Fake Survey: Is the “World Scientists’ Warning to Humanity” a Hoax?

November 19, 2017

The “Second Notice” released last week, with 15,364 scientist signatories from 184 countries, might be a hoax or a clever student prank.

What is notable and peculiar about the list of Signatories and the follow up list of Endorsers is the omissions.  No Michael Mann.  No Gavin Schmidt.  No Naomi Oreskes.  No Tim Flannery.  No Lewandowski.

James Hansen is the only eminent name I recognise.

Following on from Jo Nova’s excellent post on the recent publicity surrounding the release by the Alliance of World Scientists of their second warning to humanity, I decided to have a closer look at the AWS warning article and its 15,362 signatories, their backgrounds, and their motivation- and also, how the survey was conducted and how the Signatories and Endorsements were collected.

What I found strange is that along with the hundreds of scientists of all descriptions are theologians, philosophers, citizen scientists, renewable energy advocates, artists, musicians, photographers, a high school student- and a homeopath.

I then turned to the Endorsers, those who agree with the warning article but weren’t amongst the original Signatories.

Along with the bona fide scientists, and assorted activists, photographers, and philosophers, we find 1 wholesaler (educated in “the school of life”); 1 elementary (primary) school teacher; and 2 naturopaths.

As with the Signatories to the article, several of these later supporters entered themselves multiple times e.g. Harvey Quamme, research scientist, entered himself 3 times; David Wood, molecular genetics, entered himself twice- there were more like him.  How many more?

So I began to wonder- how well are the respondents checked, and how difficult is it to add your name- or someone elses’s?

The answer to both is: not at all.

All you have to do, dear friends, is go to their home page:

http://scientistswarning.forestry.oregonstate.edu/

Home page

Note the invitation to scientists “from any scientific discipline (e.g. ecology, medicine, economics, etc.)”

And the stipulation that “scientists only” are invited to Endorse the article.

Then click on “Endorse the Article”, and enter your details, not forgetting to confirm you are not a robot, then click save.  Your name will be added to the list of those who endorse the article.

Create Endorser

(Yes, I entered Saint Nicholas.)

Just really who are these Signatories and Endorsers? I’ve never heard of any of them (apart from James Hansen).  Are they real scientists (or homeopaths)?  Or are many of them completely fictitious, but with many real concerned individuals duped into adding their names?  And have real individuals been entered without their knowledge or consent?  How would anyone know?

It is possible to copy the lists of names into a Word document and do a word search to find how many times a particular profession is mentioned.  But look more closely at the names in various professions.  In the list of original Signatories, the names appear to be credible.  However in the list of Endorsers are some very interesting names.

The article has been endorsed by some pretty heavy hitters: amongst those who include “physics” in their entry are Albert Einstein and Ernest Rutherford.   Musicians include John Lennon and Elvis Presley.  Florence Nightingale is a nurse.  Luke Skywalker is an astronaut.  Indiana Jones is an archaeologist.

And note the name of the first respondent on the list of Endorsers.

Endorsement aaskan

Aaskan, Yushal Raseev.  Get it?

If this was a real survey, why would that entry have been left there for all to see for many days?

Check for yourself- there are sure to be many more to find.

Has this been a well-crafted, gigantic student prank?  Have we all been fooled by this farce?

The “Second Notice” of the World Scientists’ Warning to Humanity is worthless.  At the very least the survey software- at least for the Endorsing the article, and probably for the original Signatories as well-  has no security system for preventing or checking fake entries, so no one really knows if the names are real or bogus, or how many legitimate scientists really do support the article.

We know how climate change promoters ever since Hansen in 1987 have used cunning stratagems (remember “Mike’s Nature trick”?) to fool people and convince them that global warming is real.  Perhaps the whole climate change scare is a clever student prank from the 1980s that developed into a meme with a life of its own and grew and grew- the biggest practical joke ever perpetrated.

Perhaps, but it is clear that the Viewpoint article in the journal Bioscience entitled “World Scientists’ Warning to Humanity: a second notice” by Ripple et al. (2017) has no credibility and must be withdrawn.

It is a joke.

Advertisements

Summer Temperatures in South-Central Queensland Part 2: Weather Events and Spikes

October 30, 2017

In my last post I showed how on average temperature changed diurnally across a number of Queensland BOM stations.  In this post I will show examples of temperature change at some of these stations.  I am using “one minute data’, which despite its name, is really the value at the last second of every minute, in other words, sampling at 60 second intervals.

We know that temperatures spike up and down every few seconds, but these spikes are not captured by the Bureau unless they are the highest and lowest for each minute, and only noticed by a keen observer if the highest or lowest temperature spike so far that day occurs in the same minute (usually on the hour or half hour) as final second temperature reported at the Station Observations page.

Let us begin with this plot of a temperature spike at Maryborough Airport on 15 February, kindly reposted by Anthony Watts.  This was one of many examples from different locations around Australia of times when the maximum temperature of the day occurred in the same minute as a half-hourly recording, but exceeded it by a large amount (1.5 degrees in this example).

Figure 1:

Mboro 15 Feb

Please note that for this plot I only had access to the half hourly data from the Bureau, supplemented with some time offset data from the UK Met Office, usually 10 minutes before the BOM values.  With the higher resolution given by one minute data, we can gain a better appreciation of what was happening on this day.

