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INTERNATIONAL JOURNAL OF CLIMATOLOGY 

Int. J. Climatol. 23: 615–629 (2003) 

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.903 

SPRING NORTHWARD RETREAT OF EURASIAN SNOW COVER RELEVANT 

TO SEASONAL AND INTERANNUAL VARIATIONS OF ATMOSPHERIC 

CIRCULATION 

HIROAKI UEDA, a, * MASATO SHINODA b and HIROTAKA KAMAHORI c 

a Institute of Geoscience, University of Tsukuba, Tsukuba, Ibaraki 305-8571, Japan 

b Department of Geography, Tokyo Metropolitan University, Tokyo, 192-0364 Japan 

c Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan 

Received 6 November 2002 

Revised 8 February 2003 

Accepted 11 February 2003 

ABSTRACT 

An observational study is made of the seasonal and interannual variations of spring snow-disappearance over the Eurasian 

continent and the circulation mechanisms causing those variations. The spring northward retreat of the snow boundary 

over the East European Plain (EEP) between 30 and 60 °E is faster (0.4° per day) than to the east of the Ural Mountain 

range (0.3° per day). These migrations of the snow boundary lag behind the appearance of the surface air temperature 

0 °C by about 1 to 5 pentads. 

The analyses of the atmospheric heat and moisture budgets showed that the seasonal intrusion of warm air associated 

with southwesterly winds is primarily responsible for the rapid snowmelt in March and April over the EEP. In addition, 

the adiabatic heating of descending air plays a secondary role in the snowmelt in mid-March. On an interannual time 

scale, horizontal warm advection also plays an essential role in the spring northward retreat of snow cover extent. 

The present study confirms the previous finding that the surface air temperature anomalies, produced during the seasonal 

snow-disappearance period, diminished in May, suggesting a weak dynamical linkage between the EEP snow cover and 

Asian summer monsoon. Copyright © 2003 Royal Meteorological Society. 

KEY WORDS: land surface process; Eurasia; snow boundary; snowmelt; ENSO-monsoon 

1. INTRODUCTION 

The monsoon is a major climatic phenomenon affecting agriculture and socio-economic activities for a large 

number of people who live in Asia. With this regard, the interannual variations of the monsoon have been 

a major topic among the region’s climatologists and meteorologists. On an interannual time scale, it has 

been speculated for over a century that snow–monsoon interaction over the Eurasian continent modulates the 

year-to-year changes in summer monsoon rainfall and circulation. Since the first suggestion of the inverse 

relationship between the snow cover in the Himalayas and subsequent Indian monsoon (Blanford, 1884), 

there have been numerous observational studies focusing on the interaction between the strength of the Asian 

summer monsoon and Eurasian snow cover during the cold season of the Northern Hemisphere (Hahn and 

Shukla, 1976; Dickson, 1984; Banzai and Shukla, 1999). The atmospheric response to changes in snow cover 

has been well established through general circulation model (GCM) studies. Barnett et al. (1989) were one of 

the first to study the snow–monsoon relationship. They indicated that heavy (light) Eurasian snow led to weak 

(strong) monsoon precipitation through hydrological feedbacks in addition to the albedo effect. During the last 

decade, several GCM studies have been conducted to examine the snow–monsoon relations (e.g. Vernekar 

* Correspondence to: Hiroaki Ueda, Institute of Geoscience, University of Tsukuba, Tsukuba, Ibaraki 305–8571, Japan; 

e-mail: hueda@kankyo.envr.tsukuba.ac.jp 

Copyright © 2003 Royal Meteorological Society

616 H. UEDA, M. SHINODA AND H. KAMAHORI 

et al., 1995, Douville and Royer, 1996). Yasunari et al. (1991) also found that the albedo effect dominated 

in the spring to reduce surface heating over the Tibetan Plateau. However, in summer, the albedo effect 

disappeared and excess water due to snowmelt caused the surface to cool, particularly at mid-latitudes. On 

the other hand, GCM experiments of Zwiers (1993) showed that the snow–monsoon relationship was weak. 

