Time-varying structure of the wintertime Eurasian pattern: Role of the North. Atlantic sea surface temperature and atmospheric mean flow

Transcription

1 Time-varying structure of the wintertime Eurasian pattern: Role of the North Atlantic sea surface temperature and atmospheric mean flow 0 Lin Wang,,, Yuyun Liu,, Yang Zhang, Wen Chen,, Shangfeng Chen Center for Monsoon System Research and LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China Joint Center for Global Change Studies, Beijing, China College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China School of Atmospheric Sciences, Nanjing University, Nanjing, China Citation: Wang L, Y Liu, Y Zhang, W Chen, S Chen, 0: Time-varying structure of the wintertime Eurasian pattern: Role of the North Atlantic sea surface temperature and atmospheric mean flow, Climate Dynamics, doi: 0.00/s Correspondence to: Dr. Lin Wang, wanglin@mail.iap.ac.cn

2 0 0 Abstract The Eurasian (EU) pattern was shown to be closely linked to the North Atlantic sea surface temperature (SST) in boreal winter and this study suggest that such linkage varies with time and that the structure of the EU pattern also changes accordingly. During the period with strong EU-SST linkage ( and 0, denoted as HIGH epoch), the EU pattern is a well-defined barotropic wave train stretching from the North Atlantic towards East Asia-western North Pacific, and it facilitates cooling and slight reduction of precipitation over East Asia and enhanced precipitation over Europe in its positive phase. During the period with weak EU-SST linkage ( 0 and, denoted as LOW epoch), in contrast, its centre over Northern Europe weakens sharply, and the wave-like structure of the EU pattern is not well established. In this case, its influences on precipitation over Europe almost vanish, but its influences on both the surface air temperature and precipitation over East Asia amplify significantly. The Atlantic centre of the EU pattern forms from different mechanism during the two epochs. It can be excited by the underlying North Atlantic SST via eddy-mediated processes during the HIGH epoch, while it is likely generated by an incoming Rossby wave train from upstream region. Nevertheless, its location and intensity remain similar during the two epochs. Numerical experiments with a barotropic model suggest that the contrasting structure of the EU pattern is mainly attributed to the changes of the atmospheric mean flow.

3 . Introduction 0 0 As one of the major teleconnection patterns in the Northern Hemisphere winter, the Eurasian (EU) pattern (Wallace and Gutzler ; Barnston and Livezey ; Liu et al. 0) manifests itself as a barotropic Rossby wave train in the troposphere. The variations of the EU pattern can significantly influence the climate over Eurasia especially over Eastern Europe and East Asia (Wu ; Tachibana et al. 00; Sung et al. 00; Liu et al. 0; Wang and Chen 0b; Wang and Zhang 0). For example, the positive phase of the EU pattern often facilitates a strong East Asian winter monsoon on both inter-annual (Takaya and Nakamura 0; Wang and Chen 0a; Wang and Chen 0b; Wang and Lu 0) and decadal (Wang and Chen 0a) timescales, with significant enhanced coldness and reduced precipitation over large areas of eastern China (Liu et al. 0). Some studies suggest that the EU pattern is the most important teleconnection pattern to influence the interannual variations of the East Asian winter monsoon (Takaya and Nakamura 0; Wang and Chen 0b; Liu et al. 0; Hu et al. 0; Lim and Kim 0). The formation and maintenance mechanism of the EU pattern is an important issue. Unlike other wave-like teleconnections such as the Pacific-North America pattern and the Eastern Atlantic pattern, the baratropic instability cannot well explain the maintenance of the EU pattern (Nakamura et al. ). Instead, baroclinic processes and external forcing are likely play some essential roles (Nakamura et al. ). One potential candidate of external forcing is the sea

4 0 0 surface temperature (SST) anomalies over the North Atlantic (Gambo et al. ; Li 00; Liu et al. 0; Qiao and Feng 0). Using the outputs from an atmospheric general circulation model, Li (00) suggested that the SST anomalies over the North Atlantic can excite an EU-like wave train, and that the SST-induced atmospheric responses are largely maintained by the resultant vorticity forcing of transient eddies. Based on observational and reanalysis data, Liu et al. (0) analysed the linkage between the EU pattern and the North Atlantic SST. They suggested that when warm SST anomalies are observed to the southeast of Newfoundland, the SST gradient and low-level baroclinicity are intensified to the north of the warm SST anomalies, leading to enhanced activity of transient eddies. As a result, anticyclonic tendency is induced via eddy vorticity forcing over the warm SST anomalies, severing as the first centre of action of the EU pattern. The crucial role of the North Atlantic SST in the formation of the EU pattern has been revealed by the abovementioned studies based on dataset of approximately 0 years. However, many studies suggest that the linkages between some particular oceanic forcing and climate are not stationary (e.g., Wang et al. 00; Chen et al. 0a; Chen et al. 0b). For example, the connections of the North Atlantic SST tripole with atmospheric circulations and climate over the North Atlantic and Eurasia experienced clear decadal changes (e.g., Chen et al., 0a; Chen and Wu, 0). These studies motivate us to inspect whether the relationship between the North Atlantic SST and the EU pattern also experiences some decadal changes

