A couple of days ago, I highlighted a worst of the worst NOAA climate monitoring station in Arizona with the help of a scientist from the University of Washington.
My friend Jim Goodridge, former California State Climatologist continues to be busy in his retirement, and sends this along today. He’s been tracking a group of weather stations in California, and has been doing so for over 20 years. In fact, it was Jim who first introduced me to that light bulb moment where I realized that global warming wasn’t really all it was cracked up to be when he made this short publication in the Bulletin of the American Meteorological Society in 1996.
I guess you could say it was the graph that launched a thousand blog posts, because as we all know, CO2 can’t heat differently based on county population.
So with that in mind, have a look at his current analysis:
What is most notable is the red dots, which cluster in the San Francisco Bay Area, as well as the Los Angeles basin. You can also make out the I-80 corridor from San Francisco to Reno, traced in red.
Jim’s Excel spreadsheet is here, you can play with the data yourself: CA-Temp-map-100-Years
Of the stations showing the greatest 100 year warming rate, the one station right on the border of Arizona and California, Parker 6NE, has the greatest at 0.0625/year degrees Fahrenheit as this screen cap from his worksheet shows:
That’s a whopping 6.25 degrees Fahrenheit ( 3.47C) per century! That’s a bigger rate than some of the climate model predictions. Wow, the greenhouse effect must surely have gone into overdrive in Parker, right?
I decided to have a look at the Parker 6NE station, and started with the B91 forms of original data, boy was I surprised:
Look at all that missing data, which I’ve marked in yellow. 10 days in November 2015 and 16 days in December 2015. Of course NOAA/NCEI “corrects” this by infilling it with other data from surrounding stations so that no station record is incomplete in their database. In the case of December, 2015, over 50% of the readings aren’t actually real data from the station in Parker, they are “fabricated” from other data using NOAA/NCEI’s special FILNET sauce. No worries, all’s fair in love and climate science, right?
NASA GISS keeps a plot of Parker 6NE data, and it seems missing data has been a hallmark of this station for quite some time. Notice all the gaps:
Source: http://data.giss.nasa.gov/cgi-bin/gistemp/show_station.cgi?id=425000262500&dt=1&ds=14
With that many gaps in annual data, you’d think this station might not be suitable for climate science use, much less categorized as a “best of the best” USHCN station, right? No worries, all’s fair in love and climate science.
Steve Goddard had a look at Parker 6NE a few months ago, and plotted the infilled data from NOAA NCEI:
It seems pretty clear that the majority of the warming trend is all about the minimum temperature, which has a sharply higher trend than the daytime maximum temperature. This mirrors the temperature trend of nearby Las Vegas, NV which has had explosive growth. The UHI signal in the nighttime Tmin is very clear:
But, it turns out that most of that trend is in overnight temperatures, which are most affected by the explosive infrastructure growth of Las Vegas and the resultant UHI:
Inconveniently, there is no upward trend in maximum temperatures, in fact it appears there has been a slight downward trend since the late 1930’s and early 1940’s:
So surely, Parker 6NE must have had similar explosive growth contributing to UHI, making the Tmin trend grow large, right?
Nope. It’s a siting issue. According to the B91 form, the Parker 6NE USHCN climate monitoring station is located at radio station KLPZ in Parker, it is a volunteer observing site, which sort of explains why NOAA gets what it pays for when we have 16 days of missing data in December 2015.
A cursory look at the station in Google Earth shows the problem, can you spot the official climate monitoring temperature sensor in this aerial view?
I couldn’t either. But thanks to Google Earth street view, I found it. You may have to click the images to see better. Annotations are mine.
The junk piles and junk cars are certainly a nice touch for NOAA’s official climate observing station, don’t you think? Note also the big “swamp cooler” on the roof of the radio station about 20 feet to the right of the MMTS temperature sensor. That will put extra humidity into the nearby air, which will contribute to local warming due to moist enthalpy, in addition to the heat sink effects provided by the junk, cars, and nearby building. Those who live in the deep south understand how a how a humid summer night can stay at 80 degrees for a Tmin, while over in the desert of Arizona, away from the swamp cooler A/C units, the temperature can fall to 50 degrees at the same latitude on the same day, with an even higher Tmax.
And then there’s the nearby tree, which we know will limit LWIR going from the ground to the upper atmosphere at night, keeping the air near the ground warmer than it normally would be. That’s a factor too.
But I think the biggest factor is the solid metal fence that surrounds the compound, which can be clearly seen in the aerial view. Then there’s the building itself to the south. That essentially cuts off the temperature sensor from any wind flow near the ground in any direction, and as we know from basic meteorology, windless nights are the biggest problem for UHI. In this case, thanks to the fence, all nights are less windy at the sensor than they normally would be, resulting in less mixing of the boundary layer air, and warmer temperatures at night. This site mimics a big city UHI effect due to these factors I’ve noted.
But NOAA says they can “fix” garbage temperature station data like this.
If it were up to me, I’d remove this station from all climate databases rather than trying to fix this hodgepodge of inaccurate and highly biased data. But NOAA and their fanboys prefer keeping junk data like this.
This is why I’ve said before and will continue to say:
“The majority of weather stations used by NOAA to detect climate change temperature signal have been compromised by encroachment of artificial surfaces like concrete, asphalt, and heat sources like air conditioner exhausts. This study demonstrates conclusively that this issue affects temperature trend and that NOAA’s methods are not correcting for this problem, resulting in an inflated temperature trend. It suggests that the trend for U.S. temperature will need to be corrected.” He [Watts} added: “We also see evidence of this same sort of siting problem around the world at many other official weather stations, suggesting that the same upward bias on trend also manifests itself in the global temperature record”
“Our viewpoint is that trying to retain stations with dodgy records and adjusting the data is a pointless exercise. We chose simply to locate all the stations that DON”T need any adjustments and use those, therefore sidestepping that highly argumentative problem completely. Fortunately, there was enough in the USHCN, 410 out of 1218.”
But, they at NOAA keep these garbage climate stations anyway. No worries, all’s fair in love and climate science.
ADDENDUM: I hope Anthony won’t mind if I add this. I took Jim Goodrich’s Excel data from above, added county population density data, and that gave me the following graph:
Best to everyone,
w.
America, you are not alone with this “world’s best practice”.
We in Australia are also met with the very same brick wall.
