15 FEBRUARY 2019 W U A N D F R A N C I S 1137

Summer Cold Anomaly Dynamically Linked to East Asian Heat Waves

BINGYI WU Department of Atmospheric and Oceanic Sciences, and Institute of Atmospheric Sciences, Fudan University, Shanghai, China

JENNIFER A. FRANCIS Woods Hole Research Center, Falmouth, Massachusetts

(Manuscript received 12 June 2018, in final form 3 December 2018)

ABSTRACT

During recent years, the rapidly warming Arctic and its impact on winter weather and vari- ability in the mid- and low latitudes have been the focus of many research efforts. In contrast, anomalous cool Arctic summers and their impacts on the large-scale circulation have received little attention. In this study, we use atmospheric reanalysis data to reveal a dominant pattern of summer 1000–500-hPa thick- ness variability north of 308N and its association with East Asian heat waves. It is found that the second thickness pattern exhibits strong interannual variability but does not exhibit any trend. Spatially, the positive phase of the second thickness pattern corresponds with significant Arctic cold anomalies in the mid- and low troposphere, which are surrounded by warm anomalies outside the Arctic. This pattern is the thermodynamic expression of the leading pattern of upper-tropospheric westerly variability and significantly correlated with the frequency of East Asian heat waves. The Arctic has experienced frequent summer cold anomalies since 2005, accompanied by strengthened tropospheric westerly winds over most of the Arctic and weakened westerlies over the mid- and low latitudes of Asia. The former significantly enhances baroclinicity over the Arctic, which dynamically contributes to increased frequency of anom- alous low surface pressure during summer along with decreased frequency over high latitudes of and . The latter is exhibited by sustained high pressure anomalies in the mid- and low troposphere that dynamically facilitate the occurrence of East Asian heat waves. A systematic northward shift of Asian zonal winds dynamically links Arctic cold anomalies with East Asian heat waves and produces a seesaw structure in zonal wind anomalies over the Arctic and the Tibetan Plateau (the third pole). Evidence suggests that enhanced Arctic westerlies may provide a precursor to improve predictions of the East Asian winter , though the mechanism for this lag association is unclear.

1. Introduction circulation affect summer vari- ability over Eurasia (Wu et al. 2009, 2013; Screen 2013). Over the past two decades, Arctic warming and Arctic Arctic sea ice loss would reduce (enhance) summer pre- sea ice loss are among the most remarkable signals cipitation over the mid- and high latitudes of East Asia of change in the climate system and have received a (northern Europe) (Wu et al. 2013; Screen 2013). How- great deal of attention, particularly in summer. The ever, what dominant features of summer Arctic tempera- Arctic dipole anomaly, Arctic anticyclonic surface wind ture variability in the mid- and low troposphere that closely anomalies, enhanced downwelling longwave radiation, relate to atmospheric variability in the mid- and low lati- and increased Atlantic and Pacific water inflow are be- tudes of East Asia remain unclear. lieved to contribute to Arctic sea ice loss (Shimada et al. Summer high temperature and heat waves have fre- 2006; Wang et al. 2009; Ogi et al. 2010; Polyakov et al. quently occurred worldwide since the beginning of the 2010; Overland et al. 2012; Wu et al. 2012; Ding 2000s, and they directly caused a high fatality and et al. 2017). Observations and model simulations dem- produced widespread economic impacts (Meehl and onstrate that anomalies in Arctic sea ice and atmospheric Tebaldi 2004; Barriopedro et al. 2011; Bador et al. 2017). Compared with 1991–2000, casualties related with high Corresponding author: Bingyi Wu, [email protected] temperature and heat waves increased by more than

DOI: 10.1175/JCLI-D-18-0370.1 Ó 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). 1138 JOURNAL OF CLIMATE VOLUME 32

FIG. 1. The first two patterns of summer (JJA) 1000–500-hPa thickness variability north of 308N. (a) Normalized PC time series (red: PC1; blue: PC2), the red dashed line represents a linear trend in PC1, and the blue dashed line indicates the mean of PC2 averaged over 2007–12. (b) Summer 1000–500-hPa thickness anomalies, derived from a linear regression on the normalized detrended PC1, the white and black contours represent thickness anomalies at 95% and 99% confidence levels, respectively. (c) As in (b), but for the regression on the normalized PC2. (d)–(f) Summer 1000–500-hPa thickness anomalies (relative to the mean averaged over 1979–2016) in (d) 2006, (e) 2013, and (f) 2016. The first two patterns, respectively, account for 29% and 10% of the variance.

