface up. The anomalous high pressure therein, analogous to the Ural blocking or intensified Siberian high, is conducive to freezing weather in the Eurasian lands by steering massive cold air from the Arctic to march southward (Hwang et al. 2022; Inoue et al. 2012; Luo et al. 2017, 2016; Messori et al. 2018; Woods et al. 2013; Yao et al. 2017). It does not surprise us that an evident cooling accompanied by deep Arctic warming emerges over Eurasia in the presence of a strong positive H anomaly nearby in our composite results. This sustained positive H anomaly of large intensity may correlate with the decelerated westerlies and small meridional gradient of potential vorticity at mid–high latitudes, which results from the weakened poleward temperature gradient and reduced Arctic potential vorticity related to deep Arctic warming (Chen et al. 2021; He et al. 2020; Luo et al. 2019). The interaction between Atlantic cyclones and Eurasian high-latitude blockings might also play a role in amplifying and maintaining the high pressure system, according to the latest findings by Murto et al. (2022), since deep warming events are found to be associated with activities over the North Atlantic in section 5.
Composite patterns of T (colors; °C) and H (contours; interval of 20, 25, 50, and 75 gpm from the bottom up) anomalies at the near-surface level and 850, 500, and 300 hPa at day −4, −2, 0, +2, and +4 for deep Arctic warming events. Specifically, near-surface anomalies present the anomalies of T2m and 1000-hPa H. Only T anomalies significant at the 95% confidence level are shown. The solid and dashed contours denote the positive and negative H anomalies, respectively, with zero contours omitted. The green boxes denote the BKS region (70°–80°N, 30°–70°E).
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
As in Fig. 2, but for shallow Arctic warming events.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
In contrast, the dipole pattern of anomalous H shifts southeastward in shallow Arctic warming events (Fig. 3), and the maximum H anomaly therein is weaker and less persistent. Correspondingly, the cooling anomaly over the Eurasian midlatitude continent is feeble or even absent during shallow Arctic warming events, in line with Yao et al. (2017) and Chen et al. (2018), who found that only persistent Ural blockings can result in significant cold surges in the Eurasian midlatitudes. To be precise, the anomalous cooling associated with shallow warming events is displaced southward and is also less amplified and persistent than that associated with deep events (not shown). In short, differences between deep and shallow Arctic warming events lie in not only the BKS warming profile but also in the attendant anomalies of large-scale atmospheric circulation and Eurasian cooling.
4. Thermodynamic diagnoses of deep and shallow Arctic warming events
In this section, we investigate what processes are responsible for the difference between deep and shallow Arctic warming events in developing phases. The thermodynamic energy equation, namely Eq. (1), is used to diagnose the time-varying T anomalies on every pressure level, following Clark and Feldstein (2020b).
As the anomalous T tendency displayed in Figs. 4a and 4b shows, both event types undergo a heating and a cooling period of several days before and after the peak day, respectively. Their differences depicted in Fig. 4c indicate that the additional warming around day 0 in deep events could be traced back to an extra heating maximized in the middle troposphere in advance. To determine whether the termwise-calculated T tendency correctly drives the BKS T anomalies, Figs. 4j–l present the integrated T anomalies derived from the corresponding T tendency in Figs. 4a–c following a similar method of Seo et al. (2016). Their high consistency with Figs. 1b–d in terms of pattern correlation coefficients (very close to one) verifies that the utilized variables from two different datasets (the diabatic term from ERA-Interim and the other variables from ERA5) are in harmony.