Those of you who are familiar with Jo Nova’s site would sense an air of deja vu with wattsupwiththat observations.
So many are now aware of their rediculous practices but still they persist.
How do we stop them?
Yet the BOM trend is well below that of UAH v6? The “gold standard” satellites show a much higher warming trend.
Local temperatures are not global ones. AMO and other oscillations shift heat around the globe in a time frame of decades. I guess the southern part of the globe had actually a cooling the last decades. Just think of the growing antarctic ice.
Johannes, sorry, I should have been clearer. Jo was constantly complaining that the ACORN data set for Australian temps was cooked, and adjusted to show more warming than there is, yet UAH v6 shows a much higher warming trend for Australia than ACORN.
Ps, what growing ice in Antarctica? If you couldn’t tell by the lack of posts here about it, sea ice is now below average. Both in Antarctica and in the Artic. It just set a new global minimum.
Could you post a link please, Daveo?
I can only find Roy Spencer saying of v6 UAH that “We also find that the resulting LT trends over the U.S. and Australia are in better agreement with other sources of data.”
That could cover a lot of different meanings. E.g. By itself it doesn’t mean they are in good agreement, only better than previously.
Daveo, I’ll also add that I don’t think JoNova was complaining about the recent match between satellite and surface measurements (which both embarrass the models).
The surface record goes much further back in history than when the satellites started in 1979.
I can’t speak for JoNova but from what I’ve read at her blog the biggest complaints are about the adjustments to the long term record which, like the USA, usually seem to make the past cooler and thus inflate the magnitude and continuity of late 20th Century warming.
The southern oceans have ben cooling for a couple of decades. For most of the past four years global SI has been at or above the mean. That it is currently low is not due to some sudden onslaught of CO2. Many factors besides air T play into global sea ice. The 30 percent costal masked (for accuracy) DMI arctic graphic is at a record, well above any recent year. So we have more ocean with at least 30 percent ice, and less with only 15 percent ice. Hum? If a portion of the record denser 30 percent sea ice were to move from the 30 percent area, into the 15 % ice area, then there would be a great deal more 15 percent ice, likely showing an increase instead of the current decrease. (The ice is there, it is just more dense then normal in the 30 percent pus area, and thinner in the 15 percent area)
I have not looked into the current Antarctica decline. It is not Southern ocean T that is for certain. Perhaps it is storm and ocean current related. At any rate Antarctica has recently set records for greater ice extent, and there is no correlation to CO2.
Says who?
ACORN
http://i255.photobucket.com/albums/hh154/crocko05/ACORN_zpsmzrjjdc6.jpg
UAH – Australia
http://i255.photobucket.com/albums/hh154/crocko05/UAH%20-%20Australia_zpsemu6ihsl.jpg
According to UAH v6, there has been ZERO warming for neigh-on 21 years in Australia!
Michael Hart says:
Could you provide a link please.
Sure.
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/
V6.4 had a trend of .24
V6.5 the trend has drooped to .15
“I can’t speak for JoNova but from what I’ve read at her blog the biggest complaints are about the adjustments to the long term record…”
Yes, she did. She and a few others even made such a song and dance about it, there was even a review set up to look into it. Did you here about the results of the review?
https://www.environment.gov.au/minister/baldwin/2015/mr20150618.html
An independent review has endorsed the Bureau of Meteorology’s management of Australia’s official temperature record.
The Australian Climate Observations Reference Network – Surface Air Temperature dataset (ACORN-SAT), which is managed by The Bureau of Meteorology, is an important part of Australia’s official climate record.
The dataset is used to monitor climate variability and change in Australia and contains more than 100 years of temperature records.
This was set up by a conservative government, so you cant complain it was a white wash.
Bruce C
Where did you get your UAH chart from? and why does it stop in early 2015?
The chart is based on UAH v6.5 with a 12 month running mean, hence the early 2015 cut-off.
LOL, Daveo’s independent review went for ONE DAY (26th March, 2015) and contained 9 employees from the BoM (incl: David Jones, Rob Vertessy & Blair Trewin) and 6 employees from the Department of the Environment.
“Ps, what growing ice in Antarctica? If you couldn’t tell by the lack of posts here about it, sea ice is now below average. Both in Antarctica and in the Artic. It just set a new global minimum.”
You mean your lacking post that it is below “average” levels (whatever “average” is)? You mean below means MORE?
Antarctic Sea Ice Reaches New Record Maximum
http://www.nasa.gov/content/goddard/antarctic-sea-ice-reaches-new-record-maximum
NEW RECORD MAXIMUM, but new record maximum is less than average to global warming fanboys.
NASA Study: Mass Gains of Antarctic Ice Sheet Greater than Losses
http://www.nasa.gov/feature/goddard/nasa-study-mass-gains-of-antarctic-ice-sheet-greater-than-losses
http://www.nasa.gov/sites/default/files/styles/full_width/public/antarctic_seaice_sept19_1.jpg?itok=dOXhVW_K
The old Melbourne station near the historical society building was a riot! Huge glass fronted apartments and sky scrappers due south of that site and surrounded on both sides by paved asphalt.
Daveo, the key word missing in your comment regarding the initial enquiry into the BOM ACORN methodology is “independent”. Following a number of complaints regarding the results of this enquiry, a second was scheduled with genuinely independent experts, but was cancelled by the Minister for the Environment (Greg Hunt) who happens to be my local Member of Parliament. As a result I have notified him that after 50 years of supporting the Liberal (conservative) Party I will not be supporting either him or the new Prime Minister Malcolm Turnbull at the coming election due to their record on supporting the waste of money being spent on “green energy” alternatives. They do not reflect the policies on which the Government was elected with Tony Abbot as Prime Minister.
Overthrowing him before his term of Government was finished has led to a weakening in the sensible attitude toward warming alarmists that he had promoted.
Bulldog44
Daveo, the key word missing in your comment regarding the initial enquiry into the BOM ACORN methodology is “independent”.
An INDEPENDENT review has endorsed the Bureau of Meteorology’s management of Australia’s official temperature record.
it’s the second word in the quote, not sure how you missed it?
Daveo,
I meant independent in the true sense of the word. The group you refer to was composed of people selected by the BOM and even they made suggestions on the need for more transparency and clarity which would allow others to replicate the results of the Bureau’s methods – Totally ignored!
