Electricity Generation: The Impact of Rooftop Solar

Capacity Factor of an electricity generator is its actual generation as a percentage of its installed capacity.  A generator with an installed capacity of 1,000 Megawatts that generates 500 Megawatts has a Capacity Factor of 50%.  Obviously it is a good idea to have CF as high as possible as that will give a better return for the time, money, and effort used to build and run it.

In this post I am looking at Capacity Factors of all generators in the National Electricity Market (NEM), firstly excluding rooftop solar, then looking at CF when rooftop solar is included.

I use data available from Open NEM for the week from 8^th to 15^th March.

Firstly, Figure 1 shows the total of all major generators in Queensland, New South Wales, Victoria, Tasmania, and South Australia.

Figure 1:  Total NEM Generation 8-15 March

Solar and wind get preference, such that coal is curtailed when the sun is shining, but has to ramp up to meet demand from late afternoon to breakfast time.  Hydro and gas follow the same pattern at a much lower level, while wind generation adds its two bob’s worth at unpredictable times.

Figure 2 shows the Capacity Factor for the whole network (if there was no rooftop solar):

Figure 2: Capacity Factor NEM (excluding rooftop solar)

During this week CF varied in a regular cycle, from 27.9% to 43.8%.  Figure 3 shows this daily cycle:

Figure 3: Capacity Factor by Time of Day- NEM excluding rooftop solar

The NEM is at its most efficient- makes best use of generation resources- between 6pm and 7pm at night.  There is a lower peak in CF at 7am to 7.30am.  There is a drop in CF in the early morning (at baseload time), but the lowest CF is between about 11.30am and 12.30pm on several days.

Capacity Factors for coal, gas, and hydro have cycles reflecting that of the NEM without rooftop solar.

Figure 4: Capacity Factor by Time of Day: Coal, Gas, Hydro

By contrast, wind’s CF, which on the afternoon of the 8^th was briefly over 50%, could be as low as 2.4% and averaged 20.5% for the week.

Figure 5: Capacity Factor by Time of Day: Wind

Decidedly unreliable and inefficient.

Solar generation is much more reliable (in the sense of predictable) as we see in Figure 6.

Figure 6: Capacity Factor by Time of Day:  Solar

Solar CF is between about 40% and 60% in the middle of the day.  Note that utility solar, with tracking panels, reaches close to maximum CF by mid-morning and maintains higher CF than rooftop at nearly every 30 minute period of daylight.  Between sunset and sunrise, CF is zero.  All those millions of panels are useless.

When we include rooftop solar in the generation mix, see what happens to the CF for the whole NEM grid:

Figure 7: Capacity Factor by Time of Day- NEM excluding rooftop solar

Maximum CF is now in the middle of the day.  Figure 8 shows the difference rooftop solar makes to the CF of the whole network:

Figure 8: Change in Capacity Factor by Time of Day with Rooftop Solar

Before 9am and after 3.30pm the system is worse off. While the CF for the whole network has been increased in the middle of the day by between 2% and 6%, the average has been reduced by 4.5%, at baseload times by about 6.5%, and in the evening by nearly 10%.  Every additional panel will reduce CF even further, and this is not even considering the additional network capacity needed to keep the system balanced with such a wildly fluctuating supply.  Not a bad effort for a generating system with an average CF last week of 14.9%.

The final two figures compare actual generation at 12 noon and 4am.

Figure 9: 12 Noon Generation 8-15 March 2023

That’s all the renewables enthusiasts see: solar outperforming coal.  They are willfully blind to baseload needs:

Figure 10: 4:00 a.m. Generation 8-15 March 2023

When the remaining 1,500 MW of Liddell are lost in April, and 2,880 MW at Eraring in August 2025, the 4,330 MW gap in supply at 4:00 in the morning won’t be filled by rooftop solar or by solar farms: it will be made up by the remaining coal units working even harder (giving coal an even higher CF) until the strain is too much and they break down, and by gas and hydro.  Inevitable result: higher prices and probable blackouts (sorry- load shedding).

People of my generation often say we have lived through the best of times.

What will the coming generation say?

(Source: OpenNEM)

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The Challenge Ahead For Renewables: Part 3

In Part 1 I showed how the low Capacity Factors of wind and solar mean enormous wastage of resources and money has been incurred over the past 20 years. 

In part 2, I showed the impact of the policies of the major parties, with the costs of replacing fossil fuels in electricity generation, and the enormous cost of using renewables for all our energy use.

However, Net Zero is the goal of the whole developed world, not just Australia.  There are many, and not just the Greens, who say that replacing fossil fuel for all energy is not enough.  We must also ban all exports of coal and gas.

We produce far more energy than we consume- mainly coal (cue wailing and gnashing of teeth).  Most is exported.

According to the Department of Industry, Science, Energy and Resources (2021) total energy production (for domestic consumption plus exports of coal and gas) in 2019-2020 was 20,055 PetaJoules. 

Figure 1:  Australian energy production 2019-2020

All renewables and hydroelectricity amounted to a little over 2% of energy produced in Australia.

