Theoretical and Applied Climatology

, Volume 121, Issue 1–2, pp 167–177 | Cite as

Trends in precipitation indices in Croatia, 1961–2010

  • Marjana Gajić-Čapka
  • Ksenija Cindrić
  • Zoran Pasarić
Original Paper


Precipitation data from the period 1961–2010 and from a dense rain-gauge network over Croatia is analysed for spatial characteristics of trends in precipitation amounts and precipitation indices. Besides large spatial variability, the area is characterized by large temporal (seasonal) variability. Thus, analysis is performed on annual and seasonal scales over seven predefined subregions. Ten precipitation indices are selected to assess the intensity and frequency of extreme events as well as their contribution to annual and seasonal precipitation changes. The results reveal that the changes in annual and seasonal amounts are predominantly weak. A significant trend is detected only for annual amounts (negative) in the mountainous region and for summer (negative) in the mountainous littoral, mountainous region and central hinterland. A significant positive trend for autumn appears in eastern mainland. Negative trends in summer are associated with a decrease in frequency of moderate wet days, in maximal 1- and 5-day precipitation and in an increase in light precipitation. A negative annual trend is mainly caused by a decrease in frequency of very wet days and their contribution to the total precipitation. A positive autumn trend is associated with more very wet days and an increase of their contribution to the total precipitation as well as an increase in maximal 1- and 5-day precipitation. This study complements the existing analysis of five Croatian secular data series of extreme precipitation indices by involving the whole precipitation dataset since the mid-twentieth century and fills the gap present in the trend assessment of precipitation trends in Mediterranean and Europe.


Mountainous Region Daily Precipitation Precipitation Amount Precipitation Extreme Precipitation Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been partly realized in the framework of HyMeX project and supported in part by Croatian Sciece Foundation under the project 2831. The authors wish to thank the three anonymous reviewers for the in-depth review of the paper and for the helpful comments.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Marjana Gajić-Čapka
    • 1
  • Ksenija Cindrić
    • 1
  • Zoran Pasarić
    • 2
  1. 1.Department for Climatological Research and Applied ClimatologyMeteorological and Hydrological Service of CroatiaZagrebCroatia
  2. 2.Geophysical Department, Faculty of ScienceUniversity of ZagrebZagrebCroatia

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