{'fraction_non_alphanumeric': 0.022963367960634227, 'fraction_numerical': 0.002733734281027884, 'mean_word_length': 5.224489795918367, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Contributing factors to Koshava wind characteristics

Koshava is a local wind usually observed in the cold part of the year over the large part of Serbia, parts of Romania, parts of Hungary, and east Croatia. The main characteristics of the Koshava wind are its high wind speed, southeasterly direction, persistence, and gustiness. This paper analyses the synoptic [Mediterranean cyclones (MCs) and Eurasian anticyclones (EAs)] as well as the mesoscale contributors to the Koshava wind. Time and spatial features of the pressure systems have been analysed using an automatic cyclone tracking scheme. The results show that the MCs and EAs that generate Koshava are approximately 1000 km away from the Koshava region. It is demonstrated that the strong anticyclones are the main trigger for the Koshava wind. Less than 3% of the Koshava winds occurred without the occurrence of either an anticyclone or a cyclone. The Synoptic Koshava Index (SKI), developed in this study and defined as the difference between the area‐averaged mean sea level pressures in the anticyclone and cyclone regions, has been shown to be a good indicator of the Koshava occurrence. Koshava has also been investigated from the perspective of the gap flow windstorm. The across‐mountain pressure difference, ΔP, is the most important mesoscale contributor to the Koshava characteristics. The across‐mountain potential temperature difference, Δθ, together with ΔP, can be successfully used to predict Koshava's occurrence. A simple (linear) probabilistic model for forecasting the Koshava mean hourly wind speed has been constructed. The results demonstrate that the occurrence of the Koshava wind can be predicted with the significantly higher accuracy than the Koshava mean hourly speed. The correlation between Koshava and winds at higher levels is small.