Figure 2:

1 min T Mboro 15 feb

Note the spike at 13:00.  It is just part of the constant fluctuation during daylight hours which is not apparent from the data available for Figure 1.

Let’s have a closer look at the period from 12:00 to 14:00.

With the caveat that we can only guess at the 59 one second values in between the final second samples, we can use the latter values to investigate temperature response by day and night to various influences.  Assuming that the intervening one second fluctuations are approximately equally above and below a 60 second de facto mean represented by the value at the final second (as the Bureau’s Fast Facts would have us believe), a centred 5 minute mean of one minute (final second) data would approximate a mean of the complete 300 seconds.  I use a centred 5 minute mean to compare with the one minute data, but please understand this is an approximation, a best guess, when applied to short time lengths.  Its real value will be with all 115,200 data points- more later.

Figure 3:

1 min T Mboro 15 feb 12 to 2

Firstly, note how well the five minute centred mean represents most of the larger fluctuations, while considerably smoothing the final second data.

Secondly, note that the day’s maximum, 33.7C, was reached in the final second of 12:59, and was still at 33.7C at some second of the next minute, before falling 1.5 degrees to 32.2C in the final second of 13:00.

Thirdly, note that if this was a station in the USA, where 5 minute means are used, the maximum for the day would have been approximately 32.5C, still 1.2C less than the official value.

The temperature also fell 1.6C in the 60 seconds to 12:53.   And here are all the minute to minute temperature changes at Maryborough on 15 February (large outliers circled).

Figure 4:

1 min T change by hr of day Mboro 15 Feb

As shown in the previous post, this is the typical diurnal pattern.  Figure 5 shows one minute temperature fluctuation for the whole period, 1 January to 21 March 2017.

Figure 5:

1 min T change by hr of day Mboro 1 Jan 21 Mar 2017

Note the swelling of fluctuation in daylight hours, the constriction at sunset and sunrise as heating/ cooling regimes change, and the outliers: values can change by up to +2.3C or -2.1C in 60 seconds.

And here is an example of how a day’s temperature can change quite naturally, but we have to ask: would a mercury thermometer be able to match this?

Figure 6:

1 min T Mboro 6 mar

I now turn to other stations.  Hervey Bay Airport is about 30km from Maryborough Airport, only a couple of kilometres from the sea.  Firstly, how temperature changes from one minute to the next for the whole period.

Figure 7:

1 min T change by hr of day Hervey Bay 1 Jan 21 Mar 2017

Note that the daily increase in fluctuation is much less than at Maryborough.  Hervey Bay Airport is only a couple of kilometres from Sandy Strait, and proximity to a water body may be a tempering influence.

Note also the large outlier of -2C in one minute- still less than the 2.2C downwards spike on 22 February in less than a minute, which prompted my first query to the Bureau!  What could have caused such an outlier?  Here’s the one minute temperature plot for 16 March:

Figure 8:

1 min T Hervey Bay 16 March 2017

This outlier was the result of an entirely natural weather event, a sudden cool change, possibly a storm front: 4.4mm of rain was recorded at 09:00 on the 17th.  Would a mercury thermometer be sensitive enough to capture that?

And here’s 22 February:

Figure 9:

1 min T Hervey Bay 22 Feb 2017

Note the unusual spiking between about 04:30 and 06:30.  Something was going on.  Note also that the minimum temperature at 06:00 was far below at 23.2C, 1.6 degrees below any other temperature that day- for one second.

I now turn to Thangool Airport, a few kilometres from Biloela in the Callide Valley, 150km from the coast.

Figure 10:

1 min T change by hr of day Thangool 1 Jan 21 Mar 2017

Note the same shape, and though much further inland, not apparently different range from Maryborough.  Most of the change between 09:00 and 15:00 is within the bounds of +/- 1 degree each minute, but there are many outliers.

I shall now look at how temperature changed on a sample of days.  Firstly, 31 January shows a typical temperature curve for a clear sunny day.

Figure 11:

1 min T Thangool 31 jan

Figure 12 shows 7 January, a day with a mid-morning drop.  0.2mm of rain was recorded on the 8th.

Figure 12:

1 min T Thangool 7 jan

Note how after the sudden plunge the temperature quickly returns to “normal” as if nothing has happened.

28 January shows a late afternoon drop with a smaller recovery until sundown.

Figure 13:

1 min T Thangool 28 jan

Figure 14:

1 min T Thangool 24 jan

Note the typical warming curve which lasts until 16:47 when there is a sudden drop of 2.3 degrees in 3 minutes, with continued cooling.  I suspect a wind change was the cause.

Figure 15:

1 min T Thangool 20 mar

This shows a midday weather event, with the rapid return to the “normal” curve.  6mm was measured next morning.

Figure 16:

1 min T Thangool 17 feb

Note the sudden spike mid-morning.  The temperature spikes nearly 4 degrees in a few minutes to a value not expected for another hour or two.  This is odd and I cannot think of a natural weather event that could be the cause.  Whatever the cause, I doubt a mercury thermometer would track this change.

