by Tom Quirke
The raw Melbourne temperature records of the Bureau of Meteorology are compared to the ACORN-Sat values. The ACORN-Sat adjustments are evaluated. This analysis shows evidence for a strong urban heat island effect.
The Melbourne temperature record is one of the “long time” instrumental records of Australian temperature. It starts in 1855 and continues to the present day. Originally measurements were made in the Flagstaff Gardens. Then when the Melbourne observatory was established in 1863 near the Botanical Gardens, the measurements were taken at that location until 1907 when there was a move to the present location on the corner of Victoria and Latrobe Streets in central Melbourne.
The raw annual average measurements[1] are shown in Figure 1. The Melbourne location statement (July 2014) records no thermometer changes between 1907 and 2000 for the minimum-temperature thermometer and between 1907 and 2001 for the maximum-temperature thermometer
Figure 1: Melbourne Regional Office annual average minimum and maximum temperatures, first measured in the Flagstaff Gardens, then at the Observatory, and then from 1907 at the present site, the corner of Victoria and Latrobe Streets.
The Bureau of Meteorology (BOM) considers only the measurements after 1910 as being reliable but note that the raw record itself does not suggest anything wrong with the earlier data.
The maximum temperature, which generally occurs in the middle of the afternoon, shows almost no trend at all until about 1995. However the minimum temperature, which generally occurs in the early morning before sunrise, shows an upward trend starting at about 1945. With no sunlight on the ground, the night air cools but the heat emitted by buildings and human activities, the “urban heat island” effect, lessens the cooling. The upward trend of minimum temperature since 1945 perhaps reflects the change in the number and size of the buildings in the area surrounding the location of the thermometers.
Figure 2: Site of the BOM Regional Office measurement station[2]
We can compare the Melbourne measurements with those starting in 1944 at Laverton, some 20 km from the Melbourne Regional Office location. See Figures 3 and 4. The Laverton instruments were moved some 1.2 km from the original site in 1997. One year of overlap measurements at Laverton show no significant change at that time in maximum-temperature readings, but do show a 0.2 degree decrease in the minimum-temperature readings.
Figure 3 shows an increase in the minimum temperatures, using the raw data, at the Melbourne location compared to that at Laverton from 1944 to the present. The comparison, roughly an increase of about 2 degrees compared with an increase of about 1 degree, is almost certainly an indication of the much larger urban heat island effect in Melbourne. Figure 4 shows both the maximum temperatures and the trends of maximum temperature in Melbourne to be much the same as in Laverton.
Figure 3: Annual average minimum temperatures for the ACORN-SAT homogenized Melbourne Regional Office measurements, raw minimum temperatures for the Melbourne Regional Office and Laverton.
Figure 4: Annual average maximum temperatures for the ACORN-SAT homogenized Melbourne Regional Office measurements, raw maximum temperatures for the Melbourne Regional Office and Laverton
The third temperature series in each of Figures 2 and 3 is of the average annual temperatures recorded in the ACORN-SAT data[3] which has been “homogenized” by the Bureau of Meteorology. A comparison of the measured and adjusted temperature increases from 1944 to 2013 is shown in Table 1.
Table 1 Temperature increases from 1944 to 2013
| Locations | Minimum temperature increase 0C per decade | Maximum temperature increase 0C per decade |
| ACORN-SAT Melbourne | 0.18 ± 0.02 | 0.13 ± 0.03 |
| Raw Melbourne | 0.35 ± 0.02 | 0.21 ± 0.03 |
| Raw Laverton | 0.14 ± 0.03 | 0.16 ± 0.03 |
| Raw Melbourne – Raw Laverton | 0.21 ± 0.03 | 0.05 ± 0.05 |
Two conclusions can be drawn from this analysis:
- There is a clear heat island effect in central Melbourne that is detectable in the minimum temperature measurements. It may be as much as 0.2 degrees per decade (or 1 degree over 50 years!).
- The adjustments made to obtain the homogenised ACORN-SAT Melbourne data reduce the apparent long-term temperature increases. So these adjustments compensate somewhat for the urban warming but by increasing the temperatures of the earlier years!
The result of the ACORN-SAT adjustments made to the raw data for Melbourne is illustrated in Figure 5. There are sharp breaks rather than gradual changes that would be expected from the slow growth of the urban surroundings. The breaks do no appear to coincide with instrument changes. The Bureau explains the adjustments for the maximum and minimum temperatures as being “statistical”.
Figure 5: ACORN-SAT adjustments to the raw Melbourne temperature measurements shown in Figures 2 and 3.
