Mesoscale Modelling of Waterspouts

Abstract

Wind energy is becoming an important renewable energy source. An increased number of offshore wind farms are constructed due to the relatively higher wind speeds. Besides, compared with the land, the ocean areas offer more empty space for the installation of wind turbines. In recent years, several governments in Europe have the plan to expand their countries’ wind farms over the North Sea area. With this surge in the development of offshore wind farms, extreme weather events over the sea pose threats to the installations. A waterspout is one of such phenomenon of concern.

In this study, we simulated and characterized the atmospheric conditions associated with two waterspout events observed recently over the North Sea. These cases were selected from the European Severe Weather Database. Various types of observational data, including radiosondes, radar reflectivities, satellite imageries, lighting maps, and floating liar-based wind profiles, were utilized for detailed characterization. Atmospheric circulation patterns associated with waterspouts were deduced from surface-level and upper-air synoptic charts. A mesoscale model, called the Weather Research and Forecasting model, was used for simulations with a high spatial resolution of 1 km. We used five different parameterizations of varying complexities to quantify the sensitivity of the simulated results with respect to cloud microphysics. A number of meteorological variables and indices (e.g., thermodynamic indices, wind shear, vertical velocity, reflectivity) are extracted from the simulations and compared with the observational data. In general, our results are in agreement with the findings from previous studies. For instance, we have found that a double moment microphysics parameterization produces more realistic results in comparison with a single moment one. However, we have noticed that our simulated results fall outside the range specified by the so-called Szilagyi waterspout nomogram. This nomogram was initially proposed based on observational data from the Great Lakes region and is widely used by the operational meteorologists. Based on the results, updating this nomogram is needed with additional observational and simulated data from the North Sea region.