The final station for this post is at Lady Elliott Island, about 80km off the coast in the Coral Sea.  The screen is on white coral sand, about 100 metres from the water to the east.  First, one minute change over the whole period.

Figure 17:

1 min T change by hr of day L Elliott Is 1 Jan 21 Mar 2017

Note again the typical shape, but with much smaller daytime range of changes than inland sites.  Upward outliers are muted (there is only one instance of a temperature change in one minute of more than one degree).  However, downwards outliers are large and occur throughout the 24 hour period.

Here are some plots of several days on a tropic island.

Figure 18:

1 min T L Elliott Is 7 jan

Note the early morning downward spikes: rain showers.

Figure 19:

1 min T L Elliott Is 16 jan

Note the sudden drop just before midday: another rain shower.  But note how the temperature quickly returns to nearly what it was before.

Figure 20:

1 min T L Elliott Is 28 jan

Again, morning showers (quite normal near the sea in the wet season).

Now for the largest one minute temperature drop of -2.3 degrees just before midnight on 14 March.

Figure 21:

1 min T L Elliott Is 14 mar

Now watch the temperature recovery next day.

Figure 22:

1 min T L Elliott Is 14 15 mar

So, with a drop of nearly 6 degrees in a few minutes, this was a perfectly natural weather event.  Apart from sudden weather generated decreases like those shown above, it seems that there is a floor to minima of about 26C to 27C, due of course to the sea temperature.

While these examples are interesting, what about a day with sunny, fine weather?  Here’s the plot for 16 February.

Figure 23:

1 min T L Elliott Is 16 feb

Note a much more regular daytime curve (with rapid large spikes between 09:00 and 15:00), peaking only just after midday- except for a spike at about 14:30.  Here’s a closer look at the time from 12:00 to 15:00.

Figure 24:

1 min T L Elliott Is 16 feb 12 to 3

The second largest downwards spike (-1.3C) of the whole record occurred at 14:32.  This was purely a spike, not due to any weather event.  Could a mercury thermometer possibly match this?  If not, it would not reach the same maximum (30.8C).  On a hot sunny day on a coral island 100 metres from the sea, daytime temperature spikes up and down rapidly by up to a degree (or more) at a very high frequency.  Compare this with Maryborough in Figure 3.

This confirms generalisations I made in my last post:

“Temperatures in daylight hours are very volatile, while at night temperatures change very little except in unusual weather events.  Fastest and most sustained warming is in the hour after sunrise.  Fastest and most sustained cooling is also in daylight hours.  Night time cooling is much more gradual.  Cooling is on average more rapid than warming.  Rapid warming occurs when the sun suddenly appears.  Rapid cooling is associated with weather events such as rain storms.”

The Bureau of Meteorology have claimed that their AWS sensors are so designed that they mimic the mercury in glass thermometers they have replaced.   They claim a mercury in glass thermometer would track the above fluctuations closely.  However they have as yet provided no papers or comparative data to back this up.  From analysis of these stations’ data, I find that hard to believe.

Again we say, show us the data.

Summer Temperatures in South-Central Queensland Part 1: Diurnal Patterns of Temperature Change

October 15, 2017

In March of this year I purchased from the Bureau of Meteorology one-minute temperature data for the period 1 January to 21 March 2017, for a number of Queensland stations within 250km of Bundaberg.  “One-minute temperature data” is not the temperature of the whole minute, but means temperatures at  of the final second of each minute, so are spot samples taken at regular intervals.  Temperatures can be higher and lower in the intervening seconds, and so for example daily maxima can be several tenths of a degree or more above the final second values, as I demonstrated in earlier posts.

I have analysed data from these stations:  Maryborough, Hervey Bay Airport, Gayndah Airport, Thangool Airport, Bundaberg Airport, Rosslyn Bay, Gladstone Radar, Gladstone Airport, Rundle Island, Nambour, Kingaroy, Tewantin, Maroochydore, Gympie, Double Island Point Lighthouse, and Lady Elliott Island.  Most of these have few missing observations, but all still needed tedious checking.  Kingaroy’s record is atrocious, with days and weeks of intermittent data drop out.

I looked at: one minute temperature change, that is, from one data point to the next; temperature change after 10 minutes; the number of minutes of uninterrupted rise; the number of minutes of uninterrupted fall; and the number of minutes the temperature remained at the same value.

In this post I firstly plot averages of the above metrics across all 16 stations by time of day, to show the range of temperature variation from one minute to the next throughout the day and night, in distinctive diurnal patterns.

Figure 1:  One minute temperature change:-

Mean 1 minute dT

All stations show this distinctive shape, with some variance in range from island to inland stations.

Remember, this plot shows the average of 16 stations every minute of every day for 80 days.

Note the narrow range (averaging less than +/-0.1C) between sunset and sunrise, and the much larger swings from one minute to the next in daylight hours, especially between 09:00 and 15:00.  Outlier points are from weather events at individual stations.

The next plot shows the range of temperature change over 10 minute periods:

Figure 2:  10 minute temperature change:-

Mean 10 minute dT

Note the sharp increase from shortly after sunrise to an early morning peak, then a gradual decrease in the mean to a small dip at around 6 p.m..  Note again the small variation in the absence of the sun, and the many individual weather events shown by outliers.

The next plot counts the number of minutes when the temperature increases each minute at least +0.1C.

