Introduction

In March 2011 I analysed trends in Australian Maximum Temperatures from 1910-2010, and now I am following up with Minima.  Since that time I have looked at adjustments made by the Bureau of Meteorology (BOM) and in a paper co-written by Dr David Stockwell proposed an alternative network of climate sites we call the Minimally Adjusted Network (MAN).  This network comprises sites included in BOM’s High Quality (HQ) network but makes adjustments by comparison of overlapping raw data only.

I have further revised this network by removing all sites where there is less than two years of overlapping data, where there is less than 80 years of data, where the record shows spurious data, or where metadata supplied by BOM indicates serious problems.  I have deliberately included all urban sites including all capital cities except Darwin, usually at a nearby airport.  The MAN dataset for Minima now comprises 89 sites.

I shall explain with one example what “Minimally Adjusted” means.  Here is a graph showing the raw data available for sites near Cairns in North Queensland:

There is good overlap of 10 years from 1943 to 1952.  The graph shows Cairns Airport minima are warmer than the Post Office, and in fact the mean difference is 0.29 degrees.  Therefore the Post Office raw data may be adjusted up +0.29 degrees so that the two series are comparable, to give this graph of the spliced data:

No assumptions are made about the data, and no subjective decisions are made about whether to adjust and by how much, unlike the adjustments used in BOM’s HQ datasets.  No other adjustments are made.  If a site meets the criteria but the metadata indicates serious problems (e.g. Nhill) or the data appears to be spurious (e.g. Halls Creek), it is excluded.  As more metadata becomes available it may be that further sites will be excluded.

To compare temperature across Australia I convert all data to anomalies from the 1961 to 1990 mean for each site.  I then calculate the mean anomaly for each year for a selection of sites.  While I show data from 1910 to 2011, much 2011 data has still not been “quality assured”, so many annual means were not available.  For these sites I found the annual mean from the daily means, which is not the correct method, but is close.

 Caveat:  There is considerable uncertainty in all temperature data.  BOM says that Automatic Weather Station (AWS) data has an accuracy of +/- 0.3C.  Celsius thermometers (mercury in glass) have an accuracy of at best +/- 0.5C.  Fahrenheit thermometers, certainly no more accurate, were used before September 1972 and temperatures recorded before then were converted to Celsius for modern comparison.    The records show that in the Fahrenheit era, many observers used whole degrees even though BOM’s instructions to observers were to record temperature in tenths of a degree.  That’s hard enough on a Celsius max/min thermometer.  A number of quite recent observations appear to be recorded in whole degrees. The change to Celsius in 1972 may have led to an artificial warming relative to pre 1972.  Certainly the Australian temperature record must be treated with great caution.  Therefore my figures are subject to the same uncertainty.

Results

Here is the graph of Minima for all 89 MAN sites:

While Australian temperatures have been rising, it has been by no means a steady increase.  There was an enormous jump up in the 1970s.  The 4^th order polynomial trend line shows the distinct fall and rise.  Are we following a natural cycle?  The next few years will be decisive.

What’s with WA?

Here’s Western Australia;

And here’s the rest of the continent:

Wildly different!  It’s worth putting both together to show the difference more clearly.

WA is clearly a different climate zone.

City vs Country

Not such a great difference.  Urban sites are warming slightly faster- UHI?- cooler up to 1950s, and in the 1990s, and are a little more variable, which is surprising.

Beach or Bush

Sites within 100km of the coast have much less variability than inland sites, due to the oceanic influence.  Inland sites have greater extremes, but the overall trends are very similar, except that coastal sites are getting warmer, whereas inland sites’ extreme peaks have been decreasing since 1973.  The extremes are at identical times, but the standout differences are 1973, 1976, and of course 2011.  Note the late 1970s step up is very clear.

North and South

The boundary line is the South Australia/ Northern Territory border.  First southern Australia:

Northern Australia:

Wildly different!  Note the warmest year by far was 1998, and 2011 was colder than any year since the 1970s.  Now let’s combine:

Note that northern minima- further from the South Pole- are warming faster than the southern.  The north has much greater extremes and appears to have peaked.

Maxima and Minima

I have plotted Maxima and Minima only to 2010.

While the linear trend for Minima is greater than for Maxima, and after initially decreasing, Minima anomalies have been rising since the 1940s, in the past decade (“the hottest on record”), minima have flattened.  The record means have been caused by much higher maxima.  This is especially visible in a plot of the annual Max-Min range, which shows the linear trend steadily decreasing as is expected with the Greenhouse Effect.  However, the range has increased steeply since the 1980s which is not what is expected.  This is not the signature of Anthropogenic Global Warming, at least in Australia.

Conclusion:

The Minimally Adjusted Network provides an alternative network of 89 long term sites with few adjustments to the raw data.  Uncertainties in the data accuracy of at least +/- 0.3C mean that the temperature record must be viewed cautiously.

There is little difference between Urban and Non-Urban minima.

Western Australia has a completely different climate to the rest of Australia.

Coastal and Inland trends are not greatly different, except for variability, until 2011.

Much can be learned from looking at Means, but an analysis of Minima yields further interesting information.  Remember: Anthropogenic Global Warming due largely to the greenhouse effect should be visible in Minima.  Temperature increase should be greater at night, in winter, and towards the poles.  It is plain, however, that in Australia this is not the case.

Since the 1940s, very cold years have been getting progressively milder, but since 1973 very mild years have been getting progressively cooler.  Further, the increase in minima is more pronounced in northern Australia than in the south- and while southern Australian minima have been steadily increasing, northern minima have a much greater variation and appear to be now decreasing.   The Range bewteen Maxima and Minima does not show the greenhouse Effect signal.   My guess is that El Nino/ La Nina conditions have a very large influence on northern Australian (largely Queensland) minima and consequently Australian minima.

The huge variations we see from the 1970s to about 2000 have decreased.  The huge step up of the 1970s (The Great Climate Shift) is clearly visible in the minima, but the next few years will show if it has run its course.  I expect it has.

And finally, 2011 was not particularly unusual- except in inland and northern Australia where it was the coldest since 1994.

Appendix:  Minimally Adjusted Network

The December UAH value is +0.13  making the running 12 month mean +0.15 +/- 0.1.  December SOI reached 23.

All through 2011 I watched my predictions get further and further away from the actual 12 month mean of UAH temperatures.  I decided to change two factors in my algorithm with startling results- the calculated 12 month mean temperatures are closer- much closer- at least for the last two years.   Here are my old figures and new calculations compared:

So we’ll see how we go this year!

Last month I tipped “the next major enhancement to weather with heavier rainfall should be in the last week of December to mid January”.   Two cyclones appeared and caused major flooding in the Northern Territory, plus a Christmas Day storm in Melbourne (probably not connected!) and heavy storms about the Queensland Central Coast, so a little earlier than I expected but not much.

Although there are extremes about right now (12 January) I expect the next major build up of heavy rain and possibly cyclones off the east coast around 22 January to mid February.  This is the usual time for the arrival of the Wet season in this part of Queensland- when school starts.

So here’s my plot of what global temperatures could be like over the next 11 years, excluding major volcanic eruptions or other unforseen factors.  These represent my long range predictions for 12 month running mean global tropospheric temperatures as recorded by UAH.  This is based on my analysis of the UAH record compared with the 120 month running mean of the Southern Oscillation Index with a lag of 11 years and the 12 month running mean of the SOI with a lag of 6 months.

The upper and lower limits are for the maximum and minimum historical values for the 12 month mean SOI (+23 and -23).   If the global 12 month means exceed either of the black lines for more than 2 years I would consider this prediction falsified.

I calculate as follows:

T(12)m,y = [(SOI(12) m-6, y) /9 + (SOI(120) m, y-11)] /12 + FF

where

T = 12 month running mean up to month m of year y of global atmospheric temperature anomalies in degrees Celsius

SOI = running mean of inverted SOI values for (12) or (120) months

FF = fine-tuning factor, which for long term purposes can be assumed to be +/- 0.1.

(FF is some factor I am unable to identify but may be related to PDO, aerosol concentrations, or maybe even CO2!)

Here is a plot of the calculated means vs actual UAH 12 month means since 1979.

Note there is great variability.  Far from falsifying my hypothesis, I consider that this clearly shows the effect of volcanic eruptions.  The correlation between my calculated and actual values for 12 month mean UAH from January 1998 (the year of the big El Nino) to December 2011 is 0.7348, and from 1979-2011 is 0.6898.

I also include graphs showing the contribution of various factors.

12 month running mean of SOI values is obviously related to UAH, but other factors are involved.

Running 120 month mean of SOI since 1876- note the big jump since 1976.  What if we advanced it by 11 years and combined it with the 12 month mean.

Here’s the calculated values 1979-2011.

I expect that I will need to rework my calculations in the light of future data.  In particular, I’m sure that the long term values have varying influence  which is why there is variation.  These are still early days.

Here’s an excerpt:

The concert hall at the Syndey Opera House holds 2,700 people. This blog was viewed about 12,000 times in 2011. If it were a concert at Sydney Opera House, it would take about 4 sold-out performances for that many people to see it.

Click here to see the complete report.

The November UAH value is +0.12  making the running 12 month mean +0.16 +/- 0.1.  November SOI is 13.8 and rising.

Last month I tipped an early start to the Wet, with a monsoon trough (and possibly a tropical low) appearing on Australian weather maps by mid November (35-49 days from the beginning of October).  I predicted the next significant weather system to affect eastern Australia from mid to late November.  These arrived as expected, with heavy rain and flooding in SE Queensland and Northern NSW:

Wet season storms and rain will continue, but the next major enhancement to weather with heavier rainfall should be in the last week of December to mid January.