Recently, it has been found that the precursory land surface signals on an interannual time scale are not strong 

enough to determine the intensity of the broad-scale summer monsoon activities through GCM experiments 

(Shen et al., 1998) and observational studies (Shinoda, 2001; Shinoda et al., 2001). Although, Liu and Yanai 

(2001) showed that the springtime tropospheric temperature anomalies over the Eurasian continent positively 

correlate with the subsequent summer monsoon activity, they indicated that the temperature anomalies are 

mostly independent from those of the land surface conditions. 

Given the potential importance of the interannual variation of snow cover to the monsoon strength, it is no 

surprise that there have been many efforts to understand the extent of snow cover and its possible influence 

on the atmosphere. In contrast, there have been few studies that focus on the physical processes regulating 

the snow cover itself. 

Furthermore, it should be noted here that the results from the analyses of snow and ice charts data, 

produced by the National Oceanic and Atmospheric Administration’s (NOAA’s) National Environment 

Satellite Data and Information Service (NESDIS; e.g. Hahn and Shukla, 1976), include uncertainties in 

determining areal snow coverage due to cloud contamination. As pointed out by Shinoda et al. (2001), there 

are considerable differences between the NOAA/NESDIS satellite data and ground-based snow depth data 

observations. However, relatively little documentation of snow-depth climatology and its physical process has 

been conducted until now. Thus, before discussing the snow–monsoon relationship, it is vital to reveal the 

snow-disappearance mechanism during the spring and early summer. 

On a decadal time scale, it is found that the snow extent for the spring season has exhibited a marked 

decreasing trend over central Eurasia during recent decades, in conjunction with global warming (Folland 

et al., 2001). In this context, the circulation mechanisms causing the snow cover variations should also be 

examined. The snow depth data used here consist of long-term observations, providing an opportunity to 

explore the decadal-scale changes. 

Therefore, the purpose of this study is first to reveal the climatological features of the spring snowdisappearance 

based on in situ snow depth data, and second to relate these features to the atmospheric 

circulation based on an objective analysis. These analyses are conducted on the time scale of a pentad 

to detect abrupt changes that often occur during the spring (Shinoda et al., 2001). Third, we investigate 

year-to-year variations in the snow mass in relation to the atmospheric circulation. 

2. DATA 

The dataset utilized in this study comprises the daily station data of snow depth, surface temperature 

and precipitation for the former Soviet Union (FSU), archived by the All Union Research Institute of 

Hydrometeorological Information in Obninsk for the period between 1966 and 1990. This dataset is the 

same as used in Shinoda et al. (2001) and Shinoda (2001). The total number of stations consists of 223 points 

covering the Eurasian continent broadly from 20 °E through to 140 °E north of 40 °N except for Mongolia and 

the northern part of China (see Figure 1). Because of a number of missing observations, the data after 1990 

are not used in the present analysis. The observations are made to 1 cm accuracies for the snow depth, 1 °C 

for the temperature and 1 mm for the precipitation. 

Also used are twice-daily (0000 and 1200 GMT) European Centre for Medium Range Weather Forecasts 

(ECMWF) reanalysis data between 1980 and 1990. The data contain horizontal winds (u, v), temperature T 

and vertical p-velocity ω defined at every 2.5° longitude by 2.5° latitude grid point over 17 vertical levels 

from 1000 to 10 hPa. Since the purpose of the present study is to reveal the detailed seasonal change process, 

we have used 5-day (pentad) averaged data for the analysis. 