Figure 2:  Relative share of energy production

Therefore if we are to maintain our role as an energy exporter (of electricity or hydrogen), and thus our standard of living, then just to keep up with our 2019-2020 production, renewables will have to produce 48 times current production- an EXTRA 19,636 PJ. 

Figure 3: All renewables compared with energy consumption and production

Can this be achieved?

19,636 PJ is 5.45 billion MegaWattHours, which will need 622,227 MW generation (at 100% capacity).

If the extra generation is to come from solar (wind would require far too much land- over 6% of Australia’s land area), we will need an extra 4.149 million MW- 290 times 2020 solar capacity.

Therefore the cost would be at least

$7.47 TRILLION (if all solar).

And that figure doesn’t include storage, extra infrastructure like transmission lines and substations, charging points for vehicles, building hydrogen plants, and losses involved in electrolysis of water, conversion to ammonia and back again, and conversion of hydrogen to motive power.  Neither does it include the costs of decommissioning and replacement, safe burial of non-recyclable solar panels, turbine blades, and used batteries, nor the human costs of child labour in Congolese mines supplying cobalt for batteries.

(Australia’s nominal GDP will be around $2.1 trillion in 2022.)

Figure 4 shows the comparison between Australian GDP and the cost of solar generation needed.

Figure 4:  Cost of extra solar generation needed for Net Zero compared with the whole of the economy

So can it really be achieved?

In the minds of some, yes.

The report from the Australian Energy Market Operator (AEMO) containing the Draft 2022 Integrated System Plan (ISP) makes interesting (and scary) reading.  The favoured scenario is called “Step Change” which involves a rapid transformation of the Australian energy industry (rather than “Slow Change” or “Progressive Change”), which relates more to my analysis in Part 2.

However the scenario called “Hydrogen Superpower” received 17% of stakeholder panellists’ votes in November 2021 and must be considered a possible political goal.

Here is a summary of the Step Change and Hydrogen Superpower scenarios:

• Step Change – Rapid consumer-led transformation of the energy sector and co-ordinated economy-wide action. Step Change moves much faster initially to fulfilling Australia’s net zero policy commitments that would further help to limit global temperature rise to below 2° compared to pre-industrial levels. Rather than building momentum as Progressive Change does, Step Change sees a consistently fast-paced transition from fossil fuel to renewable energy in the NEM. On top of the Progressive Change assumptions, there is also a step change in global policy commitments, supported by rapidly falling costs of energy production, including consumer devices. Increased digitalisation helps both demand management and grid flexibility, and energy efficiency is as important as electrification. By 2050, most consumers rely on electricity for heating and transport, and the global manufacture of internal-combustion vehicles has all but ceased. Some domestic hydrogen production supports the transport sector and as a blended pipeline gas, with some industrial applications after 2040.

• Hydrogen Superpower – strong global action and significant technological breakthroughs. While the two previous scenarios assume the same doubling of demand for electricity to support industry decarbonisation, Hydrogen Superpower nearly quadruples NEM energy consumption to support a hydrogen export industry. The technology transforms transport and domestic manufacturing, and renewable energy exports become a significant Australian export, retaining Australia’s place as a global energy resource. As well, households with gas connections progressively switch to a hydrogen-gas blend, before appliance upgrades achieve 100% hydrogen use.

Household gas switching to 100% hydrogen? What could possibly go wrong?

Here are the AEMO projections:

“The ISP forecasts the need for ~122 GW of additional VRE by 2050 in Step Change, to meet demand as coal-fired generation withdraws (see Section 5.1). This means maintaining the current record rate of VRE development every year for the decade to treble the existing 15 GW of VRE by 2030 – and then double that capacity by 2040, and again by 2050.”  (VRE= Variable Renewable Energy)

 “In Hydrogen Superpower, the scale of development can only be described as monumental. To enable Australia to become a renewable energy superpower as assumed in this scenario, the NEM would need approximately 256 GW of wind and approximately 300 GW of solar – 37 times its current capacity of VRE. This would expand the total generation capacity of the NEM 10-fold (rather than over three-fold for the more likely Step Change and Progressive Change scenarios). Australia has long been in the top five of energy exporting nations. It is now in the very fortunate position of being able to remain an energy superpower, if it chooses, but in entirely new forms of energy. “ (p.36)

Figure 5:  Projections of different renewable needs from the draft report

And capacity factors have not been considered!

And here are the “future technology and innovation” ideas for reducing emissions:

Figure 6: How to achieve emissions reductions

I’m glad I won’t be around to see this play out.

The Challenge Ahead For Renewables: Part 2

In Part 1 I showed how the low Capacity Factors of wind and solar mean enormous amounts of wastage of resources and money have been incurred over the past 20 years. 

I also said that the wastage can only get worse.  Here’s how.

In Part 1, I only looked at historical electricity generation.  What of the future according to the major political parties? (The Greens don’t count because they can’t count.)

The major parties are committed to Net Zero emissions by 2050, which will require massive changes to our energy use.

