From the Pacific Northwest National Laboratory (PNNL), more confirmation of a night-time warming bias in climate records due to increased infrastructure.
RICHLAND, Wash.—City living has its perks: Live music, museums, trendy cafés and much more.
But urban living isn’t so cool when it comes to summer weather.
Living in a city translates to an extra two to six hours of uncomfortable weather per day in the summer for people in the eastern and central United States, according to research published Dec. 9 in Geophysical Research Letters. The scientists present this and related work this week at the annual meeting of the American Geophysical Union.
The additional uncomfortable hours occur mainly at night. Cities bake in the summer sun, with concrete, dark pavement and structures soaking in the heat during the day and releasing it at night, raising the nighttime heat index.

Living in a city boosted the nighttime urban heat stress index anywhere from 1.9 to 4.9 degrees Celsius (about 3.5 to 9 degrees Fahrenheit) compared to nearby rural areas. The effect in the daytime was much less. During daylight hours, some cities actually become slightly more comfortable due to lower humidity.
Researchers at the Department of Energy’s Pacific Northwest National Laboratory also found that when a heat wave hits, the heat penalty of living in a city grows even more. Though everyone in the region is experiencing warmer temperatures, the extra amount of heat that the city residents feel compared to their rural neighbors becomes even larger. The hotter it is, the bigger the penalty—a concern especially in light of future global warming.

Because more than four out of five Americans live in urban areas, the scope of the penalty is likely extensive. Extreme heat is now listed routinely as a leading weather-related cause of death in the U.S., usually ahead of floods, wildfires and hurricanes.
“People have known about the urban heat island effect for more than 180 years, but the fact that the differences between nighttime and daytime and among different cities is so substantial is somewhat surprising,” said PNNL atmospheric scientist Yun Qian, corresponding author of the paper.
“Our findings show that urban living makes nighttime hours in all U.S. cities studied more uncomfortable,” Qian added.
Gap between urban and rural
The researchers found that in the U.S. cities studied, a temperature increase of 1 degree C (about 2 degrees F) translates to an extra 30 minutes of uncomfortable weather in a day for city residents. That means a heat wave, or future warming, that increases the background temperature 6 degrees C—roughly 11 degrees F—could translate to three more hours of uncomfortable weather in a day.
That’s above and beyond the extra discomfort that other residents living in less urban areas in the same region experience.
To do the study, scientists designed and ran a climate-urban model and analyzed the results for six summers, from 2008 to 2013. The study included large cities such as New York, Boston, Philadelphia, Washington, Atlanta, Miami, Chicago, Detroit, Houston and Dallas. The scientists looked at the heat stress index, which describes how the temperature feels when humidity is taken into account.
Then the team calculated “heat caution hours,” which they defined as hours when the heat index reached above 27 degrees C, or about 80 degrees F—the dividing line they used between comfortable and uncomfortable.

The team observed a competing dynamic between temperature and humidity in cities. When it comes to comfort, cities have the advantage when it comes to humidity. There’s usually less humidity in urban areas because there aren’t as many plants, trees and other vegetation to give off moisture. But uncomfortable higher temperatures in cities are a more powerful factor, with an impact about five times that of humidity.
In all the cities studied, the air became more uncomfortable at night as temperatures rose, regardless of humidity. Beyond that, the effects of urban living varied a bit from region to region.
Regional differences
At night, urban areas in the Northeast, such as New York and Philadelphia, experienced the largest nighttime penalty, with the heat index increasing up to about 4.5 degrees C.
But in terms of the number of extra hours of uncomfortable weather, the effects were most pronounced in the southeastern United States. Residents of Atlanta, for instance, experience on average four to five extra hours a day during the summer of uncomfortable weather. People living in the Northeast are more likely to have two or three such hours.
In many cities, urban living makes the daytime hours less comfortable too. Philadelphia, Washington, New York and Chicago all experience a higher heat index and more heat stress during the daytime, compared to more rural regions nearby. But because of lower humidity that accompanied higher temperatures in cities, daytime comfort was slightly enhanced in the southern and eastern United States, including Dallas, Houston, Atlanta and Miami.

“It’s important to note the differences between cities,” said coauthor T.C. Chakraborty. “What is useful for heat mitigation in Chicago, for example, may be different than what is useful in Miami. Even within one city, different neighborhoods can be very different—for example, an area along a river compared to a neighborhood with no grass or water nearby.”
Along with Qian, former PNNL postdoctoral researcher Chandan Sarangi, now at the Indian Institute of Technology in India, is a lead author of the paper. Other PNNL authors are Jianfeng Li, Ruby Leung and Ying Liu.
The research was funded by the DOE Office of Science.
