Posts Tagged ‘minimum temperature anomaly’

The Australian Temperature Record Revisited: Part 4- Outliers

July 16, 2014

Update 2 February 2015

Rereading this, I just noticed a stupid error:  I had said Brisbane’s Acorn trend is less than its neighbours’ Acorn trend, but it is actually more- as with the other outliers.

In my previous posts I showed how the Acorn adjustments to the ‘raw’ minimum temperature data have the effect of enormously increasing the apparent trend across the whole network, and very differently in different regions.  In this post I am looking more closely at the six locations where the adjustments cause a change in trend of greater than +2 degrees Celsius.  These are:  Brisbane Airport, Amberley RAAF, Dubbo, Rutherglen, Rabbit Flat, and Carnarvon.

And I am mystified.

The purpose of homogenisation adjustments is to remove discontinuities in data, which show up as differences between the ‘candidate’ site’s record and those of its neighbours, the ‘reference’ sites.  The Acorn method of detecting discontinuities uses pairwise comparison with up to 40 neighbouring sites, and this includes sites many hundreds of kilometres distant.  Adjustments are made with a Percentile Matching algorithm which compares with up to 10 neighbouring sites.

I use my own method to compare sites with neighbours.  When comparing any sites, anomalies from a common base period (1961-1990) are used.  Only sites with data (at least 15 years) in this period can be used.  Sites also need long data records.  While in closely settled areas there will be a selection of observation sites, very few meet these requirements.  Therefore I compare the data of each of these six locations with those of their nearest surrounding Acorn sites’ ‘raw’ data, (adjusted by me only when necessary to create a long combined series), individually and with their mean.

Even with only five neighbours, for Carnarvon and Rabbit Flat these can be over 500km away.

I then repeat this using Acorn (adjusted) data for the neighbours.

The results are surprising.

Here are the six outliers and their surrounding Acorn neighbours:Outliers map

Note the remoteness of Rabbit Flat and Carnarvon.


Brisbane Air

Fig. 1a: Brisbane ‘raw’ spliced vs Acorn minimabris raw v acorn

The neighbours are: Amberley, Cape Moreton Lighthouse, Bundaberg, Gayndah, Miles, and Yamba Pilot Station.

Fig. 1b: Brisbane raw vs mean of neighbours (‘raw’ data)bris raw v reg mean raw

Fig. 1c: Brisbane Acorn vs neighbours’ raw meanbris acorn v reg raw

Note the adjusted trend (+1.95C per 100 years) is greater than the mean of the neighbours (+1.06) by nearly +0.9C.

Fig. 1d:  Brisbane Acorn vs mean of neighbours (Acorn, adjusted data)bris acorn v reg acorn

As you would expect, the data are now very similar, and the trend for Brisbane is thus 0.23C per 100 years more than the trend for the mean of the neighbours’ Acorn data.


Neighbours are the same as Brisbane’s, including Brisbane, 50km away.

Fig. 2a:  Raw vs Acornamberley tmin

Fig. 2b: Amberley and mean of neighbours (raw).amb raw v reg mean raw

Fig.2c: Amberley Acorn vs neighbours mean (raw)amb acorn v reg raw

Note the trend is more than one degree steeper than the trend of the neighbouring Acorn sites’ raw data.

Fig.  2d: Amberley Acorn vs neighbours’ mean (Acorn)amb acorn v reg acorn

Amberley’s adjusted trend is +0.87C greater than that of the mean of its neighbours’ adjusted data.


Neighbours are: Gunnedah, Scone, Bathurst, Cobar, Wyalong

Fig. 3a:  Raw vs Acorndubbo tmin

Fig. 3b: Dubbo and mean of neighbours.dubbo raw v reg mean raw

Fig.3c: Dubbo Acorn vs neighbours mean (raw)dubbo acorn v reg raw

+1.47C difference.

Fig.  3d: Dubbo Acorn vs neighbours’ mean (Acorn)

dubbo acorn v reg acorn

Now only +1.29C per 100 years greater than the neighbours.


Neighbours are: Deniliquin, Wagga Wagga, Sale, Kerang, Cabramurra

Fig. 4a:  Raw vs Acornrutherglen tmin

Fig. 4b: Rutherglen raw and mean of neighbours (raw).rutherglen raw v reg mean raw

Note that Rutherglen’s cooling trend is only 0.3C different from that of its neighbours.

Fig.4c: Rutherglen Acorn vs neighbours mean (raw)rutherglen acorn v reg raw

Fig.  4d: Rutherglen Acorn vs neighbours’ mean (Acorn)rutherglen acorn v reg acorn

+0.51C per 100 years greater than the neighbours.

