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Meteorologische Zeitschrift, Vol. 24, No. 1, 113–118 (published online January 13, 2015)© 2015 The authors

MetZet Classic Papers

Northern Hemisphere climate variability during winter:
Looking back on the work of Felix ExnerJames W. Hurrell∗ and Clara Deser
National Center for Atmospheric Research1 , Boulder, Colorado, USA(Manuscript received January 1, 2014; in revised form April 17, 2014; accepted September 18, 2014)

Abstract
We present a brief commentary on the landmark study of Exner (1913), in which an analysis of the correlation between monthly
anomalies of “polar pressure” and sea level pressure from numerous stations around the Northern Hemisphere during winter waspresented. Exner’s analysis still stands today as an excellent description of the spatial structure of the leading pattern of atmosphericvariability over the extratropical Northern Hemisphere (NH); namely, the North Atlantic Oscillation (NAO). Moreover, Exner
provided an accurate commentary on regional changes in surface air temperature driven by NAO variability. His quantitative analysisof these aspects represented a major step forward in the history of research on NH climate variability that, prior to his study, wasprimarily qualitative.
Keywords: climate variability, North Atlantic Oscillation, science history

1 Introduction
Contemporary atmospheric and climate scientists arevery familiar with the North Atlantic Oscillation (NAO)
as the most prominent and recurrent pattern of atmospheric variability over the middle and high latitudesof the Northern Hemisphere (NH), especially during thecold season months (November–April). The NAO refers
to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one
phase to another produce large changes in the mean
wind speed and direction over the Atlantic, the heatand moisture transport between the Atlantic and theneighboring continents, and the intensity and number ofstorms, their paths, and their weather. As a result, winter weather over large regions of the NH, and especiallycontinental regions around the Atlantic Ocean, is dominated by the NAO, impacting agricultural harvests, water management, energy supply and demand, and yields
from fisheries, among many other things. It is worth noting that the original meaning of the term “oscillation” in
the NAO acronym is that of a seesaw in space rather thantime: that is, atmospheric mass “oscillates” between the
Arctic and subtropical Atlantic, while NAO variations intime are irregular (Hurrell and Deser, 2009).
As a result of such pronounced impacts, the historyof scientific research on the NAO is rich, with someof the earliest descriptions of it dating back to seafaring Scandinavians several centuries ago. As noted by
van Loon and Rogers (1978), for instance, the Danish
priest and missionary to Greenland, Hans Egede Saabye∗ Corresponding author: James W. Hurell, National Center for AtmosphericResearch, P.O. Box 3000, Boulder, CO 80307-3000, Colorado, USA, e-mail:jhurrell@ucar.edu
1

The National Center for Atmospheric Research is sponsored by the National
Science Foundation.

DOI 10.1127/metz/2015/0578(1746–1817), noted in his diary “In Greenland, all winters are severe, yet they are not alike. The Danes havenoticed that when the winter in Denmark was severe,
as we perceive it, the winter in Greenland in its manner was mild, and conversely.” This temperature seesaw between Greenland and northern Europe is one of
the classic characteristics of NAO variability, and the simultaneous, out-of-phase temperature variations it describes over regions far apart are commonly referred toas “teleconnections” in the modern meteorological literature. Teleconnections are a consequence of the transient
behavior of atmospheric planetary-scale waves, so thatanomalies in climate on monthly or seasonal time scales
typically occur over large geographic regions. Some regions may be cooler or perhaps drier than average, whileat the same time thousands of kilometers away, warmer
and wetter conditions prevail.
The increasing availability of observed temperature
measurements at stations scattered across the NH madeit possible for such spatial and temporal variations inclimate to be qualitatively described by climatologists
as early as the 19th century. Dove (1838; 1839), for instance, confirmed Saabye’s observations by investigating 60 time series from stations all over the NH. He
noted an opposition of monthly and seasonal northern
European temperature anomalies with those from partsof North America, and he further noted that east-west
variations in temperature anomalies across the NH were
often more pronounced than north-south variations.
Wanner et al. (2001), Stephenson et al. (2003),
and Luterbacher et al. (2008) provide much more
complete accounts of these, and other early, qualitative studies of NH climate variability. As they also
note, the paper by Felix Exner “Über Monatliche
Witterungsanomalien auf der Nördlichen Halbkugel im
Winter” (On Monthly Weather Anomalies in the Northern Hemisphere in Winter), published in Sitzungs-© 2015 The authors
Gebrüder Borntraeger Science Publishers, Stuttgart, www.borntraeger-cramer.com

