Abstract

Fog and low-level stratiform clouds have been identified as hazardous weather phenomena, resulting in various losses, including time, money, and, most importantly, human lives in aviation transportation. Fog and low-level stratus pose substantial risks to aviation, especially during takeoff, landing, and low-level flying, due to conditions of reduced visibility. Forecasting low-level stratiform clouds and fog is a challenging aspect of aviation meteorology due to the similarity in the mechanisms of their formation, complex and non-deterministic processes in the atmospheric boundary layer, and their high dependence on local conditions. Given these challenges, weather observations, a primary source of information on local meteorological conditions, can be utilized to establish statistical dependencies of fog/low-level stratus characteristics, enabling the differentiation of both phenomena and the improvement of their forecast accuracy. To find the characteristics of fog and low-level stratiform clouds and identify local dependencies for enhancing the forecast of these phenomena at Lviv Airport, Ukraine, three-hourly METARs information from the airport’s Meteorological Station for the period 2010-2020 were analyzed. Employing a statistical approach, the annual, seasonal, and diurnal distribution of fog and low-level stratiform clouds, along with their frequency distribution associated with various meteorological parameters, were determined. Applying a statistical approach, the empirical relationship between the occurrence of fog/overcast low-level stratus and a set of potential local predictors, namely 2 m air temperature and relative humidity, was identified. The results obtained can be instrumental in providing historical data to weather forecast models and improving the accuracy of forecasts for fogs and low-level stratus.

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