I use data from the BP Statistical Review of World Energy 2021, the National Energy Market website, and the report of the Department of Industry, Science, Energy and Resources (2021).

To replace 2020 fossil fuel electricity with renewable electricity will require an extra 200.6 TeraWattHours:

Figure 1:  Total Electricity Generation

That’s an extra 22,884 MegaWatts of renewable capacity at 100% capacity factor.  Remember, wind’s capacity factor is about 32%, and solar is about 15%.  At $1.8 million per MW, that will cost somewhere between 129 and 275 billion dollars. 

That is of course entirely achievable.  Costly, but achievable.

However, electricity makes up only a small part of Australia’s total energy use.  Transport alone uses much more.  That is why there is a push for more electric vehicles: the ALP wants 89% of new car sales to be electric vehicles by 2030.

Australia’s 2020 energy consumption was 5,568.59 PetaJoules, a decrease of 5.25% on 2019.  One PetaJoule is the equivalent of 0.278 TeraWattHours, or 277,778 MegaWattHours, which is the power generated by 31.7 MW over one year.

Figure 2:  Total Energy Consumption in Australia

Renewables of all sorts accounted for just 8% of energy consumed in Australia in 2020.  Include hydro and that rises to 10.4%.  Figure 2 shows the amount for each.

Figure 3:  Energy Consumption by Type

Note the complete absence of nuclear energy.

If Australia is to be completely fossil fuel free (with no increase on 2020 consumption, which was reduced because of Covid), renewables will have to produce an extra 4,990.9 PetaJoules.  Our consumption will look like this:

Figure 4:  Energy Consumption without Fossil Fuels

4,990.9 PJ is 1.387 billion MegaWattHours, which will need 158,152 MW generation (at 100% capacity)- only 27.8 times 2020 generation.

If this is to be supplied by wind alone, we will need an additional 494,225 MW of installed capacity in wind farms- 52 times 2020 wind capacity- at 24 Hectares per MW.  An extra 118,600 square kilometres of suitable land for wind farms will be difficult to find.

Solar at 2-3 Hectares per MW would probably be a better proposition.  If the extra generation is to come from solar, we will need an extra 1,054,357 MW- 60 times 2020 solar capacity.

Therefore the cost of meeting our current energy consumption- transport, domestic, commercial, and industrial- with no allowance for growth, and ignoring the cost of converting our entire domestic, commercial, industrial, mining, and air transport capacity to some form of electric vehicles, would be between:-

$ 889.6 BILLION  (if all wind)

and

$1.898 TRILLION (if all solar).

(Australia’s nominal GDP will be around $2.1 trillion in 2022.)

That’s up to $73,700 for every man, woman, and child in Australia.

Figure 5 shows the comparison between Australian GDP and the cost of solar generation needed.

Figure 5:  Cost of extra solar generation compared with the whole of the economy

How much of that investment would be in wasted capacity? Between 68% and 85%-from $605 Billion to $1.613 Trillion.

Moreover, the life of a wind turbine is 20 to 25 years, and 25 years for solar panels, so we can look forward to more expense in decommissioning and replacement in the future.

(By the way- do you think that “future technology and innovation” will be any cheaper?)

That’s just what would be the result of the major parties’ commitment to Net Zero.

But wait- there’s more. Stand by for Part 3.

The Challenge Ahead For Renewables: Part 1

As we are committed by all major parties to the goal of Net Zero emissions by 2050 perhaps we need to reflect on the scale of the challenge ahead.

I shall first deal with electricity, as that is the only thing that renewables such as wind and solar can produce (except perhaps for a warm inner glow in those who love them.)

Being less of a romantic, I prefer facts and figures.  In this post I use data from the BP Statistical Review of World Energy 2021, the National Energy Market website, and by tracking down opening and closing dates for various facilities.

Figure 1 shows the total generating capacity for coal, wind, and solar electrical generation for the last 20 years.  (Gas is excluded as it makes up less than 8% of generation over a year.)  This is the maximum possible output if all plants are operating at 100% of their rated capacity.

Figure 1: Generating Capacity 2021 – 2020

Note how coal fired electrical capacity fell below 25,000 MegaWatts (MW) with the closure of power stations in SA, WA, and Victoria.  Meanwhile from a very low base wind capacity rose steadily and accelerated from 2018.  Solar generating capacity has exceeded wind since 2012 and really took off in 2019 and 2020.  Wind and solar combined now exceed coal generating capacity.

Now let’s look at how much electricity was actually produced

Figure 2: Coal Capacity and Generation 2021 – 2020

Note how coal generation is falling steadily.  The gap between generation and capacity may be regarded as wasted resources (and money).  This has remained fairly constant over the years.

Figure 3: Wind Capacity and Generation 2021 – 2020

Despite the large increase in capacity, generation is not increasing as fast.  The gap is widening.

Figure 4: Solar Capacity and Generation 2021 – 2020

Again, the gap (i.e. waste) is increasing even faster.  More on this later.

