There’s some excitement around blogdom with the Australian Bureau of Meteorology (BOM) apparently questioning the UHI adjustments it’s made to the temperature record.
The actual press release
But the story is proving difficult to pin down. I’ve located the BOM Media Release of 13 October, 2010, which says (emphasis added):
Wednesday 13 October 2010
MEDIA RELEASEHot cities
If you thought our cities are getting warmer, you’re right.
Bureau of Meteorology researchers have found that daytime temperatures in our cities are warming more rapidly than those of the surrounding countryside and that this is due to the cities themselves.
Bureau climate scientist, Belinda Campbell, said: “we’ve known for a while that city night-time temperatures have been warmer because the heat’s retained after sunset just that much longer than the countryside, and that city day-time temperatures have been warming too.”
“But what we didn’t know was whether city day-time temperatures were also warmer because of the urbanisation or whether it was due to the overall warming of the planet associated with the enhanced greenhouse effect.”
“We can now confidently say that the reason our cities are warmer and warming faster than the surrounding countryside during the day is because of the urbanisation — the fact that all those offices, houses and factories absorb the heat and retain it a little bit longer,” Ms Campbell said.
On average, the enhanced greenhouse effect is responsible for about 0.5 to 1.0 degree of observed warming around the globe (more in some areas, less in other areas).
The additional effect of urbanisation on warming varies from city to city (depending on the buildings and open parkland close to the observation site).
The research team analysed data from 70 sites in the Bureau’s meteorological data archive in order to quantify how much the increases in day-time temperature can be attributed to urbanisation and how much to the enhanced greenhouse effect.
The sites were mostly from towns with populations ranging from 500 to 100,000, with a handful being either in cities with more than 100,000, or in isolated locations with hardly anybody for hundreds of kilometres.
Ms Campbell is presenting the results of the team’s work at the Australia – New Zealand Climate Forum in Hobart on Thursday (14 October, 2010).
There’s no mention of their questioning the temperature record. Reason is given to do so, but no sign that they do, so bloggers might be premature in claiming the BOM are recanting their official temperature record.
So let’s ask them
On the face of it, since Belinda said the reason Australian cities are warmer than the countryside is urbanisation, this work weakens the case for disastrous future warming caused by humanity. But it is a conditional conclusion which depends on the actual quantity of warming caused by the UHI effect.
We need to find out the amount of warming the BOM attributes to the newly-discovered UHI. So I have today emailed them asking for information about the team’s results. Here’s an extract from my email:
On 13 October, 2010, the BOM issued a Media Release (available here) quoting one of your climate scientists, Miss Belinda Campbell, announcing the discovery of the Urban Heat Island effect in Australian towns and cities. … I would like to know if you could send us the presentation of the team’s work? Or if it’s available on the Internet? Anything related to this announcement would be helpful.
Yes, there’s a scrap of tongue-in-cheek humour there which I could not resist. I’ll let you know what they say, when and if they respond.
More to come
In the meantime, this result is important and, if it hasn’t yet put doubts about the temp record into the minds of BOM’s scientists, it ought to. If it doesn’t do that, it must at the very least raise doubts about the effects and the speed of CAGW. So I’m putting together a post looking at BOM’s past statements relating to man-made climate change to chart their attitude changes.
UPDATE 1 15 November
An anonymous correspondent at the BOM has sent the following reply. As it contains no closing full stop I question whether I received the whole abstract. I have asked for the proposed publication and date. I would be grateful for comments on the abstract and its relation, if any, to the claims that BOM is questioning its UHI adjustments. I was under the impression that they might now begin making adjustments — it would be a step forward. But I may have been mistaken.
Good morning Richard
The abstract is below. The paper has not been published yet.
Urbanisation and maximum temperature
Harvey Stern1, Belinda Campbell1, Michael Efron, John Cornall-Reilly1, and John McBride2
1Victorian Regional Office, Bureau of Meteorology, Box 1636, Melbourne, 3001, Australia.
2Centre for Australian Weather and Climate Research, Box 1289, Melbourne, 3001, Australia.
The Australian Data Archive for Meteorology (ADAM) is used to compare trends in maximum temperature (MAXTEMP) at Sydney and Melbourne with those at other (less urbanised) Australian localities. By this means, the relative extent to which MAXTEMP increases in those cities can be attributed to urbanisation, the enhanced greenhouse effect, and other causes, is quantified.
The influence of cities on overnight temperatures is well documented. However, their influence on daytime temperatures is less well documented.
Sydney and Melbourne MAXTEMP data are compared with other ADAM data sets and are found to be increasing at a faster rate than elsewhere.
For both localities, annual MAXTEMP data are statistically modelled over various control periods using MAXTEMP data at surrounding non-urban stations as input. Thereby, sequences of non-urbanised MAXTEMP can be constructed for the hypothetical circumstance of the cities not being built.
Synoptic stratification of daily data shows that a recent “jump” in the Melbourne series is due to buildings constructed immediately to the south of the site.
In contrast to the current study, Torok’s (1996) PhD work identified, and adjusted for, “… jumps in the time series due to non-climatic changes… (and this consequently removed) …urbanisation signals from the time series”. Torok’s adjustments have been applied to the derivation of the Bureau of Meteorology’s high quality data sets (HQDS).
The current study’s approach (using ADAM data sets) has been to identify, and preserve, the urbanisation signals in the time series.
As would be expected, MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed)
UPDATE 2: 17 NOVEMBER
Ken Stewart has kindly sent us (through Val Majkus) a paper Ken referred to: A historical annual temperature dataset for Australia, by Simon Torok and Neville Nicholls in 1996. You can download the paper from our Files area.
