New paper: UHI, alive and well in China

the australian labour gov,t has stooped to a low low act they have visited nursing homes and retirement villages and told them that due to sea level rise they will all be under water and will have to move to higher ground, this to me is a low act ? what do you think of this act

This paper appears to reconfirm what many suspect, namely that UH is significant AND it has played a part in the recent appearance of warming these past 30 years or so.
I know that we will soon see a number of the ‘usual’ posts suggesting that since we are looking at anomalies and not absolute temperatures, the overall trend is unaffected and that the statistic of large numbers cancels these anomalies out. Personally, I consider such arguments to be bunkum although I do accept that once a temperature measuring station has been fully swamped (saturated) by the effects of urbanisation, thereafter, but only thereafter, the anomalies will become little affected by UHI. .
It may be the case that in stable urbanisations, UHI, whilst having an effect on absolute temperature, has little effect on anomalies. This begs the question; when and which urbaisations are truly stable? In the UK, for example, there has been much urban sprawl since the 1950s AND there have been many new towns being built in what were once rural locations. Even in the Capital, as regards places like Kew Gardens and Heathrow, which are used for temperature measurements, these are very different places to what they use to be in the 1940s and 1950s. Likewise, areas that were once war time air strips are now radicially different and even in places which are not growing laterally, they are growing upwards with ever increasing high rise buildings. Just think how office blocks have changed these past 50 or so years with better heating, better aircon and often with electric lights left on 24/7. The idea that this is not ‘polluting’ the temperature record is niaive at best, if not damn right facetious.
Further, even if surburbia has not changed much in area, life style has certainly changed these last 40 or 50 years and these life style changes are also have an effect.. For example in the UK, back in the 1950s, central heating was extremely unusual, now it is almost universal. In the UK, houses are not well insulated and they must be pumping out much heat which was not being produced in the 1950s. Gardens which were once laid with lawn and flower beds, have been paved over to be used as parking spaces for cars which paved areas now act as storage heaters radiating warmth in the evenning.. Indeed, the increase in car use alone adds to the temperature (just think of all the hot engines coming home at 7 to 9pm at night and giving off heat for many hours). Shops and businesses which once closed at 5pm and were not open at all at the weekend, are now open 24/7. The reality is that semi-rural and surburban life style is very different compared to just 40 or 50 years ago and this is playing a role in the recent ‘apparent’ land based temperature record.
In fact, one probably only needs to look at how energy consumption has increased, these past 50 years or so, to see how much development there has been, and how much additional heat energy is being pumped into the general vacinity and which inevitably is being picked up by temperature measurement stations and is influencing the temperatures recorded.
These type of research is very useful and in turn it means that there needs to be a close and careful re-examination of the temperature record to check and see how and whether adjustments for UHI are being properly and rigourously being made. , .

Tango,
Exactly who in the Labor (not Labour) government visited what nursing homes and retirement villages and when ? Sounds a bit alarmist to me.

Tallbloke writes, “Stitch that, Phil Jones.”
Jones has written that the UHI effect is quite small and is part of why the IPCC AR4 wrote:
“Studies that have looked at hemispheric and global scales conclude that any urban-related trend is an order of magnitude smaller than decadal and longer time-scale trends evident in the series (e.g., Jones et al., 1990; Peterson et al., 1999).”
There were questions raised about the China data, and Jones later came around to the UHI side, agreeing with higher estimates, writing “Urban-related warming over China is shown to be about 0.1°C decade-1 over the period 1951–2004, with true climatic warming accounting for 0.81°C over this period.”
Urbanization effects in large-scale temperature records, with an emphasis on China
http://www.agu.org/pubs/crossref/2008/2008JD009916.shtml
This UHI effect thus accounts for 40% of the measured warming.

There is nothing “common” about Common Sense in the 21st Century. It’s more rare than Gold. UH is THE Missing Link in the AGW Mumbo-Jumbo Hoop-La; it has been since AGW was first created. Of course one does have to subtract the natural rise in global heat following the Little Ice Age, which technically hasn’t ended, but which some think ended in the late 19th or early 20th centuries. Oh well, that’s why history books never go out of style. People always love to read how stupid their parents and grandys and greats were. Of course too much history is not good for the soul and leaves a pessimistic taste in your mouth too.