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Meteorol. Z., 24, 2015

berichte der Kaiserl, Akademie der Wissenschaften in1913, represented a major step forward in the history ofscientific research on NH climate variability and, in particular, the NAO. A short summary of this iconic paper
appeared in Meteorologische Zeitschrift in 1914, and istranslated in this issue. Exner (1913) made use of thestatistical technique of correlation analysis, conceived
by Galton (1888) and introduced into climate researchby Sir Gilbert Walker (1909), to produce the first correlation map showing the spatial structure of the NAO.
His quantitative analysis, based mainly on a decade ofstation records of sea level pressure (SLP) and temperature from 50 stations across the NH, is remarkable inthat his findings are robust today, as we will show below. Moreover, many of the qualitative investigations ofclimate variability by Exner’s predecessors, based on visual inspections of time series, led to the identification ofmany spurious relationships between climate variables(Stephenson et al., 2003).
Felix Maria Exner (1876–1930) was a pioneer inthat he was the first to accurately depict not only thespatial structure of what we now know as the leading
pattern of atmospheric variability over the NH, but healso provided a very insightful and accurate commentaryon the role of the changing atmospheric circulation in
driving regional variations in temperature. Moreover, byapplying a lagged correlation analysis, Exner (1913)
explored the utility of his findings for forecasting. To put
Exner’s research into perspective, it is useful to briefly
examine some modern techniques for determining the
spatial structure of the NAO, as well as the impact of
NAO variability on surface climate.

2 Spatial structure of the NAO
There is no single way to “define” the NAO. One approach is through conceptually simple correlation maps
(e.g., Fig. 5 of Hurrell and Deser, 2009), much like
Exner (1913). Another technique, more often used today, is Empirical Orthogonal Function (EOF, or principal component) analysis. In this approach, the NAO is
identified from the eigenvectors of the cross-covariance(or cross-correlation) matrix, computed from the time
variations of the grid point values of SLP or some otherclimate variable. The eigenvectors, each constrained to
be spatially and temporally orthogonal to the others, arethen scaled according to the amount of total data variance they explain. This linear approach assumes preferred atmospheric circulation states come in pairs, inwhich anomalies of opposite polarity have the same spatial structure.
The NAO is the only teleconnection pattern evident
throughout the year in the NH (Wallace and Gutzler
1981; Barnston and Livezey, 1987). During the boreal winter season (defined here as December-March),when the atmosphere is most active dynamically andperturbations grow to their largest amplitudes, the NAO
accounts for more than one-third of the total variance inFigure 1: Leading empirical orthogonal function (EOF 1) of thewinter (December-March) mean sea level pressure anomalies over(top) the North Atlantic sector (20 °–70 ° N, 90 ° W-40 ° E) and (bottom) the Northern Hemisphere (20 °–90 ° N), and the percentage ofthe total variance they explain. The patterns are displayed in termsof amplitude (hPa), obtained by regressing the hemispheric sea levelpressure anomalies upon the leading standardized principal component time series. The data cover 1899–2013. The green dots inthe top panel represent the locations of Lisbon, Portugal and Stykkisholmur, Iceland used in the station based NAO index of Hurrell(1995).

SLP fluctuations from one winter to the next over the
North Atlantic (20 °–70 ° N, 90 ° W–40 ° E). In the socalled “positive phase” (depicted in Fig. 1, upper panel),higher-than-normal surface pressures south of 55 ° N
combine with a broad region of anomalously low pressure throughout the Arctic to enhance the climatological meridional pressure gradient. The largest amplitude
anomalies occur in the vicinity of Iceland and acrossMeteorol. Z., 24, 2015