2000% in 2001–10 (WMO 2013). East Asia has experi- (Sun et al. 2014; Min et al. 2014; Coumou et al. 2014, enced frequent heat waves since the 1990s (Ding et al. 2015; Mann et al. 2017). Additionally, sea surface tem- 2010). The well-documented example is the East Asian perature (SST) anomalies, Arctic sea ice loss/snow cover heat waves of 2013 (Min et al. 2014; Imada et al. 2014; melting, and precipitation anomalies in India and the Zhou et al. 2014). South Korea had its hottest sum- South China Sea also contribute to East Asian summer mer nights and second hottest summer days since 1954 high temperature and heat waves (Hu et al. 2011; Sun (Min et al. 2014), and China suffered the strongest heat 2014; Min et al. 2014; Imada et al. 2014; Tang et al. 2014; wave since 1951 (Zhou et al. 2014). Anthropogenic Liu et al. 2015). Sun (2014) proposed that SST over the global warming generally has been shown to increase mid–North Atlantic in July 2013 was the warmest in the the likelihood of summer heat waves over East Asia past 160 years, which connects to weakening of the East 15 FEBRUARY 2019 W U A N D F R A N C I S 1139

FIG.1.(Continued)

Asian upper-level westerly and strengthening of the (JJA) atmospheric thickness (1000–500 hPa) variabil- northwest Pacific subtropical high (NWPSH) through ity north of 308N and demonstrate the association be- a wave train. This contributes to sur- tween summer Arctic cold anomalies and East Asian face air temperature variability and heat waves over the heat waves. Jianghuai–Jiangnan region of China. More direct causes can be attributed to sustained high pressure systems, 2. Data and methods particularly the NWPSH (Wang et al. 2013; Sun 2014; Imada et al. 2014; Wang et al. 2017; Freychet et al. 2017; Atmospheric data used in this study include monthly Gao et al. 2018). It is not clear whether simultaneous mean sea level pressure (SLP), winds, and geopotential Arctic atmospheric circulation anomalies during sum- heights from January 1979 to December 2016, and daily mer are linked to summer heat waves in East Asia, and surface air temperatures (SATs), SLP, air temperatures, this is the question explored in this study. We use Na- and winds at 17 pressure levels from 1 January 1979 tional Centers for Environmental Prediction–National to 31 December 2016. Data were obtained from Center for Atmospheric Research (NCEP–NCAR) re- the NCEP–NCAR Reanalysis-I (http://iridl.ldeo.columbia. analysis data to identify dominant patterns of summer edu/SOURCES/.NOAA/.NCEP-NCAR/.CDAS-1), with a 1140 JOURNAL OF CLIMATE VOLUME 32

