New Paper “Climatic Trends In Major U.S. Urban Areas, 1950–2009″ By Mishra and Lettenmaier
By Dr. Roger Pielke Senior
There is a new paper
Mishra, V., and D. P. Lettenmaier (2011), Climatic trends in major U.S. urban areas, 1950–2009, Geophys. Res. Lett., 38, L16401, doi:10.1029/ 2011GL048255
which reports on the effect of urban areas on multi-decadal surface temperature trends.
The abstract reads [highlight added]
We evaluate changes in climatic indices for the 100 largest U.S. urban areas and paired surrounding non‐urban areas. During the period 1950–2009, we find that there were statistically significant changes in as many as half of the urban areas in temperature‐related indices, such as heating and cooling degree‐days and number of warm and cool nights, almost all of which are reflective of a general warming.
Similarly, statistically significant changes (mostly increases) in indices related to extreme precipitation, such as daily maximum intensities and number of days with heavy precipitation, were detected in as many of 30% of the urban areas. A paired analysis of urban and surrounding non‐urban areas suggests that most temperature‐related trends are attributable to regional climate change, rather than to local effects of urbanization, although the picture is more mixed for precipitation.
Among the conclusions
Consistent with previous studies [Easterling et al., 2000; Kalnay and Cai, 2003], trends related to temperature minima in the urban areas are generally stronger than those related to temperature maxima.
For both minimum daily temperature based climate indices and precipitation‐related trends, changes in urban and non‐urban areas are generally consistent; suggesting that the trends are dominantly a response to climate [Parker, 2004; Peterson, 2003], rather than local land cover changes during the period of analysis. However, there is somewhat less consistency in urban vs. non‐urban trends in climate indices related to daily maximum temperature, which suggests that land cover change may be at least partially responsible for those trends.
An important caveat to their study is that they have not factored in the role of microclimate changes at the observing sites which we have started to explore, as reported on in our paper
Fall, S., A. Watts, J. Nielsen-Gammon, E. Jones, D. Niyogi, J. Christy, and R.A. Pielke Sr., 2011: Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends. J. Geophys. Res., 116, D14120, doi:10.1029/2010JD015146.Copyright (2011) American Geophysical Union.
Their finding of less of an effect on minimum temperature trends on whether they are located in urban or rural areas is, however, puzzling, as the urban heat island effect on minimum temperatures is very well know (e.g. see EPA heat island effect). Since the spatial scale, density of build-up and type of constructions on urban areas continues to change over the time, the failure to find a difference between rural and urban areas needs more investigation as to why this was found in the Mishra and Lettenmaier analysis.
I recall someone leaving this youtube video at this site. The video is about 3 years-old. It is worth viewing again
http://www.youtube.com/watch?v=LcsvaCPYgcI&feature=player_embedded
Congrats Anthony, Roger, John’s and others!
Is this paper complimentary to Menne et al 09?
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Edit notes:
“is very well
know” known“build-up and type of
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whay” whyIt will be interesting to compare these results to those of the Berkeley Earth Surface Temperature project. They’re also trying to determine the effects of the UHI. There was mention at Climate Etc. that papers were close to being submitted, and the work will also be presented at the AGU. The abstracts don’t suggest large differences between their estimates and those of other groups. Some snippets:
ABSTRACT FINAL ID: GC43B-0908
”Applying the Berkeley Earth techniques, we broadly confirm the temperature histories presented by prior groups. However, the improved methodology allows the uncertainties to be reduced (often by 50%) and also has allowed the instrumental temperature record to be extended back to 1800.”
ABSTRACT FINAL ID: GC44B-01
”The results we obtain are compared to those published by the groups at NOAA, NASA-GISS, and Hadley-CRU in the UK.”
These sorts of studies seem to all be using already available data, simply massaging or modeling such data in different ways.
I really am only interested in doing actual experiments, you know, actual science.
The method would be simple, you need, say a camper, and some portable climate measuring equipment (or even just a calibrated temperature measurement device of the same type used in official stations). Then, drive out from the city you are comparing urban versus rural temperature at, find a suitable site in a rural area as close to said urban city as possible, take measurements for say 24 hours (hence why you need the camper), then compare those to the official measurements in the urban environment.
I am willing to bet that there will be a noticeable and significantly lower temperature overall in the portable rural site compared to the nearby urban site. Any other method other than the above is just shuffling data around and is not an actual scientific experiment or using the actual scientific method which could be said to be “you say you believe X, SHOW ME”.
