Readers recall that I carried a guest post from Dr. Roy Spencer on what he learned from analysing the CRUTem3 data: Spencer shows compelling evidence of UHI in CRUTem3 data.
Now he has turned his attention to what I consider a better data set – the ISH data set, and comparing it to CRUTemp3 the results are surprising.
He writes:
The impact of making regional — rather than whole U.S. — population adjustments on the U.S. average temperature variations results in only a slight increase in the resulting temperature trend I posted yesterday, which is still well below that computed from the CRUTem3 dataset (click for high res. version):
Here are the population-adjusted temperature variations for the 3 northern U.S. sectors, with just the trailing 12-month averages plotted to reduce the messiness:
…and here are the 3 southern U.S. sectors:
The bottom line is that there is still clear evidence of an urban heat island effect on temperature trends in the U.S. surface station network. Now, I should point out that most of these are not co-op stations, but National Weather Service and FAA stations. How these results might compare to the GHCN network of stations used by NOAA for climate monitoring over the U.SA., I have no idea at this point.
Also, I need to clear up a misconception…the adjustments I perform do not remove the trends in the data. They remove only the component of the trend which is due to population density, using the regression coefficient alone (not the regression constant). There are no adjustments in January 1973 (the beginning of my data record), and then the adjustments increase linearly with time.
More at:
Regional U.S. Population Adjustments to Surface Temperatures Since 1973: Still Little Warming
If you wish to examine UHI, you need a set of weather stations that are plausibly without UHI, to act as a baseline. I studied about 44 carefully culled candidates in Australia from the year 1972 to 2006, the former being the year of change from recording deg F to deg C.
It was not possible to find a baseline “climatic” rate of temperature change in pristine sites because of the noise, which I tried to correlate with other factors, the best correlation being longitude for T max (but not for Tmin). See graphs at base of sheet 2 of the URL below.
If you can’t construct a baseline, then you can’t look for increases caused by UHI. Simple as that. Here are the data if you wish to play with them.
http://www.geoffstuff.com/Pristine_Summary_1972_to_2006.xls
What about satellite-based lower troposphere global and regional temperature
anomaly indices? Such as UAH and RSS? Surely, those are hardly prone to
UHI effects. Global UAH and RSS lower troposphere show warming trend since
beginning of 1979, at rate of .13-.135 degree/decade.
This would indicate climate sensitivity to CO2 change roughly 2 degrees C/K
per 2x CO2, except that a periodic component having period ~60-65 years is
easily visible in HadCRUT3 and explains some of this. That appears to me to be
some combo of AMO, PDO, and a ~60 year solar cycle that may only be in
existence temporarily. Therefore, I like to see current global climate sensitivity
to CO2 change being much less than 2 degrees per 2xCO2. Some works I have
done indicate anywhere from .67 to 1.5, as opposed to 3 that IPCC favored in
AR4.
Another thing: Lower troposphere as considered by satellite data appears to
me to over-50%-consider everything below the 500 millibar level, and to give
~7-8% of peak consideration to the 300 millibar level. Increase of GHGs
increases the lapse rate in the troposphere globally, and especially in the
polar regions, mainly the Arctic. Therefore, recent-decades warming in the
Arctic at surface level should indeed be greater at surface level than according
to lower troposphere satellite-based indices.
But then again, upticking of status of AMO also warms the Arctic, and does so
more at surface level than above the 700 millibar level.
What about satellite-based lower troposphere global and regional temperature
anomaly indices? Such as UAH and RSS? Surely, those are hardly prone to
UHI effects.
It depends on what causes UHI. If I’m correct and its a atmospheric aerosol/cloud effect, then there will be a lower troposphere effect as well. You see this in the dry season data from India. Although the sign of the troposphere aerosol effect is opposite to the surface data.
It also explains the satellite surface divergence.
http://rogerpielkejr.blogspot.com.au/2009/08/evidence-that-global-temperature-trends.html
I was recently at a small airport in Northern Ontario (population under 3,000). A number of newer large buildings surrounded the older weather station around which was entirely paved. On the days we were there the snow plow (a large diesel front end loader) was parked in front of the weather station warming up before clearing the runway. The wind sock didn’t work anymore (too many buildings nearby) so they erected a new one further away from the terminal. Many of the rural airports I’ve visited in the past 10 years have been paved as part of local infrastructure upgrading. Not sure that it means anything.
DocMartyn: Closed military bases are hardly going to be “deurbanized” in our lifetimes, especially ones that are currently “urbanized”. Most bases closed in the last 40 years have been at least partially reused for industrial purposes. I would dare say none of the bases closed in the US since the 1960s have reverted to pre-construction conditions.
Robert Austin @ur momisugly 2:00
Steve from Rockwood’s response above partly answers your question. If the area in question hasn’t had a population increase approaching 10 times the number, or if the infrastructure has not changed, then you’re right and there should be no real change. In practice, how many airfields or roads were tarmac or pavement 100 years ago compared with today? How many building level heat exchangers (air conditioning units) were in use 100 years ago to artificially raise the temperature immediately down-wind from the buildings?
Here in Calgary, Alberta we had a couple of inches of snow mid-week that has slowly been melting ever since. The roads and sidewalks were all clear the next day (pavement, heat absorption, albedo, etc). The snow melt progressed from these initial melt points onto grassy areas. Now all that is left with snow are areas that are sheltered from wind and direct sunlight. When I go for a walk to a large park area, I see the same trends in how the snow melts, but there is more snow around because the primary melting items (pavement etc) aren’t found there.
While Dr. Spencer’s plot of temperature vs. time presents us with data points of large number, the more pertinent question is of the number of independent statistical events that have been observed in the interval between 1973 and 2012. In climatology, the canonical duration of an event is 30 years. In Spencer’s data, there are at most one of them. At least, there are zero of them. In either case, generalizations from events as few as 0 or 1 cannot be made.
Doug Proctor says:
April 8, 2012 at 8:04 pm
If you simply compare the solidly urban data pre-adjustment to post-adjustment, there should be a DECLINE in values reflecting a UHIE correction. If there is no negative difference, then a UHIE was not done.
Top 50 urban centres, before and after: what is that like?
Hansen et al say they have correctly adjusted for UHIE. You should quickly be able to see what they did. I have no clue.
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Why the heck do you think Phil Jones said “The dog ate my homework” and all the Climate “Scientists” have fought tooth and nail to prevent anyone from seeing what goes on in the “black box” they use for messaging and adjusting the data.
“A Goat ate my Homework” – NIWA
Here is Hansen’s revisionist corrections on temperature.
Blink graph US temp data: http://i31.tinypic.com/2149sg0.gif
US temp raw vs adjusted: http://i31.tinypic.com/5vov3p.jpg