# # #
Link for published paper here.
Interesting piece of research and noteworthy that, for example in the Houston conurbation, the heat island effect is noticeable down wind of the prevailing southerly / southeasterly…
I’ve always said that in urban areas the strength and direction of wind has a direct effect on the temperature. Any weather station downwind will also be contaminated.
Many temperature measurement stations are in those heat island areas.
They all read high temperatures, which ups the average for the whole world.
China, India, Japan, etc., have very large heat island areas
https://ntrs.nasa.gov/api/citations/20040081268/downloads/20040081268.pdf
UHI …. the only measurable affect man has on climate. Answer to that ? Move everyone to the suburbs and the country 🙂
and watch the rocketing crime rates destroy the quality of my country life?
Pass.
Idon’t know where youre located but in the UK there is a lot of rural crime. Perhaps not as much knife crime as seen in cities. Theft is a common problem on farms, tractors are more valuable than sports cars.
Generally speaking, theft is only a problem where people can’t protect them selves, ie they have guns.
I understand that burglary rate of occupied homes is much higher in the UK than in the US because American burglars are afraid of being shot by homeowners.
In rural PA tractors are rarely stolen because we post trespass signs like,, “AMMUNITION IS EXPENSIVE SO THERE WILL BE NO WARNING SHOT”
All the violent gangs too?
markl,
I was under the impression that the greens want every [surviving] to live in densely set, high-rise ‘utopias’, with the minor exception of themselves, and the other ‘elites’.
Per this article, the survivors, who will be peons at best [slaves and concubines at worst], will also have to suffer heat stress. Likely to reduce their numbers – unless the next Ice Age comes to their rescue [I won’t be around in 2050, I suspect!].
Auto
Breaking news: Scientists “discover” that UHI is real. Next, they intend to study water, and how wet it really is.
That is Comedy Gold!!
I am available to receive a large grant to study whether it flows uphill or downhill.
I don’t think they are ready for that yet. The first phase of the research will be to see IF water is wet, and to what extent anthropogenic warming affects the asserted wetness.
Prepare yourself for a blizzard of research papers describing wetness as a social construct. 😉
So it sure sounds like a terrible idea to become more dependent on solar power. When folks are home at night, air conditioning helps a lot to get good rest. Making it more challenging to supply the grid in the dark won’t end well.
A very interesting article about Urban Heat Islands. As the article points out 4 out of 5 (80%) of the US population live in urban areas. These urban populations are experiencing the direct affect of human influenced (anthroprogenic) warming of their environment from large areas of cement, asphalt, brick, steel and dark roofs in their city. It is no wonder that the urban populations have accepted the Global Warming “Theory”, they live in Urban Warming. I have created a web site that provides qualitative and quantitative Land Surface Temperature maps from Landsat data for numerous cities in the US and Canada, including Houston. The details can be found at:
http://www.urbanhi.net/uhi-cities/houston-area.html
“It’s no wonder the urban populations have accepted the Global Warming “Theory”, and that problem is exacerbated because the media propagation is done from there and the pointy head university intellectualistas that are addicted to the koolaid all live there.
Nice work Michael.
I have been thinking that locations in China should show quite dramatic changes over the last two decades. The energy increase in China over the past two decades has been staggering. The change in urban heat should show a dramatic change in just two decades.
Rick, let me know what city in China you are interested in seeing changes in the UHI. Including the Lat & Long would ensure I do the analysis for the correct location. I will work on that this week. The analysis will be similar to what I did for Sydney, Australia.
That is really cool. I’ll put a request in to add St. Louis. I realize that may be a lot of work and you can’t satisfy everyone.
Hello bdgwx, I will work on St. Louis after I finish the city in China that Rick talked about.
“I’ll put a request in to add St. Louis.”
We definitely have it. Not so bad in my current Southampton cop and teacher neighborhood, But I grew up in almost all brick Baden and Walnut Park….
https://www.stlouis-mo.gov/government/departments/public-safety/emergency-management/hazards/threats-extreme-heat.cfm#:~:text=Louisans%20are%20especially%20vulnerable%20to%20heat%2Drelated%20hazards.,%22urban%20heat%20island%22%20effect.
Interesting. I had no idea you live in St. Louis. I’m way out there in St. Charles.
My link was kind of off topic. Got me there.
I’d also be interested in UHI hotpots here. My last observation was flippant. As you know, there are red brick houses all over here. I’m assuming it has more to do with black top and trees. I grew up on Switzer, just north of Calvary cemetery (Baden school and Sumner HS are/were not/never big feeders to Missouri School of Mines), with that big green area nearby, and only an average black top fraction. So, I could be wrong in my last impression of where hot spots are.