Copyright © 2003 Royal Meteorological Society Int. J. Climatol. 23: 615–629 (2003)

EURASIAN SNOW COVER AND ATMOSPHERIC CIRCULATION 617 

Figure 1. Spatial distributions of climatological (a) snow-disappearance pentads, and (b) surface temperature of 0 °C between 1966 and 

1990. 223 observation stations are denoted by filled circles. Light shaded regions indicate April, and dark shaded regions correspond 

to May 

3. SNOW DISAPPEARANCE AND WARM ADVECTION 

To illustrate the seasonal changes in snow cover and its association with surface temperature, we present 

climatological pentad numbers for the snow disappearance timing and appearance of the surface air 

temperature 0 °C (Figure 1). Generally, the East Eurasian Plain (EEP) is lower than 200 m, except for the 



Ural mountain range, whereas Mongolia and the adjacent area are characterized by high elevation in excess 

of 1000 m. In this study, we masked out these highly elevated regions in Figure 1. The snow begins to 

disappear from the southwestern part of the FSU and migrates in a northerly direction until May. Glancing 

at this figure, it is clear that the northward retreat is not zonally uniform. The advance of the snow boundary 

exhibits an abrupt change in April over the EEP between 50 and 60 °N. This region corresponds to the location 

that reveals high interannual variability of snow depth and a negative correlation with the Indian summer 

monsoon rainfall (Kripalani and Kulkarni, 1999; Shinoda et al., 2001). One can notice that the northward 

migration of the 0 °C isotherm (Figure 1(b)) precedes that of snow-disappearance (Figure 1(a)) by about 1 to 

5 pentads. The surface air temperature exceeds 0 °C widely between 50–60 °N over the EEP in late March 

(pentads 17 and 18). This is followed by the wide disappearance of the snow in April. 

As described previously, we regard the EEP as the significant key region for which land surface processes 

may influence the monsoon activity. Figure 2(a) displays the latitude–time sections of surface air temperature 

averaged over the longitudes over 30–60 °E. Also superimposed are the snow-disappearance pentads, denoted 

as a dashed line. In general, the snow disappearance lags behind the 0 °C isotherm by about 1 to 5 pentads. 

The rapid surface warming between late March and April seems to be closely associated with atmospheric 

circulation, as is seen in Figure 2(b). This figure shows the same section but for 850 hPa winds. Throughout 

the winter to spring season, westerly winds dominate over the EEP. As for the meridional wind, the southerly 

wind intrusion during March and April is concurrent with the abrupt surface warming seen in Figure 2(a). In 

order to investigate the stability of the atmospheric vertical profile, we have calculated the vertical gradient 

of potential temperature θ between 850 and 700 hPa. The computation was performed using the following 

formula: 

γ = (θ700 − θ850) 

(Z700 − Z850) 

This parameter is a useful indicator for the stability of the boundary layer associated with the snow cover, 

as was proposed by Shinoda et al. (2001). The smaller values of γ less than 4.5 K km −1 , associated with 

an unstable boundary layer, are found to occur during mid March (>55 °N) and April. The atmosphere 

becomes more unstable with regard to stratification nearer the summer season, which might be attributed to 

surface heating. 

Figure 3 provides a description of the monthly mean atmospheric circulation from March to May. The 

wind vectors at 850 hPa are plotted with the mean vertical gradient of potential temperature (shaded areas) 

to indicate conditional instability in the lower troposphere. During March, the northwesterly winds prevail 

to the east of 60 °E, where the vertical θ differences are larger (>5.0). In contrast, the northern part of the 

EEP between 30 and 60 °E is under the influence of southwesterlies. At this time, the vertical profile θ over 

the northern part of the EEP exhibits a more unstable condition (γ < 5), which may be caused by low-level 

warm advection due to the southwesterly winds. The small γ is also found for April to the south of 50 °N 

and for May to the south of 60 °N, which may be attributed to a land surface effect resulting from the snow 

disappearance. Of particular interest in May is that the southwesterlies over the EEP become weak and the 

westerlies to the east of 60 °E are replaced by vigorous northwesterly winds. 

Figure 4 shows the seasonal change of the large-scale vertical circulation averaged over the 30–60 °E 

meridians between March and May. The shaded area denotes southerly winds stronger than 1 m s −1 . During 

March, the northward intrusion of lower winds with an upward component can be found between the surface 

and 700 hPa over 55–70 °N. There appears to be only weak motions in the middle and upper troposphere. 