They just talk about the increases in the urban setting and are silent on changes (if any) at the rural pairings – at least that is what I’m reading in this summary. Am I wrong?
last paragraph, first sentence, fourth word. “less” rather than “leass”?
[Fixed. Thank you, Robt.]
Ray Spencer is vindicated again.
Wear your scars with pride Dr Spencer.
Note also in AGU abstract GC44B-01 that Anthony Watts is acknowledged specifically!
“…We calculate the effect of poor station quality, as documented in the US by the team led by Anthony Watts by estimating the temperature trends based solely on the stations ranked good (1,2 or 1,2,3 in the NOAA ranking scheme). “
I find the wording somewhat confusing frankly.
1. “…there were statistically significant changes in as many as half of the urban areas in temperature‐related indices…”
OK. So what about the other half? And what does “as many as” mean? 40% I understand, 1/2 I understand, but how many does “as many as half” actually mean?
2. “… trends related to temperature minima in the urban areas are generally stronger than those related to temperature maxima…”
OK…was that true for non urban areas as well?
3. “…For both minimum daily temperature based climate indices and precipitation‐related trends, changes in urban and non‐urban areas are generally consistent…”
OK…so it sounds like urban and non urban were about the same then?
4. “However, there is somewhat less consistency in urban vs. non‐urban trends in climate indices related to daily maximum temperature, which suggests that land cover change may be at least partially responsible for those trends.”
Well that one at least makes sense. Maximum temps occur in day time when things like tar and pavement and on and on are absorbing heat from the sun that would otherwise be reflected. But at night, cooling prevails as the dominant process which is going to be predicated on how much heat built up during the day, and how easy it is for that heat to escape. So even with NO effect from GHG’s, I would expect daily minimums to increase more in urban areas than in non urban.
But without knowing exactly what was meant by “as many as half” and what the results were for the OTHER half, not to mention strength of prevailing winds which would move the warm air from the urban to the downwind non urban… which would futz up oh….given the variability of prevailing winds and the likelihood that the rural pairs were downwind…about 50%? As many as half I mean?
Nothing too surprising here. if you select 100 major urban areas in the US and compare them to their rural partners you will find differences. Heck a random blogger did this over a year ago using all of GHCN not just the US
http://residualanalysis.blogspot.com/2010/04/urban-heat-island-effect-model.html
the cutoff he found was a population of 1 million. making a cutoff on raw population size is probably not the best way to do things as it doesnt take area into account, so its probably better to look at population density. density drives the things that drive UHI. It will be interesting to see which 100 cities they used.
Its also import to note ( after Imhoff and Oke ) that the characteristics of the rural environment are just as important as the characteristics of the urban environment.
the hundreds of thousands of tons of asphalt, concrete, sidewalks, and building surface area per square mile of a city absorbs vast amounts of heat that simply must skew the urban temperature record. as air moves over and beyond urban area, it carries that heat elsewhere. i’d be willing to bet that rural areas in the prevailing downwind path of a large urban area also show a similar warming trend. the null hypothesis, i think, would be to compare the temperature trends when the wind is blowing the opposite direction.
it’s fascinating to see a weather front move into the dc area on the local weather radar and watch the storm immediately and severely intensify as soon as it passes into the much warmer urban areas.
thumbnail calculations of the btu storage capacity of a dense, urban fabric indicate staggering quantities of heat storage capacity. rural areas don’t have this component, and it simply has to make a measurable difference.
thanks for all your hard work, anthony – love coming here for a good read.
Their finding of leass of an effect on minimum temperature trends on whether they are located in urban or rural areas is, however, puzzling,
I think that needs to be reworded as its meaning isn’t clear.
If it means they found less of an effect (ie increase) in minimum temperatures in rural areas then that doesn’t surprise me as I believe much of the change in minimum temperatures is due to reductions in near horizon particulate pollution (smoke and haze) causing earlier (in the day) and hence higher minimums.
There is a clear seasonality difference between the sources of particulate pollution in urban and rural areas. In the 1950s and 60s smoke haze from fires would be predominantly in the winter in urban areas, but predominantly in the late summer in rural areas from crop residue burning.
There is also a regional difference as domestic coal fires were replaced earlier in the USA than in Europe. And I would expect a larger increase in min temps in Europe compared to the USA since 1950.
