English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The trend analysis of meteorological time series has gained prominence in recent decades, the most common method being the so-called ‘linear analytical trend analysis’. Until the mid-1990s, trend analysis was commonly performed on non-homogenized data sets, which frequently led to erroneous conclusions. Nowadays, only homogenized data sets are examined, so it really is possible to detect climate change in long meteorological data sets. In this paper, the methodology of linear trend analysis is summarized, the way in which the model can be validated is demonstrated, and there is a discussion of the results obtained if unjustified discontinuities caused by changing measurement conditions, such as the relocation of stations, changes in measurement time, or instrument change occur. On the basis of an examination of records for the preceding 118 years, it is possible to state that both annual and seasonal mean temperature trends display a significant warming trend. In the case of homogenized data series, the change is significant over the entire territory of Hungary; in the case of raw data series, however, the change is not significant everywhere. The validity of the linear model is tested using the F-test, a task as yet carried out on the entire Hungarian data series, series comprising records for over 100 years. Furthermore, neither has a comparison been made of the trend data for raw data series and the homogenized data series with the help of information on station history to explore the causes of inhomogeneity.

To what extent does the detection of climate change in Hungary depend on the choice of statistical methods?