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Abstract. A detailed spatial geodatabase of aufeis (or naled in Russian) within the Indigirka River watershed (305 000 km2), Russia, was compiled from historical Russian publications (year 1958), topographic maps (years 1970–1980s) and Landsat images (year 2013–2017). Identification of aufeis by late spring Landsat images was performed with a semi-automated approach according to Normalized Difference Snow Index (NDSI) and additional data. After this, a cross-reference index was set for each aufeis field to link and compare historical and satellite-based aufeis datasets. The aufeis coverage varies from 0.26 % to 1.15 % in different sub-basins within the Indigirka River watershed. The digitized historical archive (Cadastre, 1958) contains the coordinates and characteristics of 896 aufeis fields with a total area of 2064 km2. The Landsat-based dataset included 1213 aufeis fields with a total area of 1287 km2. Accordingly, the satellite-derived total aufeis area is 1.6 times less than the Cadastre (1958) dataset. However, more than 600 aufeis fields identified from Landsat images are missing in the Cadastre (1958) archive. It is therefore possible that the conditions for aufeis formation may have changed from the mid-20th century to the present. Most present and historical aufeis fields are located in the elevation band of 1000–1200 m. About 60 % of the total aufeis area is represented by just 10 % of the largest aufeis fields. Interannual variability of aufeis area for the period of 2001–2016 was assessed for the Bolshaya Momskaya aufeis and for a group of large aufeis fields (11 aufeis fields with areas from 5 to 70 km2) in the basin of the Syuryuktyakh River. The results of this analysis indicate a tendency towards an area decrease in the Bolshaya Momskaya aufeis in recent years, while no reduction in Syuryuktyakh River aufeis area was observed. The combined digital database of the aufeis is available at https://doi.org/10.1594/PANGAEA.891036.

Abstract The last comprehensive statistics of tornadoes in northern Eurasia (NE) were published more than 30 years ago. This paper introduces a new database of tornadoes in NE that spans from the tenth century to 2016. The database, compiled using various sources, contains 2879 tornado cases over land and water and includes tornado characteristics. Tornadoes are common for most regions of NE, with a density reaching four cases per 104 km2 in 1900–2016 in some regions. Tornadoes over land have distinct annual and diurnal cycles: they form mostly in May–August, with a maximum in June, and during daytime, with a maximum at 1700–1800 local time. Waterspouts form in all months with a maximum in late summer and mostly at 0900–1300 local time. Most tornadoes are weak and short lived. The Fujita-scale intensity is ≤F1 for 80% and ≥F3 for 3% out of all rated tornadoes. Half last less than 10 min. The average annual number of all tornadoes over land is around 150, including 10 and 2 tornadoes with ≥F2 and ≥F3 intensity, respectively. Annually, 1–2 tornadoes lead to casualties and result in 2.9 fatalities and 36.3 injuries. Despite the incompleteness of the dataset, our results show that tornadoes in NE, although being rare, are not as extremely rare as has been thought before. The results illustrate the substantial underestimation of tornado threat by the general public, researchers, and meteorologists, and unambiguously indicate the need for systematic assessments and forecasting of tornadoes by national weather services.

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Large-scale wildfires and windstorms are the most important disturbance agents for the Russian boreal forests. The paper presents an assessment of fire-related and wind-induced forest losses in the Ural region of Russia for 2000-2014. The assessment is based on the use of Landsat images,

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The author describes the methods and results of current climate change mapping in the Ural region. The maps of temperature and water vapor pressure dynamics (for 1951–2010) and also precipitation amount changes (for 1966–2010) are presented. The maps of temperature and water vapor pressure are created basing upon spline interpolation of weather stations data, taking into account altitude-dependent regression. The altitude gradient of temperature and water vapor pressure was estimated using reanalysis data. The maps of precipitation amount were created basing upon spline interpolation combined with multiple linear regression model. Altitude and large-scale slope and aspect are used as independent variables. Accuracy assessment is carried out by cross-validation method. Basing upon the created maps, it is shown that the average annual temperature increased by 0,7–1,2° between 1951–1980 and 1981–2010 throughout the Ural region. In the North-Western Ural (i. e. in Komi Republic) the rise of average annual temperature is less significant, than in other parts of the mentioned area. The increase of water vapor pressure is also observed across the Urals. The changes of precipitation amount between 1966– 1995 and 1981–2010 are multidirectional. In general, the precipitation amount increased in the western part of Ural. At the same time, the precipitation amount decreased in some regions of Eastern Urals.