Figure 3:  Uninterrupted temperature increase:-

Mean Duration Rising

As you might expect, temperatures rise predominantly during daylight hours, with a sudden jump up just after sunrise, and a dip at sunset.

The next plot counts the number of minutes when the temperature decreases each minute at least -0.1C.

Figure 4:  Uninterrupted temperature decrease:-

Mean Duration Falling

Temperatures generally don’t fall very much just after sunrise.  However note that between 0900 and 1800 it is very rare for the temperature to be falling for zero minutes.  Most long temperature falls occur in daylight hours.  Surprising? What goes up must come down.

The next plot shows the length of time when the temperature does not change from one minute to the next:

Figure 5:  Unchanged temperature:-

Mean Duration Unchanged

Note that during the night on average temperatures are never the same for zero minutes (i.e. they are frequently the same), while in daylight hours temperatures are much less stationary, with a gradual rise from 1500.

The next graphs show the range of these metrics for individual stations.  This will be explored further in a future post.

Figure 6:  One minute temperature change:-

Max min dT comp

This shows the fastest minute to minute temperature change, both up and down.

Figure 7:  10 minute temperature change:-

Max min dT10 comp

Note that there was much faster cooling than warming over 10 minute periods, mostly associated with rain showers, storms, or cool changes.

Figure 8:  Uninterrupted temperature increase:-

Max Duration Rising comp

Figure 9:  Uninterrupted temperature decrease:-

Max Duration Falling comp

Note that Lady Elliott Island (far out to sea) and Rundle Island (in Gladstone Harbour) both had shorter periods of constantly rising and falling temperature.

Figure 10:  Unchanged temperature:-

Max Duration Unchanged comp

On the night of the 6th March at Maroochydore Airport the temperature was 26.1 degrees for 118 minutes.  As you can see nearly all stations had stable temperatures for nearly an hour on at least one occasion.

These results confirm that temperatures in daylight hours are very volatile, while at night temperatures change very little except in unusual weather events.  Fastest and most sustained warming is in the hour after sunrise.  Fastest and most sustained cooling is also in daylight hours.  Night time cooling is much more gradual.  Cooling is on average more rapid than warming.  Rapid warming occurs when the sun suddenly appears.  Rapid cooling is associated with weather events such as rain storms.

In Part 2 (probably not for a week or two) I will look at daily warming and cooling at individual stations.

Replicating Lewis et. al. (2017): Another Junk Paper

October 9, 2017

The recently released scarey predictions about “50 degree temperatures for Sydney and Melbourne” touted by Sophie Lewis are hardly worth wasting time on.  The paper is

Australia’s unprecedented future temperature extremes under Paris limits to warming, Sophie C. Lewis , Andrew D. King  and Daniel M. Mitchel, (no publication details available).

The paper is junk.  It has some very sciencey sounding words but is at heart pure speculation.  Like most “projections” by Global Warming Enthusiasts, the predictions are untestable.  Scarey temperatures are possible IF (and only if) IPCC scenarios are valid and we get either 1.5C or 2C warming by the last decade of the century.  That’s what the paper rests on.

The paper looks at Australian summer means, Coral Sea autumn means, and New South Wales and Victorian daily January maxima.  AWAP data are used for Australia and NSW and Victoria, and HadCruT4 for the Coral Sea region (which includes most of Queensland).

I have just looked at Australian Summer Means, and that was enough for me.  Lewis et.al. say that the decadal mean from 2091-2100 may have Australia wide summer means of 2 to 2.4 degrees above the mean of 2012-13, or 30.1 to 30.5C, with resultant very high daily maxima in southern cities.

I could have saved them the trouble, and at considerably less cost.

All I needed was the AWAP data for summer means (I purchased monthly AWAP data up to 2013 a couple of years ago), and plotted it with a 2nd order polynomial (quadratic) trend line:

lewis predictions summers1

And also showing decadal means (although the first and last decades have several missing summers):

lewis predictions summers2

There: the trend line goes smack through the higher (+2 degrees) projection, so it must be right!

Only trouble is, extrapolating with a quadratic trend is not a good idea. Lots can go wrong in the meantime.

So my plot is about as useful as the Lewis et.al. paper, and that’s not much.

Australian Temperature Data Are Garbage

September 14, 2017

From the Bureau’s hastily published “Fast Facts”:

“This means that each one second temperature value is not an instantaneous measurement of the air temperature but an average of the previous 40 to 80 seconds.”

That is complete nonsense.

At the end of each minute, the following data are recorded:

  1. Lowest one second reading of the previous 60 seconds
  2. Highest one second reading of the previous 60 seconds
  3. Reading at the final second of the minute.

Firstly, 40 seconds is not one minute, the integration period recommended by the WMO in 2014 and by the Bureau’s own officers in 1997.  Anything less than 60 seconds is not compliant.

Secondly, consider this plot, which is from actual 1 minute temperatures recorded at Hervey Bay Airport on 22 February 2017.  (Data purchased by me from the Bureau).

