The eastern Mediterranean teleconnection pattern: identification and definition

INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 27: 727 737 (27) Published online 1 October 26 in Wiley InterScience (www.interscience.wiley.com) DOI: 1.12/joc.1429 The eastern Mediterranean teleconnection pattern: identification and definition M. Hatzaki, a H. A. Flocas, a, * D. N. Asimakopoulos a and P. Maheras b a Department of Applied Physics, Faculty of Physics, University of Athens, Greece b Department of Meteorology and Climatology, Faculty of Geology, University of Thessaloniki, Greece Abstract: In this study, an attempt is made to investigate possible teleconnection patterns of atmospheric circulation, centered over eastern Mediterranean (EM) with the aid of gridded NCEP/NCAR daily values of geopotential heights for the period 1958 23. For this purpose, two approaches have been used: correlation analysis and rotated principal component analysis (PCA) on a seasonal and monthly basis. A teleconnection pattern between the EM and northeastern Atlantic was identified at and 3 hpa in winter, which will be referred to as the Eastern Mediterranean Pattern (EMP), appearing as an independent mode of the upper circulation. The pattern also exists in autumn but is substantially weakened with its dipole centers being shifted eastwards. Significant monthly variations were found in the location, strength and structure of the pattern. The employment of a standardized index demonstrated that the negative phase of the EMP prevails throughout the year with the maximum frequency at wintertime. Copyright 26 Royal Meteorological Society KEY WORDS mediterranean; seasonal and monthly geopotential heights; teleconnection index; correlation analysis; principal component analysis Received 3 July 25; Revised 31 July 26; Accepted 17 August 26 INTRODUCTION The term teleconnection pattern refers to the statistically significant negative correlation of recurring and persistent circulation anomalies between two or more geographical areas that could be or may not be adjacent. Teleconnection patterns appear as preferred modes of low-frequency (or long timescale) natural variability of the atmospheric circulation with geographically fixed centers of action (poles). Two approaches have been used in relevant studies to define low-frequency circulation patterns: (1) the correlation method where the two (or more) poles of the pattern are characterized by the strongest negative correlations in the domain. However, this method requires considerable time of both the computer and researcher while it is not straightforward to define the most representative set of centers within the spatial coverage of the pattern or its temporal evolution and (2) rotated principal component analysis (RPCA), where the eigenvectors of the correlation matrix are individually scaled according to their contribution to the total data variance and then rotated under certain constraints to obtain the most detailed and robust teleconnection counterparts (Horel, 1981; Wallace and Gutzler, 1981; Esbensen, 1984; Blackmon et al., 1984a,b; Hsu and Wallace, 1985; Barnston * Correspondence to: H. A. Flocas, Department of Applied Physics, Faculty of Physics, Building PHYS-5, University of Athens, University campus, 157 84 Athens, Greece. E-mail: efloca@phys.uoa.gr and Livezey, 1987; Kushnir and Wallace, 1989; Kutiel and Benaroch, 22). While RPCA offers the advantage of its ability to reduce the original dataset into the fewest number of significant independent components and computational convenience compared to the previous method, it is characterized by certain constraints associated with the selection of the principal components (PCs) and their physical interpretation. The two methods yield strong correspondence when dipole or wavelike patterns are exhibited in the upper troposphere; however, RPCA is more appropriate for identifying prominent structures at sea level, which would not be evident in the correlation method (Horel, 1981; Hsu and Wallace, 1985). In previous studies (Conte et al., 1989; Hurrell, 1995; Kutiel and Benaroch, 22), differences of normalized geopotential height or mean sea level pressure anomalies at the action centers were used with the aid of station or gridded data to calculate indices in order to represent the phases and strength of the teleconnection patterns. In other studies, the teleconnection index was defined with the aid of the time series of the loadings of the pressure or geopotential Principal Component, representing the specific teleconnection pattern (Horel, 1981; Ambaum et al., 21; Ambaum and Hoskins, 22). The teleconnection indices indicate the degree to which these patterns are independent modes of atmospheric variability and allow the examination of their time variations and implications for regional climate (Esbensen, 1984; Yin, 1999; Brunetti et al., 22; Quadrelli and Wallace, 24). Copyright 26 Royal Meteorological Society

