trends in aerosol optical depth in the russian arctic and their links with synoptic climatology

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Science of the Total Environm

Trends in aerosol optical depth in the Russian Arctic and their

links with synoptic climatology

Maria Shahgedanova*, Mikhail Lamakin

Department of Geography, The University of Reading, Whiteknights, P.O. Box 227, Reading RG6 6AB, UK

Received 25 November 2003; received in revised form 10 August 2004; accepted 2 September 2004

Abstract

Temporal and spatial variability of aerosol optical depth (AOD) are examined using observations of direct solar radiation in

the Eurasian Arctic for 1940–1990. AOD is estimated using empirical methods for 14 stations located between 66.28N and

80.68N, from the Kara Sea to the Chukchi Sea. While AOD exhibits a well-known springtime maximum and summertime

minimum at all stations, atmospheric turbidity is higher in spring in the western (Kara–Laptev) part of the Eurasian Arctic.

Between June and August, the eastern (East Siberian–Chukchi) sector experiences higher transparency than the western part.

A statistically significant positive trend in AOD was observed in the Kara–Laptev sector between the late 1950s and the

early 1980s predominantly in spring when pollution-derived aerosol dominates the Arctic atmosphere but not in the eastern

sector. Although all stations are remote, those with positive trends are located closer to the anthropogenic sources of air

pollution. By contrast, a widespread decline in AOD was observed between 1982 and 1990 in the eastern Arctic in spring but

was limited to two sites in the western Arctic. These results suggest that the post-1982 decline in anthropogenic emissions in

Europe and the former Soviet Union has had a limited effect on aerosol load in the Arctic. The post-1982 negative trends in

AOD in summer, when marine aerosol is present in the atmosphere, were more common in the west.

The relationships between AOD and atmospheric circulation are examined using a synoptic climatology approach. In spring,

AOD depends primarily on the strength and direction of air flow. Thus strong westerly and northerly flows result in low AOD

values in the East Siberian–Chukchi sector. By contrast, strong southerly flow associated with the passage of depressions results

in high AOD in the Kara–Laptev sector and trajectory analysis points to the contribution of industrial regions of the sub-Arctic.

In summer, low pressure gradient or anticyclonic conditions result in high atmospheric turbidity. The frequency of this weather

type has declined significantly since the early 1980s in the Kara–Laptev sector, which partly explains the decline in summer

AOD values.

D 2004 Elsevier B.V. All rights reserved.

Keywords: Aerosol optical depth; Air pollution; Trends; Climatic variability; Synoptic climatology; Arctic

0048-9697/$ - s

doi:10.1016/j.sc

* Correspondi

E-mail addr

ent 341 (2005) 133 –148

ee front matter D 2004 Elsevier B.V. All rights reserved.

itotenv.2004.09.018

ng author. Tel.: +44 118 37887745; fax: +44 118 9755865.

ess: [email protected] (M. Shahgedanova).

M. Shahgedanova, M. Lamakin / Science of the Total Environment 341 (2005) 133 –148134

1. Introduction

Atmospheric aerosol is a potent agent of climate

change (IPCC, 2001). It exerts strong influence on

radiative processes through scattering and absorption

of solar radiation and causes an indirect radiative

forcing by changing properties of clouds and concen-

trations of other climatically important constituents of

the atmosphere such as greenhouse gases (Schwartz et

al., 1995). The quantification of aerosol forcing

remains difficult partly because aerosol concentrations

vary significantly in time and space (IPCC, 2001). In

response to this problem, ground-based and airborne

monitoring of atmospheric aerosol began in many

regions in the 1970s (Holben et al., 2001) and satellite

observations began in 1980 (King et al., 1999). While

satellite observations are particularly suited for anal-

ysis of regional and global variations, ground-based

observations of aerosol burden are more accurate and

easier to perform. Estimating aerosol optical depth

(AOD) is the most frequently used way to assess

aerosol load from the ground. AOD is an index of the

attenuation of solar radiation due to the presence of

aerosol derived from measurements of direct solar

radiation. It is a spectral characteristic and in aerosol

studies, AOD at 500 nm is usually considered. In

urban or arid environments, AOD in this spectral

interval can approach unity that implies almost a

100% probability that direct solar radiation is scat-

tered or absorbed before reaching the surface. Under

background conditions, AOD values vary between

0.02 and 0.08 (Shaw, 1982). An important obstacle on

the way to a better understanding of spatial and

temporal variability in AOD is a lack of long-term

continuous records. As Holben et al. (2001) point out,

Fig. 1. Location o

bthe vast majority [of observations] are site-specific,

short-term investigations with little relevance for

seasonal, annual, or long-term trend analysisQ.This paper investigates a unique long-term data set

of AOD derived from the measurements of direct

solar radiation conducted in the Russian Arctic

between 1940 and 1994 (Fig. 1). For comparison,

AOD observations at Barrow, Alaska date back to

1976 (Bodhaine and Dutton, 1993) and observations

in northern Canada date back to 1979 (Barrie and

Hoff, 1984). The Arctic region has been given special

attention because of the high concentrations of

pollution-derived aerosol, which is transported to the

Arctic mainly from Eurasia (Rahn and Lowenthal,

1984; Ottar, 1981). Concentrations of aerosol and,

consequently, AOD values in the Arctic exhibit a

pronounced seasonal cycle, being an order of magni-

tude higher at the end of winter and the beginning of

spring than in summer and autumn. Two main factors

are responsible for the continuous accumulation of

aerosol throughout the winter: polar night and the

absence of photochemical reactions; and low deposi-

tion rates controlled by atmospheric stability and

precipitation. Barrie (1986a), Shaw and Khalil (1989),

and Shaw (1982, 1995) provide comprehensive

reviews of climatology of Arctic aerosol.