Fig. 1:

Hervey Bay 1 min 5 to7am 22 Feb

Sunrise was at about 5:40 a.m.  Temperatures do not increase until about 6:30 a.m.  Note the strangely low temperature- the daily minimum- which was reported as occurring sometime in the 60 seconds before 06:00:00.  The BOM would have us believe that each of the values in Figure 1, including the low of 23.2C, are “averages” of the previous 40 to 80 seconds.

Next consider what happens in that minute from 5:59 to 6:00, as per the following plot.

Fig. 2:

Hervey Bay 1 min 0559 to 0600am 22 Feb

We don’t know in which seconds the high and low readings for that minute occurred, so I have shown them for each of 59 seconds.  I have shown the 5:59 and 6:00 readings: both were 25.3C.

Consider how the value at 06:00 was obtained:

If by an “average” (however derived) of less than 60 seconds, the methodology is non-compliant.

If by an “average” of the previous 60 seconds, it must include values that contributed to the High of 25.4C and the Low of 23.2C.

If by an “average” of anything greater than 60 seconds, it must include values that contributed to both the Low and High values, and as well, values that contributed to the 5:59 reading- which is the same as the 06:00 reading.

Similar logic applies to the Low and High readings.

It follows that the intermediate instantaneous atmospheric temperatures that contributed to all three reported “average” values must have ranged from much higher than 25.4C to very much lower than 23.2C.

Look at Figure 1 again.  The air temperature at Hervey Bay on 22 February must have spiked down very much lower than the 23.2C plotted.

Really?

In the early morning there is very little near ground turbulence so temperatures do not fluctuate from one minute to the next by very much.  In How Temperature Is Measured in Australia Part 2 I showed that 91% of low temperatures vary from final second temperatures in the same minute by 0.2C or less.  A difference of 2.1C is extraordinary.  Fluctuations greater than that are difficult to believe.

However, in a comment at How Temperature Is Measured In Australia Part 1, Tony Banton, a retired meteorologist, says that the BOM explanation of cooler ground level air mixing upwards is correct.  If we accept that explanation, we must then face the problem of “comparability”.

In 61 seconds, the Hervey Bay AWS has reported temperatures of 25.3, 25.4, 23.2, and finally 25.3 degrees.  The BOM asserts that a liquid-in-glass thermometer will be able to respond as quickly and show similar temperatures- and remember, 23.2C was the morning’s official minimum.

My response: rubbish.  The data for 22 February at Hervey Bay show that no averaging is used at all, and the Low Temperature of 22.3C  23.2C is an instantaneous one second recording from a rogue downwards spike, whatever the cause, whether a natural event or other (e.g. electrical) factor.

Temperatures reported by the BOM are not fit for purpose of accurate reporting of maxima and minima, identifying records, or identifying warming or cooling by comparison with historic liquid-in-glass data.

Watch an AWS Fail

August 30, 2017

(With thanks to Lance, Phill, and others)

A week ago, a colleague alerted me to strange behaviour at an Automatic Weather System at Borrona Downs in NSW.  This is a brand new weather station, with its first observation on 21 July.

Phill writes in an email:  Do you ever wonder why you get a shiver down your spine?  Pity the poor folks in the NSW far west.  

 From this mornings (20th  August) NSW observation list: The minimum temperature at Borrona Downs AWS was -62.5C at 9:59pm last night.  Probably some clowns with a bucket of dry ice or liquid nitrogen.  Perhaps Odin’s host crossed the night sky or maybe death just walked on by…  The individual reads don’t show anything lower than -37.5C also at 9:59 so the cold spike was quite sudden.  It went from -62.5C sometime between 21:58:00 and 21:59:00 to -37.5C at exactly 21:59:00 to -4.4C at 22:00:00.

I was too busy and preoccupied until now to follow this up, but I have a few days now.

Borrona Downs Station is in sandhill and claypan country in the far northwest of NSW:

Borrona Dns map

Borrona Dns aerial

Here is the Climate Data Online minima record (note minima indicated on two days):

Borrona Dns cdo

The following plots show the deterioration in the performance of the AWS.  Firstly, the comparison with Tibooburra, 110km away, showing a sudden change at 29 July:  Subtracting Borrona Downs data from Tibooburra shows that Borrona Downs Tmin is too high from this date.  The whole (brief) record should be scrapped.

Borrona Dns Tibooburra comp

But the devil, as Phill found, is in the detail.  Here is part of the record for the 19th:  Note the Low Temp at 9.59 pm, and I have indicated the official minimum for the day which would have occurred early that morning.

Borrona Dns 19 Aug

The Bureau has the minimum at 4.6C, but how was this value obtained?  The erroneous values, (including that of liquid nitrogen), are flagged, then manually removed, and the previous lowest temperature is retrieved from the one minute data for the day.  This also happened on the 26th:

Borrona Dns 26 Aug

Things got much worse on August 27th:

Borrona Dns 27 Aug

Why could no minimum be found?  Did the BOM realise that none of the data were reliable, and were essentially random errors?  Remember that the AWS records values every second, and the highest, lowest, and final second values for each minute are stored.  My guess is that many of these values were unreliable as well, even though many of the final second half hour values seem reasonable- for example 4.4C at 5.30 am.

This continued on August 28th   with an all time low of -69.5C:Borrona Dns 28 Aug

And the BOM ceased reporting values at 3:30 pm.

This description of events was confirmed by the Bureau’s response to a query:

“Do you know what is causing the very low temperature recordings?

