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climate change wa

Have automatic weather stations corrupted Australia's temperature records?

Extreme temperatures spike with electronic probes

Australian climate change and extreme daily temperatures are as likely to have been influenced by automatic weather stations (AWS) as by CO2 since the 1990s.

Following Australia's Glasgow commitment to net zero CO2 emissions by 2050, and having previously had a close look at the extraordinary distribution of rounded .0 Fahrenheit decimals before 1972 metrication, let's pay attention to how the advent of AWS might have influenced temperature trends.

AWS installations have replaced most but not all liquid-in-glass thermometers that used to be read manually. They use an electronic probe to measure temperatures and it's claimed their more rapid response times to brief periods of hot air cause an increase in the frequency of extreme maximum observations.

Bureau data downloads in 2022 suggest that 105 of the 112 weather stations in the Australian Climate Observation Reference Network (ACORN) are AWS, their average start year 1996. Of those 105 AWS installations, 14 were from 1986 to 1991, 66 from 1992 to 1999, and 25 from 2000 to 2018.

Furthermore, most 230 litre Stevenson screen shelters were replaced with 60 litre shelters from the 1990s and these smaller screens altered the dimension of thermal influence on the new electronic probes.

Daily temperature percentile analysis

AWS extreme maximum temperature observations can be measured with trends in the 90th percentile (hottest 10%), 95th percentile (hottest 5%) and 99th percentile (hottest 1%) of all daily maxima during the 20 years before and after electronic probes replaced manual thermometers at all but seven of the 112 ACORN weather stations used by the BoM to calculate Australia's national average temperatures.

The seven excluded locations had not been converted to AWS and continued with manual thermometer observations in 2021.

Percentiles are calculated from every unadjusted daily RAW maximum observation (over 12 months in each year) since 1910 at each station (1910 the first year of estimated annual Australian temperatures within ACORN), with collective annual percentile averages calculated over the 20 years before and after AWS installation at each station.

Despite earlier installation, the BoM began using electronic probes as the primary temperature instrument for almost all automatic weather stations as of late 1996, and this analysis calculates averages in the 20 years before and after 1996 when AWS observations replaced manual thermometer readings in the bureau's RAW temperature datasets.

Such analysis shows 70 ACORN AWS stations (exactly two thirds the total number) had an immediate increase in the average annual frequency and temperature of these hot, very hot and extremely hot days when observations from these first electronic probes were introduced to the RAW datasets.

extreme hot days and aws

The four stations charted below are examples of changes in 90th, 95th and 99th percentile temperature days 20 years before and after an AWS was installed (black line frequency, red line temperature).

australian weather stations with aws influence

Among the 35 remaining ACORN AWS stations, there was either little change or a reduction in the average annual frequency and temperature of 90th, 95th and 99th percentile days, their collective averages charted below.

aws lack of influence on extreme temperatures

The collective annual average 90th, 95th and 99th percentile frequency and temperature at all 105 ACORN AWS locations are charted below.

automatic weather station influence on extreme temperatures

Note : most weather stations have differing numbers of missing observation days in all years since 1910 and this creates an unknown margin of error in all percentile frequency and average temperature calculations. However, in the five years before the most common year of original AWS installation in 1996 (1991-1995) there was an average annual total of 896 missing maximum observation days among all 105 AWS stations, and in the five years after AWS installation (1997-2001) there was an average annual total of 1,422 missing days. This means that despite the significant and rapid increase in the frequency of high percentile days, there were fewer total days within which to count the hottest 10%, 5% or 1%. The greater number of missing days includes extreme heat days that are not counted, meaning the calculations above are probably a slight underestimate of their rapidly increased frequency following AWS installation.

There are seven remaining ACORN stations that are not AWS and continue to have manual thermometer observations, and their annual average frequency and temperature of 90th, 95th and 99th percentile days since 1962 are charted below (Barcaldine opened in 1962), with rainfall trends likely to have influenced both frequency and temperature over the past 20 years at both the manual stations and all 105 AWS locations analysed above.

average temperature at australian manual thermometer weather stations

In the 90th percentile (10% hottest days), the seven manual ACORN weather stations without electronic temperature probes were 0.02C warmer in 1991-1995 than 1997-2001, compared to a 0.15C increase at the other 105 locations in the five years following AWS installation - of which a large proportion became the primary instrument (device from which official temperatures are observed and used in BoM datasets) in 1996.

Hot, very hot and extremely hot days have a strong influence on monthly and annual average temperatures calculated by the bureau, partly due to their frequency and partly because more extreme temperatures have a greater influence than cooler temperatures on overall averages.

