Archive for the ‘temperature’ Category

Better Late Than Never- BOM Releases Adjustment Details

September 11, 2014

On Monday, quietly and without any announcement, a new tab appeared on the Bureau’s ACORN-SAT webpage.

adj tab

This “Adjustments” tab opens to a page explaining why homogenisation is necessary, supposedly showing how the adjustments don’t make much difference to the mean temperatures, and how Australia really is warming because everyone agrees.  More on this later.  So how do we get to see the actual adjustments for each site?  Tucked away under the first graph is a tiny link:

adj tab link

Click on that and a 27 page PDF file opens, listing every Acorn station, dates and reasons for adjustments, and most importantly, a list of reference stations used for comparison.  (You have to go to Climate Data Online to find the station names, their distance away, site details, and their raw data.)

Finally it will be possible to check the methods and results using the correct comparison stations- until now we could only guess.

Back in September, 2011 the Independent Peer Review Panel made a series of recommendations, including that

“C1. A list of adjustments made as a result of the process of homogenisation should be assembled, maintained and made publicly available, along with the adjusted temperature series. Such a list will need to include the rationale for each adjustment.”

The Bureau responded on 15 February 2012, just before the release of Acorn:

“Agreed. The Bureau will provide information for all station adjustments (as transfer functions in tabular format), cumulative adjustments at the station level, the date of detected inhomogeneities and all supporting metadata that is practical. This will be provided in digital form. Summaries of the adjustments will be prepared and made available to the public.”

That was two and a half years ago.  What took so long?  Why was it not publicly available from the start?  Perhaps it is just a co-incidence that the long awaited information was released shortly after a series of articles by Graham Lloyd appeared in The Australian, pointing out some of the apparent discrepancies between raw and adjusted data.  Graham Lloyd deserves our heartfelt thanks.

The Bureau of Meteorology has been dragged kicking and screaming into the 21st Century.  The Bureau is having trouble coming to terms with this new era of transparency and accountability, an era in which decisions are held up to public scrutiny and need to be defensible.

I trust we won’t have to wait another two and a half years for the other information promised, such as “sufficient station metadata to allow independent replication of homogeneity analyses” and “computer codes… algorithms… and protocols”,  “the statistical uncertainty values associated with calculating Australian national temperature trends” and “error bounds or confidence intervals along the time series”

The final recommendation of the Review Panel, and undertaking by the Bureau:

“E6. The Review Panel recommends that the Bureau assembles and maintains for publication a thorough list of initiatives it has taken to improve transparency, public accessibility and comprehensibility of the ACORN-SAT data-set.

Agreed. The Bureau will provide such information on the Bureau website by March 2012.”

I must have missed that.

 

 

 

Homogenisation: A Test for Validity

September 8, 2014

This follows on from my last post where I showed a quick comparison of Rutherglen raw data and adjusted data, from 1951 to 1980, with the 17 stations listed by the Bureau as the ones they used for comparison when detecting discontinuities. 

Here is an alternate and relatively painless way to check the validity of the Bureau’s homogenisation methods at Rutherglen, based on their own discontinuity checks.  According to the “Manual” (CAWCR Technical Report No. 49), they performed pair-wise comparisons with each of the 17 neighbours to detect discontinuities.  An abbreviated version of this can be used for before and after comparisons.  For each of the 17 stations, I calculated annual anomalies from the 1961-1990 means for both Rutherglen and the comparison site, then subtracted the comparison data from Rutherglen’s.  I did the same with Rutherglen’s adjusted Acorn data.

A discontinuity is indicated by a sudden jump or drop in the output.  The ideal, if all sites were measuring accurately and there are no discontinuities, would be a steady line at zero: a zero value indicates temperatures are rising or falling at the same rate as neighbours.  In practice no two sites will ever have the same responses to weather and climate events, however, timing and sign should be the same.  Therefore pairwise differencing will indicate whether and when discontinuities should be investigated for possible adjustment.

Similarly, pairwise differencing is a valid test of the success of the homogenisation process.  Successful homogenisation will result in differences closer to zero, with zero trend in the differences over time.  The Bureau has told the media that adjustments are justified by discontinuities in 1966 and 1974.  Let’s see.

Fig. 1:  Rutherglen Raw minus each of 17 neighbours

pairwise diffs Rutherglen Raw

Note: there is a discernible drop in 1974, to 1977.  There is a very pronounced downwards spike in 1967 (ALL differences below zero, indicating Rutherglen data were definitely too low.)  There also a step up in the 1950s, and another spike upwards in 1920.  Rutherglen is also lower than most neighbours in the early 1930s.  Also note several difference lines are obviously much higher or lower than the others, needing further investigation, but the great majority cluster together.  Their differences from Rutherglen are fairly consistent, in the range +/- 1 degree Celsius.