There is a hardware fault within the AWS which is generating spurious values. The Bureau’s technicians are investigating but a site visit will be required.

Why was the August 19 low temperature recording not left blank?

Manual quality checking confirmed that the spiking on 19 August did not occur near the minimum  temperature for that day, as a result, the minimum temperature was recorded.”

This begs the question: is this what happened at Goulburn Airport on 2 July ? The initially reported figure of -10.4C was flagged as suspicious, so the previous low temperature of -10C was then reported, then this was removed , then the initial -10.4C was reinstated.  Perhaps.

-10.4C certainly should not have been flagged as too low for that location, as many other  values below 10C have been observed, including the record -10.9C recorded on 17 August 1994.  However, perhaps it was flagged as suspicious by comparison with the series of values before and after: too large a change in temperature from second to second.  But if so, why didn’t the BOM CEO just say so, instead of getting tangled in a web of conflicting explanations?

The AWS at Borrona Downs has failed.  So has the Bureau of Meteorology.

 

The Pause Update July 2017

August 11, 2017

The complete UAH v6.0 data for July have been released. I present all the graphs for various regions, and as well summaries for easier comparison. I also include graphs for the North and South Temperate regions (20-60 North and South), estimated from Polar and Extra-Tropical data.

The Pause has ended globally and for all regions including the USA, Australia, and the Southern Hemisphere, except for Southern Extra-Tropics, South Temperate, and South Polar. The 12 month mean to July 2017 for the Globe is +0.35 C.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and eight months long- 464 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are July 2017.
[CLICK ON IMAGES TO ENLARGE]

Globe:

Pause July 17 globe

The Pause has ended. A trend of +0.53C/100 years (+/- 0.1C) since February 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

Pause July 17 globe mthly

Northern Hemisphere:

Pause July 17 NH

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

Pause July 17 SH

The Pause has ended but temperatures for the last 19 years are rising very slowly.

Tropics:

Pause July 17 Tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +0.52C/ 100 years.

Northern Extra Tropics:

Pause July 17 NExt

The Pause has ended and the trend is increasing, but the slowdown since 1998 is obvious.

Northern Temperate Region:

Pause July 17 Nth Temp

Using estimates calculated from North Polar and Northern Extra-Tropics data, the slowdown is obvious.

Southern Extra Tropics:

Pause July 17 SExt

The Pause has weakened but still just persists, and 12 month means have peaked.

Southern Temperate Region:

Pause July 17 Sth Temp

Using estimates calculated from South Polar and Southern Extra-Tropics data, the Pause likewise persists but has shortened.

Northern Polar:

Pause July 17 NP

The trend has increased and will continue to do so even though 12 month means are falling rapidly.  The strong trend in Arctic temperatures is due to a step change from 1995 – 2002, and the strong 2015 – 2016 El Nino.

Southern Polar:

Pause July 17 SP

The South Polar region has been cooling (-0.12C) for the entire record. Although the 12 month means may have peaked, this cooling trend will slow over the next few months, and Global Warming Enthusiasts may start to get excited.

USA 49 States:

Pause July 17 USA 49

The warming trend is increasing.

USA 48 States:

Pause July 17 USA 48

Excluding Alaska the USA has only +0.23C/ 100 years warming.  This trend will increase however.

Australia:

Pause July 17 Oz

The Pause has ended, but the trend since June 1998 has reduced from +0.42C/ 100 years to +0.3C, and since September 2002 is +0.13C.

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

Pause length July 17

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record. Note that the Tropic influence has been enough to end the Pause for the Southern Hemisphere, and the Pause is likely to disappear from all southern regions except South Polar in the next couple of months.

The variation in the linear trend for the whole record, 1978 to the present:

Trends 1978 july 17

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

Trends 1998 july 17

For 19 years “global” warming has been dominated by the influence of the Tropics and North Polar regions.

The imbalance between the two hemispheres is obvious.

The Pause has disappeared from the USA, Australia, and the Southern Hemisphere, but not the Southern Extra-Tropics, South Temperate, and South Polar regions.  Interestingly, July anomalies have decreased in Northern regions but increased in Southern regions and the Tropics.  The next few months will be interesting.

Garbage In, Garbage Out

August 7, 2017

(By Ken Stewart, assisted by Bill Johnston and Phill Goode; and cross-posted with Jo Nova)

Early ABC Radio news bulletins last Wednesday morning were led by this item, which you can read in full at ABC Online.

More climate scientists needed to avoid expensive mistakes, review urges

Apparently we urgently need 77 climate scientists to predict the future of areas like the Murray-Darling Basin with climate modelling.

Interestingly, Professor McDougall of the Australian Academy of Science points out that one of those “expensive mistakes” was the $2 billion desalination plant built in Queensland as a response to the millennium drought, “which really wasn’t an indication of climate change at all”.   Why didn’t the good professor raise his voice before the money was wasted?

But I digress.

Reliable modelling and projections for the future are surely desirable.

But such modelling must be based on reliable data, and the reliability of temperature data in Australia is demonstrably poor.