5 during the past decades, and if any, what consequences it may cause and what the involved mechanism is. These issues will be addressed in this paper. The remaining parts of the paper are organized as follows. Section introduces the datasets and methodology. Section shows the observed interdecadal changes in the relationship between the EU pattern and the North Atlantic SST. Section presents the time-varying structure of the EU pattern and associated climate anomalies during epochs featuring different EU-SST relationships. Section discusses the possible mechanism of the altered EU pattern, and Section summaries the main findings and discusses some remaining issues. 0. Data and methods 0 The atmospheric data used in this study are from the monthly mean National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis dataset, spanning the period from to the present (Kalnay et al. ). The dataset has a horizontal resolution of.. and extends from 000 to 0 hpa with pressure levels. The global SST data are from the Met Office Hadley Centre s sea ice and SST datasets (HadISST) with horizontal resolution (Rayner et al. 00), covering the period from 0 to the present. The monthly mean precipitation data are from two datasets. One is from the Precipitation Reconstruction Over Land (PREC/L) with.. horizontal resolution, spanning from to the present (Chen et al. 00). The other is from the monthly global gridded high-resolution station (land) dataset for air temperature

6 0 0 and precipitation (version ) provided by the Center for Climatic Research, Department of Geography of the University of Delaware (Willmott and Matsuuta, 00). This dataset has a resolution and spans from 0 to 0. Winter mean are considered in this paper, and they are constructed by averaging the monthly data of December, January and February (DJF). The period considered is the winters of / 0/ (hereafter 0). Liu et al. (0) identified the EU pattern by applying the rotated empirical orthogonal functions (REOF) to the winter mean 00-hPa geopotential height anomalies from to 00. They defined the sixth REOF (REOF) mode as the EU pattern and the corresponding PC time series as the EU index. To keep consistency of this study and Liu et al. (0), the winter mean 00-hPa geopotential height anomalies from to 0 are projected onto the pattern of REOF used in Liu et al. (0) to obtain a longer time series of the EU index. In this way, the EU index used in this study is identical to that in Liu et al. (0) during their overlapping period. The wave activity flux (Takaya and Nakamura 00) is employed to illustrate the propagation of Rossby wave associated with the EU pattern. The anomalies regressed onto the normalized EU index are taken as the perturbations in the calculations of the wave activity flux. As in our previous study (Song et al. 0), the geopotential height tendency induced by the transient eddies is evaluated to illustrate the forcing of eddies on the mean flow following Lau and Holopainen (), where transient eddies are extracted by applying a 0 day

7 Lanczos band pass filter to daily data with weights. The confidence level of the linear correlation and regressions are evaluated with the two-tailed Student s t test, and the effective sample size N * following Bretherton et al. () as follows: is estimated N rr N rr * where N is the length of the period analysed, r and r () represents the lag one autocorrelation coefficients of the two time series considered, respectively.. Interdecadal changes in the EU-SST linkage 0 0 Figure a shows the 00-hPa geopotential height anomalies in the positive phase of the EU pattern. It features a wave train-like structure stretching from North Atlantic across Eurasia towards East Asia and western North Pacific. Two cyclonic centres are located over Northern Europe and Japan, and two anticyclonic centres are over the North Atlantic and northern Siberia. The EU index shows strong interannual variations (Figure b) with peaks of period centred on years (Figure d). The local wavelet spectrum indicates that the year variability is significant from the mid-0s to the late 0s and from the mid-0s to the late 000s (Figure c), and that the year variability is significant in the 0s and from the mid-0s to mid-0s (Figure c). On one hand, these results are overall consistent with Liu et al. (0). On the other hand, they imply that the interannual variability of the EU pattern may experience some interdecadal change.

