Posts Tagged ‘Acorn’

DTR and Rainfall

September 12, 2016

I’ve been looking at DTR and rainfall relationships for Northern and Southern Australia.  I’ve also analysed them by winter and summer (southern and northern wet seasons).

I’ve used a different approach.  Instead of comparing DTR with rainfall anomalies (differences from the mean) I’ve converted these to percentage differences from the mean rainfall.

Data are from the BOM climate change page, so DTR is based on Acorn.  DTR before 1950, and especially before 1932, may be suspect.  However the data are useful for this comparison.

Propositions to test:

DTR which is supposed to decrease as a fingerprint of greenhouse warming, is strongly related to rainfall variation.

There is an unexplained increase in DTR around 2001.

In the time series plots below, rainfall has been inverted, so ‘up’ is dry and ‘down’ is wet.  The rainfall anomalies are expressed as percentages difference from the mean and scaled down by 50.

dtr-rain-oz-ann

dtr-vs-rain-oz-ann

dtr-rain-n-oz-ann

dtr-vs-rain-n-oz-ann

dtr-rain-s-oz-ann

dtr-vs-rain-s-oz-ann

Now comparisons during northern wet season (November to April, basically summer), and southern wet season (May to October- winter and spring).

dtr-rain-oz-summ

dtr-vs-rain-oz-summ

dtr-rain-oz-wint

dtr-vs-rain-oz-wint

dtr-rain-n-oz-summ

dtr-vs-rain-n-oz-summ

dtr-rain-n-oz-wint

dtr-vs-rain-n-oz-wint

dtr-rain-s-oz-summ

dtr-vs-rain-s-oz-summ

dtr-rain-s-oz-wint

dtr-vs-rain-s-oz-wint

Results:

table

 

 

 

 

 

 

Notice that Southern Australian winters dominate DTR.  The impact of rainfall on DTR in Southern Australian winters is twice that in Northern Australian winters, and correlates better as well.  Also note that Southern summers have very slightly higher DTR change per rainfall change and slightly better correlation than Northern.  No doubt you realise winters up here can’t really be compared with southern winters, being mild and very dry.  In many places it is not very difficult to double the mean rainfall in winter with not many millimetres of rain, and zero rain for many months in winter is not unusual.

This plot shows Cusums of DTR and inverted, scaled rainfall.

cusums

The turning points line up exactly, including 2001.  There is no visible unusual change in 2001.  There are however times when the Cusums diverge: 1932, 1958, 1985, and 2003 and 2011.

DTR is strongly related to rainfall variation, especially in southern Australia in winter.

There is no unexplained increase in DTR in 2001.

 

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Rainfall and Temperatures Part 2

November 29, 2015

In my last post I showed how in Australia more than three quarters of the difference between surface maxima and tropospheric anomalies can be explained by variation in rainfall alone. Figure 12 from that post showed that clearly:

Fig. 1: 12 month rainfall vs surface maxima – TLT difference: Australia

max diff v rain scatterplot

In this post I am looking at the different contributions made by the north and the south of Australia. This map shows the regions used for climate analysis by the Bureau.

Fig. 2: Climate regions

Climate regions
Northern Australia and Southern Australia have vastly different climates, as shown by the following graphs of mean monthly rainfall:

Fig. 3: Mean Monthly Rainfall: Northern Australia

Nthn rain av

Fig. 4: Mean Monthly Rainfall: Southern Australia

Sthn rain av

The sheer volume of wet season rain in the north dominates, and distorts, the national means, therefore it is sensible to analyse northern and southern influences separately.

Northern Australia, north of 26 degrees South, has less than 3 degrees outside the Tropics, so may be considered the tropical northern half of Australia. Do not think of this as a lush tropical paradise. Far from it. There are a couple of very small areas of wet tropics, and some softer country in the far south-east, but the rest is either monsoonal wet/dry (very wet summers, almost completely dry for the rest of the year), or desert. The rainfall graph for Northern Australia is for the whole region- most of which is desert. If the monsoon is weak or fails altogether we get drought.

Southern Australia is largely influenced by the Southern Annular Mode. Each winter the southern high pressure systems move north, and cold fronts sweep across the south bringing winter rains. If these systems don’t move far enough north, the rain systems dodge the bottom of the continent, resulting in drought conditions. The far north-east of Southern Australia (southern Queensland and northern New South Wales) gets a wet summer/ dry winter pattern, and Tasmania and coastal New South Wales get rain in all seasons.

Comparing the influences of northern and southern rainfall on the national surface- TLT differences:

Fig. 5: Northern rain vs national maxima- TLT difference

Nthn rain v nat max diff

More than two thirds of the national maxima-TLT difference can be explained by variation in the northern rainfall alone.

Southern rainfall has a much weaker correlation with national maxima- TLT difference:

Fig. 6: Southern rain vs national maxima- TLT difference

Sthn rain v nat max diff

Now let’s plot Northern rain vs northern maxima- TLT (for the whole of Australia) difference, firstly for each month:

Fig. 7: Northern rain vs northern maxima- national TLT difference: monthly

Nth rain v nth diff monthly

Nearly two thirds of the monthly difference can be explained by monthly rainfall alone.

Fig. 8: Northern rain vs northern maxima- national TLT difference: 3 monthly

Nth rain v nth diff 3m

Three quarters of the 3 month mean surface maxima minus national TLT difference can be explained by rainfall.

Fig. 9: Northern rain vs northern maxima- national TLT difference: 12 monthly

Nth rain v nth diff 12m

R squared value of 0.8348 corresponds to a correlation of -0.91! But wait- there’s more! The 24 month means give an even better fit!

Fig. 10: Northern rain vs northern maxima- national TLT difference: 24 monthly

Nth rain v nth diff 24m

And 120 month means show an extremely close fit:

Fig. 11: Northern rain vs northern maxima- national TLT difference: decadal

Nth rain v nth diff 120m

97% of decadal northern surface maxima- national TLT difference is explained by decadal northern rainfall variation.

Fig. 12: Southern rain vs southern maxima- TLT difference: monthly

Sth rain v Sth diff monthly

Fig. 13: Southern rain vs southern maxima- TLT difference: 3 monthly

Sth rain v Sth diff 3m

Fig. 14: Southern rain vs southern maxima- TLT difference: 12 monthly

Sth rain v Sth diff 12m

More than half the difference between southern Australian maxima and TLT can be explained by southern rainfall variation.