Example 1:  As has been widely reported in The Australian, and by Jennifer Marohasy and Jo Nova, cold temperatures at two separate sites (and possibly many others) were altered to appear warmer, then changed back, then deleted.  The BOM gave two conflicting explanations, both of which cast grave doubt on the reliability of “raw” temperature data from an unknown number of stations.

Example 2:  After enquiring why there are frequently two different temperature readings for exactly the same minute at various weather stations, a Bureau spokesperson told me that:

Firstly, we receive AWS data every minute. There are 3 temperature values:
1. Most recent one second measurement
2. Highest one second measurement (for the previous 60 secs)
3. Lowest one second measurement (for the previous 60 secs)

(See here and here.)

In other words, Australian maximum and minimum temperatures are taken from ONE SECOND readings from Automatic Weather Stations.  Spikes due to localised gusts of hot air, or instrument error, become the maximum for the day.  (This rarely has a large effect on minima, as night time temperatures are fairly smooth, whereas during the day temperature bounces rapidly up and down.  This is shown in this plot of temperatures at Thangool Airport in Queensland on Australia Day this year.)

Thangool 26 Jan 17 1 min

And this is for the same day between 3.00pm and 4.00pm.

Thangool 26 Jan 17 3 to 4pm

As you can see the temperature spikes up and down in the heat of the day by up to one degree between one minute and the next.  But these are the temperatures at the final second of each minute: during the intervening 59 seconds the temperature is spiking up and down as well, which we know because occasionally the highest or lowest temperature for the day occurs in the same minute as a final second recording on the BOM database (usually on the hour or half hour).  This can be up or down by two or three degrees in less than 60 seconds.

This is in contrast to the rest of the world.  The WMO recommends 1 minute (60 second) averages of temperature to be recorded to combat this very problem of noisy data, and this is followed in the UK.  In the USA 5 minute (300 second) averages are calculated.

From THE WEATHER OBSERVER’S HANDBOOK by Stephen Burt (Cambridge University Press, 2012):

Observers handbook

Even without software or human interference as in Example 1, this means Australian temperature data, in particular maxima, are not reliable.

Example 3:  Historically, temperatures were observed from Liquid In Glass (LIG) thermometers.  From the 1990s, Automatic Weather Stations (AWS) were installed using Platinum Resistance Thermometers (PRT) and are now the source for daily data.  AWS thermometers are very precise, but as I showed in Example 2, their data is used idiosyncratically to record 1 second spikes, frequently resulting in higher maxima and less often slightly lower minima than a 1 or 5 minute average.

One would think that with such a major change in technology there would be comparative studies reported in the BOM’s meteorological journal or other “peer reviewed” literature.  Apparently not.

Dr Bill Johnston has investigated this and says:

Parallel data were collected all over Australia for over a decade, some until last year when thermometers were removed, at manned sites, mainly major airports (Ceduna, Sydney, Hobart, Perth, Darwin, Alice Springs, Albany, Norfolk Island, Wagga to name a few) and also met-offices such as Cobar and Giles. However, comparisons between screens were done at one site only (Broadmeadows, Melbourne, which is not even an official weather station) using PRT only and reported as a “preliminary report”, which is available (https://www.wmo.int/pages/prog/www/IMOP/WebPortal-AWS/Tests/ITR649.pdf) however, after AWS became primary instruments, as I’ve reported before, the Bureau had an internal policy that parallel liquid-in-glass thermometer data were not databased. Furthermore, they had another policy that paper-data was destroyed after 2-years. So there is nothing that is easily available…. there is also no multi-site replicated study involving screen types and thermometers vs. PRT probes ….

Deliberate destruction of data is scandalous; the only way now to compare Automatic Weather Stations (AWS) and Liquid in Glass, is to hunt for sites where there is overlap between two stations; where the AWS is given a new number. This is possible BUT the problem is that the change-over is invariably confounded with either a site move or the change to a small screen.

Therefore we suspect that the introduction and reliance on AWS has led to artificially higher maxima (and thus record temperatures) than in the past, but we have no way of knowing for sure or how much.

So we now have (1) temperatures that are altered before they even become ‘raw’ data; (2) use of one second spikes for recording daily maximum and minimum temperatures, very probably resulting in artificially high maxima and slightly lower minima; and (3) no way of telling how the resulting data compare with those from historical liquid-in-glass thermometers.

How can the CSIRO hope to produce reliable climate modelling with any number of climate scientists when the BOM cannot produce reliable temperature data?  Garbage in, garbage out.

The Pause Update: June 2017

July 19, 2017

Better late than never!  I’m sorry for the lateness of this post.  A couple of issues and events got in the way.

The complete UAH v6.0 data for June have been released. I present all the graphs for various regions, and as well summaries for easier comparison. I also include graphs for the North and South Temperate regions (20-60 North and South), estimated from Polar and Extra-Tropical data.

The Pause has ended globally and for all regions including the USA, Australia, and the Southern Hemisphere, except for Southern Extra-Tropics, South Temperate, and South Polar. The 12 month mean to June 2017 for the Globe is +0.36 C.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and seven months long- 463 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are June 2017.
[CLICK ON IMAGES TO ENLARGE]

Globe:

Pause June 17 globe

The Pause has ended. A trend of +0.49 C/100 years (+/- 0.1C) since February 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

Pause June 17 globe monthly

Northern Hemisphere:

Pause June 17 NH

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

Pause June 17 SH

The Pause has ended but temperatures for the last 19 years are rising very slowly.