Here’s another way of looking at this problem, for solar.

Figure 5: Solar Generation as a Factor of Installed Capacity 2021 – 2020

Over the last 20 years there has been a fairly constant and close relationship between the amount of electricity generated and the installed capacity it is produced from.  This illustrates the low capacity factor of renewables.  Capacity factor is average actual generation divided by the nameplate capacity, usually expressed as a percentage. 

Figure 6: Capacity Factor 2021 – 2020

Coal has a capacity factor of between 65% and 80%.  Hydro depends on rainfall and has averaged 21% over the last 10 years.  Wind averaged 32% over the last 10 years, but solar struggles to get above 15%- mainly because it sits idle at night, there are large losses in conversion from DC to AC, and also because it produces more than the grid can handle in the middle of the day so supply is curtailed. 

Investors take heed: for every MegaWatt of solar electricity you may wish to generate, you will need to install 6.7 MW.  Every 1 MW of wind electricity needs 3.125 MW installed.  But wind takes up about 24 Hectares of land per Megawatt as against 2-3 Hectares for solar.

Figure 7 shows how much investment has been wasted over the years.

Figure 7: Wasted Capacity

Waste costs money.  In the case of wind and solar, $1.8 MILLION per MW.

I hate waste- but it can only get worse. 

Downwelling Infra-Red Radiation and Temperature: Part 2

In Part 1 I showed that:

• Downwelling infra-red radiation (so called “back radiation”) is real and measurable including at night.
• It is greatly increased by cloud and humidity,
• It results from daytime heating of the ground, which then loses heat by conduction, convection, evaporation, and radiation, into the atmosphere where the IR is repeatedly absorbed and re-emitted in all directions by greenhouse gases (including water vapour).
• A warmer atmosphere from whatever cause, natural or enhanced, will result in greater downwelling IR.

In this post I will look at the relationship between downwelling IR and temperatures at five Australian locations during 2018 (the last year for which complete irradiance data is available.)  Those locations are Alice Springs, Darwin, Rockhampton, Melbourne, and Cape Grim, and are shown on this map.

Fig.1:  Australian stations with solar exposure data

Cape Grim, set on a clifftop above the Southern Ocean, is most exposed to marine influences.  Melbourne, Rockhampton, and Darwin are surrounded by land but are subject to marine influence at times when the wind blows from the ocean.  Alice Springs has a desert climate and the ocean is thousands of kilometres away.  Most examples in this post will come from the Alice.

The Relationship Between Maxima and Minima:

Consider this plot of temperature at Walgett (NSW):

Fig. 2:  Latest weather graph for Walgett 27 – 31 January 2018

During a fine clear day the sun heats the ground which by conduction and convection raises the near-surface air temperature.  The hot ground emits upwelling IR, some of which greenhouse gases in the atmosphere absorb and re-emit in all directions, including towards the earth.  This is downwelling IR (DWIR), which adds to the solar radiation during the day, and slows the loss of heat at night.  The air temperature, and DWIR, peaks usually in the mid to late afternoon.  As the ground cools slowly throughout the evening and night hours, IR continues to be exchanged upwards and downwards, with enough being lost to space for ground and air temperatures to cool to the minimum.  This is usually reached, in fine clear conditions, sometime after sunrise.  And that is usually the time when DWIR also reaches minimum values.

Before I look at the relationship between DWIR and minima, let’s look at plots of maxima and minima.

Fig, 3:  Maxima and Minima at Alice Springs during 2018:

Note that usually (but not always!) peaks in maxima are matched by peaks in minima.  Here’s a closer look at the period from 6 May to 20 July, with minima scaled up by 19 degrees:

Fig. 4:  Maxima and Scaled Minima, 6 May – 20 July 2018

Note that maxima highs and lows precede those of minima by one day NEARLY ALWAYS.  (Sometimes they occur together, and sometimes maxima precedes minima by two days.)  The minimum temperature reflects the previous day’s maximum.  Why?  Due to DWIR, the ground cools slowly.  A hot day generates lots of DWIR, which keeps the ground (and air temperature) warmer next morning.  A cool day means less DWIR available next morning.  However, clouds lower maxima by reflecting sunlight but increase DWIR to keep nights and minima warmer, as we shall see later. The pattern seen above is also seen at Cape Grim, Melbourne, and Rockhampton, but not in Darwin where it is not so clear at all.

The Relationship Between Downwelling IR and Minima:

I used solar irradiance data to find daily (to 9.00 a.m.) minimum DWIR values for 2018 at Alice Springs, Darwin, Rockhampton, Melbourne, and Cape Grim, for comparison with daily temperature minima. 

Fig. 5:  Daily minima for 2018 at all stations

Fig. 6:  Daily minimum DWIR for 2018 at all stations

At all sites, as daily minimum IR increases, daily minimum temperature increases.  However, the strength of the relationship varies.  I calculated derivatives of Tmin and IR to find the daily change in values.  The relationship is strongest at Alice Springs, with a correlation of 0.69, Figure 5:

Fig. 7:  Change in temperature as a function of change in DWIR at Alice Springs.