However, 24 month means are not as good a fit:

Fig. 15: Southern rain vs southern maxima- TLT difference: 24 monthly

Sth rain v Sth diff 24m

And the long term means are a much poorer fit:

Fig. 16: Southern rain vs southern maxima- TLT difference: decadal

Sth rain v Sth diff 120m

Only 34% of the decadal southern Australian maxima-TLT difference is due to rainfall variation.

In tabular form:

Fig. 17: Range of rainfall anomalies and R-squared values for regional rainfall vs regional surface maxima- national TLT differences

Table rain r2

Conclusion:

Australian climate is dominated by the tropics, and tropical rainfall variation dominates the national surface- troposphere differences, and even more so the tropical surface – national troposphere temperature differences: the greater the rainfall variation, the greater the difference between surface and tropospheric temperatures.

For a better analysis, we would need UAH anomalies for Australia separated into north and south of 26 degrees South.

Case Studies in “World’s Best Practice” 2: Kerang

November 5, 2015

Introduction:  This series of posts is intended to show that despite Greg Hunt’s loyalty, all is not right at the Bureau of Meteorology.

Please refer to my first post, Case Studies in “World’s Best Practice” 1:  Wilsons Promontory, for a complete description of the Bureau’s claims, the problems, data sources, and my methods.

Here are some further examples of “World’s Best Practice”.

********************

Kerang is on the Murray River, about 250 km from Melbourne.  The story of temperature adjustments here illustrates much that is wrong with the Bureau: misinformation, incompetence, lack of transparency, and unscientific behaviour.  This post took longer than expected because the more I looked, the more problems I found.

Note: Both maxima and minima at Kerang are warming. I have no comment on whether the adjustments are justified.  I am only interested in the methods used.

Problem 1: Missing data

The Bureau’s claim that they provide raw data as well as adjusted data is a half-truth, and completely misleading- some would say, dishonest.

The Bureau has adjusted Kerang maxima at 01/06/1957 and 01/01/1922, and minima at 18/01/2000 and 01/08/1932, and provides daily adjusted temperatures from 1/1/1910.

Unfortunately, there are NO daily raw data for Kerang before 1/1/1962.

Where are 52 years of daily temperatures?  How is it possible to have adjusted digitised data but no raw digitised data for half of the record?

Another issue brought to my attention is that there is an enormous amount of data missing even from Acorn: a large proportion every year before 1960, especially from 1932 to 1949, when 100 to 180 days are missing every year.

null days kerang

This lack of transparency makes it impossible to replicate and analyse the adjustments at Kerang.  If it can’t be replicated, with all data made available, it isn’t science.

Problem 2: Nonsense temperatures

There is only one instance when Acorn shows that the minimum temperature, the lowest temperature for the 24 hour period, was higher than the maximum temperature.

min max kerang

That dot at ‘0.6’ shows that on 2nd February 1950 the coldest temperature was 0.6C hotter than the hottest temperature!  Unfortunately it is impossible to compare with the missing raw data.

Any organisation that can’t perform a basic quality control test on its product is incompetent, as is any Review Panel or Technical Advisory Forum that endorses it.

Problem 3: Artificial warming 

Even though UHI makes Melbourne unsuitable for use in climate analysis, the Bureau still uses it to adjust the early data at Kerang!

Problem 4:  Neighbours

One of the neighbours used to adjust Kerang is Broken Hill, 477 km away, and another is Snowtown in South Australia, 565 km away.

Problem 5:  Results of adjustment

Comparison of differences between Kerang and its neighbours, pre- and post adjustment, using annual temperatures.

Firstly, minima, from the 2000 adjustment: Kerang minus neighbours, annual anomalies from 1985-2014.

Kerang comp 2000 min

The adjustment of -0.4C applied to years before 2000 is too great.  The slope of the mean difference from the neighbours is much too steep.

Next, for the 1932 adjustment (annual anomalies from 1917-1946 means):

Kerang comp 1932 min

Again, the adjustment is too great, as they make the differences from neighbours much greater.

The same pattern follows with maxima.  The 1957 adjustment (anomalies from 1944-1973):

Kerang comp 1957 max

And the 1922 adjustment (anomalies from 1910-1938):

Kerang comp 1922 max

In both cases Kerang is cooling compared with neighbours, but the adjustments reverse this and make Kerang compare less well with its neighbours.

Problem 6:  Undocumented adjustments

The Bureau lists only two adjustments to minima at Kerang:  -0.4 on 18/01/2000 and -0.61 on 01/08/1932.  This is not the whole story, as a plot of the actual annualised adjustments shows:

Kerang adjustments min

If the adjustments were as stated, the difference between adjusted and raw temperatures would be indicated by the blue lines.  The actual adjustments are shown by the brown lines.

The queried adjustments are not mentioned in the Bureau’s list here.

Similarly, there are two documented adjustments to maxima: -0.71 on 01/06/1957 and +0.33 on 01/01/1922.  These are visible in the next graph, but note the extra adjustment before 1950, and a series of adjustments from 1948 back to 1925.

Kerang adjustments max

I understand why these are needed: to adjust for the steadily increasing difference between Kerang and neighbours in this period.  But why was this not documented?

Thus we see at Kerang further misinformation and lack of transparency through failure to supply digitised raw data to allow replication; incompetence through not using basic checks for data integrity, resulting in publication of the “world’s best practice” temperature dataset with minimum temperatures higher than maximum; use of UHI contaminated sites when making adjustments; use of distant neighbours from different climate regimes; over-zealous adjustments resulting in worse comparison with neighbours than before; and undocumented adjustments.

Half-truths, incompetence, lack of transparency, and unscientific practices are evident at many other sites.  A proper investigation into the Bureau is overdue.

Case Studies in “World’s Best Practice” 1: Wilsons Promontory

October 26, 2015

Introduction: This series of posts is intended to show that despite Greg Hunt’s loyalty, all is not right at the Bureau of Meteorology.

The Bureau describes its methodology for creating the ACORN-SAT temperature reconstruction as “world’s best practice”, as it was described thus by the 2011 International Review Panel. The recent Report of the Technical Advisory Forum accepts this claim, reporting that “the Forum did not prioritise further international comparison of the Bureau’s curation methods in this report. However, the Forum will revisit this issue at its next meeting in 2016.”