Time cross sections of composite BKS-averaged T tendency anomalies [sum of the RHS terms of Eq. (1) except the residual term; colors; °C day−1] in the troposphere from −10d to 10d for (a) deep and (b) shallow Arctic warming events, and (c) their difference. Contours (interval of 0.5°C day−1) also denote the T tendency anomalies that are calculated using the central finite difference approximation, namely the LHS of Eq. (1). (d)–(f),(g)–(i) Colored as in (a)–(c), but for the anomalous dynamic heating [sum of the first three terms in the RHS of Eq. (1); °C day−1] and anomalous diabatic heating [the fourth term in the RHS of Eq. (1); °C day−1], respectively. (j)–(l) Anomalous T (colors; °C) computed as the temporal integration initializing at −10d of the corresponding T tendency anomalies in (a)–(c). Contours (interval of 2°C) display T anomalies identical to Figs. 1b–d. The PCCs denote the pressure-weighted pattern correlation coefficients between the anomalies presented by colors and contours in the same plot. Hatched regions and thickened contours indicate anomalies or differences exceeding the 95% confidence level. The solid and dashed contours denote the positive and negative values, respectively, with zero contours omitted. The pressure levels of 850 and 300 hPa are marked by green lines.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
Next, we examine the relative contributions of dynamic (Figs. 4d–f) and diabatic heating (Figs. 4g–i). For both kinds of events, the dynamic terms bear a striking resemblance to the total heating except in the near-surface levels, suggesting a dominant role of dynamic heating in the warming aloft. Many previous studies have argued that the surface Arctic warming is mainly due to excessive moisture transported northward into the Arctic and the resultant enhanced downward longwave radiation back to the surface (Cardinale et al. 2021; Flournoy et al. 2016; Lee et al. 2011; D.-S. R. Park et al. 2015; H.-S. Park et al. 2015; Woods and Caballero 2016; Woods et al. 2013). Do the diabatic processes therein also contribute to the middle-to-upper tropospheric warming, such as via releasing latent heat? We may here give an answer of no based on our results. Specifically, Figs. 4g–i present ignorable anomalies of diabatic heating compared with the dynamic terms, thereby hardly contributing to the BKS warming above 850 hPa. Thus, the warming difference aloft between deep and shallow warming events is governed by dynamic terms, in which anomalous atmospheric circulations may play crucial roles. In addition, the strong surface-trapped negative diabatic anomalies before the peak day both in deep and shallow warming events (Figs. 4g,h) are in tandem with sea ice loss (Fig. S1 in the online supplemental material). However, downward (positive) instead of upward (negative) surface turbulent heat flux anomalies prior to the peak day of warming events (Fig. S2) suggest that the sea ice loss is the response rather than the trigger of the preceding lower-tropospheric warming. Around 10 days after the peak day of a deep warming event, upward heat flux anomalies emerge that help to prolong the BKS warming, indicating a delayed positive feedback from sea ice loss (Fig. S2a). Nevertheless, it should be pointed out that reanalysis datasets including ERA5 show poor skill in simulating surface turbulent heat fluxes over ice-covered areas (Graham et al. 2019). Also be aware that the findings here about the roles of diabatic processes and sea ice loss in BKS warming can only apply to the intraseasonal time scale, and not necessarily to interannual variations and long-term trends.
Figure 5a exhibits the T tendency along with T anomalies that have been vertically averaged from 850 to 300 hPa where the largest heating difference lies (Fig. 4) for two kinds of warming events. Their heating rates are similar before −5d but differ substantially afterward. The heating rate reaches 1°–2°C day−1 for deep events while it is below 1°C day−1 for shallow events, resulting in the pronounced difference in T anomalies around 0d.
(a) Temporal evolution of BKS-averaged layer-mean T anomalies (black; left ordinate; °C) within 850–300 hPa and its tendency (green; right ordinate; °C day−1) from −10d to +10d. Solid and dashed curves stand for deep and shallow Arctic warming events, respectively. Values exceeding the 95% confidence level are marked by dots, while the line segments between two curves signify their difference significant at the 95% confidence level. (b) Contributions of various terms in Eq. (1) averaged from −5d to −1d to the BKS-averaged layer-mean T tendency anomalies shown in (a) for deep and shallow events, and their difference (shown from top to bottom). The terms of LHS, RHS, ZA, MA, and
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
Stemming from the analyses above that have stressed the profound effects of dynamic terms, Fig. 5b dives into each term of dynamic heating with ZA and MA further decomposed using Eqs. (2) and (3). Slight differences between LHS and RHS indicate that the residual term of Eq. (1) is negligible, and the temperature budget is nearly balanced. Averaged from −5d to −1d when the heating difference is significant (gray shading in Fig. 5a), the term
To explain the difference in term ZA2 between deep and shallow events, Fig. 6 presents the horizontal distributions of T anomalies and climatological wind. At −5d for deep warming events, there is an emerging warming to the east of Greenland, generating measurable negative
Composite patterns of layer-mean T anomalies (colors, °C) within 850–300 hPa and climatology of 500-hPa horizontal wind (arrows; m s−1) from −5d to 0d for (left) deep and (right) shallow Arctic warming events. Only T anomalies significant at the 95% confidence level are shown. The black lines highlight the contours of T anomalies starting from 2°C with interval of 2°C (1°C) for deep (shallow) events. The green boxes denote the BKS region (70°–80°N, 30°–70°E).
