The seasonality and day-to-day variation of near-surface temperature
patterns can greatly control nearly all physical and biological processes
though temperature predictions at such scales remain challenging. This paper
implements a simple analytical approach in
order to generate daily average temperatures which implicitly accounts for surface heating and drivers
through a comprehensive representation of station-based
temperature records on a universal standard calendar propagated by the earth’s
dynamics features. The modeled and observed pattern of daily temperatures
exhibits a close agreement with the level of strength agreement exceeding 0.56.
The extreme high and low values of the observed temperature patterns are
equally well captured although model underestimates
the probability of temperatures around the two modal peaks (~25.6℃ and
27.5℃). Additionally, a theoretical thermal-based division led to the identification of six seasons,
including two hot and cold periods along with two pairs of mixed hot-cold. The
theoretical division proposed here appears to be a good approximation for the
understanding of rainfall seasonality in this area.
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