In light of this endorsement, here are some examples of “World’s Best Practice”.
**********************************************************

Wilsons Promontory Lighthouse is on the southernmost tip of the Australian continent, about 170 km from Melbourne. The story of temperature adjustments here illustrates much that is wrong with the Bureau: misinformation, incompetence, lack of transparency, and unscientific behaviour.

Note: Both maxima and minima at Wilsons Promontory are warming. The Minima trend has been cooled, the maxima warmed.  I have no comment on whether the adjustments are justified. I am only interested in the methods used.

ACORN-SAT, (Australian Climate Observation Reference Network- Surface Air Temperatures), was introduced in March 2012, with several revisions mainly to bring the series up to date. It is a daily dataset of minima and maxima, from which monthly and annual means are derived, for 112 sites around Australia. Raw temperature data at these sites were homogenised by a complicated algorithm by comparison with neighbouring sites.

After much criticism, the Bureau has been forced to provide some answers, and agreed to ‘checking’ by a Technical Advisory Forum. The Bureau has provided additional information at the Acorn website, and in September 2014 released a list of the sites with adjustment dates, amounts, and the neighbour sites used for adjustment (see http://www.bom.gov.au/climate/change/acorn-sat/documents/ACORN-SAT-Station-adjustment-summary.pdf). Unfortunately, this additional information has raised more questions than it has unsuccessfully answered.

Problem 1: Missing data
The Bureau says at its FAQ No. 6 at http://www.bom.gov.au/climate/change/acorn-sat/#tabs=FAQs ,
the Bureau provides the public with raw, unadjusted temperature data for each station or site in the national climate database, as well as adjusted temperature data for 112 locations across Australia”, and at No. 8, “Daily digitised data are now available back to 1910 or earlier at 60 of the 112 ACORN-SAT locations, as well as at some non-ACORN-SAT locations.

This is a half-truth, and completely misleading- some would say, dishonest.

The Bureau provides raw data at Climate Data Online at http://www.bom.gov.au/climate/data/, and adjusted data at http://www.bom.gov.au/climate/change/acorn-sat/#tabs=Data-and-networks.

The Bureau has adjusted all Wilsons Promontory maxima before 1/1/1950, and minima before 1/1/1930, and provides daily adjusted temperatures from 1/1/1910.

Unfortunately, there are NO daily raw data for Wilsons Promontory before 1/1/1957.

Where are 47 years of daily temperatures? How is it possible to have adjusted digitised data but no raw digitised data?

Likewise, of the 10 neighbouring sites used for the pre-1950 maxima adjustments, only five have daily raw data before 1957, and for minima, only two (and one is Melbourne- more later). Were the adjustments made with only two comparisons? Otherwise, where are the data for the others?

This lack of transparency makes it impossible to replicate and analyse the adjustments at Wilsons Promontory. If it can’t be replicated, with all data made available, it isn’t science.

Problem 2: Nonsense temperatures
There are 79 instances when Acorn shows that the minimum temperature, the lowest temperature for the 24 hour period, was higher than the maximum temperature.

min max wils promThat dot at ‘1’ shows that on 5th December 1911 the coldest temperature was one degree hotter than the hottest temperature!

All of these occurred before 1950, so it is impossible to compare with the raw data.

The Bureau dismisses this as a minor hiccup of no importance, as an artefact of the adjustment process. The Bureau goes to great pains to explain how carefully the raw data was checked to remove any glaring errors and mistakes. On page 31 of CAWCR Technical Report No. 049, the section “Quality control checks used for the ACORN-SAT data set” describes a test for internal consistency of daily maximum and minimum temperature, which was carried out on the raw data of the ACORN-SAT sites. This test for minima greater than maxima, the first and most important quality control check, obviously was not applied to the adjusted data at all, and these nonsensical values remain years after sceptics made the Bureau aware. Any organisation that can’t perform a basic quality control test on its product is incompetent, as is any Review Panel or Technical Advisory Forum that endorses it.

 

Problem 3: Artificial warming
Here are the neighbouring sites used.

Maxima: East Sale Airport, Geelong SEC, Laverton RAAF*, Orbost, Queenscliff, Cape Otway Lighthouse, Melbourne Regional Office*, Essendon Airport, Currie, and Ballarat Aerodrome.

Minima: Cape Otway Lighthouse, Kerang, Melbourne Regional Office*, Eddystone Point, Geelong SEC, Bendigo Prison, Swan Hill PO, Cape Bruny Lighthouse, Currie, and Ballarat Aerodrome.

On page 71 of CAWCR Technical Report No. 049 is the statement, “the potential still exists for urbanisation to induce artificial warming trends relative to the surrounding region, and it is therefore necessary to identify such locations to prevent them from unduly influencing assessments of background climate change.

Included in the eight stations not used in climate analysis because their records exhibit Urban Heat Island effects are Laverton RAAF and Melbourne. Even though UHI makes Melbourne and Laverton unsuitable for use in climate analysis, the Bureau still uses them to adjust the data at Wilsons Promontory!

 

Problem 4: Neighbours
Cape Bruny Lighthouse is on the far south east coast of Tasmania, and is 509 km south of Wilsons Promontory. Kerang is on the Murray River, 413 km northwest, in a dry inland area, as is Swan Hill, 468 km away. Were there no better correlated sites nearer?

 

Problem 5: Results of adjustment.
To compare the temperature record at Wilsons Promontory with its neighbours, as we don’t have daily data, we can only use monthly or annual data. A simple but reliable method is to calculate the difference between Wilsons Promontory and each neighbour. This is done for raw and adjusted anomalies from the mean of a common baseline period. If Wilsons Promontory compares well with its neighbours, the differences should be close to zero, and most importantly, in spite of any short fluctuations, there should no trend: Wilsons Promontory should not be warming or cooling relative to its neighbours.

 

Unfortunately there are no monthly or annual data before 1957 for Eddystone Point or Bendigo Prison, so comparison is further restricted.