In more detail, the ACORN-SAT Melbourne minimum temperatures before 1990 are shifted up relative to the raw data. The stepped adjustments would suggest instrument changes but the BOM records show thus is not the case. Further, there is no sign of the step changes in the direct Melbourne temperature records. An upward correction is also applied to the maximum temperatures, but is applied only to the past, before 1990, and not the present.
A step adjustment does not compensate for a gradual rise due to an urban heat island effect.
Would a time of observation change need a step adjustment? The explanation for the step change in 1964 is a change in the reading time of the thermometers from midnight before 1964 and at 9.00 am after 1964. This seems a remarkable adjustment. If the thermometers were read at midnight then the minimum and maximum would be for that day while a shift to a 9.00 am reading would give the minimum temperature for the day of the reading but the maximum for the previous day. How could this give rise to an adjustment? Even if the temperature were recorded for the wrong day only one day in a year would be wrong and then only by a small amount.
The Melbourne mean annual minimum and maximum temperature readings are shown in Figure 6. There is an unusual feature in the maximum record occurring in 1996. It is a break with a difference of 0.7 +/- 0.2 0C. The two straight lines are a best fit to the measurements and the difference is calculated from the line values in 1996. There is no statistically significant break in the minimum record. The fits are made between 1960 and 2014 as the minimum temperatures start increasing in the 1940s.
Figure 6: Annual average raw minimum and maximum temperatures for the Melbourne Regional Office. The straight lines represent the best fit for two lines for the maximum record and one straight line for the minimum that shows no statistically significant break.
The ACORN-SAT adjustment record (Figure 5) shows only an increase of 0.41 0C to the maximum temperature record starting at 1 Jan 1990. This adjustment is explained as “statistical”. Interestingly the adjustment record shows a break in 1996 for the minimum temperature record and this change is ascribed to a new large apartment building “across the street to the south of the site”.
It would appear that this step in 1996 is not a thermometer change as none is detailed in the raw data site record. However in the ACORN-Sat record a change to an Automatic Weather Station (AWS) is noted for 1996! An instrument change being the cause is ruled out by the above analysis. However the maximum temperature break does indeed come from the screening of the site from summer southerly winds[4] by the building of “City Gate” at 33 La Trobe Street (Figure 7). This is a 15 story 50 m high apartment tower completed in 1997 and to its east a further apartment building completed in 1998. These building are visible in Figure 2 on the south side of La Trobe Street and to the south east of the thermometer positions.
Figure 7: City Gate tower directly to the south east of the BOM thermometer site in 2015 after the site was closed (see Figure 2)
The explanations of the ACORN-SAT data adjustments do not provide much support for their validity. Only one of the many adjustments seems to be specifically linked to a change in procedure, and the term “statistical” conveys no physical or procedural change as justification.
The Importance of the Urban Heat Island Effect
The changes in temperature can be further explored by looking at summer and winter time series. Summer is the months of December, January and February while winter is June, July and August. The annual maximum temperatures for summer and winter are shown in Figure 8 and minimum temperatures in Figure 9.
Figure 8: Melbourne Regional Office annual summer and winter maximum temperatures
Figure 9: Melbourne Regional Office annual summer and winter minimum temperatures
There are two significant features for these time series:
- The maximum summer temperature shows no increase in temperature from 1863 to 1996 when the site was effected by high rise buildings nearby. In fact the change from 1863 to 1996 is 0.03 +/- 0.02 0C per decade. This a rise of 0.45 +/- 0.29 0C in 133 years
- The summer minimum and the summer and winter minima all show an increasing temperature after the mid 1940s. The increases are summarised in Table 2.
Table 2 Minimum and maximum temperature changes
| 1950-2014 | Temperature increase 0C per decade | |
| Summer | Max* | -0.12+/- 0.12 |
| Min | 0.23+/- 0.03 | |
| Winter | Max | 0.36+/- 0.06 |
| Min | 0.30+/- 0.03 | |
| Annual | Min | 0.33+/- 0.02 |
* 1950-1996
It is apparent that the urban heat island effect is present in both minimum and maximum temperature records.
This effect is well illustrated by comparing the La Trobe Street – Victoria Street measurements with the new BOM site in Olympic Park, some 2.5 km distance to the south. There is some overlap of the sites and Figure 10 shows 19 months of overlap.
Figure 10: Differences for BOM Melbourne Regional Office less Olympic Park monthly mean temperatures.
The differences are greatest in the summer for both minimum and maximum temperatures. This indicates a strong urban heat island effect over a short distance of 4 km. This raises the question of how well sites can be used to determine adjustments if their monthly temperature variations are different.
Conclusions
There are two conclusions that arise from this analysis:
- It appears that not sufficient attention has been paid to examining the site surroundings and
- “Statistical” evidence is only useful if it can be used as a guide to finding instrumental or environmental changes.