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
We are aware that the analysis focusing on the 850–300-hPa mean cannot reveal the cause of shallow warming events; instead, it clearly answers how the intraseasonal middle-to-upper tropospheric warming forms and why the two types of warming events have such distinct vertical structures. Analogous to Fig. 5b, Fig. S3 further showcases the results focusing on the average below 850 hPa. Consistent with Fig. 4, at near-surface levels there is a strong cooling by the diabatic term both in deep and shallow warming events and no significant discrepancy of total heating (RHS) between them is seen. The terms of ZA and MA are the drivers of lower-tropospheric warming, with the contribution of ZA (MA) being larger in deep (shallow) warming events, which is similar to the situation of 850–300-hPa mean. Both ZA and MA are dominated by their first terms shown in Eqs. (2) and (3), namely ZA1 and MA1, indicating the significance of wind anomalies. The disappearance of the contribution by ZA2 to the lower-tropospheric warming suggests a slight difference of cause between the tropospheric warming above and below 850 hPa in deep warming events. Meanwhile, this highlights the importance of the preceding aloft warming in the west of BKS in generating the middle-to-upper tropospheric BKS warming through the term of ZA2.
5. Deep Arctic warming events probably linked to upstream activities
It is necessary to investigate the extra upstream warming prior to the peak day of deep warming events. Figure 7 displays significant QLH+SH anomalies at −5d in deep events, and they are concurrent with the distribution of warming around 30°W–0°. In the following days, while these positive QLH+SH anomalies anchor and intensify near Greenland, positive T anomalies exhibit a gradual increase as well as an evident shift toward east into the BKS (also seen in the left panel of Fig. 6). Apparently, the QLH+SH anomalies over eastern Greenland in advance are distinctly stronger than those over the BKS around day 0, implying that the anomalous diabatic heating would be a possible factor fueling the upstream warming even though it hardly contributes to the BKS warming. Meanwhile, anomalous MA also plays an important role in producing the upstream warming (Fig. S4). Given that MA anomalies take effect both in deep and shallow warming events (Figs. S4 and S5) and greater difference consists in QLH+SH anomalies (comparing Fig. 7 and Fig. S6), we assume that QLH+SH may better explain the discrepancy of deep and shallow warming per se.
Composite patterns of 70°–80°N-averaged QLH+SH (colors; °C day−1) and T (contours; interval of 1°C starting at 2°C) anomalies from −5d to 0d for deep Arctic warming events. Only QLH+SH anomalies significant at the 95% confidence level are shown. The topography is masked in black. The range of BKS region is marked by green lines.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
As seen in Fig. 8, the spatial distributions of positive QLH+SH anomalies match well with the increased precipitation and meridional moisture transport from −6d to −1d, suggesting that the anomalous QLH+SH could be potentially caused by the in situ convection via delivering abundant latent heat into the free troposphere. Note that here we cannot isolate the contribution from latent and sensible heat as three-dimensional latent and sensible heat are not provided respectively in reanalysis. The latent heat is emphasized because it is generally more related with excessive convective activities and also more effective in heating the middle-to-upper troposphere. With a careful scanning of the anomalous QLH+SH magnitude, there is an enormous but regional maximum anchored at southeast Greenland, aptly where the positive QLH+SH anomalies debut at −6d. Subsequently, the significant QLH+SH and associated precipitation anomalies rapidly spread to cover the entire upstream area, finally resulting in what we see in Fig. 7.
Composite patterns of 500-hPa QLH+SH (colors; °C day−1), vertically integrated meridional moisture flux (contours; interval of 20 kg m−1 s−1 starting at 10 kg m−1 s−1), and positive total precipitation (green dots) anomalies from −6d to −1d for deep Arctic warming events. The hatched blue areas denote the area with SLP lower than 996 hPa, representing coverages of the deepened Icelandic low. Only QLH+SH and precipitation anomalies significant at the 95% confidence level are shown. The green boxes denote the BKS region (70°–80°N, 30°–70°E).
