Severe hard rime accretion in the Far North of Russia: observations and modeling

• Published in: IOP Conference Series: Earth and Environmental Science
• Main Authors: Leonov, I I, Sokolikhina, N N
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: IOP Publishing 2022
• Subjects: Rime; nenets; Nenets Autonomous Okrug; Yamalo Nenets; Yamalo-Nenets Autonomous Okrug
• Online Access: http://dx.doi.org/10.1088/1755-1315/1023/1/012012; https://iopscience.iop.org/article/10.1088/1755-1315/1023/1/012012; https://iopscience.iop.org/article/10.1088/1755-1315/1023/1/012012/pdf

Abstract Severe weather means any hazardous meteorological phenomena which can cause significant damage, serious social disruption, or loss of human life. Such weather phenomena include thunderstorms, hurricanes, tornados, ice storms, and many others. The main purpose of this research is a study of formation mechanisms of rime accretion and methods for their prediction. This is necessary to forecast these phenomena and minimize their economic and other losses. This work is dedicated to a detailed study of an extraordinary case of formation of rime accretion in the territory of the Yamalo-Nenets Autonomous Okrug, which occurred in early January 2016. Numerical experiments are used for an analysis of various methods for predicting areas of possible ice accretion formation. For the numerical experiments, the atmospheric model WRF-ARW has been chosen. For a theoretical assessment of icing intensity, the Makkonen formula is used. The results of this research are as follows: the main mechanisms of ice accretion formation have been identified for the territory of the Far North of Russia. Numerical experiments with the WRF-ARW model have been successful and reproduced the main signs of rime accretion. The results show that the model has successfully reproduced the icing start time and the icing intensity distribution throughout the entire numerical experiment. The quality of the model's assessment of the mass of rime accretion is difficult to estimate from data of only two meteorological stations; however, the values obtained are close to the observed ones.