728 M. HATZAKI ET AL. Climate dynamics research has demonstrated the existence of several teleconnection patterns that affect the greater European region, such as North Atlantic Oscillation (NAO) in the lower troposphere between Iceland and the Azores (Wallace and Gutzler, 1981; Barnston and Livezey, 1987; Stephenson et al., 2; Wanner et al., 21; Hurrell et al., 23), the Eastern Atlantic pattern, as the upper air manifestation of NAO (Wallace and Gutzler, 1981; Esbensen, 1984), the Southern Europe-North Atlantic (SENA) pattern at 7 hpa (Kutiel and Kay, 1992), the Eastern Atlantic-West Russia (EAWR) Pattern at 7 hpa and 8 hpa (Barnston and Livezey, 1987; Krichak and Alpert, 25) and the North Sea-Caspian Pattern (NCP) at hpa (Kutiel and Benaroch, 22; Kutiel et al., 22). Conte et al. (1989) suggested the existence of a teleconnection pattern in the annual geopotential height fields at hpa between the eastern and western Mediterranean basin that was defined as the Mediterranean Oscillation (MO). They defined the Mediterranean Oscillation index (MOI) as the standardized geopotential height difference between Alger and Cairo. As a further evidence of the MO, Piervitali et al. (1997) and Maheras et al. (1998) demonstrated a positive trend of the hpa geopotential height in the western Mediterranean basin with an opposite sign trend in the eastern basin. Recent studies demonstrated that this oscillation is reflected in the time series of temperature and rainfall between western and EM (Kutiel and Maheras, 1998a; Kutiel and Paz, 1998b; Maheras and Kutiel, 1999; Maheras et al., 1999a,b; Douguedroit, 2). In an attempt to identify the main coupled circulation-precipitation patterns in the Mediterranean basin, Dunkeloh and Jacobeit (23) suggest the existence of the MO in addition to a Mediterranean Meridional Circulation (MMC) pattern, being defined between the British Isles and Italy in winter and spring, mainly at upper levels. On the basis of the above mentioned results, the objective of this study is to: (1) investigate the existence of any teleconnection patterns centered over the EM throughout the whole troposphere on a seasonal and monthly basis with the aid of correlation and rotated principal component analysis (PCA) and (2) further define a teleconnection index based on gridded data and examine the temporal variations of the identified patterns. In our study, the EM is defined as the region extending from the Ionian Sea to Syria (Meteorological Office, 1962). The mean annual, seasonal and monthly values for each time series were calculated. In this study, the standard definition of seasons was followed: winter (December, January and February), spring (March, April, May), summer (June, July, August) and autumn (September, October, November). Following this definition, winters were extracted for each year using the December data of the previous year. First, a linear correlation index of the mean annual, seasonal and monthly values of geopotential height was calculated between each grid point with all the others of the examined area at all isobaric levels. One-point correlation matrices were calculated, in order to investigate the existence of teleconnection patterns concerning the EM and teleconnectivity maps were plotted so that two or more poles of a potential oscillation could be identified. The calculations of the linear correlation index were initially performed in the geopotential height fields at 3 and hpa because they are less influenced by surface characteristics. Furthermore, PCA was applied to the geopotential height data at all isobaric levels on an annual, seasonal and monthly basis. This method aims to confirm the existence of patterns identified with the aid of correlation analysis. Owing to the large number of grid points of the datasets, it was not possible