From the end of 2011 on I will concentrate on long term estimates.

For what it’s worth, here’s my long range predictions for 12 month running mean global tropospheric temperatures over the next 10 years, excluding major volcanic eruptions or other unforseen factors, as recorded by UAH.  This is based on my analysis of the UAH record compared with the 120 month running mean of the Southern Oscillation Index with a lag of 11 years and the 12 month running mean of the SOI with a lag of 6 months.

The upper and lower limits are for the maximum and minimum historical values for the 12 month mean SOI (+23 and -23).   If the global 12 month means exceed the black line for more than 2 years I would consider this prediction falsified.

Background

Sea level rise is in the news again, with Nils-Axel Morner’s article in the Spectator and news in the Daily Telegraph that papers arguing against official claims of sea level rise have been stopped from being published.

It’s two years since the release of  the CSIRO and Climate Change Department’s  publication, Climate Change Risks to Australia’s Coast, (Dept of Climate Change and Energy Efficiency ,2009) which  predicted sea level rise of up to 1.1 metres above 1990 levels by 2100.  Scary stuff. This led to many local governments and State governments suggesting restrictions on coastal developments.

Since then we’ve had Climategate 1 and 2, some leadership changes, an election, floods and cyclones, and two cool years.  We’ve also seen the Climate Commissioners broadcasting their doom and gloom, in their May report and their recent Climate Change and Health report.  I’ll let others demolish the nonsense in this most recent one.  Instead I’ll investigate the honesty and reliability of the Climate Commission, the CSIRO, and the Department of Climate Change, in their continued predictions of dangerous sea level rise.

In Chapter 2 of their May report, the Climate Commissioners state:

A plausible estimate of the amount of sea-level rise by 2100 compared to 2000 is 0.5 to 1.0 m. There is significant uncertainty around this estimate, the largest of which is related to the dynamics of large polar ice sheets

 And show this diagram:

This is in line with Climate Change Risks to Australia’s Coast.   The  authors of both reports base the prediction of 1.0m this century  largely on IPCC AR4, 2007, and  claim this is supported by high-quality satellite observations which showed a rate of 3.1 mm per year between 1993 and 2003, and National Tidal Centre gauges at 14 locations around Australia which showed a mean rise similar to the global mean between the early 1990s and 2008.

0.5m per century is 5mm per year.  1m per century is 10mm per year.  Therefore I will look at evidence for this claim from existing Australian data.

 The claim of accelerated sea level rise from the early 1990s to 2008 should be examined in historical context.  Here’s what Climate Change Risks to Australia’s Coast says: 

For the past 6,000 to 7,000 years, the sea level has oscillated within a narrow band of plus or minus 2 metres. This period of relative stability is sometimes referred to as the ‘stillstand’ period (Box 1.1). The coast that we recognise today stabilised in this period.2

…Global mean sea level has risen about 20 centimetres since pre-industrial times (Figure 2.6), at an average rate of 1.7 millimetres per year during the 20th century.16…

 (Sea level has risen) 1.8 millimetres per year from 1961 to 2003.

 And satellites show a rise of 3.1mm/year from 1993-2003, which agrees with NTC data. So where do they get claims for acceleration?   

 These rates of increase are an order of magnitude greater than the average rate of sea-level rise over the previous several thousand years. …   implying acceleration, for 2 metres in 6000 years is 0.3mm per year.  However, sea level oscillated in a +/- 2 metre band- so the time frame for each rise or fall in this period was much shorter- if it rose or fell 2m in 2000 years, that would be 1mm per year.  Is there evidence for this?  Well, there is for sea level fall.  From an article in the Journal of Coastal Research, here’s a diagram from a study of sand ridges at Beachmere on Moreton Bay in SE Queeensland.

Note on Ridge 7, pebbly sand couldn’t be wind blown, and sits above B Horizon, and B Horizon is at about 1.7m above current mean sea level.  Ridge 7 is 1700 +/- 130 years old.  1700mm in 1700 years is 1mm per year.  Ridge 6 is 1140+/- 80 years old, and B Horizon is about 1.5m above current MSL, so fall was rapid until 600 yrs ago.

Again from  Climate Change Risks to Australia’s Coast

Sea level around Australia rose by about 17 centimetres between 1842 and 2002 – a rise in relative sea level of about 1.2 millimetres per year.17 The rise in sea level has been very variable from decade to decade. The rate of increase was low between the 1970s and early 1990s due to more frequent and severe El Niño events.18

 The authors then explain how CSIRO has developed three simple scenarios for sea-level rise (relative to 1990), based on AR4.

Scenario 3 (High end) considers the possible high-end risk identified in AR4 and includes some new evidence on icesheet dynamics published since 2006 and after AR4.

http://www.climatechange.gov.au/publications/coastline/~/media/publications/coastline/2-chapter.pdf

The National Tidal Centre’s sites are at Cape Ferguson, Rosslyn Bay, Port Kembla, Burnie, Spring Bay, Portland, Port Stanvac, Thevenard, Esperance, Hillarys, Broome, Darwin, Milner Bay and Cocos (not used in this analysis).  These were set up in the early 1990s as part of an international effort to accurately measure sea level rise.  This is how Climate Change Risks shows the data:

The 2009-10 Annual Report of the National Tidal Centre says:

 Although the length of record from Baseline stations is relatively short in climate terms there are a number of clear results emerging. The sea level records for all stations, when corrected for local land movement and changes in atmospheric pressure, demonstrate a regional pattern of sea level trends that is consistent with sea level changes detected by satellite-based altimeters.

While the BOM in its annual report 2009-2010 on the National Tidal Centres admits that the record is not long enough to derive any trends, it seems it was quite long enough for the CSIRO and the Climate Change Department. 

So what is most likely for the next 89 years?  3.1mm/year, 5mm/year, or 10mm/year?  Let’s look at the data from a selection of the NTC sites, and compare with nearby tidal gauges.  Note that the Bureau of Meteorology has longer term records from a number of these sites, using earlier equipment, and one hopes the new gauges were calibrated with these records.

Discussion:

I downloaded sealevel data from BOM’s website for NTC sites and for selected nearby sites to get a longer record for comparison.  This Table shows NTC sea level data with comparisons:

The grey highlighted lines are for non-NTC sites used for comparison.  Column H shows the figures given by Climate Change Risks, which says only that the data is from “the early 1990s” to 2008, so cannot be replicated.  Column D shows long term trend, column G shows the short term trend, column K is data for stations with more than 20 years data, and Column L is for those with more than 40 years data.  Longer term sites show a lower trend.

All except two of the sites (Cape Ferguson and Milner Bay) have short term trends that are greater than their own long term trends or that of nearby sites.  Sometimes they are only a little greater but mostly several times greater. Is this acceleration or natural variability?

Some sample plots:

Cape Ferguson

To avoid the large early gap, here’s the plot from 1984

3.07mm/yr?  and finally 1991

3mm/yr

 Townsville from 1959

1.35mm/yr ; and from 1991

3.4mm/yr.

Esperance from 1965

0.9mm/yr

and Esperance from 1991

4.5mm/yr

Hillarys

 7.9mm/yr.

and Fremantle- from 1897!

1.6mm/yr.  Fremantle from 1991:

5mm/yr!

Port Kembla from 1983 (earlier data spurious with gaps):

0.19mm/yr!!  and from 1991

 2.6mm/yr.  Not too far away Sydney- NOAA has data from 1885

but NTC only from 1914

0.89mm/yr but from 1991

2mm/yr

Differences may be due to uneven rise or fall of land and corrections for this.

Here’s a spaghetti plot of anomalies from 1991-2010 for all 19 records.

Apart from Milner Bay (at Groote Eylandt, in the Gulf of Carpentaria),which has a much greater variability, there is little inconsistency. Broome, Hobart and Darwin have some up and down spikes, and Burnie has a period in the 1950s that may be spurious.  However, in general they are remarkably consistent- so much so that I am confident in calculating mean and median series.

1.4mm/year.  The 6 year running mean clearly shows the interdecadal variability.  There was a steady rise from 1920 to the late 1950s, particularly from the mid 1940s, followed by a flat/declining trend to the late 1980s.  Note also the step ups every 20-30 years.

It is important to remember however that the early data is based on few stations:

Therefore, while we can say quite confidently that for most of the  20^th Century sea level rise could not have been above 1.7mm/year, as stated in Climate Change Risks to Australia’s Coast, we cannot rely on data from only one or two stations.  I have therefore plotted graphs of the mean from 1959 (when 4 sites became available) and 1966 (10 sites), to show trends over 52 and 45 years respectively.

1.15 or 1.2mm/year?

Compare this with the 1991-2010 graph for all 19 sites:

3.8mm/year

But what happens if we start from a different year?  Try 1988:

2.3mm/yr

Alright, that’s cherry picking, I started from a high point.  Try 1987 instead:

2.63mm/yr – which is still a far cry from 3.8mm/year!

A lot depends on the start year!  For another example, here’s another 20 year period of rapid sea level rise: 1938-1957

4.5mm per year!   That’s much more than 1991-2010.

Another thing to remember is that the mean tells you nothing about local conditions, and sea level is all about local conditions.   High tide is far more significant.

Let’s compare this with Ocean Heat Content (OHC):

 Note the rises in 2003-04 and 2007-08- matches the mean graph, but not trending up.

And finally, the 1966-2010 graph of MSL and scaled SOI (monthly values/ 100).

The relationship is pretty obvious.

Conclusions:

Sea level has been rising gradually since records began.

Interdecadal variability is highly visible.  SOI is a major influence on sea level.

The rapid rise of the late 1990s is not unusual- it was more rapid 1938-1957.  Any projections based on this short period are therefore spurious. There is no recent acceleration.