 

Firstly, minima: Wilsons Promontory minus neighbours, annual anomalies from 1916-1945, raw data.
raw min diffs wils prom

The differences range from +2 degrees to – 2 degrees, so there is plenty of variance, but the bulk of differences are +0.5 to -0.5 degrees. The spaghetti lines can be averaged to show the mean difference.
raw min avg diff wils prom

While there are periods of significant differences (1924-26, 1958-60, and 1974) it is plain that the raw data difference shows zero trend, indicating good comparison between Wilsons Promontory and its neighbours. Now compare the differences following the 1930 adjustment:
raw v adj min wils prom

The Acorn adjusted record preserves the periods of large differences, but has Wilsons Promontory cooling relative to its neighbours by more than half a degree per 100 years. The adjustment was too large.
Here is the comparison for maxima (anomalies from 1936-1965).
raw v adj max wils prom

The raw data show Wilsons Promontory cooling a little (-0.13C per 100 years) relative to the neighbours, but Acorn overcorrects, resulting in warming (+0.18C per 100 years) too much compared with the neighbours.

 
Problem 6: Site quality
On pp. 22-23 of Techniques involved in developing the Australian Climate Observations Reference Network – Surface Air Temperature (ACORN-SAT) dataset (CAWCR Technical Report No. 049) by Blair Trewin, March 2012, we find:-
Standards for instrument exposure and siting in Australia are laid down by Observations Specification 2013.1 (Bureau of Meteorology, 1997). Among the guidelines are:
• Sites should be representative of the mean conditions over the area of interest (e.g., an airport or climatic region), except for sites specifically intended to monitor localised phenomena.
• The instrument enclosure (if there is one) should be level, clearly defined and covered with as much of the natural vegetation of the area that can be kept cut to a height of a few centimetres.
• The distance of any obstruction should be at least four times the height of the obstruction away from the enclosure. (This criterion is primarily directed at elements other than temperature; for temperature the last guideline is more important.)
• The base of the instrument shelter should be 1.1 metres above the ground, with the thermometers approximately 1.2 metres above the ground.
• If no instrument enclosure is provided, the shelter should be installed on level ground covered with either the natural vegetation of the area or unwatered grass, and should be freely exposed to the sun and wind. It should not be shielded by or close to trees, buildings, fences, walls or other obstructions, or extensive areas of concrete, asphalt, rock or other such surfaces – a minimum clearance of five times the width of the hard surface is recommended.

 
The following photos are from Dayna’s Blog, a fascinating blog about bushwalking in SE Australia. (Interested readers are encouraged to visit https://daynaa2000.wordpress.com/ for some excellent walking tour information and photographs.)

 
The first view is towards the southwest, towards the direction of the prevailing south-westerly winds.
WilsonPLighthousenSolarPanels notes

Note the large areas of concrete under and near the Stevenson Screen; the nearby rock walls, the nearby solar panels almost directly to the south of the screen.

 
The second photo is in the opposite direction and shows the proximity of a building, another rock wall, and the steep slope of the site.
wilspromphoto east

These photographs make a mockery of the Station Catalogue description, which calls it “a very exposed location”. There are several man made features which surely influence temperatures recorded. Jennifer Marohasy recently asked the Bureau whether the solar panels would reflect onto the screen. The reply was,
“The angle of the panels means that any reflection from the panels is likely to only intersect the instrument shelter for a small part of the day during a limited part of the year. As the instrument shelter is fitted with double-louvered wall panels, it is virtually impossible that a direct beam of light would be able to enter the screen. Further, it is unlikely that the solar panels are influencing the instrument shelter as the shelter is painted to reflect direct and indirect radiation.”

 
Yet in the Station Catalogue for Alice Springs we find this statement “The site was enclosed by a rock wall about 1 m high and painted white that would have interrupted wind flow and reflected heat.”

 
They cannot have it both ways. If a 1m high rock wall interrupts wind flow and reflects heat in Alice Springs, then surely rock walls and buildings, large areas of concrete, and solar panels, all on a downward sloping lee side of a hill, will cause artificial warming at Wilsons Promontory.
Wilsons Promontory is a far from ideal site.

 
Thus we see at Wilsons Promontory misinformation and lack of transparency through failure to supply digitised raw data to allow replication; incompetence through not using basic checks for data integrity, resulting in publication of the “world’s best practice” temperature dataset with minimum temperatures higher than maximum; use of UHI contaminated sites when making adjustments; use of distant neighbours from different climate regimes; over-zealous adjustments resulting in worse comparison with neighbours than before; all at a very poor quality site.
Half-truths, incompetence, lack of transparency, and unscientific practices are evident at many other sites. A proper investigation into the Bureau is overdue.

More on the absurd ACORN adjustment process

September 29, 2015

This is a Letter to the Editor of The Australian I sent recently, but not published.

Sir

Dr Jennifer Marohasy (Ideology adds heat to the debate on climate change, 29/9)  claims that sites prone to Urban Heat Island effect, such as Melbourne, have been used to adjust the temperature records at sites such as Cape Otway.

This is indeed absurd, but true.  Of the 104 sites used for climate analysis, 22 have been adjusted at least in part by comparison with sites whose artificially raised temperatures make them unsuitable for use in that same climate analysis.

The Bureau of Meteorology lists eight sites which are not used in climate analysis because their records exhibit Urban Heat Island effects: Townsville, Rockhampton, Sydney, Richmond (NSW), Melbourne, Laverton RAAF, Adelaide, and Hobart.

According to the Bureau’s “ACORN-SAT Station adjustment summary”, seven of these sites are still used as comparison sites when adjusting raw temperatures at other locations.  Adelaide is used at Snowtown and Port Lincoln; Townsville at Cairns, Mackay and Charters Towers; Rockhampton at Townsville, Mackay, Bundaberg and Gayndah; Sydney at Williamtown, Bathurst, Richmond, Nowra, and Moruya Heads; Laverton at Orbost, Sale, Wilson’s Promontory, Melbourne and Cape Otway; Melbourne at Orbost, Sale, Wilson’s Promontory, Laverton, Kerang, and Cape Otway; and Hobart at Launceston, Eddystone Point, Cape Bruny, Grove, and Butlers Gorge.

Richmond (NSW) is apparently the only site not used in the adjustment process.

Greg Hunt’s faith in the credibility of the Bureau of Meteorology is touching, but just as absurd.