By April, the region to the south of 50 °N is dominated by southerly winds up to 200 hPa, and the area to the 

north of 50 °N is replaced by northerly winds. It should be emphasized here that the southerly wind intrusion 

is remarkable in spring, particularly in March and April, and the winds gradually retreat southward toward 

the summer season. 

Copyright © 2003 Royal Meteorological Society Int. J. Climatol. 23: 615–629 (2003) 

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Figure 2. Latitude–time sections showing (a) mean (1966–90) seasonal evolution of the surface temperature (degrees Celsius) 

along a longitude of 30–60 °E. Thick black contour indicates surface temperature 0 °C. The dashed contour denotes climatological 

snow-disappearance pentads. (b) The same as in (a), except for 850 hPa horizontal wind obtained from ECMWF reanalysis (1980–90). 

The southerly wind component greater than 1 m s −1 is denoted by two-tone shadings. (c) The same as in (a), but for static stability γ 

between 850 and 700 hPa. Shading is region of γ less than 5.0 K km −1 



Figure 3. Monthly mean distributions of horizontal wind vector at 850 hPa and static stability γ between 850 and 700 hPa. Shaded area 

denotes the region of γ less than 5.0 K km −1 



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40N 45N 50N 55N 60N 65N 70N 

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Figure 4. The 11-year mean (1980–90) pressure–latitude sections of meridional and vertical wind fields along a longitudinal sector 

averaged over 30–60 °E for (a) March, (b) April and (c) May. The shaded regions are southerly wind components greater than 1 m s −1 



4.1. Seasonal evolution 

4. MEAN HEAT AND MOISTURE BUDGETS 

To examine more quantitatively the heating and moisture processes relevant to the snow disappearance 

over the EEP, we examine the atmospheric heat and moisture budgets. The advective, diabatic, and adiabatic 

heating estimates are obtained by the thermodynamic and moisture balance equations from a 12 h sequence 

of upper air data: 

∂T 

∂t 

∂q 

∂t 

 

RT 

= −V ·∇T + ω 

cpP 

∂q Q2 

= −V ·∇q − ω − 

∂p Lc 

 

∂T 

− + 

∂p 

Q1 

Cp 

where T is temperature, q is the mixing ratio of water vapour, V is the horizontal wind, ω is the vertical 

p-velocity, cp is the specific heat for dry air, and Lc the latent heat of condensation. Q1 and Q2 are called 

the apparent heat source and moisture sink respectively, because of possible contributions resulting from 

unresolved eddies associated with dry thermal convection and moist convection (Yanai et al., 1973). 

As shown by Yanai et al. (1973), vertically integrating Equations (2) and (3) from the tropopause pressure 

PT to the surface pressure Ps, we obtain 

where 

〈Q1〉 = 〈QR〉 + LcP + S (4) 

〈Q2〉 = Lc(P − E) (5) 

〈〉 = 1 

g 

Ps 

PT 

() dp (6) 

P, S, E and QR are respectively the precipitation rate, the sensible heat flux, the evaporation rate per unit 

area at the surface and the radiative heating rate. 

We compare the horizontal advection, vertical advection, and adiabatic heating terms averaged over the 

key region (30–60 °E, 45–60 °N) (Figure 5(a)). We recognize that the local warming over the EEP in March 

and April (thin solid line) is indeed the result of horizontal (meridional plus zonal) warm advection by 

southwesterly winds and, particularly in mid March, the adiabatic warming by descending air contributes, 

in part, to the local temperature increase. Then, the horizontal warm advection tends to decrease toward the 

summer season. The time series of the 〈Q1〉 and 〈Q2〉 (as expressed in Equations (2) and (3)) reveal drastic 

seasonal changes during April–May of the snow-disappearance timing (Figure 5). Prior to this period, a large 

amplitude of negative 〈Q1〉 is manifested during March through to early April, in conjunction with the course 

of marked snowmelt (Shinoda, 2001; Shinoda et al., 2001). This fact indicates that the heat, gained through the 