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
In contrast, significant precipitation and diabatic heating anomalies are barely found near Greenland prior to the peak day of shallow events (Figs. S6 and S7). This may in part result from a preceding cooling over the North Atlantic mid–high latitudes (Fig. S8) since it is unfavorable for local synoptic activities to form and subsequently intrude toward the pole. Instead, the meridional temperature advection anomalies south of the BKS show that warm air from inland Eurasia directly penetrates into the BKS, contributing to the shallow warming there as depicted by Fig. 5b and Fig. S3. The air from the continent in shallow events is drier and with lower temperature relative to the oceanic air from the North Atlantic during deep events; it could not cause precipitation (or convection) and hence middle-to-upper heating as intense as that in deep events shown in Figs. 7 and 8.
Enlightened by recent research of Berdahl et al. (2018) that has first quantitatively linked the southeast Greenland precipitation to Icelandic low characteristics, we further investigate the potential effects of the Icelandic low in two different warming events. The Icelandic low is a semipermanent center of low pressure in boreal winter with its minimum located between southern Greenland and Iceland (Fig. S9), effectively regulating the atmospheric variability over the North Atlantic. Different characteristics of the Icelandic low are manifested during the developing phases of deep and shallow warming events. For deep warming events (Fig. 8), the Icelandic low undergoes a reinforcement but only confined within southern Greenland, in line with the 1000-hPa negative H anomalies that envelops Greenland in Fig. 2. This in situ deepened Icelandic low induces substantial southerly winds at its eastern flank, thereby channeling ample moisture as well as warm air mass northward and forming favorable conditions for precipitation. For shallow warming events (Fig. S7), the Icelandic low not only strengthens over southern Greenland, but also noticeably extends eastward into the Norwegian Sea, which parallels the eastward displacement of negative anomalies of 1000-hPa H in Fig. 3. Likewise, significant southerly anomalies related to the eastern flank of Icelandic low displace farther east—situated over the Eurasian lands—directly heating the BKS via transporting warm but relatively dry air from the lower-latitude lands. This is consistent with the results of Berdahl et al. (2018) in their Figs. 8 and 9, although their focus is on the interannual time scale.
Besides abundant moisture gathering over southeast Greenland in deep warming events, strong uplifting effects are still demanded for the extreme and regional precipitation to take place there (Fig. 8). In reality, over southeast Greenland there stand two summits precisely of the first and second highest peaks: the mountain Gunnbjørn Fjeld (elevation of 3694 m, https://en.wikipedia.org/wiki/Gunnbjørn_Fjeld) and Mont Forel (elevation of 3383 m, https://en.wikipedia.org/wiki/Mont_Forel). It has been stated that the steep near-coastal mountains in southeast Greenland can efficiently generate orographic augmentation of precipitation, making the annual-mean and particularly winter-mean precipitation in southeast Greenland the most adequate among Greenland (Berdahl et al. 2018; Hanna et al. 2006). Figure 9 outlines the precipitation in the windward slope of southeast Greenland topography. At −6d, south of the high Greenland terrain witnesses noticeable southerly wind anomalies heading inshore, accompanied by the emerging anomalous precipitation and diabatic heating with mild but significant strength. Provided continuous moisture transport from the ocean, the released diabatic heating anomalies therewith mature at −4d and −3d, with the core of large magnitude vertically protruding into almost 300 hPa (shown as Q1 illustrated by blue contours; Q1 is the calculated total diabatic heating and provides supporting details to QLH+SH). Such cases of intense coastal precipitation accompanied by a simultaneous burst of inshore wind anomalies are found to occasionally happen in southeast Greenland, and they also feature sudden warming conditions similar to Fig. 7 (Cappelen 2014; Sodemann et al. 2008).
Composite patterns of 40°–20°W-averaged QLH+SH (colors; °C day−1), Q1 [blue contours of 1°C day−1; namely, diabatic heating calculated using the method of Yanai et al. (1973) as the reference of QLH+SH], positive total precipitation (green dots), and υ along with ω (arrows; ω is multiplied by 1000) anomalies from −6d to −1d for deep Arctic warming events. Only QLH+SH, precipitation, and wind anomalies significant at the 95% confidence level are shown. The topography is masked in black.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
As synthesized in Fig. 10a, the deep BKS warming as well as the accompanying Eurasian cooling (T2m averaged over 45°–65°N, 60°–120°E), namely the WACE pattern displayed in Fig. 2, lags behind the southeast Greenland precipitation (total precipitation averaged over 65°–70°N, 40°–20°W) by around four days. The observational Tasiilaq precipitation supports the result above based on the ERA5 reanalysis. The peak day of Eurasian cooling will lag the BKS warming peak by one or two days if it is defined using the region displaced five degrees south (not shown). The lead–lag correlation between the Southeast Greenland precipitation and the BKS middle-to-upper tropospheric temperature shown as the black curve in Fig. 10b peaks when the southeast Greenland precipitation predates the BKS aloft warming by three or four days (r > 0.22 with p < 0.05), implicating the robustness of their linkage.