to apply PCA to the entire examined area (9 W 9 E, 9 N). Hence, a smaller area ( W E, 25 N 67.5 N) was used, as derived from the correlation analysis, transforming the full grid to a lower resolution grid rejecting interval points. Thus, a total of 297 grid points was used as the input variables for the PCA. In our case, the first four PCs are retained for all datasets that satisfy the empirical criterion of each component explaining more than 1% of the total variance, trying to keep the PCs with physical interpretability (Kushnir and Wallace, 1989). These PCs share 7% of the total variance, approximately. Finally, the varimax method is used for the PCs rotation (Horel, 1981) which maximizes the variance of the squared correlation coefficients between each rotated principal component and each of the original time series, thus increasing the discrimination among the loadings and making them easier to interpret (Barnston and Livezey, 1987). Also, the rotated PCs are less dependent on the domain of the analysis and their spatial patterns more closely resemble observed anomaly fields (Horel, 1981). DATA AND METHODOLOGY Datasets of daily geopotential height used in this study were obtained from the NCEP/NCAR Reanalysis Project (Kalnay et al., 1996) for the isobaric levels of the 3,, 7, 8 and 1 hpa. The datasets cover the period 1958 to 23 on a 2.5 2.5 latitude by longitude grid for the quarter-spherical window extended from 9 W to9 E and to 9 N. CORRELATION ANALYSIS RESULTS The correlation analysis of the annual geopotential values did not reveal any statistically significant negative correlation between the EM grid points and any other point in the examined area at any isobaric level (not shown). The seasonal correlation results verified the existence of the well-known patterns of NAO at 1 hpa and Eastern Atlantic Pattern at hpa throughout all seasons. Also, the NCP is demonstrated in winter, autumn Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

THE EASTERN MEDITERRANEAN TELECONNECTION PATTERN 729 and spring. However, the Correlation Analysis on a seasonal basis did not reveal the existence of any teleconnection pattern between the western and EM basin. This discrepancy can be attributed to the fact that Conte et al. (1989) identified the MO in the correlation map of the hpa mean annual geopotential heights of Alger with those of specific EM stations, while our study employed gridded mean seasonal and monthly values on a 2.5 longitude by 2.5 latitude grid. Our finding is consistent with Kutiel and Benaroch (22), who also used gridded mean monthly geopotential height data, but on a coarser 1 1 grid. Also, it should be noted that the time period of our analysis may not be sufficiently long enough to identify the MO, which appears with a periodicity of 22 years (Palutikof et al., 1996). Therefore, it is suggested that the MO might not appear as an independent mode of the large-scale circulation at upper levels, but rather as a predominant pattern linked to Mediterranean precipitation and temperature variability, as shown by many previous studies (e.g. Maheras et al., 1999b; Brunetti et al., 22; Dunkeloh and Jacobeit, 23). Instead, a pattern between the EM and northeastern Atlantic was identified in the correlation matrices. This pattern was predominantly identified in the upper troposphere, in winter with negative correlations of.62 to.67. More specifically, at the isobaric level of hpa, a maximum negative correlation (teleconnectivity center) was found between 25 W, 52.5 N in the northeastern Atlantic and 22.5 E, 32.5 N in the EM. Figure 1(a) represents the teleconnectivity between the two areas, as derived from the one-point correlation map of the EM center. At 3 hpa, two corresponding closed maxima are formed in each region, at the grid points 17.5 W, 55 N and 2 W, N and at 27.5 E, 35 N and 17,5 E, 3 N, respectively. In Figure 1(b), the solid and the dashed lines represent the two dipoles as allocated from the one-point correlation maps. This teleconnection pattern will hereafter be referred to as the Eastern Mediterranean pattern (EMP). At lower levels, the analysis demonstrated that the pattern develops at 7 hpa as well (Figure 2(c) and (f)), but weakened, while it is not evident at 8 hpa or 1 hpa (not shown). This fact suggests the role of upper level dynamics in the development of the pattern. Moreover, topography