In-Cloud Icing - A case study at Fagernesfjellet, Norway using Weather Research and Forecasting model and observations

Abstract

Atmospheric icing poses significant challenges to infrastructure integrity and transportation safety, especially in mountainous regions such as Fagernesfjellet, Norway. This paper presents a comprehensive case study of in-cloud icing over Fagernesfjellet, leveraging hindcast data obtained through dynamic downscaling with the Weather Research and Forecasting (WRF) model alongside observational data. Spanning from October 1, 2022, to December 31, 2022, the study focuses on evaluating the performance of microphysical schemes in predicting icing rates, liquid water content and other hydrometeors. Various statistical analyses are employed to assess model accuracy and validate against field measurements. The findings highlight the proficiency of the WRF model in simulating in-cloud icing, with the Thompson scheme exhibiting better performance in replicating low icing rates threshold compared to alternative schemes while Morrison for high icing rates threshold. This study underscores the critical role of model physics selection in accurately assessing in-cloud icing conditions, offering valuable insights for icing prediction and infrastructure resilience efforts. Additionally, we utilize NEWA data to analyse icing climate from 2005 to 2018, and further validate WRF results against NORA3 data over a three-month simulation period.