More Rutherglen Nonsense

August 15, 2015

Jennifer Marohasy had an interesting post this week on further explanations by the Bureau for their weird adjustments at Rutherglen.  I was particularly interested in this graphic, which is Chart 3 on the Bureau’s station adjustment summary for Rutherglen.  http://www.bom.gov.au/climate/change/acorn-sat/documents/station-adjustment-summary-Rutherglen.pdf

rutherglen comp BOM

The Bureau is comparing Rutherglen’s raw minima with the adjusted data from Wagga Wagga, Deniliquin, and Kerang.  Three questions immediately spring to mind:  1. As Dr Marohasy points out, what is the Bureau doing comparing raw with adjusted data?  Of course they’re going to have different trends!  2.  Why is Kerang shown, when Kerang is NOT included as a neighbour station used to adjust Rutherglen?  And 3.  What difference does this make?

Time for a reality check.

This graph compares like with like: raw minima for Rutherglen and the same neighbours.  Note that only Kerang is warming, and Wagga Wagga is flat, but Deniliquin and Rutherglen are cooling.

rutherglen comp raw

This graph again compares like with like, the same stations but with adjusted data.

 rutherglen comp adjusted

You might think that this shows Rutherglen is now homogenised with the others correctly.  However, when we examine the differences in anomalies from the 1961-1990 means between Rutherglen and the others, we get this:

rutherglen comp differences ADJ

They still got it wrong!  The trend in differences should be close to zero.   Rutherglen’s adjusted record is warming too fast (+0.5C per 100 years) relative to the three neighbours used by the BOM in their explanation.

And note that since 1974, Rutherglen’s minima have been cooling relative to the others.  Perhaps that cooling they corrected for was real after all?

Even if Rutherglen needs to be adjusted; even if these three sites are adjusted correctly; even if Kerang is one of the stations used by the Bureau to adjust Rutherglen- the adjustments at Rutherglen are over cooked.

The “scientists” in charge of the climate change department in the Bureau deserve all the ridicule they get.

More than that- they are not to be trusted with the nation’s climate history.  We don’t trust their data; we don’t trust their methods; we don’t trust their results; and we don’t trust their motives.

The effect of two adjustments on the climate record

June 24, 2015

The warming bias in Australia’s ACORN-SAT maximum dataset is largely due to just two adjustments.

Last week’s Report of the Technical Advisory Forum’s review of the ACORN-SAT temperature reconstruction produced some rather bland, motherhood type statements.  However, hidden in the public service speak was a distinct message for the Bureau of Meteorology: lift your game.  Two of the areas I have been interested in are (a) whether individual adjustments are justified, and (b) the effect of these adjustments on national and regional temperature trends.  In this post I look at adjustments at just two sites, which are responsible for the single largest increase in national trend.

On page 17 of the Report we find the following graphic:

Fig. 1: Scatterplot of difference between AWAP and Acorn annual mean temperature anomalies.

scatterplot awap acorn mean diff

This is a clear statement of how much Acorn adjustments have cooled past temperatures, as AWAP is regarded as being only “partially homogenised”, and close to raw temperatures.   There is a considerable difference- more than 0.2 degrees- between the two interpretations of temperatures 100 years ago.

Mean temperature is the average of maximum and minimum.  In this post I shall look at just maximum temperatures, from 1911 to 2013.  The following graph is a plot of the difference between monthly Acorn and AWAP maximum anomalies, which I think is much more informative:

Fig. 2:

scatterplot awap acorn max months

Note there is a trend of +0.22 degrees / 100 years in the differences, indicating a predominance of cooling of earlier data; there is a very large range in the first 50 years, from about -0.7C to +0.3C, and one outlier at +0.4C, reducing to a much narrower band in the 1960s before increasing in the last 20 years; and the bulk of differences are negative before 1970.

Now let’s look at what has been happening in the past 35 years- in fact, in the satellite era:

Fig. 3: Monthly differences between AWAP and Acorn before and after December 1978

scatterplot awap acorn max phases

The trend in differences for the first 67 years is 0.33C / 100 years, but there is a very small tendency for Acorn to be cooler than AWAP recently- and the range of differences has been increasing.

That’s an interesting find, but I want to examine in more detail the effect of the adjustments which cause those differences.  Here are annual maxima in AWAP compared with Acorn.

Fig. 4: Annual mean of monthly maximum anomalies: AWAP and Acorn

graph awap acorn max

Again we see that Acorn has increased the warming trend from +0.59C to +0.81C per 100 years, an increase of +0.22C, or 37.3%.

However, the difference appears more marked before the mid 1950s.  The next graph shows the trends from 1911 to 1955 compared with the trends from 1956 to 2013.

Fig. 5: Comparison of trends in maxima before and after the middle of the 20th Century.

graph awap acorn phases

Note: while the trends of AWAP and Acorn are very similar (+1.32 to 1.4C per 100 years) since the 1950s- which the Bureau never tires of proclaiming- before then the plot tells a different story.  Acorn reduces the cooling trend by 0.44C per 100 years, a reduction of 86%.

How was this achieved?

On page 44 of the technical paper CTR-050 we find this explanation:

Returning now to maximum temperature, the differences between the AWAP and ACORN analyses show a marked drop in the early 1930s, with a sudden decrease of about 0.15 °C. This is most likely attributable to substantial negative adjustments between 1929 and 1932 in the ACORN-SAT dataset, indicating substantial discontinuities (expressed as artificial cooling) at a number of individual locations with a large influence on national analyses, because of the sparsity of data in their regions in that period. These discontinuities are mostly related to site moves that are associated with concatenated records for single locations. These include Alice Springs, Kalgoorlie and Meekatharra. Alice Springs, where the adjustment is associated with a site move in late 1931 or early 1932 from the Telegraph Station to a climatologically cooler site in the town, has a notably large “footprint”; at that time there were only two other locations within 600 kilometres (Tennant Creek and Charlotte Waters) which were observing temperatures, while the nearest neighbours to the west (Marble Bar and Wiluna) were more than 1200 kilometres away.

This large change between AWAP and Acorn is shown in the next graph.

Fig. 6: 12 month mean difference in monthly maxima anomalies

graph awap acorn diff 1930 drop

As I explained in my post in September 2014, Acorn sites are homogenised by an algorithm which references up to 10 neighbouring sites.  A test for the validity of the adjustments is to compare the Acorn site’s raw and adjusted data with those of its neighbours, by finding the differences between them.  Ideally, a perfect station with perfect neighbours will show zero differences: the average of their differences will be a straight line at zero.  Importantly, even if the differences fluctuate, there should be zero trend.  Any trend indicates past temperatures appear to be either relatively too warm or too cool at the station being studied.  My aim is to check whether or not individual adjustments make the adjusted Acorn dataset compare with neighbours more closely.   If so, the trend in differences should be close to zero.

