Jump point identification in hydro-meteorological time series by crossing methodology

Şen Z.

Theoretical and Applied Climatology, vol.144, no.1-2, pp.769-777, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 144 Issue: 1-2
  • Publication Date: 2021
  • Doi Number: 10.1007/s00704-021-03576-2
  • Journal Name: Theoretical and Applied Climatology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, IBZ Online, PASCAL, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, CAB Abstracts, Environment Index, Geobase, Index Islamicus, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.769-777
  • Keywords: Discharge, Jump point, Lake level, Rainfall, Statistical analysis, Time series, Upcrossing
  • Istanbul Medipol University Affiliated: Yes


The climate change impact appears as a decreasing or increasing monotonic trend in hydro-meteorology time series records due to greenhouse gas (GHG) emissions causing to global warming and climate change impacts. On the other hand, there may be abrupt changes in the form of jumps in these series due to natural and engineering activities. Although trend identification methods are rather common in the literature, jump determination conventional methodologies are rather rare and their applications present some restrictive asumptions like the serial independence and normal (Gaussian) probability distribution function (PDF). The methodology presented in this paper is away from each of such assumptions and it depicts the minimum number of upcrossing along horizontal truncation levels within the time series variation domain. The applications of the methodology are given for annual Danube River discharge records, Romania; New Jersey rainfall and temperature records, USA; monthly rainfall records and Van Lake level fluctuations, Turkey.