Views: 110
Here goes; I have no scientific training or expertise so hope I get this accurate but if I don’t I’m sure someone will correct me
The BOM temperature data consists of (using BOM’S words)
1. The Australian Reference Climate Station (RCS) network established for high quality, long-term climate monitoring, particularly with regard to climate change analysis.
2. High Quality HQ dataset containing the Operational monitoring of Australia’s changing climate
3. Historical climate data (raw data) provided in both graphical and textual formats at climate sites. Graphs can be viewed as either mean/total data or as anomalies from the standard 1961-1990 base period (1971-2000 is used for pan evaporation due to shortness of record). Daily data are only plotted from 1995 onwards to avoid over-crowding the graphs, but the full daily record is available as text.
The HQ dataset is the set on which the official Australian temperature analyses are based. The network is shown at http://www.bom.gov.au/climate/change/hqsites/. You can google BOM High Quality to go to the BOM page. For temperature enthusiasts an explanation of the methodology is here ftp://ftp.bom.gov.au/anon/home/ncc/www/change/HQannualT/HQannualT_info.pdf Homogenity is the key. A non-urban set of 99 stations from the updated HQ dataset are used to prepare timeseries of annual all-Australian temperature, and maps of trends in temperature. Based on the methodology used for annual trends urban sites (sites that have or have had at some time since 1910 a population over 10,000) are not to be included.
Ken Stewart’s work compares the HQ to the raw data. The HQ dataset is well explained on Ken’s site under the heading The Australian High Quality Climate Site Dataset http://kenskingdom.wordpress.com/2010/05/12/the-australian-temperature-record-part-1-queensland/ together with explanations Ken received from BOM to enquiries. Ken found just in Qld some urban sites are included. Other states have similar anomalies.
My understanding is the BMO make no allowance for UHI in its HQ dataset when preparing timeseries as the 99 stations are ‘non urban’. However, notwithstanding the HQ dataset rules (that is that is that sites should not be included if they are urban sites if they have had a population over 10,000 at some time in the last 100 years) this rule has not been uniformly applied so there are many sites in the BOM HQ timeseries data which have no adjustments for UHI.
Ken’s conclusion in his Problems in his Big Picture article with the HQ data include:
• It has been subjectively and manually adjusted.
• The methodology used is not uniformly followed, or else is not as described.
• Urban sites, sites with poor comparative data, and sites with short records have been included.
• Large quantities of data are not available, and have been filled in with estimates.
• The adjustments are not equally positive and negative, and have produced a major impact on the Australian temperature record.
• The adjustments produce a trend in mean temperatures that is roughly a quarter of a degree Celsius greater than the raw data does.
• The warming bias in the temperature trend is over 40%, and in the anomaly trend is 50%.
• The trend published by BOM is 66.67% greater than that of the raw data.
The questions remain
1. The extent if any to which temperatures were subjectively altered even before they gained the description “raw data”.
2. What if any adjustment is BOM prepared to make to its HQ dataset for those of its 99 ‘non urban’ stations which are undoubtedly ‘urban’
UHI is a huge problem.
Warwick Hughes has some articles on his site about UHI http://www.warwickhughes.com/blog/index.php?s=uhi including Two degrees C Urban Heat Island in small village of Barmedman, NSW, Australia (277 people)
I’m a bit depressed that noo-ne has provided an additional comment
I’m looking for negatives and/or positives to my comment
H’mmm I’ve asked for comments from some Aussie connections
hopefully they’ll reply
My view still is that BOM have recanted with regard to UHI but how far it will go is a matter I believe it is not prepared to indicate
If anyone including the BOM has an alternate view then please say so;or ….
and i suppose the same question could be asked of NIWA
“I’m a bit depressed that noo-ne has provided an additional comment”
Val, I’m not sure I can offer much, I have just been following what you have been doing and also I’m probably more interested in satellite, ocean heat content and model issues so land temps are on my periphery. FWIW here goes.
My understanding from what I’ve seen at WUWT and elsewhere is that UHI decreases in significance as the size of the urban expanse increases. There are studies and blog posts around that I can’t put my finger on at the moment but could hunt down if you wanted (search UHI at WUWT).
For example, an additional 100,000 population to a city of 1, 000,000 will have less effect than say an additional 10,000 to a city of 100,000. i.e. the temperature increase will be significant in the latter but negligible in the former (don’t quote me on this).
The main point I think is that in any adjustment for UHI, the early temperatures remain fixed and the later temps are adjusted downwards. UHI influenced temperatures are best discarded in my view; otherwise all that’s being measured is global warming due to urbanization and increased energy use. Infrared cameras make a mockery of temperature in this regard e.g. every electricity transmission line loses energy in the form of heat and where does the heat go and is it adjusted for?
I’m probably stating what everyone already knows but from what I can gather, the contentious issue is that the IPCC does not consider the downwards adjustment for UHI to be of any importance contrary to the evidence. It follows that the magnitude of downward adjustment has not been established for varying size and population or applied. Again, I’m really not up to speed on this.
As to what the BOM is up to, I think we will all have to watch that space for developments but at the moment it seems to be your zone.
Here’s a serious heat island at the Glenbrook steel mill south west of Auckland.
1500 Deg C in the melters and lots of carbon action 24/7/365 – a global warmists nightmare.
If the heat from all the furnaces around the world actually was “trapped” by GHG’s, we would have all fried long ago.
This illustrates the fallacy of a globally averaged temperature.
