Statistical Analysis of Categorical Time Series of Atmospheric Elementary Circulation Mechanisms - Dzerdzeevski Classification for the Northern Hemisphere

PLoS One. 2016 Apr 26;11(4):e0154368. doi: 10.1371/journal.pone.0154368. eCollection 2016.

Abstract

Northern hemisphere elementary circulation mechanisms, defined with the Dzerdzeevski classification and published on a daily basis from 1899-2012, are analysed with statistical methods as continuous categorical time series. Classification consists of 41 elementary circulation mechanisms (ECM), which are assigned to calendar days. Empirical marginal probabilities of each ECM were determined. Seasonality and the periodicity effect were investigated with moving dispersion filters and randomisation procedure on the ECM categories as well as with the time analyses of the ECM mode. The time series were determined as being non-stationary with strong time-dependent trends. During the investigated period, periodicity interchanges with periods when no seasonality is present. In the time series structure, the strongest division is visible at the milestone of 1986, showing that the atmospheric circulation pattern reflected in the ECM has significantly changed. This change is result of the change in the frequency of ECM categories; before 1986, the appearance of ECM was more diverse, and afterwards fewer ECMs appear. The statistical approach applied to the categorical climatic time series opens up new potential insight into climate variability and change studies that have to be performed in the future.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Atmosphere / analysis*
  • Forecasting
  • Models, Statistical*
  • Periodicity
  • Seasons
  • Time Factors

Grants and funding

The results were obtained through the research programme “Groundwater and Geochemistry” (P 0020) of the Geological Survey of Slovenia of Republic of Slovenia and through the bilateral project between Slovenia and Russia Federation BI-RU/12-13-024 and BI-RU/14-15-040 lead by Polona Vreča - Jožef Stefan Institute. All activities were financially supported by the Slovenian Research Agency.