The longer the record, the lower the trend.

3.1mm/year rise has been achieved- in the 20 years since 1991.  5mm/year was almost reached 1938-57, but is almost double the trend since 1987.

10mm per year is more than 2.6 times the trend since 1991, and 8 times the trend of the last 50 years!  That’s a lot of glaciers and ice sheets to melt, and a lot of ocean heat content!

There is nothing to indicate that the long term average sea level rise of 1.2 – 1.7mm per year (with periodic increase and decrease with the SOI) should not continue for the foreseeable future.  Anything more is speculation.  As BOM says in its NTC Report:

Sea level and climate can fluctuate about a long-term climatological mean from one decade to the next. The project to date is only just beginning to span two complete decades, so it is important to recognise that the sea level change observed over this time is largely a measure of decadal variability. Continued monitoring is needed to quantify the longer-term trend that is associated with climate change.

We hope that Dr Jones and his team don’t hear about this- they’ll correct, adjust, and homogenise for sure!

http://www.spectator.co.uk/essays/7438683/rising-credulity.thtml

http://www.dailytelegraph.com.au/news/sydney-nsw/climate-change-science-being-stifled-by-nsw-labor-bureaucrats/story-e6freuzi-1226211748047

http://www.bioone.org/doi/abs/10.2112/04-0375.1

http://www.climatechange.gov.au/en/publications/coastline/climate-change-risks-to-australias-coasts.aspx

The October UAH value is +0.11  making the running 12 month mean +0.17 +/- 0.1.  The sharp drop arrived as expected.  October SOI is 7.3.

When I first started posting this series, I hoped to be able to estimate temperatures 7 months in advance.  That
appears to be falsified as the temperature lag seems to be much less this year.  (The lag should be between 5 and 9 months,
typically 7, but I have been using 6 months for some time.  The climate oscillations appear to vary in frequency as well as amplitude, if you like.)
So from the end of 2011 on I will concentrate on long term estimates.

I’m tipping an early start to the Wet, with a monsoon trough (and possibly a tropical low) appearing on Australian weather maps by mid November (35-49 days from the beginning of October).  The next significant weather system to affect eastern Australia I expect from mid to late November.  This is due to upper level disturbances generated apparently by the Madden-Julian Oscillation in the Indian Ocean.

First, some background:

In March last year I began comparing adjusted temperature data from Australia’s 134 “High Quality” sites with the raw figures.  I published my analysis of the results for Non-urban and Urban sites in July and August 2010 (with an update in March this year)  .  I repeatedly requested information from the Bureau of Meteorology on the reasons for the discrepancy between raw and adjusted data, and the apparent warming bias Australia wide, with no success.

After nothing in reply but an anonymous  “go away and write a scientific paper” email, I wrote to Minister Tony Burke on 26 October with a formal complaint and eventually received a reply  written on 10 February 2011 by Dr Greg Ayers, head of the Bureau of Meteorology, which did very little to answer my queries.  However, he did promise to send me information with the reasons for the large adjustments at the worst nine sites.

On 1 June, after another letter of complaint, (with a copy to Greg Hunt, the Shadow Minister), I was sent the following anonymous email from Web Climate Requests:

Dear Ken Stewart,

thank you for your recent request for information about the Australian annual high-quality temperature data. Attached is a detailed description of station histories, adjustments and relevant information as promised in the Letter from Dr Greg Ayers dated 10 February 2011.

Kind Regards,

Webclim

and soon after, an apology from Dr Ayers.

 Here is the information that I had requested:

8. Please provide complete details, including station metadata, of the reasons for the large adjustments to the temperature records of the following sites: Omeo, Deniliquin Post Office, Nhill, Wagga Wagga AMO, Kellerberrin, and of the following Urban sites (not used in climate analyses but adjusted): Wangaratta Aero, Echuca Aerodrome, Benalla Shadford St, Dubbo Airport AWS.

I had also included in my original reply to Tony Burke the following:  Thank you in anticipation, as I hope this will answer some questions.  I trust that it will include some real explanations for the “subjective decisions” used to make adjustments at these sites.

The attachment with the station metadata and adjustments is included in full in the Appendix.

My reason for this request was that the papers cited by Dr Ayers, namely Torok and Nichols (1996) and Della-Marta et al (2004), both plainly state that while discontinuities in the data series indicating a need for adjustments were identified by “objective” methods, the decisions about whether to adjust and by how much were made subjectively after visual analysis.  Further, gaps in the records (including at sites with no overlapping comparative data) were infilled with estimates based on subjective techniques. 

Della-Marta et al go on to lament that it was impossible to reproduce exactly Torok and Nichols’ adjustments, as slightly different techniques, reference stations, and source data “can apparently produce different results”.  It seems they were surprised by this.

It is these “subjective decisions” about the magnitude of the adjustments that perplex me.

The adjustment details given by BOM are almost exactly the same as those given by Torok in his 1995 thesis.  The reasons for adjustments (with my interpretation of meaning) are given as :

Reason :

These indicate how the need for adjustment was detected, when supported by metadata documenting changes to the station.  However, remember that every decision to adjust and by how much, even when based on the above “reasons” including objective test and median, was made by visual reference and undisclosed “subjective” techniques.

It is not difficult to find when adjustments applied, and the magnitude.  All you have to do is subtract the raw maximum or minimum data from the adjusted data. 

So, we know when adjustments were made, how big they were, and how the need for them was identified- all of this anyone could find from an analysis of the data and from Torok’s thesis.  The only new information supplied was the station metadata and the adjustments since Torokand Nichols’s paper (1996). 

However, the critical information is missing:

• NO explanation for the size of the adjustments;
• NO criteria for thresholds for any objective test, diurnal range, anomaly detect, or median tests;
• NO lists of neighbouring non-urban sites;
• NO reference temperature sets.

I shall now examine each site in turn, examining the adjustments and their reasons, with reference to the supporting metadata now supplied.

Omeo is high in the ranges of north eastern Victoria. Here are the plots for minima, maxima, and adjustments.

BOM gives as reasons Objective test, Median, and Detect (see Appendix).  It is very difficult to figure out what sites are used for these methods, as many nearby stations are disqualified by Torok’s and presumably BOM’s own criteria, being over the ranges, on the coast, or much higher up mountains, or far to the north (over more mountainous country).  This is especially a problem as the Detect method requires comparison of anomalies with two neighbouring sites.  Anomalies have usually been from the 1961-90 mean, and data for these years are very scarce- indeed for any 30 year period in this region. Only Orbost (near the coast) and Beechworth (inland Victoria) have records which overlap in the second half of the century, and only Hotham Heights and Kosciusko Hotel are mountainous sites, with records in the early part of the century.  I compared both sets.

Minima

The spurious data for 1936-38 is obvious and needs correcting.  Most of the time Omeo’s anomalies are quite different from Orbost, but appear to track fairly closely with Beechworth, especially in the late 1950s.  The differences show that Omeo is too high relative to Orbost and Beechworth in the 1950s, too low from the mid 60s to mid 70s, and too high in the late 70s.  While the 1962 adjustment may well have been needed, it should not have been applied to all previous years.  Similarly the Kosciusko record is close to Omeo’s in the late 1920s, while Hotham Heights is completely different.  This does not indicate any need for adjustment, and certainly not for all previous years.  Further, the 1930 adjustment is for a move- but there is no move documented in the metadata.

Maxima

Notice that the HQ record appears to be based on Beechworth, then Orbost.  The 1978 adjustment of -0.4 appears to be the wrong sign- the adjustment should have been up- and should not have been applied to previous years.    There is not enough evidence to evaluate the 1934 adjustment.  It appears that the 1917 adjustment makes the anomalies similar to those of Kosciusko so seems appropriate.

The 1996 adjustment is small, and for a move, for which it appears there is no parallel data. Della-Marta et al describe the problems of adjusting station data where a station has moved.  Generally, at least 2 years of parallel comparative observations are needed, and adjustments calculated from this would be compared with the objective test method, however the objective method only detects discontinuities caused by site moves of at least 0.5 degrees Celsius.   Here the adjustment was +0.1!  They continue:

For site moves where no parallel data were available the shift value calculated by the objective technique was used.  If this was not available an estimated value was used based on subjective techniques.

Therefore, even though at least 2 years of comparative data are needed, sites such as this with no overlap at all are still used and are adjusted by “subjective” methods. 

The best we can say about Omeo is that we don’t know, as there are no nearby overlapping stations with a similar climate.  The metadata and “reasons” do not give an explanation for the enormous adjustments at Omeo.

Nhill, in western Victoria, is another example of  a station that has moved.

Maxima:

Minima:

Adjustments:

The metadata identifies moves in 1930, 1949, 1966, 1970, 1976, a “small” move in 1992, and 1995.  Adjustments are made for the 1930 move (in 1931), 1949, and 1995 moves.   There are no overlaps for any of these moves.  In fact, there are gaps. 

In December 1994 the observer died and the station closed.  There were no observations from 17^th December until 17^th January.   In January 1995 it had moved 5km.  Normally BOM does not give a monthly mean if there are more than 7 days missing, and does not give an annual mean for any year with a missing month.  Therefore, 1994 and 1995 should not have annual means, and there is a gap of two months with no overlaps at all.  (Adjustments for site moves are made by examination of monthly overlapping data for two years.)  This site should not have been considered for the “High Quality” network.

However, it has been included as HQ, so let’s continue looking at its adjustments.   Let’s look at Diurnal Temperature Range (DTR): Some minima adjustment is possibly necessary in 1994, given the large jump in annual diurnal range (not the method used but an indication of possible discontinuity), so we will look at this in more detail shortly, but there appears to be no such need for an equivalent (-0.8) adjustment in 1948.  (And notice the adjustment is made to maxima in 1950, and in minima in 1948.  Shouldn’t they be together?) 