8 0 0 Figure presents the winter mean SST regressed against the simultaneous EU index. Significant positive anomalies are observed over the central North Atlantic to the southeast of Newfoundland (Figure a), consistent with Liu et al. (0). An SST index is defined as the SST averaged over the North Atlantic (. W. W, 0. N. N) indicated by the box shown in Figure a. The domain to define the SST index is also the same as that in Liu et al. (0). The lag correlation between the EU index and the SST index suggests a close coupling between the EU pattern and the North Atlantic SST from when the SST leads the EU index by five months to when the SST index lags the EU index by four months. The maximum correlation coefficient is observed when the EU pattern leads SST by one month. All these results are consistent with Liu et al. (0) although longer period is considered in this study. To examine the possible non-stationary relationship between the EU pattern and the North Atlantic SST, sliding correlation coefficients between the winter mean EU and SST indices are calculated with a year window (Figure ). It is obvious that their relationship shows clear decadal changes. The correlation coefficient is strong and significant during the periods and 0, and it is weak and insignificant during other periods. In the following analysis, we name the years with high correlation coefficient ( and 0) as the HIGH epoch, and the years with low correlation coefficient ( 0 and ) as the LOW epoch.

9 0 Figure shows the EU-SST relationship during the two epochs. During the HIGH epoch, significant and positive SST anomalies are observed over the central North Atlantic (Figure a), resembling that derived from the whole period (Figure a). The lag correlation coefficient between the wintertime EU index and the SST index begins to exceed the % confidence level when the SST index leads the EU index by five months (Figure b). This is also consistent with that derived from the whole period (Figure b) except that the maximum correlation coefficient is observed during lag 0 (Figure b). During the LOW epoch, in contrast, the warm SST anomalies over the central North Atlantic are weak and insignificant (Figure c), and the lag correlation coefficient between the EU and SST indices is insignificant (Figure d). Hence, these results confirm that the interannual relationship between the EU pattern and the North Atlantic SST is non-stationary and quite contrasting between the two epochs. The EU-related air-sea interactions are strong and active during the HIGH epoch and weak and inactive during the LOW epoch.. Time-varying structure of the EU pattern and associated climate anomalies 0 Considering the importance of the North Atlantic SST in the formation of the EU pattern (e.g., Liu et al. 0), the weakened EU-SST coupling (Figures c, d) implies that the EU pattern may not be well excited and maintained during the LOW epoch. To confirm this inference, the structure of the EU pattern is examined during the two epochs. Figures a and c show the 00-hPa geopotential height anomalies

10 0 0 in the positive phase of the EU pattern. During the HIGH epoch, the wave-like pattern is clear and significant with continuous wave activity fluxes from the North Atlantic to East Asia (Figure a), consistent with Liu et al. (0). During the LOW epoch, in contrast, the centre over Northern Europe is quite weak and insignificant, and the EU-related wave train is almost disconnected between the North Atlantic and Eurasia (Figure c). It suggests that the EU pattern is not well established during the LOW epoch when the air-sea interactions over the North Atlantic are weak. Nevertheless, the cyclonic centre near Japan is stronger in the LOW epoch than in the HIGH epoch. In addition, the centres of actions of the EU pattern other than the one over Northern Europe are located slightly westward in the LOW epoch compared with those in the HIGH epoch (Figures a, c). The abovementioned changes can also be observed in the lower troposphere because the EU pattern is equivalent barotropic (Liu et al. 0). For example, the EU-related sea level pressure (SLP) anomalies near Scandinavia show similar pattern during the two epochs (Figures b, d), but they are statistically insignificant during the LOW epoch (Figure d). This feature is consistent with that in the upper troposphere (Figures a, c), and it confirms that the EU pattern is not well established during the LOW epoch when the air-sea coupling is weak over the North Atlantic. Meanwhile, the anticyclonic centre of the EU pattern over central Siberia shifts westward by approximately ten degrees in the LOW epoch (Figure d) compared with that in the HIGH epoch (Figure b). On one hand, this feature is 0