While AOD observations from Alaska and Canada

have been extensively analysed with regard to

seasonal (Lowenthal and Rahn, 1985; Shao-Meng et

al., 1993) and long-term trends (Bodhaine and Dutton,

1993), and synoptic conditions (Shaw, 1985; Smirnov

et al., 1996), discussion of changes in AOD over the

Russian Arctic focused primarily on the impacts of

volcanic eruptions (Marshunova and Mishin, 1988;

Marshunova and Radionov, 1988). Radionov et al.

f the sites.

Table 1

Location of the sites and details of the observation programmes

Station Latitude

(8N)Longitude

(8E)Beginning End

Krenkel 80.6 58.1 1960 1993

Zhelaniya 77.0 68.6 1957 1993

Vize 79.5 77.0 1958 1993

Dikson 73.5 80.2 1940 1993

Uedineniya 77.5 82.2 1950 1992

Golomyanniy 79.6 90.6 1959 1992

Fedorova 77.7 104.3 1950 1993

Preobrazheniya 74.7 112.9 1966 1993

Kotelniy 76.0 137.9 1955 1993

Muostakh 71.3 130.0 1955 1992

Chetyrekhstolbovoy 70.6 162.4 1966 1993

Wrangel 71.0 181.5 1966 1994

Vankarem 67.8 184.1 1966 1993

Uelen 66.2 190.2 1966 1993

M. Shahgedanova, M. Lamakin / Science of the Total Environment 341 (2005) 133 –148 135

(1994) investigated the long-term trends in atmos-

pheric turbidity at one site (Dikson Island) and

reported a downward trend between 1985 and 1991,

which they attributed to a decline in anthropogenic

emissions in Europe and the former Soviet Union.

This was consistent with the findings by Bodhaine

and Dutton (1993), who reported a downward trend in

AOD for Barrow, Alaska between 1982 and 1991.

The long-term trends in AOD at other sites have not

been investigated and there has been no attempt to put

the AOD data from the Russian Arctic in the synoptic

and climatic contexts.

Understanding of the long-term dynamics of

aerosol concentrations in the Arctic is necessary

because of the radiative forcing of aerosol. This is

not fully understood but Valero et al. (1986) suggested

heating rates of 0.15–0.25 K day�1 due to the

dominant effect of absorption and low significance

of scattering over snow-covered surface. Therefore, a

decrease in aerosol concentrations in the Arctic may

offset the projected warming of the Arctic climate

(Rahn and Lowenthal, 1984; IPCC, 2001). It is,

therefore, important to understand whether the decline

in aerosol concentrations reported by Bodhaine and

Dutton (1993) for Barrow and Radionov et al. (1994)

for Dikson Island is characteristic of the Arctic region

as a whole or has a limited spatial extent. It is

important to examine the potential of characterization

of optical state of the atmosphere on the basis of

synoptic climatology because changes in tropospheric

circulation may contribute to variations in AOD. An

increase in depression activity has been observed in

the Barents–Laptev sector of the Arctic since the mid-

1980s (Rogers and Mosley-Thompson, 1995; Masla-

nik et al., 1996) and a dramatic decline in sea-level

pressure has occurred in the central Arctic Ocean in

the late 1980s with significant pressure anomalies

extending into the 1990s (Walsh et al., 1996; Cull-

ather and Lynch, 2003).

This paper provides a comprehensive analysis of

AOD data from 14 stations in the Russian Arctic

addressing the following research questions: (i) how

does AOD vary across the Russian Arctic in different

seasons? (ii) are there any statistically significant

long-term trends in AOD in the Russian Arctic? (iii)

do synoptic (air mass and circulation) conditions

contribute to variability in AOD and how? (iv) are

there any statistically significant trends in frequency

and characteristics of synoptic types in the Russian

Arctic? (v) do changes in frequency and character-

istics of synoptic types affect long-term changes in

AOD in addition to changes in emissions of air

pollutants?

2. Measurements of solar radiation and estimation

of AOD

The AOD values used in this study have been

estimated from integral measurements of direct solar

radiation performed between 1940 and 1991 at 14

stations located along the Arctic coast (Fig. 1; Table

1). Although observations continued until 1994, the

post-1991 measurements have not been used because

of the strong increase in turbidity due to the Pinatubo

eruption (Radionov et al., 1994; Stenchikov et al.,

2002). All sites were located in the biomes of arctic

tundra or arctic desert characterized by continuous

snow cover and the presence of sea ice between

October and June (Shahgedanova and Kuznetsov,

2002). The local production of aerosol during this

time of year is minimal. In the absence of snow, the

surface cover is that of bare rocks or vegetation

consisting of mosses and dwarf shrubs. The locations

of the observation sites remained the same throughout

the period of observations. There were no local

anthropogenic sources of pollution with the exception

of the Dikson Island site located in the vicinity of a

settlement with a population of about 5000. The


measurements of solar radiation were accompanied by

standard meteorological observations.

Direct solar radiation was measured using thermo-

electric pyrheliometers (AT-50 model produced in the

former Soviet Union) with 108 view field angle and

spectral response of 0.4–4.0 Am. These instruments

were analogous to the Angstrom pyrheliometer

recommended by the WMO (WMO, 1971) and were

calibrated once a month against an Angstrom pyrheli-

ometer. The accuracy of the measurement of the flux

of direct solar radiation was F10 W m�2 with

measured signal ranging between 600 and 1000 W

m�2. The resulting error of AOD estimation is in the

order of 0.001. These pyrheliometers have been used

at all sites and throughout the period of observations,

thus providing internal consistency of the data set. All

measurements were taken manually under the dclearskyT conditions defined as the area of clear sky aroundthe solar disk equal to twice the area of the solar disk,

and for solar elevations above 108. The measure-

ments, usually three to seven per day, were made at

different times of day and these did not necessarily

correspond to the standard meteorological times.

The permanent location of the observation sites,

simplicity of the instruments (suited to the routine

operations in contrast to sun photometers operated in

the BAPMoN network) and consistency in their use

make this AOD data set particularly suitable for

analysis of spatial patterns and long-term trends.