BOM gives one of the reasons for the 1948 adjustment as Detect, so I used a similar (manual) method: I plotted the differences between anomalies of Nhill , Rainbow PO, and Jeparit, the closest sites with good overlap over 1949.   Torok says “Any spurious trends or discontinuities at the candidate station should be apparent in the two series involving data from the candidate station, but not in the series of difference between the two neighbours.” 

The difference series shows Nhill was too low from 1942-45, too high from 1947-54 (except 1953), so individual year adjustments are needed, but also the difference series fluctuate wildly, especially in the 1930s, so any adjustments should not have been applied to all previous years.  Using this method for 1994 by comparing with Stawell, Horsham, and Ararat Prison: It is plain that 1992-94 need adjusting, but the records around 1989-92 are fairly close; when the -0.8 adjustment is applied, the anomalies are closer to Ararat Prison and Stawell, but appear too high by 0.3-0.4.  0.8 is too much. 

You could go mad…

BOM’s adjustments at Nhill are based on the Objective Test (Torok’s median method), which apparently detected a discontinuity of more than 0.5 degrees (see above); however they have not supplied any information which will allow this to be checked.

Although BOM’s anonymous spokesperson assures me that all adjustments have now been explained to me, there are several examples of adjustment with no supporting metadata such as Nhill minimum in 1915.

Deniliquin, in south western NSW:

First, raw minima and maxima vs HQ.

The adjustments:

The 1971 minimum adjustment of -0.8:  Using a manual detect method, with Falkiner Memorial and Echuca as neighbouring stations (Echuca is urban, I know, but it has a long record) the anomalies show some discrepancy in 1971, but large ones in 1972, and to a lesser extent 1973.  However, the years before this, except for 1960-61, do not appear to have any marked discrepancies.  Again, without access to the data for the Objective test, I would therefore contend that the 1971 adjustment should be a single year adjustment, and should not apply to all previous years.  Although Detect is not used for the 1951 adjustment, the method does not indicate any discontinuity at Deniliquin.  Moreover, there doesn’t appear to be anything unusual about the diurnal range around 1951.  However, this plot of Deniliquin/ Echuca/ Kerang differences shows Deniliquin compares with Echuca, with Kerang being too low from the 1920s to the 1960s.The Deniliquin adjustments do not appear to be justified.

Wagga Wagga, in inland NSW

Maxima

Minima

Adjustments

The combining of the records for Kooringal and AMO with the good overlap in the 1940s produces a maximum record whose adjustments have little impact on the temperature trend.  The minimum overlap appears to show a UHI signal as the minima for Kooringal diverge from the initially identical AMO.  I therefore combined the minima records by reducing Kooringal by 0.1C- the average difference for the first 5 years of overlap, whereas BOM adjusts down by 1.0C. This adjustment (made in 1949) thus includes the UHI signal, and applies to all previous years.  We do not have any information to examine or replicate the Objective Test used to identify the need for this or the 1969 adjustment, so we must rely on Detect using overlapping nearby stations, Adelong PO, Deniliquin, and Cootamundra, as well as the Resource Centre.  

The plot of differences of anomalies shows from 1940-1949 Wagga Wagga is too high; and again in 1967; too low 1973-1975; and far too low in 1917 and 1918.  From 1950 to 1970 the AMO anomalies are fairly similar in most years, with some years higher, but which data record is correct?  However, BOM adjusts down by 0.7C in 1969 and applies this to all previous years.  Without additional information it is impossible to determine the necessity for these adjustments, or their size, but the 1949 adjustment at least appears to be unnecessarily large, and should not be applied to all previous years, especially as BOM metadata shows “documentation unclear”.

Kellerberrin is a small town in the West Australian wheat belt.

Minima

Maxima

Adjustments

The main adjustment to maxima occurs in the 1930s, following a period of poor observation practice.  The data from the 1930s looks poor and the adjustment is necessary- but for all previous years?  The 1996 adjustment upwards is more concerning.  This followed a move about 1.5km north to the airstrip, as the town site was unsuitable due to being bitumen surfaced.  So why were the maxima increased, not decreased?  Is bitumen cooler than grass under the midday sun?   Detect doesn’t show anything, and nothing in 1986.

Looking at minima, the 1996 adjustment appears necessary, but the size is questionable.  Here’s the Diurnal Temperature Range, used to justify the maxima and minima adjustments, compared with those of neighbouring Merredin, Cunderdin and Corrigin.  All four show little difference in range before 1996, but increasing through different ranges after 1996.  Now here’s a plot of daily DTR for 1995, 1996, and 1997.  Notice the gaps in September and October 1995.  There are large gaps in observations, more than 14 days each in either maxima or minima, so September and October should both show null by BOM’s standards, and therefore so should 1995.  The daily range appears to be less before this discontinuity, so I suspect this is when the station moved.  If so there is a gap with no comparative monthly data, and Kellerberrin should not be a HQ site.  Alternatively, was this when the site was bitumenised?  The comparison of anomalies shows Kellerberrin definitely needs adjusting.  Here’s a plot with the -0.8 adjustment:

Here’s a plot with an adjustment of -0.4, not -0.8.  This shows closer agreement with other site’s anomalies and BOM’s HQ anomalies. The move from the town to the airport was about 1 to 1.5km, and despite the documented problems with the site, there are no overlapping comparative data.

The 1979 move to Telecom land shows in the DTR and anomalies, and the corrections are probably justified- but are not documented at all.

The 1972 minima adjustment is based on Objective test and Detect.  The difference series of anomalies of Kellerberrin, Cunderdin, and Corrigin are almost identical from the 1950s to the mid 1970s;

It is obvious that Kellerberrin is different from Merredin and Corrigin after 1995, but in some previous years Merridin is more like Cunderdin whereas Kellerberrin and Corrigin are close.  Merredin is the outlier in the 1950s.  There is confusion in the 1970s; in 1971 and 1972  Merredin is again different.  Anomaly comparison may suggest that from 1950 to 1965 Kellerberrin may need adjustment down by 0.2 to 0.4 in individual years, however after 1965 this would increase the already high Diurnal Range even further.  Yet the minimum series was adjusted down for all previous years.  This is an example of how the need for adjustment can depend on which anomalies are being compared.  Without BOM’s list of nearby sites used for comparison, it is impossible to replicate the need for and size of this adjustment, and we can only assume that they used sites further away than these.

Apart from the 1930s, the undocumented 1979-80 adjustments, and 1996, Kellerberrin’s adjustments do not appear to be justified, and should not be applied to all previous years.

The following four sites are classified as Urban, and therefore are not used in the official climate analyses, however they also have been subject to large adjustments.

Wangaratta Aero in inland Victoria

Maxima:

Minima:

Adjustments:

BOM’s information indicates “Strong urban warming” and the metadata shows numerous site moves; also recent moves are not documented.  It is also immediately obvious that Wangaratta should not be a High Quality site because of the two year gap between the two site records, with BOM infilling with estimates.  It is therefore necessary to use nearby overlapping data for comparison.

The major adjustments were in 1994 and 1960, with smaller ones in 1951/1953 and 1988, with cooling adjustments in 1918, 1939, and 1974.  With no information about data used for Objective test or median, we can only use a manual Detect method to examine differences from neighbouring sites, which compares the differences in anomalies between the target station and two neighbours. 

Anomalies

Comparison of minimum anomalies of Wangaratta (including Aero), Benalla, Rutherglen, and Albury Air with Wangaratta HQ shows that the 1994 adjustment is about right, as are the 1986-87 estimates- which still doesn’t make the site HQ.  The adjustment should not have been applied generally to years before 1986.  In the mid 1940s and early 1950s and mid 1960s Wangaratta is too high and/or Benalla is too low; From 1910s to mid 1930s Wangaratta is low/ Benalla is high.  It can be quite clearly seen that the HQ anomaly data is spuriously as much as 1 degree below that of all the others for all years up to 1950, with the possible exception of 1939.  Similarly, the maximum anomalies show the closeness of the records, and that the HQ adjustment produces spurious data between 1919 and the late 1950s.

Wangaratta definitely should not be a High Quality site, and the adjustments wrongly increase the warming trend. 

Echuca Aerodrome on the Murray River in northern Victoria

Minima

Odd, eh?  We’ll look at this later.

Maxima

Adjustments

Once again without necessary information for replicating the Objective Test, we must rely on comparison of anomalies to manually replicate Detect.

Anomalies

The minimum anomalies of Echuca, Deniliquin and Kerang show  much disagreement from 1910 until 1924, then close agreement (0.1 to 0.3) between Echuca and Deniliquin (with a couple of exceptions  such as 1930 when Deniliquin is 0.6 higher, 1953-56 when it is 0.2 to 0.3 lower, and 1961 when it is 0.7 lower) until 1960, then up to 0.8 higher from 1972-79, then fair agreement from 1980 to 1983, then a difference of 0.2 to 0.4 from 1984 to 1991, then the records diverge.  It appears that Kerang is spuriously different from Echuca and Deniliquin from 1910 until the 1970s, then diverges again after 1985 until 2000.   The HQ adjusted data appears to favour Kerang or Kyabram in recent decades, and appears to be spurious from 1934 to 1968. 

Kerang maximum anomalies are much closer to the others than minima, except 1942-1952 .  Echuca is spuriously low from 1921 to 1938, 1950-55, 1968-71, 1986, 1995-97, and 2000. 