Not stalking, but I did run across your long time contributions to a (local?) weather blog. Your dispassionate data evaluation is truly Nick Stokesian.
Yep, I post at https://morethanweatherstl.com/ frequently. It’s a pretty active local blog.
Nick Stokes is a smart guy. I’m no where near that level, but thanks for the compliment. You’re posts are packed full of useful information as well.
You can often see the UHI hotspots with the GOES-16 satellite. I posted this image a couple of years ago. In fact you can see it pretty well right now on channel 14. There are a couple of publication documenting the St. Louis UHI. One is Rozoff et al. 2003 and Vukovich and King 1980.
At night the ground often cools first before the air a few feet higher up. Fruit farmers take advantage of this by putting fans that draw air from 60 or 80 feet up and blowing the warmer air on their orchards. In the city buildings are continually built taller, increasing this effect during nightime breezes, plus the buildings themselves block more of the ground level spherical view of outer space, reducing IR emission to start with.
So whatever we thought the UHI effect was 25 years ago, it’s more today.
The Blacktop Effect (BTE) is a first-order forcing of climate change.
Of course it is. It’s always much cooler in city parks than on city streets. When you have millions of acres of pavement and concrete re-radiating everyday, what else would anyone expect?
Exactly.
And underreporting of UHI contaminates the weather records.
To verify the UHI effects, just plot surface estimates against radiosondes and satellites. They keep increasing their divergence rates over time.
I have an ignorant question: Why are urban streets so damned dark? How much have people tried to come up with better road surfaces?
I realize asphalt is naturally black from being oil-based; is there anything which can be added to make it much less so?
I reckon the colored paints used for crosswalks, lane markings, etc, are probably either too expensive or doesn’t last long enough, since I have never heard of entire roads being painted.
Concrete is not a good substitute. It is more prone to cracking, much harder to dig through to get to buried utilities, much harder to restore after the utilities have been fixed. You can fix asphalt potholes in minutes, and it is driveable almost immediately, as long as you don’t mind asphalt spatters; concrete takes much longer to dry and will not support any useful weight until it is dry.
It seems to me, ignorant about such matters, that road technology hasn’t changed much in a century, which seems like an opportunity, which means I am missing a whole lot to be so naive.
Tires degrade with use, leaving black dust. Any other color road surface will be black in days.
[NICE EMAIL ADDRESS -mod]
I agree
In hot areas we should be coming up with some sort of white pigment that also strengthens the asphalt but in colder areas like here in canada keep the traditional black.
Create UHI where beneficial, reduce it where it isn’t.
Think of all those brilliant white buildings in the pictures of Greek islands
Pat,
Have a look at the commercial price of Titanium Dioxide, the whitest white pigment widely used in paints. Nearing $3,000 a tonne. A bit rich to throw on the ground.
Those Greek islands are while, like the white cliffs of Dover, from other minerals like calcite, Calcium Carbonate. Probably too soft to use on big roads. Geoff S
There is also an issue that currently it is uncomfortable to be driving into the sun on wet pavement at sunset or sunrise (commute times). I suspect that white pavement wouldn’t have to wait for rain to make driving hazardous.
The protestors who want oil drilling to be shut down completely would be the first to harangue their local city councils about insufficient asphalting of the streets & roads.
Teslas look just the same as ordinary cars when everything is covered in dust, you see.
Road building technology is quite sophisticated these days. There are national standards for road building to cover various conditions. Main highways are different to local roads. If you look closely you will find that the road colour is the stone colour of the aggregate and is mainly grey. the asphalt is stripped off the surface fairly quickly. Concrete and paint are slippery when wet.
In a past life I sold additives for asphalt. In another past life I sold test equipment from beakers to nuclear density meters.
As roads engineer, I know why it is very difficult and expensive to change asphalt colour. It requires coloured or white aggregate and you can buy expensive clear asphalt cement to reduce the overall colour of the mix. It is a costly solution.
To paint the road reduces the skid resistance significantly so the road is less safe.
To make any real difference would cost many billions and yet there still will be many other buildings and structures that will continue adsorb heat during the day and expel it at night.
Paint is slicker than asphalt when wet. Plus paint won’t last long if cars drive on it.
I’m a layman on climate science and data and I wondered how they could adjust old temperatures down and more recent temperatures up.This didn’t make sense. This is the opposite of what would be logical when considering the impact of the UHI effect. Combine this with the homogenisation of data to guesstimate remote readings and I believe it’s possible that all of the official warming over the last 100+ years is made up entirely of these arbitrary adjustments. It’s even plausible that actual temperatures have fallen overall and at best you could say that the actual move is not more than the margin of error.