and the land-sea distribution seem to contribute to the pattern s weakening in the lower troposphere, since they greatly determine the surface pressure distribution. This is further supported by the fact that the northern center located over the sea extends downwards to the surface while the southern center located over a topographically complex region- vanishes at lower levels (not shown). Wallace and Gutzler (1981) demonstrated that the regional scale patterns dominated the correlation patterns in the upper troposphere, contrasting the global scale patterns that are most clearly defined at sea level. During autumn, the pattern exists only at upper levels with substantially weaker correlations and with the northern pole shifted eastwards over central Europe (Figure 2(d) and (f)). In spring, the EMP still exists at upper levels but it is very weak (the correlations are not statistically significant). In summer, the pattern completely vanishes. Although this cold season predominance of the EM pattern has to be further explored in terms of large-scale dynamics, previous studies suggest that this could be related to jet stream dynamics and Rossby wave dispersion (Hoskins and Karoly, 1981; Blackmon et al., 1984b; Kushnir and Wallace, 1989). From the correlation analysis of the geopotential fields on a monthly basis, remarkable intermonthly differences were found in the position and strength of the EMP at upper levels. More specifically, the pattern does 3hPa 3 2 - - - -3-2 -1 1 2 3 65 hpa 55 45 35 25 15 - - - -3-2 -1 1 2 3 Figure 1. Teleconnectivity map for winter geopotential height values at (a) 3 hpa and (b) hpa. Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

73 M. HATZAKI ET AL. 8 8 2 2 2 a. winter_3 hpa 8 2 2 2 d. autumn_3 hpa 8 2 2 2 2 b. winter_ hpa 8 2 2 e. autumn_ hpa 8 2 2 2 2 c. winter_7 hpa 2 2 f. autumn_7 hpa Figure 2. One-point correlation maps of seasonal geopotential height at 7, and 3 hpa exhibiting the EMP in (a) (c) winter (d) (f) autumn. not exist from May to September, since no significant negative correlation was found between the two regions. The pattern seems to form in October and November and strengthens in December. In January, it weakens significantly while it reinforces in February, persisting until April. This point will be further explored in the next section. ROTATED PRINCIPAL COMPONENT ANALYSIS RESULTS In winter at the isobaric level of hpa, the first component explains 26.7% of the total variance while the other three represent 22%, 15.7% and 12%, respectively. The spatial pattern associated with the first PC (Figure 3(a)) is virtually identical to the pattern shown in Figure 1(a). Hence, the EMP, as identified previously with the aid of correlation analysis, has been objectively substantiated using RPCA, although the northern pole has shifted westwards. The second component reveals a pattern corresponding with the NCP (Figure 3(b)). The third component seems to form the EA pattern, although its two centers are marginally captured in the examined area (Figure 3(c)). The fourth component resembles the East Atlantic/West Russian pattern (Krichak and Alpert, 25) or Eurasia-2 pattern (Barnston and Livezey, 1987). Of interest is to note that none of the four factors bear any relation to the MO pattern, further confirming the correlation analysis results. The same analysis at 3 hpa in winter showed that the EMP forms as the second component (Figure 4). The first component emerges in the EA; the NCP is represented by the third component while the forth component reveals the East Atlantic/West Russia pattern. The total variance explained by each factor is 25%, 24%, 15.5% and 11%, respectively. In autumn, the produced hpa and 3 hpa circulation pattern of the fourth component reveals two weak poles representing the EMP (not shown). The dipole centers are found very close to the teleconnectivity centers of Figure 2(b). Consistent with the correlation analysis at all isobaric levels, the RPCA for spring and summer did not elucidate the EMP as one of the four components. It should be mentioned that similar application of RCPA on the isobaric temperature fields revealed a similar pattern of EMP in the temperature field at hpa and 3 hpa with its poles slightly shifted (not shown). Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