11 0 0 consistent with the slight westward shift of the EU pattern in the upper troposphere (Figure a, c). On the other hand, the shifted SLP anomalies over East Asia imply that the associations of the EU pattern with the East Asian climate may be different between the two epochs. Figure shows the EU-related 0hPa wind anomalies during the two epochs. Anomalous northerly winds are observed over almost the entire East Asia (Figures a, b), indicating that the climatological northerly winds (e.g., Figure in Chen et al. 000) are enhanced. The basic temperature field features strong meridional gradient over East Asia with low temperature to the north (Figure ). Therefore, the enhanced northerly winds could lead to cold anomalies over East Asia (Figures a, c, a, c) via meridional temperature advection (Figures a, b). Meanwhile, less precipitation is observed over mid-latitude East Asia (Figures b, d, b, d) because enhanced northerlies brings more dry air southward and reduces northward transport of water vapour significantly (Wang and Chen 00). Although the EU-related wind anomalies bear similar patterns during the two epochs, the magnitude of the wind anomalies is larger over East Asia during the LOW epoch (Figure c). Hence, the associations of the EU pattern with the East Asian winter climate is tighter during the LOW epoch than during the HIGH epoch, as indicated by the stronger and broader temperature (Figure a, c, a, c) and precipitation (Figure b, d, b, d) anomalies over East Asia. The difference of the magnitude of the anomalous northerlies arises from the different zonal pressure gradient caused

12 mainly by the centre over the North Pacific (Figures b, d, c). In addition to the above differences over East Asia, the EU pattern is more closely associated with precipitation over Europe during the HIGH epoch (Figures b, b) than during the LOW epoch (Figures d, d) due to its well-established centre over Europe (Figure ).. Mechanism of the time-varying structure of the EU pattern 0 0 a. Role of the North Atlantic SST The extratropical atmosphere can respond to changes in underlying SST during which the eddy-mediated processes play crucial role (Frankignoul ; Kushnir et al. 00; O Reilly and Czaja 0; Ma et al. 0; Ma et al. 0; Xiao et al. 0; Nie et al. 0; Ogawa et al. 0), and this mechanism is also valid to explain the excitation of the EU pattern by the North Atlantic SST (Liu et al. 0). During the HIGH epoch, the EU-related SST anomalies are located right to the south of the Gulf Stream (Figure a). Therefore, the presence of the warm SST anomalies can increase the meridional SST gradient and thereby the low-level baroclinicity along the Gulf Stream (not shown), leading to enhanced activity of transient eddies (Figure a) to the north of the climatological mean North Atlantic storm track (Figure 0). As a result, barotropic anticyclonic tendency is induced via eddy vorticity and heat forcing over the warm SST anomalies, forming the Atlantic centre of the EU pattern (Figure b). This mechanism is further validated by circulation and eddy-related variables regressed onto the North Atlantic SST index (Figures a,

13 0 0 b), which quite resemble their counterparts regressed onto the EU index (Figures a, b). These results suggest that the EU pattern can be well excited by the North Atlantic SST via eddy-mediated processes during the HIGH epoch. During the LOW epoch, in contrast, the EU-related SST is quite weak over the North Atlantic (Figure c) so that the modulation effect of the SST on the low-level baroclinicity is weak (not shown). In this circumstance, although the changes of transient eddies show similar pattern to those during the HIGH epoch, they are relatively weak and less statistically significant (Figure c). Moreover, the eddy-induced geopotential height tendency does not match the Atlantic centre of the EU pattern (Figure d). Therefore, the Atlantic centre of the EU pattern is not likely excited by the underlying SST and the resultant feedback forcing of transient eddies. This conclusion is further confirmed by the transient eddy activities and eddy-induced geopotential height regressed onto the North Atlantic SST index, which cannot explain the SST-associated geopotential height pattern (Figures c, d). In fact, the correlation coefficient between the EU and SST indices is weak at lag 0 and shows a peak when SST lags the EU pattern by one month (Figure d). Though statistically insignificant at the % confidence level, the lag correlation analysis confirms that the active role of the North Atlantic SST on the EU pattern is weak during the LOW epoch, and that the forcing of the EU pattern on the underlying SST is likely of the primary order.

14 0 0 In the absence of the oceanic forcing, the EU pattern should be induced by some other processes. In fact, clear wave activity fluxes are found to propagate towards the Atlantic centre of the EU pattern from North America during the LOW epoch (Figure c), which are not observed during the HIGH epoch (Figure a). It suggests that the quasi-stationary waves from upstream region are important for the formation of the EU pattern during the LOW epoch. In addition, considering the effect of stationary waves to shape transient eddies (e.g., Kaspi and Schneider 0) and the inconsistency between the EU pattern and eddy-induced geopotential tendency over the North Atlantic (Figure d), it is reasonable to regard the changes of transient eddies (Figure c) as a response to other than a forcing for the EU pattern during the LOW epoch. b. Role of the atmospheric mean flow Although the coupling between the EU pattern and the underlying SST show different natures, the location and intensity of the Atlantic centre of the EU pattern are quite similar during the two epochs (Figures a, c). The EU-related Rossby wave source (Sardeshmukh and Hoskins ) also shows similar pattern over the North Atlantic despite some differences in their intensity (Figure ). Hence, the contrasting structures of the EU pattern outside the EU s source region cannot be explained by the different role of the North Atlantic SST discussed in Section a. Considering that the EU pattern manifests itself as a quasi-stationary Rossby wave (Liu et al. 0) and that the propagation of Rossby wave depends on the structure