Apart from a majority of ACORN stations (70 v 35) experiencing an increase in the frequency of 90th, 95th and 99th percentile days, analysis results show that although conversion from manual to AWS observations caused a frequency and temperature increase at some stations and a decrease at others, the AWS extreme temperature influence is biased toward heating rather than cooling.

90th percentile (10% hottest days)

< Five years > AWS at 70 stations : 27.9% frequency increase / 0.28C temperature increase

< Five years > AWS at 35 stations : 2.2% frequency decrease / 0.09C temperature decrease

< 10 years > AWS at 70 stations : 31.2% frequency increase / 0.27C temperature increase

< 10 years > AWS at 35 stations : 7.9% frequency decrease / 0.06C temperature decrease

95th percentile (5% hottest days)

< Five years > AWSat 70 stations : 37.6% frequency increase / 0.21C temperature increase

< Five years > AWSat 35 stations : 19.5% frequency decrease / 0.08C temperature decrease

< 10 years > AWS at 70 stations : 45.5% frequency increase / 0.20C temperature increase

< 10 years > AWS at 35 stations : 11.2% frequency decrease / 0.05C temperature decrease

99th percentile (1% hottest days)

< Five years > AWS at 70 stations : 56.0% frequency increase / 0.03C temperature decrease

< Five years > AWS at 35 stations : 27.1% frequency decrease / 0.06C temperature decrease

< 10 years > AWS at 70 stations : 72.3% frequency increase / 0.01C temperature decrease

< 10 years > AWS at 35 stations : 17.4% frequency decrease / 0.04C temperature decrease

The frequency and temperature of hot, very hot and extremely hot days continued to increase rather than plateau in the 20 years following AWS installation, possibly because 19 stations have converted since 2001 (20 years before 2021) with an accumulating influence, and possibly because many locations experienced a rainfall decline after the year 2000 which increased the likelihood of hot days. A majority of AWS electronic probes have also been replaced since the year 2000 (see AWS electronic probe replacements below).

For example, Karijini North AWS opened in 2018, replacing the manual thermometer observations at nearby Wittenoom.

average temperature at karijini north aws

Note : Annual percentile calculations for all 112 ACORN weather stations in the AWS analysis above can be downloaded as an Excel (xls 6.6mb), a CSV (1.1mb) or an Apple Numbers (11.9mb). Alternatively and if you don't like using spreadsheets, all of the results can be viewed in a PDF (3.3mb).

AWS electronic probe replacements

59 of the ACORN automatic weather stations have had their electronic probes replaced during the years since original installation.

The chart below shows the 84 stations that had an immediate increase in their annual average frequency and temperature trends of 90th, 95th and 99th percentile maximum days in the 20 years before and after their latest probe installation (replacement or original if no replacement).

aws electronic probe replacement

The chart below shows the 21 stations that had either no change or a decrease in their annual average frequency and temperature trends of 90th, 95th and 99th percentile maximum days in the 20 years before and after their latest probe installation (replacement or original if no replacement).

aws electronic probes

The chart below shows the annual average frequency and temperature trends of 90th, 95th and 99th percentile maximum days in the preceding and following 20 years only at the 59 stations that have had probe replacements (excluding stations that only have an original probe that hasn't been replaced).

temperature probe replacements

The chart above can be compared with annual average extreme percentile trends at the 46 stations that have only had one original probe installed which has never been replaced.

temperature probe replacements

These results suggest that replacement probes had a more significant influence than their predecessors on the maximum temperature percentile frequencies.

temperature probe replacements

This analysis raises questions about the accuracy of Australian temperature averages since the 1980s, as well as the veracity of claimed record heat days where the artificial influence of automatic weather stations may have caused the record rather than actual heat.

The AWS electronic probe influence on the frequency of extreme temperature percentile observations is rapid and significant.

It's not know how this affects overall temperature averages calculated by the BoM but it is likely to cause artificial warming as these are the hottest 10% of all daily observations with a strong commensurate influence on averages.

Among 90th percentile maximum temperatures, or the hottest 10% of days since stations opened, the original AWS installation at all 105 ACORN stations saw an annual average 3.85 additional such days within five years. At the 59 stations that had their probes replaced, there were an annual average 8.12 additional such days within five years.

This suggests that on average all ACORN AWS stations had almost 12 extra 90th percentile days annually after their probes were either first installed or replaced.

Using Nuriootpa as an example, there were an average 17.25 more 90th percentile days annually in the 20 years following AWS installation than in the 20 years before, with the average temperature of such days increasing by 0.5C. The average Oodnadatta maximum in the three summer months of 2019/20 was 29.4C, and if 17 of these summer days are cooled by 0.5C the station's overall summer maximum would be 0.1C cooler at 29.3C.

