Climatology and Formation Environments of Heavy Snowfall Events in the Ural Region (Russia)

Heavy snowfall events in the Ural region have drawn significant attention due to their substantial frequency, the region’s relatively high population density and its developed network of roads and power lines. This study summarizes the main characteristics of the hazardous heavy snowfall (HHS) events (≥20 mm 12 h−1) that have occurred in the Ural region between 1981 and 2025, as well as in related synoptic-scale environments, for the first time. The dataset consists of 116 HHS reports, with 12-hourly snowfall intensities ranging from 20 mm to 47.6 mm. The main characteristics of these events (snowfall amount, spatial distribution, inter-annual and seasonal variability and trends, associated weather phenomena, and related damage) are examined based on the data from weather stations, the ERA5 reanalysis, scientific literature, and media reports. While there is no statistically significant trend in HHS events, the frequency of the most damaging late spring and early autumn snowfalls has decreased. Using 72 h backward trajectories according to the NOAA HYSPLIT model and the ERA5 reanalysis, we classified the HHS events into five types according to air mass origin, and performed a composite analysis for each type. The main finding is that 46% of HHS reports are related to cyclones forming over the Caspian and Aral seas, resulting in a higher frequency of HHS events to the east of the Ural Mountains compared to the western part of the region.

Authors

Institutions

Publication Details

Journal
Atmosphere
Published
2025-12-08
DOI
https://doi.org/10.3390/atmos16121386
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climatology and Formation Environments of Heavy Snowfall Events in the Ural Region (Russia)

Andrey Shikhov, N. A. Kalinin, Евгения Владимировна Пищальникова
Atmosphere
Meteorological Phenomena and Simulations
article

Climatology and Formation Environments of Heavy Snowfall Events in the Ural Region (Russia)

Andrey Shikhov, N. A. Kalinin, Евгения Владимировна Пищальникова
article en

Abstract

Heavy snowfall events in the Ural region have drawn significant attention due to their substantial frequency, the region’s relatively high population density and its developed network of roads and power lines. This study summarizes the main characteristics of the hazardous heavy snowfall (HHS) events (≥20 mm 12 h−1) that have occurred in the Ural region between 1981 and 2025, as well as in related synoptic-scale environments, for the first time. The dataset consists of 116 HHS reports, with 12-hourly snowfall intensities ranging from 20 mm to 47.6 mm. The main characteristics of these events (snowfall amount, spatial distribution, inter-annual and seasonal variability and trends, associated weather phenomena, and related damage) are examined based on the data from weather stations, the ERA5 reanalysis, scientific literature, and media reports. While there is no statistically significant trend in HHS events, the frequency of the most damaging late spring and early autumn snowfalls has decreased. Using 72 h backward trajectories according to the NOAA HYSPLIT model and the ERA5 reanalysis, we classified the HHS events into five types according to air mass origin, and performed a composite analysis for each type. The main finding is that 46% of HHS reports are related to cyclones forming over the Caspian and Aral seas, resulting in a higher frequency of HHS events to the east of the Ural Mountains compared to the western part of the region.

AtmosphereVol. 16(12)
Perm State University (RU)
Openalex Percentile: Top 57%
Meteorological Phenomena and Simulations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.