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North Atlantic Storm Track Variability and Its Association to the North Atlantic Oscillation and Climate Variability of Northern Europe

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North Atlantic Storm Track Variability and Its Association to the North Atlantic Oscillation and Climate Variability of Northern Europe JULY 1997 ROGERS 1635 North Atlantic Storm Track Variability and Its Association to the North Atlantic Oscillation and Climate Variability of Northern Europe JEFFREY C. ROGERS Department of Geography, Ohio State University, Columbus, Ohio (Manuscript received 8 January 1996, in ®nal form 4 November 1996) ABSTRACT The primary mode of North Atlantic storm track variability is identi®ed using rotated principal component analysis (RPCA) on monthly ®elds of root-mean-squares of daily high-pass ®ltered (2±8-day periods) sea level pressures (SLP) for winters (December±February) 1900±92. It is examined in terms of its association with 1) monthly mean SLP ®elds, 2) regional low-frequency teleconnections, and 3) the seesaw in winter temperatures between Greenland and northern Europe. The principal storm track component is characterized by high synoptic variability preferring one of two areas at any given time. The northeastern Atlantic center (identi®ed by positive RPCA scores) is characterized by deep cyclones in the area extending from Iceland northeastward to the Nor- wegian and Barents Seas, whereas the Bay of Biscay center (negative scores) is linked to cyclone activity around that area and into the Mediterranean basin. Combined principal component analysis is used to link the high- frequency storm track pressure variability with that of lower frequencies (monthly mean pressures). In this, the primary storm track pattern is linked to large monthly mean SLP variations around the Bay of Biscay and near northern Scandinavia and the Barents Sea. This pattern does not suggest a strong storm track link to the North Atlantic Oscillation (NAO). Instead, the results presented indicate that the dominant mode of variability in the storm track is associated with low-frequency SLP anomalies in the extreme northeastern Atlantic. When the component scores reach their highest positive values, both the mean Atlantic subpolar low and subtropical high are unusually strong and displaced farther northeast than normal. The pressure ®eld intensi®es to the northeast and produces strong zonal ¯ow extending into Europe, bringing abnormally high surface air temperatures as far east as Siberia and below normal temperatures over Greenland and northern Africa (the ``Greenland below'' seesaw mode, GB). Besides this eastward extension of the mean pressure ®eld, anomalously high European winter temperatures can also be somewhat less frequently caused by mild return ¯ow around the Siberian high, which is displaced farther west than normal. In this situation the Icelandic low is in its normal Denmark Strait location and cyclones move along the more southerly storm track toward the Mediterranean basin, contributing to the synoptic forcing that helps develop the westward extended high. The NAO appears to be only indirectly linked to the European component of the GB mode of the winter surface air temperature seesaw. 1. Introduction tion and is linked to observed climatological and ocean- ographic variability (van Loon and Rogers 1978; Lamb Climate variability associated with changes in inten- and Peppler 1987; Moses et al. 1987; Mann and Drink- sity and location of storm tracks has not been studied water 1994; Hurrell 1995). There are, however, other to as great an extent as that associated with low-fre- Atlantic regional teleconnections, including the west At- quency components of the circulation such as standing lantic and east Atlantic patterns, identi®ed at the 500-mb waves (van Loon and Williams 1976; Shabbar et al. level (Wallace and Gutzler 1981); the NAO; east At- 1990), blocking ¯ows (Rex 1951; Namias 1964, 1978; lantic and Eurasian patterns at 700 mb (Barnston and Dickson and Namias 1976; Lejenas 1989), and atmo- Livezey 1987); and three additional sea level pressure spheric teleconnection patterns. The latter constitute a patterns beside the NAO (Rogers 1990). set of slowly varying circulation features that retain their It is well established that synoptic-scale eddy activity identities on monthly charts, each having speci®c spatial is largest downstream of the major stationary wave centers of action. In the lower troposphere over the troughs. For example, the amplitudes of the variance North Atlantic, the North Atlantic Oscillation (NAO) is statistics of bandpass ®ltered (2.5±6-day periods) typically regarded as the primary regional teleconnec- 500-mb heights are characterized by zonally elongated maxima extending across the western ocean basins from the east coasts of North America and Asia, representing areas of high temporal variability in geopotential heights Corresponding author address: Dr. Jeffrey C. Rogers, Depart- ment of Geography, Ohio State University, Columbus, OH 43210- and preferred trajectories of weather systems (Blackmon 1361. et al. 1977; Blackmon et al. 1984). Cai and Van den E-mail: [email protected] Dool (1991) demonstrate that storm tracks also occur q1997 American Meteorological