Richard you may be interested in Warwick Hughes’ post
How NASA GISS inserts warming into USA rural T data
http://www.warwickhughes.com/blog/?p=27
this is dated 2006 but Trawling through files from 2001 I came across this rare example of an email from Dr Jim Hansen that actually gives an insight into what GISS does with temperature data.but quoting
For background I have my page commenting on Jones et al use of Miami.
http://www.warwickhughes.com/climate/miami.htm
Then my page on the five degree grid cell covering much of Florida and commenting on Jones 1994 additions.
http://www.warwickhughes.com/climate/florida.htm
Then this page commenting on GISS data which inserts warming into rural data west of Miami.
http://www.warwickhughes.com/climate/giss_fl.htm
and he has other GISS articles (just search on his search button) some of which have comments where commentators have noticed warming adjustments to rural data to meet urban trends
in IPCC, Jones et al, Surface Record | 22 Comments »
and an article NASA GISS data does not back BoM hottest decade claim (Jan 2010)
Warwick’s comment
I think a fair statement would be that given the data quality in the outback – it looks unlikely the 2000-2009 decade could be warmer than 1990-1999 in a statistically significant sense.
I am asking – what is the BoM doing wasting our money making dubious lineball claims like this ?
There’s an interesting article on Jo Nova’s site by Chris Gillham (a Western Australian)
http://joannenova.com.au/2010/10/bom-giss-have-record-setting-bugs-affecting-a-million-square-miles/
quoting
Fresh doubts have emerged about the reliability of temperatures within the Goddard Institute of Space Studies Surface Temperature Analysis database with revelations that missing data errors have appeared for various months in the 2009 records of Australian locations, even though the correct mean temperatures are available from the Australian Bureau of Meteorology (BoM).
In turn, the BoM data itself has seen adjustments that might leave researchers wondering about claims that Australia has suffered record high temperatures over the past 12 months.
So it leaves you wondering about the accuracy of satellite data as well
and Richard more of Warwick’s work
At http://www.warwickhughes.com/climate/bom.htm Warwick says ‘Internationally the BoM does not have things all its own way, NASA / GISS publish on their web site (see www links) UHI adjusted trends for Australian cities and also have for download SE Australian rural records that show no warming since late 19 C, which the BoM say are incorrect’
the comment at http://www.warwickhughes.com/climate/gissbom.htm
is posted 27/9/2000 and Warwick says ‘This page presents three Australian State Capital temperature records compared to nearby rural or more rural neighbours.
This is a significant area for study because south eastern Australia has probably the best set of long term rural temperature records in the southern hemisphere.
GISS / NASA adjustments for urban warming are presented in the case of the State Capitals, contrasting with the Australian Bureau of Meteorology (BoM) adjustments.’
The differerence is stark with BoM finding much warming over SE Australia since late 19 C while NASA finds little trend.
At http://www.warwickhughes.com/climate/ 26, June, 2005, Warwick has a site which in his words exposes the errors and distortions in temperature records used by the IPCC as evidence of “global warming”, Warwick says the central contention of these pages is that for over a decade the IPCC has published global temperature trends distorted by purely local warmth from Urban Heat Islands (UHI’s). There is simply no systematic compensation for urban warming in the Jones dataset. Occasionally there is a slight adjustment in a record for a site change or other anomaly but the majority of records are used “raw”.
Warwick gives some history of this amazing work at http://www.warwickhughes.com/
For those who do not know this is his blog and you can learn about him as the ‘about’ button http://www.warwickhughes.com/blog/
He was also the recipient of the famous Jones letter which you can read about on WUWT http://wattsupwiththat.com/2009/09/23/taking-a-bite-out-of-climate-data/ ‘The Dog ate Global Warming’ That article informs us that ‘Warwick Hughes, an Australian scientist, wondered where that “+/–” came from, so he politely wrote Phil Jones in early 2005, asking for the original data. Jones’s response to a fellow scientist attempting to replicate his work was, “We have 25 years or so invested in the work. Why should I make the data available to you, when your aim is to try and find something wrong with it?”
“So it leaves you wondering about the accuracy of satellite data as well”
The data quality issues are not much different to land series issues. Basically two parts: measuring equipment (siting, drift, calibration etc) and data management/quality control.
The same issue of errors by paid custodians of data being uncovered by unpaid scrutineers is occurring with land and satellite series. These errors would probably have gone unnoticed if it wasn’t for the AGW-climate change debate.
Re UHI. I found this on the CESM Homepage:
“Capturing heat islands in climate models”
http://www2.ucar.edu/staffnotes/research/2563/capturing-heat-islands-climate-models
Showing a satellite temperature image of Atlanta, USA contrasted with a vegetation map that demonstrates evaporative cooling.
From the blurb:
Results from the modeling experiment show that present-day annual mean urban air temperatures are up to 4°C (7.2°F) warmer than temperatures for surrounding rural areas, a finding that is important for verifying the model’s accuracy since scientists already have observational evidence that urban areas are warmer than surrounding rural areas.
“This study demonstrates that climate models need to begin to account for urban surfaces to more realistically evaluate the impact of climate change on people in the environments where they live,”
(Just ignore the IPCC emissions scenario BS)
So the models that have been relied on so far to predict temperatures in 2100 have not even BEGUN to realistically account for urban surfaces and UHI.
Gday Val:
I’m back again. BOM are really saying they haven’t got a clue, which is basically what Torok and Nicholls said in 1996. They know there is UHI but (up til now anyway) haven’t been able to quantify it. The asbstract says “MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed)” which is fine; but how much is the urbanisation signal from the ADAM datasets? UHI is very strong in Sydney and Melbourne I agree, but is also distinctly present in many small towns. It depends more on the actual surroundings than the surrounding population. You can see this when there are station moves from a town centre to an airport e.g. Bowen, Charters Towers, Cobar. Even when the move was back in the 1940s. But occasionally you see the opposite- a warming e.g. Cardwell. Local factors apply.