However, one should compare these data with other

data sets with care as different instruments and

methods of AOD estimation are used elsewhere. The

main disadvantage is that observations are limited to

the polar day (March–October) and to the dclear skyTconditions (infrequent in September and October).

This effectively restricted observations to March–

August. Each month, there were on average about 10

days with observations of solar radiation from which

AOD values were derived. These data, as all ground-

based observations, do not allow one to distinguish

between tropospheric and stratospheric aerosol.

Impacts of the eruptions of El Chichon and Pinatubo

on AOD have been discussed by Radionov et al.

(1994) and Stenchikov et al. (2002) and will be

addressed in this paper briefly.

In this study, two sets of AOD data are used.

Spatial distribution and long-term trends have been

analysed using monthly time series of AOD for 500

nm (s500). Analysis of the links between AOD and

synoptic conditions has been performed with regard to

two sites, Dikson Island and Wrangel Island, using

daily AOD statistics for 550 nm (s550). The values ofs550 are marginally lower than the values of s500(Angstrom, 1929, 1961). The difference is inversely

proportional to the size of aerosol and the largest

differences are observed in summer when fine aerosol

dominates the Arctic atmosphere. Daily means have

been calculated using all AOD estimates available on

the day and this varied between days.

s500 has been estimated using a regression model

derived from the simultaneous integral measurements

of direct solar radiation by pyrheliometers and spectral

measurements by sun photometer:

s500 ¼ � 0:110� 0:892ln P2 ð1Þ

where P2 is the transmission coefficient of the

atmosphere with two optical air masses (i.e., solar

elevation of 308). P2 is estimated from the flux of

direct solar radiation using the equation derived by

Evnevich and Savikovsky (1989):

P2 ¼

S

1:367

!sin hð Þþ0:250:41

ð2Þ

where S is direct solar radiation (W m�2) and h is

solar elevation (8). Eq. (2) represents an improved

version of Sivkov’s (1960) empirical model based on

more than 13,000 observations. The calculation of P2

is similar to the procedure for the estimation of

dapparent transmissionT first introduced by Ellis and

Pueschel (1971) and widely used in radiation studies

(e.g., Bodhaine et al., 2002). The concurrent spectral

and integral measurements, used to derive Eq. (1),

have been conducted at different locations in the

Arctic (Sakunov et al., 1988; Radionov et al., 1994).

Values of the coefficient of determination (R2) ranged

between 0.67 and 0.82 for the atmosphere with high

transparency and 0.96 for the atmosphere contami-

nated by volcanic aerosol following the El Chichon

eruption (1983). Regression coefficients for 1983

were significantly different from those for other years

and data for 1983 were not used. Lower values of R2

(0.67–0.70) were characteristic of March–May while

higher values (0.70–0.82) were typical of June–

September.


While the error associated with accuracy of solar

radiation measurements is insignificant, the attenu-

ation of solar radiation by other atmospheric

constituents and their variability may contribute to

the uncertainty of s500 estimation. The value of P2,

upon which s500 is based, is estimated from a wide

range of wavelengths between 0.4 and 4 Am and,

therefore, depends on Rayleigh scattering (which

accounted for about 50% of the total attenuation of

solar radiation), aerosol scattering, and absorption by

water vapour, O2, O3, CO2 and NO2. Marshunova

and Radionov (1988) and Marshunova and Mishin

(1988) analyzed the relative contributions of these

factors into the variability in P2 over the Arctic

Ocean and concluded that atmospheric aerosol and

water vapour were the most important contributors

while other influences were less important (e.g., O3

optical depth at 500 nm for the total ozone of 300

D.U. is 0.009) or negligible. In March and April, the

attenuation of solar radiation by aerosol and water

vapour accounted for 38% and 16% of total

attenuation, respectively. Between May and Septem-

ber aerosol accounted for 21–29% and water vapour

for 24–30%. The strong correlations between the

s500 time series estimated from integral and spectral

measurements confirm that variability in precipitable

water does not affect the performance of the

regression model significantly. The west–east gra-

dient in precipitable water is small and does not

introduce significant uncertainty in the analysis of

spatial distribution of s500. In March, the amount of

Fig. 2. Time series of precipitable water (mm) in 1000–300-mb layer for th

June–August (JJA).

precipitable water in the 1000–300-mb layer changes

from 4–5 mm over the Kara Sea to 3–4 mm over the

East Siberian Sea and to 4–5 mm over the Chukchi

Sea. In July, a south–north gradient is observed with

changes from 16 mm near the coast to 14 mm at

808N (Serreze et al., 1994). Temporal variability in

precipitable water in the 1000–300-mb layer between

1959 and 1980 in the Eurasian Arctic has been

analysed by Burova (1988) using radiosonde meas-

urements; no statistically significant trends have been

found. The time series of precipitable water for the

Dikson Island and Wrangel Island (Fig. 2) for 1959–

1990 also does not contain statistically significant

trends. Therefore, variability in precipitable water

does not introduce additional uncertainty into the

analysis of the long-term changes in s500.To exclude the contribution of water vapour in the

attenuation of direct solar radiation further, an

empirical method of estimation of AOD for 550 nm,

which accounts for the absorption by water vapour,

has been developed by Tarasova and Yarkho (1991):

s550 ¼ln Sð Þ� 0:186w�0:183þ 0:879w�0:0094 � 1ð Þ=sin hð Þð Þ0:8129w�0:0021 � 1þ 0:4347w�0:0321 � 1ð Þ=sin hð ÞÞ

ð3Þ

where S is direct solar radiation (W m�2), h is solar

elevation (8), and w is amount of precipitable water (g

cm�2). To verify Eq. (3), over 300 simultaneous

integral measurements of direct solar radiation using

pyrheliometers and spectral measurements using sun

e Dikson Island and Wrangel Island sites for March–April (MA) and


photometers were performed at a number of back-

ground locations with negligible concentrations of

tropospheric NO2 and O3 (Tarasova and Yarkho,

personal communication; Radionov et al., 1999). The

s550 values derived from integral measurements

using Eq. (3) were in close agreement with s550derived from spectral measurements with a correlation

coefficient of 0.95. This method has been recommen-

ded for the estimation of AOD at those Russian

stations where spectral observations of solar radiation

are not available. However, in this study it has been

used for two sites only because precipitable water (or

vapour pressure used in its estimation) data were not

available for other sites at daily resolution.

