EGU24-8702, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-8702
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessing the Performance of the Weather Research and Forecasting (WRF) Model in Simulating Atmospheric In-Cloud Icing Over Fagernesfjellet, Norway

Pravin Punde1, Yngve Birkelund1, Muhammad Virk2, and Xingbo Han2
Pravin Punde et al.
  • 1Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway (pravin.b.punde@uit.no)
  • 2Arctic Technology & Icing Research Group, UiT The Arctic University of Norway, Narvik, Norway

Atmospheric icing ensues when water droplets in the atmosphere freeze upon interacting with diverse objects, presenting substantial hazards to infrastructure and leading to disruptions in both road and air traffic. 

This study introduces a detailed analysis of in-cloud icing conducted specifically over Fagernesfjellet, Norway. Utilizing the Weather Research and Forecasting (WRF) model, ERA-5 data was employed for both initial and lateral boundary conditions. The simulation covers a three-month period from October 1, 2022, to December 31, 2022, with a grid spacing of 9,3,1 km.

Acknowledging the substantial influence of local terrain on icing conditions, the analysis prioritizes the highest model resolution. The determination of the icing load involves the utilization of a Makkonen ice accretion model, and the resultant values, alongside surface parameters, undergo validation against field measurements taken at Fagernesfjellet, Norway. The representation of supercooled liquid water (SLW) in numerical weather prediction (NWP) models is crucial for precise atmospheric icing forecasts. Hence, we conduct a comprehensive evaluation of the Thompson scheme's performance in simulating liquid water content (LWC) and, consequently, the icing load, along with general weather parameters associated with icing.

From our preliminary analysis, the WRF model showcases effectiveness in simulating in-cloud icing conditions. WRF adeptly reproduces crucial surface parameters such as temperature, pressure, relative humidity, wind speed, and direction. Nevertheless, there are discernible differences between the observed data and WRF results, particularly noticeable in the case of wind speed and direction.

How to cite: Punde, P., Birkelund, Y., Virk, M., and Han, X.: Assessing the Performance of the Weather Research and Forecasting (WRF) Model in Simulating Atmospheric In-Cloud Icing Over Fagernesfjellet, Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8702, https://doi.org/10.5194/egusphere-egu24-8702, 2024.