Climatic Change

, Volume 156, Issue 3, pp 385–404 | Cite as

Influence of instrumentation on long temperature time series

  • Fiorella Acquaotta
  • Simona FratianniEmail author
  • Enric Aguilar
  • Guillaume Fortin


In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspé Peninsula, a region of Canada. They have 6 years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+ 10%) and extremely warm (+ 35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.



This research was developed in the framework of the project Nexdata_Nextsnow (national coordinator, V. Levizzani; unit scientific responsible, S. Fratianni). We greatly thank the Ministry of Sustainable Development, Environment and Fight against Climate Change (MSDEFCC) (Province of Quebec) for providing the weather data for the Gaspé Peninsula area. The authors would like to thank Jeremy Hayhoe and Elisabeth Marchand for proofreading assistance.


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Earth SciencesUniversity of TorinoTurinItaly
  2. 2.Centro Interdipartimentale sui Rischi Naturali in Ambiente Montano e Collinare, NatRiskTurinItaly
  3. 3.Center for Climate Change (C3)Universitat Rovira i VirgiliTarragonaSpain
  4. 4.Département d’histoire et de géographieUniversité de MonctonMonctonCanada

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