15 0 0 of the background flow (e.g., Hoskins and Karoly ; Yang and Hoskins ), the possible role of the atmospheric mean flow is examined with a spectral barotropic model, who has the truncation at rhomboidal wave number 0. Here, the barotropic model is employed for two reasons. First, the EU pattern is equivalent barotropic in the troposphere (Figure ) and share similar Rossby wave source over the North Atlantic (Figure ) during the two epochs. Second, although the eddy heat flux tends to offset the effect of the eddy vorticity flux in the upper troposphere, the net effect of is dominated by the eddy vorticity flux (e.g., Lau and Holopainen ; Lau and Nath ). In this aspect, the barotropic model can well capture the fundamental dynamics of the atmospheric responses to prescribed vorticity forcing (Sardeshmukh and Hoskins ). Therefore, the possible role of the atmospheric mean flow can be isolated by using the same vorticity forcing with different background flow. Two pairs of experiments, denoted as Exp_HIGH and Exp_LOW, were performed with the same vorticity forcing, and they differ only in their atmospheric background flow. The climatology in Exp_HIGH and Exp_LOW is based on the average over the HIGH epoch (i.e, - and -0) and the LOW epoch (i.e, 0 and ), respectively. In each pair, the model is forced by the climatological winter mean divergence plus prescribed divergence and convergence anomalies in two separate runs. The difference between the two runs is used to indicate the atmospheric responses to the prescribed vorticity forcing, which

16 0 0 in our case is located over the North Atlantic with a maximum intensity of 0 - s - at 0 N, W (red contours in Figure ). The location of this prescribed vorticity forcing is right over the SST anomalies over the North Atlantic (Figures a, a) and consistent with the EU-related anticyclonic Rossby wave source to the southeast of Newfoundland (Figure ). In each experiment, the model was integrated for 0 days, and the averaged results over model days -0 are shown. Figure displays the model response in Exp_HIGH and Exp_LOW. A zonally-oriented wave train is observed stretching from the North Atlantic to Eurasia in Exp_HIGH (Figure a). It bears some resemblance to the observed EU pattern (Figure a) and the observed pattern associated with the North Atlantic SST (Figures a, b) during the HIGH epoch, although differences exist in the location and structure of the wave train over the North Atlantic and Eurasia. In Exp_LOW, the atmospheric response displays a meridional tripole over the North Atlantic and a zonal wave train over Eurasia (Figure b), bearing a close resemblance to that in the observation (Figure c). In particular, the cyclonic anomaly and associated negative potential height anomalies around the Scandinavian Peninsula are much weaker in Exp_LOW (Figure b) than in Exp_HIGH (Figure a), which quite resembles the observed differences of the EU-related wave pattern between the HIGH and LOW epochs (Figures a, c). Note that the differences of the atmospheric responses between Exp_HIGH and Exp_LOW originate solely from the different atmospheric mean flow. Hence, the results of model experiments

17 suggest that the contrasting wave structure of the EU pattern except for the centre over mid-latitude North Atlantic are very likely attributed to the differences of the atmospheric mean flow between the HIGH and LOW epochs.. Summary and discussion 0 0 a. Summary Based on reanalysis and observational datasets, this study suggests that the coupling between the EU pattern and the North Atlantic SST experiences clear interdecadal changes. More interestingly, it reveals that the structure of the EU pattern is quite contrasting when the coupling shows different characteristics. During the period and 0 (i.e., HIGH epoch), the positive EU pattern is closely related to the warmer-than-normal SST over the North Atlantic, and it features a well-defined barotropic wave train stretching from the North Atlantic across Eurasia towards East Asia and western North Pacific. As a result, the positive EU pattern facilitates warm (cold) anomalies over northern Eurasia (East Asia) and more (less) precipitation over Europe (central Asia). During the period 0 and (i.e., LOW epoch), in contrast, the EU pattern is loosely related to the underlying SST, and its centre over Northern Europe is weak and statistically insignificant. Therefore, the EU-related barotropic wave train is not well established, and it is almost disconnected between the North Atlantic and Eurasia. In this circumstance, the EU pattern cannot alter precipitation over Europe efficiently due to its weakened centre over Northern Europe, but it could lead to broader and