This is why I don’t like it when sceptics concede ‘ yes, the world has been warming, but it’s not dangerous.’ Don’t make any concessions! With 80% of the world being ocean , the way things are homogenised is pretty critical. What is an average global temperature anyway.
I have seen zero evidence in reliable data that there is even a slight trend between CO2 and temperature. Even after adjustments they couldn’t adjust out the cooling from the 40s to 70s which should not have occurred if temperatures are driven primarily by Man made CO2.
The only thing about this UHI article is that it’s newsworthy as the information is so obvious. An article that articulates the quantifiable extent to which adjustments have been made to temperature data in defiance of logic would be more illuminating.
That is exactly what Roy Spenser found. Once you take out UHI the continental USA has seen no warming in the last 1/2 century.
It’s all UHI leading to warmer evenings and winters
UAH TLT is believed by many to be mostly immune from the UHI averaging bias. It shows a warming trend of +0.18 C/decade for the USA48 region.
Over a period of cyclical warming on a cycle of about 70 years.
It’s arrant nonsense, is wot it is.
Adjustments are made to correct biases that occur due to station moves, instrument changes, time of observation changes, SST measurements, urban heat island averaging effects, etc. The net effect of all adjustments applied on a global scale average actually reduces the long-term warming trend. The net effect of all adjustments makes little difference after WWII. It is also interesting to note that UHI effect on the global mean temperature averaging procedure is actually close to zero and perhaps even slightly negative. [1]
That was not the reason for adjustment. They had to reduce the very rapid, not-CO2 related, natural warming from 1900 to the 1940s. This warming was an embarrassment to the CO2 theory.
Can you show me where in the PHA and GISTEMP source code an arbitrary adjustment like that is happening?
The raw data adjustments are in the thousands.. jeezes.
Then it should be really easy to spot the malicious bit of code making arbitrary and unjustifiable adjustments in the links above.
“bit of code”? I think they are talking about actual temperature readings, not code.
Code is the problem. All sorts of things can be done with Code. Legitimate things, and illegitimate things.
Actual temperature readings trump Code.
If you can find illegitimate things in the code let me know. I’ve looked through it myself and can’t find anything illegitimate. I also execute it on my own machine and have verified that it produces the same result as the official dataset published by GISS.
What do you mean “legitimate?” You proved the climate system works the same as the model predicts?
I suspect not. But isn’t the issue here with the data being adjusted? Nobody is talking about the code (except you), are they? Please correct me if I’m misinterpretting.
Legitimate adjustments would be those to correct for known biases like station moves, instrument changes, time of observations change, SST measurement methodology differences, and other non-climatic effects that introduce artifical changepoints into the record. The adjustments being discussed are applied via the PHA computer code found here and documented here.
We’ve been down this road before. Adjustments are *NOT* data. No matter how well meaning the intention, they are still nothing more than subjective guesses.
The *real* answer is to start new data collection sequences when you move a station, make an instrument change, change observation times, etc. Then, if you must, you can compare the old data sequence trends with the new data sequence trends to see any differences between them. If you re-calibrate a sensor then just add a calibration date field to the data so that you can tell before and after differences.
BTW, I still maintain that if you think you need a temperature snapshot metric then all temperature measurements should be made at the same time, perhaps 0000UTC.
And if, hypothetically speaking, such a dataset existed that started a new timeseries when there is a changepoint would that satisfy you?
It would be a start.
But I *still* don’t like the use of Tmax and Tmin being used to calculate a mid-range value which is then propagated through several iterations to form a global average temp. First, it isn’t an “average” temp, it is a mid-range temp and it hides the variance of daily temperatures. Second, the uncertainty grows with the original summation of terms and then grows even larger with each successive use. Third, the temperature data, when combined globally, represents a multi-modal curve, e.g. hot temps in the Northern Hemisphere combined with cooler temps in the SH. Temperature swings in the winter/spring are generally larger than in the summer/fall affecting the daily variances thus causing problems in doing least square regressions over an annual time frame. In such a case an “average” is meaningless. Yet no attempt appears to be made by the climate scientists to use proper techniques for a multi-modal distribution. Fourth, temp is a time variant variable. If the temp at one station is sin(t) and at a second station is sin(t + φ) then the correlation between the stations is cos(φ). φ itself is a function of several factors including distance, elevation, humidity, pressure, and terrain. Yet none of these appear to be taken into consideration when infilling unknown temperatures by using values from other stations. A latitude difference of only 25 miles can cause a difference in temp that is larger than the differences being attempted to measure in the global average temp.
In order for the climate models to *really* be useful they need to take all of this into consideration. They need to be able to give future estimates on a regional basis broken down by season and daily temperature variances. These need to be corroborated against past data broken down in a similar fashion.