Melbourne has almost exactly the same correlation (0.68), followed by Cape Grim (0.64) and Rockhampton at 0.61.  However Darwin is much different:

Fig. 8:  Change in temperature as a function of change in DWIR at Darwin.

The reason for this is not as complex as I thought, but first I’ll show a method of showing (and testing) the relationship between DWIR and Tmin more easily.

Converting DWIR to Representative Atmospheric Temperature

From the Bureau’s solar radiation glossary, http://reg.bom.gov.au/climate/austmaps/solar-radiation-glossary.shtml#globalexposure :

Downward infra-red irradiance … is related to a `representative (or effective radiative) temperature’ of the Earth’s atmosphere by the Stefan-Boltzmann Law:

E = σ T4

Where: E = irradiance measured [W/m2]
σ = Stefan-Boltzmann constant [5.67 x 10-8 W/m2/K4
T = representative atmospheric temperature [K]

From this we can calculate the daily Representative Atmospheric Temperature (RAT) above each weather station.  Here is a plot of RAT for Alice Springs.

Fig. 9: Representative Atmospheric Temperature and Minima at Alice Springs

RAT is always colder than the surface.  Notice how closely Tmin tracks with RAT. 

To compare them more closely, I scaled up RAT by adding the average monthly difference from Tmin.  Now you can see how closely minimum temperature is related to RAT and thus DWIR.

Fig. 10:  Scaled Representative Atmospheric Temperature and Minima at Alice Springs

Zooming in to the period from 31 March to 4 June:

Fig. 11 :  Scaled RAT and Minima at Alice Springs, 31 March – 4 June 2018

The timing of variations is very close.

Here is a plot of the actual daily difference between minimum surface temperature and Representative Atmospheric Temperature.  I have marked some unusually low and high values for closer inspection..

Fig. 12:  Daily difference between Surface Minima and RATat Alice Springs

What causes these fluctuations?  Returning to actual temperature and calculated RAT, here is the plot for the year to 15 April:

Fig. 13:  RAT and Minima at Alice Springs, 1 January – 15 April 2018

Both Tmin and RAT usually move in unison, rising and falling together.  However, notice at point A there is very little difference between the values, but at point B there is a very large difference.

Here’s the plot for November and December.  A and B have very small differences, while C and D have very large differences.

Fig. 14:  RAT and Minima at Alice Springs, 6 November – 31 December 2018

Cloudy conditions increase downwelling IR.  With no daily cloud data, rainfall will be a proxy for some cloudy days.  (There will be plenty of cloudy days when there is no rain.)  Here is a plot of rainfall and the difference between surface minima and calculated RAT.

Fig. 15:  Rainy weather and Tmin minus RAT at Alice Springs

Rainfall appears to coincide with very low differences when RAT (derived from DWIR) has increased but corresponding Tmin has not increased as much as expected.  Let’s zoom in to look at Points A and B from Figure 13 above.

Fig. 16:  Rainy weather and Tmin minus RAT at Alice Springs, January – April

In fact rain coincides with nearly all of the low differences.  Point B remains anomalously high.  What about November and December?

Fig. 17:  Rainy weather and Tmin minus RAT at Alice Springs, November – December

Here we have a problem.  Points A and B from Figure 14 above line up with rain events.  Instead of being a low difference as expected, point C has a high value coinciding with a small rain event, and D is on its own.  Why?

When RAT is scaled up, the problem (and likely reason) is obvious:

Fig. 18  Scaled RAT and Minima at Alice Springs, December 2018

No IR data is recorded for 11 December.  I suspect that IR values should also be missing for 12 and 13 December.  Moving remaining data for the month two days later removes these strange inconsistencies (and also dramatically improves correlation between IR change and temperature change to above 0.7.)

Which still leaves the odd spike in Figure 13 at point B.

The Exception Proves The Rule

Here is a count of the number of days with no IR data at Alice Springs in 2018.

Fig.19:  Count of days with no data at Alice Springs

There are a few minutes of missing data on nearly every day, but data was completely absent for eight whole days in March, and three days in December.  Did the pyrgeometer stop recording suddenly?  Was it a sudden fault or was it failing gradually?  Figure 20 shows the 31 day centred running correlation between change in DWIR and change in Tmin, with missing days shown.

Fig. 20:  Centred 31 day running correlation between change in DWIR and change in Minima

If all is well, and the relationship between change in DWIR and temperature minima is sound, the correlation between them should be fairly constant.  However, if the pyrgeometer reads incorrectly (or else the temperature probe- another possibility, but not in this case), correlation will suffer.  This is shown in March and December.  From April to September, change in Tmin correlates well with change in DWIR being between 0.8 and 0.9 for nearly the whole time.

Now let’s look at Darwin, which we saw in Figure 8 above was poorly correlated.   The running correlation shows when faults may have occurred.

Fig. 21:  Centred 31 day running correlation between change in DWIR and change in Minima

The dips above coincide with equipment failure in January, March, November and December.  There also appears to be a problem in August – September.