From 1910 to 1958 the adjustments make the BOM HQ maximum anomalies spuriously low, except for a couple of years. From 1992 HQ appears to be a 0.1 to 0.2 too high

Finally, in all adjustment records there are numerous small “ticks” up and down of about 0.1C, due to rounding perhaps, which are annoying but of no great consequence.  However, in Echuca’s minimum in 2005 there’s an enormous undocumented adjustment of +3.4 that sticks out like the proverbial.  This disparity is surely evidence that these adjustments have NOT been checked at all, that there is little quality control: or perhaps evidence of just plain incompetence.

Benalla Shadforth Street, in northern Victoria.

There is a gap – no monthly data, although there are daily observations (“Not quality controlled or uncertain, or precise date unknown” is BOM’s description of this data),  from September 1986 until observations resume in October 1987 (except for February 1987), although the metadata says the station moved in 1985:  this indicates some doubt about the metadata’s accuracy.  If there are no comparative observations, a gap in the record, when the station moved, then Benalla should not be HQ.

Adjustments:

Anomalies comparison:

Without information allowing replication of the Objective test, we can only use anomaly differences  to examine the adjustments.  Benalla’s maximum record  appears too high up to 1936, and too low from the mid 1940s to mid 1950s, and from the mid 1960s to mid 1980s is similar to or lower than neighbours.  HQ minimum anomalies appear spuriously low from 1910 to 1959.  The 1960 adjustment, applying to all previous years as well, does not appear justified by comparison with other sites.  Some of the 1938-1940 adjustments are justified, but not as great.  The 1976 adjustments are not documented in the metadata or the adjustment “reasons” and anomaly differences are not conclusive.  HQ maximum anomalies appear spuriously low from 1922-1925, 1929-1938, and 1941 to 1959. 

Benalla should not be HQ, as it appears to have a 2 year gap with no comparative data.  The Benalla adjustments do not appear justified, without the supporting information regarding Objective Test criteria.

Dubbo Airport, in inland NSW.

Dubbo is another combined site, but with many moves (see Appendix).  Once again, without information about reference sites for Objective Test and Median, we must rely on anomaly comparisons.

Maxima

The maximum anomalies are messy until about 1937.  The 1998 adjustment appears correct from comparing the raw data for Darling St and AWS, but the anomalies show that the 1987 adjustment of +0.5, while appearing to match anomalies back to 1954, makes the HQ record after 1987 spuriously low.  The 1954 correction of -0.5 is not warranted (1951-52 maybe) and the HQ record before 1954 is spuriously low.  The 1924 adjustment is not justified.

Minima

The record is messy until 1950; after that the anomalies are fairly close.  The 1987 5km site move is clearly evident in the minimum anomalies, and when the 0.8 adjustment is made to previous years, the anomalies closely track back to 1970. 

Comparison of differences of the Dubbo 2 splice (adjusted by -0.8) with Wellington, Agrow, Molong, and Mudgee shows how messy the records are.  By comparison with the decades before the 1950s, the difference between Molong and Dubbo 2 is relatively minor (-0.4 to +0.4), suggesting that the Dubbo record from 1957-1964 is fairly sound.

There appears to be no need for the adjustments of +0.3 in 1977, -0.7 in 1970, or -0.4 in 1952, applying to all previous years.  The late 1960s are messy, but without further evidence we cannot confirm the need for the 1970 adjustment to all previous years. The effect of these is clearly visible as the HQ anomalies appear to be spuriously below the others apart from a few years (e.g. 1916-1918 which have been adjusted correctly).  1943-1946 may need adjusting, but not 1940-41.  1929 is not warranted, and 1924 appears to be the wrong sign.  And good luck to anyone trying to make sense of the 1910-1915 data.

The minimum adjustments lead to a warming trend of 1.3, compared with the trend of 0.9 when including only the 1987 correction.

The Dubbo record is a mess.

Conclusion:

 These nine sites were identified as the ones with the largest adjustments of the 134 High Quality stations.  The timing of the adjustments, their size, and the method of identifying the need for the pre-1996 ones have for some years been publicly, if not readily, available.  Although the Bureau has been repeatedly requested to provide an explanation for the large adjustments, the only new information provided was the station metadata and the reasons for identifying the need for adjustments post 1996. It is impossible to replicate or justify adjustments without:

• detailed explanation for the size of the adjustments;
• the criteria for thresholds for objective tests, diurnal range, anomaly detect, or median tests;
• lists of neighbouring non-urban sites;
• reference temperature sets.

However, using the limited information available, an analysis of the adjustments at these nine sites was conducted.  To summarise some of the problems found:-

Omeo:  we don’t know: not enough supporting information, no nearby overlapping sites.

Nhill: gap in the record, should not be HQ.

Deniliquin:  no apparent significant anomaly differences from nearby sites; no evidence to justify the large adjustments.

Wagga Wagga: large adjustment takes no account of overlapping data showing UHI effect; little supporting information; blanket adjustments to all previous years.

Kellerberrin: UHI wrongly accounted for (wrong sign); no overlapping data; gaps in the record not documented; some adjustments needed but not for all previous years: not enough information.  Should not be HQ.

Wangaratta: 2 year gap during move with no overlapping data- should not be HQ; adjustments wrongly increase warming.

Echuca Aerodrome: gross undocumented adjustment shows lack of quality control.

Benalla Shadforth Street: gap in monthly data suggests metadata problematic, possible lack of comparative data- should not be HQ; some undocumented adjustments; not enough information.

Dubbo Airport:  a mess.  Adjustment of -0.8 justified, others doubtful.

We can conclude that:

• A small number of the adjustments do indeed appear to be justified.
• Many of the adjustments were wrongly applied to all previous years.
• Some are the wrong sign.
• The adjustments, being made subjectively, are mostly impossible to replicate, and often questionable and too large.
• Some adjustments have no supporting metadata.
• Some metadata appear inaccurate.
• Some adjustments are not documented at all.
• It is difficult to locate neighbouring overlapping sites with sufficiently long records for anomaly comparison.
• Some adjustments appear to make Urban Heat Island effect worse.
• Nearly all of the sites have a poor station history.  Some have multiple moves, and others reveal poor location, dubious observations, and gaps in the record infilled with estimates. 
• Wangaratta, Benalla, Kellerberrin and Nhill should not be High Quality as there are site moves with gaps in the record.  Kellerberrin and Nhill (2 of the 5 examined) are however used for climate analyses.
• There is evidence of lack of checking or quality control.
• Several sites feature adjustments that wrongly increase warming.

Nine of the 134 High Quality sites feature adjustments that are problematic and not explained; without complete detailed information and tedious analysis it is not possible to assess the validity of adjustments at the remaining 125- their adjustments remain unexplained.

The Bureau of Meteorology has failed to provide adequate explanation for the large adjustments to the HQ data for even this small subset of the High Quality sites.

The whole saga of BOM’s delays and lack of response to quite fundamental questions, reveals an arrogant, don’t care attitude.

The Australian High Quality Temperature Network has a poor and patchy record.  Instead of claiming it to be High Quality (meaning the best they can manage with the poor resources), BOM should admit that the record is a mess.  Rather than trying to defend it, BOM should immediately agree to an independent audit.

Another thing:  Dr Ayers also promised that he would send me copies of (1) a journal paper reviewing potential bias in warming trends to be published “later in the year” and (2) and an updated summary of operational adjustments  “after this is published in the scientific peer review literature”.    Well, it is much later in the year, and I’m still waiting.  Perhaps I should remind him again?

References:

Della-Marta, P, Collins, D., and Braganza, K:  Updating Australia’s high quality annual temperature dataset. Australian Meteorological Magazine, 53 (2004) pp. 75-93. 

Torok, S.J.: The development of a high quality historical temperature database for Australia.  PhD Thesis: School of Earth Sciences, University of Melbourne, 1996.

Torok, S.J. and Nichols, N: A historical annual temperature dataset for Australia. Australian Meteorological Magazine, 45 (1996) pp. 251-260. 

Climate data:  http://www.bom.gov.au/climate/data/

HQ data:  http://www.bom.gov.au/climate/change/hqsites/

 Further information available in

 Della-Marta P Collins C and Braganza K (2004), Updating Australia’s high-quality annual temperature dataset, Australian Meteorological Magazine 53 75-93.

Torok S J and Nicholls N (1996), A historical annual temperature dataset for Australia. Australian Meteorological Magazine 45 251-260.