FIG. 2. Summer mean 500-hPa geopotential height anomalies, derived from a linear regression on the normalized PC2. White and black contours represent anomalies at 95% and 99% confidence levels, respectively. horizontal resolution of 2.5832.58 and 17 pressure levels (1000–10 hPa) in the vertical direction. Daily SATs are used to calculate the frequency of summer (June–August) FIG. 3. (a) Regression map of the frequency of summer heat extreme heat wave events, identified when daily SATs are wave events, regressed on the normalized PC2 of atmospheric above 1 standard deviation for a given date and location thickness variability. White and black contours denote 95% and 99% confidence levels, respectively. (b) Regionally averaged heat (note similar results were obtained using a 1.5-standard- wave frequencies (normalized time series) over the domain bounded deviation threshold). Similarly, daily SLP data are used to by the green box in (a). The dashed line represents a linear trend at assess the frequency of summer anomalous low pressure 99% confidence level in (b). when daily SLP is below 21.5 standard deviations for a given date and location. air temperature in the mid- and lower troposphere. The This study uses NWPSH indices, which include inten- empirical orthogonal function (EOF) analysis method sity, ridge location, and western ridge point, obtained from is applied to extract the first two dominant patterns of National Climate Center (China; http://cmdp.ncc-cma.net/ summer mean 1000–500-hPa atmospheric thickness vari- Monitoring/cn_index_130.php). The NWPSH intensity ability north of 308N for the period 1979–2016. The first index is defined as the sum of the grid area with a geo- two patterns account for 29% and 10% of the variance. $ potential height 5880 gpm multiplied by the difference Similarly, EOF analysis is also used to analyze the leading $ between the geopotential height ( 5880 gpm) minus pattern of summer 300 hPa zonal wind variability north of 8 8 8 8 5870 gpm within 10 –60 N and 110 –180 E. The NWPSH 208N, which accounts for 14% of the variance. ridge location is defined as the average of the lati- The maximum Eady growth rate (EGR) relates 5 tudes at each longitude where zonal wind u 0.0 and baroclinic instability to the vertical wind shear (Vallis › › . : 8 8 8 8 u/ y 0 0 at 500 hPa within 10 –60 N and 110 –150 E. 2006; Simmonds and Lim 2009), characterizing the The NWPSH western ridge point is defined as the conduciveness of the environment to synoptic de- westernmost location of the isoline with 5880 gpm velopment (Crawford and Serreze 2016). EGR s is 8 8 8 8 E within 10 –60 Nand90E–180 . This study also uses the given by monthly mean (AO) index for the period from 1979 to 2016 (http://www.cpc.ncep.noaa. f ›U s 5 0:3098 , gov/products/precip/CWlink/daily_ao_index/monthly. E N ›z ao.index.b50.current.ascii). We use summer mean 1000–500-hPa atmospheric where f is the Coriolis parameter, U is the vertical profile thickness to approximately represent a vertically averaged of the daily zonal wind, z is the vertical coordinate, and 15 FEBRUARY 2019 W U A N D F R A N C I S 1141

FIG.4.(Continued)

FIG. 4. Weakened tropospheric westerly steering flow links East calculated in terms of the daily meridional temperature Asian heat waves to Arctic cold anomalies. (a) Spatial distribution gradient using the thermal wind equation. of summer 300-hPa zonal wind anomalies, derived from a linear regression on the normalized PC2. White and black contours rep- resent anomalies at 95% and 99% confidence levels, respectively; 3. Results the green line represents 08–1808Eat308N. (b) Normalized PC2 (blue line) and PC1 of summer 300-hPa zonal wind variability a. Atmospheric thickness variability and Arctic north of 208N (red line; the leading wind pattern accounts for 14% cold anomaly of the variance; r 5 0.81). (c) As in (b), but for normalized, area- weighted, and regionally averaged 300-hPa zonal winds north of SATs are generally used to characterize Arctic warm- 708N (red line). Correlation between the two time series is 0.88. ing and Arctic amplification. Because SATs are strongly (d) As in (a), but for zonal wind anomalies along the longitude– influenced by sea ice concentrations and SST, however, pressure cross section at 308N [green line in (a)]. The gray area differences in SATs between the Arctic and mid- 8 indicates topography along 30 N. (e) As in (d), but for geopotential latitudes may exaggerate the thermal contrast of the height anomalies. column in the mid- and lower troposphere (Sellevold et al. 2016; Wu 2017). This study uses the summer 1000– N is the Brunt–Väisälä frequency [N2 5 (g/u)(›u/›z), 500-hPa thickness to represent the mean temperature where g is acceleration due to gravity, and u is potential in the mid- and low troposphere (Overland and Wang temperature]. For EGR at 600 hPa, the vertical profiles 2010; Francis and Vavrus 2015), and its first two domi- of u are calculated as differences between their daily nant patterns are shown in Figs. 1a–1c. The leading pat- values at 500 and 700 hPa. The vertical shear of U is tern displays strong interannual variability superposed on 1142 JOURNAL OF CLIMATE VOLUME 32

