Annual and seasonal ANOVA and trend analysis of sub-daily temperature databases in Hungary

Abstract

Commonly studying climate is gaining more and more space thanks to the expansion of the tools of statistical climatology and the development of the informatical background. Trend analyses of annual and seasonal mean temperature values clearly show that the Hungarian values are mostly in line with the global trend, and in some cases exceed it. Since a sufficient number of measurements are only available from the 1970s, we used hourly temperature values (03 UTC, 09 UTC, 15 UTC, 21 UTC) of the period 1971–2020 for station data series in Hungary for the trend analysis. In order to make the examined datasets sufficiently representative, we homogenized the station data series, filled in data gaps, and performed quality control using the MASH software. To ensure spatial representativeness, we interpolated the homogenized station data onto a dense, regular grid network with the MISH system. In addition, we used the ANOVA method to examine the expected values, standard deviations assigned to the hourly values, and we analyzed on maps how the values within the day changed in each region over 50 years.