The plan put forward under Abbott’s leadership called for a review by outside experts in statistics and science. The fact remains that the BOM methodology remains shrouded in mystery and, “If results aren’t replicable they are false”.
My thoughts as well. As soon as I read about the UHI problem I asked the same question; we know the data is bad, it should be discarded. My guess (and I have nothing really to base it on) is some dweeb GS-12 decided it could be “fixed” by “adjustment” and the games began. Since then the entire land based temperature record has been corrupted to the point of uselessness. The sadder part is, once the door to fabricating data was opened, it grew like a fungus and became a kind of justification for even more egregious “adjustment”, after all, if it got a nod for UHI, why not anything else they can think of?
More important to me though is the UHI effect isn’t being given proper consideration. The conversation on that subject seems limited to the effects of local outside heat sources (A/C equipment vents etc.) and hardscape like buildings, tarmac and concrete. Occasional fences are mentioned (as in this article).
But I’ve yet to see a comprehensive investigation of what I consider the “elephant in the living room”, which is structural heating. Virtually all inhabited structures outside the tropical latitudes are equipped with some mechanism for providing artificial heat. Propane, natural gas or electric are the most popular, some use wood stoves, but all of them generate heat.
While one or two buildings might not have an effect on average climate, certainly billions of them will, and the effect will be most noticeable in high density population areas, but I haven’t seen any discussion of this. Surely it should be easy enough to estimate, especially in industrialized countries, just by measuring the number of kilowatt hours or cubic feet of propane/natural gas used in an area? These devices essentially do nothing more than heat air, which naturally escapes the structures. They’re primarily used at night.
Warming alarmists are quick to point out the “real” problem (as if there was a real problem), isn’t higher highs, it’s higher lows, which occur at night. When people everywhere turn the furnace on. Near temperature sensors. In cities and suburbs (and even in the countryside) all over the planet.
What astounds me is these so called “scientists” haven’t figured this out. I think they’re being paid too much.
fascinating and important info. NOAA/NASA have an agenda. It is obvious. They can make the temperatures, past and present, anything they want them to be, and of course the want the past to be cooler than the present. Urban heat islands, be damned. They don’t care. They fill in whatever numbers they thinnk they can get away with to try to support their nonsensical AGW hypothesis…. and to keep the money rolling in. It is all a travesty and a dark period in science.
Considering that even with NOAA’s inclusion of recording stations with the UHI effect, the overall temperature of the US is not showing much warming occurring. This is not a good sign.
I think it’s remarkably coincidental that the “flattening” of the warming trend in the US lines up nicely with a virtual cessation of new home construction. Maybe just happenstance….
I’ve added an addendum at the end, with this graphic:
w.
Interesting plot Willis. A lot of that scatter may be from microscale influences, beyond the overall urban influence. Anthony’s work definitely points in that direction.
It should possible to correlate population growth by decade (US census data) to temperature trend by decade.
Yes, that would have been what i’d expetct. Maybe Willis could explain the logic behind dT vs pop.
What would be more revealing is to compare the difference of Parker to a nearby rural site that has remained rural and plot the temp difference against Parker pop.
SadlyI don’t have time, I have to do some real work on an injector pump and stop messing around on WUWT. 🙁
Willis, thanks. A good addition.
Nicely done Willis. And how many therms does the average household consume for heating? My bet is that correlation will even be stronger.
Great investigative work Anthony. I especially like the map plot of temperature trends in CA. It would be nice to see similar plots for other parts of the US and to see maps showing trends for both USHCN and USCRN sites for the same time period. I recently looked at temperatures at Mount Washington NH, which does not appear to be a USHCN site. I’m not sure why, since it may actually be a good site to measure trends in the lower troposphere. This is my take on the temperature trend patterns, which seem to be very similar to the satellite derived TLT trends:
It would be interesting to see a few USCRN sites established on high mountain peaks. Mauna Loa and Pikes Peak come to mind. I realize this is much easier said than done for places like Pikes Peak, but should be doable. With all the CO2 and other measurements from Mauna Loa, I’m surprised that I can’t find any temperature data. Shame on NOAA.
Mt Washington has had a weather station from 1933 to the present. Not sure why the graph only starts at 1948. I have checked into this from time to time over the years, but not have been able to construct the continuous data from 1933:
“…Normal, Means, and Extremes:
The following tables provide the “normal” average weather conditions on Mount Washington for each month, averaged over the period of 1981-2010. Also included are the extreme (record) conditions recorded during the station’s history, from 1933 to the present….”
Reference: https://www.mountwashington.org/experience-the-weather/mount-washington-weather-archives/normals-means-and-extremes.aspx
They must have all that information somewhere, but I can’t find it on their site even though they have “archives”. (Maybe it contradicts Global Warming).
Philip, the NCEI web site only had data back to 1948 and January 1948 was incomplete. Not sure why they don’t have the older data.
I know I have contacted them about this (CAGW) and never got a satisfactory answer. Have seen their site recently and they did away with some of their “Past Projects” had eliminated some of their older data…
Sure would like to see all there older DATA…
oz4caster:
I used Ipswitch WS_FTP successfully for a number of years for file transfers. I am sure there are others but it worked very well for me.
oz4caster February 19, 2016 at 5:24 pm
Hourly temperatures at Mauna Loa since 1977 available here … no shame on NOAA.
w.
Also, oz4, you might enjoy this analysis of the MLO temperature record …
w.
Thanks Willis. Shame on me for forgetting I had seen this ESRL link once before. Since I retired, I have had trouble trying to get FTP data that I used to get easily at work. I have FireFox on Win7 and installed FireFTP, but it never connects to any FTP site. I have not been able to figure out what is blocking it, although I suspect it is my Norton AV. I have the same problem with Tony Heller’s new software, it won’t connect to FTP.
Looks like the Mauna Loa data through 2006 does not show much upward trend since 1977, despite all that extra CO2 measured there, and shows a downward trend 1999-2006. Too bad NOAA doesn’t have temperature data going back to when the CO2 measurements started. If I can figure out how to get the FTP data I will go and get it. Even back to 1977 is slightly better than the satellite and CFSR temperature data. I’d like to see what has happened there since 2006.
No worries. Just for you I just put the zipped files on dropbox here. Only goes up to 2014, but it’ll get you started.
