Fog is a very important and complex atmospheric phenomenon of the utmost importance for the environment and for human society. For practical reasons, fog occurrence is observed regularly at meteorological stations worldwide. Decreasing trends in fog frequency reported from numerous regions have been often associated with either decreasing pollution or climate change, including increasing temperature and changes in atmospheric circulation. We have examined the data on fog occurrence from twelve Czech sites representing different environments (urban, rural, mountain), geographical areas, and altitudes across the country. For our analysis we used long-term records from the time period of 1961-2018, covering both the ambient air's heavily polluted periods of the 1970s and 1980s and the cleaner period, following the adoption of new, more stringent legislation and effective countermeasures after the 1990s. We applied a generalised additive model (GAM) framework as a flexible, semiparametric regression approach to address nonlinear trend shapes in a formalised and unified way. In particular, we employed a penalised spline approach with cross-validated penalty coefficient estimation. Our study confirmed non-linear behaviour for both year-to-year trends and annual seasonality. Our results showed further that over the analysed, almost sixty-year period, fog occurrence has decreased significantly at all the examined sites, though the pattern of the long-term change differed among individual sites. Moreover, we have found significant seasonality in fog occurrence, though it is different at individual sites. Furthermore, apart from the overall annual fog probability change over the years, at some sites the fog's seasonal profile has also deformed substantially over the long term.
Keywords: 1961–2018; Fog; GAM; Long-term trends; Semiparametric statistical modelling.
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