Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia

• Published in: Global and planetary change Vol. 100; pp. 172 - 182
• Main Authors: Gocic, Milan, Trajkovic, Slavisa
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.01.2013; Elsevier
• Subjects: air temperature; autumn; Earth sciences; Earth, ocean, space; Exact sciences and technology; External geophysics; Hydrology; Hydrology. Hydrogeology; Mann-Kendall test; meteorological data; meteorological variables; Meteorology; relative humidity; Sen's slope estimator; Serbia; spring; statistical analysis; summer; trend analysis; vapor pressure; weather stations; Serbia; Southern Europe; Europe; Sen's slope estimator; Mann-Kendall test; meteorological variables; trend analysis; detection; atmospheric precipitation; meteorology; air; surface water; water vapor; temperature; humidity; seasonal variations
• ISSN: 0921-8181; 1872-6364
• DOI: 10.1016/j.gloplacha.2012.10.014

The annual and seasonal trends of seven meteorological variables were analyzed for twelve weather stations in Serbia during 1980–2010. The non-parametric Mann-Kendall and Sen's methods were used to determine whether there was a positive or negative trend in weather data with their statistical significance. The occurrence of abrupt changes was detected using cumulative sum charts and bootstrapping. In the present study, the increasing trends were indicated in both annual and seasonal minimum and maximum air temperatures' series. The relative humidity decreased significantly in summer and autumn, while the vapor pressure had a significant increasing trend in spring, summer and autumn. Besides, no significant trends were detected in summer and winter precipitation series. In general, the results of using the Mann-Kendall and Sen's tests demonstrated the good agreement of performance in detection of the trend for meteorological variables. ► The annual and seasonal trends of seven meteorological variables were analyzed. ► The datasets were collected from 12 weather stations from Serbia during 1980–2010. ► We used the non-parametric Mann-Kendall and Sen's methods. ► The trend methods used in this study demonstrated a good agreement of performance in trend detection.