But, but, but, true to form the BBC in the UK was giving priority to some loons who are rowing to the North Pole. It had all the usual trimmings too, disappearing ice, how different it looks and, incredibly, how hot it is in the Arctic Circle!
Nearly choked on my coffee.

Professor Wei-Chyung Wang of the State University of New York at Albany will probably have no comment on this story.
And I’m sure Professor Wei-Chyung Wang of the State University of New York at Albany will continue to withhold the temperature measurement locations that he used to claim that UHI was minimal in China.
http://wattsupwiththat.com/2010/02/01/climategate-intensifies-jones-and-wang-hid-chinese-station-data-issues/

SteveE says:
July 28, 2011 at 3:35 am
An interesting statement, … I’ve only seen studies showing that the trends are the same in both rural and urban site over the last ~50 years in both China….
Interesting statement. What studies other than the one that involved Professor Wei-Chyung Wang of the State University of New York at Albany?

Verity Jones says:
July 28, 2011 at 6:02 am
Studies have shown that even small populations near a temperature sensor can and do affect the reading. On the other hand, the IPCC seems to consider any town smaller than 100,000 to be rural.

“but even then 75.8% of the warming is from other sources”
Even the IPCC admits that changes in solar intensity account for 20 to 30% of the warming.
Then there is the all but confirmed cosmic ray/cloud formation factor.
There there is the documented problems with the ground based temperature network causing a warming bias.
All in all, not much of the signal is left for CO2 to be responsible for.

@ Mark Wilson – you are going random math again.
I don’t think you’ll find an mainstream climate scientist claiming that CO2 is responsible for 100% of the warming. What you will find is that it is an important forcer that gets augmented by other GHG.

Kev-in-Uk,
I think that there are interesting leads. Böhm et al. 2001 is a great door. To pass with care.

phi says:
July 28, 2011 at 12:52 pm
I am not sure of your point – I just quickly googled Bohm et al 2001 and it would appear from the abstract that they are suggesting a mean temp trend increase over and above what CRU produce. Presumably, in the Alps, this would not be due to UHI – I will have to look for a direct link to the paper and it’s graphs. Nevertheless, I am still perturbed by the references in the abstract to various statistical analysis and homogenisation……
I am fairly convinced (as a geologist – who deals with ‘spatial’ awareness!) that spatial determination and averaging is a very subjective and locally specific problem – meaning that ‘local’ weather/conditions are reflected by local topography, prevailing winds, station siting, etc, etc. My own simple analysis of the UK station data (off the metoffoce site) shows an amazing difference from west coast compared to east coast stations (this is totally to be expected BTW) – Ergo, a direct ‘averaging’ of the two would not necessarily be representative. I don’t really consider that ‘gridded’ data are valid in any significantly varying topographical area. A couple of stations in the sahara desert are more likely to be similar than a couple of stations either side of the english channel for example – yet the channel only spans 20 miles!
I am not overly familiar with all the statistical methods – and I really don’t have the inclination to learn it in detail at my age! – but on the simple points regarding UHI, a station within an urban sprawl must logically be affected by that urbanisation. IMO – Rural stations should be ‘king’ in the real data world, because adjustments for UHI, if and when applied, are highly likely to be subjective. Taking a very basic and simplistic view of averaging say, 2 rural stations with say 6 urban stations to give a gridded average must introduce a bias. Personally I’d suggest ignoring urban stations altogether (or at least use them only for indicative purposes). I think, though I accept I may be challenged here – that basic and trusted data (i.e known to be unaffected by UHI) should always be the ‘preferred’ data – that fact that some airport or other has reams of data – does not automatically make that data any better (probably worse in some sense!) than some rural station manned by a couple of old codgers with thermometers! In terms of actual individual station data, I would prefer to see each station analysed seperately – if you like, with each plot overlaid onto a base graph – then you would see which stations were grossly affected by UHI as those stations would show markedly different trends – whereas simple UHI ‘adjustment’ and then averaging them altogether is likely to introduce a bias in my opinion (could be either way depending on how good the UHI adjustment is guessed!) and so what value would one put on the resultant ‘combined’ average plot?. I am reasonably sure that if anyone actually plotted all the UK stations on a graph, one would see a range of trends, with most/all the higher trends being in the urban stations – and lower trends in the rural stations – in effect, I wouldn’t be surprised to see two distinct ‘bands’ emerging, and logically THAT, not direct comparison between an urban station and its nearest ‘rural’ neighbour – would provide a realistic indication as to the likely UHI effect? Has anyone ever done this?