THE EASTERN MEDITERRANEAN TELECONNECTION PATTERN 731 -.3 -.5 -.7 -.1.1.3.5.7.1.1 -.3 -.1 -.7 -.5.1.3..7 3 (a) PC1 3 (b) PC2 - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3.2.5.8.5 -.2 -.4 -.2.6.4.2 3 (c) PC3 3 (d) PC4 - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3 Figure 3. The four principal components produced from RPCA using seasonal geopotential values at hpa in winter..2.4.6.8.6.4.2 -.3 -.7 -.5 -.1.1.3.5.7 3 (a) PC1 3 (b) PC2 - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3.1 -.1 -.5 -.3.1.3.5.7.2.4.2 -.2 -.4 3 (c) PC3 3 (d) PC4 - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3 Figure 4. As in Figure 3 but for 3 hpa. Figure 5 displays the principal components as produced from the RPCA of the hpa monthly average values that best represent the EMP. It can be seen that these results support the corresponding correlation analysis results. The EMP exhibits a pronounced monthly variation in its location, structure and strength. More specifically, it emerges from October to April while it does not exist in the other months. In December (Figure 5(a)), EMP forms as the second PC appearing with the greatest similarity with the winter version (Figure 3(a)), with a total variance of 19.5%. In January (Figure 5(b)), it is verified that the pattern is weak, as it is marginally recognizable in the fourth component. The February EMP mode (Figure 5(c)) is mixed with the NCP, with its dipole centers being shifted eastwards (second component with 21% of total variance). In March (Figure 5(d)) the pattern weakens, as suggested by the loadings, while in April it still appears but with the Mediterranean pole located over the Balkan Peninsula as part of the EA pattern (Figure 5(e)). After the summer period, in October (Figure 5(f)) the pattern starts to form as a mixed version of NCP, resembling the structure of the autumn pattern with a weak Mediterranean pole. In November, the EMP appears as a part of the Eastern Atlantic pattern with the southern pole extending over the Mediterranean region (Figure 5(g)). INDEX DEFINITION Intending to examine the intensity and temporal changes of the identified EMP and to further investigate its relationship with the large-scale circulation and other, mainly European, teleconnections, a corresponding index Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

732 M. HATZAKI ET AL. -.6 -.8 -.4 -.2.2.4.2 -.2.2..6 3 (a) December PC2 TV:19.4% 3 (b) January PC4 TV:113% - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3.1 -.1 -.3 -.5.1.3..7 3 (c) February PC2 TV:v21.3% - - - -3-2 -1 1 2 3 -.3 -.5 -.3 -.1.1.3.5.7 -.5 -.3 -.1 -.3 -.7 -.5.1.3 3 (d) March PC4 TV: 13.4% 3 (e) April PC2 TV: 13% - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3.6.4.2 -.2 -.4 -.6 -.4.2.4 -.8 -.6 -.4 -.6 -.2.2.4 3 (f) October PC2 TV: 21% 3 (g) November PC3 TV: 13.5% - - - -3-2 -1 1 2 3 - - - -3-2 -1 1 2 3 Figure 5. The EMP as represented in the results of RPCA at hpa using monthly data: (a) December (PC 2) (b) January (PC 4) (c) February (PC 2) (d) March (PC 4) (e) April (PC 2), (f) October (PC 2) (g) November (PC 3). The annotated percentage on each month indicates the explained variance of each principal component. should be determined based on the exact position of two base points, representing the centers of dipole pattern. In this attempt, the results of both the correlation and RPCA analyses at hpa were taken into account to appropriately catch the dynamic variability of the pattern throughout the year. Barnston and Livezey (1987) have demonstrated that the rotated patterns, characterized by very high correlation with their teleconnection counterparts, are robust. The selection of the two base points was based on the following criteria: first, the two base points should have high negative correlation in winter, as derived from the one-point correlation maps (Figure 1). Second, the selected points should be located within the dipole centers identified by the RCPA of the seasonal values (Figure 3). Third, the selected points should account for intermonthly variations in the position and structure of the pattern, as derived by the monthly results of the RPCA. It should be noted that the sensitivity of the index calculation on the considered number of neighboring grids defining each pole was examined and it was verified that the index values are only marginally affected if the mean geopotential height value of two or more adjacent grids is considered at each base