The current “global average temp” is a useless metric. “Average” means as many locations below as above the “average”. Yet all we ever hear is that *everywhere* is going to see the earth on fire by the end of the century. No snow, no rain, no polar bears, no food, no coastal cities, no glaciers, etc. Not a single word about what is actually changing.
BEST starts a new time series for each changepoint. ERA provides hourly grids using sub-hourly timesteps. Both of your concerns have been addressed.
from the BEST site:
Yeah, tell me again that my concerns have been addressed!
What is the probability that with several reasons for adjustment, the net adjustment would be dominantly upward prior to 1945 instead of random?
The dominant factor is that SST bucket measurements cause a systematic low bias. The bucket technique had a pretty quick phase out during WWII. See Haung et al. 2015 for details.
Dip buckets can gain or lose energy relatively quickly because of the small volume. If the deck is much hotter than the SST, which is often the case in daytime, the bias should be high instead of low.
However, I thought that we were talking about terrestrial air temperatures.
If those data sets include SST, what about the practice of adjusting ARGOS buoys to the high-biased boiler-inlet temperatures after dip buckets were abandoned, as used by Karl to ‘prove’ there was no hiatus?
I see you didn’t get an answer. Hope you didn’t expect one.
Wasn’t the pre-WW2 warming mentioned in the Climategate emails as something of a problem for “the cause” (as M. Mann describes their “science”)?
It was the model mapping tree ring growth behavior to temperatures showing a decline after WWII that was the problem. The problem being that the model diverged from observations. That is the divergence problem as it is called.
Unless you are going to say there is no programming code to modify recorded data measurements then all you are really saying is that there are no errors in the code that is doing the adjusting.
Modifying existing, recorded data without concrete findings on why they the readings were in error is unethical. Justifying it by saying that in general you can find bias by comparisons with other stations is likewise unethical. By doing so you are impeaching the dedication and knowledge of numerous NWS employees and their methods of acquiring data.
As I have said to you before, would you recognize modified data for the speed of light or other physical measurements made in the past if the data was changed for whatever reason? I sincerely hope you would not. Yet when it comes to changing past recorded temperatures, you obviously have no problem with propagandizing politicians and the media with changed data.
Yet another strawman. I never said there were no errors in code. And as best I can tell the rest of your post is not related to anything I said or the tree ring divergence problem.
Yes, I think they said something like: “What about the 1940’s blip? What do we do about it?”
And we know what they did about it, they cooled it into insignificance in their computers, to promote the lie that current times are the hottest times in human history.
This is the heart of the scaremongering and it couldn’t be carried out without distorting the historical temperature record like they have done.
This distortion is also the only “evidence” the alarmist have to show. It’s a very important Lie. THE most important lie in the Human-caused Climate Change Scam.
Without the distorted temperature record, there is no CO2 crisis.
“What about the 1940’s blip? What do we do about it?”
You got a reference for that Tom?
Yes, I do, on a harddrive that needs some recovery done on it.
You haven’t ever seen the “1940’s blip” comment by the Climategate Charlatans before? I know I’ve posted it more than once.
When I fix my harddrive, I’ll post it for you.
Tom you do know there were eight committees investigated the climategate emails/allegations and published reports, and all found no evidence of fraud or scientific misconduct. I’m not sure a 100,000 would convince you, but eight is enough in my book to tell me they weren’t cooking the books. And yet skeptics still hang on to these stolen emails like they were some smoking gun. That was over 10 years ago and the planet has warmed significantly since then. What was that about the Titanic and deck chairs?
“no adjustments”
That’s funny! It looks a lot like the adjusted ones, wouldn’t you say?
Before WWII…no. After WWII…yes.
Did you notice what this article said about the number of people experiencing UHI? It kinda makes GAT a worthless metric since it vastly understates what many folks truly experience. You made fun of the suggestion to look at Cooling Degree Days to see what people experience. The fact that HVAC engineers use this data every day and not GAT should indicate how valuable these measurements are.
I never said CDD wasn’t a useful and valid metric to track. I also never said that tracking the GAT was a be-all-end-all metric that renders other metrics like HCH useless. If you have something useful to contribute to zigmaster’s post or my response to it feel free to do so otherwise I have no choice but to dismiss your post as little more than just another one of your strawmen laced rants
What is the probability that with several reasons for adjustment, the net adjustment would be dominantly upward prior to 1945 instead of random?
Zigmaster said: “What is an average global temperature anyway.”
It is what is. That is it is the average global temperature…literally. It is similar in concept to standard pressure (1 atm), mean sea level pressure, mean sea level itself, and many other scalar properties that are either spatially averaged over the entire surface area of Earth themselves or refer to such properties in some way. Probably without realizing it you rely on the concept of global spatial averages of properties in your everyday life.
