Theoretical and Applied Climatology

, Volume 87, Issue 1–4, pp 185–199 | Cite as

A method to reconstruct long precipitation series using systematic descriptive observations in weather diaries: the example of the precipitation series for Bern, Switzerland (1760–2003)

  • U. Gimmi
  • J. Luterbacher
  • C. Pfister
  • H. Wanner


In contrast to barometric and thermometric records, early instrumental precipitation series are quite rare. Based on systematic descriptive daily records, a quantitative monthly precipitation series for Bern (Switzerland) was reconstructed back to the year 1760 (reconstruction based on documentary evidence). Since every observer had his own personal style to fill out his diary, the main focus was to avoid observer-specific bias in the reconstruction. An independent statistical monthly precipitation reconstruction was performed using instrumental data from European sites. Over most periods the reconstruction based on documentary evidence lies inside the 2 standard errors of the statistical estimates. The comparison between these two approaches enables an independent verification and a reliable error estimate.

The analysis points to below normal rainfall totals in all seasons during the late 18th century and in the 1820s and 1830s. Increased precipitation occurred in the early 1850s and the late 1870s, particularly from spring to autumn. The annual precipitation totals generally tend to be higher in the 20th century than in the late 18th and 19th century. Precipitation changes are discussed in the context of socioeconomic impacts and Alpine glacier dynamics. The conceptual design of the reconstruction procedure is aimed at application for similar descriptive precipitation series, which are known to be abundant from the mid-18th century in Europe and the U.S.


Precipitation Total Statistical Reconstruction Precipitation Series Documentary Evidence Town Hospital 
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.


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • U. Gimmi
    • 1
  • J. Luterbacher
    • 2
    • 4
  • C. Pfister
    • 3
    • 4
  • H. Wanner
    • 2
    • 4
  1. 1.Swiss Federal Research Institute WSLBirmensdorfSwitzerland
  2. 2.Institute of Geography, Climatology and MeteorologyUniversity of BernSwitzerland
  3. 3.Institute of HistoryUniversity of BernSwitzerland
  4. 4.National Center of Competence in Research (NCCR) ClimateSwitzerland

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