above-mentioned horizontal warm advection and adiabatic process, is largely used for the snowmelt through 

the sensible heat flux included in 〈Q1〉 (see Equation (4)). Aizen (2000) also pointed out that the advective 

energy is the same as the heat used for snowmelt in a central area of the EEP during early April, which 

coincides with our results. Their estimates of the heat consumed for snowmelt have amplitudes comparable 

to our 〈Q1〉 values. The EEP region reveals a moisture sink (a positive 〈Q2〉) between winter and the end 

of April, indicating snowfall. 〈Q2〉 values abruptly turn to negative from early May, which is concurrent 

with the enhanced surface evaporation, as will be found in Figure 7. The moisture advection terms changed 

in conjunction with those of the heat budget. Namely, the large meridional transport of water vapour is 

recognizable in April, whereas it decreases abruptly in May. These variations are closely associated with the 

northward advection of warm and moist air in April and the southward intrusion of cold and dry air in May. 

Copyright © 2003 Royal Meteorological Society Int. J. Climatol. 23: 615–629 (2003) 

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(3)

a) 

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0 

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b) 

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-10 

JAN 

JAN 


FEB MAR APR MAY JUN 

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[Wm -2 ] 

Q2 

zonal adv 

meridional adv 

adiabatic 

local change 

5 10 15 20 

pentad number 

Q1 

zonal adv 

meridional adv 

adiabatic 

local change 

25 30 35 


25 30 35 

Figure 5. Climatological (1980–90) time series of atmospheric vertically integrated (a) heat and (b) moisture budgets for the EEP 

(45–60 °N, 30–60 °E) in units of W m −2 . Diabatic heat source (Q1; thick line), zonal heat advection (−u∇T ; open circles), meridional 

heat advection (−v∇T ; filled circles), vertical advection plus adiabatic compression (ω∇T − ωRT /Cpp; dashed line) and local time 

change (∂T /∂t thin line) are shown. Moisture sink (Q2), zonal moisture advection (−u∇q; open circles), meridional moisture advection 

(−v∇q; filled circles), vertical moisture advection (ω∂q/∂p; dashed line) and local time change (∂q/∂t; thin line) are shown 

4.2. Vertical cross-sections 

Figure 6(a) shows the mean vertical distribution of the heating rate Q1/cp in the latitudinal plane along 

30–60 °E. Over the EEP region, an apparent cooling is dominant in the lower troposphere below 700 hPa, 

which is compensated by the advection heating (Figures, 6(b) and (c)) as well as the adiabatic heating 



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40N 45N 50N 55N 60N 65N 70N 

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Figure 6. North–south vertical cross-sections during March and April over the EEP (30–60 °E) showing (a) heating rate (Q1/cp), (b) 

zonal advection, (c) meridional advection and (d) adiabatic component 



(Figure 6(d)). This heat balance was also observed in the time series of each component (Figure 5). The 

zonal (eastward) advection is a main component for the heating north of 60 °N, whereas the meridional 

(northward) advection is a dominant player south of 60 °N, including the key area in the EEP (Figure 5). 

These features are consistent with the atmospheric circulation fields (see Figure 4). 

We can also estimate the vertically integrated values of 〈LcE〉 as residuals of surface precipitation 〈LcP 〉 

minus 〈Q2〉 (see Equation (5)). Figure 7 shows the time series of calculated values of 〈LcE〉 and observed 

〈LcP 〉 for the key region. The estimated evaporation is relatively small in winter and gradually increases from 

April toward the summer season. Interestingly, the evaporation begins to exceed the precipitation in early 

May, following the snow-disappearance period over the EEP region. This suggests that the increased 〈LcE〉 

may reflect the wet soil conditions due to the addition of the melting snow. Recently, Suzuki et al. (1998) 

estimated the evaporation and vegetation activity over western Siberia (50–60 °N, 60–80E). They found that 

the evaporation increased abruptly from May toward the subsequent summer after snow disappearance. The 

absolute values of the evaporation are also consistent with our computed values. 

