Abstract

In this study over the Asian territory of Russia (ATR) (45° N–80° N, 60° E–180° E) for the period of 1979–2010 the temporal variability of the surface air temperature field was investigated. There are several climatic factors which can influence temperature variability including radiative balance at the top of atmosphere (TOA), heat balance at the surface, total cloud cover, and large-scale atmospheric circulation in the Northern Hemisphere. The contribution of these factors to temperature variability is also investigated. It was found that during the past decade, over the ATR, the process of warming prevails mainly in the warm season, but in the cold season it is either not as marked or there is cooling instead. In the winter season there is a positive relationship between temperature anomalies and anomalies in cloudiness, effective radiation, and the Arctic Oscillation (AO) index. During the same period, a negative relationship between anomalies of temperature and anomalies of net radiation at the TOA, net shortwave radiation at the surface, and the Scandinavian (SCAND) index was observed. In the summer season, the relationship between temperature and cloudiness becomes negative and the relationship between temperature and atmospheric circulation indices decreases. For the period 2001–2010, radiative fluxes obtained from reanalysis data sets Japanese Reanalysis Data (JRA-25) and Modern Era-Retrospective Analysis for Research and Applications (MERRA) were compared to satellite remotely sensed data project Clouds and the Earth’s Radiant Energy System (CERES). It was found that there is a good agreement between estimates of the net radiation at the TOA calculated using reanalysis data and satellite data: the difference is about 1.5 W m−2 and the correlation coefficient is more than 0.7. As for the comparison of radiative fluxes estimates at the surface for clear sky, there is less difference between MERRA and CERES. So, during the period 2001–2010 the relation between atmospheric circulation and surface air temperature variability increased in winter months. Obtained regression models allow us to describe from 27% to 82% of temperature variability in different months if we take into account both circulation and radiative factors.

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