You are correct about things like “Global Sea Level” (GSL). It is an average of various tide gauges at dispersed locations and has no adjustments for things like prevailing winds or land movement. IOW, about as accurate as GAT!
Atmospheric pressure is not and hasn’t been an average for a very long time. It is a very specific measurement of a height of mercury in a tube regardless of “height above sea level”.
Temperature is the same thing. It is a defined gradation between two very accurately defined points.
Averaging anything to get a metric does not define anything except the mean of the distribution. Averaging temperatures in order to get something like an “homogenized temperature” is mistreating the individual measurements. It ends up creating a number THAT IS NOT DATA.
“This is why I don’t like it when sceptics concede ‘ yes, the world has been warming, but it’s not dangerous.’ Don’t make any concessions!”
Agreed!
At best, it has only been warming since the 1980’s. It was cooling before that period of time, according to the written temperature record.
Alarmists, when they say “warming” are claiming the warming has been continuous since the end of the Little Ice Age. But the truth is the temperatures since the Little Ice Age have warmed for a few decades, and then cooled for a few decades and then warmed again for a few decades. In other words, there is no continuous warming going on as the alarmists claim.
If Skeptics are not careful when talking about warming, they will seem to be confirming the alarmists contention of continuous warming since the Little Ice Age, which is not born out by the facts.
Tricks are used to make deliberately erroneous adjustments (homogenisation) to the mangled data. Typically, a weather station on the edge of town shows a warming trend as the town expands to surround the weather station with an UHI. Eventually, the weather station is relocated to the new edge of town, but to splice the data from the old location to the data from the new location, the old temperature series is lowered. The “best” part is that this trick can be repeated in another twenty years when urbanisation has encroached on the current site.
I can easily prove UHI to anyone.
Where I live is mostly rural, but in a 50 minute drive on an interstate, I can be moderately large city. I also own a convertible. Some mornings I have to leave at 6:30 or 7:00 in the morning to drive to this city. In summer, I will drive with the convertible top down. When I leave, it is usually too cool to drive comfortably. But as I get near this city, it is quite comfortable. The temperature will rise 3F to 4F between when I leave and when I arrive. Early in the morning, the temperature doesn’t rise that fast. (The only fast temperature changes I can think of in my area are with cold fronts.) That can only be UHI.
I have seen the same thing in the evening driving out of the southern suburbs of London where my car thermometer has changed by 5C – about 10F – in 45 minutes. One of the UK’s climate crooks Phil Jones has claimed that UHI is only 0.5C!
“I can easily prove UHI to anyone.”
I believe it.
It should be obvious to anyone who looks at it. I live about 40 miles from the large city of Tulsa, and Tulsa is almost always warmer than the surrounding towns by a few degrees.
The good thing about heat island effects is they won’t cause us to shut down our fossil fuel use because they have nothing to do with fossil fuel use.
Heat Island effects can be mitigated by turning on the air conditioner.
I’m not sure I can accept this as “proof.” But scientifically, it’s not really any less sound than the model outputs we’re supposed to accept without question
“The hotter it is, the bigger the penalty—a concern especially in light of future global warming.”
Having underestimated UHI in this way means a serious overestimate of anthropo global warming because of inadequate correction to UHI. A large percentage of the network weather stations should therefore have had their temps reduced even more before using them in measurement of global warming.
Studies done on the network by Anthony Watts and a study of California stations by Roy Spencer showed that rural stations showed little to no warming and even cooling in many over time compared to urban and near urban stations “corrected” for UHI. So there just might be no “future global warming” of any concern. At least there is no convincing sign as yet, and considerable thought of late by GISS and IPCC that models have been running too hot and that we may be entering a 30yr cooling period.
A number of good ideas on mitigating Urban Heat, such as roof top gardens, more trees, etc, could be all that’s needed.
But that would increase humidity.
I have another example.
Many years ago, I went to a football game and stayed overnight before the game. (This is American football, which is mostly played in the winter.) In the hotel I was staying in, some jerk pulled the fire alarm in the middle of the night. Everyone evacuated, but not dressed for the weather. As long as we stayed near the brick wall of the hotel building, we were quite comfortable, even though the outside temperature was measured in the mid 40’s F.
I suspect that UHI is already saturated in large cities, having seen this for myself in data. Cities tend to grow outwards, new development several miles away surely has no effect, except where that development is located.
i find that unlikely. heat rises. breezes come in to replace the rising air. The further away the cooler air is, the less cool it will be when it reaches center mass.
I have noted that air travel has increased exponentially since the 1960s until last year.