The network of radiosonde stations does not

always correspond to the network of stations measur-

ing solar radiation, and to overcome this problem,

amounts of precipitable water to be used in the Eq. (3)

have been estimated from actual vapour pressure

measured at the ground level using an approximation

suggested by Sivkov (1968) and adapted for the

Russian Arctic by Burova (1983):

w ¼ 0:33e0:775 ð4Þ

where w is precipitable water (g cm�2) and e is

actual vapour pressure (mb). This equation has been

verified using independent data sets of precipitable

water derived from radiosonde measurements and

estimated using Eq. (4) for the Dikson Island and

Wrangel Island sites. The agreement was very close

for March–April with correlation coefficients of 0.91

and 0.85, respectively, and average differences

between pairs of estimates of 0.6 and 0.3 mm. This

close agreement reflects the fact that in spring the bulk

of water vapour is typically found in the lower

troposphere, below 700 mb (Serreze et al., 1995).

The lower correlation coefficient of 0.77 for both sites

and average differences of 1.6 and 0.6 were obtained

for June–August. Note that a change in precipitable

water from 13 to 16 mm (twice the average difference

for the Dikson Island site and typical July values)

results in the s550 estimation error of 0.008 at solar

elevation of 308 and solar radiation flux of 700 W

m�2 while the typical June–August values of s550range mainly between 0.05 and 0.10. Potential

uncertainty is associated with radiosonde measure-

ments too because humidity data are often not

transmitted at temperatures below �408C. However,this error is small in spring and summer (F5% for

vertically integrated vapour flux) because air temper-

atures below �408C are not common at low levels

during these seasons (Serreze et al., 1995).

3. Spatial distribution of AOD

Table 2 illustrates spatial and seasonal variability in

s500 (estimated using Eq. (1)) across the Russian

Arctic in March–September. The mean values are

estimated for the period between 1966 and 1991 when

observations were conducted at all stations. Fig. 3

shows frequency distributions of s500 daily means

(1966–1990) for the Dikson Island and Wrangel

Island sites for March–April, May and June–August.

This division is used because of the seasonal

peculiarities of aerosol behavior in the Arctic whereby

the annual maximum in aerosol load is observed

between the end of February and April (Shaw, 1982,

1995; Barrie, 1986b; Shaw and Khalil, 1989). May is

a transitional month and a sharp decrease in AOD

occurs between April and May from the all-station

averages of 0.18 and 0.17 in March and April,

respectively, through 0.13 in May and to 0.08 in

June. Seasonal trends between June and September

are small.

Analysis of monthly values of s500 at different

stations shows that distribution of s500 is uneven

across the Russian Arctic. While the difference

between March and September means of s500 at

different stations is moderate with a range of 0.096

at Uelen to 0.129 at Kotelny, monthly averages

exhibit a greater range. Between March and May

atmospheric turbidity is higher in the western part of

the Arctic (Kara–Laptev sector) where it ranges

between 0.19 and 0.22 while in June and July the

eastern (East Siberian–Chukchi) sector experiences

higher turbidity than the Kara–Laptev sector. The

spring maximum occurs in March in the Kara–

Laptev sector while in the east (from Chetyrehstol-

bovoy to Uelen) it is observed in April. Particularly

high s500 values are observed at the Krenkel,

Fedorova, and Preobrazheniya sites in March when

monthly means exceed 0.20. Frequency distributions

of daily means of s500 for the Dikson Island and

Wrangel Island sites also show that s500 of 0.10–

Table 2

Monthly mean values and standard deviations (the second line for each station) of s500 for 1966–1991

Station Monthly mean and standard deviation Mar–Sep

Mar Apr May Jun Jul Aug Sepmean

Krenkel 0.229 0.170 0.135 0.061 0.058 0.070 0.036 0.108

0.062 0.043 0.046 0.029 0.029 0.045 0.022

Zhelaniya 0.182 0.142 0.134 0.088 0.064 0.053 0.057 0.103

0.076 0.038 0.051 0.032 0.028 0.022 0.036

Vize 0.198 0.183 0.141 0.067 0.085 0.072 0.058 0.115

0.055 0.054 0.053 0.029 0.022 0.033 0.027

Dikson 0.190 0.184 0.132 0.078 0.079 0.071 0.065 0.114

0.051 0.047 0.036 0.036 0.029 0.048 0.038

Uedineniya 0.194 0.171 0.151 0.081 0.084 0.078 0.043 0.115

0.056 0.042 0.063 0.040 0.027 0.047 0.022

Golomyanniy 0.187 0.174 0.135 0.078 0.065 0.055 0.056 0.107

0.054 0.047 0.038 0.038 0.031 0.025 0.046

Fedorova 0.220 0.189 0.138 0.076 0.076 0.070 0.048 0.117

0.049 0.051 0.039 0.038 0.037 0.029 0.021

Preobrazheniya 0.205 0.180 0.150 0.094 0.083 0.047 0.062 0.117

0.056 0.050 0.034 0.040 0.033 0.026

Kotelniy 0.198 0.199 0.151 0.099 0.093 0.079 0.082 0.129

0.050 0.039 0.052 0.045 0.039 0.045 0.039

Muostakh 0.165 0.173 0.141 0.094 0.096 0.085 0.068 0.117

0.064 0.046 0.035 0.033 0.058 0.043 0.045

Chetyrekhstolbovoy 0.162 0.172 0.118 0.094 0.081 0.075 0.045 0.107

0.043 0.042 0.032 0.036 0.038 0.032 0.025

Wrangel 0.144 0.168 0.124 0.082 0.088 0.076 0.060 0.106

0.041 0.044 0.034 0.034 0.042 0.030 0.027

Vankarem 0.151 0.143 0.116 0.081 0.079 0.074 0.048 0.099

0.058 0.046 0.044 0.035 0.036 0.035 0.033

Uelen 0.119 0.150 0.113 0.087 0.078 0.070 0.053 0.096

0.048 0.037 0.035 0.028 0.032 0.030 0.037


0.20 are most commonly observed at the Dikson

Island site in spring while the Wrangel Island

experiences higher transparency in March–April

with the most frequent s500 values ranging between

0.10 and 0.15 (Fig. 3). These distributions are typical

of the Kara–Laptev and East Siberian–Chukchi

sectors in general although at the Krenkel Observ-

atory (not shown) daily means exceeding 0.2 are

observed more frequently than at other sites. s500values exceeding 0.20 occurred at the Dikson Island