Thanks Willis. Got the data and will crunch through it an post on it soon.
oz4caster, Firefox is self destructing and it becomes even bigger entropy laden bloatware. I dropped it last year because of a slew of problems. Others are doing the same:
http://www.computerworld.com/article/2893514/an-incredibly-shrinking-firefox-faces-endangered-species-status.html
The Firefox market share continues to slide:
http://www.w3schools.com/browsers/browsers_stats.asp
I use Chrome now, and have uninstalled Firefox…nearly all of the weird problems in browsing have disappeared now.
This phenomenom of less cold night temperatures and less warm day time temperatures seems to be all around the world. It also shows up as a trend of less cold and less warm over the period of record in a lot of locations. Bob Tisdale wrote an article on diurnal variation with respect to the GCM model expectations but it seems to me clouds and a whole lot of other things could cause this. A lot of people have commented on this trend both in the diurnal record and the long term record. The long term temperature has been showing this trend for up to 125 years based on the data I have downloaded. I have no idea what it means, just an observation. Most places haven’t been getting warmer, just a tad less cold. I don’t see that as a problem except for missing some of the 40 below November cold spells we could use to kill the pine beetles in Alberta and Eastern BC.
But other than in Bob’s Analysis, I haven’t seen a lot of discussion on this issue but it is there in the Mona Loa data. They say it is consistent with CO2 warming per the IPCC but then they say it is also consistent with SST. Their paper rejects cloud cover since there is no distinctive seasonal variation in the Diurnal Temperature Range from season to season. I am unconvinced yet, then they say it might be Anthropogenic CO2 (although they say it in the negative – “does not reject the hypothesis that the decrease in DTR may be associated with the increase in global anthropogenic CO2.”
Their conclusion is that it “might” be due to anthropogenic CO2 or it might be other factors, more study is required. I believe Bob Tisdale’s writings cover this along with information from BEST and comparisons of DTR from southern latitudes to northern latitudes. But the data doesn’t match the models … yet.
Interesting information but no strong conclusions.
With apologies for including a long quote but this closure of minimum temperature and maximum temperatures both diurnally and over the total period of record at many sites has intrigued me for a very long time (perhaps 20 years or more).
The Mona Loa summary published August 31, 2011:
Bob Tisdale’s paper dealt with this in detail and the fact that observations and models still don’t match (my interpretation). I am left wondering since even correlation does not mean causation.
oz4caster:
I used Ipswitch WS_FTP successfully for a number of years for file transfers. I am sure there are others but it worked very well for me.
Thanks Willis and oz4. Looks like if you average out the noon temps and the midnight temps you would almost have a horizontal line. (slightly uphill by a fraction of a degree) I realize that type of averaging is not really “Kosher” as far as climate scientists go but it is interesting. I wonder how their data compares to the satellite data since it is over the same period/years.
Lower daytime maxima and higher nighttime minima would result from more clouds.
Willis, I finally figure out what was blocking my attempts to FTP. It was my new high speed cable modem/router. The router firewall was the problem. I had to lower the firewall security setting from “medium” to “low” to get FTP to work. Did so and got the 2014 and 2015 Mauna Loa data and made a time series of compiled annual averages:
Write-up about it here:
https://oz4caster.wordpress.com/2016/02/24/mauna-loa-temperature-trend/
Thanks again for your help and inspiration.
Everyone, I found out that NOAA does now have a USCRN site on Mauna Loa. Below is a photo of the shielded and motor aspirated temperature sensors.
http://www.esrl.noaa.gov/gmd/obop/mlo/programs/coop/crn/img/img_crn_3.jpg
Que Stokes explaining that NOAA really doesn’t use that station and Mosher explaining how his “best” algorithm corrects that station to within .01 degree F.
Reblogged this on 4timesayear's Blog and commented:
You know, I don’t think the argument against CAGW is going to be won with equations – there are too many ways to play with the numbers and equations. The argument is going to be won with common sense arguments. And this is really good; it makes you reconsider whether the numbers are worth anything to start with. As I say, an average doesn’t melt ice anywhere.
You know, I don’t think the argument against CAGW is going to be won with equations – there are too many ways to fudge numbers. The argument is going to be won with common sense arguments. Those things that make you reconsider whether the numbers are worth anything to start with. Surface station temps don’t seem to be worth a whole lot (and for even more reasons than presented here). Keep up the great work, Anthony!
I agree plane old cold weather will do it and falling food production would sheet it home.
Unfortunately if the background post LIA trend remains up they will manage to keep this alive till all resistance is gone.
There are too many in the U.S. Congress and Senate aligned with the climate change agenda to do anything about the temperature data situation. If this was not the case something would have already. been done.
Provides an excuse for renewable energy projects. Suits the big U.S. money interests.
Years ago when I learned that about a third of all weather station were not showing any warming or some were showing cooling, my thought then and now is until you can explain that, you cannot make any claims about what the overall climate is. Yet in this modern era, it seems hard work and good research, is a thing of the past.
Talk about dodgy data! Not quite another set of AC sets, but close.
Another great job Anthony. Very well explained. Somehow the meme must be pushed that in order to use less than ideal data – such as outlined in the piece – the real data (not the infiliated data) must be assigned a much larger error than would otherwise be necessary. ie, if the temp sensors calibrate at +- 0.2 deg C [NIST traceable of course] a much larger margin of, say 1-2 deg C must be assigned in these cases.
NOAA wouldn’t like this of course because the calculations of what is a ‘real’ remp quickly get a LOT more complicated. That very complication makes a convincing case showing that the data should NOT be used for climate change research purposes.
“remp” = temp, sorry!
Well, anorher expose, perhaps thanks to Tony Heller. For a much more ecumenical view from many more perspectives, see essay When Data Isn’t in ebook Blowing Smoke.
. For a sharp, specific criticism see guest post here concerning the karlization of temperatures. Yah, there was a slight post goof. Corrected in the comments. Karlization conclusion remainded unchanged.
Might have to have a look at some of the UK ones as well. I just had a look at the met office website and found the 2 nearest to me – one is at a busy RAF station, between the main runway and a carpark, another is in a park surrounded by mature trees right next to a busy main road near the city centre. Not ideal either.
“Tallbloke’s” been doing it.
https://tallbloke.wordpress.com/index-page-surface-stations-project/
Have a look at this PDF which explains what sites make up CET:
http://www.metoffice.gov.uk/hadobs/hadcet/Parker_etalIJOC1992_dailyCET.pdf
You will note that many of them that used to be in the countryside are now in built-up urban area’s so are also recording heat emanating from buildings, traffic etc, resulting in ‘The Heat Island Effect’
I know the one at Weston Park in Sheffield, http://tinyurl.com/nr7x39s .