By the way there are 100 non-urban sites, but 15 of these used to be classified as urban but were included because otherwise the dataset would not have been large enough.
So basically, BOM are saying they recognise UHI, including in maxima (everyone thought it was mainly in minima) but they don’t know how to adjust for it.
Another observation- I don’t believe UHI is solely responsible for 20th century warming, as many sites far from towns show some warming. However UHI is enough to mess with the data. And their heads.
Ken
Ken thank you for your contribution and for your correction of my error (100 non urban sites and not 99) but it’s a bit concerning when 15 previous urban classified station are included with I’m still assuming no correction for UHI
By the way do you have a copy of the Torok and Nicholls paper and the subsequent paper which updated it
and if so could you please provide a link on this page
I like what you say BOM are saying they recognise UHI, including in maxima (everyone thought it was mainly in minima)
UHI has a huge affect and I doubt whether proper adjustments are being made for it
have you seen Warwick Hughes comment http://www.warwickhughes.com/blog/index.php?s=melbourne%27s+
January 13th, 2010 by Warwick Hughes
On the night of the 11th-12 of Jan 2010 Melbourne sweated through an uncomfortably hot night. Just a couple of media refs will give you the gist but Google could find more no doubt. There is talk of Melbourne’s “..equal hottest night ever.” But I see no sign of balancing statements which should have refered to two facts.
[1] The record equal temperature was measured in the centre of the Melbourne urban heat island (UHI) which has grown at night by 2 degrees centigrade in the last 60 years.
[2] The BoM should have stated that there was little sign the hot night was a record breaker outside of Melbourne.
There’s a number of comments there by readers who are puzzled by inconsistenies with BOM data
New Zealanders should be concerned about the accuracy of BOM work because BOM is to audit NIWA’s records at some time
Hi Val
The 2 papers are:
Torok, S.J. and Nicholls, N. 1996. A historical annual temperature dataset for Australia. Australian Meteorological Magazine, 45, 251-260. (I’ll email it to you)
and
http://www.giub.unibe.ch/~dmarta/publications.dir/Della-Marta2004.pdf
Ken
Val and Richard – I admire your efforts to understand the BoM. It will be interesting to see the “Urbanisation and maximum temperature” paper by – Harvey Stern1, Belinda Campbell1, Michael Efron, John Cornall-Reilly1, and John McBride2.
– when it emerges peer reviewed and published.
Of course I doubt any of us common herd will ever get to examine their ADAM data.
On the face of the authors statements there seems to be some conflict with the very influential 1996 work of Torok & Nicholls which heavily corrected BoM data leaving an IPCC compliant warming trend.
I suppose you have seen this ten year old paper;
“Urban heat island features of southeast Australian towns”
http://www.bom.gov.au/amm/docs/2001/torok_hres.pdf
Then there is our 64 station review by Hughes and Balling , “Eastern Australia temperature variations 1930-1992”
http://www.warwickhughes.com/papers/eastoz.htm
The page 19 graphic;
http://www.warwickhughes.com/papers/Hbeoz19.gif
sums up changes in mean T and DTR for stations with population ranging from 1000 up to a million and more.over Eastern Australia.
From
“Urban heat island features of southeast Australian towns”
Results from Karl
et al. (1988) suggest an exponential relationship
between mean urban-rural annual temperature difference
(T – *u-r) and urban population (POP) of:
T –*u-r = a(POP)0.45 …3
The coefficient, a, was found to be -3.9 x 10-4 for maximum
temperatures, and 3.61 x 10-3 for minimum temperatures.
In towns with populations below 10,000, a
was found to be -0.77 x 10-3 for maximum temperatures
and 5.12 x 10-3 for minimum temperatures
So the effect diminishes as the population increases.
From my comment up-thread
“I’m probably stating what everyone already knows but from what I can gather, the contentious issue is that the IPCC does not consider the downwards adjustment for UHI to be of any importance contrary to the evidence.”
From AR4 WGI
Urban heat island effects are real but local, and have not biased the large-scale trends. A number of recent studies indicate that effects of urbanisation and land use change on the land-based temperature record are negligible (0.006ºC per decade) as far as hemispheric- and continental-scale averages are concerned because the very real but local effects are avoided or accounted for in the data sets used. In any case, they are not present in the SST component of the record. Increasing evidence suggests that urban heat island effects extend to changes in precipitation, clouds and DTR, with these detectable as a ‘weekend effect’ owing to lower pollution and other effects during weekends.
I’m not in the habit however, of taking IPCC science as gospel given FAQ 1.3 What is the Greenhouse Effect?
Because the Earth is much colder than the Sun, it radiates at much longer wavelengths, primarily in the infrared part of the spectrum (see Figure 1). Much of this thermal radiation emitted by the land and ocean is absorbed by the atmosphere, including clouds, and reradiated back to Earth.
This is complete BS.
Radiation is emittance but what they describe is reflectance – big difference. They really should get to grips with the meaning of the word “radiate”. Of all the vectors of radiation, in all directions from a GHG molecule, only one will be “back to Earth”.
IPCC science is c***.
But they do say of UHI: “In any case, they are not present in the SST component of the record”. About the only redeeming feature – unfortunately for them, this “line of evidence” is showing a cooling trend. Hooray for the SST.