(a) Temporal evolutions of southeast Greenland precipitation (green; left ordinate; mm day−1), BKS T850–300hPa (red; first right ordinate; °C), and Eurasia T2m (blue; second right ordinate; °C) anomalies from −12d to +12d for deep Arctic warming events. The solid (dashed) green curve stands for daily accumulated precipitation in southeast Greenland from ERA5 averaged over 65°–70°N, 40°–20°W (from automatic station observations at Tasiilaq in 65.60°N, 37.63°W). (b) The green and red curves are as in (a), but for southeast Greenland precipitation events as well as the cross correlation (black; second right ordinate) between the southeast Greenland precipitation and the BKS T850–300hPa within all winter days during 1979–2020. In both (a) and (b) values exceeding the 95% confidence level are marked by dots.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
For the cross validation, we further identify 112 events during which intense precipitation anomalies occurred over southeast Greenland using a similar method as introduced in section 3. As presented in Fig. 10b, the middle-to-high tropospheric T anomalies over the BKS are substantially warm several days after the precipitation peak, in parallel with the results with respect to deep warming events in Fig. 10a. Based on the examinations of each precipitation event, the ensuing deep BKS warming (over 4°C above the normal) takes place in 64 out of 112 events (accounting for around 60%).
The composite of these 64 selected events could help with portraying the entire evolution of how the southeast Greenland convection activities in the upstream domain stimulate a deep Arctic warming event. Thereupon, Fig. S10 shows that the deepened Icelandic low is confined in the west of Iceland as happens during deep warming events (Fig. 8), which is conducive to abundant northward moisture transport (and warm temperature advection) into Greenland according to the analyses above, thereby leading to the strong above-normal precipitation with the maximum fixed at southeast Greenland because of the terrain effects. During the following days, the positive precipitation anomalies spread farther northeast and concur with appreciable latent heat released therefrom, fueling an emerging tropospheric warming right next to Greenland (Fig. 11). Once the upstream warming forms, it would gradually move eastward into the BKS due to the climatological westerlies, whereby a deep warming event is witnessed at around +3d. Although the situations are similar to those in Fig. 7, some differences exist in that the most severe warming over the BKS is placed at the middle tropospheric level instead of the surface. This again indicates that causes of the simultaneous warming in the middle-to-upper and lower troposphere during deep warming events are not exactly the same (comparing Fig. 5b and Fig. S3). Also, the upstream Greenland-related convection activities along with the resultant diabatic heating, which are absent in shallow Arctic warming events, are of great value to the occurrence of aloft warming in deep events.
As in Fig. 7, but from −1d to +4d for southeast Greenland precipitation events.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
It should be noted that no significant Eurasian cooling is found (not shown) in the precipitation event composite despite the occurrence of deep BKS warming, implying that the activity in the upstream region is a booster just for the BKS warming aloft. However, as long as the Arctic warming is sufficiently intense and deep, it is possibly capable of adjusting the atmospheric circulation to induce the Eurasian coldness, such as stimulating a southward-propagating Rossby wave or modulating the blockings via changing the upper-level westerlies (He et al. 2020; Honda et al. 2009; Yao et al. 2017). In turn, the modulated atmospheric circulation can further maintain and amplify the deep BKS warming as well.