5. INTERANNUAL VARIATION 

Figure 8 shows the interannual variation of the snow-disappearance pentad for the key region between 

1966 and 1990. Positive values mean late snow-disappearance and negative values indicate early snowdisappearance. 

To reveal its spatial variations, we produced the map of differences in snow-disappearance 

timing in Figure 9. In this figure, large positive values are roughly located north of the Black Sea, around 

50 °N. There are also remarkable differences over the EEP region, whereas these signals are not found over 

the entire Eurasian continent. Shinoda et al. (2001) indicated that the year-to-year variations of snow field 

contain a mode having anomalies of opposite signs between the EEP and Siberian regions. 

To examine the relationship between the land surface conditions and snow boundaries in view of the 

interannual and seasonal time scales, the time–latitude section of the surface air temperature differences 

is displayed in Figure 10. We also superimposed the snow boundary lines for the early and late snowdisappearance 

years. In general, the surface temperature was lower between December and April for the late 

snow-disappearance years. Interestingly, this signal abruptly diminished in May and there was no remarkable 

difference during the summer season. This result is consistent with recent studies (Shen et al., 1998; Shinoda, 

2001; Shinoda et al., 2001). The surface air temperature anomalies prior to March are related to the snowmelting 

speeds and subsequent snow-disappearance timings. On the other hand, the temperature differences 

in April may be due, in part, to the land-surface conditions of snow cover or non-snow-cover. Another 

[Wm -2 ] 

E, P 

JAN 

80 

70 

60 

50 

40 

30 

20 

10 

0 

45-60N, 30-60E 

climate 


E(Era15) 

P(USSR) 

5 10 15 20 25 30 35 

pentad number 

Figure 7. Time series of estimated evaporation (solid line) and precipitation (dashed line) for the EEP (45–60 °N, 30–60 °E) 



pentad 

1.5 

0.0 

-1.5 

Snow-disappearance Pentads 

66 67 68 69 70 71 72 73 74 75 76 77 78 79 

year 

anomaly (45-60N, 30-60E) 

80 81 82 83 84 85 86 87 88 89 90 

Figure 8. Year-to-year variations of snow-disappearance pentads anomalies for the EEP (45–60 °N, 30–60 °E) 

Figure 9. Composite difference of snow boundary between late-disappearance years (1979, 1980, 1987) minus early disappearance years 

(1975, 1983, 1990). Positive (negative) values mean slow (rapid) northward retreat of snow-cover extent 

interesting feature in Figure 10 is that differences of surface temperature between the extreme years are 

absent in February and early March, whereas they are much enhanced in mid winter and in late March and 

April. This might suggest a periodicity of atmospheric circulation patterns across the continent that may 

be associated with seasonal change of the so-called North Atlantic oscillation (Portis et al., 2001) or other 

atmospheric teleconnection patterns. 

In order to confirm the atmospheric conditions relevant to early snow-disappearance, we present the 

composite differences of vertically integrated meridional advection during March and April (Figure 11). Larger 

heating anomalies can be found to the northeast of the Black sea. This pattern resembles those found in the 

horizontal (meridional plus zonal) advection (not shown) and wind fields (Figure 3(a) and (b)). These results 



Figure 10. Latitude–time section of composite anomalies of the surface temperature between late years (1979, 1980, 1987) years minus 

early years (1975, 1983, 1990). Solid (dashed) line denotes poleward retreat of snow boundary for late (early) years. Light (dark) 

shading indicates temperature anomaly below −4 °C (−8 °C) 

Figure 11. Composite anomaly of vertical integrated meridional advection (W m −2 ) for March and April between late years (1979, 

1980, 1987) minus early years (1975, 1983, 1990) 

suggest that the enhanced advection of warm southwesterly air in the lower troposphere during the snowdecreasing 

phase of March and April is an important factor for the regulation of snow-disappearance timing. 

