GEOPHYSICAL RESEARCH LETTERS, VOL. 30, NO. 19, 1977, doi:10.1029/2003GL018103, 2003

NAO impact towards the springtime snow disappearance in thewestern Eurasian continent
M. E. Hori
Institute of Geoscience, University of Tsukuba, Ibaraki, JapanT. Yasunari
Hydrospheric Atmospheric Research Center, Nagoya University, Aichi, Japan
Received 6 July 2003; revised 2 August 2003; accepted 2 September 2003; published 3 October 2003.

[1] The atmospheric control over the disappearance ofsnow in western Eurasia and its relationship to the North
Atlantic Oscillation (NAO) are investigated. While the
NAO has a strong effect on the lower tropospherictemperature in the region, its ability to force control overthe snow extent is confined to western Europe in January
and February. Successive composite differences and heatbudget analysis reveals a northeastward propagation ofsnow cover anomaly maintained by an anomalous zonal heatadvection related to the NAO from January to March, andthe intrusion of warm climatological southerly maintaining
INDEX TERMS: 3309
the snow anomaly until April.
Meteorology and Atmospheric Dynamics: Climatology (1620);
3319 Meteorology and Atmospheric Dynamics: Generalcirculation; 3322 Meteorology and Atmospheric Dynamics: Land/
atmosphere interactions. Citation: Hori, M. E., and T. Yasunari,
NAO impact towards the springtime snow disappearance in thewestern Eurasian continent, Geophys. Res. Lett., 30(19), 1977,
doi:10.1029/2003GL018103, 2003.

1. Introduction[2] Interannual variations and the seasonal predictabilityof monsoon activity has been of great interest to researchers
and local population of the monsoon region alike, due to its
large social-economical impact.
[3] While many explanations regarding the source ofmonsoon interannual variability have been given, it is wellrecognized that the wintertime snow cover over the Eurasian continent has a strong negative correlation with thesubsequent Indian monsoon rainfall (IMR) thus being agood predictor [Hahn and Shukla, 1976]. Bamzai andShukla [1999] showed that such correlation is createdprimarily by the variations in snow extent over western
Europe during winter (Dec. – Mar.), and in eastern Europe
during spring (Apr. – May). This negative correlation has
grown stronger since the 1970s and can be related to thewintertime lower tropospheric temperature variability in theregion [Chang et al., 2001; Liu and Yanai, 2002].
[4] On the other hand, Clark et al. [1999] have shownthat the snow extent in this particular region is subject tostrong influence by the North Atlantic Oscillation (NAO).
The NAO is characterized by a strong barotropic dipole
structure of pressure/height centered over the Atlantic basin.
Particular importance of NAO is its dominant strength in thewintertime atmospheric variability and its relation to therecent positive temperature trend in the Eurasian continent[Hurrell, 1996].
[5] Robock et al. [2003] have shown that correlations
between DJF-averaged NAO and two-month running averaged snow extent produces a seasonal change similar to thatreported by Bamzai and Shukla [1999]. Their result shows anegative snow cover anomaly which progresses eastward
from winter to spring. Saito and Cohen [2003] have also
shown a lag-lead correlation between the AO/NAO variability and Eurasian snow cover which shows an atmosphere leading correlation originating in January persisting
through to the following spring.
[6] However, it should be noted that atmospheric variability such as the NAO has a relatively short memory inmonthly time scale, and since snow disappears within 2 – 3
weeks [Ueda et al., 2003], the timing is crucial of when andwhere such atmospheric signals can be imprinted on thesurface snow cover.
[7] The objective of this study is to investigate the sourceof the strong seasonal correlation between the NAO and thesnow extent, and how an anomalous snow extent persists
through the following months.

2. Data[8] Two types of snow cover data are used throughout
this research. The NOAA/NESDIS & CPC northern hemisphere snow cover data is used for the period of 1973 – 2002
following the methods of Gutzler and Rosen [1992].
[9] In addition, we use the 10-day mean snow depth datafrom the Former Soviet Union Hydrological Snow Surveys[Krenke, 1998]. 705 stations from 20° through 60°E and
35° through 70°N are used from 1966 to 1990. Data after
1990 is not used due to a reduction in the number ofstations.
[10] Also, daily averaged geopotential height and temperature field and omega velocity from the NCEP/NCAR
reanalysis [Kalnay et al., 1996] are used for 1973 –2002.
[11] The NAO index based on a long-term normalized
pressure difference between Gibraltar and Iceland provided
by the Climate Research Unit is also used [Jones et al.,
1997; Osborn et al., 1999].