Started in 1882 in a leafy suburb when transport was horse & cart, it’s now just ~25m from the busy A57, a major bus route on a steep hill. It’s close to two large concrete hospitals (the Children’s, 50m, & Western park 100m).
They use the large tarmac area 10m to the left to land the air ambulances, often there is an Ice cream van parked at the gateway with its engine running 20m away (you can see it in the sat view); so lots of false heat sources.
How meaningful can it be to compare current & historical measurements??
Oxford is shown in here – https://notalotofpeopleknowthat.wordpress.com/2015/07/14/heat-island-at-heathrow/
Somerset House, London http://tinyurl.com/qbhdxux
dickon66
Re airfield sites, I have often wondered if the amount of fuel that is burned in a sensible assumed volume within the airport perimeter to say 50 metres altitude, has the heat to change temperature in a measurable way. Airfields can be easier than most places to test for this type of UHI because they have a simpler mix of heat sources and often have public records of fuel use over time. Have you ever tried a ball park estimate to see if fuel burned can heat the local air measurably?
The REAL issue is that the guys at GHCN have absolutely NO IDEA how bad some of their stations.
It took Anthony to show just how bad the USA sites were, and the global sites could only be worse.
Quite so.
Yet Zeke (see his recent post on Climate etc) suggests that US sites need more adjustments (at least for TOB) than the global sites. I find that assertion rather surprising.
Personally, I would have thought that the starting point to any assessment of temperature data would have been to carry out a quality audit of the stations used to report temperature data, and then to identify only those which are best sited, have the best quality control/maintenance record and documented procedures, and those with the longest continuous record. I would have thought that those, and only those stations would have been used to put together the temperature data series.
It seems rather strange that one would wish to work with crud, not cream, and then try and adjust the crud. You can’t make a silk purse out of a sow’s ear however hard one tries.
Here is Jim’s spreadsheet in an interactive map (if you have a free ESRI ArcGIS Online account). (Edited longitude value for Livermore by 1° to the east)
http://arcg.is/1RdiA1w
“. . .because as we all know, CO2 can’t heat differently based on county population”. Really, I thought CO2 was sort of like a magic elixir, you can make it do whatever you want it to.
“Look at all that missing data, which I’ve marked in yellow. 10 days in November, 2015 and 16 days in December, 2015. Of course NOAA/NCEI “corrects” this by infilling it with other data from surrounding stations so that no station record is incomplete in their database”. This seems to me to be standard procedure!
What if financial institutions did this? – I’m sorry Mr. Smith, the bank manager said, but your financial and savings records are missing so we infilled from your neighbour down the street. What did you say? You have a million dollars in savings and your neighbour is up to his eyeballs in debt. So sorry, but this is standard procedure.
Why aren’t all these shenanigans being called, loud and clear, by the scientific community for what they are – FRAUD! This is not only besmirching climate science, but all of science.
A single picture is worth a thousand words.
Pictures of sites like this need to be sent to every media outlet and government representative.
Even if it gets just one or two to start asking questions, it is worth the effort.
A number of years, ago I ran across a map on the internet that appeared to be from a doctoral dissertation. It showed how the average temperatures had changed over the last 100 years in each of California’s physiographic regions. Just eyeballing it, it appeared that there was a strong correlation with population growth in each of the regions. Notably, in the NE corner of the state, which has a very low population density, it showed a decline in average temperature. When I last looked for it, I could not find it.
For in-filling, how many places are used and is there a distance limitation?
Phoenix is a few miles closer to Parker than is Las Vegas and at the stevengoddard site, he uses it to show the trend of UHI.
For what it is worth, a poorly sited station might give incorrect discrete data and still provide an informative trend. But only data from that site could be used and you would need it to be for 99.44% of the time. Otherwise, it won’t float. [Ivory Soap® ref.]
I used to live and farm in that Northeast corner of California and I can assure you the the useful growing season has been reduced 20 days since 1970. The temperature gauge at Cedarville, elevation 4600ft, also indicates gradual cooling from that time…pg
“…reduced 20 days since 1970.” I live near there now and know quite a few farmers/ranchers in Surprise Valley, and I would say they would not agree with your assessment, as there is still the usual three-month growing season, the duration of which fluctuates on an annual basis. The last three drought years have acted to lengthen the growing season. You might recognize my last name.
Your family has been in California as long as mine!
Anthony. Please continue sending out your message and sending it loudly. The more I read, the more I am convinced that global warming = UHI. We have the satellite data, which shows a slight warming from 1979, easily attributable to natural climate change. Then there’s the meaningless garbage from the ground-based data. Take away NOAA’s’/Gavin/Hansen’s fiddled ground-based data (and take away Mikey’s hockey schtick) and there’s simply nothing left that’s even worth talking about.
One could say that UHI, and few bad apples in the science community, have cost the world trillions of dollars from carbon hysteria.
So much of this goes on in oz but they don’t even need a badly sited screen to massage the data to suit .
Whenever I hear hottest day ever ,now I just think is that figure adjusted unadjusted ,since yesterday or 20 years ago or just plain made up .
Our BOM is just as big a joke as yours .
China and Indian temperature anomaloy — maximum and minimum since 1950 — shows slightly increasing trend in minimum temperature after around 1990 in India and even earlier in the case of China. Maximum temperature presents a plateau pattern during these periods. As the urban heat-island effect not only rises night temperature at ground level but also at higher levels — included in my book of 2010 — and thus with the advection [temperature gradient] the heat is also transported to peripheries in the wind ward direction.
The important point here is — majority of the met stations are located in urban areas.
Dr. S. Jeevananda Reddy
easy to get to, and the pre-climate doom days , this is where you needed to know the weather for . To be honesty who cared about the weather conditions in the middle of desert were no one lived.
“The important point here is — majority of the met stations are located in urban areas.”
Well, “Dr.” Mann (and the rest of the “team”) would tell you that is a good thing since all we care about is scaring the man in the street into accepting the dismantling of our industrial society.
“But NOAA says they can “fix” garbage temperature station data like this.”