FIG. 5. A systematic shift northward of zonal winds in the FIG. 6. Air temperature anomalies along the latitude–pressure troposphere and stratosphere. Zonal wind anomalies along the cross section at 1108E, derived from a linear regression on the latitude–pressure cross section at 1108E, derived from a linear re- normalized PC2. White and black contours represent anomalies at gression on the normalized PC2. White and black contours repre- 95% and 99% confidence levels, respectively. sent anomalies at 95% and 99% confidence levels, respectively. Green contours denote zonal winds averaged over 1979–2016, and 8 purple contours are zonal winds averaged over Arctic cold sum- cover much of the domain north of 30 N, particularly mers, with the normalized PC2 $ 1s (i.e., 1989, 1994, 1996, 2006, over the Arctic, Eurasia, and North America where 2013, and 2016). significant positive anomalies are observed (Fig. 1b). This interdecadal shift is generally consistent with changes in surface wind variability over the in both an interdecadal shift, that is, from frequent negative spring [April–June (AMJ)] and summer [July–September phases prior to 1998 to more frequent highly positive (JAS)]: An anomalous cyclone prevailed prior to the phases afterward (Fig. 1a). According to the Student’s late 1990s, which was replaced by an anomalous anti- t test, the significance of the shift exceeds the 99% con- cyclone over the Arctic Ocean in later years (Wu et al. fidence level. Spatially, positive thickness anomalies 2012). This interdecadal shift is consistent with the

21 FIG. 7. (a) Spatial distribution of summer mean EGR anomalies at 600 hPa day , derived from a linear regression on the normalized Arctic westerly index. White and black contours denote anomalies at 95% and 99% confidence levels, respectively. (b) As in (a), but for anomalies in the frequency of the anomalous low pressure. 15 FEBRUARY 2019 W U A N D F R A N C I S 1143

FIG. 9. The 2013 summer mean 500-hPa temperature anomalies (relative to the summer mean averaged over 1979–2016; 8C).

implying summer Arctic warm anomalies (Fig. 1c), con- sistent with the well-documented rapid Arctic sea ice FIG. 8. (a) Normalized time series of the NWPSH intensity index. (b),(c) As in (a), but for the ridge location (latitude) and western loss period. Years exhibiting summer Arctic cold anom- ridge point (longitude), respectively. All data obtained from Na- alies seem to be become more frequent in the context tional Climate Center in China (http://cmdp.ncc-cma.net/Monitoring/ of Arctic warming. It should be pointed out that two cn_index_130.php). thickness patterns are independent from each other and the leading thickness pattern cannot obscure the ex- rapid declining trend in September sea ice extent. Thus, pression of the second thickness pattern. Additionally, this leading pattern is closely associated with both although summer 500-hPa height anomalies exhibit a summer Arctic warming and sea ice loss. great similarity to 1000–500-hPa thickness anomalies Here we focus primarily on the second thickness (Figs. 1c, 2), differences are also visible, including extents pattern because it is associated with summer high and amplitudes of positive and negative anomalies. temperatures and heat waves in Asia and North America. b. Dynamic linkages between Arctic cold anomalies This pattern displays strong interannual variability but and East Asian heat waves does not exhibit any trend or shift (Fig. 1a). Spatially (Fig. 1c), negative thickness anomalies are observed in Significant correlations between the leading thick- the Arctic north of 708N, indicating Arctic cold anoma- ness pattern and frequency of summer heat waves are lies in the mid- and low troposphere. Positive thickness mainly confined to near the Ural Mountains (408–608N, anomalies appear mainly over northern Europe, north- 408–808E), North America, and the Arctic, rather than eastern Atlantic, western North America, the Bering over East Asia (not shown). Cold anomalies are also Sea, north-central Canada, and mid- and low latitudes observed over near Alaska, but they are not significant of East Asia. Over the eastern Pacific–North America (Fig. 1b). This study, therefore, focuses on the second and northern Pacific–East Asia, positive anomalies thickness pattern. The positive phase of PC2 correlates form a ‘‘comma’’ structure, which is associated with the significantly with heat waves over the mid- and low upper-tropospheric steering flow anomalies (see the fol- latitudes of Asia, particularly over the Tibetan Plateau lowing section). All extreme positive anomalies occurred (the third pole) and the coast of East Asia (Fig. 3a). after 2005, that is, 2006, 2013, and 2016, with values Significant correlations also exist over most of Europe, exceeding 1.5s, corresponding with Arctic cold anom- , southwestern United States, and alies (Figs. 1d–f). The negative phases of the second northern North Pacific Ocean. Decreased heat waves principal component (PC2) dominated during 2007–12, are observed over the Arctic Ocean, consistent with 1144 JOURNAL OF CLIMATE VOLUME 32

FIG. 10. The 500 hPa mean potential temperature advection and time mean of transient eddy flux diver- gence for summer of 2013: (a) 2V =u,(b)2v(›u/›p), 0 0 0 (c) 2= u V ,(d)2›u v0/›p, and (e) sum of (a)–(d). 21 Units are K day.