18 0 0 stronger cold anomalies and reduction of precipitation over East Asia than during the HIGH epoch due to the slight westward shift of the wave pattern. The changes in the structure of the EU pattern can be understood from two aspects involving the role of the North Atlantic SST and the atmospheric mean flow. During the HIGH epoch, the North Atlantic SST plays an active role to excite the EU pattern where the eddy-mediated processes are important. Warm SST anomalies to south of the Gulf Stream can intensify the meridional SST gradient along the oceanic front efficiently. As a result, the low-level baroclinicity and transient eddy activities are enhanced to the north of the warm SST anomalies, and the first centre of the EU pattern to the southeast of Newfoundland can be generated via the feedback forcing of transient eddies. During the LOW epoch, however, the first centre of the EU pattern is likely generated by an incoming Rossby wave train from North America, and the North Atlantic SST responds passively to the EU pattern. Despite the different formation mechanism, the location and intensity of the first centre of the EU pattern are quite similar during the HIGH and LOW epochs. Numerical experiments with a barotropic model suggest that the contrasting wave structures of the EU pattern between the HIGH and LOW epochs arise from the differences of the atmospheric mean flow during the two epochs. b. Discussion When the role of the atmospheric mean flow was examined with the barotropic model, a divergent/convergent anomaly over the North Atlantic was used

19 0 0 as the anomalous vorticity forcing (Figure ). A natural question is how this anomalous divergence is connected to the underlying SST especially during the HIGH epoch. In the tropical regions, warm SST anomaly can excite deep convection that reaches up to the tropopause level. The resultant release of the latent heat in the middle troposphere can lead to divergence anomaly in the upper troposphere. In the mid-latitude regions, however, warm SST anomaly cannot excite deep convection (e.g., Kushnir et al. 00). In contrast, it can reshape transient eddies via modulating the atmospheric baroclinic instability (e.g., Liu et al. 0; O Reilly and Czaja 0; Ma et al. 0; Ma et al. 0; Xiao et al. 0; Nie et al. 0; Ogawa et al. 0). The resultant changes of transient eddy activity can serve as a significant Rossby wave source (e.g., Vallis et al. 00) and exert influences on the barotropic field. These processes can be well observed during the HIGH epoch (e.g., Figures a, b, a, b, ). During the LOW epoch, by contrast, the anomalous divergence is loosely related to the underlying SST, and it is very likely caused by the incoming Rossby wave from the North America (Figure c). The nature of EU-related air-sea interaction was shown to be quite different during the HIGH and LOW epochs, leading to different formation mechanism of the Atlantic centre of the EU pattern. Meanwhile, the configurations of the atmospheric mean flow were shown to be different during the two epochs, accounting for the contrasting structure of the EU pattern downstream of the North Atlantic. One may ask whether the altered EU-related air-sea interaction is physically linked to the

20 0 0 changes of the atmospheric mean state. This question is beyond the scope of this paper, but some studies do suggest that the atmospheric responses to mid-latitude SST anomalies are sensitive to the atmospheric mean flow (Lau and Nath ; Peng and Whitaker ; Kug and Jin 00; Hong and Lu 0; Chen et al. 0). Hence, some numerical experiments may be performed to address this issue in the future. Another interesting point is that Wallace and Gutzler () first identified the EU pattern based on data spanning from to, which is fully within the HIGH epoch. In contrast, Barnston and Livezey () reported that they did not find the conventional EU pattern proposed by Wallace and Gutzler () based on data spanning from 0 to, which is half in LOW epoch and half in HIGH epoch. Considering the contrasting EU pattern during the HIGH and LOW epochs, it is understandable why Barnston and Livezey () failed to get the same EU pattern as that in Wallace and Gutzler (). Last but not least, this study is based on NCEP/NCAR reanalysis data, and it is further confirmed by repeating the analyses with JRA- reanalysis dataset (Kobayashi et al. 0) for the period 0. The results remain almost identical when the JRA- dataset is used (e.g., Figure versus Figure ), except that a slightly smaller region (. -. W, N) is used to define the North Atlantic SST index. Nevertheless, it suggests that the results reported in this study are robust and independent on the dataset. 0

21 0 Acknowledgements. We thank the three anonymous reviewers for their insightful comments and constructive suggestions that led to significant improvement of the manuscript. We also thank Drs. Wei Chen, Kaiming Hu, Xiaowei Hong of IAP, Dr. Jie Zhang of NCC, and Dr. Wen Chen of UMD for helpful discussions. This work was supported jointly by the Key Research Program of Frontier Sciences of Chinese Academy of Sciences (QYZDY-SSW-DQC0), the National Natural Science Foundation of China (00, 00, 000), the Fundamental Research Funds for the Central Universities, and Open Research Fund Program of Plateau Atmosphere and Environment Key Laboratory of Sichuan Province (PAEKL-0-C).

