The Climate Sciences Use Of The Urban Heat Island Effect Is Pathetic And Misleading

By Geoffrey H Sherrington,

Spinal Tap’s Nigel Tufnel demonstrates his hifi speakers are louder because the numbers all go to 11.

https://www.youtube.com/watch?v=KOO5S4vxi0o

Scientific control knobs for climate change have to be used with more care.

ABSTRACT.

The ‘urban heat island’ arises because air temperatures measured in urban cities can be different to those of the rural city surroundings. Thermometers were and still are more often found in cities than surroundings. City temperatures have a synthetic, man-made component that needs to be subtracted to match the surrounding rural temperatures, which are the items of interest for climate studies.

Failure to subtract the UHI effect will lead to false results for temperature trends such as those used to claim global warming. The question arises whether rural and urban temperatures have adequate accuracy to provide reasonable results after the subtraction. This essay argues that historic Australian rural temperature records are unfit for this purpose; that global temperature records are likely to be similarly inadequate; and that as a consequence, all past estimates of UHI derived from land surface temperatures by thermometry are invalid or questionable.

In short, all past estimates of UHI magnitude before the satellite era are incorrect for reasons given. The actual rates of global temperature changes over the past century are likely to be wrong by a significant amount, of similar magnitude to the global warming claimed at about 1°C per century.

More recent estimates are being made with temperatures from instruments on satellites, which help the future path to better understanding.

THE PRELIMINARY PROBLEM.

On present knowledge, three dominant processes affect global surface air temperature estimates.

1. Natural variation

2. Greenhouse gases

3. Measurement inaccuracy, including UHI.

The relative proportions of these are not yet known. In particular, the uncertainty of estimated climate sensitivity to greenhouse gases is large and unchanged by 30 years of intensive research. The UHI effect has the capacity to be as large as the others, but its magnitude is again poorly understood.

Here are excerpts from papers often cited in UHI references.

“In the Summary to CLIMATE, Howard provides a concise statement of the temporal variation of ∆Tu-r and hints at its spatial character:

The Mean Temperature of the Climate … is strictly about 48.50° Fahr.: but in the denser parts of the metropolis, the heat is raised, by the effect of the population and fires, to 50.50°; and it must be proportionately affected in the suburban parts. The excess of the Temperature of the city varies through the year, being least in spring, and greatest in winter; and it belongs, in strictness, to the nights; which average three degrees and seven-tenths warmer than in the country; while the heat of the day, …. falls, on a mean of years, about a third of a degree short of that in the open plain.”

(p.147)

Howard 1833 in The Climate of London by Luke Howard (1833). https://www.researchgate.net/publication/292141041_The_Climate_of_London_by_Luke_Howard_1833

“Temperatures in central London, for instance, are modified by the degree of development of London’s heat-island, a mass of warm air roughly coincident with the city, and this is closely related to wind velocities and cloud amounts as controlled by weather systems and air mass characteristics. Various elements are intricately interwoven in the final climate fabric but pressure, wind speed and direction are perhaps basic controls of London’s urban climate.”

Chandler 1965, page 48 in his book

http://urban-climate.org/documents/TonyChandler_TheClimateOfLondon.pdf

“The paper demonstrates the relationship existing between the size of a village, town or city (as measured by its population), and the magnitude of the urban heat island it produces. This is accomplished by analyzing data gathered by automobile traverses in 10 settlements on the St. Lawrence Lowland, whose populations range from 1000 to 2 million inhabitants. The locations of these settlements effectively eliminate all non-urban climatic influences. The results are compared with previously published data.

“The analysis shows the heat island intensity under cloudless skies to be related to the inverse of the regional windspeed, and the logarithm of the population. A simple model is derived which incorporates these controls. In agreement with an extension of Summers’ model the heat island appears to be approximately proportional to the fourth root of the population. With calm and clear conditions the relation is shown to hold remarkably well for North American settlements, and in a slightly modified form, for European towns and cities.”

Oke, 1967

https://www.sciencedirect.com/science/article/pii/0004698173901406

“For millions of people living in cities, increased temperatures are a growing fact and concern. The urban heat island (UHI) is a phenomenon whereby urban regions experience warmer temperatures than their rural, undeveloped surroundings. The UHI is the most obvious atmospheric modification attributable to urbanization, the most studied of climate effects of cities and an iconic phenomenon of urban climate. It can be found in settlements of all sizes in all climatic regions and arises from the introduction of artificial surfaces characteristic of those of a city that radically alters the aerodynamic, radiative, thermal, and moisture properties in the urban region compared to the natural surroundings. The heat island is defined on the basis of temperature differences between urban and rural stations, and the isotherm patterns of near-surface air temperatures resemble the contours of an island.”

From M. Roth 2013 Handbook of Environmental Fluid Dynamics, Volume Two, Chapter 11, p. 143.

http://profile.nus.edu.sg/fass/geomr/roth%20uhi%20hefd13.pdf

“Urban heat island (UHI) effect is a kind of heat accumulation phenomenon within urban area due to urban construction and human activities. It is recognized as the most evident characteristic of urban climate. The increase of land surface temperature caused by UHI effect will definitely influence material flow and energy flow in urban ecological systems, as well as alter their structure and functions, exerting a series of ecological and environmental effects on urban climates, urban hydrologic situations, soil properties, atmospheric environment, biological habits, material cycles, energy metabolism and residents’ health.”

Yang et al., 2016, in

https://www.sciencedirect.com/science/article/pii/S1877705816332039

“The Urban Heat Island (UHI) effect describes the observation that temperatures in a city are often higher than in its rural surroundings. London was the first urban heat island to be documented but since then many cities have been identified as urban heat islands.”

Wickham et al., 2013, in

https://www.scitechnol.com/2327-4581/2327-4581-1-104.pdf

“Over the 19-year period, daily analyses of the regional climatological 0600 EST temperature data revealed a UHI between −3.16° and 6.0°C. The reanalyses of the NCEP MSLP data, in association with the local area climatological data, suggest that statistically significant anomalous anticyclonic conditions were associated with the warmest 17% and coolest 1% of UHI events. The position of the centre of the anticyclone was critical to UHI genesis and development.”

Morris & Simmonds 2000

https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/1097-0088(200012)20:15%3C1931::AID-JOC578%3E3.0.CO;2-D

The UHI is predominantly a night time phenomenon caused by differential cooling rates between urban and rural areas. From the energy balance study in 2004, results showed that there are large differences in evapotranspiration between urban and rural areas that lead to baseline differences in UHI intensity between the two environments because more energy is partitioned into atmospheric heating and heat storage – driving development of the UHI.

Coutts et al., 2004

https://www.researchgate.net/publication/266267164_The_urban_heat_island_in_Melbourne_drivers_spatial_and_temporal_variability_and_the_vital_role_of_stormwater

[29] A major concern about the accuracy of analyses of global temperature change has long been the fact that many of the stations are located in or near urban areas. Human‐made structures and energy sources can cause a substantial local warming that affects measurements in the urban environment. This local warming must be eliminated to obtain a valid measure of global climate change. Global temperature analyses now routinely either omit urban stations or adjust their long‐term trends to try to eliminate or minimize the urban effect. A comprehensive review of the topic is provided by Parker [2010].

[30] The urban influence on long‐term global temperature change is generally found to be small. It is possible that the overall small urban effect is, in part, a consequence of partial cancellation of urban warming and urban cooling effects. A significant urban cooling can occur, for example, if a station is moved from central city to an airport and if the new station continues to be reported with the same station number and is not treated properly as a separate station in the global analysis

Hansen et al., 2010

https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2010RG000345

Comments:

These excerpts note sixteen factors involved in UHI. They are population density, fires, seasons, day or night, degree of city development, wind velocities, wind directions, cloud amounts, artificial surfaces, moisture, urban hydrology, storm water, soil properties, time of day of observation, anticyclones, evapotranspiration, weather station relocation.

One customary method for treatment of data like these is a form of multivariate analysis such as multiple linear regression. Measured values of each factor are input to calculations showing the percent of the variability explained by each in a statistical sense. Historic data do not have this extent of metadata for most factors, so the method cannot be used. It does not seem to have been attempted with modern cities.

By default, researchers have selected one or a few of the variables for study, often for a very small number of cities. Some have derived relationships, such as UHI with population by its 4th root, by Oke, 1967. These studies are of limited use because of the lack of treatment of other variables.

None of the cited papers has any serious attempt at estimation of uncertainty of results.

The present situation is one of large, continuing lack of research attention. There is not even a detailed description of how large the UHI effect is, using a representative set of city examples, let alone its uncertainty.

This is an intolerable situation because of the possibility of the magnitude being similar to, even greater than, natural variability and greenhouse gas effects.

HISTORIC MEASUREMENTS.

Most historic temperature records now available for UHI research are from liquid-in-glass thermometers in Stevenson screens, with daily reporting of maxima and minima reached at some unknown time in the 24 hours of a day. These records lack the density of information needed to dissect out the main perturbation effects on UHI. They do not contain the information required to show that

(a) the city thermometer was situated at a designated heat location in the UHI bubble, such as maximum

(b) there was or was not a UHI signal at the (unknown) time that Tmax and Tmin were recorded

(c) there was or was not wind at the time of the UHI maximum or minimum

(d) there was or was not rainfall at the time of the UHI maximum or minimum

(e) the rural thermometer was unaffected by the heat island, including by wind from it, or by being within the bubble

(f) Either or both the city and rural thermometers recorded the temperature with adequate accuracy after accounting for errors

It is here asserted that these impediments are adequately severe to make modern efforts to correct for UHI pointless. There is no way known to discern even if a correction will make the UHI error better or worse. (Most adjustment schemes assume a warming UHI, but a cooling UHI is not uncommon.)

AUSTRALIA

Melbourne, as well as Australia in general, has been the locus of many publications about Urban Heat Island effects. The references in this paper by Morris and Simmonds of the University of Melbourne show some of the scope of research until 2000.

https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/1097-0088(200012)20:15%3C1931::AID-JOC578%3E3.0.CO;2-D

There is abundant evidence that UHI exists. It is beyond reasonable doubt. UHI has had much discussion because it changes the temperatures within cities compared those of the city surroundings and the large unsettled areas beyond. Many weather station sites are within cities. Their thermometers are assumed to be contributing a non-climate effect to the climatic temperature record of the surrounding areas for which a temperature is sought. The UHI effect needs to be quantified and subtracted from the record, station by station, if one is to avoid synthetic heat contamination.

Australia’s Bureau of Meteorology (BOM) has noted that “ … data show that Australia has warmed by approximately one degree since 1910. The warming has occurred mostly since 1950.” See “Climate Trends” in

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

The BOM treatment of UHI for its favoured ACORN-SAT temperature collection is stated here:

http://www.bom.gov.au/climate/change/acorn-sat/documents/ACORN-SAT_TAF_Short_FAQ.pdf

(Start of quote). 14. How does the urban heat island effect impact the climate data? The urban heat island effect can increase surface air temperature at urban locations. While studies have found the effect has minimal impact on global long-term temperature trends, urban sites are not included in the Bureau’s assessments of temperature trends across Australia. (End of quote).

That presumes that the BOM has a workable method to distinguish urban from rural sites.