“Of all the vectors of radiation, in all directions from a GHG molecule, only one will be “back to Earth”.”
Better qualify this I suppose.
Only one at right angles (assuming that it is not intercepted by .another molecule on the way down).
There will be more than one but as the angle of incidence becomes more acute, what minimal heating effect there is (on land – non-existent on the lakes and oceans), is diminished even further.
In other words – the IPCC’s “much of” is actually “a lessor proportion of” and the 70% of that, that strikes the oceans and lakes has no effect whatsoever.
DUH.
Got myself O/T and oversimplified, so from G&T 2009 for the physics:-
Al Gore confuses absorption/emission with reflection. Unfortunately, this is also done implicitly and explicitly in many climatologic papers, often by using the vaguely defi ned terms “re-emission”, “re-radiation” and “backradiation”.
3.5.2 Reflection
When the jump of the refractive index occurs within a length of the order of a wavelength, there will be a reflection, which is large at high absorption. In the case of gases this is only possible for radio waves of a comparatively long wave length in the ionosphere, which has an electrical conductivity, at a diagonal angle of incidence. There is no reflection in the homogeneous absorbing range.
3.5.3 Absorption and Emission
……it is impossible to describe the volumes of gases with the model of black cavity radiation. Since thermal radiation is electromagnetic radiation, this radiation would have to be caused by thermal motion in case of gases, which normally does not work effectively at room temperatures. At the temperatures of stars the situation is di fferent: The energy levels of the atoms are thermally excited by impacts
3.5.4 Re-emission
This assumption is called the assumption of Local Thermodynamical Equilibrium (LTE). Re-emission does never mean reflection, but, rather, that the absorption does not cause any rise of temperature in the gas.
3.7 The assumption of radiative balance
3.7.1 Introduction
Though there exists a huge family of generalizations, one common aspect is the assumption of a radiative balance, which plays a central role in the publications of the IPCC and, hence, in the public propaganda. In the following it is proved that this assumption is physically wrong
3.7.2 A note on “radiation balance” diagrams
From the de finition given in Section 2.1.2 it is immediately evident that a radiation intensity I is not a current density that can be described by a vector fi eld j(x; t). That means that conservation laws (continuity equations, balance equations, budget equations) cannot be written down for intensities. Unfortunately this is done in most climatologic papers, the cardinal error of global climatology, that may have been overlooked so long due to the
oversimpli cation of the real world problem towards a quasi one-dimensional problem. Hence the popular climatologic “radiation balance” diagrams describing quasi-one-dimensional situations (cf. Figure 23) are scientific misconduct since they do not properly represent the mathematical and physical fundamentals.
Diagrams of the type of Figure 23 are the cornerstones of “climatologic proofs” of the supposed greenhouse e ffect in the atmosphere [142]. They are highly suggestive, because they bear some similarity to Kirchho ff rules of electrotechnics, in particular to the node rule describing the conservation of charge [158]. Unfortunately, in the literature on global climatology
it is not explained, what the arrows in “radiation balance” diagrams mean physically. It is easily verifi ed that within the frame of physics they cannot mean anything.
Climatologic radiation balance diagrams are nonsense, since they
1. cannot represent radiation intensities, the most natural interpretation of the arrows depicted in Figure 23, as already explained in Section 2.1.2 and Section 2.1.5 ;
2. cannot represent sourceless fluxes, i.e. a divergence free vector fields in three dimensions, since a vanishing three-dimensional divergence still allows that a portion of the field goes
sidewards;
3. do not t in the framework of Feynman diagrams, which represent mathematical expressions clearly de fined in quantum fi eld theory [159].
4. do not t in the standard language of system theory or system engineering [160].
3.7.5 Non-existence of the natural greenhouse e ffect
According to the consensus among global climatologists one takes the 18C computed from the T4 average and compares it to the fictitious Earth’s average temperature of +15 C. The di fference of 33 C is attributed to the natural greenhouse e ffect. As seen in Equation (83) a correct averaging yields a temperature of 129 C. Evidently, something must be fundamentally wrong here.
In global climatology temperatures are computed from given radiation intensities, and this exchanges cause and eff ect. The current local temperatures determine the radiation intensities and not vice versa. If the soil is warmed up by the solar radiation many di fferent
local processes are triggered, which depend on the local movement of the air, rain, evaporation, moistness, and on the local ground conditions as water, ice, rock, sand, forests, meadows, etc.
One square meter of a meadow does not know anything of the rest of the Earth’s surface, which determine the global mean value. Thus, the radiation is locally determined by the local temperature. Neither is there a global radiation balance, nor a global radiation budget, even in the mean- field limit.
3.7.7 Non-existence of a global temperature
In the preceding sections mathematical and physical arguments have been presented that the notion of a global temperature is meaningless. Recently, Essex, McKitrick, and Andresen showed [169]:
“that there is no physically meaningful global temperature for the Earth in the context of the issue of global warming. While it is always possible to construct statistics for any given set of local temperature data, an in finite range of such statistics is mathematically permissible if physical principles provide no explicit basis for choosing among them. Distinct and equally valid statistical rules can and do show opposite trends when applied to the results of computations from physical models and real data in the atmosphere. A given temperature field can be interpreted as both `warming’ and `cooling’ simultaneously, making the concept of warming in the context of the issue of global warming physically ill-posed.”
Regardless of any ambiguities, a global mean temperature could only emerge out of many local temperatures. Without knowledge of any science everybody can see, how such a changing average near-ground temperature is constructed: There is more or less sunshine on the ground due to the distribution of clouds. This determines a field of local near-ground temperatures, which in turn determines the change of the distribution of clouds and, hence, the change of the temperature average, which is evidently independent of the carbon dioxide concentration. Mathematically, an evolution of a temperature distribution may be phenomenologically described by a diff erential equation. The averages are computed afterwards from the solution of
this equation. However, one cannot write down a di fferential equation directly for averages.