point. Finally, the EMP index (EMPI) was defined as follows: EMPI = gpm(25 W, 52.5 N) gpm(22.5 E, 32.5 N) (1) where gpm is the mean monthly geopotential height of the grid point representing each pole. From Figure 6, it can be clearly seen that the values of the winterstandardized anomalies between the two poles are reversed, verifying the existence of a seesaw pattern. In general, an intense positive anomaly of one pole is accompanied by a corresponding negative anomaly of the other. The index was then calculated for each season and for each month and standardized as follows: the difference between the index defined above and its seasonal longterm average divided by its standard deviation: z i = (EMPI i EMPI )/σ (2) Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

THE EASTERN MEDITERRANEAN TELECONNECTION PATTERN 733 3 2 1 1958 1961 1964 1967 197 1973 1976 1979 1982 1985 1988 1991 1994 1997 2 23-1 -2-3 atlantic pole eastern med pole Figure 6. Interannual variations of the winter-standardized geopotential heights anomalies of the dipole centers during the examined period. 3 2 1 1958 1961 1964 1967 197 1973 1976 1979 1982 1985 1988 1991 1994 1997 2 23-1 -2-3 EMP index PC1 scores Figure 7. Interannual variation of the standardized EMPI winter values (solid line) and the scores of the first PC at hpa (dashed line) during the examined period. where the EMPI is the index value of the year i, and EMPI is its long-term average and σ the corresponding standard deviation for the period 1958 23. In order to differentiate the two situations, the Negative and the Positive Phase of the EMP are defined when z i.5 andz i.5, respectively. This value was selected after comparing the interannual variations of the winterstandardized index during the examined period with those of the scores of the first principal component at hpa representing the EMP (Figure 3). From Figure 7, which displays the interannual variation of the two datasets, an excellent consistency in the variability of the two datasets is noticeable since their correlation coefficient is.86 and the peaks of the same sign coincide. Moreover, this figure demonstrates that the value z =.5 helps to adequately discriminate the exceptional cases from the normal ones and to classify a considerable number of exceptional cases in each phase allowing for their statistical analysis. More specifically, the Positive Phase indicates that the EMPI value is greater than the mean index value, EMPI, suggesting that the difference between the geopotential heights of the two centers is diminished, while during the negative phase this difference is increased, taking into account that the geopotential heights of the northern pole are naturally lower than the heights of the southern pole (Jacobeit et al., 21). Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

-.6 734 M. HATZAKI ET AL. 8 -.2 -.8 -.22 -.2 -.4 -.2 -.2 -.8 -.2 -.14 -.8 -.2.4 2.4.4 (a) negative phase - mean state -8 - - -2 2 8 8 -.2 -.8.2 -.2.6.1.14.18.22.2.6.1.2 -.22 -.2.6.2 -.2 2 -.2 (b) postive phase - mean state -8 - - -2 2 8 Figure 8. (a) Differences of the geopotential heights standardized anomalies between the negative phase and the mean state at hpa, (b) as in Figure 8(a) but for the positive phase. Figure 8 displays the standardized anomalies of hpa geopotential during the positive and the negative phase of the EMP. It can be seen that during the negative phase (Figure 8(a)) a strong negative anomaly prevails over the NW Atlantic, characterized by increased cyclonic (counterclockwise) circulation. On the other hand, a shallow positive anomaly forms over the EM and northern Africa, implying clockwise circulation around it. This pattern causes an increased southwesterly anomaly flow toward the central Mediterranean and strong westerlies across the middle Atlantic. On the contrary, the positive phase is characterized by a strong anticyclonic anomaly over the NW Atlantic, associated with the intensification of the Atlantic anticyclone and warm air advection, while a cyclonic anomaly predominates over the EM (Figure 8(b)). This pattern establishes a northerly anomaly flow toward the central Mediterranean along with cold air advection over central Europe. Therefore, it is suggested that the negative (positive) phase is associated with increased zonal (meridional) circulation over Europe. In order to examine the relationship of the EMP