For reasons like this and others, many estimates of UHI are plausibly inaccurate and difficult to put into proper context, but annualized UHI estimates are in the same range of up to 1° C as the century of alleged global warming for Australia. This would mean that the whole of the BOM warming estimate could be caused by errors in UHI correction methodology, if used.

An error of this magnitude, if proven, would have a significant effect on national policies to deal with global warming.

SOME AUSTRALIAN FACTORS.

1. The BOM has created and maintained a historic temperature record of commendable quality. It is a major part of instrumental reconstructions of the climate history of the Southern Hemisphere since roughly the 1880s.

2. Australia is a large country with an area of some 7.7 million km², similar to that of the contiguous USA. This allows testing of UHI effects under a variety of natural climates.

3. The population of Australia is about 25 million, with most grouped into the 6 main capital cities, including Melbourne (5 million). Opportunities exist to study weather stations both close to and remote from human influence.

4. Since about 1800, there has been one dominant language, English, plus one dominant heritage for the conduct of science and cultural news, again English. Therefore, historic records are consistent with each other compared (say) to a similar area of Europe, where even a simple concept like Brexit becomes complicated.

5. Until about year 2000, the study of Australian climate was largely by clean science. As global warming advocacy became widespread, the standard of overall science fell away. However, the raw records to 2000 appear to have been kept pure. Here, I use only raw records from the BOM.

6. Australians were among the earliest involved in UHI research.

EARLY AUSTRALIAN WORK ON UHI.

UHI is seldom the primary target in early temperature/climate papers, which tend to stress temperature measurement uncertainties. See for example, this 1996 work from the Ph.D. thesis of Simon Torok.

https://minerva-access.unimelb.edu.au/handle/11343/39449

http://www.geoffstuff.com/torok_excuses.doc

Around late 2004, a geologist colleague, Warwick Hughes, received an email from Professor Phil Jones of University of East Anglia, an email that has had numerous subsequent citations.

“Why should I make the data available to you, when your aim is to try and find something wrong with it.”

This quote is both a lead-in to the history of UHI in Australia and my involvement in it. You are encouraged to read the 12-page essay that I wrote about it, because it is now part of the relevant history of global warming including UHI – and it releases me from repeating myself here.

http://www.geoffstuff.com/hughes_famous_email_explained.pdf

In essence, Prof Jones selected 25 “Regional and Remote” weather stations in Australia that he seems to have thought would be free of UHI. He compared their historic temperature averages with those of 6 capital cities. By subtraction, he found that UHI was negligible. Warwick Hughes asserted that the 25 control stations did have their own significant UHI and that the subtraction of temperature averages done by Jones was misguided through wrong assumptions. Jones, at the same time, found negligible effects in China and other places. These are 2 of the key papers by Jones et al.

https://journals.ametsoc.org/doi/abs/10.1175/1520-0450%281986%29025%3C0161%3ANHSATV%3E2.0.CO%3B2

P. D. Jones, S. C. B. Raper, R. S. Bradley, H. F. Diaz, P. M. Kellyo, and T. M. L. Wigley,1986. Northern Hemisphere.

https://journals.ametsoc.org/doi/abs/10.1175/1520-0450%281986%29025%3C1213%3ASHSATV%3E2.0.CO%3B2

P. D. Jones, S. C. B. Raper, and T. M. L. Wigley, 1986 (Does not mention Australia).Southern Hemisphere.

Hughes tried to get opposing views published, but was met with opposition. Some work was published, but not in a high-impact journal.

In these early years there was a BOM draft Paper,  M.J. Coughlan, R. Tapp and W.R. Kininmonth;   1990, “Trends in Australian Temperature Records” by three senior BoM staff. They calculated UHI magnitudes by various comparisons between central city sites in the Australian state capitals and their respective airports. The BoM found substantial urban warming, greater than the scale of global warming. Here are some numbers and passages from their paper, slightly modified for smaller format.

(Start of quote) 6. Summary and Conclusions.

Trends which have occurred in urban-rural differences of maximum and minimum temperature at each of six large Australian coastal cities over the past 25 to 45 years indicate that temperatures at the urban sites are being affected by …….. (copy unclear) in their vicinity. These trends were least at the smallest of the cities examined in this study, Hobart. A limited examination revealed no consistent variations of HII by season which were common to all cities which necessarily remained constant in time at individual cities.

Table 2: Estimated linear trends (C decade¯¹) in the difference between annual average temperatures at urban sites relative to adjacent non-urban or outer urban sites in Australia. Trends are for the total period of available data.

Minima Maxima

Adelaide +0.13 (1956-78) -0.39 (1940-74)

-0.30 (1978-87) +0.72 (1974-87)

Brisbane +0.06 (1950-85) +0.29 (1950-85)

Hobart -0.0 (1958-87) -0.07 (1958-87)

Melbourne -0.31 (1945-87) – 0.16 (1945-87)

Perth +0.15 (1945-87) +0.10 (1945-87)

Sydney +0.38 (1940-87) +0.08 (1940-87)

The most rapid minima increase, of approximately +0.4 C decade¯¹ was recorded at Sydney. The relationships between city size and HII for maxima were much weaker. Overall trends in the urban-rural differences in maxima ranged between approximately +0.29 C decade¯¹ at Brisbane and -0.16 C decade¯¹ at Melbourne. (End of quote).

The emphasis here on the BOM draft by Coughlan eta al. is deliberate. In 1990, this BOM finding suggested that UHI was a strong factor, one for detailed further examination. The work of Jones et al. in the 1980-2000 era, referenced above, was to the contrary. The Establishment science community backed the Jones interpretation, based as it was on unsuitable data. After, there was a concerted effort globally to try to stuff the UHI problem under the table, to say in public that it was tiny, to represent anthropogenic global warming as 1°C over the century studied, when more accurately it could well be less than half of that.

MY LATER AUSTRALIAN STUDIES.

Around 2010, the UHI literature was simply confusing. There were many papers treating UHI correction as a fait accompli. Most relied on customary subtraction of rural temperatures from nearby city temperatures. Many were deficient in their treatment of error estimates.

About May 2007 I started to work on ‘pristine’ Australian sites. This was prompted by Steven Mosher who was associated with the Berkeley team that has produced the global BEST temperature data set. Mosher had sent me a spreadsheet with his choice of about 157 Australian stations that might be away from the hand of Man. About this time a disc crash on my PC obliterated both the primary Mosher spreadsheet and my detailed response to it. Mosher advises that his set was also lost. An intermediate spread sheet is still on my files, but it does not have much value.

http://www.geoffstuff.com/Pristine_157.xls

I had added a lot of detail to this early spreadsheet, such as Census population counts at several Census years, distance from the ocean, distance to nearest sign of habitation on Google Earth scenes of various vintage. While doing this work, the abundance of missing temperature data allowed me to narrow down the pristine search to 44 better-quality sites, a few of which received highly subjective infills of missing data that I inserted for easy subsequent spreadsheet manipulation. (The infills for some stations, e.g. Eucla, are capable of altering the outcome in a significant way.)

 

THE SPREADSHEET THAT MATTERS.

In February 2015 I produced the 44 station ‘pristine’ spreadsheet of Australian sites, with temperature records from 1972 to 2006 included (35 years). Metrication from F to C started in 1972; and the BOM data available to me in easy form ended in March, 2007, thus setting the end years of the study. This is the spreadsheet that matters for this essay.

http://www.geoffstuff.com/pristine_44_2018.xls

The simple analysis was done by fitting a linear time regression through the annual averages of both Tmax and Tmin. The slope of the line was converted, for ease of comparison with other papers, to the change in temperature per century. This is a conventional form of analysis that I dislike for a number of reasons, but many other people were doing it, so I used it for compatibility.

The 2 graphs below are of one site chosen from the 44 to show the representation method.

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http://www.geoffstuff.com/maats.JPG

These two graphs show temperature trends of -1.5 C for Tmax and -0.9 C for Tmin, so these are examples of urban cooling if the data are accurate. Overall, 6 of the 44 examined stations have cooling Tmax trends and 14 out of 44 have cooling Tmin trends. This is difficult to interpret in terms of UHI effects. One must assume that there are no UHI influences at work, but the variability of temperature trends is high, from station to station.

DISCUSSION ABOUT THE SPREADSHEET THAT MATTERS.

1. The dominant conclusion is that the historic temperature data as available are not fit for the purpose. Weather stations were designed and sited for purposes quite different to the demands now placed on them to correct for UHI.

2. Consequently, there is little point in taking analysis any further.

3. It follows that historic data from other countries, which can be assumed to be broadly similar to Australia’s are also unfit for the purpose of researching or correcting the Urban Heat Island effect.

4. The primary concern is that the signal:noise ratio of ‘pristine’ sites is too small. Maybe, quality decreases with absence of the hand of Man for maintenance and quality control.

5. While one can fit a regression to show the change of temperature with time, here named the slope – and one can chart the slope versus other variables such as latitude and altitude, the high noise level prevents a useful analysis. This is shown in a comical way by use of the World Meteorological Organization numbers of the weather stations, which show a distinct trend with the slopes at the 44 stations. I know of no theory to predict this correlation. It is highly likely to be due to noise and if so, it must be nonsensical.

6. Therefore the remainder of the graphs should to be treated as nonsensical.

7. Other papers such as Oke, 1967 and Parker, 2010 (refs. cit.)have obtained a correlation of UHI magnitude with surrounding population numbers, then others like GISS (ref.cit.) have included this observation into their adjustment schemes. An interesting question is, should the WMO number also be included in adjustment schemes for Australia?

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http://www.geoffstuff.com/wmo.JPG

SEVERITY OF THE UHI EFFECT.

Wickham et al, 2007 give some indications of severity –

https://www.scitechnol.com/2327-4581/2327-4581-1-104.pdf

First, on the severity of the problem of more thermometers in cities than in rural surroundings, they note that “Urban areas are heavily overrepresented in the siting of temperature stations: less than 1% of the globe is urban but 27% of the Global Historical Climatology Network Monthly (GHCN-M) stations are located in cities with a population greater than 50,000.”

Then, on the severity of the UHI temperature magnitude –

(Start quote) The Urban Heat Island (UHI) effect describes the observation that temperatures in a city are often higher than in its rural surroundings … A well-known example is Tokyo where the temperature has risen much more rapidly in the city than in nearby rural areas: Fujibe estimates excess warming of almost 2°C/100yr compared to the rest of Japan. The warming of Tokyo is dramatic when compared to a global average as seen in Figure 1.

clip_image009(End quote)

http://www.geoffstuff.com/magnit.JPG

From the satellite based work of Youn-Young Choi et al. there are time-of-day effects that make Seoul, Korea seem some 8°C hotter than its surroundings and Tokyo about 10°C hotter, as the largest of the observed effects. On the diagram, different hours of the day are in different line colours, witrh hours 1200 and 1300 showing the greatest heating.

To my knowledge, no routine scheme for correcting UHI copes with corrections of this magnitude.

https://pdfs.semanticscholar.org/6593/0b0b47159b3088ac72ef582f6ee1dd1f0782.pdf

clip_image011

http://www.geoffstuff.com/seoultokyo.JPG

SOME CONSEQUENCES.

There is a real UHI effect. It is large enough in some cases studied to influence century-long estimates of global warming. There is no current way to estimate the global consequences of the UHI effect. There is a small but finite probability that most global warming estimates were mainly estimates of UHI effects.