site on 18% of all days in March–April while at the

Wrangel Island site such high s500 values were

registered mostly in May, confirming that the peak in

aerosol load is observed at the Wrangel Island later

in spring (April–beginning of May). During June–

August, s500 of 0.10–0.15 are most common at all

sites. The higher turbidity observed in the western

sector in March–April can be explained by its

relative proximity to the sources of anthropogenic

pollution located in Europe, Western and Central

Siberia. The contribution of pollution-derived aerosol

is particularly important during the cold part of the

year when emissions of anthropogenic pollutants are

higher and emissions from natural sources are

insignificant as the Arctic Ocean is frozen and there

is continuous snow cover (Shaw, 1982, 1995; Barrie,

1986b; Shaw and Khalil, 1989). The opposite pattern

observed in summer can be explained by regional

differences in atmospheric circulation. The eastern

Arctic experiences more frequent high pressure or

low-pressure gradient systems with low wind speeds

in summer and this results in a less efficient removal

of aerosol from the atmosphere (see this paper).

Large day-to-day variability in s550 and more

complex frequency distributions characteristic of

the Barents–Kara–Laptev sector in all seasons are

Fig. 3. Frequency distributions of daily means of s500 for the Dikson Island and Wrangel Island sites for March–April (MA), May (M), and

June–August (JJA) for 1966–1990 (% of all days with s500 estimates).


also due to strong variability in weather patterns and

air mass trajectories.

4. Long-term trends in AOD

The nature of long-term trends (their significance

and a rate of change) can be affected by three factors:

changes in emissions of air pollutants, climatic

variability, and changes in concentrations of strato-

spheric aerosol derived from volcanic eruptions.

Three major eruptions occurred during the period of

observations: Agung (March, 1963), El Chichon

(April 1982) and Pinatubo (June 1991). The impact

of Pinatubo was the strongest during the 20th century

(McCormick and Veiga, 1992; Thomason, 1992;

Herber et al., 1996) and for this reason the post-

Pinatubo years (1991–1994) have been excluded from

the analysis. The Agung eruption has affected the

Southern Hemisphere significantly while its impacts

on the Northern Hemisphere were small especially in

the high latitudes (NASA; http://www.giss.nasa.gov/

data/strataer/). The inspection of the monthly time

series of s500 has shown that changes in values

following the Agung eruptions were well within the

range of interannual variability during the years not

affected by volcanic eruptions. The El Chichon

eruption produced a much more significant impact

on the Arctic region (NASA; http://www.giss.nasa.

gov/data/strataer/). Monthly s500 values for 1981,

1982, and 1984 have been compared for each station

to evaluate the duration of its impact. A comparison of

the s500 values for the spring and summer months of

1981 and 1982, respectively, has shown that most

differences between individual pairs of months did not

exceed one standard deviation (calculated without the

1983 values). Similarly, monthly s500 values for 1984did not systematically exceed the respective values for

1981 and 1982, being in many cases lower than in

1981 and 1982. It has been concluded that the impact

of the El Chichon eruption on AOD has been limited

in the Eurasian Arctic to 1983, which is consistent

http://www.giss.nasa.gov/data/strataer/



with the conclusions by Post et al. (1996) who

estimated that the enhancement of scattering caused

by the products of the El Chichon eruption continued

for about 200 days after the eruption. The year of

1983 has been excluded from the analysis.

The long-term trends in s500 have been estimated

for two parts of the record, the beginning of record

(which differs between stations) and 1981, and 1982–

1990 (without 1983), because at many sites two

different trends were evident with a change in

direction in 1982. Table 3 shows coefficients of

determination for the trends statistically significant

at 0.05. The time series for three stations, Dikson

Island, Muostakh Island and Wrangel Island, are

shown in Fig. 4. Prior to 1982, the statistically

significant positive trends were observed in the

Table 3

Variance (R2) explained by the long-term trends significant at 0.05

(a) between beginning of observations and 1982, and (b) between

1982 and 1990

Station Mar Apr May Jun Jul Aug

(a)

Krenkel

Zhelaniya

Vize

Dikson 0.53 0.48 0.42 0.15

Uedineniya 0.13 0.48 0.32

Golomyanniy

Fedorova 0.28 0.18

Preobrazheniya

Kotelniy 0.23 0.37 0.32 0.37 0.32

Muostakh 0.17 0.19

Chetyrekhstolbovoy

Wrangel

Vankarem

Uelen 0.54 0.44

(b)

Krenkel

Zhelaniya 0.50 0.64

Vize 0.90

Dikson 0.88 0.67 0.81

Uedineniya 0.56 0.54 0.73 0.60

Golomyanniy

Fedorova 0.15

Preobrazheniya

Kotelniy

Muostakh 0.69 0.56

Chetyrekhstolbovoy 0.66 0.54

Wrangel 0.52 0.74

Vankarem 0.65 0.88 0.57

Uelen 0.96 0.68

Kara–Laptev sector mainly in March, April and May

but not in the East Siberian–Chukchi sector with the

exception of the Uelen station, which is located close

to Barrow, Alaska, and where changes in AOD are

similar to those observed at Barrow (Bodhaine and

Dutton, 1993). The significance of the positive trends

observed at the Kara–Laptev stations in spring can be

partly attributed to the length of the time series:

aerosol load began to increase in the late 1950s. The

earliest observations in the eastern Russian Arctic date

back to 1955 at Kotelny Island (statistically signifi-

cant trend) and Muostakh (no statistically significant

trend) while at other sites observations began in 1966.

