**4. Spatial variations in aerosol optical depth AOD**

Table 1 gives the multiyear means and extrema of the annual values of AOD and the standard deviations from these means, which are averaged over the all 53 stations under consideration (pointed in Fig.1) for the two periods. It is seen that the AOD mean over all the stations and the entire observation period is equal to 0.14 and varies from 0.29 to 0.07, which is in good agreement with the spatial range of the AOD variations obtained from the satellite and model data (for the Russian region) that are given in the IPCC third and fourth reports (0.30–0.05).


**Table 1.** Multiyear means, maxima, minima, and standard deviations of the annual means of AOD over all stations in absolute units.

**Figure 2.** Statistics of the annual means of AOD for each of the stations: the ratio of the AOD means (black) over the period 1976–1994 and the AOD means (grey) over the period 1995–2010 and the standard deviations (red) in the series of the annual values of AOD for each of the stations.

Variations in the Aerosol Optical Depth Above the Russia

from the Data Obtained at the Russian Actinometric Network in 1976–2010 Years 7

with consideration for its limitations and errors:

cloudy) when the Sun is not blocked by clouds.

**4. Spatial variations in aerosol optical depth AOD** 

Period АОD σ

1976 – 2010

1995 – 2010

all stations in absolute units.

The AOD of the vertical atmosphere was calculated with a method specially developed and used at the MoscowStateUniversity meteorological observatory (Abakumova et al., 2006)

AOD={lnS-[0.1886w(-0.1830) + (0.8799w(-0.0094) -1)/ sinh]}/{0.8129w(-0.0021) – 1 + (0.4347w(-0.0321) -1)/sinh} (3) An index of the Angström spectral attenuation which depends on the size distribution of particles and the coefficient of particle reflection—is assumed to be equal to 1; Sis the direct solar radiation reduced to the average distance between the Earth and the Sun, W/m2 ; and w is the water content of the atmosphere, g/cm2 . The conditions of observations at the stations, as a rule, correspond to the weather of an anticyclonic type (clear or slightly

Table 1 gives the multiyear means and extrema of the annual values of AOD and the standard deviations from these means, which are averaged over the all 53 stations under consideration (pointed in Fig.1) for the two periods. It is seen that the AOD mean over all the stations and the entire observation period is equal to 0.14 and varies from 0.29 to 0.07, which is in good agreement with the spatial range of the AOD variations obtained from the satellite and model data (for the Russian region) that are given in the IPCC third and fourth reports (0.30–0.05).

> Mean 0.14 0.04 -0.02 Maximum 0.29 +0.02 Minimum 0.07 -0.05

> Mean 0.12 0.04 -0.01 Maximum 0.22 +0.05 Minimum 0.05 -0,06

**Table 1.** Multiyear means, maxima, minima, and standard deviations of the annual means of AOD over

**Figure 2.** Statistics of the annual means of AOD for each of the stations: the ratio of the AOD means (black) over the period 1976–1994 and the AOD means (grey) over the period 1995–2010 and the standard deviations (red) in the series of the annual values of AOD for each of the stations.

**LONGITUDE**

Trend of AOD variations inover 10 years

**Figure 3.** Spatial distributions of the multiyear means of AOD over the observation periods 1976–1994 (upper part) and 1995–2010 (lower part).

The annual values of AOD for each of the stations multiyear means over 1976–1994 years, over 1995–2010 years, their standard deviations are given in Fig.2. Each column of the diagram corresponds to the longitude positionof the station in accordance with Table 1. The means of the AOD characteristics are corresponds to the multiyear (1976–1994 years) annual means of AOD (black), grey corresponds to the multiyear (1995–2010 years) annual means, red corresponds to standard deviations of the annual values of AOD from its mean for each station. A spatial distribution of AOD is shown in more detail in the maps (Fig. 3) drawn by interpolating the data obtained at 53 stations to Russia's territory. For this interpolation, the technologies of the MATLAB 7.5.0. program package were used: there are options to create a uniform grid for the entire region, onto which the given functions Z= F(x,y*)*were projected, where *x* and *y*are the latitude and longitude, respectively, for each of 53 observation points, and *Z* is the AOD mean. In addition, a bilinear interpolation of data was performed. Under bi-cubic and bi-square interpolations, the results, in principle, do not differ from those given in Fig. 3. The spatial distribution of the AOD means over the 35 - year period is in a good agreement with the results of modeling a spatial atmospheric-aerosol distribution, which are given in the IPCC third report (IPCC, Climate Change 2007). The model described in this report takes into account aerosols of different origins anthropogenic and natural sulfates, organic particles, soot, mineral aerosol of natural origin, and marine saline particles) which have certain specific properties of distribution over the globe, and it yields a decrease in AOD over Eurasia from the southern to the northern latitudes in the presence of areas with increased atmospheric turbidity over southern Europe, the Middle East, southeastern Asia,

Ukraine, and Kazakhstan. Fig. 3 shows that the AOD over Russia decreases from the southwest to the northeast. The increased values of aerosol haziness in the southeast and southwest are most likely caused by an advective arrival of air masses from the regions with high aerosol content in the atmosphere: from Ukraine and Kazakhstan in the southwest and from southeastern Asia and China in the southeast. Fig. 3 (upper part) shows the localizations of regional tropospheric aerosol sources (western and eastern Siberia and Primorskii Krai). In the last 15 years (Fig. 3, lower part), in the absence of powerful volcanic eruptions and under conditions the atmosphere being purified of the stratospheric aerosol layer, the sources of aerosol arriving in the troposphere have become more pronounced. In addition, in the last decade, the AOD has noticeably increased for a few stations in the Far East, which is probably due to increased volcanic activity on Kamchatka .

