While NCDC’s Dr. Thomas Peterson tries to ignore UHI, from Hans Von Storch at Die Klimazwiebel (h/t to Jos de Laat) we learn that many other people are actively measuring it. WUWT reader may remember my “do it yourself UHI kit” for vehicles…now there’s one for a bike:
Studying urban heat island effect on a bike
It is long known that in cities there may be a significant climatic effect due to urbanization – thus in cities we have the interesting and challenging task of determining at least three significant drivers for change, if not more, namely the effect of the local modification of the environment as well as the local manifestation of global change due to greenhouse gases (plus, possibly other global factors). Unfortunately, systematic studies about the determination and separation of these effects – in principle a detection and attribution task – have not been done often. At least, I am not aware of such efforts; indeed even studies only on the size and distribution of the urban heat island effect (UHI) are not done often; in Hamburg, a first study was only published in the last few years – before that one could hear that in a maritime climatic environment as Hamburg, the effect would be negligible. It is not.
Now, an innovative study is about to be published – see the manuscript here: Measurement and statistical modeling of the urban heat island of the city of Utrecht (the Netherlands) by Theo Brandsm and Dirk Wolters from KNMI. The trick was, to do the year long observations by bike, as described in this abstract:
Mobile temperature and humidity measurements have been performed along a 14 km transect through the city of Utrecht (311,000 inhabitants) in the period March 2006 – January 2009. The measurements took place on a bicycle during commuter tra c and resulted in 106 nighttime profiles (before sunrise) and 77 daytime (afternoon) profiles. It is shown how the intensity of the urban heat island depends on wind direction, cloudiness and wind speed. Statistical models are constructed that relate the mean and maximum nighttime urban heat island intensity profiles to area-averaged sky-view factors and land use combined at both the micro and local scale. Sky-view factors are estimated from a 0:5 x 0:5 m surface elevation database and land use is obtained from a 25 x 25 m land use database. The models are calibrated using the mobile measurements and provide estimates of the spatial distribution of the mean and maximum nighttime urban heat island intensity in Utrecht. Both models explain more than 75% of the variance. A separate non-linear model is introduced that relates the temperature differences between the warmest and coolest part of the transects to wind speed and cloudiness.
The paper:
Brandsma, T. and D. Wolters, Measurement and statistical modeling of
the urban heat island of the city of Utrecht (the Netherlands)
Journal of Applied Meteorology and Climatology, 2012, 51, 1046-1060.
available here:
http://www.knmi.nl/publications/fulltexts/uhi_manuscript_brandsmawolters.pdf
I put a couple of the figures side by side to give you an idea of what was discovered:
Really?? Since the scale STARTS at +0.1, I wonder how that can be? Using my finely calibrated Mark 1 eyeball and the browser zoom feature, it appears that the deviation is not less than POSITVE 0.4 and no more than POSITIVE 1.5. But thanks for pointing out the location.
I was referring to the T-graph in the paper along the transects.
In the graphs of the analyzed transects the KNMI temp are well below the rest of the transect.
I guess you were referring to Picture whit the title:
Spatial distribution of the mean nighttime UHI
intensity for the city of Utrecht and its surroundings as
_calculated from the model_ in Equation 4 with respect to
the _rural background_ temperature.
Yes, over the length of the transect, at the KNMI location, the anomoly with respect to the transect appears to be about -0.25 during the day and -0.75 at night. But if the transect as a whole is 1-2 degrees above the surrounding rural area, then the KNMI location is just less hotter; it’s still biased “hot” when the data goes in the GISS mill. The nightime model thermograph would seem to support that conclusion.
D. J. Hawkins says:
October 11, 2012 at 4:29 pm
…
Yes, over the length of the transect, at the KNMI location, the anomoly with respect to the transect appears to be about -0.25 during the day and -0.75 at night. But if the transect as a whole is 1-2 degrees above the surrounding rural area, then the KNMI location is just less hotter; it’s still biased “hot” when the data goes in the GISS mill.
What brings you to the idea that the whole transect is 1-2 degrees (°C I assume) above the Rural back ground”. Rural background is a term which should be clarified in a state like the Netherlands with a population density (for the whole state) being higher than the one in the Boston SMSA
If you follow the route of the transect on the thermal map, by inspection it doesn’t appear to have any significant length passing through an area less than 1.5 degrees above the lowest areas displayed. One may cautiously assume that truely rural areas in the Netherlands, as opposed the lower temperature areas immediately adjacent to the urban zone, are even cooler.
Before dismissing the likelyhood of the existence of such areas, let me point out that I live in New Jersey, USA and using Wikipedia entries as the bench mark, we are even more urban (459/km^2 vs 397/km^2), and I can assure you there are plenty of very rural areas left in the state. We raise more horses than Kentucky. As for the Boston SMSA (Greater Boston Area), Wiki gives the population density as 947/km^2. A little more than the Netherlands, ja? But thanks for playing!
majormike1 says:
October 10, 2012 at 11:23 am
“…certainly by 2020, Detroit will have shrunk to a lower population than 100 years ago. Detroit experienced both rapid growth and decline during that time. I hope temperature records pre- and post-decline are available.”
I wouldn’t think the concept works quite as well in reverse. I mean: as a city’s population decreases they’re hardly going to start ripping up the concrete structures and replace them with fields are they?
@ur momisugly David, UK
“I wouldn’t think the concept works quite as well in reverse. I mean: as a city’s population decreases they’re hardly going to start ripping up the concrete structures and replace them with fields are they?”
Nature itslef will do this if the area remains depopulated long enough. This process does take a lot longer than building the city in the first place though.
It might not take as long as you think. As the neighborhoods thin out, the city is trying to get people to consolidate, offering incentives to relocate. Then they cut off services to entire blocks. I think they’ve even bulldozed a lot of the now-empty houses. Once you fill in the foundation, you’ve got an open field. Emotionally wrenching for residents, but what can you do? It’s too expensive to keep services going when only 2 out of 20 houses on a block are occupied.