It does not help that the equipment failures occur in rainy, cloudy periods (Wet and Build-up).

Fig. 22:  Rainy weather and Tmin minus RAT at Darwin

In the Dry, with no rain, the difference between Tmin and the RAT (Representative Atmospheric Temperature) still fluctuates wildly.  Here is a plot of the difference for June 2018:

Fig. 23:  Daily difference between Surface Minima and RATat Darwin June 2018

If the relationship is valid, and there are no recording problems, then large differences occur during fine and cloudless conditions and low values indicate cloudy conditions.  The daily total of Global Solar Exposure can also be a metric of cloudiness, because smaller amounts of sunlight reach the ground on cloudy days.   Figure 24 is a plot of the sum total of Global Irradiance in kiloWattminutes per square metre received each day.

Fig. 24: Daily total of Global Irradiance Darwin, June 2018

Apart from 10 – 12 June, the relationship holds.  Darwin’s apparent poor relationship between DWIR and Minima is very probably due to equipment failure.

The apparent exceptions to the “rule” that large differences between minima and Representative Atmospheric Temperature occur in dry, cloud free conditions, and small differences in cloudy conditions, in fact confirm it. 

Conclusion:

• Downwelling infra-red radiation (so called “back radiation”) is real and measurable including at night.
• It is greatly increased by cloud and humidity.
• It results from daytime heating of the ground, which then loses heat by conduction, convection, evaporation, and radiation, into the atmosphere where the IR is repeatedly absorbed and re-emitted in all directions by greenhouse gases (including water vapour).
• A warmer atmosphere from whatever cause, natural or enhanced, will result in greater downwelling IR.
• Temperature Maxima highs and lows precede those of minima by one day NEARLY ALWAYS, due to the influence of downwelling IR.
• Calculating Representative Atmospheric Temperature from downwelling IR using the  Stefan-Boltzman Law provides further insights.
• The daily minimum RAT is always much colder than minimum temperature.
• The difference between the two changes with the weather.  Sunny, dry, cloudless weather is associated with large differences, while cloudy weather is associated with small differences.
• When recording error is accounted for there is very good correlation between downwelling infra-red irradiance and daily minimum temperatures at a range of sites across Australia.
• In Australia, meteorological equipment can deteriorate for some time and fail completely, resulting in faulty data being included in national databases.
• Finally, the effect of DWIR on minima is not site dependent.  Both Melbourne and Rockhampton have Urban Heat Island influence but the relationship is similar to that of other sites.  Minima are directly related to DWIR, but DWIR is increased not only by clouds, but also by large trees, nearby buildings, and areas of concrete and bitumen.

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Downwelling Infra-Red Radiation and Temperature: Part 1

Way back in July last year I posted about the long term decrease in downwelling IR at Cape Grim and Alice Springs, despite rising CO2.

From the Bureau’s solar radiation glossary,
“Downward infrared irradiance is a measurement of the irradiance arriving on a horizontal plane at the Earth’s surface, for wavelengths in the range 4 – 100 μm (the wavelength emitted by atmospheric gases and aerosols). It is related to a `representative (or effective radiative) temperature’ of the Earth’s atmosphere by the Stefan-Boltzmann Law:
E = σ T4
Where: E = irradiance measured [W/m2]
σ = Stefan-Boltzmann constant [5.67 x 10-8 W/m2/K4
T = representative atmospheric temperature [K]
Consequently, this quantity will continue to have a positive value, even at night time. It can be measured using an Eppley PIR pyrgeometer.”

As atmospheric temperature increases, DWIR must also increase. This would be a symptom of warming.
A reader commented: ”What we need is DWIR nighttime measurements only (preferably without clouds) in a location where there is little or no water vapour. Atacama Chile would be perfect. Alice Springs maybe but less so. i am willing to bet that one couldn’t measure the DWIR at night without clouds in Atacama because it would be so low.”
I am unable to get data for Atacama, but here is DWIR data for Alice Springs for July 2018. July is mid-winter and usually dry and cloud free. No rain fell in July 2018 at the Alice.
Figure 1 shows maxima and minima for the month:
While July had no rain, there were several large weather changes shown by the spikes and dips in temperature. Coldest temperatures were on 12-13-14 July.
Fig.1: Surface temperatures Alice Springs July 2018

Next, downwelling IR. The weather changes show up in IR as well.
Fig.2: Downwelling IR Alice Springs July 2018

Now for IR in the hours of darkness:
Fig.3: Downwelling IR Alice Springs July 2018 at night (6pm to 6am)

Clearly, DWIR is real and measurable at night, in all conditions. It usually (but not always) decreases in a smooth curve. Putting it together, we see a clear daily cycle: DWIR usually increases rapidly in daytime, and decreases at night.
Fig.4: Downwelling IR Alice Springs July 2018 by day and night

Now we look at typical IR behaviour in cool, dry conditions on 12 and 13 July 2018. The x-axis is in 3 hourly divisions and I have marked in midnight of 12-13.
Fig.5: Downwelling IR Alice Springs 12-13 July 2018