I also note that a significant percentage of weather stations are based at air fields. Is there any literature investigating UHI specifically relating to Air travel?
My hypothesis is that increasing air traffic in the region above a weather station, causes higher reported temperatures (esp at night). This could occur due to airplane exhaust fumee acting a seed particles for cloud formation. Especially when you consider busy airports ‘stacking’ planes in a spiral above the airport.
Interested if anyone else has considered this?
Because of covid, there should be good with/without air traffic data to use.
As Anthony noted in his study of weather station locations, many of the stations are poorly sited (close to external heat sources). This inspired me to use Landsat temperature data to examine the Urban Heat Island effect. I included GISS weather station locations in some of the Land Surface Temperature (LST) maps. The GISS station sites are shown for the DC Ronald Regan Airport, Andrew’s Air Force Base, Newark Airpot, and Minneapolis Airport. The locations of these GISS sites have noticeably higher LST values than the nearby areas. You can find this information on my web sit.
www,urbanhi.net
Pretty easy to see UHI effect here in Calgary. In the fall as the climate cools we start getting frost warnings for areas surrounding calgary but not the city itself.
Last Feb during the cold spell I was west of the city, drove home near the city core then headed east for Sask.
Was -32c west of town, -26 in the center, -33 to the east
Human global warming proven.
I once told a bright younger architect who I was working with that “cities were parasites,” no offense to parasites or their hosts as they are technically rather fascinating biologically. He was rather surprised, remarked on all the benefits, but apparently hadn’t thought about mass in/mass out, energy in/energy/out. Some scientists also haven’t done much of such thinking. Carbon cycle is more than kind of complicated.There may be better metaphors but successful parasites do hide their effects.
Studies I have done on heatwaves in Australia’s six State capitals (among the largest cities here) have not shown any credible increase of average Tmax of heatwaves of 1, 3, 5 and 10 days duration over the historical period starting in the 1860s. The inference is that UHI does NOT add on to the highest temperatures reached in heatwaves. (There are some exceptions, like Perth warming as recent rainfall lowers.)
The reason is probably that many Australian heatwaves commence in the hot, dry, central desert (no UHI here) and get blown over the big population centers. So, it is the weather in central Australia that dictates the severity, not so much the local weather as recorded in the cities.
I suspect that much the same mechanism could be found in USA, for places like Florida and coastal Texas. Nothing much to do with climate change. Geoff S
The UHI impacts nighttime temps. That means that the daily average of Tmax and Tmin goes up. The daily average going up causes the UHI to impact the global average temperature. Tmax is a small player in the growth of daily, monthly, annual, and global average. Think Tmin instead.
Also why Lindzen and others have advocated monitoring temps using daily max, not average of min/max. Min is affected by UHI and boundary layer effects, daytime max is not.
AFAIK temperature trends in daily max are much less.
Tim G,
Why bother with Tmin?
The hot air blown in from central Australia hangs around through the nights of multi-day heatwaves and makes Tmin look hotter. Simples. Geoff S
Some offhand comments:
The human species evolved as hunter/gatherers living a nomadic life. We are not evolved, either physically or psychologically, for life in densely populated limited space conditions. I know that some, like Freedman, dispute this but I’ve always thought of the Tragedy of the Commons as a pretty good description of what happens with overcrowding. Resource domination becomes a primary goal leading to all kinds of problems.
My two cents. Yours may vary.
Two years ago I wrote up UHI on WUWT. It covers more aspects than the lead article here, for those who want an overall view. Geoff S
The Climate Sciences Use Of The Urban Heat Island Effect Is Pathetic And Misleading – Watts Up With That?
Over 10 years ago I wrote up UHI vs Electrical usage & waste heat.
2010
I could never understand how UHI was minimized. If you look at New York City as an example.
Area, including water 468.9 sq mi ( 2,590,000 sq m)
Power used (2008) 54,869 GW-hr
(www.nyc.gov/html/planyc2030/downloads/pdf/progress_2008_energy.pdf)
Watts/sq m = 2,416 total. The Mayor says 80 percent is used by buildings and therefore 100 percent ends up as heat loss. So the forcing is 1,933 W/Sq M
The file also remarks that the city has seen a 23 percent increase in the last 10 years, which is close to the increase showing up in the charts.
Then add in all the vehicle waste heat. Then add in all the city generated power and the +30% waste heat to generate electrical power.
Still waiting to hear if +1,933 W-hr/Sq M raise the temperature more than 100 ppm CO2?
Over 60K temperature stations outside of urban heat islands (airports and sea buoys) shows T is declining. Scroll down for graph and data info.
temperature.global
In fact we are BELOW the published NOAA global average 1961-1990 baseline of 14.0°C !
