Lakatos, L., Sümeghy, Z., Soltész, M., Szabó, Z., & Nyéki, J. (2012). Spatial and temporal variation of extremely low minimum temperatures in Hungary during the period between 1951 and 2010. International Journal of Horticultural Science, 18(2), 75–80. https://doi.org/10.31421/IJHS/18/2/1037
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
For this study, data of 16 meteorological stations have been processed over a period of 60 years with the purpose to reveal the spatial and temporal structure of the frequencies of absolute extreme minima in Hungary with special reference to the surmised global rise of temperatures on a worldwide scale. In the main areas of fruit growing, the monthly or seasonal absolute temperature maxima and minima are presented during the 60 year-long period and projected on the geographical map. For the main fruit- and vegetable growing regions the probability of winter- and late frosts is of prime interest. The time series of extreme temperatures though did not prove signifi cant changes over the period observed, but the information upon changes and their tendencies is a precious tool being utilised in planning, choice of adequate varieties for a longer period of time in the future. The deleterious winter frosts experienced in fruit production is not a consequence of a sole drop to a minimum temperature, but of an earlier period of mild temperatures during the winter, which sensibilised the trees. Frequent and extreme variations of temperatures may cause troubles at any time during the year and reduce the yields conspicuously. We ought to get familiar with the hazards of our climate and fi nd optimal solutions to mitigate the damages expected. The seasonal and monthly distribution projected on the geographical map we can follow up also the spatial relations and the signifi cance of their occurrence. Coeffi cients of variation between meteorological happenings at different localities facilitate the calculation of the probability of risks on the surrounding areas.