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29 Figures Captions 0 0 Figure. (a) Regression (contour)/correlation (shading) of the winter mean 00-hPa geopotential height on the normalized winter mean EU index for the period 0. (b) Normalized winter mean EU index for the years 0. (c) Local wavelet power spectrum and (d) global wavelet spectrum of the winter mean EU index based on the Morlet wavelet. In (a), contour intervals are gpm, zero contours are omitted, negative values are dashed, and the dark and light shading indicate the % and % confidence levels, respectively. Bold contours in (c) and dash line in (d) indicate the 0% confidence level. Figure. (a) Regression (shading) of the winter mean SST on the normalized winter mean EU index for the period 0. (b) Lag correlations between the winter mean EU index and the North Atlantic SST index. In (a), shading intervals are 0. C, stippling indicates the % confidence level, and the blue box indicates the region to define the SST index (.. W, 0.. N). In (b), data are smoothed by the three-month running mean, and the dashed and dotted lines indicate the % and % confidence levels, respectively. Figure. Sliding correlation coefficients between the winter mean EU index and the winter mean SST index with a -year window. The label in x-axis denotes the central year of the -year window. The dashed and dotted lines indicate the % and % confidence levels, respectively. Figure. (a) and (b) are the same as Figure, but during the HIGH epoch. (c) and

30 0 0 (d) are the same as Figure, but during the LOW epoch. Contours in (a) and (c) indicate the climatology of the winter mean SST averaged over the period 0. Blue boxes in (a) and (c) are the same as that in Figure a. Figure. (a) Winter mean 00-hPa geopotential height anomalies [contour, contour interval (CI)=gpm] and the horizontal components of the wave activity flux (arrow, unit: m s - ) and (b) winter mean SLP anomalies (CI=0.hPa) associated with the EU index obtained via a linear regression during the HIGH epoch. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Zero contours are omitted, and negative values are dashed. The dark and light shading indicate the % and % confidence levels, respectively. Figure. Winter mean 0-hPa wind anomalies (vector, unit: m s - ) associated with the EU index obtained via a linear regression during (a) the HIGH epoch and (b) the LOW epoch. (c) Difference between (b) and (a). Shading indicates the climatology of the winter mean 0-hPa air temperature averaged over the period 0. Figure. Winter mean (a) 0hPa air temperature anomalies and (b) precipitation percentage anomaly associated with the EU index obtained via a linear regression during the HIGH epoch based on NCEP/NCAR reanalysis dataset and PREC/L dataset. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Stippling indicates the % confidence level. Figure. Same as in Figure, but based on observational data from the University of Delaware. 0

31 0 0 Figure. Winter mean (a) storm track anomalies (shading), and (b) 00-hPa geopotential height tendency induced by transient eddies (shading) associated with the EU index, obtained via a linear regression overlaid by the 00-hPa geopotential height anomalies (contour, CI=gpm) regressed onto the EU index during the HIGH epoch. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Zero contours are omitted, and stippling indicates the % confidence level of shading. Storm track in (a) and (b) are estimated by the standard deviation of 0 day band-pass filtered 00-hPa geopotential height. Figure 0. Climatology of the winter mean storm track estimated by the standard deviation of 0 day band-pass filtered 00hPa geopotential height. Contour intervals are 0 gpm. Figure. Same as Figure, but regressed on the winter mean SST index. Figure. Winter mean 00-hPa Rossby wave source anomaly (shading) associated with the EU index obtained via a linear regression during (a) the HIGH epoch, and (b) the LOW epoch. Shading intervals (SIs) are 0 - s -. Stippling indicates the % confidence level. Black boxes are the same as that in Figure a. Figure. Geopotential height perturbation in the barotropic model (black contour, CI=0gpm starting from ±0gpm) in response to idealized divergence forcing (red contour, CI= 0 - s - ) over the North Atlantic using the winter mean climatology derived from (a) the HIGH epoch, and (b) the LOW epoch. Figure. Same as Figure, but based on JRA- dataset.