Now let’s look at the differences AFTER homogenisation adjustments:

Fig. 2:  Rutherglen Acorn minus the neighbours: The Test

pairwise diffs Rutherglen Acorn

The contrast is obvious.  The 1920 and 1967 spikes remain.  Differences from adjusted data are NOT closer to zero, most of the differences before 1958 are now between 0 and -2 degrees Celsius, and there is now an apparent large and artificial discontinuity in the late 1950s.  This would indicate the need for Rutherglen Acorn data to be homogenised!

Compare the before and after average of the differences:

Fig. 3:

pairwise diffs Rutherglen Raw v Acorn average

There is now a large positive trend in the differences when the trend should be close to zero.

There are only two possible explanations for this:

(A)  The Bureau used a different set of comparison stations.  If so, the Bureau released false and misleading information. 

(B)   As this surely can’t be true, then if these 17 stations were the ones used, this is direct and clear evidence that the Bureau’s Percentile Matching algorithm for making homogenisation adjustments did not produce correct, successful, or useful results, and further, that no meaningful quality assurance occurred.

If homogenising did not work for Rutherglen minima, it may not have worked at the other 111 stations. 

While I am sure to be accused of “cherry picking”, this analysis is of 100% of the sites for which the identities of comparison stations have been released.  When the Bureau releases the lists of comparison stations for the other 111 sites we can continue the process.

A complete audit of the whole network is urgently needed.

Rutherglen: Spot the Outlier

September 2, 2014

In today’s Australian there was another article by Graham Lloyd, “Climate scientists defend data changes”. The Bureau of Meteorology is quoted as claiming that “statistical analysis of minimum temperatures at Rutherglen indicated jumps in the data in 1966 and 1974….. These changes were determined through comparison with 17 nearby sites”.

 Two and a half years after being asked to explain the reasons for the myriads of changes to the data, the Bureau has finally given up some of the information it should have released in 2012.  I have been given the names of these 17 sites.  They are:

74034 Corowa, 82053 Wangaratta, 82002 Benalla, 72097 Albury Pumping Station, 82100 Bonegilla

74106 Tocumwal, 81049 Tatura, 81084 Lemnos, 72023 Hume Reservoir, 82001 Beechworth

72150 Wagga Wagga, 74114 Wagga Research Centre, 80015 Echuca, 74039 Deniliquin (Falkiner Memorial)

74062 Leeton, 74128 Deniliquin, and 75032 Hillston.

 This at last allows me to understand how they went about turning a cooling trend of -0.33C per 100 years into a warming trend of +1.74C. 

 Fig. 1: Rutherglen unadjusted data vs adjusted, 1913 – 2013

rutherglen tmin

  I checked the monthly unadjusted minimum data for Rutherglen, the adjusted data for Rutherglen, and the unadjusted data at all 17 of the listed neighbours, in the period 1951 – 1980, which according to the Bureau is the critical period containing the 1966 and 1974 break points.  30 years is a suitably long period for analysis.  For the technically minded, I calculated monthly anomalies from the 1951-1980 means for each record, then 12 month averages.  This should allow us to see the problems around 1966 and 1974.

 Here is a chart of the results.  Can you spot the outlier?

 Fig. 2:  Rutherglen raw (unadjusted), the 17 neighbours’ raw data, and Rutherglen Acorn (adjusted)

 rutherglen v Acorn v neighbours all

You won’t be able to pick out the light blue line of Rutherglen raw data in the spaghetti lines of the neighbours, but you should be able to see the dark red of the adjusted data peeping above and below the others.

 For a clearer picture, here is the same information, but with the 17 neighbours averaged to a single orange line.

 Fig. 3: Rutherglen unadjusted (blue), average of the 17 neighbours (orange), and Acorn- the homogenised version of Rutherglen (dark red).

 rutherglen v Acorn v neighbours avg

Forgive me, but I thought the idea of “homogenising” was to adjust the data so that it is not so different from the neighbours.  That happens in1966.  They got that right, but not in 1974, where the adjustments have increased the difference, and have produced warming.  Odd things also happen in 1952, 1954, 1957, 1969, and 1975-80.

 It is clear that the changes to the temperatures at Rutherglen do not “homogenise” them.  They make the differences from the neighbours greater, and change a cooling trend into a warming one.

