Kilometer-scale simulation of atmospheric in-cloud ground icing over complex terrain in Norwegian Arctic

This study investigates in-cloud ground icing over Fagernesfjellet, a complex terrain site in northern Norway, using new kilometer-scale simulations from the Weather Research and Forecasting model (WRF) during the year 2022–2023. The WRF-derived icing results and meteorological parameters relevant to in-cloud icing are validated using measurement data (MEAS), with focus on model resolution and terrain height. Our findings indicate that WRF effectively represented the temporal evolution of icing events, with higher altitudes indicating more severe icing and an increased number of annual icing hours. However, in the current model setup, WRF underestimates the magnitude and variability of icing loads; an improvement in icing load amount is found when accurate terrain height point is used. The highest spatial resolution improved the simulation of key meteorological parameters, such as temperature and wind speed, but struggled with relative humidity and wind direction. Our study shows that high-resolution simulation and accurate terrain height are essential for improving atmospheric in-cloud ground icing simulations over complex terrain. • We report the first validation of high-resolution (1 km) WRF-simulated icing loads and meteorological variables over Fagernesfjellet, a complex terrain site in the Norwegian Arctic, based on 2022–2023 measurements. • A simplified model to compare measured icing load against WRF simulations. • Importance of high-resolution modelling for accurate atmospheric icing estimation. • Altitude-dependent icing assessment to improve icing predictions across different altitudes.

Authors

Institutions

Publication Details

Journal
Cold Regions Science and Technology
Published
2026-01-29
DOI
https://doi.org/10.1016/j.coldregions.2026.104851
Primary Topic
Icing and De-icing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Kilometer-scale simulation of atmospheric in-cloud ground icing over complex terrain in Norwegian Arctic

Xingbo Han, Yngve Birkelund, Pravin Punde, Muhammad S. Virk et al.
Cold Regions Science and Technology
Icing and De-icing Technologies
article

Kilometer-scale simulation of atmospheric in-cloud ground icing over complex terrain in Norwegian Arctic

Xingbo Han, Yngve Birkelund, Pravin Punde, Muhammad S. Virk, Trude Eidhammer
article en

Abstract

This study investigates in-cloud ground icing over Fagernesfjellet, a complex terrain site in northern Norway, using new kilometer-scale simulations from the Weather Research and Forecasting model (WRF) during the year 2022–2023. The WRF-derived icing results and meteorological parameters relevant to in-cloud icing are validated using measurement data (MEAS), with focus on model resolution and terrain height. Our findings indicate that WRF effectively represented the temporal evolution of icing events, with higher altitudes indicating more severe icing and an increased number of annual icing hours. However, in the current model setup, WRF underestimates the magnitude and variability of icing loads; an improvement in icing load amount is found when accurate terrain height point is used. The highest spatial resolution improved the simulation of key meteorological parameters, such as temperature and wind speed, but struggled with relative humidity and wind direction. Our study shows that high-resolution simulation and accurate terrain height are essential for improving atmospheric in-cloud ground icing simulations over complex terrain. • We report the first validation of high-resolution (1 km) WRF-simulated icing loads and meteorological variables over Fagernesfjellet, a complex terrain site in the Norwegian Arctic, based on 2022–2023 measurements. • A simplified model to compare measured icing load against WRF simulations. • Importance of high-resolution modelling for accurate atmospheric icing estimation. • Altitude-dependent icing assessment to improve icing predictions across different altitudes.

Cold Regions Science and TechnologyVol. 245
NSF National Center for Atmospheric Research (US), UiT The Arctic University of Norway (NO)
Openalex Percentile: Top 74%
Icing and De-icing Technologies
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.