Torok S (1996), The development of a high quality historical temperature data base for Australia. PhD Thesis, School of Earth

 All high-quality homogenised temperature data available at http://www.bom.gov.au/climate/change/hqsites/

 All monthly temperature data available at http://www.bom.gov.au/climate/data/

 Key to Adjustments

Station
Element (1021=min, 1001=max)
Year
Type (1=single years, 0=all previous years)
Adjustment
Cumulative adjustment
Reason : o= objective test
                f= median
                r= range
                d= detect
                l= overlap data
documented changes : m= move
                                    s= stevenson screen supplied
                                    b= building
                                    v= vegetation (trees, grass growing, etc)
                                    c= change in site/temporary site
                                    n= new screen
                                    p= poor site/site cleared
                                    u= old/poor screen or screen fixed
                                    a= composite move
                                    e= entry/observer/instument problems
                                    i= inspection
                                    t= time change
                                    *= documentation unclear
 

OMEO

083025

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 2 URBAN: N
The 1996 Torok rank of this station : 3 URBAN: N

Good complete, non-urban record. Objective test picked up 1996 site move and small adjustment made for Max T. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 083025
For the period: 1879 to 2003

Land use and surface types of current and previous stations from SITESDB

083025
Land Use 100m: Small town < 1000 population Surface Type: mostly covered by grass
Land Use 1 km: Small town < 1000 population Soil Type: clay
Land Use 10 km: Open farmland, grassland or tundra

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.02 p-value = 0.46
Trend in MaxT rural interpolated data = 0.05 p-value = 0.97
Trend in MaxT difference = -0.03 p-value = -0.98

Trend in MinT HQAT data = 0.13 p-value = 1.00
Trend in MinT rural interpolated data = 0.06 p-value = 0.99
Trend in MinT difference = 0.07 p-value = 1.00

METADATA & Adjustments

METADATA Summary

Omeo,083025
08/1899: “Thermometer shed very old and imperfect”.
03/1902: Stevenson screen sent.
12/1914: First correspondence. Possible move.
11/1935: Move from newspaper to PO.
07/1950: Screen repainted, max was reading high.
11/1963: Move and new screen as old one had an iron roof since 1950.
11/1977: Move to outskirts of town.
06/1984: Move due to growth of trees.
09/1996: SITE MOVE- 400m SW of previous
09/1996: Screen replaced
11/2000: THERMOMETER CHANGE- Temperature,alcohol,minimum (13th)
12/2000: THERMOMETER CHANGE- Temperature,mercury,maximum (18th)
02/2001: THERMOMETER CHANGE- Temperature,mercury,maximum (13th)
02/2001: THERMOMETER CHANGE- Temperature,alcohol,minimum (14th)

Latest Adjustment details

Maximum Temperature

083025 tmax 1996 0 +0.1 +0.1 om
083025 tmax 1978 0 -0.4 -0.3 fdm
083025 tmax 1934 0 -0.5 -0.8 odm
083025 tmax 1917 0 -0.3 -1.1 ord
083025 tmax 1907 0 +0.6 -0.5 ord
083025 tmax 1903 0 -1.3 -1.8 os
083025 tmax 1896 0 +1.5 -0.3 dr
083025 tmax 1887 0 -2.5 -2.8 frd
083025 tmax 1883 1 +2.5 -0.3 rd

Minimum Temperature

083025 tmin 1985 0 -0.2 -0.2 dm
083025 tmin 1978 0 +0.4 +0.2 odm
083025 tmin 1962 0 -0.8 -0.6 om
083025 tmin 1938 1 +1.0 +0.4 fd
083025 tmin 1937 1 +2.0 +1.4 fd
083025 tmin 1936 1 +2.0 +1.4 fd
083025 tmin 1930 0 -0.3 -0.9 odm
083025 tmin 1907 0 -0.2 -1.1 od
083025 tmin 1899 0 +0.3 -0.8 on*
083025 tmin 1883 1 -1.5 -2.3 fd

DENILIQUIN POST OFFICE

074128

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 2 URBAN: N
The 1996 Torok rank of this station : 3 URBAN: N

Good complete, non-urban record. No new adjustments required. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2002

Station: 074128
For the period: 1858 to 2002

Land use and surface types of current and previous stations from SITESDB

074128
Land Use 100m: Town 1000 to 10,000 Surface Type: mostly covered by grass
Land Use 1 km: Town 1000 to 10,000 Soil Type: red soil
Land Use 10 km: Town 1000 to 10,000

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = -0.01 p-value = -0.31
Trend in MaxT rural interpolated data = 0.04 p-value = 0.91
Trend in MaxT difference = -0.05 p-value = -1.00

Trend in MinT HQAT data = 0.10 p-value = 1.00
Trend in MinT rural interpolated data = 0.09 p-value = 1.00
Trend in MinT difference = 0.01 p-value = 0.02

METADATA & Adjustments

METADATA Summary

Deniliquin,074128
Some data deleted by BoM prior to 1964.
12/1925: First correspondence.
12/1949: Buildings have restricted yard.
02/1967: More building in 1950 rendered site very poor.
09/1971: Site moved 1 km northwest.
09/1984: Site moved to airport 3.7 km south.
03/2000: Screen replaced
02/2001: THERMOMETER CHANGE- Temperature,mercury,maximum (8th)
02/2002: THERMOMETER CHANGE- Temperature,alcohol,minimum (14th)

Latest Adjustment details

Maximum Temperature

074128 tmax 1984 0 -0.3 -0.3 odm
074128 tmax 1961 1 -0.7 -1.0 frdb
074128 tmax 1960 1 +1.0 +0.7 frdb
074128 tmax 1959 1 -0.7 -1.0 frdb
074128 tmax 1958 1 -0.7 -1.0 frdb
074128 tmax 1957 1 -0.7 -1.0 frdb
074128 tmax 1949 1 +0.4 +0.1 odb
074128 tmax 1948 1 +0.4 +0.1 odb
074128 tmax 1947 1 +0.4 +0.1 odb
074128 tmax 1946 1 +0.4 +0.1 odb
074128 tmax 1945 1 +0.4 +0.1 odb
074128 tmax 1944 1 +0.4 +0.1 odb
074128 tmax 1909 0 -0.8 -1.1 od
074128 tmax 1905 0 -1.6 -2.7 od
074128 tmax 1889 1 -0.6 -3.3 fd
074128 tmax 1888 1 -0.6 -3.3 fd
074128 tmax 1887 1 -1.8 -4.5 fd
074128 tmax 1886 1 -0.6 -3.3 fd
074128 tmax 1884 0 +1.5 -1.2 ord

Minimum Temperature

074128 tmin 1971 0 -0.8 -0.8 odm
074128 tmin 1951 0 -0.3 -1.1 orb
074128 tmin 1908 0 +1.0 -0.1 ords*
074128 tmin 1907 1 +1.0 +0.9 fd
074128 tmin 1903 0 +0.7 +0.6 ord
074128 tmin 1900 1 -1.2 -0.6 fd
074128 tmin 1899 1 -1.2 -0.6 fd
074128 tmin 1898 1 -1.2 -0.6 fd
074128 tmin 1877 1 -1.0 -0.4 d
074128 tmin 1874 1 +0.8 +1.4 d

NHILL

078031

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 3 URBAN: N
The 1996 Torok rank of this station : 2 URBAN: N

No overlap data for 1995 site move. Good completeness since move. Objective test detected move in Max T – adjustment made. Adjustment for Min T estimated. Oct 2007: Problems with homogeneity of early Min T record identified – so 1924-1930 single year adjustments removed, 1911 adjustment removed and 1915 adjustment identified by objective test added. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2006

Station: 078031
For the period: 1897 to 2006

Land use and surface types of current and previous stations from SITESDB

078031
Land Use 100m: Open farmland, grassland or tundra Surface Type: mostly covered by grass
Land Use 1 km: Town 1000 to 10,000 Soil Type: clay
Land Use 10 km: Town 1000 to 10,000

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.07 p-value = 1.00
Trend in MaxT rural interpolated data = 0.08 p-value = 1.00
Trend in MaxT difference = -0.01 p-value = -0.39

Trend in MinT HQAT data = 0.03 p-value = 0.76
Trend in MinT rural interpolated data = 0.08 p-value = 1.00
Trend in MinT difference = -0.05 p-value = -1.00

METADATA & Adjustments

METADATA Summary

Nhill,078031
03/1898: Thermometers broken by lame cockatoo.
03/1911: First correspondence.
07/1926: Iron shed to be built near screen.
07/1930: Likely move 1.5 miles from PO to flour mill.
08/1949: Site moved from PO to aerodrome.
03/1966: Move from aerodrome to good town site.
11/1970: Move across street due to likely building.
03/1976: Move within town.
08/1992: Small move away from garage.
12/1994: OBSERVER- long time observer died- station will close till new obvserver trained
01/1995: SITE MOVE- Station re-opens 5km from former- good exposure
01/1995: THERMOMETER CHANGE- Temperature,Drybulb (16th)
01/2002: THERMOMETER CHANGE- Temperature,Alcohl,Minimum (25th)

Latest Adjustment details

Maximum Temperature

078031 tmax 1994 0 +0.3 +0.3 om
078031 tmax 1950 0 -0.4 -0.1 odm
078031 tmax 1915 1 +1.0 +0.9 fd
078031 tmax 1905 1 -3.5 -3.6 frd
078031 tmax 1904 1 -2.5 -2.6 frd

Minimum Temperature

078031 tmin 1994 0 -0.8 -0.8 fm
078031 tmin 1948 0 -0.8 -1.6 odm
078031 tmin 1931 0 +0.2 -1.4 odm
078031 tmin 1915 0 -0.6 -2.0 o
078031 tmin 1905 1 +3.5 +1.5 frd
078031 tmin 1904 1 +1.8 -0.2 frd
078031 tmin 1903 1 +0.8 -1.2 frd
078031 tmin 1902 1 +0.8 -1.2 frd

WAGGA WAGGA AMO

072150 072151

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 2 URBAN: N
The 1996 Torok rank of this station : 2 URBAN: N

Good complete record. Located at airport since 1943 – urban warming unlikely. No new adjustments required. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 072150
For the period: 1943 to 2003
Station: 072151
For the period: 1908 to 1942

Land use and surface types of current and previous stations from SITESDB

072150
Land Use 100m: Airport Surface Type: fully covered by grass
Land Use 1 km: Airport Soil Type: red soil
Land Use 10 km: City area, buildings < 10 metres (3 storey)

072151
Land Use 100m: Surface Type:
Land Use 1 km: Soil Type:
Land Use 10 km:

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

072151 1928

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = -0.04 p-value = -0.77
Trend in MaxT rural interpolated data = -0.00 p-value = -0.08
Trend in MaxT difference = -0.04 p-value = -1.00

Trend in MinT HQAT data = 0.18 p-value = 1.00
Trend in MinT rural interpolated data = 0.05 p-value = 0.92
Trend in MinT difference = 0.13 p-value = 1.00