phi says:
July 28, 2011 at 3:19 pm
thanks – I will try and get a few hours together to read through…(unlikely as too much work – but I will try, honest!) – but I hope you can understand my (probably badly presented) suggestion, that a graphical representation of essentially raw data from various stations superimposed together should easily identify the trend differences between urban and rural stations. (This being infinitely more preferable that a direct averaging of rural/urban stations)
Even if it just shows a concentration of urban stations in a different graphical position to the rural stations, this would give an empirical indication of the UHI value. I just feel this provides a more realistic assessment of the actual levels of UHI in the overall sense, yet I have never seen such a graph…
I am thinking of a way to plot it in such a way as to be indicative – perhaps the simplist way would be to set the opaqueness and/or colour of the plotted station line according to its urban/rural status. e.g. urban sites could be red hued and rural sites more blue hued – whats the betting that the redsites would be grouped together etc – and the blue hued sites would show a lower rising trend than the urban sites?

richard verney says:
July 28, 2011 at 2:39 am
“I know that we will soon see a number of the ‘usual’ posts suggesting that since we are looking at anomalies and not absolute temperatures, the overall trend is unaffected and that the statistic of large numbers cancels these anomalies out. Personally, I consider such arguments to be bunkum although I do accept that once a temperature measuring station has been fully swamped (saturated) by the effects of urbanisation, thereafter, but only thereafter, the anomalies will become little affected by UHI.”
I applaud your excellent post. You are way too kind to the Warmista. No temperature station has ever been fully swamped by the effects of urbanization. Warmista must learn that as the Gates of Hell are widened so the temperatures are raised proportionately. Urbanization is not a one-shot proposition like clear cutting a forest or damming a river. Urbanization is ongoing. As your truck stop succeeds, it will get busier and larger indefinitely and it will attract other truck stops. (We all know the principle that if you want to open a new book store you should open it next door to the most successful existing bookstore.)
Anomalies are just tricks for avoiding actual empirical observations and better hiding the pea.

Steven Mosher,
I wouldn’t worry about whether they have the correct nightlights or not. Just the fact that they found a number of stations that have trends about .25c more than a bunc of others shows that your mantra about it not mattering is unsupported in other than the contaminated, overadjusted surface records.

A couple of people have asked about other Rural – Urban comparisons, particularly the “Peter and his Dad” comparison covered here on WUWT in 2009. In that comparison, Peter & Dad extracted temperature data for 28 location ‘pairs’, one Urban and one Rural, spread around the US for years 1900 -2006. http://wattsupwiththat.com/2009/12/09/picking-out-the-uhi-in-global-temperature-records-so-easy-a-6th-grader-can-do-it/
I repeated the data extraction and cleanup as described in that article.
Here is what came from the analysis:
Rural 0.57/century C
Urban 1.07/century C
More results comparing Rural and Urban temperatures at the 28 paired sites, all in DegC:
……………….Rural ……..Urban
Minimum …….5.8………….7.2
Maximum ….22.4…………23.3
Average……..13.1…………14.3
As others have pointed out, the slopes of temperature change per time are probably more important than the averages, since there may be true siting differences in some pairs. Additional poking at the data showed no particular trends in the slopes based on warmer or colder areas in the paired sets.
*There are 6 of 28 (~20%) Rural negative slopes (cooling).
*None of the Urban temperature slopes are negative/cooling.
*Five of the Rural slopes are higher than the corresponding Urban slope (almost 20% of pairs), which also means that those five Urban slopes are lower temperature change than the corresponding Rural slope.
for what it’s worth.

Heres a compare for East China urban-stations vs rural:
http://hidethedecline.eu/media/ARUTI/Asia/China/fig21.jpg
– taken from the new RUTI project (see China)
http://hidethedecline.eu/pages/ruti.php