At the Dikson Island site, the long-term trends remain

statistically significant in spring if estimated for the

1955–1981 period and AOD remained largely

unchanged between the mid-1960s and the early

1980s. The post-1982 negative trends show the

opposite spatial distribution: the statistically signifi-

cant trends in March, April and May occur primarily

in the eastern Arctic, at all five sites. Only two stations

in the Kara–Laptev sector, Dikson Island and Uedi-

neniya Island, exhibit negative trends significant at

0.05 in spring. At the Dikson Island site s500 declinesfrom 0.197 in March 1982 to 0.124 in 1990 (Fig. 4).

By contrast, in summer statistically significant trends

have been registered mainly in the western sector. At

Cape Zhelaniya, Vize Island, Dikson Island, and

Uedineniya Island mean monthly values of s500declined from 0.135, 0.119, 0.196 and 0.176 in

1982 to 0.044, 0.010, 0.040 and 0.037, respectively.

A significant decrease in anthropogenic emissions

of air pollutants occurred in Europe and the former

Soviet Union (FSU) in the last 20 years. The total

quantity of emissions in the FSU declined from

42�106 tonnes in 1984 through 36�106 tonnes in

1990 to 21�106 tonnes in 1998 (Shahgedanova,

2002a). The most pertinent sources of air pollution

(particularly sulfur that is the main component of the

Arctic aerosol) affecting the Arctic region are the

industrial areas of Western and Central Siberia, in

particular the non-ferrous smelters located in the town

of Norilsk in the Taymyr peninsula, as well as the

non-ferrous smelters of the Kola peninsula (Shahge-

danova, 2002a). The SO2 emissions from both regions

declined considerably from 2.4�106 tonnes in 1985

through 2.2�106 tonnes in 1990 to 1.8�106 tonnes in

1995 in Norilsk and from 0.52�106 tonnes in 1985

Fig. 4. Time series of monthly means of s500 for the Dikson Island, Muostakh, and Wrangel Island sites for March.


through 0.48�106 tonnes in 1990 to 0.38�106 tonnes

in 1995 in the Kola peninsula (Shahgedanova,

2002a). It is pollution-derived aerosol that predom-

inates in the Arctic in spring and the lack of spatially

uniform trends in the spring values of s500 during the

1982–1990 period suggests that the effect of the

decline in the anthropogenic emissions on aerosol

load in the Eurasian Arctic has been limited. A

decrease in atmospheric turbidity in spring has

occurred in the eastern Kara Sea located relatively

close to the industrial regions of Siberia and

particularly the Norilsk smelters. Although substan-

tial, the observed decline in SO2 emissions at Norilsk

has not resulted in higher atmospheric transparency in

the Laptev Sea.

5. Meteorological controls over AOD

The lack of uniform trends in s500 behavior invitestwo questions: (i) how do synoptic conditions affect

aerosol load and (ii) have there been any significant

long-term changes in weather type frequency and

could these be responsible for the long-term dynamics

of aerosol load? Significant changes in the tropo-

spheric circulation over Western and Central Siberia

have been reported by Rogers and Mosley-Thompson

(1995) and Maslanik et al. (1996).

A synoptic climatology approach has been used to

assess the relationships between synoptic conditions

and AOD (s550 estimated using Eq. (3)). Temporal

synoptic indices have been developed for two sites,

the Dikson Island and Wrangel Island, using daily

meteorological observations conducted during 1940–

1990 and 1966–1990, respectively. A comprehensive

review of the synoptic climatology approach and the

multivariate statistical techniques it is based on are

given by Yarnal (1993). In this study, P-mode

Principal Component Analysis with Varimax rotation

(RPCA) has been used in conjunction with Ward’s

method of cluster analysis (Yarnal, 1993; Wilks,

1995). P-mode RPCA produces temporal one-point

indices. These have been chosen rather than spatial

classification because of the spatial scale of the study

area and the length of the s500 time series. The two

stations considered in this research are characterized

by different climates (Shahgedanova, 2002b) and one

spatial classification may not be able to capture

weather regimes typical of both locations. The s550time series dates back to 1940 and daily geopotential

height and even reliable sea level pressure data used in

spatial classifications are not available for the entire

Table 4

Results of RPCA for the Dikson Island and Wrangel Island sites for

March–April (MA) and June–August (JJA)

Dikson JJA Wrangel JJA

Component 1 2 3 – 1 2 3 –

Cumulative

variance %

27.1 48.6 68.6 – 27.2 51.1 72.9 –

Dikson MA Wrangel MA

Component 1 2 3 4 1 2 3 4

Cumulative

variance %

38.6 56.9 73.8 90.3 27.8 50.0 69.2 86.3

Only statistically significant components are shown. Total variance

explained is highlighted in bold.

Table 5

Cluster-mean values of meteorological variables and s550 for the

Wrangel Island site for March–April

Type characteristics Type 1 Type 2 Type 3 Type 4

Temperature, 8C �20.1 �19.1 �25.3 �16.1

Relative humidity, % 70.0 74.5 75.5 84.1

Pressure, mb 1024.3 1019.5 1023.2 1018.6

North scalara 10.2 0.8 �0.9 0.6

East scalara 0.1 �10.1 0.4 2.6

s550 average 0.119 0.113 0.148 0.147

rs550 0.058 0.038 0.069 0.060

s550 median 0.109 0.120 0.141 0.142

s550 average+r 0.177 0.151 0.217 0.207

Days s550N(s550 average+r), %

12 10 13 15

Days s550N0.200, % 8 0 18 18

Days total 250 117 897 848

Days with s550observations

49 20 354 195

a Positive north scalar—northerly wind; positive east scalar—

easterly wind.


length of observations. In addition to geopotential

height or pressure fields that are representative of

circulation types, air mass characteristics such as air

temperature and humidity are important controls over

aerosol load (Smirnov et al., 1994, 1996, 2000;

Kotchenruther et al., 2000; Nilsson et al., 2001).