Rabbit Flat

Rabbit Flat is a roadhouse in the Tanami Desert on the track between Alice Springs and Halls Creek.  Climate Data Online shows the current Rabbit Flat site 015666 as being 71km away from the old closed site 015548, though the Acorn Station Catalogue says it’s only 200 metres.  This in itself is peculiar.

The nearest non-Acorn site is Balgo Hills 211 km  away.

Acorn neighbours are:  Giles (567km), Halls Creek (328km), Victoria River Downs (433km), Tennant Creek (440km), and Alice Springs (568km).

Fig. 5a:  Raw vs Acornrabbit flat tmin

Fig. 5b: Rabbit Flat and mean of neighbours (raw).rbt flt raw v reg mean raw

Fig.5c: Rabbit Flat Acorn vs neighbours mean (raw)rbt flt acorn v reg raw

+1.17C more warming than neighbours.

Fig.  5d: Rabbit Flat Acorn vs neighbours’ mean (Acorn)rbt flt acorn v reg acorn

Rabbit Flat adjustments give it a trend +0.75C more than the neighbours’.


Carnarvon’s Acorn neighbours are Learmonth (298km), Wittenoom (560km) , Meekatharra (524km), Geraldton (447km), and Morawa (538km).  The only non-Acorn site with continuous data for the early part of last century is Hamelin Pool 6025 (174km away).

Fig. 6a:  Raw vs Acorncarnarvon tmin

Fig. 6b: Carnarvon and mean of neighbours (raw).carnarvon raw v reg mean raw inc morawa

Now note the effect of just one of the neighbours- Morawa.

Fig. 6c:   Carnarvon raw vs neighbours’ mean excluding Morawacarnarvon raw v reg mean raw excl morawa

Note the much closer comparison.

Fig.6d: Carnarvon Acorn vs neighbours mean (raw) (including Morawa)carnarvon acorn v reg raw

Note the trend is +1.58C per 100 years more.

Fig.  6e: Carnarvon Acorn vs neighbours’ mean (Acorn)carnarvon acorn v reg acorn

The difference is +1.49C.

The Acorn trend at Carnarvon is also greater than the Acorn trends at each of the neighbours separately.

Conclusion: –

The Acorn adjustment algorithm creates homogenised data by comparing with up to 10 neighbouring sites.  I have shown that the adjustments have made the Acorn trends greater than, not only the raw data trends for each site, not only the raw data trends of the closest neighbours in the Acorn dataset, but in every case but one, greater even than the trends of Acorn homogenised data from the same neighbouring locations.   The adjustments created thus appear to be spurious and the algorithm faulty.

Still No Evidence of Greenhouse Warming!

January 8, 2014

This morning I noticed at Jennifer Marohasy’s post

a comment from “Luke” (who else) objecting to my use of 2nd order polynomials in yesterday’s post.  Strictly I should stick to linear trends for a 35 year timescale, and use polynomials only for much longer periods.   Therefore, here is a plot of Australian annual minima and maxima for the 104 years from 1910 to 2013, using data straight from the BOM.minvmax poly2

Note that the red 2nd polynomial curve (maxima) shows a fairly flat trend until the 1950s, with an increasing rise since then. (Yes! It’s getting hotter!)

Note how the blue (minima ) curve also gradually rises over the years and apparently continues to do so.

However I have circled the graphs in the 1980s and the last few years.   I have blown this up so you can see more clearly what is happening.minvmax blownup

Since the mid 1980s there is a divergence in trends.  Daytime temperatures are rising faster than night time temperatures.

This is a problem because increasing CO2 and other greenhouse gases should be slowing back radiation, which should be evident in night time temperatures increasing faster.

Something else is happening.


The Hottest Year, but NOT due to Greenhouse Warming

January 7, 2014

ACORN-SAT- the gift that keeps on giving!

Unfortunately for doomsayers, the fact that 2013 was the hottest year on record in Australia is no evidence for the effects of greenhouse warming.  In fact, it is the very opposite.

Why?  Any sort of warming will eventually produce the hottest year on record.  But warming due to the enhanced greenhouse effect is quite special.  Warming due to greenhouse gases is evidenced by

greater warming of night time temperatures than daytime temperatures”

amongst other things, according to Dr Karl Braganza (

I discussed this in April  last year.  Now, with the updated data for 2013, it’s time for a reality check to see whether there is now evidence of greenhouse warming in Australia (a region as large as Antarctica, Greenland, the USA, or Europe, and supposed to be especially vulnerable to the effects of global warming.)

Once again I am using data straight from the Bureau’s website.