Briefly, the present section reveals a credible correlation between the aloft BKS warming and its upstream precipitation, wherein the peak of the latter predates the former by four days or so. Modulated by the in situ deepened Icelandic low located in southern Greenland, considerable warm and moist air flows readily reach the southeast Greenland coast in which there are strong topographic uplifts, simultaneously giving rise to the initial upstream warming and outbreak of heavy precipitation. With a vast amount of released diabatic heat, the sudden increase of T maximized in the midtroposphere is seen near Greenland, which is followed by the deep BKS warming through the zonal temperature advection effect. It has been demonstrated that the upstream region where the warming initially occurs is a hotspot for moist intrusion events (Cardinale and Rose 2022; Woods et al. 2013). During moist intrusion events, poleward atmospheric energy fluxes not only directly heat the Arctic troposphere via channeling warm oceanic air northward, but also strengthen the greenhouse effect due to the increase in moisture and further warm the Arctic surface. Besides the dynamic heating effect that has been proposed by previous studies, this research highlights that the intense diabatic heating anomalies associated with precipitation also play an essential role in the middle-to-upper tropospheric warming over the upstream region.
6. Discussion and summary
a. Discussion
As referred to in the introduction, promoting a comprehensive understanding of Arctic-to-midlatitude linkage is our primitive motivation to classify Arctic warming events into deep and shallow groups. Here, we probe into the winter-mean WACE pattern, which has been more frequently discussed (He et al. 2020), through the lens of intraseasonal deep and shallow Arctic warming events. To reflect the variation of interannual WACE anomaly, the winter-mean WACE index is defined as the difference of domain-averaged T2m between the BKS and Eurasia. Likewise, the WACE time series is detrended. Based on the 0.5 SDs of the detrended WACE sequence, 13 winters of positive WACE phases (WACE+ years: 1979, 1983, 1984, 1987, 1993, 2000, 2004, 2005, 2009, 2011, 2012, 2015, and 2016) are identified, with a composite value of 2.65°C (Fig. 12). To investigate the linkage of winter WACE pattern to intraseasonal Arctic warming events, the approach of Luo et al. (2022) is employed. Specifically, discrepancies in the winter average of WACE index between that calculated with and without the days when Arctic warming events are happening are roughly regarded as the contribution of these intraseasonal warming events. Given that the e-folding time of a warming event is approximately 5 days, a total of 11 days from 5 days before to 5 days after the peak date is considered as the duration of a warming episode.
Composite value of the winter-mean WACE index of years in positive phase (i.e., WACE+ years), as well as its counterparts with ±5 (also ±3 and ±7) days centering the peak date of deep and shallow Arctic warming events discarded when calculating the seasonal average, respectively. The right ordinate shows the winter WACE index reduction in percentage against the original value after skipping the days in deep and shallow warming events.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
By masking these 11 days related to deep Arctic warming events when computing the seasonal mean, the WACE index average of all WACE+ years sharply reduces to 1.43°C, namely decreasing by nearly 50%. The same goes for the situation associated with shallow warming events but decreasing by merely less than 20%. We further test the sensitivity of the duration length to be removed by shortening or adding 4 days centering the peak, which yields generally dramatic reduction percentages ranging from 35% to 60% with respect to deep events. Yet, there is just a slight alteration (15%–20%) for shallow events. In other words, the intraseasonal deep Arctic warming events within a winter can to a large extent determine whether this winter belongs to a WACE+ year or not, highlighting an upscaling effect of intraseasonal deep warming events. Our findings together with those by Luo et al. (2022), who found that the winter-mean WACE pattern would become very weak in the absence of Ural blocking events, indicate that there might be a close relationship between deep Arctic warming and Ural blocking. Considering the linkage of deep Arctic warming to the upstream activities proposed in section 5, it is likely that the convective conditions near Greenland can modulate the winter-mean WACE pattern, and this important issue requires future investigations.
Although we build the lead–lag relationship between the aloft warming of BKS and the southeast Greenland precipitation by using statistical methods and reanalysis data, whether and to what extent the physical processes proposed above function in reality remains a subject for continuing research.
Furthermore, apart from the evident decreasing trend of intraseasonal temperature variability at the high latitudes that has been previously pointed out (Blackport et al. 2021; Dai and Deng 2021; Screen 2014), there also seems to be a decadal variation in the number of Arctic warming days or events in Fig. 1a. That is, the absence of warming is witnessed circa 2000, particularly for the late winter months from January to March. It is worth investigating if there is any parallel decadal change in one of the Arctic warming-related systems (e.g., the Icelandic low or Siberian high) in concordance with that of temperature.
b. Summary
In the current study, the intraseasonal Arctic warming events are divided into two types (deep versus shallow) based on their vertical extension. Respectively, the characteristics as well as the diagnostic of potential causes for deep and shallow Arctic warming episodes are elucidated. Figure 13 clearly summarizes all the key physical processes revealed in this study.