Current large-scale numeric processing of country data to remove UHI effects are not based on solid science. They are based on very little demonstrated science, more on wishful thinking and sweeping guesswork. For these methods to succeed, historic temperatures would need subtraction of the ‘rural’ UHI effect after full quantification of possible perturbing variables, such as those listed above

in the numbered block starting “1. How far from a thermometer does a synthetic heat source have to be … “ One then realises that there is no possible answer to some of the questions. Even the simple question of where in the heat bubble the temperature was taken cannot now be answered because the conditions cannot be re-created. There is far from adequate detailed metadata.

There have been some papers that note many of the points that I have raised here. A good example is the 2013 paper by Hausfather et https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2012JD018509

The major difference between Hausfather’s work and mine is that Hausfather makes assumptions that cannot be verified because critical parameters were never measured. Also, there are no tests to show that Hausfather’s ‘rural’ sites have historic data of adequate quality to allow their classification and use. They do not have adequate quality, in these Australian examples. It would be difficult to find sites anywhere that are more isolated from Man than these in Australia. When one graphs the temperature trend from annual data over time, the software is always going to find a line of best fit. That line can, in ideal cases, lead to the establishment of quantified causation. In these Australian examples, it does not. It is merely the mathematical line of best fit by the least squares method.

There are sites that are very likely free of UHI effects. One is remote Macquarie Island in the Southern Ocean, with an Automatic Weather Station maintained by Australia’s BOM. Here are the trends over the last 50 years for Tmax and Tmin. (Note: These BOM data start in year 1949, but I have cherry picked the last 50 years to show how little deviation and how little trend there is. As Rosanne D’Arrigo said to the US Congress, “That you had to pick cherries if you want to make cherry pie.”)

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This Macquarie Island graph is shown to suggest that there might be some weather station sites that do not appear to show UHI and are thus candidates for ‘pristine’ status, suitable for subtraction from nearby city sites. The standard deviation of the data is far smaller than for the Australian sites, about 0.38 versus typically 0.3 to 1.0 for Australian sites analysed here. http://www.geoffstuff.com/macq.jpg

Scientific inquiry might better be directed towards explaining why Macquarie Island has such a low temperature trend, rather than selecting sites elsewhere with high temperature trends and subtracting from them using numbers that have a high guesswork component.

SOME DETAILS OF CURRENT UHI ADJUSTMENT METHODOLOGY.

The following extracts from the given references provide a guide to current thinking and practice.

“Step 2: Urban Adjustment. (Short records are discarded). Stations identified as urban, using values obtained from satellite measurements of nighttime brightness, have their trend adjusted to match the trend of a composite record made from nearby rural stations. At least 2/3 of the adjusted period must have 3 rural stations contributing to the composite record. Periods and stations that do not have sufficient support from rural stations are dropped. The composite rural record is made from rural stations within 500 km, or 1000 km if necessary to meet the above requirement. This step is documented in

Hansen et al 1999 (the basic scheme),

Hansen et al 2001 (allowing the break point in a two leg fit to vary in time), and

Hansen et al 2010 (the use of satellite nightlights).”

https://data.giss.nasa.gov/gistemp/sources_v3/gistemp.html

“[12] GISS analyses beginning with Hansen et al. [1999] include a homogeneity adjustment to minimize local (nonclimatic) anthropogenic effects on measured temperature change. Such effects are usually largest in urban locations where buildings and energy use often cause a warming bias. Local anthropogenic cooling can also occur, for example, from irrigation and planting of vegetation [Oke, 1989], but on average, these effects are probably outweighed by urban warming. The homogeneity adjustment procedure [Hansen et al., 1999, Figure 3] changes the long‐term temperature trend of an urban station to make it agree with the mean trend of nearby rural stations. The effect of this adjustment on global temperature change was found to be small, less than 0.1°C for the past century. Discrimination between urban and rural areas was based on the population of the city associated with the meteorological station. Location of stations relative to population centers varies, however, so in the present paper we use the intensity of high‐resolution satellite night light measurements to specify which stations are in population centers and which stations should be relatively free of urban influence.”

Hansen et al 2010 (the use of satellite nightlights).

https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2010RG000345

“Urban heat islands are a result of the physical properties of buildings and other structures, and the emission of heat by human activities. They are most pronounced on clear, calm nights; their strength depends also on the background geography and climate, and there are often cool islands in parks and less‐developed areas. Some old city centers no longer show warming trends relative to rural neighbourhoods, because urban development has stabilised. This article reviews the effects that urban heat islands may have on estimates of global near‐surface temperature trends. These effects have been reduced by avoiding or adjusting urban temperature measurements. “

Parker, 2010

https://onlinelibrary.wiley.com/doi/abs/10.1002/wcc.21

“[29] A major concern about the accuracy of analyses of global temperature change has long been the fact that many of the stations are located in or near urban areas. Human‐made structures and energy sources can cause a substantial local warming that affects measurements in the urban environment. This local warming must be eliminated to obtain a valid measure of global climate change. Global temperature analyses now routinely either omit urban stations or adjust their long‐term trends to try to eliminate or minimize the urban effect. A comprehensive review of the topic is provided by Parker [2010].

“[30] The urban influence on long‐term global temperature change is generally found to be small. It is possible that the overall small urban effect is, in part, a consequence of partial cancellation of urban warming and urban cooling effects. A significant urban cooling can occur, for example, if a station is moved from central city to an airport and if the new station continues to be reported with the same station number and is not treated properly as a separate station in the global analysis.”

Hansen et al., 2010

https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2010RG000345

GISS Homogenization (Urban Adjustment)

One of the improvements — introduced in 1998 — was the implementation of a method to address the problem of urban warming: The urban and peri-urban (i.e., other than rural) stations are adjusted so that their long-term trend matches that of the mean of neighboring rural stations. Urban stations without nearby rural stations are dropped. This preserves local short-term variability without affecting long term trends. Originally, the classification of stations was based on population size near that station; the current analysis uses satellite-observed night lights to determine which stations are located in urban and peri-urban areas.

https://data.giss.nasa.gov/gistemp/

WHAT OF THE FUTURE?

Readers are strongly encouraged to read the 1965 book “The Climate of London” by Tony Chandler referenced at the start of this essay. Between then and now there has been a change in the way that Science is done. Chandler’s work is observation, measurement, then deduction. He describes the construction of weather stations designed to start quantification of the spatio-temporal variables that affect London’s climate. After you read his book, you might conclude that this type of measurement work is lacking in modern times and that many problems would be solved if this approach had been executed at many city locations around the globe.

In the 50 years after Chandler’s book, UHI climate Science has largely changed to “define a social objective, then define ways to support it with Science that is convenient, that is, by the use of assumptions and guesses when measurements are lacking”. (I call this ‘assumption science’.)

Assumption science for UHI has produced a series of deceptions. How can scientists state that “The effect of this adjustment on global temperature change was found to be small, less than 0.1°C for the past century” as James Hansen et al. did in 2010, when this essay has examples of warming of city centres like Tokyo, Seoul and Beijing by 8 to 10°C? Can one believe that the present GISS adjustment for UHI copes with this? If it fails to cope with this, how much more is wrong before finally, the adjustment moves into examples which might be plausible?

A UHI effect of ‘less than 1°C averaged globally’ is not the appropriate metric to express that all is well, though James Hansen maintained it was. Where are the uncertainty estimates?

There can be no significant advancement in understanding of UHI until many more locations are either fitted out with ground instruments or studies with satellite temperatures, to see at least what the variation between sites is really like. All of the correction schemes to data rely on subtraction of rural from urban temperatures, but there is no proven way to distinguish between urban and rural.

I have attempted to reinforce this missing factor by questioning whether existing data are accurate enough to even classify a site as urban or rural and I find that in Australia, the data are not accurate enough.

Even the simple observation that in historic data, the precise past location of the thermometer relative to the (unknown shape and size of the) alleged heat bubble is enough to warn of the likelihood of very large errors. How can a scientist construct an ‘average’ rural site when there is a lack of historic information to do this, let alone accurate information?

In conclusion, one has to admit that the present UHI correction procedures are ‘junk science’ – but with huge price tags attached for being wrong. Some have seen through the deceptions of assumption science – here is but one reference expressing disquiet.

“Local land surface modification and variations in data quality affect temperature trends in surface‐measured data …  Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.”

McKitrick & Michaels 2007

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007JD008465

(END)

Geoffrey H Sherrington

Scientist.

Melbourne, Australia.

17th December, 2018.

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121 thoughts on “The Climate Sciences Use Of The Urban Heat Island Effect Is Pathetic And Misleading

  1. So much to read here…I will get to it later. But hat Macquarie Island chart is rather interesting. The tmin especially.

  2. “Tokyo about 10°C hotter, …….
    To my knowledge, no routine scheme for correcting UHI copes with corrections of this magnitude.”

    …but according to Mosh…the adjustments lower the temperature

    Oh course they do….when UHI increases temps 10 degrees…and you only adjust down 2 degrees
    …it’s a twofur…

  3. Mike,
    Yes, it is long because it is a review plus a history plus a lesson. Make sure to bookmark, because it is meant as a future GoTo reference. Geoff.

  4. Excellent detail and addressing the issues.
    Any analysis addressing whether roads were predominently made of asphalt (tar) or concrete?

  5. If I want to fly to Boston, my luggage gets a tag with BOS. seems reasonable.
    If I fly to Miami, my luggage gets tagged MIA, reasonable again. And if my luggage gets lost as often happens there, I take comfort that it is properly tagged as Missing In Action. Very practical.
    If I fly to O’Hare International in Chicago, my luggage gets tagged ORD. What is up with that!!!!!
    ORD stands for Orchard (!). O’Hare used to be a peach orchard. The first takeoff and landing strip was cut right between the trees, back in the days of cloth covered biplanes.

    Many of our long term temperature records have nothing to do with Global Warming, but instead are accurate records of the development of Commercial Aviation in the 20th century.
    Fit for purpose???? Depends on the purpose, I suppose.

    • When I was a kid, the city of Chicago’s “official temperatures” used to be taken by weather instruments located at Midway Airport, starting when Midway was the hub of Chicago’s air traffic in mid-WWII. Chicago’s “official temperature” station was relocated out to O’Hare (ORD) in 1980. Between 1960 until roughly 1975, I lived in the western suburbs midway between Chicago and O’Hare… in summer it was always cooler near the lake, than in our area out west away from Lake Michigan, toward O’Hare. Prior to 1942 (when Midway and then 1980 when O’Hare became the official weather stations), Chicago’s weather measurements were taken at several sites much closer to the lake front, where temperatures would typically be cooler yet.

      • I have always suspected that the Urban Heat Island effect was way more than the one or two degrees recognized by the Church of Anthropomorphic Global Warming, and closer to the +10C cited for Tokyo.

        I live on the west side of O’Hare in Elk Grove Village, which is home to the world’s largest industrial park. It’s many square miles of almost continuous pavement, concrete, and building roofing located just west of the airport is upwind of O’hare due to the prevailing westerly winds and has to preheat the local atmosphere before it even gets to the official thermometer at the center of the airport’s miles of concrete.

