Prediction of In-Cloud Icing Conditions at Ground Level Using the WRF Model

AbstractIn-cloud icing on aircraft and ground structures can be observed every winter in many countries. In extreme cases ice can cause accidents and damage to infrastructure such as power transmission lines, telecommunication towers, wind turbines, ski lifts, and so on. This study investigates the potential for predicting episodes of in-cloud icing at ground level using a state-of-the-art numerical weather prediction model. The Weather Research and Forecasting (WRF) model is applied, with attention paid to the model’s skill to explicitly predict the amount of supercooled cloud liquid water content (SLWC) at the ground level at different horizontal resolutions and with different cloud microphysics schemes. The paper also discusses how well the median volume droplet diameter (MVD) can be diagnosed from the model output. A unique dataset of direct measurements of SLWC and MVD at ground level on a hilltop in northern Finland is used for validation. A mean absolute error of predicted SLWC as low as 0.08 g m−3...

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