This article is part of preparing the way for later revelations about instrumentation defects.
Figure 1 (upper), Figure 2 (lower) computed mean insolation for horizontal surface at this exact location and weather parameters, no cloud.
Figure 1 (upper), Experimental work showing nearly daily temperature variation from expected, specifically designed to exclude diurnal but include detail variation at the fastest scale feasible. Time graticule at 10 days, data points at 12 hours. Surprisingly the July 1st hot period has vanished. Plots of other sites show a similar effect. The most frequent warm and cool periods of weather are brief and readily seen.
This computation will produce different values from the mean values computed from thermometer minimum and maximum data because data shape at other times is taken into account, min/max does not. The filter used is also windowed, leakage is negligible.
Extracting a climatology from just over a year of hourly data, the whole archive length here, is impossible by conventional means, nor are these available for all Met Office Datapoint stations, including that some are recent stations. The solution uses existing innovative software by the author which will non-discrete Fourier match data, in this case locked on the almost wholly dominant two terms, 12 and 6 months. Checking the results against published climatology on a few stations shows good agreement. No attempt has been made to extract an absolute climatology (a mean temperature) but is nevertheless in good agreement.
Evidence not shown here (Met Office data) points to high maxima tending to occur earlier in the year than the peak mean temperature.
Insolation is highest during June (figure 2). A time delay of a couple of months between insolation and mean peak is typical of sites. Exceptional temperature perhaps tends to be more about high elevation sunshine and clear skies: as the year progresses rainfall increases and sunshine decreases, see other works by the author on UK parameters where the annual variation is shown.
The shape of the annual variation varies considerably across the UK but this is a new work on 170 stations so much more can be investigated. For example in the far north the annual insolation curve is significantly asymmetric and so is the temperature.
Several oddities have turned up, unexpected variations which seem to have a pattern relating to station and station geographical location. Some of this may be related to UHI and similar thermal mass / water effects.
Heathrow shows some degree of one of the effects, the shape of the temperature builds up during the year. Bear in mind that high maxima from sunshine is immediate whereas high mean comes from thermal mass heat, so this kind of effect is normal but might sometimes be unnatural. A phase delay.
1. Dinurnal removal filter. This is a compromise giving reasonable rejection whilst not rejecting at two days and with tolerable impulse response. Interpolating over single or a few missing data points is accepted as-is, longer periods have been linearly interpolated. These are human calls where the intended result context must be considered.
Output data sample points at 12 hours, therefore Nyquist requires zero at
>= <= 24 hours. Response at 48 hours is 0.86, at 60hr, 0.97
Readers who are not familiar with filtering:, counter intuitively no data is lost as such, the process here is a trade between time resolution and amplitude resolution which becomes finer, if invisible on plots. This process is not communicative, irreversible.
The intended effect is reducing a huge number of data points and removing the large day/night change. What remains is the general variation taking into account the daily change, eg. a hot day with cold night cancels and so on.
Post by Tim