 This is not unique to Rutherglen- adjustments warm the temperature trends at 66 of the 104 Australian sites, and warm the national mean temperature trend by around 47%.

 But what would I know- I’m just an amateur according to Professor Karoly.

The Australian Temperature Record- A Quick Update

August 23, 2014

This morning (Saturday 23 August) the Weekend Australian published articles by Graham Lloyd, their Environment Editor, on homogenisation practices at the Bureau of Meteorology as questioned by Jennifer Marohasy.  As I had a small part to play in bringing this to public light, here is a brief post to bring readers up to date.

The last paragraph in the second article reads:

“And the bureau says an extensive study has found homogeneity adjustments have little impact on national trends and changes in temperature extremes.”

This is laughable.  Here is a graph of the national means of Raw and Homogenised minima data from 83 sites (out of 104) that I was able to compare directly. (I also analysed the remaining sites, finding 47% bias, but because large slabs of data had to be left out this is not reliable.)

Fig. 1: Australian mean minimum temperature anomalies 1910-2012

Tmin comp

 The ‘raw’ trend is +0.63C per 100 years.  The adjusted trend is +1.05C.  The effect of the homogenisation adjustments is an increase in the national trend of +0.42C or 66.6%.  So much for “little impact.”

The article referred mainly to adjustments at Amberley and Rutherglen.

Fig. 2:  Amberley minima

amberley tmin

According to the BOM, the major adjustment was due to a pronounced discontinuity around 1980, that is, Amberley’s drop in temperature is not reflected in those of neighbouring sites, as is evidently correct.

Fig. 3:  Amberley compared with the mean of 5 Acorn neighbours

amb raw v reg mean raw

 However, the nearest Acorn site only 50km away, Brisbane Aero, also has a pronounced cooling trend, and a local cooling cannot be discounted.

An adjustment to the raw data before 1980 may be warranted, however, the size of the adjustment is questionable to say the least.  The resulting trend at Amberley has now become greater than the trend of adjusted data at every one of the Acorn neighbours, and more than +0.86C greater than their mean.

Fig. 4: Amberley’s adjusted (Acorn) data vs mean of adjusted data at 5 closest Acorn sitesamb acorn v reg acorn

Rutherglen in Victoria again shows cooling turned into warming.

Fig.5: Rutherglen minima

rutherglen tmin

And again, the Acorn adjustments make Rutherglen’s trend greater than every one of its neighbours’ adjusted trends, as well as their mean:

Fig. 6: Rutherglen Acorn vs neighbours’ Acorn (mean)

rutherglen acorn v reg acorn

 

The BOM is defending its territory, but this latest media exposure will mean increasing and critical scrutiny.

Click for further examples and background.

 

 

 

Adjustments vs CO2

August 3, 2014

Steven Goddard has posted about the remarkable correlation between USHCN adjustments and atmospheric carbon dioxide concentrations:

goddard co2

Here’s my plot of Australian adjustments to minima, Acorn minus raw vs CO2 data (downloaded from NASA GISS at

http://data.giss.nasa.gov/modelforce/ghgases/Fig1A.ext.txt ):

acorn vs co2

R2= 0.777 not as impressive as 0.988, so not proof of anything except past cooling adjustments which we already knew.  Interesting all the same.

Tarcoola- A Cooling Outlier

July 28, 2014

In a previous post I looked at the warming outliers in the Acorn network- those sites that had homogenisation adjustments that created a difference of more than +2 degrees Celsius between the Acorn trend and the raw trend in minima.  In all of these six examples, the adjustments had created trends that were not just greater than the raw trends at each site, not just the mean of their Acorn neighbours raw data trends, but greater than the Acorn trends of their neighbours, and in all but one, greater than each of the individual Acorn trends of their neighbours.

In this post I consider the opposite scenario.  I look at one cooling outlier, Tarcoola in South Australia, where the cooling adjustments have created a difference in trend of -2.81C per 100 years.  There is one other, Forrest in W.A., with an enormous cooling adjustment of around -2.14C, but I have little faith in the accuracy of the data there.  Greg Geegman suggested in a comment that if a site that is adjusted downwards is cooled relative to the neighbour group, this may indicate the Percentile Matching algorithm operates iteratively, although Technical Report No. 49 does not mention this.  An alternative explanation might be that the algorithm is too sensitive and exaggerates necessary adjustments.

All data may be downloaded from the BOM website: Site networks and Climate Data Online.

Tarcoola is in the centre of South Australia:Tarcoola map

As before, I compare Tarcoola with its neighbours in the Acorn network, using anomalies from the 1961-1990 mean.