The analysis results also raise questions about temperature trends globally since most countries in the world began using automatic weather stations instead of liquid-in-glass thermometers during the 1980s and 1990s.

Note : Annual percentile calculations for original and replacement probe ACORN weather stations can be downloaded as an Excel (xls 6.6mb), a CSV (1.1mb) or an Apple Numbers (11.8mb). The results can also be viewed in a PDF (3.3mb).

Long-term weather station temperatures

Let's look at decimal frequency and temperatures within the 58 long-term ACORN stations that were open in 1910.

Maximum

aws influence on maximum temperatures

Minimum

automatic weather station influence on temperatures

As per the claims that an AWS is more sensitive to extreme maxima rather than minima, the first maxima chart shows a clear temperature shift around 2000 and the second minima chart shows stability since 1980 with a slight cooling probably due to a drop in rainfall (although less annual variability than in those earlier years).

The average maximum at the 58 long-term ACORN stations was 25.24C in 1990-99 and 25.62C in 2000-09, an abrupt 0.38C increase. Average minima at the 58 stations was 13.94C in 1990-99 and 13.83C in 2000-09 - it cooled 0.11C!

However, annual average rainfall at the 58 long-term ACORN stations dropped from 717.5mm in 1990-99 to 647.0mm in 2000-09. Cloud cover is an influence but when rainfall previously dropped a similar amount from 1950-59 (772.9mm) to 1960-69 (703.9mm), maxima at the 58 stations increased .only 05C.

So as in the last 1972 metrication post (link), let's again look at the distribution of decimal observations to see if they detect any change in how temperature readings were influenced by the AWS instrument changes.

Maximum

temperature decimals influence

Minimum

influence of decimals on minimum temperatures

Here the waters are muddied because, as you can see in the tables if you look closely, the number of rounded .0C observations increased significantly from 1997 to 2004 in both maxima and minima.

This is because many of the automatic weather stations installed in the mid-1990s had a recording fault acknowledged by the BoM that caused them to only report .0C readings.

For example, every single day at Cape Leeuwin from 18 May 1998 to 8 January 2003 recorded a temperature with a decimal of .0, and not a single .1, .2, .3, etc. It took well over four years but the BoM eventually noticed the problem and fixed it, claiming it was an equal up and down decimal error so it didn't corrupt the average temperatures.

The table below shows the evolution of .0, .1 and .9 Celsius decimals at the 58 long-term ACORN stations in the decade before 1996, the following nine years inclusive of acknowledged AWS rounding errors, the decade to 2018 and then 2019, Australia's driest year on record.

aws influence on temperature decimals

The frequency of .0C declined 34.8% from 1986-95 to 2019, the frequency of .1C increased 24.3%, and the frequency of .9 increased 41.5%.

To be pedantic, from 1986-1995 to 2019, the frequency of .1, .2, .3 and .4 increased 11.1%, and the frequency of .6, .7, .8 and .9 increased 13.9%.

The average number of .9 compared to .1 maximum recordings increased by 175 from 1986-1995 to 2005-2018, while the average number of .9 compared to .1 minimum recordings increased by 25.

Might the AWS increase in higher decimals help to explain why maxima increased by 1.39C at the 58 stations between those periods, while minima increased by only 0.22C?

BoM testing of AWS response times

The BoM has tested one second variations within the minute at 6am and 3pm for replacement temperature probes at 98 ACORN stations, and acknowledges that at 17 of them there was a significant breakpoint likely to suggest a change in the instrument response time (source).

alice springs aws influence

Due to area averaging that influences temperature homogenisation at neighbouring stations (hundreds of kilometes distant in the remote outback), Alice Springs is arguably the most influential station in Australia in terms of the ACORN calculation of national averages.

The table below displays maximum, minimum, rainfall and solar exposure totals and averages at Alice Springs Airport from 2009-2010 to 2012-2013.

alice springs climate elements

There were 27 fewer days of rainfall in 2012-2013 than in 2009-2010, but 66 more days at or above 30C+, 65 more days at or above 35C, and 56 more days at or above 40C.

Solar exposure, which is influenced by cloud cover, was overall the same from 2009-2010 to 2012-2013, with more days above average in 2012-2013 than 2009-2010 but those days having a lower MJ/m2 intensity in the latter years.

Comparing 2009-2010 with 2012-2013 at Alice Springs Airport, average maximum at or above 30C warmed 1.0C, average maxima at or above 35C warmed 1.1C, and average maxima at or above 40C warmed 0.6C, with the average maxima for all days throughout the years increasing 1.9C.

There was less impact on minima from the AWS Almos probe replacement on 11 November 2011, although the average minimum for all days cooled 0.6C from 2009-2010 to 2012-2013.

