Investigation of the Regularities of the Influence of Meteorological Factors on Avalanches in Eastern Kazakhstan

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F25%3A00143178" target="_blank" >RIV/00216224:14310/25:00143178 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2073-4433/16/6/723" target="_blank" >https://www.mdpi.com/2073-4433/16/6/723</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/atmos16060723" target="_blank" >10.3390/atmos16060723</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Investigation of the Regularities of the Influence of Meteorological Factors on Avalanches in Eastern Kazakhstan

Popis výsledku v původním jazyce

This paper studies the influence of meteorological factors on avalanche occurrence in East Kazakhstan using modern data analysis methods. A dataset of 111 avalanche events in nine avalanche-prone areas of the region, recorded between 2012 and 2023, was compiled. Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. During the analysis of meteorological conditions preceding avalanches at nine avalanche-prone areas in Eastern Kazakhstan, using PCA (Principal Component Analysis), the main weather factors affecting avalanche formation were determined. Clustering of 111 avalanches using the K-Means method allowed the identification of four scenario types: gradual snow accumulation without wind (33 cases), upper layer thawing due to warming (34), high snow cover (28), and storm impact (16). The DBSCAN method revealed two anomalous cases related to extreme snow depth. Correlation analysis revealed significant relationships between avalanches and meteorological parameters such as air temperature, snow cover depth, wind speed and direction, precipitation, and relative humidity. Correlation analysis revealed both negative and positive relationships between meteorological parameters. Principal component analysis identified the most significant variables affecting avalanche activity, with temperature, snow cover height, and wind making the greatest contributions. Cluster analysis demonstrated that avalanches could occur under different combinations of weather conditions within the same areas, confirming the complex nature of avalanche-forming processes. The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.

Název v anglickém jazyce

Investigation of the Regularities of the Influence of Meteorological Factors on Avalanches in Eastern Kazakhstan

Popis výsledku anglicky

This paper studies the influence of meteorological factors on avalanche occurrence in East Kazakhstan using modern data analysis methods. A dataset of 111 avalanche events in nine avalanche-prone areas of the region, recorded between 2012 and 2023, was compiled. Primary data on avalanche dates were obtained from the Department of Emergency Situations of East Kazakhstan Region (DES EKR), and meteorological data were sourced from the Kazhydromet website. Descriptive statistics, correlation analysis, principal component analysis (PCA), as well as K-means clustering and DBSCAN algorithms, were used for the analysis. During the analysis of meteorological conditions preceding avalanches at nine avalanche-prone areas in Eastern Kazakhstan, using PCA (Principal Component Analysis), the main weather factors affecting avalanche formation were determined. Clustering of 111 avalanches using the K-Means method allowed the identification of four scenario types: gradual snow accumulation without wind (33 cases), upper layer thawing due to warming (34), high snow cover (28), and storm impact (16). The DBSCAN method revealed two anomalous cases related to extreme snow depth. Correlation analysis revealed significant relationships between avalanches and meteorological parameters such as air temperature, snow cover depth, wind speed and direction, precipitation, and relative humidity. Correlation analysis revealed both negative and positive relationships between meteorological parameters. Principal component analysis identified the most significant variables affecting avalanche activity, with temperature, snow cover height, and wind making the greatest contributions. Cluster analysis demonstrated that avalanches could occur under different combinations of weather conditions within the same areas, confirming the complex nature of avalanche-forming processes. The results emphasize the need for an integrated approach to avalanche forecasting that accounts for the multi-parametric interactions of meteorological factors, and may contribute to the improvement of avalanche risk monitoring and mitigation systems in mountain regions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10500 - Earth and related environmental sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Atmosphere

ISSN

2073-4433

e-ISSN

2073-4433

Svazek periodika

16

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

22

Strana od-do

1-22

Kód UT WoS článku

001515310600001

EID výsledku v databázi Scopus

2-s2.0-105009104146