On the min–max estimation of mean daily temperatures
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.
KeywordsMean daily temperature Slow feature analysis Driving forces
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).
- Wiskott L (2003) Estimating driving forces of nonstationary time series with slow feature analysis. http://arxiv.org/abs/cond-mat/0312317/