It is beyond reason to think this can be fixed by any kind of routines. And as “Steve Goddard” (his real name is Tony Heller) has shown in multiple posts – NOAA even add a warming trend by their “adjustments”.
http://realclimatescience.com/wp-content/uploads/2016/01/2016-01-12-06-46-13.png
Tony Heller has a fine summary in this post:
History Of NASA/NOAA Temperature Corruption
On BBC 1 Scotland TV the weather forecasters put night time minimum temperatures on a map and often say “These are for towns and cities, the countryside will be 3 or 4 degrees (or sometimes “several degrees”) cooler.”
And BBC Weather in the East Midlands (of England) always several degrees difference urban to rural on still nights. Strange seeing as how these forecasts are still from the Met Office who are true believers in CAGW.
he who pays the piper calls the tune , the head of the MET office is ‘full on CAGW’ and can you blame them after all they done very well out of it .
It’s really too bad the satellite only goes back to ’79. I consider myself a “luck warmer”. But honestly I’m not entirely convinced the “true” global temperature today is any warmer than it was in the 1930s. Without trustworth data (or trustworthy keepers of said data), the only thing we can say for sure is that the ground based “record” is worthless.
Worthless and messed up beyond recognition.
Science 101 tells if you can’t accurately measure it you cannot know it you can only guess it.
The good news this is not and has never been ‘science’
What we see hear is a classic legacy issue , in the old days before ‘settled science’ we accepted that these problems existed however given the problematic nature of weather prediction there were not consider to be a show stopper .
And then came climate ‘science ‘ and with need the need for dramatic claims of unquestionable accuracy and has part its religions nature, where doubt , let along critical analysis normally seen in science, were forbidden. Only all of these types of problems had not be solved they merely been pushed aside over ‘forgotten’
Considering the surface station project, I wager we are well past how not to measure temperature #97.
I recall when the government said that it was going to spend a fortune of the poor people’s money (taxes that is) to put up satellites to measure the global temperature. I was under the impression that these satellites were going to provide good coverage of the whole of the earth — even over the oceans were we have no thermometers at all. (at least I don’t think we have a set of floating air temperature devices covering the whole ocean)
I had hoped that the system would expand till we could see the temperatures from the surface to the top of the atmosphere; or at least that would be the goal even if that is a bit of over-reach for now. We have spent Trillions of Dollars on
fakery“climate research” so we could have spent the money to get near total coverage from space.But something went wrong. The climate boys discovered that the temperatures measured from space did not fit the “CO2 will destroy us” mythology and so NASA and others decided that the satellite system was no longer a priority. Heck, it was hard to “adjust” the space readings on a daily basis to cool the ’30s and heat the present. What good are they if they don’t support the narrative? (see “Wag the Dog” for a wonderful speech on that issue — one of the best scenes in movie history)
To a common man of the 50s or before, the fact that “the books had to be cooked” tells you that there is something very fishy in the reports purporting to tell you the “bottom line”. But in this degraded time of low logical skills, the “climate boys” think that conformation bias is a good thing. Oh my.
I was raised in California and Arizona as was my parents, grandparents and great grandparents and in the case of California, since 1849. There have been several cool/hot cycles during this time which we all talked about over the last 150 years. My grandfather loved to tell about how they all nearly starved to death a very cold cycle in the 19th century and as his mom cooked the last food, some dried plums, into a ‘pudding’ she tripped and fell due to catching her toes in a knothole in the floor and it fell and spilled so they ate it all off the floor which impressed him greatly, being a very small child.
I remember the late 1960’s to the early 1970s and we all talked about a new Ice Age coming due to it being very cold and wet even in Tucson, of all places! I remember buying up all the furs we could find at Value Village to make blankets out of so we wouldn’t freeze at night since our pre-statehood homes in downtown Tucson had no central heating. Brrrr. It was really cold at night!
Wiping out the past is what ‘climatologists’ did for several years now and it is very irritating to watch this travesty in science.
By the way, this February in upstate NY feels like Antarctica, with lots of wind and chills. Highs below freezing this coming week when we should be warming up, not getting colder and colder. It is colder, much colder than December and this lopsided weather is a sign of climate change…to colder weather in general.
…If Canada gets any colder, it will no longer be known as ” The Great White North “, it will suddenly be known as ” The Great Northern Popsicle ” and Canadians will start flooding across the border by the millions ! Lucky for me I’m half American !
How will you get over “the wall” Marcus? /sarc off 😉
Has the Parker site changed much to cause the minimum temps to rise like that. If it was always like that, shouldn’t the minimum temps follow the same pattern of variation as the maximums?
Yes, it’s a BS site but has the site gotten worse over time besides the tree growing larger? (eg originally just the building, then fence added, then cooler added to building, then junk cars added…)
Analitik: “shouldn’t the minimum temps follow the same pattern of variation as the maximums?”
No. The minimums will be less due to many factors and will be “smoothed” per the explanation Anthony gave along with other factors. UHI is likely one of the reasons that the Diurnal Temperature Range is less now than in a pristine site. It’s anthropogenic but not CO2.
I would like to add that the highest temperature ever recorded in the UK was recorded in July in SE England. The Met Office thought all their birthdays had come at once, when it his was announced. Fortunately common sense prevailed when it was pointed out that the only weather station to measure this record breaking temperature was sited next to a runway at Heathrow airport!
Although that information had to be dragged out of them and of course the ‘headlines ‘ over this claim had come and gone . Even today the MET office still makes much over this ‘record’
I would suggest to make a (multivariate) regression of the temperature on both CO2 and Population as independent variables. Then we probably would see that population growth contributes significantly to the R-square. Your first graph hints at this in a graphical way. Otherwise the correlation of temperature with population observed could possibly be dismissed as spurious.
Note that the frequency of apparitions of Maria in the period 1531 – 2010 is also correlated with global temperature.(“Seeing Mary”, National Geographic Magazine, December 2015, p.40-41)
M.H.Nederlof
History of airport thermometers: when prop planes flew, they didn’t heat up much of anything and when airports were paved (they were grass in the very old days) it got hotter and then jets and lots more asphalt and highways were added, this made them very big heat islands. Using them for temperature records over many years is insane.
One would almost think they weren’t interested in the actual temperature trend.
Actually they weren’t interested in trends or the climate at all when setting up these weather stations. Many stations are at airports because aviation is very interested in the local weather, and a few degrees + because of UHI doesn’t matter at all. The wind speed and precipitation is a lot more interesting as far as a pilot is concerned, and perhaps if it is below freezing.