Note the curve is not completely smooth: there are little variations due to pockets of different temperatures in the air. The lowest DWIR values (227.36 Watts/sq.metre averaged over one minute) are reached around 8.00 a.m. shortly after sunrise, then values rise rapidly before tapering off to peak in the late afternoon. During the night they decrease until the sun heats the ground again in the morning.
Now for the period 5 to 8 July:
Fig.6: Downwelling IR Alice Springs 5-8 July 2018

On the 6th and 8th strange things happen after midnight, almost certainly clouds.
Strange things also happen from 23 to 25 July. On the 24th a heavy bank of cloud comes over and clears with a sudden dry change after sundown, with more separated clouds arriving later at night before finally clearing about 9 a.m. next morning.
Fig.7: Downwelling IR Alice Springs 23 – 25 July 2018

How do I know those spikes were caused by clouds? Here’s direct radiation and IR for 23-25 July.
Fig.8: Downwelling IR and Direct Irradiance Alice Springs 23 – 25 July 2018

Direct irradiance is the radiation from the sun’s direct beam. It is zero at night but rises rapidly to peak at local solar noon, then rapidly falls to zero at dusk. Not all solar radiation reaches the surface. Some is reflected, some is scattered by dust, smoke, or rain drops, but on a clear day the pattern is like 23 July. On 24 July clouds block the sun’s direct rays for most of the day, and downwelling IR increases markedly. This is from warm moist air in the cloud which has come from somewhere else.
My conclusion:
Downwelling infra-red radiation (so called “back radiation”) is real and measurable including at night.
It is greatly increased by cloud and humidity, and there is always some moisture in the air even in the desert.
It results from the ground heating up in the daytime, which then loses heat by conduction, convection, and radiation, into the atmosphere where the IR is repeatedly absorbed and re-emitted in all directions by greenhouse gases (including water vapour).
A warmer atmosphere from whatever cause, natural or enhanced, will result in greater downwelling IR.

Future posts will look at the relationship between solar radiation, downwelling IR, and temperature.

Solar Exposure

The Bureau of Meteorology publishes many useful datasets on its Climate Data Online portal, including one minute solar exposure data for selected sites around Australia.  You have to register to receive monthly data here.

(In contrast with their one minute temperature data which are not available at CDO but must be requested and purchased, and are really “final second of each minute”, their solar exposure data are (a) free, and (b) include for each minute, maximum 1 second irradiance, minimum 1 second irradiance, and THE MEAN IRRADIANCE FOR THE PREVIOUS 60 SECONDS.  Why not temperature?  We can only wonder.  But I digress.)

I am naturally curious and enjoy finding out new stuff, so in this post I’ll show a number of plots for the months of July 2017, December 2017, and February 2018 to illustrate some things I’ve found about summer and winter solar exposure for Rockhampton.  Why Rocky?  It’s where I live, and is just a few kilometres north of the Tropic of Capricorn.  At the end of December the sun is directly overhead, so December shows interesting information.  February is typically the wettest and cloudiest month, and July usually the coldest and driest.

One minute solar exposure data have several components:  direct (normal) irradiance (rate of energy from the direct beam of the sun tracked throughout the day); direct horizontal irradiance (the amount striking a horizontal surface); diffuse irradiance (radiation scattered from the atmosphere including dust and clouds striking a horizontal surface); and “global” irradiance which is the sum of the horizontal and diffuse components.  Also measured is “terrestrial” irradiance, which is downwards infra-red radiation on a horizontal surface, and related to the temperature of the atmosphere, including from clouds and humidity (not just at ground level, but throughout the troposphere).

Figure 1:  Irradiance for February 2018

Note that terrestrial (infra-red) irradiance is fairly constant at around 350-450 watts per square metre, while direct irradiance on a horizontal surface fluctuates from zero to ~1000 W/sq.m., and diffuse irradiance fluctuates from zero to ~900 W/sq.m.  For a closer look here are the same data for one day, 1^st February:

Figure 2:  Irradiance for 1 February 2018

Mean horizontal irradiance (the direct beam from the sun on a horizontal surface) is zero in the absence of direct sunlight- at night, but also when clouds are thick enough, and also is greatly reduced even by thinner cloud; at other times, it rises rapidly to ~900 W/sq.m. at noon.

Diffuse irradiance is zero until a few minutes before sunrise, with radiation reflecting from clouds, dust, and other atmospheric particles; similarly just after sundown.  It is much higher in cloudy conditions.

IR irradiance, relatively constant before sunrise at ~400 W/sq.m., rises during the day as the atmosphere warms.  It also fluctuates with cloudy conditions, more noticeably at night.  Clouds are composed of water droplets and emit IR radiation- a natural greenhouse effect.

The next plot shows how irradiance varies over four days as clouds and rain increase.