METADATA & Adjustments

METADATA Summary

Wagga Wagga,072150,072151
07/1923: First correspondence.
07/1925: Move to police grounds due to building at PO.
04/1928: Move due to previous site opening to public.
10/1933: Screen reoriented after facing east.
01/1943: Move to MO for composite site.
10/1994: AWS INSTALLED- Almos 21/10/1994
05/2000: Temperature Probe Drybulb serviced calibrated.
01/2001: Screen replaced

Latest Adjustment details

Maximum Temperature

072150 tmax 1942 0 -1.0 -1.0 oda
072150 tmax 1929 0 +0.3 -0.7 odm
072150 tmax 1924 0 -0.7 -1.4 odm

Minimum Temperature

072150 tmin 1969 0 -0.7 -0.7 od
072150 tmin 1949 0 -1.0 -1.7 oda*
072150 tmin 1918 1 +2.2 +0.5 frd
072150 tmin 1917 1 +0.8 -0.9 fd

KELLERBERRIN

010073

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 2 URBAN: N
The 1996 Torok rank of this station : 2 URBAN: N

Generally a good station record but some missing data during the 1980s. Adjustments added due to a site move in 1997. The new site is open and well exposed. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 010073
For the period: 1910 to 2003

Land use and surface types of current and previous stations from SITESDB

010073
Land Use 100m: Airport Surface Type: bare ground
Land Use 1 km: Open farmland, grassland or tundra Soil Type: sand
Land Use 10 km: Open farmland, grassland or tundra

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.08 p-value = 1.00
Trend in MaxT rural interpolated data = 0.06 p-value = 0.97
Trend in MaxT difference = 0.02 p-value = 0.86

Trend in MinT HQAT data = 0.11 p-value = 1.00
Trend in MinT rural interpolated data = 0.09 p-value = 1.00
Trend in MinT difference = 0.02 p-value = 0.98

METADATA & Adjustments

METADATA Summary

Kellerberrin,010073
10/1913: First correspondence
1910s : Observer problems.
06/1935: New screen after being in poor state of repair.
01/1939: Min problems due to reading of wrong end.
05/1971: Move 30m N to better exposure.
11/1971: Move 6m W of PO.
11/1979: Screen moved to Telecom land.
1979-85: No moves.
10/1985: Move 500m E of PO.
05/1997: SITE MOVED – to airport, old site bitumenised.
12/1999: Screen broken.
08/2000: Screen broken.
12/2000: Screen OK.
12/2000: SUSPECT DATA – Thermometer, Alcohol, Min broken.
01/2001: THERMOMETER REPLACED – Alcohol, Min.
03/2001: THERMOMETER REPLACED – Mercury, Max.
05/2002: THERMOMETER REPLACED – Alcohol, Min.

Latest Adjustment details

Maximum Temperature

010073 tmax 1996 0 +0.4 +0.4 rm
010073 tmax 1986 0 -0.6 -0.2 frdm
010073 tmax 1939 0 -0.6 -0.8 ord

Minimum Temperature

010073 tmin 1996 0 -0.8 -0.8 rm
010073 tmin 1972 0 -0.4 -1.2 odm
010073 tmin 1938 1 -1.3 -2.1 fde
010073 tmin 1938 0 +0.4 -2.1 frd
010073 tmin 1937 1 +1.4 +0.6 fde
010073 tmin 1936 1 +0.6 -0.2 fde
010073 tmin 1935 1 +0.6 -0.2 fde

WANGARATTA AERO

082138 082053

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 3 URBAN: Y
The 1996 Torok rank of this station : 2 URBAN: Y

Good completeness but recent site moves have no supporting metadata. Strong urban warming. Objective test failed to pick up site move – adjustment estimated for Min T only. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 082138
For the period: 1987 to 2003
Station: 082053
For the period: 1901 to 1986

Land use and surface types of current and previous stations from SITESDB

082138
Land Use 100m: Open farmland, grassland or tundra Surface Type: mostly covered by grass
Land Use 1 km: Open farmland, grassland or tundra Soil Type: red soil
Land Use 10 km: Open farmland, grassland or tundra

082053
Land Use 100m: Surface Type:
Land Use 1 km: Soil Type:
Land Use 10 km:

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

082053 1953

Urban & Rural Trend Detection Test

Torok 1996 classified this station as URBAN
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.07 p-value = 0.99
Trend in MaxT rural interpolated data = 0.04 p-value = 0.85
Trend in MaxT difference = 0.04 p-value = 1.00

Trend in MinT HQAT data = 0.13 p-value = 1.00
Trend in MinT rural interpolated data = 0.08 p-value = 1.00
Trend in MinT difference = 0.05 p-value = 1.00

METADATA & Adjustments

METADATA Summary

Wangaratta,082138,081053
11/1900: Stevenson screen sent.
03/1911: First correspondence.
10/1930: Screen repaired, roof was poor.
08/1938: Poor observer does not conform to observation times.
10/1938: Site moved to PO for new observer.
07/1952: Site was poor but even worse now due to building.
09/1952: Move to clear site on next block?
08/1961: Move 200 yards to new site.
04/1970: New site one mile west due to unreliable observer.
09/1974: Move 3 km south.
01/1987: Move to airport for composite.
06/1990: POOR EXPOSURE Screen over concrete. Should be removed.
05/1991: SITE MOVE- Screen moved off concrete slab 5m North . Concrete
slab close to screen and still compromising exposure.
06/1993: Screen replaced
09/1995: AWS INSTALLED- Almos 15/06/1993
09/1995: SITE MOVE- photose suggest AWS seems to be located in different
place to manual instruments, no site diagram in records.
08/1996: AWS CHANGE- Almos (8th) from station file. No record in SitesDB
03/1999: THERMOMETER CHANGE- Temperature,Probe,Drybulb (15th)

Latest Adjustment details

Maximum Temperature

082138 tmax 1988 0 -0.1 -0.1 fda
082138 tmax 1974 0 +0.3 +0.2 fdm
082138 tmax 1960 0 -0.7 -0.5 om
082138 tmax 1953 0 -0.5 -1.0 om
082138 tmax 1939 0 +0.3 -0.7 om
082138 tmax 1918 0 +0.6 -0.1 od
082138 tmax 1902 1 -1.0 -1.1 frs

Minimum Temperature

082138 tmin 1994 0 -1.3 -1.3 fm
082138 tmin 1988 0 -0.4 -1.7 fda
082138 tmin 1974 0 +0.4 -1.3 om
082138 tmin 1960 0 -1.1 -2.4 om
082138 tmin 1951 0 -0.4 -2.8 om
082138 tmin 1939 0 +0.7 -2.1 odm
082138 tmin 1932 0 -0.4 -2.5 odu
082138 tmin 1906 0 +0.5 -2.0 od
082138 tmin 1903 1 -1.0 -3.0 frds

ECHUCA AERODROME

080015

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 3 URBAN: Y
The 1996 Torok rank of this station : 3 URBAN: N

Good completeness in recent years but poor exposure for parts of record. No new discontinuities identified. Located within town of about 11,000 people till 1985 – urban warming possible. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 080015
For the period: 1881 to 2003

Land use and surface types of current and previous stations from SITESDB

080015
Land Use 100m: Airport Surface Type: mostly covered by grass
Land Use 1 km: Open farmland, grassland or tundra Soil Type: red soil
Land Use 10 km: Town 1000 to 10,000

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.13 p-value = 1.00
Trend in MaxT rural interpolated data = 0.01 p-value = 0.56
Trend in MaxT difference = 0.11 p-value = 1.00

Trend in MinT HQAT data = 0.04 p-value = 0.74
Trend in MinT rural interpolated data = 0.11 p-value = 1.00
Trend in MinT difference = -0.08 p-value = -1.00

METADATA & Adjustments

METADATA Summary

Echuca,080015
1892: Site is at Police station.
05/1899: Barrachi visits and pays for “painting thermometer shed etc.”.
07/1923: First correspondence.
08/1925: Screen in poor condition, sagging, sun shines on thermometers.
04/1939: Move to PO but site is hemmed in.
10/1958: Site poor and cluttered, screen facing west.
10/1966: Screen is an ‘old type’.
10/1967: Move to new site and new screen supplied.
06/1974: Move to better exposure.
04/1985: Site moved to airport.
12/1990: POOR EXPOSURE – the screen is showing signs of dry rot, will be replaced next visit. The site is open and well exposure apart form the concrete slabs leading to the screen and blue-stone in the car park.
01/1992: SCREEN CHANGE – screen in poor condition, replaced.
04/1995: SCREEN CHANGE – screen deteriorating, replaced.