I have tested the three sites named above.  I use differences in anomalies calculated from the mean of maxima for the 30 year period centred on 1931, or for the period of overlap if the records are shorter.  The neighbours are those listed by the Bureau on their Adjustments page.

Fig. 7:  Meekatharra differences from neighbours (averaged)

Meek acorn v neighbours avg

Note that the Acorn adjustment (-0.77C at 1/1/1929- the adjustment of +0.54C at 1/1/1934 does not show up in the national signal) is indeed valid: the resultant trend in differences is close to zero, indicating good comparison with neighbours.  However, since Meekatharra’s record starts only in 1927, two years of the Meekatharra adjustment cannot have had a large influence on the national trend as claimed.

Fig. 8:  Kalgoorlie differences from neighbours

Kalg acorn v neighbours avg

Kalgoorlie’s steep cooling compared with neighbours (from 170 km to 546 km away) has been reversed by the Acorn adjustment (-0.62C at 1/1/1930- the adjustment of -0.54C at 1/12/1936 does not show up in the national signal), so that Kalgoorlie now is warming too much (+1.02C / 100 years more than the neighbours).  Kalgoorlie’s adjustment is too great, affecting all previous years.

I now turn to Alice Springs, which ‘has a notably large “footprint”’.  Too right it does- its impact on the national climate signal is 7% to 10%, according to the 2011 Review Panel, p. 12.

Fig. 9:  Alice Springs differences from neighbours

Alice acorn v neighbours avg

Alice Springs, cooling slightly compared with neighbours, has been adjusted (-0.57C at 1/1/1932) so that the Acorn reconstruction is warming (+0.66C / 100 years) relative to its neighbours.  The adjustment is much too large.

And exactly where are these neighbours?

Tennant Creek (450 km away), Boulia (620 km), Old Halls Creek (880 km), Tibooburra (1030 km), Bourke (1390 km), and Cobar (1460 km)!

The site with the largest impact on Australia’s climate signal has been “homogenised” with neighbours from 450 km to 1460 km away- except the adjustment was too great, resulting in the reconstruction warming too much (+0.66C / 100 years) relative to these neighbours.  The same applies at Kalgoorlie.  Meekatharra’s record only starts in 1927 so its effect can be discounted.  These are the only remote Acorn sites that had large adjustments at this time.  All other remote Acorn sites open at this time either have similar trends in raw and Acorn or had no adjustments in this period.

The 37.3% increase in the trend of Australian maxima anomalies in the “world’s best practice” ACORN-SAT dataset compared with the “raw” AWAP dataset is largely due to just two adjustments- at Kalgoorlie and Alice Springs- and these adjustments are based on comparison with distant neighbours and are demonstrably too great.

If it wasn’t so serious it would be laughable.

Are We Getting More Heatwaves? Part 2

April 22, 2015

It is now over three weeks (15 business days) since I questioned Dr Vertessy on his claims in his ABC Radio interview, but still no reply.

To test Dr Vertessy’s claim that we are seeing “of the order of five times the number of very serious heatwaves” as in the middle of last century, I have continued to use the following metric:

“Three days or more in a row in summer (December- February) where the maximum temperature is in the top 5% of temperatures for that day at that location, with daily benchmarks calculated using daily maxima for each month from 1961 to 1990.”

I have also used as an absolute metric of very hot days the Bureau’s own definition, days above 40 degrees Celsius.  I have used ACORN-SAT maxima to 31 December 2014 downloaded directly from the Bureau’s Acorn site, and daily maxima from 1 January to 28 February this year for each site, downloaded from Climate Data Online.  I have calculated decadal running counts of the number of days meeting the criterion to show how hot weather has changed over time.

In this post I have looked at rural locations to the north and west of Melbourne, including far western New South Wales and northern Victoria.  Where there is a continuous ‘raw’ record, I compared with raw data.

Once again, results are mixed, but I also came up against the major difficulty in analysing Australian temperatures- missing data.

I’ll first show a group of locations that appear to support Dr Vertessy’s claim.- Deniliquin, Nhill, and Kerang.

Fig. 1: Decadal count of heatwave days in Deniliquin

Decadal cnt 95 3d heatwaves summer Deniliquin3

Fig. 2: Decadal count of very hot days in Deniliquin

Decadal cnt 40 Deniliquin

Fig. 3: Decadal count of heatwave days in Nhill

Decadal cnt 95 3d heatwaves summer Nhill

 Fig. 4: Decadal count of very hot days in Nhill

Decadal cnt 40 Nhill

Fig. 5: Decadal count of heatwave days in Kerang

Decadal cnt 95 3d heatwaves summer Kerang

 Fig. 6: Decadal count of very hot days in Kerang

Decadal cnt 40 Kerang

Deniliquin, Nhill, and Kerang all appear to show the present decadal count of both heatwave days in summer and very hot days to be very much greater than- 4 to 5 times greater than- that of the count to the mid 1950s.  But next consider Tibooburra.

Fig. 7: Decadal count of heatwave days in Tibooburra

Decadal cnt 95 3d heatwaves summer Tibooburra

Acorn shows the recent peak, and the number of heatwave days in the decade to 1915 is about the same as the 1920s and 1940s- early 1950s.  The raw record shows the current count is about the same or even less than in the 1950s.

Fig. 8: Decadal count of >40C days in Tibooburra

Decadal cnt 40 Tibooburra

This shows a distinct rise to 2007, with a small decline since, but still above anything previous.  However, consider the following.

Fig. 9:  Decadal percentage of available data at Tibooburra

Decadal percent obs Tibooburra

With up to a third of data missing in Acorn, the heatwave and very hot day counts are too low for more than two decades.   The apparent dip in the decadal counts can be attributed to missing data.

This problem is as bad or worse at Nhill and Kerang.

Fig. 10:  Decadal percentage of available data at Nhill

Decadal percent obs Nhill

Fig. 11:  Decadal percentage of available data at Kerang

Decadal percent obs Kerang

A fair comparison is not possible.  Only Deniliquin can conclusively confirm Dr Vertessy’s claim.