My bad but fixed thanks to G&T.
Hi Richard; wondering if your site is down; I’ve tried to post something intermittently for the last 4 hours or so
Not my site Val – Richard Treadgold’s.
I’ve noticed the intermittent unavailability too.
Warwick Ken and Richard thanks so much for your valuable contributions; Ken has now sent me the Torok paper – it’s a 10 page PDF so I could copy it here if that would be helpful –
Yes please, Val. It rejects the Rhoades & Salinger (1992) paper for being too subjective, and develops its own subjective methodology.
Now that Warwick has kindly pointed out to me the name of the paper which is referred to in the media release I’ve managed to track down this info:
http://ams.confex.com/ams/91Annual/webprogram/Paper184863.html
Harvey Stern, Bureau of Meteorology, Melbourne, Vic., Australia; and B. Campbell, M. Efron, J. Cornall-Reilly, and J. McBride
The Australian Data Archive for Meteorology (ADAM) is used to compare trends in maximum temperature (MAXTEMP) at Sydney and Melbourne with those at other (less urbanised) Australian localities.
By this means, the relative extent to which MAXTEMP increases in those cities can be attributed to urbanisation, the enhanced greenhouse effect, and other causes, is quantified.
The influence of cities on overnight temperatures is well documented. However, their influence on daytime temperatures is less well documented.
Sydney and Melbourne MAXTEMP data are compared with other ADAM data sets and are found to be increasing at a faster rate than elsewhere.
For example, Sydney’s MAXTEMP is increasing at a linear rate that is +0.065 deg C per decade faster than that of Newcastle, whilst Melbourne’s MAXTEMP is increasing at a linear rate that is +0.050 deg C per decade faster than that of Ballarat.
More generally, Sydney and Melbourne MAXTEMP data are compared with ADAM data sets for the 73 Australian localities (excluding Sydney and Melbourne) with at least 80 years of MAXTEMP data during the 100-year period 1910 to 2009 inclusive.
MAXTEMPs at Sydney and Melbourne are found to be increasing, respectively, at rates 0.080 deg C per decade and 0.071 deg C per decade faster than the average temperature at the 73 sites. The probabilities of such large differences occurring by chance is <<0.1% in both cases. That the average MAXTEMPs in the two cities are rising faster than at more rural localities is therefore largely attributed to urbanisation.
For both localities, annual MAXTEMP data are statistically modelled over various control periods using MAXTEMP data at surrounding non-urban stations as input. Thereby, sequences of non-urbanised MAXTEMP can be constructed for the hypothetical circumstance of the cities not being built.
Synoptic stratification of daily data shows that a recent "jump" in the Melbourne series is due to buildings constructed immediately to the south of the site.
In contrast to the current study, Torok's (1996) PhD work identified, and adjusted for, "' jumps in the time series due to non-climatic changes' (and this consequently removed) …urbanisation signals from the time series". Torok's adjustments have been applied to the derivation of the Bureau of Meteorology's high quality data sets (HQDS).
The current study's approach (using ADAM data sets) has been to identify, and preserve, the urbanisation signals in the time series.
As would be expected, MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed).
Now that Warwick’s pointed out the name of the paper (presumably referred to in the media release) I’ve located this info
http://ams.confex.com/ams/91Annual/webprogram/Paper184863.html
Wednesday, 26 January 2011
605/610 (Washington State Convention Center)
Harvey Stern, Bureau of Meteorology, Melbourne, Vic., Australia; and B. Campbell, M. Efron, J. Cornall-Reilly, and J. McBride
The Australian Data Archive for Meteorology (ADAM) is used to compare trends in maximum temperature (MAXTEMP) at Sydney and Melbourne with those at other (less urbanised) Australian localities.
By this means, the relative extent to which MAXTEMP increases in those cities can be attributed to urbanisation, the enhanced greenhouse effect, and other causes, is quantified.
The influence of cities on overnight temperatures is well documented. However, their influence on daytime temperatures is less well documented.
Sydney and Melbourne MAXTEMP data are compared with other ADAM data sets and are found to be increasing at a faster rate than elsewhere.
For example, Sydney’s MAXTEMP is increasing at a linear rate that is +0.065 deg C per decade faster than that of Newcastle, whilst Melbourne’s MAXTEMP is increasing at a linear rate that is +0.050 deg C per decade faster than that of Ballarat.
More generally, Sydney and Melbourne MAXTEMP data are compared with ADAM data sets for the 73 Australian localities (excluding Sydney and Melbourne) with at least 80 years of MAXTEMP data during the 100-year period 1910 to 2009 inclusive.
MAXTEMPs at Sydney and Melbourne are found to be increasing, respectively, at rates 0.080 deg C per decade and 0.071 deg C per decade faster than the average temperature at the 73 sites. The probabilities of such large differences occurring by chance is <<0.1% in both cases. That the average MAXTEMPs in the two cities are rising faster than at more rural localities is therefore largely attributed to urbanisation.
For both localities, annual MAXTEMP data are statistically modelled over various control periods using MAXTEMP data at surrounding non-urban stations as input. Thereby, sequences of non-urbanised MAXTEMP can be constructed for the hypothetical circumstance of the cities not being built.
Synoptic stratification of daily data shows that a recent "jump" in the Melbourne series is due to buildings constructed immediately to the south of the site.