Changes in ocean surface temperatures are the principal cause of climate change. In many regions of the world, there is a distinct ‘ocean signature’ in the weather station record. In California it is the Pacific Decadal Oscillation (PDO). In the UK/W. Europe it is the Atlantic Multidecadal Oscillation (AMO). The minimum daily air temperature is basically a measure of the bulk air temperature of the local weather system as it is passing through. The daily maximum temperature is a measure of the convective coupling of the solar surface heating to the air temperature. By comparing the long term (5 year) average of the ocean temperature (PDO, AMO etc.) to the average of the weather station minimum temperature over the same period of record, an estimate of the urban heat island effect can be obtained. This can be done just using a linear fit to the data, although care is needed and there can be other sources of bias in the data. The difference in slope between the ocean data and the weather station min data provides an approximate measure of the UHI effect.
The technique has provided useful UHI data for California and UK weather stations.
Further details can be found at:
http://scienceandpublicpolicy.org/originals/pacific_decadal.html
http://hidethedecline.eu/pages/posts/what-surface-temperature-is-your-model-really-predicting-190.php
Steven Mosher,
I’m thinking of looking in greater detail at all of the sites I sent you from OZ that I had arbitrarily characterised as ‘pristine’. Then it occurred to me that you might have done this in the wider BEST calculations?
Have you, or will I?
It’s handy to have a set of ‘pristine’ stations covering a large land area, where the chances of effects from the hand of man are credibly small. Sets a baseline of sorts. Lets one look at relative trends of Tmax and Tmin. Would suggest this because a preliminary look was fruitful, but personal computing power is small.
This seems to part of a pattern to downgrade the importance of urban size and morphology in urban temperature measurement, and example of this is this attempt to quantify the “weekend effect” by our old friends here. “Trend” is mentioned 6 times in the above abstract and in the title.
I can’t see what the big deal is here, temperature ‘trends’ in rural and non-rural area should follow a similar pattern, be it up or down, we are all part of land based micro-climates.
Trend is a bit of a broad brush, I take it to mean the continuation of a pattern, are they really talking about correlation?
Seems like a justification to continue urban temperature measurement and ignore the critics,
.
At some point there will be a collation of all these different differences between the IPCC CAGW story and the Real Climate story, I expect …
Clouds. Cosmic rays. UHIE. Satellite/sea-level. Deep-sea temperatures/ocean heat. Storm frequency.
To name just a few.
Paul Irwin says:
the hundreds of thousands of tons of asphalt, concrete, sidewalks, and building surface area per square mile of a city absorbs vast amounts of heat
That’s before you even consider that cities tend to also be full of artificial heat sources
The woman in the picture is a climate expert – she is outstanding in her field.
Seems this woman has many sheep to herd 😉 – yawn ZZZzz…
A bit of common sense is called for here. If I was to carry out temperature readings to prove or disprove global warming, the last place I would take measurements is in a city. The buildings, asphalt, cars etc will absorb more radiative solar heat during sunny days and then radiate it at night. This will not happen in rural areas, simply because grass, trees and shrubs could not heat up to the same degree because their biochemical processes keeping them alive would cease. In addition, in summer, heat from air conditioning units would raise the ambient temperature, likewise with central heating in winter. Cars, buses, lorries and to a lesser extent humans will also raise the ambient temperature.
If this pitiful excuse for a study demonstrates “scientific” reasoning, God help us all.
The comparison should not be rural vs urban 1950 to now. It should be *rural in 1950, urban now* vs. *rural 1950, still rural now*. I would expect the trends in places whose land use hadn’t changed over the last 60 years to be the same, whatever they were over the period.
Most UHI will take place as rural sites *begin* to develop. Stable urban will not show much additional warming.
Also, “rural” – what does that mean? Primeval forest is rural, so is open farmland. But the latter has higher daily mean temps and lower night time temps.
Did they archive their sites?
davidmhoffer, I agree with you, the language is not clear and leaves room for interpretation.
I have noticed more and more of this sort of language appearing in papers as the evidence for catastrophic human induced warming fails to make an appearance. We see papers which present evidence in such a way that the language used to describe it can mean “we looked for evidence of increasing man made warming but found diddly squat” but also allows the researcher to dispute that and claim, “that is not what we meant and we support the consensus” when they need more funding.
From Paul Irwin on September 21, 2011 at 9:13 pm:
Heck, just a mere hundred pounds or so of concrete or asphalt can affect the temperature record, when located right underneath the temperature measuring device. 😉