Fig. 1:  Tarcoola Acorn vs ‘Raw’ minimaTarcoola tmin

Cooler trend than raw.  Note the spurious data pre-1930.

Fig. 2: Tarcoola raw vs mean of Acorn neighbours’ rawtarcoola raw v reg mean raw

Tarcoola appears to need cooling.

Fig. 3: Tarcoola Acorn vs mean of neighbours’ meantarcoola acorn v reg raw

Cooler trend than neighbours’ raw

Fig. 4: Tarcoola Acorn vs mean of neighbours’ Acorntarcoola acorn v reg acorn

Cooler trend than neighbours Acorn

Tarcoola Acorn trend is also cooler than each of the neighbours’ individual Acorn trends.

So which neighbours were used to make the Tarcoola adjustments?

Conclusion:

Both warming and cooling outliers show Acorn adjustments outperforming those of the neighbours. This suggests that the algorithm exaggerates adjustments, both warming and cooling, and needs serious re-examination.

Carnarvon- a closer look

July 24, 2014

A lot of interest was generated by my last post on the Acorn outliers, especially the dependence on very distant sites for homogenisation adjustments.  In this post I will compare Carnarvon’s closer neighbours – excluding Wittenoom, Meekatharra, and Morowa- to show how  a better understanding of Carnarvon’s minimum temperature record may be derived, and how reliance on more distant sites with different climate regimes can distort adjustments.

Carnarvon Airport 6011 has been recording temperatures since 1945.  Before that, Carnarvon Post Office 6062 has data from 1885 to 1950 so there is useful overlap.

Fig. 1: Carnarvon PO and Carnarvon Airport (raw minima)carnarvon raw

These records can be spliced by reducing the Post Office data for 1946-1948 by 0.4C (as the Post Office recorded increasingly warmer minima than the Airport in these years as shown by the monthly temperatures for 1949-1950) but making no changes to PO data before this, to produce a long composite record.  I commence at 1910 to compare with the official BOM figures.

Fig. 2: Carnarvon splice vs Carnarvon Acorncarnarvon tmin

Note how Acorn reduces minima from 1974.  Note the size of these adjustments.

Fig. 3: AdjustmentsCarnarvon adjustments

So at 1910 the Acorn record shows minima 1.8C less than the raw data.

Now lets look at how Carnarvon’s neighbours compare.  To do this we need to convert to anomalies from the 1961-1990 mean.  Neighbours are listed at Climate Data Online, ranging from 19 km  to 296 km away, but most are too short or have too much missing data to be useful.

The neighbours that I have used for comparison are:  Hamelin Pool (174.4 km away), Winning (211.3 km), Emu Creek (248.5 km), and Learmonth (296.3 km).  Learmonth is almost due north of Carnarvon, and like Carnarvon right on the coast, while the others are inland sites.

Fig. 4: Carnarvon and closest useful neighboursCarnarvon neighbours

We can see that there is close agreement for most of the time.  There are minor periods of disagreement in the 1970s and 1990s, but the major disagreement is 1926-1950.  Which is a more accurate reflection of Carnarvon minima- Carnarvon PO or Hamelin Pool?  To find which is the odd one out, we need to look at other sites with data for this period.

Fig. 5: Carnarvon vs Winning- anomalies from 1910-1939 meanCarnarvon v Winning

Winning, although confirming the approximate agreement 1910-1920,  has very little data for 1926-1950, so we have to look further afield… all the way to Geraldton, which like Carnarvon is on the coast, but 447 km south.

Fig. 6:  All neighbours including GeraldtonCarnarvon inc Geraldton

Hamelin Pool is clearly the outlier, so we can accept Carnarvon raw temperatures as reasonably accurate from 1910 to 1970.  There is a short period in the 1970s of disagreement, but little difference after that… and Acorn does not adjust after 1974 anyway.

How does this compare with Acorn?

Fig. 7: All anomalies including AcornCarnarvon acorn vs all

Can you pick the outlier?

We can only presume that the Acorn homogenisation depends on data fed into the algorithm from much, much further away.

I can see no justification for any major adjustment to the raw record at Carnarvon.

 

The Australian Temperature Record Revisited: Part 4- Outliers

July 16, 2014

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.

Results:

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 less than the trend for the mean of the neighbours’ Acorn data.  (This is the only outlier site where this happens, as you will see.)

Amberley

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.

Dubbo

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.

Rutherglen

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

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.