The probe replacement influence on maxima can be illustrated with charts:

alice springs 2011 aws probe replacement

Decreased rainfall is an influence but this data contradicts the BoM claim that the November 2011 probe replacement at Alice Springs Airport only caused a 3pm increase of 0.16C and a 6am increase of 0.03C, with resultant warming of neighbouring ACORN stations due to area averaging.

Alice Springs Airport had 76.8mm of rainfall in 2009 with an average maximum of 30.0C, but 194.2mm in 2013 with an average maximum of 30.8C. There were 201 days above 30C in 2009 and 223 in 2013.

An independent analysis examines the two years before and after the original installation of AWS probes at ACORN stations, finding that average minima warmed 0.06C and average maxima warmed 0.11C. If you want a detailed breakdown of AWS installations, replacements and their influence on temperatures, pop over to a web page quite aptly titled Climate change or instrument change?

The analysis also looked at the two years before both the original installation and replacement of probes at the stations, finding that average minima warmed 0.07C and average maxima warmed 0.31C.

Also analysed are the number of rainfall days, very hot 40C+ days and solar exposure in the two years before and after.

Many of the probes were replaced over time and, measuring these, average maxima were 0.46C warmer in the two years after probe replacement compared to the two years before, with an average -0.01 decrease in solar exposure.

Parallel non-AWS and AWS weather stations

Automatic weather stations are said to exaggerate the number of maxima which spike rapidly due to brief gusts of hot air, with a similar influence on minima with brief gusts of cold air, compared to liquid-in-glass thermometers with a slower reaction time.

The table below shows the total number and average temperature of daily observations within cool and hot categories at 12 parallel weather stations.

To minimise environmental influences, the 12 are selected only where non-AWS and AWS shelters are positioned less than a kilometre from each other at sea level elevations the same or with no more than three metres difference, and only with days when observations were recorded at both stations over the same time periods (i.e days with missing observations at either station are excluded from both).

aws influence on temperature numbers

The average of all maxima above 30C recorded at AWS stations was 0.1C warmer than in parallel non-AWS stations, and the average of all minima below 20C recorded at AWS stations was 0.2C cooler than in parallel non-AWS stations.

All 12 AWS stations are manufactured by Almos. There is no consistency among the 12 but the overall averages suggest minima are recorded cooler than maxima are recorded warmer in AWS compared to their nearby non-AWS stations. However, the results do not suggest more frequent or hotter temperatures are recorded in automatic weather stations on extreme heat days above 40C.

Similar results can be seen when comparing the hottest and coldest days and nights, rather than averages, recorded at the 12 parallel stations.

aws influence on temperature numbers

Download Excel dataset of 12 parallel non-AWS and AWS weather stations (1.7mb)

These results suggest AWS response times might partly explain why Australia's national average maximum has increased at a significantly higher rate than the average minimum, as illustrated in the temperature charts higher on this page.

Instrument change = temperature change

That's all quite a jumble of decimals, time periods, maxima, minima and electronic probes, but there's a consistent pattern along the trail of breadcrumbs - the introduction of automatic weather stations appears to have caused a fundamental change in the measurement of air temperatures and the changes (particularly higher decimals) are likely to affect maxima more than minima.

And what happened to temperatures at the 58 long term ACORN stations? From 1986-95 to 1996-2005, maxima at the 58 stations increased 0.28C and minima cooled 0.03C. There was an annual average 703.4mm of rainfall in 1986-95 and 687.5mm in 1996-2005.

From 1979-95 to 1996-2012, maxima increased 0.31C and minima increased 0.01C. Annual rainfall at the 58 stations averaged 700.7mm in 1979-95 and 703.3mm in 1996-2012. There was a tiny bit more rainfall cloud cover but maxima jumped while minima behaved as it should.

From 1986-1995 to 1996-2018, maxima at the 58 stations increased 0.47C and minima increased 0.04C. Average annual rainfall at the stations averaged 703.4mm in 1986-1995 and 689.0mm in 1996-2018.

These comparison suggest either that climate warming affects daytime maxima but not overnight minima, or averages from AWS probes are more sensitive to high temperatures than low temperatures.

However and aside from 1972 metrication and AWS corruption, it's worth noting that the 2005-2018 average temperatures might also be influenced by something that happened in 2013, and the next article will analyse what that influence was.

Note : Annual Fahrenheit and Celsius decimal counts for minima and maxima from 1910 to 2019 at the 58 long-term ACORN stations are contained in an Excel file that can be downloaded here.

Note : See BomWatch for a thorough analysis of four weather stations in its analysis of are Australia's automatic weather stations any good.




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