Variations in the Aerosol Optical Depth Above the Russia

from the Data Obtained at the Russian Actinometric Network in 1976–2010 Years 9

summer, tropical air masses dominate here which are characterized by high contents of moisture and aerosol. The spring maximum is caused by snow cover melting and the

Fig. 5a gives some examples of time variations in the annual means of AOD for stations with negative and positive trends. In Fig. 7b, the examples of the time trends of the AOD annual values are supplemented by the corresponding variations in the flux of direct solar radiation (for the Sun's height *h*= 30°), which reach 100 W/m2 over the course of 35 years (3 W/m2 per year); estimates were obtained for two stations with the maximum and minimum means of AOD. Thus, the influence of a decreased aerosol load on the flux of direct solar radiation incident upon the land surface under clear skies is empirically estimated. For total radiation, this influence is less pronounced. And our estimate of the rate of a decrease in direct solar radiation does not contradict the satellite data (IPCC, Climate Change 2007) on the rate of a decrease in the flux of the total reflected (upward) solar radiation ( –0.18 ± 0.11) W/m2 per year (the ISCCP project) and (–0.13 ± 0.08) W/m2 per year (the ERBS project)) over the course of 1984–1999 and the assumption made in (IPCC, Climate Change 2007), that this is caused by a global decrease in stratospheric aerosol (the so-called phenomenon of "aerosol

At most observation sites, the atmosphere was purified of aerosol within the period under consideration. On the whole, for Russia, the trend of AOD variations is negative (Fig. 6); the absolute value of the trend (over 10 years) varies from (–0.05) to (+ 0.02) and increases generally from the south-west to the north-east of Russia. The mean of the relative trend accounts for (–14%) over 10 years, its maximum is 21% over 10 years, and its minimum is (– 35%) over 10 years at a determination coefficient of no more than 0. 5. (See also Table 1). It is evident that, in this case, a decrease in the AOD mean must be observed during the last 15 years of the whole region. The largest negative trends are observed at the Solyanka station (in the south of the Krasnoyarsk Krai), in Chita (Transbaikalia), Khabarovsk (Primorskii Krai), and in the south of European Russia. The combination of the two factors—global purification of the atmosphere from transformed volcanic aerosol and decreased anthropogenic forcing—forms the negative trends in these regions. Positive trends are observed in Arkhangelsk and the Far East (Kamchatka and Okhotsk), and almost zero trends are observed in western (station nos. 18, 19, and 20) Siberia. The positive (Arkhangelsk) and decreased negative (the indicated Siberian stations) trends may be caused by increased industrial emissions in these regions, an increase in the number and intensity of fires, and comparatively low-power volcanic eruptions (for example, in Kamchatka). The estimates of the AOD trends and integral transparency obtained by other authors (for example, Ohmura, 2006) were compared with our estimates earlier in (Plakhina et al., 2007). This comparison shows an agreement with the results presented in

replacement of the dominating arctic air masses by temperate or tropical air masses.

**5. Time variations in aerosol optical depth AOD** 

dimming").

this paper.

**Figure 4.** Spatiotemporal variations in AOD: (a) multiyear variations in the annual values of AOD for all 53 stations under consideration and (b) mean seasonal variations in AOD for all 53 stations under consideration.

The spatiotemporal inhomogeneities of the AOD annual values clearly reflect their causes (Fig. 4a): the peaks of the volcanic eruptions (El Chichon, 1982, and Pinatubo, 1991) and the tundra fires of the last decade in eastern Siberia, the frequency and intensity of which have increased due to climate changes. Fig. 4b shows variations in the mean annual cycle of AOD. The features of the AOD mean annual cycle for each concrete station are formed under the influence of seasonal variations in the character of air-mass transport to a given point from regions with different aerosol contents (synoptic processes) and seasonal variations in air temperature, humidity, and in the state of the underlying surface, in combination with an industrial load of some regions. The AOD maxima are, as a rule, observed in April and July– August, but the summer maximum is more pronounced at stations (No 4, 8, 9, 10, and 11) located in the south of European Russia. First of all, this is related to the fact that, in summer, tropical air masses dominate here which are characterized by high contents of moisture and aerosol. The spring maximum is caused by snow cover melting and the replacement of the dominating arctic air masses by temperate or tropical air masses.