The Melbourne measurements may not be used to derive the continent-wide Australian temperatures. Even so, if the treatment of the Melbourne temperature measurements is an indication of the quality of the other homogenized measurements, then there is a need to refine the analysis.
Finally the purpose for assembling the extensive temperature record is not clear as the “temperature” is what is measured and the ACORN-Sat adjustments give rise to a construct. If this is used to estimate mean temperatures then the problems of averaging minimum and maximum temperatures to give a mean raises a further series of problems that have not been addressed.
References:
[2] Image supplied from Joanne Nova- [link]
[3] ACORN-SAT information and data: [link]
[4] A summary of the winds in Melbourne [link]
JC notes: This is a guest post, submitted via email. As with all guest posts, keep your comments civil and relevant.
Just curious if BOM supplies the code and possibly other documentation of their procedures?
I see some documentation, but no code. Is that correct?
The best that they’ll do, Jim, is tell you that (whatever it is that they do), it is world’s best practice!
http://en.wikipedia.org/wiki/Global_warming
Scientific understanding of global warming has been increasing. In its fifth assessment (AR5) in 2014 the Intergovernmental Panel on Climate Change (IPCC) reported that scientists were more than 95% certain that most of global warming is caused by increasing concentrations of greenhouse gases and other human (anthropogenic) activities.[7][8][9] Climate model projections summarized in AR5 indicated that during the 21st century the global surface temperature is likely to rise a further 0.3 to 1.7 °C (0.5 to 3.1 °F) for their lowest emissions scenario using stringent mitigation and 2.6 to 4.8 °C (4.7 to 8.6 °F) for their highest.[10] These findings have been recognized by the national science academies of the major industrialized nations.[11][b]
What more is there to say?
What more is there to say?
Climate Model projections are really mostly garbage.
They do not produce output that matches real temperature data.
There is nothing more that should be said.
Some say “the planet will boil over” (Obama), some say we’re already dead by 2012. (The Canadian, some rubbish source)
Some others might claim the wiki/Global_warming is a target of aggressive political campaigning and might not reflect well AR5 nor the scientists that wrote it.
This is the IPCC charter:
«The role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the scientific, technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts and options for adaptation and mitigation.»
We can see two things here:
Man-Made global warming is taken as a given, the IPCC is starting with the conclusion, their task being merely to produce proof in accordance with the conclusion. Any inconvenient data can be ignored or tortured until it is confessing,
We also see than natural climate change is outside the IPCC charter. Clearly they have no mandate to study the sun. So it basically is ignored and/or defined away in their reports, expect for a ridiculously small effect as can be seen in AR5 figure 7.
For those of you trusting the IPCC reports, I have some prime Florida swampland I want to sell you.
I did find this. It seems the entirety of the data processing is not in code.
“The methods implemented for the ACORN-SAT data set were very labour-intensive, particularly for quality control. This presents an obstacle to such methods being scaled up to be applied to multi-national or global-scale data sets, along with the limited international availability of supporting data (for reference series) and metadata. In principle, however, it should be feasible to automate the homogenisation process, at least up to the point of producing
an initial set of homogenised data. “
Note that UHI is also visible in the Laverton series. Melb Univ Prof Karoly refers to Laverton as a “rural” site. He compares it to Melbourne to discount UHI in the Melbourne series. Laverton was an airfield, now a training college. In the 1980-90 timeframe a multi-lane freeway was built just south of the measuring station, and there is a newish prison on the north side. Massive industrial and residential development near it.
Note for information that Karoly is a member of the Climate Change Authority, which has a Board comprising nine members: Bernie Fraser, Lynne Williams, David Karoly, Elana Rubin, Heather Ridout, John Marley, John Quiggin, Ian Chubb and Clive Hamilton. Most of these members have a heavy Left-warmist bias, a number are not well-regarded by fine upstanding retired economic policy advisers such as myself. (I know three of them personally.)
Faustino
Our main local station is suddenly now the airport. Should get a good bake out there. But no-one can say it’s urban!
UHI doubters might do a barefoot shuffle on tarmacs to show us up. Shuffle might quickly turn to a tap dance in high summer, or even that old surf club stomp.
Looks like in addition to being homogenized the Melbourne data also has been pasteurized to remove the presence if not the footprint of the living.
But the work was done by the cream of the profession.
Thanks to Wagathon and Faustino for my best laugh of the day!
Fine systemically biased temperatures butter no parsnips — the thermometer at the cuckoo tree by the old abandoned hunters cabin on Wolverton Mountain has shown no global warming for 100 years.