        For almost a decade earlier in this century, I raced bicycles on the local amateur circuit and in the UCI sanctioned Tour of Elk Grove. Training for this level of competition was a +10,000 km (6,200 mi) / year habit, so we would spend 10-15 hours a week outside riding a few hundred miles on the local roads and the bike path loop in the Busse Woods / Ned Brown forest preserve. Members of our local racing clubs met at the bike shop on Thursday nights in the spring and summer for Interval Training, where we would ride the few miles east towards O’Hare to the edge of the Industrial Park to take advantage of the peculiarities of Tonne Road. Tonne offered a straight section of constant slope, first 2 degrees down, then two degrees up, which was perfect for three to five minute intervals of negative splits at peak power output with speeds in excess of 50 kph / 30 mph the whole way. Repeat 10 to 15 times, and then go home. A fabulous eye-watering heart-pounding “learn to handle the bike at race speeds” workout, but I digress.

        When the Intervals were done, we would ride the few miles west to the forest preserve for a few cool down laps on the 7 mile bike path loop. A few of us typically also rode at least one loop as a warm-up lap before heading over for the intervals, so the riding venues for us sequentially each Thursday night were Busse Woods, residential Elk Grove, the industrial park, residential Elk Grove, and Busse Woods. Late into the evening, everybody noticed that Busse Woods was noticeably cooler than the residential streets, and that the residential streets were noticeably cooler than the industrial park, to the point that most of us carried riding vests stuffed into a jersey pocket to prevent chills during the cool down lap, sometimes even in July and August.

        Back when the airport was still named Orchard, the land that was to eventually become O’Hare and the Village of Elk Grove was all farmland, woodland, and lakes. The Busse Woods forest preserve has PRESERVED that environment like a time capsule. So the riding we did for Thursday night interval training was effectively riding through time, from the 1930s in Busse Woods, through the 1960s in residential Elk Grove, and the 1990’s in the industrial park. The constant need for a riding vest in the forest preserve says it is noticeably cooler in the 1950s, and for hard core matched-kit-wearing racers to adjust their clothing means that temperature swing was more than 10F.

        Speaking of time travel, I see later down in this thread that Mr Mosher argues about people confusing micro climate with Urban Heat Island effect, and that the rates of warming will be the same between micro sites. The point of the UHI effect is that over time the thermometer has actually been moved to a new micro climate site even though it is still mounted in the same physical location. Orchard field had the micro climate of today’s Busse Woods. Modern O’Hare field has the micro climate of the industrial park. Over time, that time-based change in venue for the location-fixed thermometer supports a noticeable increase in the temperature record.

  6. “About May 2007 I started to work on ‘pristine’ Australian sites. This was prompted by Steven Mosher who was associated with the Berkeley team that has produced the global BEST temperature data set. Mosher had sent me a spreadsheet with his choice of about 157 Australian stations that might be away from the hand of Man. About this time a disc crash on my PC obliterated both the primary Mosher spreadsheet and my detailed response to it. Mosher advises that his set was also lost. An intermediate spread sheet is still on my files, but it does not have much value.”

    BEST wasnt formed at this time. I joined them in 2012.
    The data I sent you was pre BEST.

    But I was finally able to find the data. I sent it to you in 2010. not 2007.

    I have sent it to you again 1 minute ago

    Here is the mail from dec 22 2010.

    I’v invited you to a google fusion table of australian data.
    [redacted]
    ( and a few small islands throw in)

    The metadata is a concatination of

    GHCN
    WMO
    My own

    Id Lat Lon Altitude Name GridEl Rural Population Topography Vegetation Coastal DistanceToCoast Airport DistanceToTown NDVI Light_Code WmoName WmoLon WmoLat GhcnDistance NameMatch GhcnLon GhcnLat Lon Lat LandWater LandOcean CoastDistance Lights LightsF16 Bright3km Bright5km Bright10km Bright20km Isa GpwDensity GDensity Pop1850 Pop1860 Pop1870 Pop1880 Pop1890 Pop1900 Pop1910 Pop1920 Pop1930 Pop1940 Pop1950 Pop1960 Pop1970 Pop1980 Pop1990 Pop2000 GrumpUrban

    If you dont get the mail ping me. I have re downloaded the file from google fusion tables.
    They will be deprecated soon.

    • Hi Steven,
      Many thanks for the spreadsheet you emailed me about historic Australian site data.
      It is not the same as the one I was referring to, it is better because it has had a lot more work added to it in columns of populations, for example. If that is your effort, I am grateful for it.
      I am so relieved to receive it because now I will do more analysis of the historic Australian data wrt UHI.
      My apologies for my fuzzy memories on dates re BEST etc. You are quite correct.

      You might have gathered that my primary thrust is to get the most-probably-correct results from analysis of the reams of data on UHI globally. Personally, I am rather unkeen on name calling and side issues when a lot of importance is still to be uncovered about UHI, but from some public statements like the GISS ones quoted in my essay, people might be soothed into thinking it was a non-issue and that nothing was found. The UK Met Office, for example, went through a phase of saying words like “while we recognize the potential for large UHI errors, we are not going to change our estimates, but we will put larger numbers on our estimates of uncertainty.” I do not know if that is still their current position.
      It is the validity of the science that interests me and I know you as well, so I hope was can continue to work together to sort it all a bit better. Geoff.

      • Dont forget I got started because I did not like hansens approach to UHI.
        Thats why I asked for his code.

        Since 2010 I’ve come a long ways on metadata so there is more beyond what I gave you then.

        I can probably work something up for you based on.

        GHCN v4 for australia
        BEST for Aus.

        Here is the issue however:

        Say we start with a definition of urban as X. ( either a categorical defnition or continous one)

        We split the data and find out that urban and rural are not hugely different. Opps

        Someone will suggest X` as a definition
        Then X“
        Then X“`
        etc.

        At some point folks will start to argue for micro site and confuse that with UHI
        In all of this nobody ( except me) will note the actual real world existence of
        urban cool islands. heck in Seoul we construct them.

        In any case, data is data and folks should base their arguments on data and not just
        their own personal experience

        also be careful with all UHI studies in support of green cities they are designed to
        shown huge values

        • Mosher

          As Dale Quattrochi has demonstrated, weather is modified downwind of major cities such as Atlanta. So, any comparison of rural versus urban should take into account, at the very minimum, the prevailing wind direction, and preferably the wind direction and speed for the particular temperature recordings. I can envision a situation where upwind from a city, the wind will be ‘cool.’ It will be warmed as it passes over and through the city, and produce a warmed plume for several miles downwind. So, it isn’t sufficient to just compare urban with rural.

          • “As Dale Quattrochi has demonstrated, weather is modified downwind of major cities such as Atlanta. ”

            The best study is Birmingham.
            It’s unwise to generalize from these types of studies or ignore them.

            Most of dale’s work is with SUHI, do you have a particular study in mind

          • Mosher
            it was about 15 years ago that I read the particular study I was thinking of, and I think it focused on Atlanta.

        • “… as they are DESIGNED to show huge values.”

          planners manipulate the data?
          paid professionals (essentially) lie?
          administrators with an agenda are too ignorant/gullible to see the manipulations?
          are all of them coordinating together?
          just doesn’t make sense, why would all of them be misleading the public like that?
          how could all this be kept secrete?

          Conspiracies all around.

          right?

        • Steven,

          Now that this post is done and dusted, I am ruminating on some lessons from the exercise.
          One is that WUWT readers are more inclined these days to echo chamber than to chip in with useful new observations. That’s life, it is hard to control that, but the early WUWT days were far more scientific.
          Another is that few people responding, apart from you, thought about the problems of UHI in any great depth.
          But mainly, which scientific studies of UHI should be top of the next list of things to do?
          A small one is to see how ragged the data are at sites previously designated rural or pristine by one classification or another. I have looked mainly at Australian rural sites, could do with sites from other countries. Remember part of my thesis is that most historic LIG data is not fit for UHI purpose. That is not being emotional or critical, it is the way that life at weather stations turned out to be and we have what it delivered. Maybe I need more definitive statistical methods to express that.
          Then, there must be, as a high priority, an examination of present GISS & BOM & Hadley methods of compensating, because they are simply junk or bypassed for reasons that need public amplification. Their authors need to be told to take them back to the lawmakers to withdraw any past policy based on them and a correct treatment devised.
          I cannot understand why so many scientists prefer dishonest ‘say nothing to anybody’ approaches to UHI data when they must know how shonky it is how large the consequences of staying quiet are.
          Geoff.

    • Hi Steven;
      Thank you for your work in this area.

      Are we to understand that you found the original FULL dataset of the 157 pristine locations that was thought to be lost?

  7. ‘“Local land surface modification and variations in data quality affect temperature trends in surface‐measured data … Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.”

    McKitrick & Michaels 2007

    https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007JD008465

    Not sure you guys want to hang your hat on this one or the approach”

    Let me know, and then I will tell you what a deep dive into the data showed.

    • Steven,
      This McKitrick & Michaels paper gained a moderate volume of rebuttal type printed words and blog comments. Having read, I think, the essence of these before I wrote this essay, you might note that I am continuing in my efforts to have it read and understood.It is a somewhat original approach with potential for more detailed use and as such should be welcomed. I did not meet a criticism of it able to show it was wrong. Cheers Geoff

  8. Geoff, Great work ! I am still digesting it all.
    I have lived in the Adelaide Hills since 2000. Below is what I have just finished writing on the Heat Island effect for Mt Barker in the Adelaide Hills. But note the Murray Bridge BOM data which I demonstrates a heat island effect conclusively.
    It would be nice to get your thoughts on it. My email is bhankinATadam.com.au

    IS THE CLIMATE OF THE ADELAIDE HILLS GETTING WARMER ?
    By Bill Hankin

    Recently I have focussed my attention of Climate. There is a theory that the Climate is warming because of humans burning fossil fuels and increasing the amount of CO2 in the atmosphere.

    I wonder how this scientific hypothesis stands up in the Adelaide Hills.

    Let’s get ‘local’ with all this Climate Warming stuff !

    I live in Mt Barker. I have lived in the Hills since 2000 – 18 years. And as an organic farmer I’m always interested in the weather. I have kept rainfall readings for the places I have lived since 1986.

    Why ? Because I’m interested in this sort of stuff. And farmers who don’t keep informed on the weather go bust.

    So recently I’ve been studying the Mt Barker weather as recorded by the Australian Bureau of Meteorology. The BOM actually has a huge wealth of data recorded and all accessible via it’s website. And the data for Mt Barker almost the best & available for the longest period in SA from 1861 to 2018.

    Mind you, for the Mt Barker record, there are some problems :
    1: Gaps in the Records :There are NO temperature records from 1887 to 1925. Why ? I have no idea. But that 38 year gap in the 156 year record is a big gap.
    2: “Heat Island effect’ : I happen to know where the BOM equipment site is in Mt. Barker. It’s right in the heart of town close to “The Courier” building. And in the 156 years since records were first started, Mt Barker has grown enormously. In 1861 there were just a couple of hundred people living here. Now there are about 20,000 people living in Mt Barker. When that happens very often a “Heat Island” effect happens. In Winter we burn heating oil, wood, gas or electricity to stay warm. All that heat by 20,000 people warms things up ‘outside’ a little as well. In Summer we have our A/c’s going, plus fans. And all the time there are the exhaust gasses of our cars, trucks, buses etc.