I now turn to Bourke, Cobar, Walgett, Mildura, and Rutherglen.

Fig. 12: Decadal count of heatwave days in Bourke

Decadal cnt 95 3d heatwaves summer Bourke

 Fig. 13: Decadal count of very hot days in Bourke

Decadal cnt 40 Bourke

Bourke has five to ten more heatwave days than in the 1950s, not five times more.  (The peak 10 years ago got to twice as many.)  The effect of adjustments can be clearly seen, but even Acorn shows the number of very hot days (>40C) is less than the 1920s.

Fig. 14: Decadal count of heatwave days in Cobar

Decadal cnt 95 3d heatwaves summer Cobar

Fig. 15: Decadal count of very hot days in Cobar

Decadal cnt 40 Cobar

Cobar has recently had twice as many heatwave days as the 1950s, but less than the early 1930s, and the recent very hot day peak is less than the 1940s.

Fig. 16: Decadal count of heatwave days in Walgett

Decadal cnt 95 3d heatwaves summer Walgett

Fig. 17: Decadal count of very hot days in Walgett

Decadal cnt 40 Walgett

Walgett has many fewer heatwave and very hot days than the 1940s.  To 2015, the decadal count of heatwave days is half that of the mid 1950s.

Fig. 18: Decadal count of heatwave days in Mildura

Decadal cnt 95 3d heatwaves summer Mildura

Fig. 19: Decadal count of very hot days in Mildura

Decadal cnt 40 Mildura

The recent/ current peak in decadal counts of very hot/ heatwave days is about twice that of the mid 1950s, but not markedly higher than the 1940s and late 1960s.

Rutherglen is interesting.  Here is an example of how one extreme season can affect the record, with a large step up in the 1938-39 summer, but Acorn adjustments have increased the decadal count in the 1940s even more.

Fig. 20: Decadal count of heatwave days in Rutherglen

Decadal cnt 95 3d heatwaves summer Rutherglen

Fig. 21: Decadal count of very hot days in Rutherglen

Decadal cnt 40 Rutherglen

Acorn does not always cool the past.  In Rutherglen adjustments have increased the number of very hot days in the record from 1939 to the late 1940s, garbling the climate record.  Unfortunately for the Bureau, this shows heatwave days in the decade to 2015 a bit more than twice the number to 1955, but less than the 1940s.

And who knows how many heatwave days were between 1959 and 1965:

Fig. 22:  Decadal percentage of available data at Rutherglen

Decadal percent obs Rutherglen v raw

Rutherglen has November 1959 to December 1965 missing, which makes comparison with the mid 20th century period somewhat difficult.

Conclusion:

So, are rural sites getting about five times more very serious heatwaves now compared with the middle of last century?  At six of nine rural sites in western NSW and northern Victoria, No.  Only Deniliquin definitely supports Dr Vertessy’s claim.  While some sites (Nhill and Kerang) appear to support the claim, fair comparisons are not possible because up to a third of data is missing from crucial years.  None of the other sites support his claim (although no doubt careful selection of comparison periods will allow global warming enthusiasts to agree with him).  Most show similar or higher frequency of heatwave days than now, before the 1950s.

We are not getting more heatwaves.

Are We Getting More Heatwaves?

April 14, 2015

As it is now two weeks (nine business days) since I questioned Dr Vertessy on his claims in his ABC Radio interview, it appears an answer is still to be given, so I shall post what I have found so far.

Dr Vertessy claimed that we are seeing “of the order of five times the number of very serious heatwaves” as in the middle of last century.  Not knowing Dr Vertessy’s definition of a “very serious heatwave”, I have used the following metric:

“Three days or more in a row in summer (December- February) where the maximum temperature is in the top 5% of temperatures for that day at that location, with daily benchmarks calculated using daily maxima for each month from 1961 to 1990.”

I have also used as an absolute metric of very hot days the Bureau’s own definition, days above 40 degrees Celsius.  I have used ACORN-SAT maxima to 31 December 2014 downloaded directly from the Bureau’s Acorn site, and daily maxima from 1 January to 28 February this year for each site, downloaded from Climate Data Online.

Note that this does not consider other serious factors such as humidity or night time minima.

I have initially looked at all state capitals, and will later look at other locations.

I have calculated decadal running counts of the number of days meeting the criterion to show how hot weather has changed over time.

So what did I find to be the answer to “Are we getting five times more heatwaves than we did 60 years ago”?  Mostly no, but it depends where you look.

Fig. 1: Decadal count of heatwave days in Adelaide

Decadal cnt 95 3d heatwaves summer Adelaide

Yes, but the peak may be past.

Fig. 2: Decadal count of >40C days in Adelaide

Decadal cnt 40 Adelaide

This shows a distinct recent rise.

Fig. 3: Decadal count of heatwave days in Brisbane

Decadal cnt 95 3d heatwaves summer Brisbane

A peak 10 years ago, dropping to zero heatwaves in the decade to 2015.

Fig. 4: Decadal count of >40C days in Brisbane

Decadal cnt 40 Brisbane

One day, 22 February 2004.

Fig. 5: Decadal count of heatwave days in Darwin

Decadal cnt 95 3d heatwaves Darwin

As Darwin doesn’t have “summers”, the count was of all days.  Note the 1930s and 1970s.  Darwin is not seeing more heatwaves.  Darwin has never had a day over 40C.

Fig. 6: Decadal count of heatwave days in Hobart

Decadal cnt 95 3d heatwaves summer Hobart

Hobart has had no heatwave days in the past decade, compared with five in the 1950s.

Fig. 7: Decadal count of >40C days in Hobart

Decadal cnt 40 Hobart

Hobart has fewer extremely hot days than in the past.

Fig. 8: Decadal count of heatwave days in Melbourne

Decadal cnt 95 3d heatwaves summer Melbourne

Melbourne has fewer heatwave days than the middle of last century.

Fig. 9: Decadal count of >40C days in Melbourne

Decadal cnt 40 Melbourne

Melbourne has more very hot days than it did in the 1950s, but less than the 1940s.

Fig. 10: Decadal count of heatwave days in Perth

Decadal cnt 95 3d heatwaves summer Perth

Perth has had 10 heatwave days in the past decade.  In the decade to 1955 it had 6- but in the 1960s it had three times the current number.