The effect of the urbanisation bias is excluded in the following research of Willie Soon & Conolly & Conolly. After doing so, the new record is consistent with other important estimates. See below.
WR: my conclusion: using biased surface temperatures makes it IMPOSSIBLE to do good science on climate. You can not compare bad data to anything at all. Therefore getting unbiased surface temperature records should be the first thing to do for every herself respecting meteorological organisation.
Anthony, you did do and still do the most essential thing: searching for the temperature records that are reflecting REALITY. My compliments.
===
Re-evaluating the role of solar variability on Northern Hemisphere temperature trends since the 19th century
Willie Soon, Ronan Connolly, Michael Connolly
ABSTRACT
(….) Then, in order to account for the problem of urbanization bias, we compile a new estimate of Northern Hemisphere surface air temperature trends since 1881, using records from predominantly rural stations in the monthly Global Historical Climatology Network dataset. Like previous weather station-based estimates, our new estimate suggests that surface air temperatures warmed during the 1880s–1940s and 1980s–2000s. However, this new estimate suggests these two warming periods were separated by a pronounced cooling period during the 1950s–1970s and that the relative warmth of the mid-20th century warm period was comparable to the recent warm period.
(….)
We then compare our weather station-based temperature trend estimate to several other independent estimates. This new record is found to be consistent with estimates of Northern Hemisphere Sea Surface Temperature (SST) trends, as well as temperature proxy-based estimates derived from glacier length records and from tree ring widths
Sorry but this issue has recently been addressed by Hausfather et al. (2016) and it is clear that the homogenized data track temperature trends at “pristine” stations better than unadjusted data. The computer code is also available. I challenge anyone here to publish a rebuttal to Hausfather et al.
From the abstract
Numerous inhomogeneities including station moves, instrument changes, and time of observation changes in the U.S. Historical Climatological Network (USHCN) complicate the assessment of long-term temperature trends. Detection and correction of inhomogeneities in raw temperature records have been undertaken by NOAA and other groups using automated pairwise neighbor-comparison approaches, but these have proven controversial due to the large trend impact of homogenization in the United States. The new U.S. Climate Reference Network (USCRN) provides a homogenous set of surface temperature observations that can serve as an effective empirical test of adjustments to raw USHCN stations. By comparing nearby pairs of USHCN and USCRN stations, we find that adjustments make both trends and monthly anomalies from USHCN stations much more similar to those of neighboring USCRN stations for the period from 2004-2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records.
The url for the article:
http://onlinelibrary.wiley.com/doi/10.1002/2015GL067640/full
Zeke does not show what you think he shows. Perhaps even whatnhemthinks he shows.
CRN are by definition pristine rural. The closest USHCN will also be rural, but perhaps not pristine. That there is post USHCN pair wise homogenization a good match just implies few microsite problems. Says nothing about mostly not pristine (this post being an example) or UHI afflicted (this post Las Vegas being an example) or the general growth of both microsite issues and UHI with population density (this post Goodman data being a clear example).
Comcerning the comclusions of this post, Zeke’s paper is NOT a rebuttal.
@Luke: Am I getting that right? Adjusted data is more similar to the standard it has been adjusted to than unadjusted data? Well, that’s a definition of “adjustment” and it would have been newsworthy if the adjustments were AWAY FROM the curent standard rather than TOWARDS it – but what makes you (or Hausfather) think that these adjustments bring any of the data closer to local reality than the raw measurements? I for one view it with suspicion when two originally independent data sets (i.e. two neighboring stations in whatever network) generally become “much more similar” after adjustment. Sounds like wilfully losing information to me, the adjustment does not spot and correct real errors as they happen, but smears everything with the same brush, so you end up with lots of stations, but with so much spurious correlation by adjustment as to make them no better than a mere handful of independent measurements. It is foolish to assume that random noise will even out this way, it is more like every signal contaminating all the others, ending up with a pretty meaningless mish-mash.
Chris Z says “but what makes you (or Hausfather) think that these adjustments bring any of the data closer to local reality than the raw measurements?”
The answer is very simple, the data says so.
“the adjustment does not spot and correct real errors as they happen, but smears everything with the same brush”
No, the adjustments are much more complex than you suggest. Any time you have data sets with millions of observations there is the potential for errors in the data. The question is whether you try to identify those data points and adjust them or simply use the raw data. Their analysis suggests that the algorithms they use to make the adjustments improve the data and make it more similar to pristine sites. If you really want to know what they did, the code they used for the adjustments is available.
Evaluating the impact of U.S. Historical Climatology Network homogenization using the U.S. Climate Reference Network
“Non-pay-walled version:
http://www-users.york.ac.uk/~kdc3/papers/crn2016/CRN%20Paper%20Revised.pdf
“Conclusions
During the period of overlap between the USHCN and USCRN networks, we can confidently
conclude that the adjustments to the USHCN station records made them more similar to
proximate homogenous USCRN station records, both in terms of trends and anomalies. There are
no systematic trend biases introduced by adjustments during this period; if anything adjusted
USHCN stations still underestimate maximum (and mean) temperature trends relative to USCRN
stations. This residual maximum temperature bias warrants additional research to determine the
exact cause.
While this analysis can only directly examine the period of overlap, the effectiveness of
adjustments during this period is at least suggestive that the PHA will perform well in periods
prior to the introduction of the USCRN, though this conclusion is somewhat tempered by the
potential changing nature of inhomogeneities over time. This work provides an important
empirical test of the effectiveness of temperature adjustments similar to Vose et al. [2012], and
lends support prior work by Williams et al [2012] and Venema et al [2012] that used synthetic
datasets to find that NOAA’s pairwise homogenization algorithm is effectively removing
localized inhomogeneities in the temperature record without introducing detectable spurious
trend biases.”
I used to think that the foundation of caGW was built on sand.
I was wrong.
It’s built on asphalt.
Because of the persistently cold winter here in laramie, I got interested in local temperature and began tracking the airport AWOS data (klar). I noticed in January that days where the hourly data never rose above something like 20F, the maximum reported temperature would indicate something higher, even by as much as 7 higher. So far I have not found data taken in detail to show the nature of what must be some shortlived anomalous spikes.I have investigated the siting of the station which is between a taxiway and runway, but not especially close to either. All I can surmise is the drift of jet exhaust from the terminal building far to the north of the station. Nonetheless this has made me suspicious about the value of data from this station for some uses. I am pretty certain KLAR is not used in climate compilations, but it is one of the better sources of data from this region.