with other known teleconnection patterns that affect the greater European area, the seasonal and monthly correlation coefficients of the EMPI with the following indices were calculated: (1) NAO (Northern Atlantic Oscillation) index, which is defined as the normalized sea level pressure difference between the Azores and Iceland (Hurrell et al., 23) b) MOI, which is defined as the difference of normalized geopotential height anomalies at hpa between Alger and Cairo (Conte et al., 1989), (c) North Sea-Caspian Pattern Index (NCPI), as defined by Kutiel et al. (22) (d) Mediterranean Circulation Index (MCI), defined as the normalized sea level pressure between Marseille and Jerusalem (Brunetti et al., 22). It was found that the EMPI showed almost zero correlation coefficients with the NAO index and the MOI. A significant but weak correlation (.36) was found in winter between the EMPI and the NCPI, while the two indices were found to be uncorrelated on a monthly basis. A positive correlation of.5 was found in winter between the EMPI and the MCI, indicating a relationship of the EMP with a surface dipole behavior between the northwestern Mediterranean and the southeastern Mediterranean, due to the southern EMP pole rather than to its northern one that occasionally Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

THE EASTERN MEDITERRANEAN TELECONNECTION PATTERN 735 % 38% 36% 34% 32% 3% 28% 26% 24% 22% 2% Oct Nov Dec Jan Feb Mar Apr negative positive Figure 9. Relative frequency of positive and negative phases in the months October April during the examined period. covers part of northwestern Mediterranean. Therefore, it is suggested that the EMP may form as an independent mode that is not part of the known teleconnection patterns. The EMP is consistent with the seesaw temperature regime that forms as a MO (Maheras et al., 1999b) and agrees with the upper circulation within the two phases of the EMP: cooling over the EM when anomalous midtropospheric northerly air and warming under anomalous southerly flow are observed. The positive EMP phase is in accordance with the seesaw of hpa and 7 hpa temperatures between NW Europe and North Africa, as demonstrated by Lolis and Bartzokas (21), which is attributed to the prevalence of high-pressure systems over central Europe causing positive temperature anomalies over NW Europe and negative anomalies over N. Africa (Metaxas et al., 1993). Also, it is consistent with the enhanced frequency of the northerly flow over Greece (Feidas et al., 24), while contributing to an increase in precipitation over the EM (Kutiel and Paz, 1998b; Dunkeloh and Jacobeit, 23). Figure 9 displays the percentage of the negative and positive phases for each month throughout the whole examined period. It can be seen that the number of negative phases prevails during all months, except for March when the number of positive phases is slightly larger. The predominance of negative phases in winter is associated with the intense zonal circulation prevailing over Europe, being linked to a large latitudinal geopotential height difference (Jacobeit et al., 21). On the contrary, the maximum frequency of the Positive Phase in March is a result of the meridional circulation which dominates over the Mediterranean in spring when Saharan depressions are generated (Prezerakos, 199), which lead to low geopotential heights over this area. In October, the two phases appear with the same frequency. The greatest number of negative phases appears in December while the number of positive phases does not change significantly from month to month. The difference between the frequencies of the two phases is enhanced during winter, peaks in February, but decreases during the spring and autumn months, following the difference of the latitudinal geopotential height difference between the two centers of the pattern. The predominance of the EMP negative phase is consistent with the increase of the frequency of the anticyclonic types at hpa over Greece (Maheras et al., 24), the tropospheric warming over Greece (Feidas et al., 24), and the weakening of the trough over the central Mediterranean during the last two decades resulting in a precipitation decrease over the EM (Dunkeloh and Jacobeit, 23; Maheras et al., 24). According to Figure 7 there are significant interannual variations of mean winter values of the standardized EMPI, but no obvious trend