 

The Australian Temperature Record Revisited Part 3: Remaining Sites

June 15, 2014

In Part 1 of this series I showed a 66.6% increase in warming trend of Australian annual minimum temperatures caused by adjustments to the ‘raw’ data.  This was based on analysis of 83 of the 104 Acorn sites, as I restricted my study to only those sites with at least 24 months overlap between old and new stations within 30 kilometres.  I now turn to the remaining sites.

These remaining sites all have records less than the full 103 years, as I only use the longest available record from a single site, with no splicing to form a composite record.  I truncated Acorn and ‘raw’ annual data to exactly the same start and end dates.  Trends calculated over these shorter periods are therefore exaggerated.  As well, some of the records show enormous gaps.  Trends calculated for these sites showed much less warming bias than the 83 I first analysed: the mean difference in trend was +0.26 C, or 26.7% increase.  This is not a meaningful metric, however.  The crucial measure is the effect of the adjustments across the whole network.  To do this, temperature data must be converted to anomalies from the 1961-1990 mean.  This meant the loss of Tennant Creek PO, which has insufficient data in this time period.

Here, then, is the result for 103 of the 104 Acorn sites.  Figure 1 shows the straight mean of minima anomalies for the 103 sites for which data can be compared, ‘raw’ vs Acorn.

Fig.1:103 chart

The adjustments to the ‘raw’ data have the effect of increasing the trend in minimum temperatures from +0.7C per 100 years to +1.03C, or 47%.  Going by this plot, the increase is by nearly half rather than two-thirds- still embarrassingly large.  However, large slabs of data are missing or unaccounted for.  I have zero confidence that the trend in minima is +0.63, +0.7, +1.0, or +1.03, or any other figure, and an average trend for Australia is meaningless given the wide differences in different parts.  By the way, with no stations missing, the warming bias in Victoria is still +350%.

In my next post I will look at some of the ‘outlier’ sites with very large differences in trend.

The Australian Temperature Record Revisited Part 2: Regional Effects

June 1, 2014

In my last post I showed how a numerical near-balance of adjustments to the ‘raw’ minimum temperatures at 83 out of 104 Acorn sites resulted in a 66.6% increase in warming trend across the nation.

I now turn to the effect on state and regional temperatures, which is enormously varied.

Figure 1 shows the official BOM trend map of trends in minima from 1910 to 2013:Trend map min

Note the little “bulls eyes” in various places, indicating where the local trend at individual sites is out of sync with the wider trend.  I’m sure you can identify Tibooburra in north western NSW, Richmond in northern inland Qld, Rutherglen in Victoria, Marree in northern SA, and Carnarvon on the WA coast.

Figure 2 shows the median position of all 104 sites, the four unequal area quadrants, and the number of sites I analysed in each with the increased warming resulting from adjustments.
Median network position map adj results

The concentration of Acorn sites in the south east of Australia, and the concentration of warming adjustment there as well, is plainly obvious.

Now I shall show each quadrant in turn, showing the trend difference at each site.

Figure 3:  South west Quadrant sites:
Bar graph SW Quad

Figure 4: SW Quadrant minimum temperature trends:SW quad chart

Figure 5:  North west Quadrant sites:Bar graph NW Quad

Figure 6:  NW Quadrant minimum temperature trends:NW quad chart

Figure 7:  North east Quadrant sites:Bar graph NE Quad

Figure 8:  NE Quadrant minimum temperature trends:NE quad chart

Figure  9:  South east Quadrant sites:Bar graph SE Quad

Figure  10: SE Quadrant minimum temperature trends:SE quad chart

In the next section I look at how the adjustments affect the mean minima in each state.  First I’ll look at the Northern Territory, which is atypical and based on only three sites (Alice Springs, Victoria River Downs, and Rabbit Flat), the two last with less than 50 years of observations.

Figure  11:  Northern Territory- cooling reversedNT Chart

Figure 12:  South Australia- adjustments result in less warmingSA chart

Figure 13:  Tasmania- adjustments result in less warmingTas chart

Figure 14: Western Australia- 23.7% increased warming.WA chart

Figure 15:  Queensland- 37% extra warmingQld chart

So far, every state has seen an increase in warming much less than the national mean of 66.6%, so much depends on the final two states.

Figure  16:  New South Wales- 245% extra warming!NSW chart

That is pretty amazing, but the result for Victoria is even more astounding.

Figure 17: VictoriaVic chart

The implications for the trend map in Figure 1 are obvious.  One hopes that those adjustments are well and truly justified!

In the next post I will discuss the remaining 21 sites which I am unable to compare directly, and later, the trend outliers.


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