Either I missed it or that wasn’t the whole article. Somewhere in there they must have mentioned it was all the fault of CO⁰.
Based on a few comments here it seems as though there is confusion on what the “UHI bias” actually is. The bias is not caused by the urban heat island effect itself. The fact that urban areas are (or at least were) warming faster than rural areas is a real effect and it should be reflected in regional mean temperature and trend products. You don’t want to remove the UHI effect because it is real. What you want to remove is the UHI bias. The bias is caused by using urban observations as proxies for rural grid cells and vice versa. When you have a grid cell that is predominantly rural but overweight on urban observations you get a warming bias during the period of urbanization. When you have a grid cell that is predominantly urban with it’s rural-to-urban observation ratio increasing you get a cooling bias. The bias (not the effect) is accepted to be positive especially prior to WWII, but afterward when urbanization slowed down, rural observations increased, and station moved from city center’s to the suburbs that bias leveled off. In fact, Berkeley Earth says after 1950 the UHI bias on the global mean temperature is -0.10 ± 0.24 C/century mean that it is statistically consistent with zero but more likely to be negative than positive. The primary focus of this article is the magnitude of the effect which is different than the magnitude of the bias spatial averages.
When you dig deep into the data, you commonly find that the more remote the weather station, the worse the quality. Factors like missing data, equipment maintenance etc cause so much raw data noise Thai it is less useful.
Of course, homogenisation is available but improve poor raw data, but that opens a whole new can of worms. Geoff S
UHI is real. But is it caused by greenhouse gas emissions? Our beloved leaders aren’t talking about reducing UHI, they are talking about completely reengineering our society away from practical and affordable energy and using intermittent, expensive energy instead.
By eliminating UHI from the dataset, we can see if the globe is really warming.
All I can say is, well, duh! How much did the obvious cost?
In Arizona, the nighttime temperatures in the desert are much lower than those in urban areas. This isn’t a new phenomenon. Decades ago, I would ride my motorcycle from my apartment to the nearby desert mountains and would be warm until I reached the end of the developed area, cold in the orchards, and cool in the mountains. Today, there’s a much more pronounced difference, due to the much larger urban area.
Didn’t Obama’s science advisor make a statement about stopping global warming by paint our roofs white? Wasn’t that an implicit endorsement of the idea that UHI is behind most of the alleged warming?
Look at those middle temperature bubbles shaped by what I suppose is prevailing winds.
Not to anyone who has been paying attention for the last ten or twenty years!
Not in Phoenix. Gas stations, bus stops, and home patios have misters. Most homes have pools. The area of golf courses and urban green-ways probably equals the area of schools.
Could someone provide an overlay that shows where all the temperature stations are located?
Here is a pretty good interactive map that lets you select the stations and see the monthly temperatures for each.
It’s a bit late to post on this thread, but… mieux vaut tard que jamais.
I read in a comment above:
” The UHI impacts nighttime temps. That means that the daily average of Tmax and Tmin goes up. The daily average going up causes the UHI to impact the global average temperature.
Tmax is a small player in the growth of daily, monthly, annual, and global average. Think Tmin instead. ”
To such rather superficial claims about UHI’s alleged influence on Tmin temperatures, I prefer to have a look at real data, and to compare
*
To let anyone understand what I mean with ‘UHI suspects’, I post a link to the complete USCRN info, including photos and lat/lon/elev coordinates (caution: lat & lon are here very approximating values):
https://www.ncei.noaa.gov/pub/data/uscrn/documentation/site/photos/stationsbystate_lores.pdf-20161212
This of course does not mean that all currently active USCRN stations would be free of any UHI influence. A look at the very first entry in the list
63869 30.5485 -87.8757 29.0 AL_Fairhope_3_NE
clearly shows that the Fairhope station in Alabama might be more affected by UHI than is for example
26563 60.7237 -150.4484 86.0 AK_Kenai_29_ENE
which in comparison is really ‘in the middle of nowhere’: a look at Google Maps using the coordinates of the stations is significative.
*
What is less significative however, is the comparison, for CONUS+AK, of the USCRN average (of the hourly data) with that of those GHCN daily stations located in the same 2.5 degree grid cells as their USCRN mates.
The monthly averages – starting with 2007 and based on anomalies wrt the mean giving the most USCRN station data (2016-2020) – were split into Tmin and Tmax.
1) Tmin
2) Tmax
*
What the two graphs of course don’t show is that
*
But… who tells us that these differences are due to UHI?
Sources
USCRN
https://www.ncei.noaa.gov/pub/data/uscrn/products/hourly02/
GHCN daily
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/
Thanks, but the animation is NOCOMM, worse than superfluous.