6. CONCLUSIONS AND DISCUSSIONS 

The seasonal and interannual features of snow-disappearance timing over the Eurasian continent and its 

relation to the surface temperature were investigated by using station data for the FSU between 1966 and 



1990. In addition to this, the heat and moisture budgets were computed by use of twice-daily ECMWF 

reanalysis data for the period of 1980–90. The major results of the present study are summarized as follows: 

1. The springtime northward retreat of the snow boundary is about 0.4° in latitude per day over the EEP 

(30–60 °E), whereas the migrating speed is slower east of the Ural mountain range, at about 0.3° per 

day. The northward retreat of the snow boundary takes place following the appearance of surface air 

temperature 0 °C. In particular, the surface air temperature increases abruptly over the EEP during March. 

The northward shift of the 0 °C isotherm is very rapid in late March and early April, and is approximately 

1.0° in latitude per day. 

2. A pronounced northward intrusion of southwesterly winds in the lower troposphere occurs during March 

and April over the EEP region. Later in spring, the northwesterly winds in the lower troposphere replaced 

the southwesterlies and dominated north of 60 °N. The diabatic heating Ql over the northern part of the EEP 

(north of 60 °N) is characterized by a cooling concentrated in the lower layer. This is mainly compensated 

by the zonal warm advection due to westerlies and the adiabatic warming relevant to descending air. On 

the other hand, the southern part of the EEP is under the strong influence of meridional warm air advection. 

This warm advection nearly balances with the negative Ql, having a peak value of −0.8 K day −1 in the 

lower troposphere. 

3. The atmospheric moisture budget analyses showed that the evaporation began to exceed the condensation 

from early May, following the snow disappearance. 

4. The precursory signal of surface temperature anomalies can be found from December and persists until 

April, whereas the surface temperature anomalies diminish abruptly in May. It is worth noting that there 

are no significant anomalies in the subsequent summer. As for the atmospheric circulation for the early 

snow-disappearance years, the low-level warm air advection is enhanced during the snow-melting phase 

of March and April. 

The potentially important land–air interaction in the Eurasian continent has not been properly monitored 

and simulated by a coupled atmosphere–land model. In particular, the processes regulating the interannual 

variation of snow-cover extent and its connection with the previous tropospheric circulation have not been 

studied in detail. With this background in mind, the present study revealed that the winter–spring circulation 

(including the northward warm advection) anomalies control the spring snow-disappearance timing, and 

surface air temperature anomalies were attenuated as soon as snow-cover anomalies disappeared. This fact 

supports the previous findings that the land-surface anomalies over the study area might not be dynamically 

linked with the Indian monsoon activity (Shinoda, 2001; Shinoda et al., 2001). 

El Niño–southern oscillation (ENSO) has a vigorous impact on the change of mid-latitude westerly regimes 

(Yasunari and Seki, 1992). If the interannual variation of the snow-cover extent is closely linked to the 

tropospheric circulation, the modulation of the westerly jet due to the ENSO phenomenon may change the 

summer monsoon activity through land–atmosphere interaction. However, this snow–monsoon connection 

was not confirmed in the present study. On the other hand, many studies have shown that ocean–atmosphere 

interactions over the Indian Ocean play a significant role in the interannual variations of the Asian summer 

monsoon activities (e.g. Meehl, 1997; Kawamura, 1998). Recently, Kawamura et al. (2001) have revealed that 

the baroclinic Rossby wave response to tropical convective heating over the Indian Ocean, associated with 

ENSO, is found in the changes of tropospheric temperature over central Asia. This finding implies another 

mechanism regulating the Asian summer monsoon activity. Finally, it should be noted here that the station 

data for the FSU in the 1990s are not available at present. This decade exhibited some of the earliest snow 

disappearance of snow cover over the past century (Folland et al. 2001). Much research is needed in this area 

to further our understanding of the dynamics of snow-related thermal and hydrological processes and their 

relations to the westerly regimes and monsoon variability. 

ACKNOWLEDGEMENTS 

We would like to thank Masatake E. Hori for helpful discussions, and thank the reviewers for constructive 

comments and suggestions. Most of the figures are made using the GMT System (Wessel and Smith, 1991). 



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