CRUTEM vs ACORN: Tasmania

Australia has done it again- we have beaten the Poms at their own game (and I don’t mean cricket).

The English climate scientists say the temperature trend for the island state of Tasmania is +0.48C per 100 years.

We’ve beaten that: we say it’s +0.81C per 100 years- better by 69%!

Today I looked at data now available as an interface with Google Earth.

I quote firstly directly from WattsUpWithThat:

Climate researchers at the University of East Anglia have made the world’s temperature records available via Google Earth.

The Climatic Research Unit Temperature Version 4 (CRUTEM4) land-surface air temperature dataset is one of the most widely used records of the climate system.

The new Google Earth format allows users to scroll around the world, zoom in on 6,000 weather stations, and view monthly, seasonal and annual temperature data more easily than ever before.

Users can drill down to see some 20,000 graphs – some of which show temperature records dating back to 1850.

This new initiative is described in a new research paper published on February 4 in the journal Earth System Science Data (Osborn T.J. and Jones P.D., 2014: The CRUTEM4 land-surface air temperature dataset: construction, previous versions and dissemination via Google Earth).

For instructions about accessing and using the CRUTEM Google Earth interface (and to find out more about the project) visit http://www.cru.uea.ac.uk/cru/data/crutem/ge/. To view the new Google Earth interface download Google Earth, then click here CRUTEM4-2013-03_gridboxes.kml.

I immediately downloaded the new interface, and can report that it is indeed useful and fascinating.  Click anywhere and you can get mean temperature data and trend for that precise region, and individual weather stations as well.  It allows easy comparison between the temperature record as shown by the Bureau of Meteorology (BOM) and one of the world’s leading datasets produced by the renowned Climatic Research Unit in England.

Three things to note:

1.  CRUTEM4 uses data from back to the 1850s- BOM says it only uses data from 1910 as data previous to this may be unreliable.

2.  CRUTEM4 uses data from many more than the 104 ACORN sites used by BOM.  Some may be of doubtful quality.

3.  The results are vastly different.

I have downloaded data from CRUTEM4 and from BOM for Tasmania, as that appears to be the easiest region to compare records.  As you can see from the Google Earth image below, Tasmania fits fairly neatly into one 5 degree by 5 degree grid cell.

google earth tassie

First I show the annual data for both datasets:Tassie means

Note CRUTEM4 has annual data from 1883.  BOM has this as well but declares it to be unreliable.  Note also that the trends are vastly different- CRUTEM4 trend is +0.48C per 100 years, while BOM has it as +0.81C.  (+0.8C on their Time Series graph.)

(The difference is +0.33c- that’s an improvement of 69%! And they did it with only 5 sites, vs CRUTEM4’s 21.)

How was this done?  Apart from not including pre-1910 data, BOM also made some small adjustments to the raw data:bom-crutem

And that comparison is not with raw data, but with CRUTEM4.

So, what is the correct temperature trend for Tasmania?  The world acclaimed CRUTEM 4, or “world’s best practice” ACORN-SAT? Or neither?

It’s anyone’s guess.

References:

Jones P.D., Lister D.H., Osborn T.J., Harpham C., Salmon M. and Morice C.P., 2012: Hemispheric and large-scale land surface air temperature variations: an extensive revision and an update to 2010. Journal of Geophysical Research 117, D05127. doi: 10.1029/2011JD017139.

Osborn T.J. and Jones P.D., 2013: The CRUTEM4 land-surface air temperature dataset: construction, previous versions and dissemination via Google Earth. Earth System Science Data Discussion 6, 597-619. doi: 10.5194/essdd-6-597-2013

http://www.bom.gov.au/web01/ncc/www/cli_chg/timeseries/tmean/0112/tas/latest.txt

http://www.bom.gov.au/climate/change/acorn-sat/

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10 Responses to “CRUTEM vs ACORN: Tasmania”

  1. blackduck19 Says:

    The BOM should take a bow. Anyone who can so thoroughly trounce Phil Jones at his own game is truly gifted. I am pleased to see he has resurfaced as well after his Copenhagen disappearance
    .

  2. cementafriend Says:

    I think ACORN relies mainly on airport temperatures. These give ground levels temperatures which maybe useful for aircraft. The siting of airports does not correspond to average terrain. Tasmania is quite mountainous. While I do not trust CRUTEM in this case I would think 21 stations scattered around Tasmania would give a better answer than 5 stations mainly located at airports near large population centres (at least Hobart, Launceston and probably Wynyard & Devonport- where the ferries come in)
    The old Hydro Tasmania would have been collecting weather data from around 1914 at some of the dam sites which can be cold miserable places particularly in winter- I am pretty sure i saw weather stations at Strathgordon and Tarraleah administration centres.