Arctic cold anomalies (Fig. 1c). Thus, a dipole structure (Fig. 3b). Consequently, East Asian heat waves fre- is apparent between the Arctic and several midlatitude quently occurred after 2005. It should be pointed out continental areas, particularly with the third pole. Over that if the criterion for heat waves is instead defined East Asia, the regionally (25.718–39.058N, 80.6258– as $1.5 standard deviations, very similar results are 1358E) averaged frequency of summer heat waves ex- obtained (not shown). hibits an increasing trend at the 99% confidence level Why do Arctic cold anomalies correspond with more (Fig. 3b). The frequency of East Asian heat waves intense and frequent summer heat waves in the mid- and exceeded 1.0s in 1994, 2001, 2006, 2010, 2013, and 2016 low latitudes of East Asia? We find that this association 15 FEBRUARY 2019 W U A N D F R A N C I S 1145

FIG. 12. Normalized time series: summer mean AO index (red) and second thickness pattern (blue), and their correlation is 0.66.

Positive Arctic westerly anomalies are not confined to the upper troposphere; they are evident throughout the troposphere and stratosphere (Fig. 5). Negative westerly anomalies in the mid- and low latitudes also penetrate through the troposphere and stratosphere. Such a change is attributed to a systematic northward 21 FIG. 11. Mean vertical velocity at 500 hPa (Pa s ) for summer shift of zonal winds, dominantly characterized by a of 2013. shift of the East Asian westerly jet. In fact, the Eur- asian westerly jet systematically migrates northward is closely related to the large-scale upper-tropospheric (Fig. 4a). Additionally, a dipole structure in zonal wind zonal wind variability. The positive phase of the sec- anomalies is also observed over the Arctic and the third ond thickness pattern significantly strengthens upper- pole (Figs. 4a,d, 5), similar to the pattern in temperature tropospheric westerlies over most of the Arctic (Fig. 4a), anomalies discussed previously. Over the Arctic, nega- while over Eurasia, wind anomalies display a belt struc- tive temperature anomalies are completely confined to ture with significantly weaker westerlies in the mid- and below 300 hPa and the top level of the stratosphere, with low latitudes of Asia and Europe. This wind pattern positive temperature anomalies between them (Fig. 6). closely resembles the leading pattern of summer 300 hPa Tropospheric temperature anomalies in the mid- and zonal wind variability north of 208N (not shown; r 5 low latitudes are in phase with Arctic temperature anom- 0.81; Fig. 4b). The area-weighted, regionally averaged alies in the upper troposphere and much of stratosphere. 300 hPa westerly north of 708N (Arctic westerly index) Strengthening of tropospheric westerly winds may en- is also significantly correlated with the second thickness hance baroclinicity in the mid- and low troposphere, pattern (r 5 0.88; Fig. 4c). In the upper troposphere, which dynamically favors the occurrence of anomalous Arctic westerly strength is out of phase with that in the low pressure during summer. Figure 7 supports this de- mid- and low latitudes of Asia. The normalized Arctic duction. We find that significant increases in baroclinicity westerly indices exceeded 1.5s in 2006, 2013, and 2016, are observed over the Arctic Ocean, surrounded by neg- corresponding with strong East Asian heat waves ative anomalies outside the Arctic (Fig. 7a). Decreases (Fig. 3b). Over the mid- and low latitudes of Asia, in baroclinicity emerge over high latitudes of Eurasia weakened upper-tropospheric steering flow (Fig. 4d) and North America, northern North Pacific, and East favors the stagnation of air masses and dynamically Asia, generally consistent with warm areas shown in contributes to sustained high pressure anomalies in Figs. 1c and 3a. Significant increases in the frequency the mid- and low troposphere (Fig. 4e). These anomalies of anomalous low pressure are confined to the Arctic suppress convection in the lower troposphere, thereby re- Ocean and northern North Atlantic, while negative ducing cloud cover and enhancing the downwelling surface anomalies cover most of Eurasia and North America shortwave radiation, which favors high temperatures and (Fig. 7b). Over high latitudes of the continents, de- heat waves. Sun (2014) also showed a significantly negative creases in the frequency of anomalous low pressure correlation (r 520.72) between July SAT averaged over may imply that thermal exchanges between the Arctic the region bounded by 27.58–32.58N and 1108–1258E Ocean and lower latitudes weaken. It should be noted and the 200 hPa zonal wind averaged over the same that if the threshold used to define anomalous low pres- region, consistent with our results here. sure is set to below 21.0 or 22.0 standard deviations in 1146 JOURNAL OF CLIMATE VOLUME 32