In contrast to the current study, Torok's (1996) PhD work identified, and adjusted for, "' jumps in the time series due to non-climatic changes' (and this consequently removed) …urbanisation signals from the time series". Torok's adjustments have been applied to the derivation of the Bureau of Meteorology's high quality data sets (HQDS).
The current study's approach (using ADAM data sets) has been to identify, and preserve, the urbanisation signals in the time series.
As would be expected, MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed).
As to what that means in terms of UHI adjustments?
I’ve picked this up from Warwick Hughes naming of the report (thanks Warwick)
http://ams.confex.com/ams/91Annual/webprogram/Paper184863.html
Wednesday, 26 January 2011
605/610 (Washington State Convention Center)
Harvey Stern, Bureau of Meteorology, Melbourne, Vic., Australia; and B. Campbell, M. Efron, J. Cornall-Reilly, and J. McBride
The Australian Data Archive for Meteorology (ADAM) is used to compare trends in maximum temperature (MAXTEMP) at Sydney and Melbourne with those at other (less urbanised) Australian localities.
By this means, the relative extent to which MAXTEMP increases in those cities can be attributed to urbanisation, the enhanced greenhouse effect, and other causes, is quantified.
The influence of cities on overnight temperatures is well documented. However, their influence on daytime temperatures is less well documented.
Sydney and Melbourne MAXTEMP data are compared with other ADAM data sets and are found to be increasing at a faster rate than elsewhere.
For example, Sydney’s MAXTEMP is increasing at a linear rate that is +0.065 deg C per decade faster than that of Newcastle, whilst Melbourne’s MAXTEMP is increasing at a linear rate that is +0.050 deg C per decade faster than that of Ballarat.
More generally, Sydney and Melbourne MAXTEMP data are compared with ADAM data sets for the 73 Australian localities (excluding Sydney and Melbourne) with at least 80 years of MAXTEMP data during the 100-year period 1910 to 2009 inclusive.
MAXTEMPs at Sydney and Melbourne are found to be increasing, respectively, at rates 0.080 deg C per decade and 0.071 deg C per decade faster than the average temperature at the 73 sites. The probabilities of such large differences occurring by chance is <<0.1% in both cases. That the average MAXTEMPs in the two cities are rising faster than at more rural localities is therefore largely attributed to urbanisation.
For both localities, annual MAXTEMP data are statistically modelled over various control periods using MAXTEMP data at surrounding non-urban stations as input. Thereby, sequences of non-urbanised MAXTEMP can be constructed for the hypothetical circumstance of the cities not being built.
Synoptic stratification of daily data shows that a recent "jump" in the Melbourne series is due to buildings constructed immediately to the south of the site.
In contrast to the current study, Torok's (1996) PhD work identified, and adjusted for, "' jumps in the time series due to non-climatic changes' (and this consequently removed) …urbanisation signals from the time series". Torok's adjustments have been applied to the derivation of the Bureau of Meteorology's high quality data sets (HQDS).
The current study's approach (using ADAM data sets) has been to identify, and preserve, the urbanisation signals in the time series.
As would be expected, MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed).
What that means in relation to UHI in the HQ data I have no idea
Australis I’m having trouble posting and sent it to Richard Treadgold yesterday
He was I thought going to post it
Oh good that one went through! sorry I can’t copy my PDF file – if anyone who wants it can give me their e mail I can e mail it though;
As to the BOM paper I’ve picked this up from Warwick Hughes naming of the report (thanks Warwick)
http://ams.confex.com/ams/91Annual/webprogram/Paper184863.html
Wednesday, 26 January 2011
605/610 (Washington State Convention Center)
Harvey Stern, Bureau of Meteorology, Melbourne, Vic., Australia; and B. Campbell, M. Efron, J. Cornall-Reilly, and J. McBride
The Australian Data Archive for Meteorology (ADAM) is used to compare trends in maximum temperature (MAXTEMP) at Sydney and Melbourne with those at other (less urbanised) Australian localities.
By this means, the relative extent to which MAXTEMP increases in those cities can be attributed to urbanisation, the enhanced greenhouse effect, and other causes, is quantified.
The influence of cities on overnight temperatures is well documented. However, their influence on daytime temperatures is less well documented.
Sydney and Melbourne MAXTEMP data are compared with other ADAM data sets and are found to be increasing at a faster rate than elsewhere.
For example, Sydney’s MAXTEMP is increasing at a linear rate that is +0.065 deg C per decade faster than that of Newcastle, whilst Melbourne’s MAXTEMP is increasing at a linear rate that is +0.050 deg C per decade faster than that of Ballarat.
More generally, Sydney and Melbourne MAXTEMP data are compared with ADAM data sets for the 73 Australian localities (excluding Sydney and Melbourne) with at least 80 years of MAXTEMP data during the 100-year period 1910 to 2009 inclusive.
MAXTEMPs at Sydney and Melbourne are found to be increasing, respectively, at rates 0.080 deg C per decade and 0.071 deg C per decade faster than the average temperature at the 73 sites. The probabilities of such large differences occurring by chance is <<0.1% in both cases. That the average MAXTEMPs in the two cities are rising faster than at more rural localities is therefore largely attributed to urbanisation.
For both localities, annual MAXTEMP data are statistically modelled over various control periods using MAXTEMP data at surrounding non-urban stations as input. Thereby, sequences of non-urbanised MAXTEMP can be constructed for the hypothetical circumstance of the cities not being built.
Synoptic stratification of daily data shows that a recent "jump" in the Melbourne series is due to buildings constructed immediately to the south of the site.