The following variables (daily means of four

observations taken every six h at standard meteoro-

logical times) were used to construct the indices: sea

level pressure (mb), air temperature (8C), relative

humidity (%), north and east scalars of wind (defined

as products of wind speed and cosine and sine of wind

direction, respectively). Relative humidity rather than

vapour pressure was used as it is relative humidity that

controls the growth of aerosol. The indices have been

developed for two seasons, spring (defined as March

and April) and summer (defined as June, July and

August). These seasons have been selected in agree-

ment with seasonal changes in s550. Similarly to s500,s550 exhibits a distinct maximum in March and April

and declines in May. Data for May have not been used

because a strong negative trend in s550 observed in

May exceeds the day-to-day variability.

Results of the RPCA are shown in Table 4. The

dscree plotT test in which a major break in a plot of

eigennumber versus eigenvalue indicates the appro-

priate number of components to retain (Craddock and

Flood, 1969) has been used to determine the number

of statistically significant principal components, and

the number of clusters to be retained has been

determined by the inspection of dendrograms (not

shown). The average climatological characteristics of

each cluster and daily synoptic charts have been

analyzed to interpret each cluster as a synoptic type.

Aerosol signatures of the identified types have been

determined by averaging the corresponding s550values and ANOVA has been used to establish

whether the between-cluster differences in s550 are

statistically significant. Time series of the identified

synoptic types has been constructed to detect long-

term trends in the frequency of the synoptic types.

Note that the number of days for which s550 data wereavailable is lower than the total number of days used

in the construction of indices. Days containing s550data were evenly distributed throughout the period of

observations and the long-term trends in AOD have

not interfered with the results.

Synoptic indices constructed for the Dikson Island

and the Wrangel Island stations for March–April

contain five and four types, respectively. Their

characteristics and cluster-mean values of s550 are

given in Tables 5 and 6. The between-cluster differ-

ences in s550 are statistically significant at 0.04 and

0.01 levels for the Diskon Island and the Wrangel

Island sites, respectively. Wind is the single most

important factor controlling AOD at the Wrangel

Island site in spring and types 1 and 2 characterized

by strong northerly and westerly wind (and higher

deposition rates), respectively, exhibit low s550 values.Two other types are characterized by calm conditions

Table 6


Dikson Island station for March–April

Type

characteristics

Type 1 Type 2 Type 3 Type 4 Type 5

Temperature, 8C 1010.7 1001.6 1026.0 1017.0 1009.5

Relative humidity,

%

87.7 89.9 89.4 78.7 85.0

Pressure, mb �19.7 �13.2 �20.0 �26.4 �18.4

North scalara 1.7 �9.0 �4.1 �2.5 0.2

East scalara 5.6 0.6 0.0 1.9 �5.9

s550 average 0.154 0.181 0.163 0.149 0.156

rs550 0.065 0.095 0.083 0.065 0.068

s550 median 0.148 0.173 0.140 0.137 0.152

s550 average+r 0.219 0.275 0.245 0.214 0.226

Days s550N(s550 average+r),%

11 13 14 16 14

Days s550N0.200,%

21 33 27 21 23

Days total 438 557 465 1115 658


84 39 126 342 114


easterly wind.


and exhibit higher s550 values irrespective of pressurepatterns or temperature.

Results for the Dikson Island are different. The

highest cluster-average value of s550 is found in type

2, which represents depressions and frontal systems

and is characterized by strong southerly wind. To

evaluate the impact of transport direction on atmos-

pheric transparency, the 5-day isentropic back trajec-

tories starting at 850 mb surface over the Dikson

Island site have been calculated using the British

Atmospheric Data Centre (BADC)/ECMWF model

(available at http://badc.nerc.ac.uk/) for the 1979–

1990 period for all days when s550 values were

available. Trajectory analysis confirms that trajecto-

ries associated with type 2 are mostly from the

industrial areas located to the south or southwest of

the Dikson Island site (Fig. 5). In particular, s550values associated with trajectories passing over the

Norilsk non-ferrous smelters located in about 500 km

south of the Dikson Island site range between 0.20

and 0.30 in March–April. This is in agreement with

Raatz and Shaw (1984), who have demonstrated that a

strong meridional flow associated with frontal systems

is required for the transportation of air pollutants from

the regions of origin (the sub-Arctic and middle

latitudes) to the high Arctic. The above average s550values are associated with type 3, representing high-

pressure systems centered east of Dikson Island.

Strong southerly flow developing on the southwestern

periphery of the high is registered at the site (Table 6),

however, trajectories are both from the south and the

east, along the Arctic coast (Fig. 5). Two factors

contribute to low atmospheric transparency: (i) high

atmospheric stability and (ii) transportation of pol-

luted air either directly from the industrial areas

located to the south or from the eastern Kara–Laptev

sector, which experiences the highest concentrations

of aerosol in the Eurasian Arctic in spring. The lowest

s550 values occur in type 4, representing low-pressure

gradient fields with calm conditions and low temper-

atures. Air mass trajectories associated with this type

4 are mostly from the central Arctic Ocean. The low

s550 values associated with type 4 for the Dikson

Island site and type 1 for the Wrangel Island site (not

shown) confirm the conclusion by Raatz et al. (1985)

that the frozen Arctic Ocean is a source of clean

tropospheric air, and disprove the conclusion by

Vinogradova (2000) who argued that in spring the

high Arctic is sufficiently polluted to serve as a source

of pollution for the Arctic islands and the mainland.

Although there is a clear link between s550 and

synoptic types, the time series of frequencies of the

synoptic types provides little useful information with

regard to an explanation of AOD trends at both sites.