FIG. 13. (a) Normalized time series of the summer Arctic westerly index (red line) and the ensuing winter (DJF) index (blue line). Their correlation is 20.59, significant at 99% confidence level. (b) Winter 500-hPa geopotential height anomalies (gpm), derived from a linear regression on the normalized summer Arctic westerly index. White and black contours represent anomalies at 95% and 99% confidence levels, respectively. (c),(d) As in (b), but for winter SLP (hPa) and SAT (8C) anomalies, respectively. daily SLP anomalies, very similar results are obtained with the NWPSH intensity, ridge location, and west- (not shown). ern ridge point indices are 0.07, 20.09, and 20.24, re- spectively. While East Asia experienced abnormal high temperature and heat waves in 2013, the NWPSH was 4. Discussion in a neutral phase (Fig. 8). The statistical association between the NWPSH and heat waves also differs from a. Roles of NWPSH in East Asian heat waves that in Fig. 3a (not shown). Thus, increasingly frequent Although the NWPSH is believed to contribute East Asian heat waves cannot be simply attributed to to East Asian heat waves (Luo and Lau 2017; Gao the NWPSH. et al. 2018), some major characteristics of this sub- b. Possible dynamic processes linking Arctic tropical high, including intensity and location, are not cold anomalies significantly correlated with the second thickness pattern or with the Arctic westerly index. We find that We assess the statistical relationship between summer correlation coefficients of the second thickness pattern Arctic cold anomalies in the mid- and low troposphere 15 FEBRUARY 2019 W U A N D F R A N C I S 1147

FIG. 13. (Continued) and East Asian heat waves. As previously noted, we Here we carry out the case analysis of summer 2013 find strengthened westerly winds in the Arctic along (Fig. 1) to explore possible reasons for summer Arctic with weakened zonal winds in the mid- and low lati- cold anomalies in terms of wave-flow interactions at tudes of East Asia, which we attribute to a systematic 500 hPa: northward shift of the zonal wind belts. The present 0 0 study, however, cannot identify the mechanism re- ›u ›u 0 0 ›u v 52V =u 2 v 2 = u V 2 1 F, (1) sponsible for this shift nor for the temporal/spatial ›t ›p ›p behavior of the second thickness pattern. It is possible that natural variability may be a major reason for re- where u is potential temperature, V is horizontal wind cent changes in this pattern. vector, and F is the forcing term (Hoskins and Pearce 1148 JOURNAL OF CLIMATE VOLUME 32

