**Author details**

26 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

(Grinsted et al., 2004; Jevrejeva, 2003)

**9. Conclusions** 

estimations:

The continuous WT (wavelet transformation) expands the time series into time frequency space. Cross wavelet transform (XWT) finds regions in time frequency space where the time series show high common power. Wavelet coherence (WTC) finds regions in time frequency space where the two time series co-vary (but does not necessarily have high power); See

The application of the AOD and T estimationtechnique for processing the results of observations at the Russia actinometric network stations allows obtaining qualitatively new and detailed information on the level of aerosol content of the atmosphere in separate regions and in Russia as a whole. Our analysis has made it possible to formulate the following conclusions about the spatiotemporal distribution of AOD over Russia. The spatial distribution of the AOD values averaged over the 35-year period underconsideration generally corresponds to the model of global aerosol distribution over Eurasia, which is represented in the IPCC third and fourth reports. This is manifested in the AOD decrease from the southwest to the northeast in the presence of regions with continuous increasing aerosol turbidity in southwestern and southeastern Russia. Against this background, regions with increased troposphere aerosol loads are pronounced that have been more noticeable under the global purification of the atmosphere from the stratospheric aerosol layer that started in 1995. These troposphere sources are related either to an anthropogenic load (cities in southern Russia, western Siberia, and Primorskii Krai) or to forest and tundra fires in Siberia, in particular, at the Tura station in the Evenki Area. One more cause of the decreased transparency in the atmosphere over eastern Russia, which is manifested in the annual means of AOD, is the volcanoes of Kamchatka. On the whole, for Russia, the trends of multiyear variations have been negative in the last decades. However, there are stations at which the AOD trends are positive; this is particularly true of the stations of Kamchatka and the Far East.We have ascertained the peculiarities of spatial variations in the air turbidity factor in summer 2010 year in comparison with the long-term average spatial variations, which have been manifested in both distribution character and the value of the anomalies of the turbidity factor at ETR. Also we have ascertained the peculiarities of spatial and seasonal variations in the air turbidity factor T and aerosol optical depth AOD in Trans-

Baikal and Central Siberia region of RF for the year and different season

model and to the estimates obtained from satellite data (0.16);

The analysis of AOD variationsduring the last 35 years shows the following concrete

1. Total averaged AOD over all stations and the whole period under study (0.14) is very close to the annual mean global AOD value (0.14) calculated from the ECHAM-HAM

2. Maximum annual mean AOD (0.29) is reached in Krasnodar (№ 4) and the minimum one (0.07) is observed at the "aerosol pure" station of Srednekolymsk (№ 51). The

**Notice:** 

Inna Plakhina *Oboukhov Institute of Atmospheric Physics, RussianAcademy of Science, Russia* 