Fig. 1: Monthly maxima and minima with 12 month smoothing, December 1978 – December 2013, from

max v min linear

For the past 35 years, there is much LESS warming of night time temperatures than daytime temperatures.  And the divergence is increasing:

Fig 2: fitted with a 2nd order polynomialmax v min poly

Sorry, but this is not evidence of greenhouse warming over the period of the satellite era, when greenhouse gases have been increasing rapidly.  It is merely evidence of warming.

2013 Minimum Temperatures Released

January 2, 2014

Ken Stewart, 2 January 2014

UPDATE 3 January: BOM has updated it’s time series graph, but not the raw data, which still finishes at 2012! See below.

I have calculated the annual 2013 minimum temperature anomaly for Australia, well before the Bureau of Meteorology.

Not including the 8 sites acknowledged as having anomalous warming due to the Urban Heat Island (UHI) effect, I calculate the straight mean (without area averaging) to be +0.82 C.  This puts 2013 as second warmest after 1998, and just ahead of 1973 and 1988.

I expect that the BOM will publish a figure of around +1.2C, and claim 2013 as the warmest on record for minima.

I calculated this by using daily Acorn data for 1910 to 2012 from  , plus daily minima for 2013 for these same sites from Climate Data Online.  I used Acorn data from 1961-1990 to recalculate monthly means for each site, and then calculated running centred 31 day means to estimate daily means for the same period.

Then I calculated daily anomalies for each site, and amalgamated these into a straight mean for Australia.

The result is as follows:

Fig. 1:  365 day running mean of daily data.acorn 365d 1910-13 no uhi

I will analyse Fig. 1 in some detail later.  But first, how does my calculation stack up against the BOM super computer?

Fig. 2: Annual (31 December each year) means of minima 1910 to 2012.Acorn ann v me 1910-12

My calculation is in green, BOM in red.  As you can see, the match is pretty close, and of course I have not used any area averaging.  But you would expect the results to be close, as I have used exactly the same data.  You will notice that the major differences occur in years of higher or lower than normal minima.  These appear to have become larger in the last 40 years.  The official annual figures show greater extremes, as shown above.

I have also calculated trends for the 1910 to 2013 period, and hope that this will persuade you of the futility of using linear trends for temperatures, and that if you cherry pick you can prove just about anything.  The next graph is a plot of the continuous running trend from 31 December 2013 all the way back to 1 January 1910.  That is, the linear trend through datapoints between any selected date and 31 December 2013.

Fig. 3: Continuous running trend, daily minima anomaliescont trend Oz no uhi

The vertical axis measures trend in degrees Celsius at particular points in time.  Note the rapid fluctuations at the right hand end.  I’m sure no one would be silly enough to calculate trends of only a few years’ data.

As the time period increases (moving from right to left) the fluctuations smooth out.  Note that Australia has had zero trend in daily minima since 21 July 1997.  Interesting, but no predictor of the future.

Moving further back in time, the plot shows the temperature trend increasing until the early 1940s.  Up until then the long term trend is fairly stable.  Since 1910 the trend is about 1.1C per 104 years.  The maximum trend can be calculated from 1922. Therefore, a cheerful cherrypicker can choose whatever time frame they like to produce a linear trend that suits.

Back to my graph of the 365 day running means of daily temperatures. Figure 1 again:acorn 365d 1910-13 no uhi

Note that the 365 day mean peaked in early November 2013 and has dropped since then.  The peak was at +0.94C, which is still below that of 1998 and 2006.

But also note that the rise of about +1.1C over 104 years is by no means steady.  There are several sharp rises and falls along the way.  Let’s have a closer look at these.

Fig. 4: Step changes in temperatureacorn 365d 1910-13 no uhi stepups

I have shown (starting in 2014) how the minimum temperature record of Australia features a series of sharp step ups, followed by slow declines.  I have indicated the start of these periods and the linear trend lines of each one.  There may have been one in 1926, and 2013 may (or may not) be the start of another such period.  They are more frequent and more pronounced in the past 40 years than in the first 60 years.  This appears to show a link to natural climate forces, such as the El Nino- Southern Oscillation.

I will analyse these results further in future posts, and may do the same for maxima as well.  (People are interested in maxima because “that’s how hot it is”.  I like minima because they tell you more about climate e.g. if they increase faster than maxima this may indicate greenhouse warming.)

Watch for the official 2013 minimum temperature anomaly:  probably +1.2C.

Update 3 January:

Here is the official BOM graph to 2013:

timesereis tmin to 2013

and it looks like a bit over +0.9C  +0.94 C, so less than I expected and closer to mine.