A short note on quantifying and visualizing yearly variation in online monitored temperature data

Kauermann G, Mestekemper T (2012)
Statistical Modelling 12(2): 195-209.

Journal Article | Published | English

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Abstract
The paper demonstrates how seasonal variation in sequentially arriving temperature data can be visualized by the specification of landmarks and subsequent time warping. We exemplify the idea with water temperature data from the river Wupper in northwestern Germany and with air temperature data from Berlin, Germany. Landmarks are thereby based on temperature thresholds. The method allows to assess whether the seasonal variation is running ahead or behind the average.
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Kauermann G, Mestekemper T. A short note on quantifying and visualizing yearly variation in online monitored temperature data. Statistical Modelling. 2012;12(2):195-209.
Kauermann, G., & Mestekemper, T. (2012). A short note on quantifying and visualizing yearly variation in online monitored temperature data. Statistical Modelling, 12(2), 195-209.
Kauermann, G., and Mestekemper, T. (2012). A short note on quantifying and visualizing yearly variation in online monitored temperature data. Statistical Modelling 12, 195-209.
Kauermann, G., & Mestekemper, T., 2012. A short note on quantifying and visualizing yearly variation in online monitored temperature data. Statistical Modelling, 12(2), p 195-209.
G. Kauermann and T. Mestekemper, “A short note on quantifying and visualizing yearly variation in online monitored temperature data”, Statistical Modelling, vol. 12, 2012, pp. 195-209.
Kauermann, G., Mestekemper, T.: A short note on quantifying and visualizing yearly variation in online monitored temperature data. Statistical Modelling. 12, 195-209 (2012).
Kauermann, Göran, and Mestekemper, Thomas. “A short note on quantifying and visualizing yearly variation in online monitored temperature data”. Statistical Modelling 12.2 (2012): 195-209.
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