Unfortunately too many historical records have been contaminated by the urban growth effect. In Melbourne this is a direct consequence of the poor decision to site the sensors in the center of the city,
Unless the purpose of the station was to measure the urban heat island effect. If that is the case, then what we have worldwide are two sets of weather stations:
1) Set one to measure temperatures of rural areas
2) Set two to measure temperatures of urban areas
Analysis in the US has shown that set (2) reveals the urban heat island effect (UHI) in all urban places down to a few thousand population. As a consequence, set (1) is also contaminated with the UHI effect depending on the size of population and the siting.
I have seen graphs for the US that demonstrated the possibility of using a formula to estimate the UHI effect for each location as a function of population and to subtract it from temperature data sets before homogenization.
What I find odd is that government meteorological offices actually adjust the historical data so radically when publishing it. These data are public records like Census data or vital statistics. It is fair for researchers to adjust the data for special purposes.
However, I question whether or not it is legal anywhere for a met office to publish as official the “data” that has been adjusted for more than time-of-day and re-siting of the instruments.
Such adjusted “data” is not “official data” in the sense of an official public record, but an intermediate calculation for the purpose of further study.
Whoever adjusts the data should have to make clear to potential users exactly how the data has been adjusted.
Better still, the Minister responsible should set out a regulation stating which adjustments may be regarded as official and which are for the convenience of the research community.
Otherwise, we have the spectacle of an official meteorological office operating in a manner that would not be allowed a graduate student who is preparing a master’s thesis?
Victoria and Latrobe Junction, lots of traffic and buildings.
Walk past on a Summer’s day or evening, phew ! And
judging by those mini temps, heat hangs around.
The raw temperature data, though who can say it was
strictly accurate, was at least a trend, but with added
homogenizing fer statistical reasons, seemingly little
to do with UHI effects (and that’s not precise) what
has become of the official record? ACORN ‘quality’
control seems only so much hot air. A Melbourne serf.
Melbourne has a very long record, and BoM have been reluctant to lose that continuity. However, they have now moved the site to Olympic Park.
Have you thought about looking at the trends in tmin/tmax?
It seems to be a favorite meme of the skeptics that UHI shows up in tmin.
It’s my understanding that you also see an increase in tmin in rural sites from anthrogenic forcings.
I would swear Zeke (and maybe Mosher) have looked a comparison of rural to urban sites (tmin/tmax/tmean).
Can’t put my finger on it atm, if they have.
Carrick,
This might be what you are thinking of: http://onlinelibrary.wiley.com/store/10.1029/2012JD018509/asset/jgrd50037.pdf?v=1&t=i7m4bhzh&s=317433ef65a24a64fe04fab1baf304405f9cf070
Or this: http://wattsupwiththat.com/2011/12/05/the-impact-of-urbanization-on-land-temperature-trends/ (original AGU poster no longer online, unfortunately).
Regarding this post and UHI, while I can’t comment on specific BoM homogenization techniques (since I’m not really familiar with them, as they aren’t used for any global products), it does seem like they do a reasonably good job of removing the trend bias vis-a-vis the nearby rural station.
Zeke, thanks. I just got back to looking at responses (been in the field for the last few days).
The link you gave was broken. Pretty sure this one works:
http://onlinelibrary.wiley.com/doi/10.1029/2012JD018509/full
Quantifying the effect of urbanization on U.S. Historical Climatology Network temperature records
Zeke Hausfather, Matthew J. Menne, Claude N. Williams, Troy Masters, Ronald Broberg, David Jones
Regarding the PowerPoint, I’d suggest creating an account on Research Gate and posting your talks there. Google Scholar links these, so people can find the downloads without needing a research gate account.
‘half removed’ suddenly becomes ‘effectively removed’, but I don’t understand the implications of that, if any, though I suspect so.
================
There was warming in the time after the last Little Ice Age when there was supposed to be warming.There is nothing wrong when warming occurs when it would, based on natural variability, based on past data, Earth has warmed and Earth was supposed to warm.
I am sure Steven Mosher will be along, but in the meantime I will post what BEST makes of Melbourne. Note that BEST objectively detected the warming of Melbourne relative to its surroundings including the jump that happened in 1996, and would have corrected it to remove these jumps.
http://berkeleyearth.lbl.gov/auto/Stations/TAVG/Figures/151813-TAVG-Alignment.pdf
from the following page
http://berkeleyearth.lbl.gov/stations/151813
ha ya I came to post it.
Commenting on posts like this is a waste of time.
1. We know there is a UHI Bias
2. It is easy to find stations with this bias.
3. The bias is weak at global scales.
You basically have two mind sets that will never meet.
There are similar studies that look at over 400 large cities showing the same thing. so, there is nothing worthwhile in this post as it doesnt address the central mystery of UHI bias.