J.W. Hurrell & C. Deser: Northern Hemisphere climate variability during winterthe Iberian Peninsula. The positive phase of the NAO is
associated with stronger-than-average surface westerlies
across the middle latitudes of the Atlantic onto Europe,with anomalous southerly flow over the eastern U.S. andanomalous northerly flow across the Canadian Arctic
and the Mediterranean (Hurrell, 1995), very similar tothe circulation anomalies described by Exner (1913).
A well-known shortcoming of EOF analysis, however, is that eigenvectors are mathematical constructs,
constrained by their mutual orthogonality and the maximization of variance over the entire analysis domain.
There is no guarantee, therefore, that they represent
physical modes of the climate system. Moreover, theloading values of EOFs do not reflect the local behaviorof the data: values of the same sign at two different spatial points in an EOF do not imply that those two points
are significantly correlated. This means that the pattern
structure of any particular EOF must be interpreted with
care.
These issues have been at the center of a debate overwhether or not the NAO is a regional expression of alarger-scale (hemispheric) mode of variability known as
either the NH Annular Mode (NAM) or the Arctic Oscillation (AO; see Thompson and Wallace 2000). The
NAM is defined as the first EOF of NH (20 °–90 ° N)
winter SLP data (Fig. 1, lower panel). It explains about
one-quarter of the winter-mean (December-March) variance, and it is clearly dominated by the NAO structure in
the Atlantic sector. Although there are some subtle differences from the regional pattern over the Atlantic andArctic, the main difference is larger amplitude anomalies over the North Pacific of the same sign as thoseover the Atlantic. This feature gives the NAM an almost
annular (or zonally-symmetric) structure that reflects amore hemispheric-scale meridional seesaw in SLP between polar and middle latitudes. Some have argued theNAM is a fundamental structure of NH climate variability, and that the “regional” NAO reflects the modification of the annular mode by zonally asymmetric forcings, such as topography and land-ocean temperature
contrasts. It would then follow that the annular mode
perspective is critical in order to understand the processes that give rise to NAM (or NAO) variations. For
instance, the leading wintertime pattern of variability inthe lower stratosphere is clearly annular (not shown), but
the SLP anomaly pattern that is associated with it is confined almost entirely to the Arctic and Atlantic sectors
and coincides with the spatial structure of the NAO (e.g.,
Deser, 2000).

3 Impact on surface climate
Changes in the mean atmospheric circulation patterns
over the North Atlantic associated with the NAO are accompanied by changes in the intensity and number ofstorms, their paths, and their weather (Rogers, 1997).
During winter, a well-defined storm track connects theNorth Pacific and North Atlantic basins, with maximum storm activity over both ocean basins. Positive

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Figure 2: Changes in mean winter (December-March) precipitation(mm day−1 ) associated with a plus one standard deviation departureof the NAO index, defined as the leading principal component timeseries associated with the top panel in Figure 1. The precipitation
data cover 1979 through 2013 and are from the Global Precipitation
Climatology Project (Adler et al. 2003).

NAO index winters are associated with a northeastward
shift in the Atlantic storm track with enhanced activity
from Newfoundland into northern Europe and a modest decrease in activity to the south. Positive NAO index
winters are also typified by more intense and frequent
storms in the vicinity of Iceland and the Norwegian Sea(see Fig. 12 in Hurrell and Deser, 2009).
Changes in the mean flow and storminess associatedwith swings in the NAO index are also reflected in pronounced changes in the transport and convergence of atmospheric moisture and, thus, the distribution of precipitation. Winters tend to be dry over much of central and southern Europe and northern portions of theMediterranean, whereas more precipitation than normal
falls from Iceland eastward to Scandinavia, during high
NAO index periods (Fig. 2). Weaker magnitude drying
also occurs over Greenland, the Canadian Arctic, andparts of the Middle East in association with high NAO
index winters (Fig. 2).
The NAO also exerts a dominant influence on wintertime temperatures across much of the NH (Hurrell,1995). Surface air temperature and sea surface temperature (SST) across wide regions of the North Atlantic
Ocean, North America, the Arctic, Eurasia and parts of
the Middle East are significantly correlated with NAO
variability. When the NAO index is positive, for instance, enhanced westerly flow across the North Atlantic during winter brings relatively warm (and moist)
maritime air over much of Europe and far downstream
across Asia, while stronger northerlies over Greenland
and northeastern Canada carry cold air southward anddecrease land temperatures and SST over the northwest
Atlantic (Fig. 3). Temperature variations over North
Africa and the Middle East (cooling), as well as North
America (warming), associated with the stronger clockwise flow around the subtropical Atlantic high-pressure