In contrast to the current study, Torok's (1996) PhD work identified, and adjusted for, "' jumps in the time series due to non-climatic changes' (and this consequently removed) …urbanisation signals from the time series". Torok's adjustments have been applied to the derivation of the Bureau of Meteorology's high quality data sets (HQDS).
The current study's approach (using ADAM data sets) has been to identify, and preserve, the urbanisation signals in the time series.
As would be expected, MAXTEMP rising trends in the Melbourne and Sydney HQDS (with the urbanisation signals removed) are found to be slower than those in the corresponding ADAM data sets (without the urbanisation signal removed).
Hmmm…what that means in terms of adjustments who knows
Australis: In the meantime check out the papers referred to by Warwick Hughes above.
I suppose you have seen this ten year old paper:
“Urban heat island features of southeast Australian towns”
http://www.bom.gov.au/amm/docs/2001/torok_hres.pdf
Then there is our 64 station review by Hughes and Balling, “Eastern Australia temperature variations 1930-1992″
http://www.warwickhughes.com/papers/eastoz.htm
The page 19 graphic;
http://www.warwickhughes.com/papers/Hbeoz19.gif
sums up changes in mean T and DTR for stations with population ranging from 1000 up to a million and more over Eastern Australia.
Val:
I’ve only just had the time to take a look at this. Thanks for letting me know about it! Your posts went to the spam folder. The problem was with the large number of links in the post; as it’s a characteristic of spam, it triggers the spam detection software. I’ll investigate to see whether I can exempt posts for particular senders, then it will stop being a problem for you.
I had a quick look at your posts and there seem to be differences between them; I don’t have time to compare them word for word, so identify any duplicates you want deleted and I’ll get rid of them.
If you notice your post vanish in future, do send me an email directly, because I don’t see the spam comments any more. I had to put a stop to it, since the site gets up to 200 – 250 spam messages a day.
Cheers.
Thanks Richard; I think I sent very similar posts yesterday at 7.28 pm & 11.18 pm yesterday (16/11); they’re basically the same as the one I sent today (17/11 at 8.32 am) so delete whichever ones you want; or leave them; up to you
In relation to the BOM as yet unpublished paper I think Warwick Hughes has nailed it “I doubt if any of us common herd will ever get to see the ADAM data)
In the meantime Australis is asking for the Torok paper I e mailed to you yesterday; could you post that in the article; as you know it’s 10 pages
The Torok paper is added now to the Files area and mentioned as an update to the post. Thanks to you, Val, and Ken Stewart.
I picked up this very interesting paper from a commentator at Dr Marohasy’s site
(thanks cohenite)
http://landshape.org/images/StockwellCSP.ppt.pdf
Negating climate change policy by
Dr David RB Stockwell, former consultant to the
Australian Government, biodiversity scientist at
San Diego Supercomputer Center, University of
California San Diego and the University of
California Santa Barbara, publications in major
journals with over 1000 citations
Here’s his website http://landshape.org/about-the-author/
There’s a comment there by Warwick Hughes referring to this page
http://landshape.org/enm/inquiry-into-long-term-meteorological-forecasting-in-australia/
The Committee recommends that CSIRO and the Bureau of Meteorology provide to the Australian Government a report with detailed explanatory information as to why a particular dynamic forecasting model or system was chosen for use in Australia. The report should be completed by the end of 2010.
As Warwick says something to watch for
and here’s another fascinating link (thanks el gordo)
http://www.holtonweather.com/WHAT%20IS%20THE%20MAIN%20FACTOR%20CONTROLLING%20THE%20MURRAY%20DARLING%20BASIN%20SYSTEM%20RAINFALL.pdf
conclusions:
The results show that the Sinusoidal Solar-Lunar Cycles have controlled the general Murray Darling Basin (South QLD-NSW-VIC-SA) Rainfall Trends from 1900 to 2006….During the critical Autumn to Spring & River- Dam inflow- Irrigation and Dry-land farming period….And the most helpful information about this close connection, is that we are able, from the Copeland and Watts Sinusoidal Model, to forecast with a high degree of confidence the next 30 years or so Murray Darling Basin General Rainfall & Dam Inflow Trends…As the future plotted Sinusoidal Model Trace is based on regular and recurring cycles that have not altered significantly in the past, and should not alter significantly in the future…..Therefore, any general Murray Darling Basin Southern Wet Season General Rainfall Trends that we can forecast from the Sinusoidal Solar-Lunar Model are highly likely to be accurate general trend rainfall & dam inflow forecasts.
It is the firm opinion of the author that weather, ocean and rainfall patterns are cyclic. They always have been, and always will continue to do so…….And that any dire predictions of continuing & worsening drought in the Murray Darling Basin, and in fact in any region of Australia, are entirely unfounded.
Val
I was astonished at the candour of BOM in this quote:
“MAXTEMPs at Sydney and Melbourne are found to be increasing, respectively, at rates 0.080 deg C per decade and 0.071 deg C per decade faster than the average temperature at the 73 sites”.
So large cities experience UHI effects at the average rate (for daily maxima) of approx 0.75°C/century. As Belinda Campbell pointed out, the effects on daily minima are better known, and therefore probably greater.
Ergo, the UHI effect in large cities is greater than the total global warming recorded during the past century. Whether the effect is the same in smaller urban areas is not known, but the authority cited by Richard C suggests it is even greater in faster growing towns. And it is notable that BOM purportedly exclude ALL towns with populations above 10,000.
This seems to put paid to the murky paper by Jones & Wang (1992?) which has underpinned all the IPCC temp conclusions for nearly 20 years.