Schematic diagrams of the involved physical processes for (a) deep and (b) shallow Arctic warming events. The red ellipse superimposed by a taller (shorter) cap represents the deep (shallow) Arctic warming, and the blue ellipse filled with dark (light) color stands for the strong (weak) Eurasian cooling. The green hatched region in (a) signifies the above-the-normal precipitation. The deepened Icelandic low characterized by the 996-hPa isoline is marked by sky blue shading over the North Atlantic. The gray contours along with the gray arrows denote the anomalous atmospheric circulations four days before the Arctic warming peak. Also, the red hollow arrow indicates the direction toward which the warming develops.
Citation: Journal of Climate 36, 19; 10.1175/JCLI-D-22-0879.1
Overall, despite sharing something in common, the intraseasonal deep and shallow Arctic warming events conspicuously differ from each other in terms of their spatial evolutions along with causes, attendant atmospheric circulation anomalies, and potential influences. For deep Arctic warming events (63% out of all warming events), the strong Eurasian cooling and an intense abnormal anticyclone over northern Eurasia emerge concurrently, bringing about the so-called WACE anomaly of short time variation, which greatly contributes to the winter-mean WACE pattern. Under the situation of deep warming, the Icelandic low is deepened in situ where the minimum of climatological Icelandic low lies prior to the peak day, setting up moist southerly winds toward the southeast Greenland mountains, whereby heavy precipitation and positive temperature anomalies therefrom by releasing latent heat take place in the upstream region of the BKS. This upstream precipitation is deemed as an important precursor of deep BKS warming because the BKS warming at middle-to-upper levels reaches its peak around four days after the emerging southeast Greenland precipitation owing to the advection effect of climatological westerlies. Importantly, the deep Arctic warming events feature convection activities along with positive temperature anomalies near Greenland several days earlier and the subsequent eastward displacement of warming into the BKS through the interplay between the zonal gradient of anomalous temperature and mean-state westerlies. On the contrary, for shallow Arctic warming events (37% out of all warming events), the positive anomaly of pressure over northern Eurasia is relatively weak and lasts only briefly, hence leading to insignificant or even absent Eurasian cooling. In the situation of shallow warming, there prevail southerly wind anomalies over the Eurasian land, consistent with the eastward stretch of the reinforced Icelandic low. With the influence of anomalous southerly winds, the warming originates from the Eurasian land, and the shallow Arctic warming episodes eventually come into being through the meridional temperature advections. To recap, southerly flow blowing toward Greenland is the key to BKS warming with heightened vertical extent because it brings not only warm air but also abundant moisture, which cannot be paralleled by southerly wind from the continent.
Built on the previous research of He et al. (2020), this study concentrates on the discrepancies between intraseasonal deep and shallow Arctic warming events and why these discrepancies emerge. Besides presenting the detailed spatiotemporal evolutions of deep and shallow warming events, our study further investigates the relationship between the Icelandic low and two types of Arctic warming events. This might be associated with the contribution of the North Atlantic Oscillation and the Greenland blockings, which is the question raised by He et al. (2020) in their discussion. For deep warming events, the eastward displacement of warming and the association with upstream convection activities are the new findings in our study. Stemming from our results, we incline to the view that sea ice loss might not be the cause of Arctic warming on the intraseasonal time scale, even in shallow warming events.
Acknowledgments.
The authors appreciate the constructive suggestions from three anonymous reviewers, which greatly helped to improve the manuscript. The present research is supported by the National Key Research and Development Program of China (2022YFF0801701). X. Chen is supported by the China Postdoctoral Science Foundation (BX20200087) and National Natural Science Foundation of China (42105017). Y. Guo has received research support by National Natural Science Foundation of China (41905072).
Data availability statement.
The primary datasets used in this study, namely ERA5 and ERA-Interim, were offered by the European Center for Medium-Range Weather Forecasts (ECMWF), which are all openly accessible at locations cited in the reference section. To be specific, we downloaded these datasets from the following public domain resources: https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5 and https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-interim, respectively. Additionally, the daily precipitation observations at the Tasiilaq station in southeast Greenland are available at http://www.dmi.dk/fileadmin/user_upload/Rapporter/TR/2014/tr14-04.zip. Codes used in the present study are available from the corresponding author on request.
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