Latest Adjustment details

Maximum Temperature

080015 tmax 1985 0 -0.5 -0.5 odm
080015 tmax 1975 0 +0.5 +0.0 odm
080015 tmax 1968 0 -0.9 -0.9 om
080015 tmax 1939 0 +0.5 -0.4 odm
080015 tmax 1924 0 -0.8 -1.2 odu
080015 tmax 1909 0 +0.3 -0.9 od
080015 tmax 1901 1 -1.5 -2.4 frd
080015 tmax 1900 1 -1.0 -1.9 frd
080015 tmax 1899 1 -1.0 -1.9 frd
080015 tmax 1888 0 +0.6 -0.3 od
080015 tmax 1882 1 -1.0 -1.3 d

Minimum Temperature

080015 tmin 1985 0 -0.5 -0.5 odm
080015 tmin 1975 0 -0.3 -0.8 odm
080015 tmin 1968 0 -0.6 -1.4 odm
080015 tmin 1939 0 +0.4 -1.0 odm
080015 tmin 1925 0 -0.6 -1.6 odu
080015 tmin 1900 1 +1.5 -0.1 or
080015 tmin 1899 1 +1.0 -0.6 or
080015 tmin 1898 1 +0.5 -1.1 or
080015 tmin 1897 1 +0.5 -1.1 or
080015 tmin 1885 0 +1.5 -0.1 ord

BENALLA (SHADFORTH STREET)

082002

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 3 URBAN: Y
The 1996 Torok rank of this station : 3 URBAN: N

Complete record but poorly exposed. No new discontinuities identified. Located within town of approx 9,200 so some urban warming likely. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 082002
For the period: 1903 to 2003

Land use and surface types of current and previous stations from SITESDB

082002
Land Use 100m: Town 1000 to 10,000 Surface Type: fully covered by grass
Land Use 1 km: Town 1000 to 10,000 Soil Type: clay
Land Use 10 km: Open farmland, grassland or tundra

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

Urban & Rural Trend Detection Test

Torok 1996 classified this station as RURAL
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = 0.02 p-value = 0.54
Trend in MaxT rural interpolated data = 0.04 p-value = 0.89
Trend in MaxT difference = -0.02 p-value = -0.69

Trend in MinT HQAT data = 0.10 p-value = 1.00
Trend in MinT rural interpolated data = 0.07 p-value = 1.00
Trend in MinT difference = 0.02 p-value = 0.97

METADATA & Adjustments

METADATA Summary

Benalla,082002
Stevenson screen supplied around 1899?
01/1921: Move.
05/1939: Slight move away from concrete. Site is poor.
11/1944: Screen is poor with iron roof and exposure cramped. 06/1951: Move 140m from PO to better exposure.
06/1960: Move to Postmaster’s residence.
12/1968: Move due to change of house.
04/1985: Move to good site.
1993: POOR EXPOSURE- Site is in backyard on watered lawn. Surrounded by
galvanised iron fence and buildings. Shade for part of the day.
12/2000: THERMOMETER CHANGE- Temperature,Alcohol,Minimum (20th)
10/2001: THERMOMETER CHANGE- Temperature,Mercury,Maximum (2nd)

Latest Adjustment details

Maximum Temperature

082002 tmax 1959 0 -0.8 -0.8 om
082002 tmax 1938 1 -1.0 -1.8 fdp
082002 tmax 1937 1 -1.0 -1.8 fdp
082002 tmax 1912 0 +0.5 -0.3 ord

Minimum Temperature

082002 tmin 1986 0 +0.4 +0.4 om
082002 tmin 1960 0 -0.6 -0.2 om
082002 tmin 1958 1 -0.5 -0.7 fdp
082002 tmin 1957 1 -0.5 -0.7 fdp
082002 tmin 1956 1 -0.5 -0.7 fdp
082002 tmin 1949 1 -0.5 -0.7 fdu
082002 tmin 1948 1 -0.5 -0.7 fdu
082002 tmin 1940 1 -0.5 -0.7 fdu
082002 tmin 1939 1 -0.5 -0.7 fdu
082002 tmin 1938 1 -0.5 -0.7 fdu
082002 tmin 1935 0 -0.9 -1.1 oru
082002 tmin 1911 1 +1.0 -0.1 fd

DUBBO AIRPORT AWS

065070 065012

Overview

1 = very good, 2 = good, 3 = fair, 4 = poor, 5 = very poor, 6 = city
The 2002 rank of this station : 3 URBAN: Y
The 1996 Torok rank of this station : 4 URBAN: Y

New site open and well exposed. Reasonable overlap data. Site move not detected by objective test. Max T adjustment calculated using overlap data. 1998 used as change year. No new Min T adjustments. Some urban warming in the historical record. ____________________________________________________________________
COMPOSITE STATION HISTORY

The composite station record includes the years: 1910 to 2003

Station: 065070
For the period: 1994 to 2003
Station: 065012
For the period: 1871 to 1993

Land use and surface types of current and previous stations from SITESDB

065070
Land Use 100m: Airport Surface Type: partly covered by grass
Land Use 1 km: Airport Soil Type: red soil
Land Use 10 km: City area, buildings < 10 metres (3 storey)

065012
Land Use 100m: City area, buildings < 10 metres (3 storey) Surface Type: fully covered by grass
Land Use 1 km: City area, buildings < 10 metres (3 storey) Soil Type: sand
Land Use 10 km: Open farmland, grassland or tundra

Urban population test

The candidate station numbers shown below could be influenced by urbanisation due to the population of the of the surrounding or adjacent city. The year shows when the population of the city exceed 10000
Stnnum Year

065012 1948

Urban & Rural Trend Detection Test

Torok 1996 classified this station as URBAN
Trends calculated over 1910-1993 and expressed as deg.C/10years. P-value = 1.00 – P(type 1 error)

Trend in MaxT HQAT data = -0.06 p-value = -0.95
Trend in MaxT rural interpolated data = -0.12 p-value = -1.00
Trend in MaxT difference = 0.05 p-value = 0.99

Trend in MinT HQAT data = 0.20 p-value = 1.00
Trend in MinT rural interpolated data = 0.10 p-value = 1.00
Trend in MinT difference = 0.10 p-value = 1.00

METADATA & Adjustments

METADATA Summary

Dubbo,065070,065012
1873: Move of site.
1884: Move of site.
1921: Move of site.
02/1929: First correspondence.
04/1929: Observers of 60 years leave, so site moved to PO.
04/1938: New screen replaces very poor one and moved to better position.
07/1953: Building necessitates move next door after screen had been left on a fence.
11/1969: Screen moved 50 feet to better exposure.
01/1978: Move due to building 150 m west.
02/1982: Move to another poor site 300 yards southeast.
10/1986: Site moved 5 km northwest to good exposure.
10/1999: THERMOMETER CHANGE- Temperature,Mercury,Drybulb (14th)
01/2000: Station Closed 19/01/2000
01/2000: SITE MOVE to 065070 aero AWS (Micromac) opened 18/12/1992
Screen replaced 06/1//1997
04/2000: AWS CHANGE- Micromac (3rd)
01/2001: AWS CHANGE- Almos (16th)

Latest Adjustment details

Maximum Temperature

065070 tmax 1998 0 -0.3 -0.3 lm
065070 tmax 1987 0 +0.5 +0.2 fdm
065070 tmax 1954 0 -0.5 -0.3 fdm
065070 tmax 1924 0 -0.6 -0.9 odm
065070 tmax 1908 0 -1.3 -2.2 ods*
065070 tmax 1899 0 +0.8 -1.4 o
065070 tmax 1891 1 +1.3 -0.1 fd
065070 tmax 1890 1 +1.3 -0.1 fd
065070 tmax 1884 0 +2.0 +0.6 odm
065070 tmax 1876 0 +1.4 +2.0 odm

Minimum Temperature

065070 tmin 1987 0 -0.8 -0.8 odm
065070 tmin 1977 0 +0.3 -0.5 odm
065070 tmin 1970 0 -0.7 -1.2 odm
065070 tmin 1952 0 -0.4 -1.6 odm
065070 tmin 1941 1 +0.5 -1.1 fdp*
065070 tmin 1940 1 +0.5 -1.1 fdp*
065070 tmin 1929 0 +0.5 -1.1 odm
065070 tmin 1924 0 -0.5 -1.6 odm
065070 tmin 1918 1 +0.8 -0.8 fd
065070 tmin 1917 1 +0.8 -0.8 fd
065070 tmin 1916 1 +0.8 -0.8 fd
065070 tmin 1908 0 +0.9 -0.7 ods*
065070 tmin 1896 0 +0.7 -0.0 od
065070 tmin 1885 0 -2.2 -2.2 ordm
065070 tmin 1874 1 +7.0 +4.8 rdm
065070 tmin 1873 1 +2.0 -0.2 d

The September UAH value is +0.29  making the running 12 month mean +0.19 +/- 0.1.

My short term predictions are straying from the observations, with the levelling out appearing to be 4 to 5 months earlier than I expected.  However, a sharp drop in October UAH is expected.   

When I first started posting this series, I hoped to be able to estimate temperatures 7 months in advance.  That appears to be falsified as the temperature lag seems to be much less this year.  (The lag should be between 5 and 9 months, typically 7, but I have been using 6 months for some time.  The climate oscillations appear to vary in frequency as well as amplitude, if you like.)  So from the end of 2011 on I will concentrate on long term estimates.

Here is a plot of my expected long term values of the 12 month running mean of UAH anomalies, barring major volcanic eruptions or a significant shift in climate regime (which certainly is on the cards).   Any small changes you may detect from the last post are due to the fact that I have been playing with adjustments to the formula I have been devising.  I am predicting that the 12 month running mean of global UAH will not go above + 0.6 at any time in the next 11 years, which would be needed to maintain the current trend.  It may go above +0.5 in 2013-14 and 2017-18, but my tip is that temperatures will be largely in the middle to lower portion of this plot, but will rise towards the upper limit with El Ninos.  I’ve been wrong before of course.  This will be the subject of a large post I have been promising for months but am little closer to completing.

The “significant weather event in Eastern Australia (storms or rain) around the end of September to the first week in October, give or take a few days”, which I predicted in my September post, arrived in bucketloads, and has extended into the middle of October, the traditional storm season.  The storms haven’t reached this far north but have hit south-east Queensland hard. 

Storms are also building across the Top End, Gulf Country, and Cape York.  I’m tipping an early start to the Wet, with a monsoon trough appearing on Australian weather maps by mid November (35-49 days from the beginning of October).

September Global temperature is posted below, but it will be a week or two at least until the first of my next posts, which will be:

• An analysis of the BOM explanations for their adjustments to the raw temperature data
• Long term SOI influences on global temperature
• An analysis of Australian minima 1910-2010.

Thanks for your patience.