Soil, temperature and moisture

I started collecting soil temperatures in a randomly selected part of the back yard in August 2012 in an attempt to understand why beetroot was reluctant to germinate in April and May, but was quite reliable during July and August.  For no better reason than it was a convenient time to sit in the garden, the temperatures were measured around sunset on a Sunday afternoon.  Whilst this was convenient and consistent with regard to forming a time series, it was poor experimental design, by sunset the soil was usually warm, so on an April afternoon it was probably 10 deg. C, warm enough for some native english species to germinate.

One day in April, I had occasion to make frequent visits to the garden from early morning to late evening to make use of the time I decided to measure the soil temperatures over the course of the day.  The graph from this day's activity was quite instructive:

This shows that the variations in soil temperature during the day are much greater than that of the air above it. A crude extrapolation suggests that the temperature of the topsoil (0.1m) might have been from 2 - 16 deg. C, and for the two centimetres where seeds are sown could have been much greater.  During the day, the soil is warmed by the sun, during a clear night it experiences radiative cooling.

I had an attempt at taking soil temp measurements during the day on 25 July when the weather had been warm and dry for several days.  This exercise came to an abrupt end around 14:00 when a lone shower of heavy rain arrived.  The temperatures that were collected at a depth of 0.1 are shown in the graph below:

The maximum air temperature was around 25 deg. C when the soil was noticeably warmer than the air above it, it looks unlikely that the soil temperature fell to less than 10 degrees overnight.  When the surface temperature is high, it is clear that the top .01m of soil starts to loose moisture rapidly.

Do the low night time temperatures during April halt germination?

I'm new to gardening and a little lazy, so my method of sowing is to rake the soil and remove the building rubbish that abounds in the garden and then plant the seeds in a two centimetre groove formed with my index finger.  Over a few weeks it became clear that there were significant variations in moisture content.  The human body is a good measuring device for all sorts of things, e.g. solar irradiance, wind speed, humidity, air quality and soil moisture content to name but a few, the downside is that it does not produce graphs.

Over a few days I collected three soil samples from a bit of the garden that escapes watering, each sample was about 200gm (a half dog food tin), these were left to dry in the sun.  The moisture content being estimated from weight of soil at the time it was collected and its weight after drying, the resulting numbers were then turned into a graph:

The sample collected after a hot day may have been inadvertently watered, so it could be an over estimate.  So as for temperature, there are considerable fluctuations in soil water content over a short time interval.  And the lesson from this, make sure newly sown seeds are frequently watered until the plants are robust enough to withstand the turbulent environment that is the topsoil.  I think I was taught that at school.

A very short history DC in the home

Except for the washing machine and the vacuum cleaner which live in the kitchen, the native voltage of electrical things in other rooms is or could be low voltage dc.  We're slowly migrating to LED lighting which seems to have a native voltage of around 3 volts, so each lamp has circuitry which drops the voltage from 240 volts AC to a low DC one.  The efficiency of this conversion process has increased in recent years as transformers and bridge rectifiers have given way to more sophisticated circuits.  However, there is still a small loss and cost of LED bulbs and similar devices includes the necessary circuitry.  This has caused me to wonder if there are any advantages associated with a low voltage domestic distribution system, it makes sense to deliver electricity to the home as high voltage AC, but most of it gets used as low voltage DC.  Most electrical storage devices are DC, if you start adding 5 - 10 kwh of storage to a household system, is it easier to do this with DC distribution, otherwise there needs to be an inverter on the output end of the storage which incurs further losses and costs.

This is not wholly relevant to a modern household, but in the process of renovating my Edwardian semi I have unearthed the remains of a DC electrical system.  The house was built in 1901 and was lit by a mixture of gas mantels and oil lamps.  The remains of the pipes that distributed gas around the house can be found under the floorboards.  The location of the burners is often marked by a blanking plug, sadly the piping is too small to be used as the conduits for electrical cable.  I'm guessing, but mains electricity was probably installed sometime between 1920 and 1930 and there have been three, possibly four generations of wiring since then.  The first wiring consisted of fabric insulated wires kept apart by channels in a wooden conduit, at some point these were replaced by what appears to be lead cased cables, fortunately these have been replaced by modern PVC insulated cables.

Oddly, when the house was built it had a DC system of sorts.  This had two functions, one of which is still in use today.  The two main downstairs room each had a button which agitated an indicator system in the kitchen to alert the live-in cook/housekeeper of someone's need of something or that the front door needed answering.  This is neither a large or grand house and I regularly walk to the kitchen to make tea without suffering excessive fatigue.  When the indicator board was removed, possibly because of the lack of a servant to respond, it was replaced by a make-and-break electric bell operating off a 6 volt battery.  Yet again, this is a guess, the indicator board might have been powered by a lead acid accumulator.

There are some vague family memories of accumulators, mainly related to pre-war radios.  Early valve radios had two batteries, one known as the high tension battery which provided the potential for the anode with a voltage of between 40 and 120 volts, the current drain was low so they lasted a long time, but they were expensive.  The second battery known the low tension supply provided between 3 and 6 volts to heat the cathode which drew a much higher current, often accumulators provided this supply.  The younger members of the family had to carry these things to a local shop where they were charged up for a few coppers before being dragged back.

Accumulators must have been mainstream technology before WW2 as even my non-technical family seemed to have working knowledge of the things (as a boy, I was told not to stand on electric cables as the current could not flow, there is little to suggest this was a joke played on a child).  I have no idea how this conversation started, but I was chatting to a lady, maybe a little older than myself who in her youth had helped her father who was a motor mechanic refurbish batteries.  She described scraping out the old sealant so the plates could be removed, these where held together by bolts so they could be separated, cleaned an refilled after which the battery was resealed. The non resealable accumulators required regular checks for both the level of fluid and its specific gravity.