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Meteorol. Z., 24, 2015

Figure 4: Map of the correlation coefficients between monthly
anomalies of “polar pressure” and sea level pressure at around 50
sites of the Northern Hemisphere from 1887 to 1906 (from Exner,
1913).
Figure 3: Changes in mean winter (December-March) air temperature (°C) associated with a plus one standard deviation departureof the NAO index, defined as the leading principal component timeseries associated with top panel in Figure 1. The temperature data
cover 1980 through 2013 (Kalnay et al., 1996).

center are also notable, and were well-described by
Exner (1913).
The NAO also drives significant fluctuations in Arctic sea ice concentrations, which exhibit a seesaw in ice
extent between the Labrador and Greenland Seas. These,
as well as other impacts on surface climate and on bothhuman and natural systems across the NH, are beyond
the scope of this commentary but are described more
completely by Hurrell and Deser (2009), as well as
the many references within their paper. It is worth notingthat the NAO’s influence on surface climate may exhibit
some changes over time, as documented in Osborn et al.
(1999) and Hilmer and Jung (2000).

4 Summary and reflections on Exner(1913)
Felix Exner’s correlation map of NH SLP anomalies isreproduced in Fig. 4. It shows the correlation coefficients between monthly mean pressure anomalies at theNorth Pole and those at roughly 50 other sites acrossthe NH based on approximately one decade of measurements. The North Pole anomalies are approximatedby the mean of the anomalies of two stations: Gjesvaer(northern Norway) and Markowo (northeastern Siberia).
In his discussion of the map, Exner emphasized theannular appearance of the pattern and the strong local
signatures in the North Atlantic and Mediterranean areas. In fact, his correlation pattern closely resembles theNAO (and NAM) spatial patterns in Fig. 1, which were
found using the EOF analysis technique applied to a
gridded analysis of NH SLP data covering more than acentury (1899–2006). Exner (1913) also quite aptly described the spatial structure of the NAO-induced surface
temperature anomalies illustrated in Fig. 3. In particular, he notes “the spatial distribution of the temperature
anomalies resemble those expected if the air flow in areas with positive or negative pressure anomalies is similar to that in high- and low-pressure areas, transporting
temperature [anomalies] to other places”.
As mentioned earlier, Exner (1913) also used alagged correlation analysis in an attempt to determine
the relationships of non-simultaneous anomalies of airpressure and temperature at different stations, with implications for forecasting climate conditions a month or
longer in advance. We will not summarize his major
findings here, especially as Exner himself noted his efforts were only a preliminary attempt to identify forecast
skill and his analysis mostly illustrated that it would be“desirable to continue these attempts”.
A decade later, Walker (1923) made use of similarcorrelation techniques in an attempt to seasonally forecast the Indian summer monsoon and the flooding of
the Nile. In so doing, he grouped world weather variations into several distinct patterns and noted his “Iceland
Azores oscillation is not very closely related with thatbetween the Pacific and Indian oceans” and suggested
that “readers interested in northern relationships mustin any case read Exner’s interesting and important paper [Exner, 1913]”. Walker later termed the North Atlantic correlations the “North Atlantic Oscillation”, andhis concept of the NAO became popular among contemporary meteorologists (see Wanner et al., 2001 andStephenson et al., 2003 for further details).

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J.W. Hurrell & C. Deser: Northern Hemisphere climate variability during winter

It is furthermore noteworthy that Exner’s (1913)
pursuit of predictability continues to this day, more thana century later, motivated by the significant impact of
the NAO on the climate and ecosystems of the NH(Hurrell and Deser, 2009). While modern sciencehas established that most of the atmospheric circulation variability in the form of the NAO arises from theinternal, nonlinear dynamics of the extratropical atmosphere (Hurrell et al. 2003) and is, therefore, largely unpredictable, considerable research continues around theidea that external forces might nudge the atmosphere to
assume a high or low NAO index value over a particularmonth or season (Scaife et al., 2014). This is important,as even a small amount of predictability could be extremely useful. Moreover, one of the most urgent challenges is to advance our understanding of the interaction
between the anthropogenic rise in greenhouse gas concentrations and the NAO (IPCC 2013). Finally, while thepredictability of seasonal to interannual NAO variability will most likely remain low, some applications may
benefit from the fact that this phenomenon leaves longlasting imprints on surface conditions, in particular over
the oceans.

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