32 0N a) EU pattern CI=gpm 0 0N 0N 0-0 0W 0W 0W 0 0E 0E 0E 0E 0E 0 0W 0W b) EU index Time (year) c) Wavelet Power Spectrum d) Global Period (years) % Time(year) 0. 0 Power Figure. (a) Regression (contour)/correlation (shading) of the winter mean 00-hPa geopotential height on the normalized winter mean EU index for the period 0. (b) Normalized winter mean EU index for the years 0. (c) Local wavelet power spectrum and (d) global wavelet spectrum of the winter mean EU index based on the Morlet wavelet. In (a), contour intervals are gpm, zero contours are omitted, negative values are dashed, and the dark and light shading indicate the % and % confidence levels, respectively. Bold contours in (c) and dash line in (d) indicate the 0% confidence level.

33 Figure. (a) Regression (shading) of the winter mean SST on the normalized winter mean EU index for the period 0. (b) Lag correlations between the winter mean EU index and the North Atlantic SST index. In (a), shading intervals are 0. C, stippling indicates the % confidence level, and the blue box indicates the region to define the SST index (.. W, 0.. N). In (b), data are smoothed by the three-month running mean, and the dashed and dotted lines indicate the % and % confidence levels, respectively.

34 Figure. Sliding correlation coefficients between the winter mean EU index and the winter mean SST index with a -year window. The label in x-axis denotes the central year of the -year window. The dashed and dotted lines indicate the % and % confidence levels, respectively.

35 Figure. (a) and (b) are the same as Figure, but during the HIGH epoch. (c) and (d) are the same as Figure, but during the LOW epoch. Contours in (a) and (c) indicate the climatology of the winter mean SST averaged over the period 0. Blue boxes in (a) and (c) are the same as that in Figure a.

36 Figure. (a) Winter mean 00-hPa geopotential height anomalies [contour, contour interval (CI)=gpm] and the horizontal components of the wave activity flux (arrow, unit: m s - ) and (b) winter mean SLP anomalies (CI=0.hPa) associated with the EU index obtained via a linear regression during the HIGH epoch. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Zero contours are omitted, and negative values are dashed. The dark and light shading indicate the % and % confidence levels, respectively. 0

37 Figure. Winter mean 0-hPa wind anomalies (vector, unit: m s - ) associated with the EU index obtained via a linear regression during (a) the HIGH epoch and (b) the LOW epoch. (c) Difference between (b) and (a). Shading indicates the climatology of the winter mean 0-hPa air temperature averaged over the period 0.

38 Figure. Winter mean (a) 0hPa air temperature anomalies and (b) precipitation percentage anomaly associated with the EU index obtained via a linear regression during the HIGH epoch based on NCEP/NCAR reanalysis dataset and PREC/L dataset. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Stippling indicates the % confidence level.

39 Figure. Same as in Figure, but based on observational data from the University of Delaware.

40 Figure. Winter mean (a) storm track anomalies (shading), and (b) 00-hPa geopotential height tendency induced by transient eddies (shading) associated with the EU index, obtained via a linear regression overlaid by the 00-hPa geopotential height anomalies (contour, CI=gpm) regressed onto the EU index during the HIGH epoch. (c) and (d) are the same as (a) and (b), but for the LOW epoch. Zero contours are omitted, and stippling indicates the % confidence level of shading. Storm track in (a) and (b) are estimated by the standard deviation of 0 day band-pass filtered 00-hPa geopotential height. 0 0

41 Figure 0. Climatology of the winter mean storm track estimated by the standard deviation of 0 day band-pass filtered 00hPa geopotential height. Contour intervals are 0 gpm.

42 Figure. Same as Figure, but regressed on the winter mean SST index.

43 Figure. Winter mean 00-hPa Rossby wave source anomaly (shading) associated with the EU index obtained via a linear regression during (a) the HIGH epoch, and (b) the LOW epoch. Shading intervals (SIs) are 0 - s -. Stippling indicates the % confidence level. Black boxes are the same as that in Figure a.

44 Figure. Geopotential height perturbation in the barotropic model (black contour, CI=0gpm starting from ±0gpm) in response to idealized divergence forcing (red contour, CI= 0 - s - ) over the North Atlantic using the winter mean climatology derived from (a) the HIGH epoch, and (b) the LOW epoch.

45 Figure. Same as Figure, but based on JRA- dataset.