Fig. 11: Decadal count of >40C days in Perth

Decadal cnt 40 Perth

The recent peak was one more than in the 1960s.  The warming since the 1970s is clearly visible.

Fig. 12: Decadal count of heatwave days in Sydney

Decadal cnt 95 3d heatwaves summer Sydney

Four days in the last 10 years, compared with zero in the 1940s and 1950s- but less than the 1960s.

Fig. 13: Decadal count of >40C days in Sydney

Decadal cnt 40 Sydney

The current peak of seven days in the past 10 years of very hot days is about the same as the 1940s and 1960s, but much less than the 1980s.

Technically, Dr Vertessy is correct in his claim of “of the order of five (four to six?) times the number of very serious heatwaves” as in the middle of last century, at Adelaide, Darwin, and Sydney, but not at Brisbane, Melbourne, Hobart, or Perth.  However, Sydney had far more in the 1960s, and Darwin had as many in the 1970s and far more in the 1930s.  Adelaide alone shows a clear picture of many more heatwave days in the past 10 years.

In several of the records it is possible to see cycles of 15 – 20 years duration.  While there is an argument that heatwaves and extremely hot days are weather events, not climatic, resulting from blocking highs or the lateness of sea breezes, these apparent cycles indicate a climatic influence.  What would cause blocking highs to be more persistent, or sea breezes to be consistently later, for 10 years or more?  Atmospheric circulation patterns, including the location of the sub-tropical ridge, would appear to be the major influence.

The longer term analysis from 1910 shows a more complete picture than since the 1950s.  Wouldn’t it be good to use “carefully curated” Acorn maxima from before 1910.

In a future post I will look at other locations, as a continent’s climate extremes can’t be usefully analysed with only seven sites.  As well, this analysis has used ACORN-SAT data only.   What will the raw data show?  Therefore I will also compare results for Acorn and raw.   Bourke might prove interesting.

Meanwhile, I am waiting patiently for Dr Vertessy’s response.  Apart from Adelaide, the state capitals certainly don’t support his claim.

The Bureau Boss on Temperature Trends, Heatwaves, and Climate Change

March 31, 2015

On Sunday profile on ABC Radio on Sunday 29 March, the Director and CEO of the Bureau of Meteorology was interviewed.  The whole interview is here:

http://www.abc.net.au/radio/programitem/peyl3MNdrQ?play=true

For a scientist who claims to be only interested in science and not in advocacy, he certainly sounds like a fervent Global Warming Enthusiast.

Here is the feedback I sent to the Bureau.

“[THESE QUESTIONS ARE DIRECTED TO DR. BOB VERTESSY, WHO WAS INTERVIEWED ON ABC RADIO ON SUNDAY]

Dear Dr Vertessy

I was interested to listen to your interview on Sunday Profile on ABC Radio yesterday, 29 March 2015. I was particularly interested in your comments regarding public criticism of the Bureau’s adjustments to temperature data, and on the increasing frequency in heatwaves.

Several times you stated that the adjustments “make no difference at all” to temperature trends, that the raw temperature data “tell exactly the same story”, and that we see “the same result (in temperature trends) for the whole continent” as for raw data.

You also stated that heatwaves are becoming “one of our most serious natural disasters”.  They are “a bit of a silent killer- it’s the number one cause of death.”  You also said, “We are probably seeing of the order of five times as many very serious heatwaves today as we did in the middle of last century.”

I have some questions.

Q.1: Can you please supply me with a reference to your data that show that the number one cause of death is heatwave?  I was sure it was cardio-pulmonary disease usually associated with very cold weather, with mortality rates much higher in winter than summer.  Perhaps you meant heatwaves are the number one cause of death when compared with other natural disasters, which is debatable.  This was not at all clear and must surely have misled some listeners.

Q.2:  Can you please supply me with a reference to your data that show five times as many very serious heatwaves today compared with the middle of last century?  Could you also please tell me your criteria for a very serious heatwave.

For the next question I refer you to Table 1 on page 14 of On the sensitivity of Australian temperature trends and variability to analysis methods and observation networks  (CAWCR Technical Report No. 050), R.J.B. Fawcett, B.C. Trewin, K. Braganza, R.J Smalley, B. Jovanovic and D.A. Jones , March 2012 (hereafter CTR-050).  This shows that quadratic change in mean annual temperatures from 1911 to 2010 in adjusted data of the ACORN-SAT network (+0.94C) is 36% greater than in the ‘unadjusted’ data of the AWAP network (+0.69C). For maxima, the change is 38.9%, and for minima is 34.1%.  In this paper the authors claim that the rise in unadjusted data is “somewhat smaller” than in ACORN-SAT.

Q.3:  In what way can 38.9%, 36%, or 34.1% difference in quadratic change be interpreted as “no difference”, “exactly the same story”, or “the same result”? 

Perhaps you should have told your listeners that the similarity was only since 1955, and that before this, raw data show temperatures (especially maxima) were cooling, but then 60 years is not such a long climate record for making trend analyses, and this may be confusing to those who cannot understand more than a simple climate narrative.

In the Concluding Remarks of CTR-050, p.50, the authors state that “further work will be undertaken to characterise in more detail these changes, particularly at the monthly and seasonal level”.

Q.4:  When can we expect to see the results of this further work published on the ACORN-SAT website?  If it is available elsewhere please refer me to it.  I am particularly interested in any difference in quadratic change in summer maxima between AWAP and ACORN-SAT, as this is relevant to heatwave analysis.

I look forward to your reply.”

For an explanation for my interest in comparison with AWAP data, see my analysis of monthly and seasonal differences in trends between AWAP and Acorn from October last year.  My calculations indicate a 200% increase in trend in summer maxima.

One might think that if Australia wide there has been a five-fold increase in the number of very serious heatwaves, there should also be some discernible increase in the number of very hot days.

To illustrate my incredulity about this claim, here is the timeseries graph of very hot days (BOM definition: >40 degrees Celsius) straight from the Bureau’s website:

 Hot days graph BOM

The linear trend (for what it’s worth) shows an increase of 0.02 days per decade.  That’s 0.2 of a day per hundred years, or 2 days in 1,000 years.  Scarey hey.

I will be following up on the hot days and heatwaves analysis in coming posts.