I don’t entirely discount some effect from UHI situations, But since that came to the forefront some 8 years ago, there has been enough work to show that it’s not enough of a factor to explain away the long-term warming trend.
Note: Since 1992, when I saw Carl Sagan give a presentation for my college, I have been pretty skeptical about AGW. I just didn’t, and still don’t, like the comparison of Earth to Venus. I took part in Anthony Watts Surface Station data gathering exercise cause i thought actually looking at station sighting was a worthwhile scientific thing to do. But as the years have gone by, more and more of the hard-core skeptics alternate explainations as to why the temps are rising, or even if they are rising, are being dealt with scientifically.
I still think the science is not quite as bulletproof as some make it out to be, but I’m much less the skeptic than I used to be.
Mosher,
That demonstrates your bias. You are not interested in good scientific analyses of real data, unless they are buried in BS statistic and manipulated models line Michael Man’s hockey stick.
Is it any wonder that you guys reputation is going down the toilet and taking the reputation of some other branches of science with you.
Steven Mosher: I was wondering if you have researched the temperature gradient around the urban heat islands, such that you can use the temperature data from the urban area as is, but use a kriging technique to circumscribe the effect to the urbanized area itself?
I don’t want to get into the details, but sometimes a geommodel has to be corrected for unusual highly localized phenomena (say a canyon cut in Cretaceous silt and shale sequence filled with a very clean Miocene sandstone). Evidently we have to limit the Miocene fill to keep it within the sloping canyon walls, so the model has to be “fixed” to account for this local effect.
Just a few weeks ago Steven, you were saying that UHI was where people should put their efforts.
Pingback: Taking Melbourne’s temperature | Enjeux énergies et environnement
A few points :
1. I don’t think there is anything untoward about the adjustment being made to past temperatures. Stockmarket prices are adjusted that way for share splits, dividends, etc, as it allows today’s (and tomorrow’s) price to be compared with past prices without itself having to be adjusted. IOW, it’s not an entirely unreasonable way of doing it. [I’m not saying that there isn’t a better way]
2. The Time of observation (Tobs) change can have a step-change effect. With a midnight Tobs, the minimum temperature will quite often be set by the end midnight instead of the early-hours minimum as intended. IOW there will often be an incorrectly low minimum. With a 9am Tobs this will happen less often.
3. re Steven Mosher’s comment (Mar 23 at 12:45 am) : UHI is not necessarily weak at global scale, because it is possible for each urban reading to influence a large surrounding area – for example if there are few other weather stations in the region. This is the case in Australia, where many regions have stations only at airports or in country towns. ie, those stations provide the only temperatures for large regions.
1. A stock split doesn’t change the valuation of a company.
2. TOB’s from midnight to 9am does not warrant an adjustment. Any change during the morning or afternoon observations certainly merits an adjustment. Early morning or late afternoon observations may not be valid….. with the old style recorders.
3. All temperature signals are weak on a global scale, precisely because of the processing and assumptions that they are put through. Every process they are put through loses information.
used to have fogs ++ in Melbourne 40 years ago, 1/3 the size.
Are fogs reduced by heat increase and UHI?
Short answer is YES, Yes they are… WUWT had a paper on this last week or the week before looking at a specific airport in US.. sorry.. no link etc.
I recall it showed that the bottom of mists etc was raised some distance.
(sorry poor recall, though remember thinking it was interesting).
I believe this is what you are referring to, Jim :
http://wattsupwiththat.com/2015/03/05/think-uhi-doesnt-affect-the-climate-think-again/
Worth recalling that when Sydney, on January 18 2013, broke (very briefly) its 1939 daily max record, the nearby (paddling distance) harbour station was drastically cooler, nowhere near any records. Neither was it especially hot away from Sydney where I live. Just very hot. Chance of some UHI there? As for harbourless and built-up Melbourne during summer…
A non-scientist will dwell on the “record” and infer trends from superficial numbers. Those who pointed out that January 18 2013 was not even part of an El Nino managed to forget that the heat of 1939 occurred (drum roll) during a La Nina flanked by neutral years! (1939’s heat, quite apart from the fires, remains our most deadly natural disaster. A La Nina!)
A true scientist would describe January 18 2013 as a bloody hot day which broke a few records at a few Sydney sites.
Compared to what a bit of cloud will do to a temp record UHI may be pretty thin stuff. A lot of cloudy weather over an Australian winter will give you a lot of high minima. Get those same minima under clear skies and you really may have a freaky climate. You might be waiting a while.
Do our temp gurus even realise that their real job a lot of the time is noting cloudiness of which they are unaware, not temps?
Add UHI to all that…and what have you actually learned or shown?
I do think to myself “so what”. The UHI effect is well-known. This is one reason why they prefer to base climatic changes on anomalies, not the absolute temperature.