Tropics:

Pause June 17 Tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +0.49C/ 100 years. 12 month means are dropping fast.

Northern Extra Tropics:

Pause June 17 NExt

Northern Temperate Region:

Pause June 17 N Temp

Using estimates calculated from North Polar and Northern Extra-Tropics data, the slowdown is obvious.

Southern Extra Tropics:

Pause June 17 SExt

The Pause has weakened and shortened but still persists, and 12 month means have peaked.

Southern Temperate Region:

Pause June 17 S Temp

Using estimates calculated from South Polar and Southern Extra-Tropics data, the Pause likewise persists.

Northern Polar:

Pause June 17 NP

The trend has increased and will continue to do so even though 12 month means are falling rapidly.  The strong trend in Arctic temperatures is due to a step change from 1995 – 2002, and the strong 2015 – 2016 El Nino.

Southern Polar:

Pause June 17 SP

The South Polar region has been cooling (-0.14C) for the entire record. Although the 12 month means may have peaked, this cooling trend will slow over the next few months, and Global Warming Enthusiasts may start to get excited.

USA 49 States:

Pause June 17 US49

The Pause has ended. It will not re-appear for some time.

Australia:

Pause June 17 Oz

The Pause has ended suddenly, and will not re-appear for some time.

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

Pause length June 17

The Pause has disappeared from Australia.

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record. Note that the Tropic influence has been enough to end the Pause for the Southern Hemisphere.

The variation in the linear trend for the whole record, 1978 to the present:

Trends 1978 june17

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

Trends 1998 june17

For 19 years “global” warming has been dominated by the influence of the Tropics and North Polar regions.

The imbalance between the two hemispheres is obvious.

The Pause has disappeared from the USA, Australia, and the Southern Hemisphere, but not the Southern Extra-Tropics, South Temperate, and South Polar regions. El Nino tropical heat is rapidly decreasing, with all means falling. The next few months will be interesting.

The Pause Update: May 2017

June 7, 2017

The complete UAH v6.0 data for May have been released. I present all the graphs for various regions, and as well summaries for easier comparison. I also include graphs for the North and South Temperate regions (20-60 North and South), estimated from Polar and Extra-Tropical data.

The Pause has ended globally and for all regions including the USA and the Southern Hemisphere, except for Southern Extra-Tropics, South Temperate, South Polar, and Australia. The 12 month mean to May 2017 for the Globe is +0.35 C – down 0.01C from April.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and six months long- 462 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are May 2017.
[CLICK ON IMAGES TO ENLARGE]

Globe:

Pause May 17 globe

The Pause has ended. A trend of +0.46 C/100 years (+/- 0.1C) since March 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

Pause May 17 globe mthly

Northern Hemisphere:

Pause May 17 NH

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

Pause May 17 SH

The Pause has ended but temperatures for the last 19 years are rising very slowly.

Tropics:

Pause May 17 Tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +0.47C/ 100 years. 12 month means are dropping fast.

Northern Extra Tropics:

Pause May 17 NExt

Northern Temperate Region:

Pause May 17 NTemp

Using estimates calculated from North Polar and Northern Extra-Tropics data, the slowdown is obvious.

Southern Extra Tropics:

Pause May 17 SExt

The Pause has weakened but still persists, and 12 month means have peaked.

Southern Temperate Region:

Pause May 17 STemp

Using estimates calculated from South Polar and Southern Extra-Tropics data, the Pause likewise persists.

Northern Polar:

Pause May 17 NP

The trend has increased rapidly and will continue to do so even though 12 month means have started to fall.  The horizontal black lines show the pause for the first 16 years, and the pause from 2003 – 2015.  The strong trend in Arctic temperatures is due to a step change from 1995 – 2002, and the strong 2015 – 2016 El Nino.

Southern Polar:

Pause May 17 SP

The South Polar region has been cooling (-0.14C) for the entire record. Although the 12 month means may have peaked, this cooling trend will slow over the next few months, and Global Warming Enthusiasts may start to get excited.

USA 49 States:

Pause May 17 USA49

The Pause has ended. It will not re-appear for some time.  And by the way, that is almost entirely due to Alaska: here’s the plot without Alaska:

Pause May 17 USA48

Paused!  But that could disappear as well.

Australia:

Pause May 17 Oz

The Pause has shortened dramatically, but is still 19 years 9 months- over half the record.   And the trend since September 1995, two years longer, is less than +0.2C.

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

Pause Length May 17

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record. Note that the Tropic influence has been enough to end the Pause for the Southern Hemisphere.

The variation in the linear trend for the whole record, 1978 to the present:

Pause May 17 trends 78

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

Pause May 17 trends 98

For 19 years “global” warming has been dominated by the influence of the Tropics and North Polar regions.

The imbalance between the two hemispheres is obvious.

The lower troposphere over Australia has been strongly cooling for those 19 years- over half the record.

The Pause has disappeared from the USA and the Southern Hemisphere, but not the Southern Extra-Tropics, South Temperate, and South Polar regions, or Australia. El Nino tropical heat is rapidly decreasing, with all means falling. The next few months will be interesting.