    3 : BOM Data Moderating : There is also a bit of an issue with BOM data for some times & places. The BOM has been ‘moderating’ some data from earlier periods in some places according to climate modelling programs. In general the BOM has ‘moderated’ the data by ‘editing’ the actual figures and substituting data which lowers slightly the average temperatures in the early years of the BOM’s records, for many places across Australia.
    Has this happened for Mt. Barker South Australia ? I do not know. I have tried to find out from the BOM by e-mail & phone. Neither effort was successful. ( My attempts to send emails about this, were blocked by BOM’s faulty spam system. And my phone calls put on hold in a queue. After waiting a while I gave up. I suppose BOM is not getting many emails or maybe they have taken Xmas holidays early ?)

    4 An important note : You can go online and ask the BOM’s website to provide you with the data for where you live, or at least reasonably close to where you live. There are 4-5 weather stations in the Adelaide Hills.
    https://www.facebook.com/groups/144702239734255/?multi_permalinks=273076286896849&comment_id=275515243319620&notif_id=1545098946831833&notif_t=feedback_reaction_generic#

    Now back to the data for Mt Barker :
    1 : Mount Barker mean temperatures since 1863 can be found on the Bureau of Meteorology web site here : http://www.bom.gov.au/jsp/ncc/cdio/wData/wdata?p_nccObsCode=36&p_display_type=dataFile&p_stn_num=023733

    The ‘mean maximum annual temperature’ over 156 years is 20.0 degrees. The highest average temperature for Mt Barker was 22.1 degrees in 2007. In the previous year 2006, the highest average temperature was 21.2. And in 2008 the highest average temperature was 21.2 degrees. And in 2010 the highest average temperature was 21.1 degrees.

    I remember those years well. They were bloody hot, dry, droughty and fire prone years. In fact that period is seared in my memory as I was trying to establish an organic apple & pear orchard here in Mt Barker.

    2 : There is some apparent ‘warming’ trend evident in these figures. There has not been a mean maximum temperature below 20 since 1991. Whereas before 1991 a mean maximum temperature in the range 19.0 to 19.9 degrees was quite common. And before 1970 it was quite common to have a maximum average annual temperature in the range 18.0 to 18.9 degrees.

    Sooooooo some “Warming” has been ‘happening’ here. However notice the date : 1995. Mt Barker was, even then in the midst of a population boom. The Australian census says that Mt Barker was 3,000 people in 1990. A smallish country town. It’s now up round 20,000 people with 35,000 in the district. I think there is a “Urban Heat Island” effect happening in this BOM’s temperature records. I think that is giving a false impression of a ‘warming’ climate at Mt Barker. Or more likely falsely boosting the BOM’s record of a small natural increase which is evident in the record from before 1995.

    3 : Mean Minimum Temperature Records : Is there any way of testing this idea ? Maybe the average minimum temperature record will help. There is a complete mean monthly record of minimum temperatures for Mt. Barker covering 155 years since 1863. Here is the link if you wish to look at it: http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_nccObsCode=38&p_display_type=dataFile&p_startYear=&p_c=&p_stn_num=023733

    A couple of things stand out . In the early days of Mt Barker the mean minimum temperature was often around 7.0 to 8.6 degrees. But a change happened around 1988. Suddenly the mean minimum temperature went up to ~ 8.9 drees. And in the 30 years since the mean minus temperature has never been in the 7.0 to 7.9 degree range. The last time the mean minimum temperature was regularly in the 7 degree range is the 1980’s.

    (Though there is the curious exception of 2006. Then the mean minimum temperature was 7.9 degrees. That year was also a droughty hot year. One of several from 2006 through to 2009. I have memories of that year 2006, being an especially dry year with cold Winter nights being crystal clear & lots of frosts in the mornings. Lots of newly planted things in the garden died. )

    But despite this exception, there is again a definite pattern : There has been a rise in the mean minimum annual temperature since around 1988. And that pattern has continued strongly ever since. The last 7 years ( from 2011 to 2017 ) in Mt Barker have all had mean annual minimum temperature of 9.0 degrees or more.

    (Unfortunately there is not complete information for 2018 yet. I wonder what 2018 mean annual minus temperature will be. )

    But again this increase coincides with the beginning of the population growth spurt in Mt Barker. The ‘new’ shopping malls were built. The first industrial estates were developed. And this is when lot of SA Housing Trust houses were built in Mt Barker. Also a number of housing estate developments backed by the Labor state government initiatives with subsidised interest rate home loans for lower income folk such as single mothers etc.

    And that population boom has not yet ended. It is still happening, It is just a little further out. So we are probably seeing a ‘Urban Heat Island’ effect with this mean annual minimum temperature data as well, masking whatever natural temperature change is actually happening.

    4 Measuring the ‘Heat Island’ effect : Is there any way of measuring the ‘heat Island effect’ so that we can estimate the background ‘Natural’ warming going on ?
    This is a real interesting question and I spent a good few hours thinking about this problem. Finally I decided to check out the BOM’s weather records for nearby rural areas in the Hills, where there has been hardly any population increase.

    I checked out the records for Lenswood. However there are records only from 1957 to 1999. No changes show up in these records. But there are no records for what’s happened in Lenswod since 1999. Bugger !

    Then I checked out the BOM weather records for Kuitpo Forest . There are weather records for the past 20 years. And those show NO increase in either the mean average Maximum temperature. These records also show NO increase in the mean minimum average temperature either. However these records only started in 1996 and so we remain totally ignorant about what happened at Kuitpo Forest weather before 1998.

    There are not many temperature recording stations in South Australia. And I could only find 26 in this entire region of SA. There are more rainfall station records but it is temperature records which are needed here. And so I wound up looking further afield at the BOM records for Murray Bridge. And I struck gold.

    First let me make clear, Murray Bridge is NOT part of the Adelaide Hills. It is 40 ks away from Mt. Barker and close to the Murray river. That’s not why I struck Gold. Rather the Gold lies in the fact that the BOM’s weather records for Murray Bridge, by pure fluke, happen to show up the ‘extent’ of the “Heat Island effect” created by us humans living in a place with all our gear and vehicles etc. Wherever we gather in big numbers we warm that place up.

    The BOM records for MB start in 1966 and keep going till 2018. At the start of this period MB was a fair sized scattered country town of 5-6000 people with lots of market gardens. Growing vegetables was the main industry.

    The BOM weather station is in the town of Murray Bridge itself near the Testra depot And at the start there was little heat Island effect. But as the decades passed the population of MB grew enormously. And it is now about 18,000. There is a heat island affect there now at Murray Bridge.

    For the first 30 years of BOM’s weather records the annual mean average maximum temperature range was 21-22 degrees. The annual mean average minimum temperature range was roughly 9 to 9.5 degrees.

    But from 1999 both the maximum and the minimum figures go up. The annual mean average maximum temperature for the period after 1999 is ~ 23.8 degrees. And the annual mean average minimum temperature range went up to ~ 10.3 degrees.

    To see the BOM’s own records for Murray Bridge check here :
    http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_nccObsCode=36&p_display_type=dataFile&p_startYear=&p_c=&p_stn_num=024521

    But in 2006 the BOM established a second weather recording station at the Pallamarna Aerodrome 8 ks. North of Murray Bridge in an area which is not urbanised. It is rural -open paddocks. And the BOM has maintained these weather records for this station ever since.

    To see the BOM’s records for Pallamarana Aerodrome from 2006 -2017, see here:
    http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_nccObsCode=36&p_display_type=dataFile&p_startYear=&p_c=&p_stn_num=024584

    The annual mean average maximum temperature for Pallamarna Aerodrome for the past 11 years is 23.3 degrees and there has been no increase in that 11 years. This is 0.5 of a degree less than in the BOM records in Murray Bridge itself just 8 ks. away.
    Also the annual mean average minimum temperature is 9.1 degrees. This is on average, 1.1 degrees less than the BOM records for the centre of town 8 ks. away, in the same period.

    And thus I think we have indeed a measure of the heat Island effect for Murray Bridge. It increased the maximum mean average temperature by 0.5 of a degree. It increased the mean minimum average temperature by 1.1 degrees.

    This numbers could be thought small and insignificant. But they are in fact important when it comes to separating out the effect of a widespread ( maybe regional or perhaps global) warming climate from a purely local Urban Heat Island effect of human habitation.

    There are differences between Mt. Barker & Murray Bridge. Mt Barker is in the Hills. It 360 meters above sea level. While Murray Bridge is perhaps 20-30 meters above sea level. But the life style and standard of living are similar. So the ‘quantum’ of heating imposed on the natural climate by the presence of so many people, is I suggest similar. And the two towns are similar in population size: roughly the same population size, 20,000 people. They also have the same wind patterns.

    Thus I think we conclude that this heat island effect will be roughly the same Murray Bridge & in Mt. Barker.

    When we deduct that 0.5 degrees Heat Island Effect from the figure for Mt. Barker post 1988, we get a mean annual maximum temperature ~20.6. A slight increase over the 156 year time frame.

    When we deduct that 1.1 degrees Urban Heat Island Effect from the figure for Mt. Barker post 1988, we get a mean minimum temperature ~ 7. 8 degrees. Almost no change at all for the 156 year time frame.

    Ummmmm ? There is a very slight “Natural’ background warming happening in Mt Barker. But NOT very much !

    But the curious thing is that there has been very little global warming over the past 18 years.

    This means it must be a regional climate effect.

    • Thanks for putting this up Geoff. I have had a variety of responses locally. Some complimentary from locals who have been here a while in the Adelaide Hills.

      And then quite a few from people who were abusive, derogatory, or insulting.. Ahh well those I simply deleted..No need to tolerate bull sh*t artists..

      And then there were a lot from 405 people who I call ‘Greenists’ for whom this type of analysis was threatening to their ideology. All of them demanded that I ignore the local weather data because it is a Global warming problem which we have to solve..Completely circular logic…Pity one of them is a younger brother. :- (

      I will post a second section next week on rainfall to see what it shows about changes in the climate of Mt Barker next week.

      Your own paper has given me food for thought on this issue of Urban Heat Island effect..Thanks for that !

  9. Not sure if I’m interpreting what you are saying correctly Geoff, but I saw Eucla mentioned as a “pristine” site. Eucla “town” as such has moved from its original location down on the plain to the new location on top of the scarp, and since there is very little left at its original location, I’m presuming that the temperature measuring site also moved. This would have occurred probably in the 1940s-50s. Great work BTW – much to learn here, particularly in regard to the Aust temp measurements, a subject of recent prominence.

    • Pristine in the sense that there have always been very few people there at either site. maybe 100 at the maximum in 120 years…But for long periods about 30 people…

      • Yep, been to Eucla old and new places off and on and like the strange, haunting beauty of the old buildings poking through the sand. But, my comment was about missing data which anyone can verify by going to the BOM web site of Climate Data Online, CDO, and following the simple steps. Geoff.

  10. I’m not a scientist but that doesn’t preclude me from understanding basic physics. Cities generate localized heat that seeks equilibrium because they are using energy. What’s the discussion? Land based temperature sensors are limited to their location. What’s the discussion about that? UHI is probably the only measurable result from using fossil fuels because fossil fuels are what powers cities today. Even if there were no fossil fuels UHI would still exist because energy is being dissipated. No?

    • In addition to dissipated energy, UHI is augmented by addition solar gain during the day due to paved roads & parking areas, and less radiative heat loss at night due to increased humidity caused by burning fossil fuels, landscape watering, cooking, and of course lots of exhaling humans.

