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On the min–max estimation of mean daily temperatures

  • Anastasios A. TsonisEmail author
  • Xinnong Pan
  • Geli Wang
  • Catherine Nicolis
Article

Abstract

Modern data analyses of hourly temperature records reveal the existence, in addition to the daily cycle, of multiple forcings of different frequencies. As a result the routine approach of estimating daily local mean temperature directly from the average of the minimum and maximum is heavily compromised. A simple dynamical model subjected to two periodic forcings of different frequencies, amplitudes and phases is solved analytically and shown to induce substantial deviations from the min–max method that depend crucially on the values of the parameters involved.

Keywords

Mean daily temperature Slow feature analysis Driving forces 

Notes

Acknowledgements

Part of this work was supported by the National Key R&D Program of China (2017YFC1501804), the National Natural Science Foundation of China (91737102 and 41575058).

Supplementary material

382_2019_4757_MOESM1_ESM.docx (5.8 mb)
Supplementary material 1 (DOCX 5954 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Anastasios A. Tsonis
    • 1
    • 2
    Email author
  • Xinnong Pan
    • 3
    • 4
  • Geli Wang
    • 3
  • Catherine Nicolis
    • 5
  1. 1.Department of Mathematical Sciences, Atmospheric Sciences GroupUniversity of Wisconsin-MilwaukeeMilwaukeeUSA
  2. 2.Hydrologic Research CenterSan DiegoUSA
  3. 3.Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO)Institute of Atmospheric Physics, Chinese Academy of SciencesBeijingChina
  4. 4.University of Chinese Academy of SciencesBeijingChina
  5. 5.Institut Royal Meteorologique de BelgiqueBrusselsBelgium

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