3. Results[12] To illustrate the impact of the NAO towards snow
extent, we begin by presenting the composite difference of

Copyright 2003 by the American Geophysical Union.
0094-8276/03/2003GL018103$05.00

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HORI AND YASUNARI: NAO IMPACT TOWARDS SNOW DISAPPEARANCE
Table 1. Cross Correlation of Monthly NAO Index and NIRAveraged Snow Cover for December Through February
NAO Index
NIR Snow

Dec

Jan

Feb

Dec
Jan
Feb

0.37
0.17
0.11

0.16
0.69
0.32

0.10
0.37
0.79

Bold types denotes a statically 95% significant correlation based on a
two-tailed Student’s t-test. All timeseries are normalized prior to taking thecorrelation.

Figure 1. (a) Composite difference of the January surface
temperature for 14 positive NAO years and 7 negative
years. Units in °C. The region of light (dark) shades
corresponds to 95% (99%) confidence level. Thick dashed(thick solid) line denotes the zero degree line for positive(negative) NAO composites respectively. (b) Climatological
January snow cover frequency (shading) and snow depth(circles).
January surface temperature for 14 years with January NAO
index exceeding 1.0 and 7 years below the 1.0 thresholdin (Figure 1a). Light and dark shading corresponds todifferences occurring less than 5% and 1% by chance, basedon Monte-Carlo test of 1000 random composite differences.
Also, the composite zero-degree line for high (low) NAO
years is shown in thick dashed (thick solid) line.
[13] Significant positive temperature difference can beseen across western Eurasia, with the center of strong
warming located around 30°E, 55°N. However, an areawith sub-zero temperature in the low NAO years and abovezero temperature in the high NAO years is confined to anarea around 5 – 15°E, 48– 52°N.
[14] In this region, the persistence of snow and precipitation phase will be greatly affected by the NAO signature, whereas an above-zero temperature accompanying
high NAO events favor a short persistent snow coverand precipitation consisting mainly of rain instead of snow
and vice versa for the low NAO events [Clark et al.,1999]. Presence of snow cover in this region may also
have a local effect towards the surface temperature favoring such persistence of snow [Walsh et al., 1985; Shinoda
et al., 2001]. Whereas in the warming center, the climatological feature reveals a temperature below 10°C andnot even a strong warming accompanying a positive NAO
phase could overcome the zero-degree threshold. We
define this region excluding the ocean grids as the NAO

Impact Region (NIR) where the atmosphere controls thepersistence of snow.
[15] The frequency and depth of snow cover for the
climatological January from 1972 – 2002 are shown in(Figure 1b). NIR, denoted by an area surrounded by a thickdashed line, lies mostly in an area where large interannual
snow cover variability can be seen.
[16] An equivalent figure for December (not shown)shows that the NIR is primarily in the same western
European region but with a reduced area due to smaller
influence of the NAO on the surface temperature than thatin January. The equivalent figure for February (not shown)shows that the NIR shares most areas with that of Januarywith similar underlying snow variability. This resemblanceis due to similarity in climatological features between
January and February.
[17] Table 1 shows the lag-lead correlation for the NAO
index and NIR-averaged snow cover. Simultaneous correlation in January and February is significant which isconsistent with the findings of Saito and Cohen [2003].
Considering the weak correlation between January NAO
and February NAO (0.12), atmospheric control over NIR
snow cover can occur in either January or February.
[18] In this study, the following lag composite analysis isbased on January to study a long-lasting snow cover anomaly.
[19] A timeseries of the January NAO index and NIRaveraged snow cover frequency are shown in Figure 2. It
can be seen that the strength of correlation shown in Table 1
comes mostly from the late 1970s and 1980s where negative
NAO was accompanied by a large snow cover over the NIR,
and a deficit in snow cover during the early 1990s when the
NAO was positive.

Figure 2. Timeseries of the January NAO index and snow
cover frequency averaged over the NIR. The positive andnegative extreme NAO year are shown with shaded circles.
Thick dashed line denotes the climatological snow cover
over the NIR.