      SR

      • I agree…paved surfaces and buildings made of materials with a high specific heat are a large component of UHI.
        And also of microclimate effects in rural areas.
        I have written a lot about my observations over many years while building and operating a commercial plant nursery in Florida, which included hundreds of nights of sitting outside all night long over many years in all sorts of weather conditions.
        The effect of even small slabs of concrete is huge in the area right over and adjacent to them, as is the effect of buildings.
        As latitude pointed out above, it seems that not only has the UHI been poorly accounted for, the corrections we have been made aware of are in the wrong direction.
        At least, that is my recollection as well.

    • markl,
      The concern is that the official national and global temperature records might not be properly accounting for the man-made heat in cities, where most of the thermometers are/were. The hypothesis for testing is whether there is actual global warming or whether it is an illusion, in part or in whole, caused by non-representative placement of thermometers. Geoff.

      • Geoff, have you read my study of the Urban Heat effect in Mt barker & Murray Bridge ? I posted it here as a comment earlier. But it has not yet appeared…Do not know why.

        • Bill in Oz,
          Maybe it is a compliment that your comment was nearly as long as my essay. Unfortunately, it does not add new information other than anecdotal and anecdotal can be as unreliable as organic gardening. Geoff

          • No Geoff, it is based on the BOM’s own data for Mt Barker since 1861 and the BOM’s data since 1966 for Murray Bridge.

            I think it supports you precisely and strongly on Urban Heat Island effect.

          • Also I was not writing for academics such as yourself.
            I wrote this out of my own interest
            And to inform ordinary folks in the Adelaide Hills who are frequently misinformed by a Greenist lobby here.

            Just like a lot of other ordinary Australian people are because academics write for other academics.

      • Understood. I was just pointing out the obvious that is conveniently being ignored by the proponents of AGW. UHI would be present with or without fossil fuels and needs to be accounted for. Even a city powered by nothing but so called renewable energy will have UHI. It’s a compliment to your post.

  11. Tony Heller has shown that GISS NOAA, BOM and the MET office are guilty not only of not dealing properly with UHI but also outright changing > 20 year older temp data to fit the meme of global warming. Why this isn’t treason and subject to criminal prosecution I have no idea?

  12. Macquarie Island is a very remote place with very little going on there. It is an ideal example for non-UHI measurement. As a result the chart is very revealing and interesting. T max and T min do not appear to have gone anywhere over 50 years. Where is that old-time Global Warming?

  13. Homogenization of the temperature data increases the warming anomaly by about 20%.
    There are legitimate reasons to homogenize, but the reasons should randomly increase up and down.
    Besides UHI which should reduce the warming of the raw data.
    So why on earth does homogenization increase warming by so much ?

  14. Geoffrey, an excellent post on the guesswork that comprises the surface station network.

    Additionally, what are your thoughts on the BOM disregarding all temperature data prior to 1910, when they have had high-quality data from weather station(s) in Adelaide (and Melbourne, I think) since 1856 and Sydney since 1859?

    • Not Perth though Angus. Perth was using a different temp meas approach in its Supreme Court Gardens. The main issue with Perth was that its first “official” site was high up on a nice cool site above the city, and its temps were so different from the rest of Perth area that the TV stations used to report two temps – the official and much cooler one, and the more correct Perth CBD temp. Each time they moved the official site, it was to a warmer location. And yet they keep saying that Perth has warmed. Yeah, righhhht…

  15. I have looked at temperature data from remote sites around Australia for some years. It was that data that convinced me that urban heat IS so-called global warming.

    This is BoM data for Broken Hill:
    http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_display_type=dataGraph&p_stn_num=047007&p_nccObsCode=36&p_month=13
    Station is now closed but it has a long history and Broken Hill was the birthplace of Australian mining and mineral processing technology so always a solid engineering/scientific community.

    Other locations with long records are lighthouses. This is Wilson’s Promontory:
    http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_display_type=dataGraph&p_stn_num=085096&p_nccObsCode=36&p_month=13

    The more isolated stations vary markedly from those in the centre of cities; for example Sydney:
    http://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_display_type=dataGraph&p_stn_num=066062&p_nccObsCode=36&p_month=13

    Look how Sydney has changed since the beginning of the temperature record:
    https://dictionaryofsydney.org/sites/default/files/media/f73c98ebaffad72361adabdfea56f3d473fe78b6.jpg
    To what it is now:
    https://jagonal.com.au/test1/4edeb760-fa85-11e3-b729-730590e5f8bc.jpg
    It is little wonder that cities are seeing an increase in temperature. Tall buildings rely on huge amount of energy to maintain a habitable internal climate. Then there are the millions of cars that enter and exit on a daily basis.

  16. The simplest way to reveal if UHI is a large part of the observed warming is to use well situated rural stations only… Oh Wait! Someone did this and most of the warming simply disappears. This is because of UHI and the data manipulation they use to reinforce the appearance of warming.

    I don’t care if it warms at night, because nights are naturally much cooler. I certainly do not care if it warms mostly in the winter. What part of “the world is becoming more temperate” is supposed to scare me?

    I hope I live long enough to see all this nonsense exposed, but I am becoming doubtful anyone will live so long… They seem to be able to just stretch out this nonsense longer and longer.

  17. Rob of Tx,

    Please read the essay more closely before diverging from its meaning.
    The essay notes that I looked at a set of well sited rural stations … Geoff.

  18. “These excerpts note sixteen factors involved in UHI. They are population density, fires, seasons, day or night, degree of city development, wind velocities, wind directions, cloud amounts, artificial surfaces, moisture, urban hydrology, storm water, soil properties, time of day of observation, anticyclones, evapotranspiration, weather station relocation.” — in addition to these sixteen points, there are several other points, namely (1) greenary, (2) air pollution, (3) topography, (4) concentration of roads and buildings with vertical structures, (5) mixing depth [inversion layer height], (6) inland or coastal city, (7) industries within the urban cities, etc.

    Also, UHI is not continuous, isolated zones present this. Met station may not be directly influenced. For example, Hyderabad Met station shoed no trend in temperature.

    Dr. S. Jeevananda Reddy

    • “…. Met station may not be directly influenced. For example, Hyderabad Met station shoed no trend in temperature…”

      I don’t know the details about that site…but you are ignoring the possibility that it was destined to otherwise cool without UHI but was warmed into “no trend.”

  19. Estimated World population in year 1900 1.6 billion
    Estimated World population in year 2016 6.1 billion
    So an addition of 4.5 billion and increased technology emitting heat such and burning of fossil fuels surely has created UHI, particularly as number of stevenson screens in cities have increased to 27%.
    I wish more scientists would focus on getting this issue analysed in more detail.

  20. Important. I’m reblogging this.

    City temperatures have a synthetic, man-made component that needs to be subtracted to match the surrounding rural temperatures, which are the items of interest for climate studies.

    So it makes sense to ignore urban readings when calculating, average country-wide or global temperatures. Because we don’t know what UHI adjustment to make. The UHI effect varies according to local conditions. We do not measure each local UHI effect. Rather than adjust for an unknown UHI effect, or imaginary average, I say it’s better to remove urban stations from statistics.

    I made that point to Ed Hawkins and his climate science twitter followers but not a single one of them agreed with me. The specifically disagreed. That’s the climate consensus for you; a consensus for bad, pliable, data.

    • Exactly. If a station doesn’t meet truly rural (and proper microsite) standards, remove it from the “climate” calculations. Far better & easier than trying to determine the possible individual-site UHI (or bad microsite) effects.

      Then we can begin a real discussion on actual temp trends & their possible effects/causes.

  21. The problems around a lack of accurate measurements, or a shortage of coverage of measurements. Are the reason proxies for historic data and models are needed in the first place. The idea you can take a weather measurement from one zone and ‘smear’ if over hundreds miles and retain any accuracy just by throwing ‘maths’ at it, is hilarious and can be disproved just driving a car that shows outside temperature over a few miles , or just observation of the local floral and fauna between different parts of the same mountain range.
    Using airports to gather this data is frankly a bit mad given the nature of these environments and that the facilities on these sites are designed to help air movements, and not in any way tell you about wider scale weather. There are in fact the classic example of ‘better than nothing ‘which in reality makes up much of the information used in climate ‘science’ which is claimed to be ‘settled’ based on the same ‘better than nothing ‘ data, models ‘tuned ‘ to get the right results , and wishful thinking.
    Science 101 , if you cannot measure it you can only ‘guess it ‘ , computing power alone does not change that. And you can note that despite vast sums spent in the area the amount that is gone into improving the data collect process is tiny , and a great deal less that has gone into models. Which is most odd given how important we told this issue is, which if true you would think would be a very good reason to make sure the data collection method was the best possible if for no other reason that whatever action is taken you need to know if its worked.

  22. What ever happened to the Climate Reference Network data set? This should be the starting point. Then, UHI should be considered a separate issue. There is far too much complication introduced by all these abstruse considerations. The doctor takes my body temperature by looking in my ear with an IR gizmo.

  23. “Scientific inquiry might better be directed towards explaining why Macquarie Island has such a low temperature trend…. ”

    Well no, meteorological enquiry would quickly give you the answer…

    It’s a small island in the Antarctic Sea, at 54 deg south within the confines of the Antarctic circumpolar current. Look at the max/min range (~ 7/3), and here …

    http://www.antarctica.gov.au/living-and-working/stations/macquarie-island/location/climate-weather-tides

    “Rain and snow are frequent, with only a few days each year with no precipitation.”
    “The wind is almost constant on the island, averaging around 25 km/h throughout the year. Low pressure systems passing the island produce winds that gust to over 170 km/h.”

    Diurnal temperature range there is tightly constrained by the wind chiefly and the to boot the observations are made at the research station on the Island isthmus, making it even more tied to surrounding SST’S.

    Photo here….

    https://en.m.wikipedia.org/wiki/Macquarie_Island_Station

    Not only is there no UHI component there but also there can be very little AGW one, as that is most easily seen in the night-time minima experienced by stations that form regular nocturnal inversions. Doesn’t happen at windy sites ( either does UHI).

    To what extent has the ocean surface warmed at 54 deg south?
    Looking here, preciously little at that location….

    https://data.giss.nasa.gov/tmp/gistemp/NMAPS/tmp_ERSSTv5__1200km_Anom112_2017_2017_1951_1980_-9999__180_90_0__2_/amaps.png

    • I see the sea and that area are totally unaffected by AGW, why is that exactly?
      Isn’t Global actually Global anymore?

      • “Isn’t Global actually Global anymore?”
        You must have missed the bit where AGW is known to vary in extent regionally.
        Greatest over land and the Arctic. Lowest over the S oceans and Antarctica.
        Q: Why would you expect it to be homogeneous?
        Just like NV in the rising trend of GSMT due increasing CO2 forcing, the rate of regional warming varies.
        Specifically because it’s the ocean and it’s able to hold 1000x times more heat for the same temp rise as would the atmosphere.
        Because that map shows SST, as in surface and water is able to overturn.
        Also, as I stated, that area is within the ACC and subject to ice-floes blown out from that that forms around Antarctica during winter – taking a long time to melt out in summer.
        Antarctic is confined both by ocean and air currents, stretching up to the stratosphere, where the PV there is much stronger (colder with a stronger jet around). This locks in air and (see recent reverse GHE article due being at an ave alt of 8,000ft and hence sustaining v cold/dry air) and the O3 hole above (O3 is a GHG and it’s absence leads to cooling).
        The interior of Antarctica is pretty much imune from sig warming, and will be for many decades to come.