Then I found by serendipity a publication of the College of Ag at UW entitled “Temperature probabilities in Wyoming”. The data used to build the probability density were from the period 1930 to 1960, and I thought to myself that this should be a long enough period to build a reasonable control chart if climate is a stationary process, and then test it against historical data from after 1960. I built a chart for minimum temperature, but what I found is that observed data violated the lower control limit immediately and often. While the minimum temperature in January never reached below -30F, which was my 95% lower control limit for the period 1931 to 1960, minimum January temperatures from 1961 to 1975 or so routinely reached -40 to -50. I suspect that the coldest part of Winter in Laramie shifted from February during the 1931 to 1960 period, to January in the period 1961 to 2016. It may be shifting to even earlier in the winter season in most recent years. haven’t yet had to time to test this idea.
Parker?
yes
Its a good proof of how homogenization works!
the RAW data is crap
Raw monthly anomalies 3.07
After quality control 3.05
After breakpoint alignment -0.27
Skeptical hypothesis? homogenization pollutes good stations with bad stations.
Wrong
homogenization can correct even microsite
http://berkeleyearth.lbl.gov/stations/34568
If the data is crap to begin with then what are you left with after polishing it?
(An aside for Mosh. Have you ever taken an area, say 50 square miles with 20 sites, randomly eliminate all but 2, run your program and see if your results are anywhere near what the 20 sites originally said to check your program?)
Mosh? My “aside”.
Are you working on it or ignoring it?
The only “control” for climate science is to compare the results against a known. There are no knowns to serve as a control. So take what you’re program says you know based on a bunch of observation, drop a bunch of those observation out, and see how they match.
” drop a bunch of those observation out, and see how they match.”
They do, but what he doesn’t explain is how they turn a station reading into something that can be compared to the field they calculate, without doing the same processing of the station data.
Told ya’:
http://wattsupwiththat.com/2016/02/19/how-not-to-measure-temperature-or-climate-97-californias-warming-air-temperatures-are-population-and-site-bias-related/comment-page-1/#comment-2149274
Yep, agree the solid fence makes a huge difference because it cuts off ground breezes. Levees do the same. Very distinctive effect when you’re walking in their vicinity.
Willis
“ADDENDUM: I hope Anthony won’t mind if I add this. I took Jim Goodrich’s Excel data from above, added county population density data, and that gave me the following graph:”
Sorry COUNTY population will get you wildly inconsistent results.
Even population at the sites will get you nothing.
Oke, who pioneered using population density, ABANDONED the idea
1. only captured MAX uhi
2. Was dimensionaly incorrect
3. Could change if the city in question changed their adminstrative boundardy
4. The coefficients of the regression are confounded with site/continent/wind
Google UHI in 419 large cities. You will a massive study done on the ttopic. Urban AREA
is the variable you want
Introduction of micro-siting factors, such as fences, air conditioners etc. may lead to abrupt step-changes in monthly average temperatures, but they do not produce ongoing gradual increases, characteristic of UHI. The gorilla in the room at Parker is the completion in 1934-1938 of Parker Dam upstream of the town. By curtailing spring floods, the soil moisture content–thus evaporative cooling–was gradually changed for hundreds of square miles around, That is a meso-scale effect totally ignored here.
BTW, the original station record is nowhere as broken as the GISS-homogenized version shows. Viewed in the correct context, it is a very credible record.
“Nope. It’s a siting issue. According to the B91 form, the Parker 6NE USHCN climate monitoring station is located at radio station KLPZ in Parker, it is a volunteer observing site, which sort of explains why NOAA gets what it pays for when we have 16 days of missing data in December 2015.
“NASA GISS keeps a plot of Parker 6NE data, and it seems missing data has been a hallmark of this station for quite some time. Notice all the gaps:”
here is Parker:
See how we adjust the trend DOWN
http://berkeleyearth.lbl.gov/stations/29136
here is Parker 6E
http://berkeleyearth.lbl.gov/stations/34568
Not finding Parker 6NE
Here’s Parker 6NE, before Hansenization:
http://data.giss.nasa.gov/cgi-bin/gistemp/show_station.cgi?id=425723700010&dt=1&ds=1
It took me a long time to locate the Parker monitoring station on the map even given the clues. It was so disguised by junk piles and dead cars, fences, asphalt, A/C evaporative coolers, concrete and radio station that it was lost. This certainly qualifies it as a NOAA Grade A Global Warming Recording Station.
Hello Anthony
Jim Goodridge, 2/20/16
Weather records best are imperfect indices of weather.
There is no such thing as a perfect weather record.
The search for more perfect observations yielded data loggers.
These loggers record humidity, radiation, temperature, wind and rain each minute.
Instruments are exposed above the highest expected snow accumulation.
Wind causes rain gage under catch as described by Koschmieder in 1934
When historical continuity is important, too bad, cities encroached on exposure.
The tenure of observers is at most only one lifetime.
We can except blemished weather records or be forced to do without.
More perfect weather records are on the way with RAWS, Snotel and CIMIS.
Data loggers with more perfect exposure started about 1980.
California’s oldest temperature record was in the 1840s at Fort Ross,
With records in degrees Reaumur, published in Moscow in the 1840s.
We either accept blemished records and pray contents contain useful information.
A hundred years is not a long time for civilization only for us today.
From abacus to Excel in 50 years is progress; it is accelerating with great promise,
From stick measurements on rooftops to data loggers on mountaintops.
It is too soon to throw out blemished records when needing a historical perspective
Warmists have adjusted the records to show it was colder in the past then sold this apparent warming as an increase in the midday maximum with images of bushfires and boiling seas.
This excellent article may be the turning point to show what has really happened and why there is nothing to fear.
There’s no evidence of a loss of nightly cooling, so land use, ocean cycles and idiotic post processing are strong candidates for all the measured increased, whatever they really are.
FWIW, Pike’s Peak Colorado is probably as susceptible to UHI as more populous locations. It is a popular tourist destination during summer months.
“Study: Urban backyards contribute almost as much CO2 as much as cars and buildings”
One too many “as much”-es.
Sorry, Mods: posted that last in the wrong topic. Mea Culpa