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Figure 3. (a) Composite difference of snow cover frequency (shading) and snow depth (circles) for 14 positive NAO
years and 7 negative NAO years. Plots were made only for differences exceeding the 95% confidence level. An orange(white) circle is plotted for significant positive (negative) difference in snow depth. Thick red line shows the climatologicalzero-degree line. (b) same as in (a) except for a lag composite difference in following February. (c) same as in (b) except forfollowing March. (d) same as in (b) except for following April.
[20] To investigate the persistence of NAO signature on
the snow cover, a lag composite difference based on
January with high or low NAO is shown in Figure 3.
Here, the shading corresponds to a rate of frequencychange in satellite detected snow cover and circles thechange in snow depth. In January, a strong negative
difference in snow cover and snow depth centered aroundthe NIR extends well eastward of the climatological zerodegree line, which marks the disappearance of snow inthe positive NAO. In the subsequent February, significant
snow differences propagating northeastwards can be seenin the snow depth, but not as clear in the satellite-derived
snow cover which represents a change in larger area ofsnow.
[21] The progression of this signal can be seen in thefollowing March and April and was consistent with thefindings of Bamzai and Shukla [1999] and Robock et al.
[2003]. It should be noted that there is no difference in thesnow depth during January in the region where negative
signals will be seen in April. This shows that the northeastward propagation of snow extent anomaly is sensitive to theJanuary snow extent over the NIR region and not the excess
or deficit in snow mass in the region.
[22] A quantitative heat budget analysis was conducted to
explore the maintenance of such seasonal progression
following the methods used by Tanaka and Milkovich[1990].
[23] The thermal advection, adiabatic expansion or contraction, and residual term (mainly radiation) were calculated using a daily atmospheric dataset, and were is mass
integrated for 1000hPa through 100hPa and monthly
averaged.
[24] The climatological surface wind and lag composite
difference for the advective heating term based on high or
low January NAO years is shown in Figure 4. The adiabatic
term was found to be small throughout January to April

Figure 4. (a) A composite difference of January throughFebruary heat budget analysis. The dark (light) shadingwith white contours corresponds to positive (negative)
advection. Contour interval is 20 W/m2. Vectors denote theclimatological surface wind. Grids with wind speed
exceeding 1 m/s are plotted. (b) Same as in (a) but for
February through March.

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HORI AND YASUNARI: NAO IMPACT TOWARDS SNOW DISAPPEARANCE

composites, and is not shown on the figure. During January
through February, advective heating due to NAO induced
westerly anomaly is present in western Europe, corresponding
to the snow cover difference in (Figures 3a and 3b).
[25] While anomalous westerlies are weak during March,
the onset of warm climatological southerly over central
Europe around 35°E, 55°N [Ueda et al., 2003], gives astrong (weak) southwesterly feature above the region ofsnow cover anomaly in (Figure 3c) on high (low) NAO
cases, which corresponds to the heat advection anomaly
feature in (Figure 4b). Heat advection anomaly is weakduring April (not shown), and the snow cover anomaly
signals caused in the previous months are carried mainly by
the intrusion of warm southerly.

4. Discussion and Conclusions[26] Lag composite difference has been used to demonstrate the atmospheric regulation of snow extent over thewestern Eurasia.
[27] The strong coupling of the NAO and snow extent
during January and February is confined to a relatively
small area centered in Western Europe. This region isclosely related to the area used in the study of Chang etal. [2001], where a recent strong correlation between the
IMR and the temperature of western Eurasia was noted.
[28] Strong persistence of wintertime NAO signature into
the following season was responsible for the northeastward
propagation of snow cover anomaly from January to April,which was found in both a satellite-derived snow cover chart
and in situ measurements of snow depth. Heat budget
analysis reveals that anomalous zonal heat advection
centered n western Europe is mostly responsible for maintaining the snow cover anomaly from January to February.
While such anomalous heat advection is weak during March,
the onset of climatological warm southerly is sufficient incarrying the snow cover anomaly from March to April.
[29] While the result strongly supports the findings of
Robock et al. [2003], it was also found that the progress of
this signal is not a result of continental scale excess/deficit
in snow mass as hypothesized in several model experiments[Barnett et al., 1989; Yasunari et al., 1991; Vernekar et al.,
1995].
[30] It should be noted that such a seasonal march insnow cover can occur with regards to the January NAO
signature alone, and does not require the following Indian
monsoon rainfall to be in a particular state. The signal ofdisappearance of snow in western Eurasia rapidly diminishes by April [Ueda et al., 2003], and soil moisturesignature is probably not an efficient carrier of climatic
signals for the following season [Shinoda, 2001].
[31] However, snow extent may have a vital role inregulating the circulation pattern which gives backgroundfor the monsoon [Yasunari and Seki, 1992]; thus further
analysis of the effect of an anomalous snow extent on the
monsoon is required.
[32] Acknowledgments. The authors would like to thank Dr. Fujio
Kimura and Dr. Hiroaki Ueda for their helpful discussions. The reviewers

provided valuable comments and suggestions. Figures in this article are
made by the Generic Mapping Tools [Wessel and Smith, 1991].

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M. E. Hori, Institute of Geoscience, University of Tsukuba, 1-1-1
Tennoudai, Tsukuba City, Ibaraki, 305-0001, Japan. (mhori@kankyo.envr.
tsukuba.ac.jp)
T. Yasunari, Hydrospheric Atmospheric Research Center, Nagoya
University, Chikusa-ku, Nagoya City, Aichi, 464-8601, Japan. (yasunari@ihas.nagoya-u.ac.jp)