        • Here are ocean area protected sites that show no CO2 warming. Why??

          notrickszone.com/2018/03/23/uncertainty-mounts-global-temperature-data-presentation-flat-wrong-new-danish-findings-show/

        • A Banton,
          Most of us see the similarity of air composition between Mauna Loa, Cape Grim, Barrow Alaska & South Pole, to name a few, as meaning that the atmosphere is well mixed on a global acale.

          The mental gymnastics fascinate me when people steadfastly refuse to explain why locations like Macquarie Island preserve around them an envelope where the air temperatures do not change very much, according to current data. What is there on the winds that signals “Turn south now, fellow hot winds, we approach Macquarie Island and so we cannot bring air heated by global warming to upset the even temperature record of the past 50 years”.

          AB, would not your expectation be that the global signature of global warming would include an element of global warmth? That is, a gradual, omnipresent change with no pockets of exceptions?

          No wonder people like me write about special pleading to preserve the global warming meme and how cowardly are the scientists who know this but still omit to speak up.

  24. My comment is far too long to post. So, I’ve written it up on my blog with this conclusion

    Whilst direct heating is the most often cause cited for urban heating, the actual scale of direct heating is relatively small. Likewise whilst changes in albedo can be significant particularly between woodland and farmland or between housing and warehouses, the average difference in albedo between urban and rural (farmland/parkland) environments is relatively small. Therefore the main reasons for urban warming are the effect buildings have in reducing average wind speeds at the “growing level” (i.e. where most plant leaves occur), and the reduction in evaporative cooling due to a reduction in plants and an increase in hard surfaces with runoff (which is then not available for cooling).

    http://scottishsceptic.co.uk/2018/12/21/urban-heating-explained/
    (Sorry this is written in haste)

    • At higher latitudes in winter (where UHI is very noticeable) the factors you mention are minimal or absent (little sunlight, no plant leaves), so direct heating is predominant.

  25. Pretty much all global temperature data sets, whether surface or lower troposphere (satellite) are agreed that the fastest rate of warming in recent decades has occurred in the Arctic. UAH TLT for example states that the warming rate in the lower troposphere over the Arctic region since 1979 has been +0.25 C/dec; more than 1 C in total and even faster in the air above the Arctic ocean. Can we agree that this observed warming is unlikely to be the result of UHI?

    • No. Studies show that even fairly small arctic communities (like Point Barrow) have strong UHI effects as might be expected. Very few arctic weather stations are away from settlements for practical reasons. See my post on Macquarie Island below.

      • You believe that heat from a couple of isolated Arctic communities has been sufficient to warm several kilometers of the lower atmosphere above the entire Arctic region, including above the Arctic ocean, by over a degree Celsius in 40 years? Wow.

          • I mentioned them, but my specific point was the UAH lower troposphere record in the Arctic. How could urban heat from isolated communities warm several kms of the lower troposphere above the Arctic, including above the Arctic ocean, by 1 deg C in 40 years? Clearly it didn’t. So whatever the impact of UHI on temperatures anywhere, something else must also be at work.

          • DWR54.. have you considered PDO, AO, AMO as the drivers as opposed to CO2? How do you remove these natural variations?

          • EdB

            Possibly, I guess. What’s the evidence though? I didn’t claim CO2 was the cause; just that there is clearly something other than UHI driving the observed increase in temperatures.

            UHI can’t explain the observed warming over the Arctic or over the oceans, whether we use surface or satellite data. Since the oceans constitute 2/3 of global surface area, it follows that it’s just silly to claim that the observed global warming over these past few decades, whether in the surface or satellite data sets, is the result of UHI.

        • DWR54
          You misunderstand. The Arctic is only sparsely instrumented and, therefor, unduly influenced by the recording stations that are located in towns or villages.

          • Clyde

            I would point out (again) that I was referring to UAH TLT temperature data: that is, the observed increase in temperatures in the several kilometers *above* the Arctic, as determined by the UAH team.

      • tty
        When I was there, the local population used 55-gallon burn barrels to dispose of garbage (and dead dogs) and at least the Army base used toilets that automatically incinerated the human waste with natural gas torches. Things may have changed, but at least when I was there in 1967, there was an unusual amount of waste heat and CO2 for a town of its size.

      • tty, you say:

        “Studies show that even fairly small arctic communities (like Point Barrow) have strong UHI effects as might be expected. Very few arctic weather stations are away from settlements for practical reasons.”

        And I agree. Perhaps “UHI” effects are a misnomer in climate studies. What is really important for effects on temperature anomaly trends is changes in time of the local environment near surrounding the measurement locations. “Urbanization” may actually happen on very small distance scales. For instance, a site in a small town that would not qualify as “urban” could have a small paved parking area built close to the site that would affect the temperature trend relative to a baseline determined before the parking area was built. Many of these effects may be gradual and cumulative over time as direct anthropogenic influence encroaches from population increases in nearby areas. In Arctic areas, encroachment by nearby warm human structures over time could have an impact even in tiny villages, especially in winter. The real UHI temperature anomaly issue is changes in these influences over time and not necessarily only in large urban areas.

        Most of the relatively new US Historical Climate Reference Network (US HCRN) sites have been carefully sited in rural areas well away from changing potential human influences over time. However, it could take many decades to confidently compare temperature anomaly measurements from these sites with other US Historical Climate Network (US HCN) in order to determine how much difference there is in the temperature anomaly trends for HRCN vs nearby HCN sites.

        • “Perhaps “UHI” effects are a misnomer in climate studies. What is really important for effects on temperature anomaly trends is changes in time of the local environment near surrounding the measurement locations. ”

          About a year or more ago there was a thread or set of them about how a worse problem than UHI was micro-site standard-violations. IIRC, Anthony made a big point about this factor.

          • Roger,

            I remember Anthony posted a comparison of trends from properly sited HCN temperature monitors versus poorly sited monitors in the US and the result was that the poorly sited monitors showed significantly higher temperature trends. What is missing is a history of site exposure documentation for each site over time.

            Ideally site measurement method and site exposure should be well documented with photographs and a detailed description of the instrument, as well as a photographic panorama view of surroundings, and aerial imagery out to a radius of about 1 km at least about once every five years for each site. Also, site operators should keep a log of changes in instrumentation or site surroundings that occur which might affect the temperature measurements. I am not aware of any such effort for HCN sites at present and especially not in the past.

          • But much of the weather statistics we are dealing with are historic statistics from much earlier times..For example the BOM weather temperature stats for Mt. Barker I discuss above, started in 1861..

            Also be aware that many of the BOM weather stations in smaller cities and towns or laclities, were placed where they were because the sites had staff present.Mostly the staff were in Australia, Post Master General (PMG ) staff at post offices across the country. Later on I think when the national phone service was separated off from the PMG, ( 1960’s ? ) the task of providing the BOM with the daily weather statistics was done by staff from the government owned Telecom Australia ( now Telstra ?)

          • Bill in Oz, you say:

            “But much of the weather statistics we are dealing with are historic statistics from much earlier times..”

            Since we do not have good site documentation for old measurements, that means there is much greater uncertainty about the accuracy of those measurements, which in turn affects what we can assess about trends since then. We need to make sure that our current temperature monitoring sites are well documented now and in the future to better establish future trends. Unfortunately I don’t see this happening very quickly.

    • DWR54,
      Please read the caveats about lack of satellite coverage near the Poles by the people at UAH and RSS.
      There is merit in your observations when they are applicable. I know it needs explanation, but my task here was to highlight the difficulties of the main approaches so far.
      Thanks Geoff.

  26. Even the Macquarie island measurements are doubtfully pristine. I was there some years ago and the weather station is within the base complex with several buildings only a few tens of meters away, though with the prevailing strong winds UHI is probably quite small.

    There was also several seals lying around near the Stevenson screen. Are they to be considered rural or urban?

  27. Lots of data, Geoff, and it adds up to real questions of UHI treatment. As a past manager of a research group adapting satellite data to gold deposit exploration (you can’t detect the gold directly but you can detect the alteration associated with it, especially utilizing Supervised Classification and Spectral Angle Mapper algorythms) I think it would be a complicated/tedious undertaking to adapt satellite temperature datasets to show a fairly accurate UHI effect. Satellites utilize microwave and/or thermal IR sensors to detect reflected energy and it is converted to temperature. Sure, there are problems with calibration, instrument drift, orbit decay, etc, but I am totally confidant a UHI signal can be identified from satellite data. Correct the processed data with digital terrain models and then compare the detected thermal anomalies with know urban sites.

    • for satellite products its called SUHI
      surface urban heat Island

      Google SUHI surface urban
      tons of studies.

      Problem: Surface Heat Island doesnt translate simply into higher air temp at 2m

      • Steven Mosher,
        Yes, agreed. It is similar to my comment that you should not use the temperature of a site to represent the site and its possible heat bubble without a lot of work on its geography and its ability to mean anything much.
        Thanks for joining in on this topic.
        Geoff.

    • Ron Long,
      My colleagues and I were initial discoverers of some of the gold at Tennant Creek, the gold/copper at Northparkes, the gold Lake Cowal and the gold at Kanowna North. Value of sales to date are in the mid tens of billions of $$$, on 2015 metal prices and money values. So I’ll see your satellite remote sensing and raise you for conventional land-based science, done with skill and rigour.
      Some of the authors quoted in my essay are using satellite data to start to map heat envelopes around large cities. I have, as yet, no idea of how small a city scale they will find meaningful. But all inputs that progress the present woeful and dishonest state of the public face of UHI are to be commended and encouraged. Geoff

  28. My work is in human physiology and engineering…so an outsider…BUT

    The use of TMIN and TMAX for temperature trends seems reasonably sloppy.

    A TMIN or TMAX lasting only 5 minutes on a given (probably windy) day IS NOT THE SAME THING ENERGETICALLY as TMINS and TMAXES lasting 2 hours or more at that same location….there could easily a several degree variance between an average temperature and a temperature integrated over the entire day. It would seem that good science would integrate temperatures over time each day to look at temperature trends at a station…rather than tracking Mins/Maxs. (Mins and Maxs are, of course, useful information, but not nearly as accurate a picture of a day’s temperatures as a time integrated temperature…especially when looking at trends.)

    Of course, there is not enough historical data to look at integration derived temperature trends going too far back, but enough post-1970 stations should exist with enough data (hourly temperatures probably available) to see how well the temperature trends derived via time integrated temperatures AND trends derived via TMin and TMax correlate.

    It may be that “integration derived” temperature trends are statistically “similar enough” to TMAX and TMIN derived temperature trends…but I doubt it.

    AND (and this is the point of this post) my data analysis instincts strongly tell me that the UHI effect would greatly effect temperature trends derived by time integration…much more so than Min/Max temperature trends referred to in this essay.

    • That seems like a fascinating and logical concept, not just for UHI but all temperature readings as you state.

    • DocSiders
      There has been plenty of discussion in the past about how the current meteorological data are unfit for the purpose of climatology. They are an anachronism. But, it is all we have for historical data. So, climatologists are trying to make the proverbial silk purse out of a sow’s ear.

  29. Geoff Sherrington, I take exception at one of your statements – “1. The BOM has created and maintained a historic temperature record of commendable quality.”