is present. Commonly, a year being assigned to a negative or positive phase is followed by a normal year while there are consecutive years being characterized by the same sign phase. Peak positive (negative) values appear in April and July (October). Low index values form in the mid-197s and 198s, while the maximum value is reached in 1981. Furthermore, the interannual variations of the EMPI confirm the occurrence of extreme years in terms of precipitation or temperature: the exceptional peak of the positive EMPI in 1992 is in accordance with an extremely cold year in Greece (Flocas et al., 25; Feidas et al., 24) while a large negative EMPI value appears in 1994 which is depicted as an extremely warm year (Feidas et al., 24). Also, the maximum value of 1981 seems to be associated with the extreme annual rainfall reported over western Turkey for this year (Türkes, 1996). CONCLUSIONS In this study an attempt is made to investigate possible teleconnection patterns of atmospheric circulation throughout the troposphere centered over the EM, using both correlation and rotated PCA on a seasonal and monthly basis. The following conclusions were deduced: Both approaches revealed clearly and consistently the existence of the dipole pattern between the EM and the northeastern Atlantic at upper levels, and is referred to as the EMP on the seasonal and monthly scales. Copyright 26 Royal Meteorological Society Int. J. Climatol. 27: 727 737 (27) DOI: 1.12/joc

736 M. HATZAKI ET AL. The EMP identified at and 3 hpa in winter, weakens at 7 hpa while it does not exist at lower levels. Furthermore, the upper level pattern weakens in spring, fades away in summer and returns in autumn. Both approaches demonstrated that the EMP exhibits a pronounced intermonthly variation in its location, structure and strength. The pattern emerges from October to April while it does not exist in the other months. In December, the pattern seems to intensify and form as an independent circulation mode. In the other months, it forms as a mixed version of the EA and NCP patterns or with weak signal. The negative and positive phases of the EMP were discriminated with the aid of a standardized index. It was found that the number of negative phases prevail during all months, except in March and October, while the greatest frequency difference between the two phases is observed in winter months. During the negative phase of the pattern, an increased zonal flow is established over the European region. On the contrary, the positive phase is characterized by an intensification of the Atlantic anticyclone resulting in increased meridional flow of northerly component toward the central Mediterranean. The EMP appears as an independent circulation mode without any relationship with the NAO and MO. A considerable relationship between the EMPI and the surface MCI was found which is probably related to the southern EMP pole. The development of the EMP seems to explain trends of the upper level circulation changes over the EM while supporting the formation of sea level pressure anomalies directly related to certain temperature and precipitation regimes over the EM. The identification of EMP is considered important for climate research in the Mediterranean, since the EMP, as an independent mode of upper level circulation, contributes to Mediterranean climate variability. The degree of this contribution should be further assessed. Thus, the results of previous studies examining the temperature and precipitation regime over Mediterranean regions in relation to large-scale circulation should be reconsidered. Further work will include investigation of the dynamics responsible for the formation of the EMP. Furthermore, the impact of the EMP on the EM climate will be examined using datasets representing the present and future climate conditions. In this attempt, the definition of the EMP index and the discrimination of negative and positive phases will prove very important. ACKNOWLEDGEMENTS This work is funded by the State Scholarships Foundation of Greece through the scholarship of the Ph.D. student M. Hatzaki. REFERENCES Ambaum MHP, Hoskins BJ. 22. The NAO troposphere-stratosphere connection. Journal of Climate 15: 1969 1978, DOI: 1.1175/152-442. Ambaum MHP, Hoskis BJ, Stephenson DB. 21. Arctic Oscillation or North Atlantic Oscillation? 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