Society Unauthenticated | Downloaded 09/26/21 02:59 AM UTC 1636 JOURNAL OF CLIMATE VOLUME 10 ahead of troughs associated with traveling low-fre- in the pure sense. Serreze's (1995) automated cyclone quency waves. These waves are associated with monthly detection and cyclone tracking algorithm represents an averaged circulation anomalies that are frequently as- improvement on trajectory methods and is used on sociated with modes of speci®c teleconnection patterns. twice-daily gridded National Meteorological Center Lau (1988) showed that teleconnection patterns found (NMC, now known as the National Centers for Envi- in monthly time averages are linked to storm tracks. For ronmental Prediction) analyses in order to examine cli- example, he linked large latitudinal/meridional displace- matological characteristics of cyclones and their trajec- ments in the easternmost or downstream portion of the tories. Lau (1988) identi®es storm track modes by ap- Atlantic 500-mb storm track to the east Atlantic tele- plying empirical orthogonal function (EOF) analysis of connection pattern, while baroclinic activity in the west- the monthly root-mean-square statistics of bandpass ernmost or upstream portion of the storm track is linked (2.5±6 day) ®ltered twice-daily 500-mb geopotential to the west Atlantic pattern. heights. The unique patterns in the variance statistics Relatively few papers have addressed how storm track represent a simple way to evaluate storm tracks, in- variability is associated with regional variability of cli- volving fewer arbitrary decisions than traditional tra- mate, as measured by monthly mean ®elds of surface jectory (manual) methods (Wallace et al. 1988), but cre- air temperature, precipitation, and pressure. This may ating proxies of the cyclone tracks (Anderson and Gyak- partly be due to dif®culty in applying cyclone frequency um 1989) that do not identify individual cyclone and and trajectory datasets, and interpreting results from anticyclone centers as might be required when diag- them, and due to an emphasis on monthly mean cir- nosing instantaneous weather conditions. Wallace et al. culation anomalies in studies of climate variability. The (1988) point out that both cyclones and anticyclones are recent development of automated cyclone tracking al- associated with the maxima in the bandpass ®ltered pres- gorithms (Serreze 1995) and the use of second-moment sure ®eld variances. Although the usage of ``storm statistics of pressures ®ltered over synoptic timescales tracks'' is somewhat misleading in describing the prod- (Lau 1988) has helped focus interest on the role of storm uct of variance methodologies, the isolated patterns have tracks in climate variability. For example, Rogers and been found to closely match those found by manual Mosley-Thompson (1995) link recent increases in storm methods. Hence, in this study, the phrase ``storm track'' activity in the Barents and Kara Seas to unusually mild refers to high-frequency ¯uctuations in the ®ltered pres- winters of the 1980s in Siberia, and Serreze et al. (1997) sure ®elds rather than to the trajectory of individual examine the synoptic characteristics associated with the cyclones. mean Icelandic low and recent atmospheric circulation changes. 2. Data and methodology The purpose of this paper is 1) to identify the primary mode of Atlantic storm track variability, 2) to show how Northern Hemisphere gridded daily and monthly it is related to low-frequency teleconnections, and 3) to mean sea level pressure (SLP) data are used. The data relate it to regional climate variability in northern Eu- are available at every 58 of latitude and longitude from rope and elsewhere. The paper argues for a new inter- 208 to 858N for the period November 1899±March 1992. pretation of how atmospheric circulation variability is Gridded maps are available once daily for either 1300Z linked to a well-known regional climatic phenomenonÐ (from 1899 to 1939) or 1200 UTC and are available the seesaw in winter air temperatures between Green- twice daily (0000 and 1200 UTC) from 1955±56 land and northern Europe. The air temperature seesaw through 1959±60 and for all winters starting with 1962± was ®rst qualitatively linked to the North Atlantic Os- 63. Daily maps are missing from December 1944±De- cillation by van Loon and Rogers (1978, hereafter vLR), cember 1945, but monthly charts are available for cal- and the assumed linkage has often been repeated. The endar year 1945. Other than this 13-month period, miss- Atlantic storm track and its long-term variability is ex- ing daily data were replaced by pressure averages of the amined with a historical sea level pressure dataset ex- day prior and the day after. The different SLP data tending back to 1899. The analysis is performed (see sources are listed in Table 1 of Trenberth and Paolino section 2) so as to obtain both a spatial representation (1980), who extensively examine the monthly SLP data of the storm track pattern plus a long-term temporal for errors, inhomogeneities, trends, and discontinuities. index of the strength and polarity of the storm track. Monthly mean surface air temperature data on a 58 The storm tracks are also analyzed in conjunction with lat 3 108 long grid (Jones et al.
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