  3. Berynn Schwerdt Says:

    The CRUTEM and BOM anomalies are very similar. Is the difference really grounds for concern?

    BOM – CRUTEM = 0.01C/decade trend difference.

    That’s less than the largest difference betwen satellite and surface trends (0.03C/dec), and well within uncertainy envelopes. Expanding the y-axis by a factor of 4 to show the differences is not as enlightening as it would have been had you kept the y-axis constant for both graphs.

    I believe if you plotted anomalies and trends for both data sets for the same time period (apples to apples), and maintained the original scaling of the y axis, you’d see very little difference.

    Just to clarify, is BOM – CRUTEM from the exact same time period? Seems to be the case, but just checking.

    I think if there’s any issue here, it is BOM’s choice to reject data pre-1910. I picked through pre-1910 data from BOM weather stations recently. The excursions for the late 19th century/early 20th are often highly abnormal, in both directions. No wonder BOM considers them unreliable for a national/state estimate, and with sparseness a significant factor. And while the Met Office time series go back to 1850, the error bars get get wider. Most centennial estimates from IPCC and others start at 1900.

    • kenskingdom Says:

      Naturally they are similar- as you would expect from using similar data. Your 4th para.- my first plot is exactly what you describe, anomalies and trends for both datasets for the same time period, same y axis. Just that Acorn doesn’t use pre-1910. Big difference as a result. BOM – CRUTEM is for exactly the same time period.
      So you are saying that the Crutem data is unreliable for Australia (specifically Tasmania)? Best take it up with the authors. You agree with me 50%- but I say Acorn is unreliable too.

    • cementafriend Says:

      Berynn, you seem to be an apologist for BOM. Just had a look that the CRUTEM with Google earth. All except three stations of the 21 Tasmanian are located on or near the cost leaving most of the Tasmanian land area (which is mountainous) with no data. I also tried to look at some of the BOM stations, I was right about Strathgordon which still exists and Tarraleah (which seems to have been closed this year or last year) In fact searching for Queenstown shows that just about all the stations in the central and western area of Tasmania have been closed.
      I then had a look at Brisbane and the Sunshine Coast. A lots of airports there (CRUTEM has three readings from Amberely airport and two from Brisbane airport plus Gold Coast but strangely no Maroochydore/Sunshine Coast airport). I would say both CRUTEM and BOM are a waste of time and money.

  4. Berynn Schwerdt Says:

    Hmm, now I’m unclear about the trend plots.

    my first plot is exactly what you describe, anomalies and trends for both datasets for the same time period, same y axis. Just that Acorn doesn’t use pre-1910. Big difference as a result.

    You used the same time period (1910+ only) to derive both trends, or did you use the extended data for CRUTEM?

    (Bolding to show what confused me)

  5. Berynn Schwerdt Says:

    So you are saying that the Crutem data is unreliable for Australia (specifically Tasmania)?

    It’s not black and white.

    BOM dataset is smaller, and the pre-1910 data is obviously unreliable. I don’t know if CRUTEM’s larger data set is more useful, but I do know that they apply wide error bars, and point out that the data is less reliable the further back you go in time. They also point out that uncertainty errors for land temps are much greater than sea surface, owing to greater variability, and this is especially true for regional and sub-regional historical temps.

    19th century sub-regional land temperature data is not nearly as well constrained as 20th century, which is probably why Met Office only do linear trend analyses from 1900 even on a global scale. So yes, I would be cautious about attaching much significance to trends using 19th century data, especially sub-regional.

    If you didn’t match time periods for the trend analysis, what is the result if you do?

    • kenskingdom Says:

      For the period 1910- 2012 the Acorn trend is +0.12C / 100 years above Crutem, due to additional adjustments having a small effect. Before 1925 both data sets rely on very few sites so the record is not very reliable. My point which you may have missed: both datasets are questionable, and the longer Crutem record shows much less warming.

    • Berynn Schwerdt Says:

      Yes, eyeballing the second graph I guessed the difference was about 0.01C/dec. This is similar to the difference between all the data sets on global scale. In fact, I’m surprised that the agreement is so good for a very localised set. The difference between GISS and RSS, for example, is 0.03C/decade globally.

      The trend differences in the full records, then, is mainly a result of the added data, and not a reflection of quality of data. You can’t compare data sets for quality when using different time periods, they should be the same. Getting markedly different trend results by doing so is no suprise.

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