A strong increase in the number of low-pressure

systems (type 5) has been observed at Dikson Island

in March–April since 1970 with the positive trend

accounting for 34% of the variance in the time series

but this type is characterized by average aerosol load.

The number of low-pressure systems was higher

between 1984 and 1990 than at any other time since

record began in 1940 with the exception of 1964 and

1962. This result is in agreement with the conclusions

by Rogers and Mosley-Thompson (1995) and Masla-

nik et al. (1996). No similar increase has been

observed in the eastern part of the Russian Arctic.

Synoptic indices constructed for the Dikson Island

and the Wrangel Island stations for June–August

contain four types each (Tables 7 and 8). The

between-cluster differences in s550 are statistically

significant at 0.01 for the Dikson Island site and at

0.04 for the Wrangel Island site. At both sites, the

highest values of s550 are typical for the types

http://www.badc.nerc.ac.uk/

Fig. 5. Isentropic back trajectories for the identified synoptic types (March–April) arriving to the Dikson Island site.


representing low-pressure gradient fields or high-

pressure cells and characterized by weak wind,

comparatively high temperatures and low relative

humidity that is consistent with traditional views in

air pollution climatology. During summer, a high

proportion of atmospheric aerosol is of marine origin

and, being produced locally, it is controlled by

meteorological factors in the same way as air

Table 7


Wrangel Island station for June–August


Temperature, 8C 1.9 5.0 0.6 1.9


Pressure, mb 1009.5 1013.4 1018.2 1009.2

North scalara �1.2 1.9 0.5 �0.8

East scalara �2.7 1.3 2.4 1.9

s550 average 0.058 0.070 0.063 0.060

rs550 0.034 0.032 0.033 0.035

s550 median 0.054 0.070 0.057 0.050

s550 average+r 0.092 0.102 0.095 0.095


16 14 16 13

Days total 776 246 1087 1102


123 106 229 85


easterly wind.

Table 8


Dikson Island station for June–August


Temperature, 8C 5.4 11.9 2.8 1.0


Pressure, mb 1012.3 1014.1 1002.5 1012.8

North scalara �1.2 �1.7 �4.3 3.5a


pollutants. These synoptic types occur more fre-

quently in the eastern Arctic than in the west, which

explains the lower atmospheric transparency charac-

teristic of the eastern Arctic in summer. Time series of

frequencies of the identified synoptic types has been

constructed in order to detect long-term trends in

atmospheric circulation and their effects on s550. Asignificant decline in frequency of high-pressure

systems occurred between 1982 and 1990 at the

Dikson Island site with the long-term trend explaining

61% of the variance. Although high-pressure systems

are not frequent in this sector of the Arctic in summer

(observed on 267 days between 1940 and 1990), it

accounts for 19% of the days with AOD data and the

observed decline may play a role in the negative AOD

trends observed at this site in summer (Table 3). The

respective time series for the Wrangel Island site does

not exhibit statistically significant trends, which is

consistent with the lack of long-term change in AOD.
East scalar 1.0 2.8 �3.8 1.5
s550 average 0.066 0.087 0.050 0.061

rs550 0.048 0.059 0.031 0.041

s550 median 0.052 0.075 0.043 0.054

s550 average+r 0.114 0.146 0.081 0.101


16 17 16 17

Days total 1433 267 996 1903


292 109 38 148


easterly wind.

6. Conclusions

This paper examined spatial distribution and long-

term trends in AOD in the Russian Arctic using data

from 14 sites, and the relationships between AOD and

weather types at two sites. All stations exhibited a

clear spring maximum and summer minimum. Atmos-

pheric turbidity was higher in the Kara–Laptev sector

than in the east in March and April while between

June and August the East Siberian–Chukchi sector

experienced higher turbidity than the western sector.

An increase in AOD was observed in the Kara–Laptev

sector between the late 1950s and the early 1980s

mainly in March, April and May when pollution-

derived aerosol dominates. AOD estimates for the

eastern sector are available from 1966 and there has

been no statistically significant increase in AOD since

the beginning of record with the exception of

easternmost station Uelen on the Bering Strait coast.

It is difficult to establish whether it is the length of the

record or remoteness of the eastern Arctic that is

responsible for the difference in long-term dynamics

of AOD. By contrast, the spring values of AOD

declined in the eastern sector between 1982 and 1990

while similar trends in the western sector were

observed at two stations only. In summer, negative

trends were more common in the western Arctic. It

can be suggested that the effect of a decline in

anthropogenic emissions that occurred in Europe and

the former Soviet Union in the last 20 years on aerosol

load in the Arctic has been limited.

The relationships between AOD and weather types

have been examined for the Dikson Island site in the

Kara Sea and the Wrangel Island site in the East

Siberian Sea for March–April and June–August. The

statistically significant between-type differences in

AOD are observed in all seasons but different factors


are responsible for the intraseasonal variability. The

directions of airflow and wind speed are the main

controls over AOD in spring. High atmospheric

transparency is associated with strong northerly and

westerly flows at the Wrangel Island site while strong

southerly flow associated with the passage of depres-

sions and frontal systems results in low atmospheric

transparency at the Dikson Island site. Trajectory

analysis has confirmed that the latter is due to the

contribution of industrial sources located in the sub-

Arctic and middle latitudes. In summer, low-pressure

gradient fields or high-pressure cells bring about

higher AOD values. A decline in frequency of this

weather type has occurred in the western Arctic in

summer and this might have contributed to the

negative trend in AOD, in addition to the decline in

anthropogenic pollution.

Acknowledgements

The authors wish to thank Dr. V.F. Radionov

(Institute of Arctic and Antarctic Research, St.

Petersburg, Russia) for providing the data and

Professor K.P. Shine (Department of Meteorology,

The University of Reading, UK) for useful discus-

sions. M. Lamakin has been supported by The

University of Reading Postgraduate Studentship for

Overseas Students.

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trends in aerosol optical depth in the russian arctic and their links with synoptic climatology

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