“Even if the temperature were recorded for the wrong day only one day in a year would be wrong and then only by a small amount.”
Can you justify this claim?
Tom Quirke,
Melbourne always was a very ‘hot’ town. Sydney’s a much better place :)
By the way, well done and thank you. Your work is always intereseting informative and relevant.
Yeah, apart from the stinking humidity, deluges and mould on everything that doesn’t move.
Well, at least the Sydneysiders play sport instead of sitting on their backsides watching it. :)
“Would a time of observation change need a step adjustment?”
Indeed yes!
” So these adjustments compensate somewhat for the urban warming but by increasing the temperatures of the earlier years!”
Yes, that is the convention. Homogenisation says that a relative change is detected. You can “warm the past” or lower the present, equally. They keep the present unchanged, since they are the most frequently quoted.
“The Bureau explains the adjustments for the maximum and minimum temperatures as being “statistical”.”
Like you, they do pairwise comparison, and notice that Mel is warming faster than nearby. At some stage they make a “statistical” correction. What do you think they should do?
I was thinking that myself – the way the term “statistical” is used with inverted commas seems to imply it is a negative term in some way. So I ask Tom Quirke, why use the term “statistical” as a pejorative?
I interpret the implication is that they’ve said ‘statistical’ to avoid having to provide a meaningful and believable explanation for the discrepancy. It would have been more honest to admit they don’t have a clue why the manipulated data is bent in a what that suits the message they want to portray, but they will leave it as is without further investigation. Of course abrupt changes in the trends that do not support the cause will be closely invested and readjusted to support the cause. That’s how climate ‘science’ works. Ask an authority: Michael Mann.
But Judith- I thought the BEST study, to which you lent your name, was supposed to assure us that UHI had been properly taken into account, and that fudging of the figures was under control.
What was that all about?
A useful cross reference would be to compare The Melbourne and Laverton sites with Scoresby. Scoresby is situated on a large grassed area with no inhabited buildings close by and up until recently was an agricultural scientific establishment. It is at the intersection of Burwood Hwy and Scoresby Rd but is as far from them as is possible. I have lived in the area for 46 years and have not noticed any great changes to its environment.
Please allow some facts and deductions about this Melbourne Regional site from one who lives in Melbourne (as I believe Tom Quirk does also – I am in agreement with his comments above) and who has used this station 86071 as a training set for new ideas since 2005.
(A). UHI effect.
Yes, there are 2 classes of data, those with UHI and those without. To attempt to quantify the latter, I selected some 44 stations from all over Australia, on the basis of being as close to pristine (= no UHI) as I could imagine. The trends of these stations were calculated over the study period 1972-2006 (chosen because the change from deg F to deg C was in 1972 and because I started this study with the latest data in 2008). It was hoped that these very rural stations would provide a good baseline for what the climate was actually doing without much help from the Hand of Man. The results are at
http://geoffstuff.com/pristine_feb_2015.xls
Conclusion – there is no uniform or even useful baseline trend for time series analysis. Even the World Meteorological Organisation Number correlates, with a trend, with temperature change.
Lesson – the more remote a station, the lower the quality of the data.
(B). Data quality of Melbourne 86071.
Australia’s Bureau of meteorology advised me by email of 1 Sept 2014 that their web pages that show “Computer Data Online” or CDO use raw data as collected by observers, exception as noted:
“The data made freely available through Climate Data Online are the raw station data as recorded by observers and automatic weather stations, corrected for gross errors only (such as writing down rainfall with the decimal point missing or in the wrong place). There are various reasons why gross errors in reported observations may occur, including instrument, communication and observer error.”
So far as I have measured correctly, the temperature data at this site are not intrinsic in the mathematical sense. E.M. Smith notes about intrinsic/extrinsic measurements or entities that –
“Climate Science is dedicated to the notion that you can average just one, intensive, variable, that being temperature, and do thermodynamics. (Or calorimetry). It is just absurd on the face of it, but at a much deeper philosophical level, it has no standing. No basis in a valid philosophy. It is bankrupt of meaning. “Global Average Temperature” is an oxymoron. A global average of temperatures can be calculated, but it is not a temperature itself and says little about heat flow. Calculating it to 1/100 of a unit is empty of meaning and calling it “Degrees C” is a “polite lie”. It is a statistical artifact of a collection of numbers, not a temperature at all. (There is no thing for which it is the intrinsic property).”
https://chiefio.wordpress.com/2011/07/01/intrinsic-extrinsic-intensive-extensive/
The temperature data are not independent and identically distributed random variables, or i.i.d, for statistical purposes. Here are some plots of the very central part of the distribution of Tmax starting with the period from 86071 for 1856 to 1900, when readings were in deg F. When converted to deg C, the first place after the decimal is preserved. This analysis is about the distribution of the day-to-day differences.
http://geoffstuff.com/melbourne_bins_1855_1899.jpg
The distribution of these results is, by eye, leptokurtic and skewed. You can tell me if the data are heteroskedatic.