    The “commendable quality” part is very questionable, I am pretty sure that you are aware of the work that has been done identifying various issues with BOM data by Jennifer Marohasy et al.

    • ACO,
      “Commendable” is used in relation to the Climate Data Online site of the BOM, where commendable means it has been left unadjusted and accessible. Geoff.

      • Thanks Geoff for this note about the BOM online data. I was not sure if it had been left unadjusted or not…. As mentioned in note 3 in my long comment above. By the way did you already know about the differences in maximum & minimum mean temperature for Murray Bridge ( town center ) and the aerodrome 8 ks. away over the period 2006-2017 ?

  30. It has been demonstrated for about half of a century in the US that UHI of major metro areas like St. Louis and Atlanta affect the climate for hundreds of miles (e.g., change long-term precipitation patterns and quantities). IPCC is not interested.

  31. Just like the deliberate obstruction of any progress on the climate sensitivity value, you see the exact same thing w/determination of UHIE. The climate gate-keepers don’t want answers to either question, for obvious reasons.

  32. Ron Long,
    My colleagues and I were initial discoverers of some of the gold at Tennant Creek, the gold/copper at Northparkes, the gold Lake Cowal and the gold at Kanowna North. Value of sales to date are in the mid tens of billions of $$$, on 2015 metal prices and money values. So I’ll see your satellite remote sensing and raise you for conventional land-based science, done with skill and rigour.
    Some of the authors quoted in my essay are using satellite data to start to map heat envelopes around large cities. I have, as yet, no idea of how small a city scale they will find meaningful. But all inputs that progress the present woeful and dishonest state of the public face of UHI are to be commended and encouraged. Geoff

  33. UHI is far simpler than these frackin’ clowns are trying to make it. They want it more complicated so they can continue their prestidigitation with silly statistics, and therefore maintain control over the narrative. But dammit, it’s simple. There’s concrete, asphalt, buildings, roads, and parking lots, which heats the local area unnaturally, and the hard surfaces and storm sewers inhibit standing water and humidity at the surface, causing relatively fast drying and relatively lower humidity after it rains. And then on the opposite side of the ledger, there’s the tendency of humans to plant trees and grass, and to then irrigate those plants, which offsets a tiny bit of the concrete-caused warming and reduced humidity. These are the main forces of UHI. But it’s the hard surfaces absorbing UV and then releasing IR, the roads built for cars, to reduce muddy roads and to control runoff that make a city into a heat island.

  34. Would you be able to explore the UHI effect by comparing data from some of the airfield temperature records that form part of temperature series such as HadCrut (Heathrow is one such) with the surrounding observations from the Weatherlink reports? The latter are based on the use of Davis Vantage Pro weather stations which have identical temperature probes of quite good accuracy, mounted in small screens, and also capture wind data as well.

  35. Surprised no mention that night time temperatures more effected due to much higher Co2 levels near the surface that trap heat, especially in the winter.

    Going back 30+ years ago, pollution helped to minimize UHI since it kept daytime temperatures a bit lower. Today with cleaner air this offset does not exist as much except perhaps in China due to heavy smog

    In the Asian city I live in streets are now using blacktop instead of reflective surfaces, trees are being excessively trimmed and contrail activity is especially heavy in advance of cold fronts or on clear low humidity days which coincidentally or not altogether lead to higher daytime and night time temperatures and a very significant UHI not to mention an increased mean temp anomaly supporting the AGW meme.

  36. @ Bryan – oz4caster : I agree that there May have been errors made in gathering weather data in the early days. But three comments need to be made about this1: This problem could have happened in the major towns & cities of Australia as well remoter or smaller locations
    2 : No one prove that the data for a given location is systematically wrong for any reason.

    3 : This weather data is what we have. It cannot be reinvented. We do not have time mmachines to go back & redo them.

    Thus we make do with what we have.

      • “Uncertainty “?
        Ummm what ever do you mean ?

        And would you apply this ‘uncertainty’ to weather readings we have only for remote lower populated of Australia ?

        Or will you acknowledge that your ‘uncertainty’ applies to all weather readings from historic times – for eample Melbourne, Sydney, Adelaide, Perth etc. ?

        in which event what is the aim of your comment ?

        To discredit all the historic weather data from BOM ?

        But what purpose does that serve ?

        I am frankly suspicious.

        • Bill in Oz, you say regarding temperature measurement uncertainty:

          “Ummm what ever do you mean ? And would you apply this ‘uncertainty’ to weather readings we have only for remote lower populated of Australia ? Or will you acknowledge that your ‘uncertainty’ applies to all weather readings from historic times – for eample Melbourne, Sydney, Adelaide, Perth etc. ?”

          There is uncertainty in all temperature measurements, including accuracy, precision, and representativeness. Here is my take on uncertainty of temperature assessments, whether they be global, regional, or local:
          https://oz4caster.wordpress.com/2015/02/16/uncertainty-in-global-temperature-assessments/

          • Bryan
            Thanks for the link to your blog. I have looked briefly at it & a couple comments about it but first a reply to your latest comment here.
            In order to understand the present we must rely on the past. There is always the issue of how reliable the ‘evidence’ is. But that is frankly speaking an issue of history and specifically historiography which examines this specific issue in a broader context. How to assess the historical evidence.

            But here is not the time or place for such a discussion. The evidence is what we have’. There is no other human evidence except what humans have recorded.
            And that leads me to a reflection on your blog : I don’t see that historical perspective there very much….And that is perplexing for me as Climate Warmists rely on fears of great change in climate but seem to have no grasp or understanding of past climate, even the recent past climate..

            I am also ersplexed by your ‘handle Bryan-oz4caster. i thought that indicated I was speaking to someone who is here in Australia. But your blog is (almost ) devoid of any material on Australia..I did a number of searches of your blog on Australia, BOM, etc and found nothing. It is USA/North American & Global in focus…
            My focus as my long comment about about local Mt. Barker temperatures indicates is local & historical..And I am convinced there is much value in such data.

            You on the other hand seem far more concerned and interested in the high tech whizz bang modern computer approach to climate …

            So really we are talking past each other

          • Bill of Oz, you say:

            “And that leads me to a reflection on your blog : I don’t see that historical perspective there very much…. And that is perplexing for me as Climate Warmists rely on fears of great change in climate but seem to have no grasp or understanding of past climate, even the recent past climate..”

            Perhaps you missed my Paleo Climate investigations summarized here:
            https://oz4caster.wordpress.com/paleo-climate/

            As far as my handle “oz4caster”, I came up with it many years ago when I set up my first email account, long before I started my paleo climate and climate investigations around 2008. I used to forecast ground level atmospheric ozone and particulate matter air pollution, beginning in 1992 for ozone and around 2000 for particulate matter. So my handle is simply short for “ozone forecaster”. Back then I had no contacts in Australia and only later realized the confusion it might cause, but because I’ve used it for such a long time, I have stuck with it.

            I am now retired and I have lived in Texas all my life. Being an avid meteorologist ever since my teens, I do have a strong interest in Texas and US weather and climate, including tropical cyclones, that continues in my retirement, but I don’t blog about that. My blog is focused on paleo climate and current global climate trends, including latitudinal-zonal perspectives (NH, SH, 90S-60S, 60S-30S, 30S-30N, 30N-60N, and 60N-90N) that I picked up several years ago when I started following the University of Maine’s Climate Reanalyzer.

            As I mentioned previously, my comments about uncertainty in climate assessments apply to all geographical scales and they also apply to all temporal scales. It’s just something to keep in mind when studying climate and even when studying weather. We have to guard against drawing improper conclusions about the data that are not warranted by uncertainty in the data. Unfortunately, most of the climate work I see ignores the overall uncertainty, probably in part because it is difficult to quantify objectively. Most climate related temperature uncertainty assessments I have seen only cover limited objectively defined statistical uncertainty, which is only a small part of the overall uncertainty. And very often what is presented to the public implies much greater certainty than is warranted, especially in regards to climate alarmism.

  37. Geoff, I have been thinking about Urban Heat Islands a lot in the past few days. And thinking also about the link posted above by Jeff : https://landsat.gsfc.nasa.gov/vegetation-essential-for-limiting-city-warming-effects/?fbclid=IwAR2WXhZb61_aiBW-Q1vD0JYcZ_sKfzlECG_m2lYzw-jVVbnbPM6DRtuH7Ro

    I read it and then wondered about what has been happening to the vegetation is our large Australian cities.

    Three things come to mind :
    1 The move away from deciduous vegetation & trees & towards native trees & shrubs that are drought tolerant. ( Eg gums and wattles instead of oaks & elms & ashes. ) Thus there is less water vapor being transpired = higher temperatures

    2: Since the 1970’s water authorities in cities like Melbourne, Adelaide, Perth , Sydney have encouraged lower watering of our gardens….So the vegetation does not transpire as much water vapor into the air = higher temperature

    3: Smaller houses on big blocks with big gardens are now disappearing in all our big cities. They are being replaced by small blocks with big houses and tiny gardens = higher temperatures.

  38. There’s much to agree upon with Geoff about the woeful lack of useful SCIENTIFIC knowledge that is required to make credible corrections to individual UHI-corrupted station records.

    Yet, the situation is not quite as dire as is painted here from a rather small-scale perspective using the very limited analytic power of linear regression . The key to scientifically demonstrable valid estimation of regional and larger scale temperature variations unaffected by UHI lies in the ability to systematically recognize relatively UNCORRUPTED, century-long station records. Whatever other vagaries may be found in individual records, they are greatly reduced by aggregate averaging geographically representative, well-vetted records. Because serious vetting eliminates the great majority of available station records on one basis or another, it also prevents the rise of fanciful notions of narrow confidence intervals based upon grossly inflated numbers of stations involved.

    Because the great majority of “climate scientists” (not to mention climate data “junkies”) have no experience in maintaining met stations in remote locations, and those who do still lack analytic insight into how pristine records co-vary spatio-temporally, they fail miserably in that recognition. Instead of vetting or rejecting available records on a realistic basis, they resort to various indiscriminate “homogenization” and “krigging” schemes that ASSUME spatio-temporal properties not present in the actual temperature field or time series.

    The result is global or continental indices that purport to show “climate change” over century-long scales, but are merely collages of unvetted snippets of decadal-scale data anomalies, often lacking even a true common datum-level. Using only vetted, century-long station records (not necessarily all “rural”), a former colleague (who communicated years ago with Geoff) showed quite convincingly that ALL of the published indices are only weakly coherent at multi-decadal frequencies with representative aggregate averages of vetted records and manifest much higher 20th-century trends.

    • Big words designed to to confuse. And so NOT worth the effort of thinking about Isky1. I will have more time for your words after you have gone away and actually examined some long term weather data for a specific location.

  39. Geoff: Missed your post when it came out. Thanks for making the effort to write this and noting the shift away from evidence to partisan belief.

    I’d like to note that UHI bias alone isn’t important, only CHANGING UHI bias makes a difference. If UHI means all the thermometers in the Melbourne area have been reading 1 degC “too high” from 1900 until today, the warming TREND for Australia will still be correct. If UHI bias has risen from 1 degC to 2 degC during this period, the warming trend will be biased upward. Since the IPCC’s attribution statement begins with 1950 and since global warming took off in the 1970’s, you might choose to focus on CHANGING UHI bias since 1970.

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