Its stretching a point, but there is some historical basis for the concept of a low voltage home.

But clouds got in my way

I'm old enough to remember when software came with manuals bound up in ring binders which allowed pages to be replaced as errors were found, bugs removed and features inserted.  Not a few of these volumes had chapters prefaced with a quote from "Alice in Wonderland" often without any context.  Having contributed to software documentation I will confess seeking out displacement activities such as the hourly mug of coffee, routine admin chores and listening to the radio, maybe I should have delved into poetry and and attempted to engage my reader (assuming that there ever was one).  Another useless fact, all modems in the 1970's were called Gandalf.

Over the past few months, I've been up working my way through a diverse collection of routines and attempting to package them up into commented Python modules.   The comments include a description of the functionality and a reference which points to source of an algorithm.  This usually takes longer than writing the code, but less time than rewriting it when the re-use event fires.  I'm also contemplating adding some poetic quotes to the comments.

I was revisiting the code which produces these cloud height and extent diagrams (which is written in VB.Net) when I heard the radio playing Joni Mitchell's "Both Sides Now" and thinking these graphics were a poor substitute for "Rows and flows of angel hair, And ice cream castles in the air, And feather canyons everywhere...."

Clouds have a significant effect on the output of solar devices.  At the time of writing during the afternoon of an overcast July day, I guess the solar irradiance is around 250 watts/m2, two weeks ago when the sky was almost clear of cloud, it was closer to 850 watts/m2 or in human terms frowns and smiles.   The ideal place to put a solar device, but possibly not to live if you like sea breezes, is a hot dry desert, the clear sky irradiance is high and the number of clouds few.  This is illustrated in the diagram below:

Each circle is a pie chart showing the extent of the cloud cover over a given month for a given height interval.  The dark slices denote an overcast sky and the light ones that there are just a few clouds.  Visually this means the darker the pie, the more clouds in the sky.  The yellow pies show the proportion of clear sky.  This example is for a desert location with lots of clear sky, when clouds do appear most of them are high in the sky and in general, high level cloud causes less attenuation of solar irradiance than low level ones.

Compare this with a plot for a temperate maritime climate, the most striking difference is that most of the cloud is low level, in the south of England this frequently overcast stratus in winter and few and scattered cumulus in summer (except to day which is just dull).  The intervals of clear sky are much shorter than in the desert and there just a lot more clouds.

These diagrams do not take into account the seasonal variations in solar irradiance due to Sun-Earth geometry which cause the irradiance to be significantly lower in winter than summer.

The source data for these plots is Metar reports which are designed to facilitate the safe operation of aircraft, but can also be applied to solar energy.  The plot is based on the highest reported layer of cloud.

At the risk of going off an a tangent, most of this blog was written using a Raspberry Pi.  This was acquired for an energy management project, but is proving to be an effective alternative to my laptop.  I have not done any serious energy analysis, but it is quiet (no cooling fan) and nothing is warm to the touch, so there is little heat dissipation.  About twenty years ago when I first started writing software in this room, the four computers where the heating system, now I have to light a fire in winter to keep warm.

Cross Correlation - Clear Sky Detection

Auto correlation and cross correlation can both be used to extract information from a time series.   In auto correlation, two datasets, say x and y are created from a single stream/source, but separated by a time lag appropriate to the application.  Cross correlation is based on two separate data sources.

This work has not been reviewed and therefore should be treated with caution.

Cross correlation can be used identify "cloud free" intervals in a stream of solar radiation data.  Under a clear sky, solar radiation is a smooth time series which is zero at sunrise, peeks at noon and returns to zero at sunset.  The presence of clouds in the sky introduces disturbance into the time series.  As the "clear" sky and the "cloud" sky required different forms of analysis, it is useful to be able to separate them.

The contrived diagram below shows the solar irradiance during a day which starts with a clear sky, around noon some broken or overcast cloud passes over, possibly bringing rain after which the clouds disperse leaving a fine afternoon.

Clear sky global horizontal irradiance (GHI) can be estimated by several methods.  In this application we only need an approximation that produces a time series similar to the data for a clear day, the magnitude of the estimates is not critical.  GHI is a combination of direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI).  DNI can be estimated using the Meinel formula (see reference below).

A similar correlation (see previous post "Diffuse Irradiance - Part 3" for details, provides an estimate for DHI:

These can be combined into an estimate for GHI using this formula.  In all three equations, the Air Mass is calculated using the plane parallel method.

The average value of the solar constant is 1370 w/m2.

If the time and location of the observations is known, the Air Mass (AM) can be estimated using Sun-Earth geometry.

If the sky is completely clear, there will be a high level of correlation between the estimated and observed data.  Solar radiation measurements are very sensitive to changes in the atmosphere, even a small amount of high level cloud which is barely visible to the human eye can introduce some disturbance into the time series.

The graph below shows the correlation between the estimated and observed datasets.  When the sky is clear, the correlation coefficient is close to one, when the Sun is obscured by cloud, it is similar to a random number.  For this application, the sky was assumed to be clear, if the absolute value of the correlation coefficient was greater than 0.95.

As with any statistical or numerical method, the results can vary according parameter settings and assumptions, in this case these include the duration of the correlation period and the critical value of the correlation coefficient.  The results from this methodology are similar to those obtained by selecting clear sky intervals by eye from plots of solar irradiance.

Reference:

A.B. and M.P. Meinel
Applied Solar Energy (Pages 46 to 48?)
Addison Wesley Publishing Company, 1976