The usual conversion from deg F to deg C is not reversible in all cases, if the deg C are expressed to one point after the decimal. Unless you have the original, paper copies of the early records in deg F, you cannot reconstitute the record.
There is also autocorrelation within this data set. Here is a graph showing the daily temperature data correlated against itself, with lags of 1, 2, 3 …. 12 days.
http://geoffstuff.com/melbourne_lagged_correlations.jpg
Conclusion: Thus, there are some philosophic and practical limits to the type and complexity of statistics that are valid for this data set. Operations like the ‘law of large numbers’ and the ‘central limit theorem’ are perhaps not initially valid.
Lesson: Try to understand your data before you get fancy with it.
(C). Why not compare Melbourne with surrounds?
Here are several Excel pages of sites that the public can use, from suburbs of Melbourne to small towns further out, to try to subtract rural from urban to get UHI estimates.
Good luck.
http://geoffstuff.com/melbourne_suburbs_2013_4.xls
(This post is not as polished as I would like. I am working with severe medical complications and have little time to update).
Feel free to email at sherro1 at optusnet dot com dot au
As you say, the temperatures are intrinsic to the object measured. Weather stations measure the air temperature in contact with a terrain underneath. For a whole host of reasons analyzed by Pielke Sr., the landscape for each station uniquely affects the climate at that site, both the absolute measures and also the trends of changes.
Thus, to understand temperature changes, we have to study the changes, not the temperatures themselves. I choose to analyze the monthly slopes from each station history to see local, regional or larger scale patterns.
Goeff:
As long as linear regressions as short as yours (1972-2006) are computed, no consistent “baseline” trend will found, no matter how pristine the non-urban station data. The presence in varying strength of multidecadal and longer spectral components in the time-series will always produce strongly time-varying and spatially inconsistent short-term “trends.” To obtain something more akin to a baseline secular trend, one has to employ regressions more than a century in length. Even then, as the CET record shows, the 120-yr linear trend is not stable.
Given the indication by proxy data (e.g., GISP2) that quasi-millenial oscillations are even stronger than quasi centennial ones, the persistence of all linear “trends” needs to be questioned. It’s best to recognize that such computed trends are mere snapshots of the output of a very crude band-pass filter and move on to more sophisticated low-pass filters to establish the long-term sojourn of highly smoothed temperatures. The discrepancy between strongly urbanizing and stable locations then becomes starkly apparent.
Reducing past temperatures in years prior to the anthropogenic signal simply shows a warming trend with no political value.
There is also a problem with US temperature records.
We have 23 long-service USHCN stations top-rated for their siting away from urban heat source. The raw data shows diversity of climate patterns and a modest average warming trend over the last century.
GHCN adjusted data warms the average station by +0.58 C/Century, from +.18C to +.76C, comparing adjusted to unadjusted records.
19 station records were warmed, 6 of them by more than +1 C/century. 4 stations were cooled, most of the total cooling coming at one station, Tallahassee.
So for this set of stations, the chance of adjustments producing warming is 19/23 or 83%.
Details and supporting excel workbooks are here: https://rclutz.wordpress.com/2015/03/17/adjustments-multiply-warming-at-us-crn1-stations
Just for context, this whole discussion would be purely academic if it weren’t for
this
http://www.dailytelegraph.com.au/news/special-features/the-proof-australia-is-getting-hotter/story-fnknbqfy-1227235090301
and this
http://www.smh.com.au/environment/climate-change/hotter-harder-times-forecast-for-the-farm-as-climate-changes-food-production-20150314-143xai.html
and this
http://www.abc.net.au/pm/content/2013/s3927578.htm
and so on… now would it?
Is this the skeptics fault?
I can’t see how nitpicking one weather station will change the temperature averages and trends much. The BOM may not even be including that station in the climatic averages.
hto,
For those who care about truth in science, several Australian temperature summary summaries from the early 1900s, official documents, allow the inference that the most Australia warmed from the 1880s to year 2010 was 0.4 to 0.5 deg C.
If nobody can argue against this inference, then nobody can argue alarming global warming/GHG episodes in Australia’s written history.
For example, see Chris Gilham’s extensive work at
http://jennifermarohasy.com/wp-content/uploads/2015/02/acorn-review-submission.pdf
I am sure the BOM have their own systems of review. Not really interested in others trying to find fault with the BOMs work so they can post about it on the internet, make accusations and hopefully get media coverage.