1983). The overbar and prime denote time mean and anomalies exhibit a tripole structure, and the positive transient eddy terms, respectively. For this case, the time height anomalies cover East Asia, indicating a weakened mean is defined as the mean over 2013 JJA (92 days), east trough (Fig. 13b). This configuration resembles the so- and the transient eddy is obtained by subtracting the called Eurasian pattern (Wallace and Gutzler 1981; Wang time mean for a given date and location. Summer 500 hPa and Zhang 2015). Negative SLP anomalies occupy the temperature anomalies are shown in Fig. 9; the spatial mid- and high latitudes of Eurasia (Fig. 13c). Thus, winter pattern closely resembles the thickness anomaly pattern atmospheric circulation anomalies associated with strength- shown in Fig. 1e. Negative anomalies are confined to the ened Arctic westerly winds result in anomalous winter Arctic, surrounded by positive anomalies to the south. warming and a weakened winter monsoon over East Summer 500 hPa potential temperature anomalies closely Asia (Fig. 13d). Thus, the summer Arctic westerly index resemble that in Fig. 9 (not shown). We then calculated is an important precursor for winter surface air tem- the contributions of each term [2V =u, 2v(›u/›p), perature anomalies over East Asia and it may prove 0 0 0 2= V u , 2›u v0/›p] to the mean potential temperature to be useful predictor. It is not clear, however, which tendencies (Fig. 10). We find that both positive and mechanisms are responsible for this lagged relationship. negative contributions from each term occur simulta- It is possible that summer high temperatures and strong neously in the Arctic, and negative contributions mean heat waves in central and eastern Asia produce anom- that both mean potential temperature advection by the alies in soil temperature and moisture that lead to a mean flow as well as transient eddy flux divergence con- weakened East Asian winter monsoon. This question tribute to summer Arctic cold anomalies. Compared to requires further investigation. the transient eddy flux divergence, the vertical advection of mean potential temperature plays a more important 5. Conclusions role in driving Arctic cold anomalies. Over the mid- and low latitudes of Asia and northwestern Pacific, negative This study reveals the first two dominant patterns vertical advections are predominant except for central of summer 1000–500-hPa thickness variability north of and eastern China where the vertical advection is posi- 308N, and they, respectively, account for 29% and 10% tive, contributing to increases in mean potential temper- of the variance. The leading thickness pattern displays ature (Figs. 6, 9). The summer mean vertical velocities at strong interannual variability superposed on an inter- 500 hPa during 2013 (Fig. 11) suggest that vertical mo- decadal shift that occurred in the late 1990s, consistent tions dominate the contribution of vertical advection of with summer Arctic warming and rapid Arctic sea ice mean temperature (Fig. 10b). We repeat the same anal- loss. Spatially, positive thickness anomalies cover much ysis process for 2006 and 2016 summers, producing simi- domain north of 308N, particularly over the Arctic, lar results (not shown). This implies that Arctic upward Eurasia, and North America where significant positive motion in the mid- and low troposphere is a major reason anomalies are observed. The second thickness pattern for summer Arctic cold anomalies. Ogi et al. (2004) in- exhibits strong interannual variability but does not exhibit vestigated summer annual mode and its association with any trend or shift. The positive phase of the second anomalies in zonal mean temperature and meridional thickness pattern corresponds with significant Arctic cold circulation and found that summer Arctic cold anomalies anomalies in the mid- and low troposphere, which are in the mid- and low troposphere correspond to upward surrounded by warm anomalies outside the Arctic. Arctic motion anomalies (see their Fig. 3d), consistent with re- cold anomalies have occurred more frequently in the sults here. Although anomalous atmospheric circulation context of Arctic warming (2005–16). patterns discussed by Ogi et al. (2004) exhibit some sim- The second thickness pattern is the thermodynamic ilarities to the second thickness pattern, their differences expression of the leading pattern of upper-tropospheric are robust (Fig. 12). We also note that downward and westerly variability and shows significant positive cor- upward motions coexist simultaneously over the Arctic relations with frequencies of East Asian heat waves. In (Fig. 11) and their roles are opposite. the upper troposphere, enhanced Arctic westerly winds are out of phase with winds in the mid- and low latitudes c. Precursor to predict East Asian winter monsoon of Asia. The stronger Arctic westerly winds significantly Finally, we find that the strengthened summer Arctic enhance baroclinicity, which dynamically contributes to westerly is significantly correlated with the ensuing increased frequency of anomalous low pressure over the Asian winter climate variability (Fig. 13). The correla- Arctic. The weaker westerly winds favor stagnation of tion between the Arctic westerly index and the winter warm air and dynamically contributes to sustained high Siberian high index is 20.59, significant at 99% confi- pressure anomalies in the mid- and low troposphere, dence level (Fig. 13a). At 500 hPa, geopotential height increasing the likelihood of East Asian heat waves. 15 FEBRUARY 2019 W U A N D F R A N C I S 1149

These wind anomalies can be attributed to a systematic Gao, M., B. Wang, J. Yang, and W. Dong, 2018: Are peak summer northward shift of zonal winds, dominantly character- sultry heat wave days over the Yangtze–Huaihe River basin 31 ized by a shift of the East Asian westerly jet. This predictable? J. Climate, , 2185–2196, https://doi.org/10.1175/ JCLI-D-17-0342.1. shift dynamically produces a dipole structure in zonal Hoskins, B. J., and R. P. Pearce, 1983: Large-Scale Dynamical wind anomalies over the Arctic and the third pole. Dy- Processes in the Atmosphere. Academic Press, 397 pp. namic analysis indicates that Arctic upward motion in Hu, K., G. Huang, and R. Huang, 2011: The impact of tropical the mid- and low troposphere is a major reason for Indian Ocean variability on summer surface air temperature in 24 summer Arctic cold anomalies. The enhanced Arctic China. J. 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