Figure 3:  Irradiance for 1 – 4 February 2018

The effect of cloud on horizontal irradiance is obvious.  Diffuse irradiance is maximised on the 3^rd; on the 4^th, clouds reflect most solar radiation, the surface is cool, and IR irradiance which had increased due to cloudiness on the 2^nd and 3^rd, returns to ~400 W/sq.m.

By contrast, Figure 4 shows irradiance during the hottest week of February with maxima above 39.1C (41.1C on the 12^th).

Figure 4:  Irradiance for 11 – 15 February 2018

Note the smooth curves of horizontal and diffuse irradiance on 11^th and 12^th; early morning cloud on 13^th – 15^th with diffuse and IR increasing; and IR increases with surface temperature, peaking in the late afternoon- with little surges as clouds pass overhead.

Figure 5 shows the variation of IR irradiance during February.

Figure 5:  IR Irradiance for February 2018

The diurnal fluctuation typically of 60-70 W/sq.m. is obvious, as is the change over time.  The bottom of the daily fluctuation occurs in the early morning.  Notice the effect on the minimum temperature:

Figure 6:  Minima for February 2018

The last plot for February shows the irradiance from the direct beam of the sun tracked throughout the day:

Figure 7:  Direct Irradiance for February 2018

It’s interesting that the irradiance of the direct beam is not constant, even on clear sunny days.  It is possible that the rain of the first four days removed suspended particles; from 5^th to 9^th the wind was from the east or south-east (from the sea); from the 11^th to 15^th it was from the north west to north, blowing dust and smoke from the land, resulting in slightly dimmer conditions.

I now turn to July 2017.  July is usually the coolest and driest month in Rockhampton.

Figure 8:  Irradiance for July 2017

Due to the much lower solar angle, horizontal irradiance is much lower than February, mostly from 600 to 700 W/sq.m.  IR irradiance is more variable, so needs a closer look.

Figure 9:  Irradiance for 6 – 10 July 2017

These were cloudy days, with wind from the north-west on the 6^th to 8^th, with a south-east change on the 9^th with light rain on 9^th and 10^th.

19^th to 22^nd shows more of this atypical winter weather.

Figure 10:  Irradiance for 19 – 22 July 2017

Overcast and 90% Relative Humidity in the morning of the 19^th, then RH fell rapidly, with the lowest 3:00 p.m. reading for the month (16%) and 9:00 a.m. (36%) on the afternoon of the 21^st and the morning of the 22^nd– when IR, and minimum temperature, were lowest for the month.  The 20^th and 21^st were clear sunny days.   Some cloud arrived on the afternoon of the 22^nd.

Figure 11:  Irradiance for 25 – 28 July 2017

This is typical winter weather- clear skies, cool nights followed by warm sunny days.  Note the smooth curves for horizontal and diffuse irradiance, both much less than February.  This indicates cloudless skies and low humidity.  There is a little early morning fog or mist as indicated by small wiggles in IR irradiance, but not enough to affect diffuse irradiance.  IR irradiance again peaks in mid afternoon.

Figure 12:  IR Irradiance for July 2017

Due to less direct irradiance, cooler temperatures, and lower humidity, IR irradiance is much lower than in February, and rarely exceeds 400 W/sq.m.  IR fluctuates less in clear dry conditions.   Again, IR is reflected in minima:

Figure 13:  Minima for July 2017

Figure 14:  Direct Irradiance for July 2017

Note that direct irradiance is not much less than in February, even for being soon after aphelion: it is the sun’s lower angle in the sky that makes most of the difference.  The clear dry days on the 20^th and 21^st have the highest irradiance.

The next plots are for December, around summer solstice and close to perihelion, when days are typically hot and sultry.

Figure 15:  Irradiance for December 2017

The first four days, and the 9^th, were cloudy, with rain on 3^rd and 4^th, as you can see from the horizontal irradiance.  On the remaining days irradiance was close to 1000 W/sq.m.

Figure 16:  IR Irradiance for December 2017

Heavy cloud, swept in from the Coral Sea, on the first four days, and hotter maxima on the last two, pushed IR well above 400W/sq.m.

And the plot for minima:

Figure 17:  Minima for December 2017

Last one!

Figure 18:  Direct Irradiance for December 2017

You will notice that with the sun virtually directly overhead around noon each day (from 1.56 degrees from zenith on 1^st December to 0.01 degrees from zenith on Christmas Day), sun tracking direct irradiance is almost the same as the horizontal irradiance.

What have I learnt?  The variability of solar exposure, which is strongly affected by what’s in the atmosphere: dust, smoke, gaseous water, liquid water (clouds); as well as time of year and time of day.  The extent that downwards infra-red irradiance, which is an indicator of atmospheric temperature, is increased by daytime surface temperature and also very noticeably by clouds, and decreased by lower humidity.  How IR strongly influences minima- the greenhouse effect.

Nothing new probably, but I hope you found it as interesting as I did.

Finally:  why, oh why, can’t the Bureau make one minute temperature data freely available, and why does it persist with one second temperature readings rather than the mean over the previous minute, which it calculates with solar exposure?

My next post will look at different factors influencing temperature, including solar exposure.