“Two conclusions can be drawn from this analysis:
There is a clear heat island effect in central Melbourne that is detectable in the minimum temperature measurements. It may be as much as 0.2 degrees per decade (or 1 degree over 50 years!).”
UHI effects begin when the surrounding environment begins to change and ends when the change has stabilized. The effect occurs over a time span and results in a bias. With out knowing that time span don’t know how it can be characterized as “1 degree over 50 years.” I would think that in many, if not most, instances it would be over a relatively short time period; the measurement is in a cow pasture one day and a year later it is in the middle of a parking lot.
anecdotally.. I listen to the ABC weather forecast about 7.00 each morning (I also live in a suburb of Melbourne.)
The BOM weather bloke some time last year happened to drop that the UHI for Melbourne was about 6C.
I also found some papers a while ago on this subject,
e.g. https://clearwater.asn.au/user-data/resource-
files/Urban_Heat_Island_in_Melbourne2009.pdf
“Simmonds 2000; Torok et al. 2001; Walker 2004) ranging from a mean of around 2 ºC to 4 ºC, with daily peaks as high as 7 ºC, depending on location and time of day and year.
The UHI is particularly important from a human health perspective as high urban temperatures place urban inhabitants under heat stress (especially in combination with heat waves) and the UHI restricts night time recovery from daily heat stress. Research has shown an increase in the numbers of excess deaths (increases of 19–21% over expected death rate) occur when daily minimum temperatures exceed 24°C (Nicholls et al. 2008).”
…
“This paper outlines research conducted in Melbourne aimed at demonstrating the temporal and spatial variability of the UHI across the city and identifying the specific drivers that cause this variability. In particular, research investigated whether the UHI increases with increasing urban density and the role of vegetation cover and pervious surface area (and other surface characteristics) on evapotranspiration and the UHI.
Evapotranspiration is a particular focus as it is influenced by the amount of water in the urban environment – which is partly controlled by stormwater management.”
try this search term “Melbourne UHI study” papers if your interested.
There was another paper I found a while ago that compared Melbourne
to smaller townships (Horsham was one I think).. (sorry can not find that at this time).
Cheers
Jim
Thanks.
Australia has an abundance of weather stations around the country with long temperature records. The BOM ACORN project was supposed to use “high quality” stations to produce an accurate picture of the national and regional temperatures trends. Including stations with obvious high UHI effects clearly does not conform to this. The BOM ACORN network of stations should have included only those stations with long records that have always been and still are rural.
BOM’s adjustment method for UHI is the same as is used in other authorities around the world to report global temperatures and trends. Logically if an urban station with a UHI effect is to be included, either or both of it’s Tmax or Tmin should be adjusted down for the period in which the UHI effect was and is applicable. Conversely what consistently occurs though is that old pre-UHI records, most often Tmin, are adjusted down bizarrely often periodically and cumulatively. Recent records are either not adjusted at all for UHI or adjusted upwards, most often Tmin. Adjusted records are then homogenized resulting in other non-UHI stations being adjusted in a similar fashion to the UHI effect station. The overall effect is to produce or magnify an increasing temperature trend when it may not have been present in the observed non-UHI stations temperature records. Adjusting Tmin is more invisible than adjusting Tmax and there are limits to which recent year Tmax adjustments can go to be completely out of line with other methods and records e.g. satellite.
The consistency of this urban station UHI adjustment in Australia and around the world naturally arouses suspicions of a co-ordinated effort to emphasize a global warming trend. BOM and other temperature record authorities should either reverse and correct the way in which UHI is adjusted, and/or discontinue including any stations with a UHI effect in their regional, national and global temperature calculations.
A pretty good indication of 20th-century UHI development in Melbourne is provided by comparing its time-series of yearly average temperatures with the aggregate average of those at three stations that bracket its location: Cape Otway, Maryborough and Wilsons Promontory. It’s becomes plain as day that over the last century Melbourne has warmed by more than a degree Celsius relative to the surrounding non-urban stations. The more-proximate Laverton Aero station confirms this stark discrepancy, but over a shorter time-interval.
This is very typical of discrepancies world-wide between major cities and non-urban stations, when the latter are available. Particularly striking is the strong divergence in the 1960s and 1970s, when there was world-wide cooling at the same time that large cities were growing rapidly and intensifiyng their UHI.
Alas, in many large regions of the world, there are virtually no century-long records available at non-urban locations. UHI-corrupted records are often illegitimately used as indicators of “regional temperature trends.” Highly inconsistent development of UHI in various cities on various continents prevents any reliable universal correction. Thus “global temperature” indices are edifices constructed on shifting foundations of sand and mud.
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