Note: clearly satellites can see urban heat, as demonstrated by this recent paper unveiled at the 2010 AGU meeting by NASA. See: Satellites Image the Urban Heat Islands in the Northeast. It can also be demonstrated that the UHI biases the thermometers upwards. As cities grow, so does the increased bias. In that paper NASA says:
The compact city of Providence, R.I., for example, has surface temperatures that are about 12.2 °C (21.9 °F) warmer than the surrounding countryside…
So when you see images like this one above, where the satellites can clearly see the UHI, wouldn’t it make sense to then just look at the biggest low pass filter heat sink on the planet, the oceans, to see what the difference might be? After all, we don’t have urban heat islands in the oceans. Frank Lansner thinks it is worth exploring in this guest post. – Anthony
UAH reveals Urban Heat
Guest post by Frank Lansner
How UAH (University of Alabama, Huntsville) satellite temperature data supports Urban Heat (UHI) as a real and significant factor when estimating global temperatures.
Northern Hemisphere temperatures in recent years:
Fig1. UAH global temperatures trend equals global sea surface temperatures: The black temperature graph – average RSS+UAH satellite NH (Land + Sea) – has a smaller warming trend than the other (brown) land data series – but in fact resembles the cooler Sea Surface Temperature trend. (The blue graph “CSST” is an average of the rather similar SST´s: MOHSST6, HADSST1, HASSST2, ERSST.v3b, HADISST1and Kaplan SST 98.)
The satellite data represents both land and ocean temperatures – and yet they resemble only the SST´s. Why ?
Satellite temperatures and SST do have one thing in common: They are for sure without the UHI warming error from the cities and airports – they are excluding UHI:
Fig2. Now we split the UAH data up in a land fraction and an ocean fraction. Both still seems to yield considerably lower temperature trends than the land data (brown) measured from mostly cities and airports on the ground.
So UAH land temperatures have colder temperature trend than the ground based land temperatures. Are the land-data deviations due to general issues with the satellite data then? Perhaps the satellite data happens to show colder trends for some “known” reasons etc?
Not likely: There is a good resemblance between the UAH ocean temperature trends and then the directly measured ocean data, SST (“CSST”). This shows that satellite data (and thus also satellite land data) are indeed useful and likely to be correct.
So, unless the satellites always starts to fail just when flying over land, the deviation between land data measured on the ground (mostly from cities and airports) vs. satellite land data is likely to originate mostly from the ground based land measurements. This “extra heat trend” seen in the ground based land temperature data may be explained by UHI + possibly faulty adjustments of data and siting problems.
– One more result might also support the correctness of UAH data:
Systems will always seek equilibrium.
On fig 2 we see a pattern of gabs between the UAH land and ocean data. However, after the gabs the UAH land and ocean data these data unite again and thus despite the temporary deviations, they still seem to produce a common trend.
Is it surprising that the temperatures over land and sea will seek equilibrium? Or would it rather be surprising if they did not? What force should maintain a still bigger difference in temperatures between land and see trends?
Fig 3. Lets focus on the temporary gabs between satellite land and ocean temperatures. The green curve represents a de-trended version, just the difference between the land and ocean temperature data from satellite. From fig 3 it appears to some degree that land and sea temperatures align or reaches equilibrium mostly when temperature do not change fast.
Lets take a look at the same phenomenon in the decades just before the satellite age – I use original temperature data published en around 1974-84 for this:
Fig 4. On this illustration we have confirmed, that the land-AIR temperatures are fastest to reach a temperature change “100%”, then the Marine-AIR temperatures comes soon after “80%” and finally the sea water surface temperatures reaches the new temperature level. Again it seems, that after a given time ocean temeperatures and land temperatures tends to find equilibrium. The bac-to-equilibrium-between-land-and-sea-surface-temperatures seems to happen whithin few years, escpecially if general warming/cooling pauses or reverses.
With a reasonable argumentation that also the Land fraction of satellite data is a good indicator of land temperatures, lets look at the “extra heat” seen in the ground based land temperature measurements (mostly from cities and airports). How much “extra heat” do the ground based land data contain?
Fig5. The extra heat in CRUTEM3 land data compared to UAH on NH is 0,103 K per decade.
Fig6. On global scale, the extra heat in CRUTEM3 land data compared to UAH on NH is 0,088 K per decade. (0,23K over 26 years from 1981 to 2007).
If the extra heat in data measured on land is applied to a period 1900-2010 – just to get a rough idea of the possible impact – using 35-40% land area as hadcrut does – we get global extra heat of +0,34 to +0,39 K added to the overall warming of the Earth related to the extra heat occurring when measuring from cities, Airports etc.
0,34-0,39 K is roughly half the supposed global warming 1900 – 2010 , but in this context we cannot claim to have quantitative precision, obviously. But the rough estimate of 0,34-0,39 K suggests that the impact of “extra heat” that cannot be detected by satellites plays an important role when trying to estimate global temperature trends.
The problem of “extra heat” in land temperatures (likely to be UHI and more) is escalated by GISS because they extrapolate the ground based land temperature measurements over the oceans in stead of using real ocean data:
Fig7. In the case of Hadcrut temperature series they use around 35-40% land data when calculating global data, but GISS have a temperature product using roughly twice this fraction for land area as fig 7 shows.
Fig 8 until around 2008 this illustration of land vs ocean temperatures was online at the NASA/GISS website. As we have seen, satellite data indicates that land temperatures from ground has trend around twice the trend of land data from satellite data – and as almost twice the warming trend of SST, ocean data. This tendency is confirmed on fig 8. From 1880 to 2007 we have an ocean warming trend around 0,6K and for land its around 1,2 K – twice.
Again, we saw from 30 years of satellite temperatures that global satellite data matches ocean temperatures rather closely. If valid, then the fig 8 indicates a 0,6 K faulty extra heat, UHI etc from 1880 to 2007.
****
Article from which most graphics where taken:
Review and feedback of the above article by E.M.Smith, Musings from the Chiefio:
“The rewritten past”: http://chiefio.wordpress.com/2010/12/13/the-rewritten-past
Well if this isn’t a”Spanner in the Works”….
Great analysis, thank you Frank Lansner.
“So, unless the satellites always starts to fail”
s/b
“So, unless the satellites always start to fail”
Cool …
Ah yes, the revisions are coming fast and furious, to try and make the newly fabricated GISS data meet up with the whims of what is desired to be. All to try and convince ignorant people, while they are freezing, and the hurricanes all but disappeared, that they are going to melt by exhaling. But looks like thermodynamics isn’t playing along.
Satellite data, who needs it – we have “peer” reviewed paper covering some Chinese cities that establishes that the UHI is minimal, please move on – this issue is settled, and no you don’t get to see the Chinese data. Trust me, I’m a scientist.
Frank Lansner wrote, “There is a good resemblance between the UAH ocean temperature trends and then the directly measured ocean data, SST (“CSST”). This shows that satellite data (and thus also satellite land data) are indeed useful and likely to be correct.”
There is? You have not illustrated it. Please provide a link of the graph from which you are drawing your conclusion.
Also, your first comparison only includes the Northern Hemisphere. Why? Please show the Southern Hemisphere or the global data.
Anthony, why can’t somebody just calculate the earth’s temperature using data from stations unaffected by UHI? I’d be more trusting of what this data says even if it showed an increase (and I suspect it would).
REPLY: Easier said than done- the problem is that only a handful have been identified in the USA that are free from UHI and siting biases, and we haven’t even begun to look at the entire world. – Anthony
I always enjoy Frank’s posts, and his little linguistic quirks make me smile. “Gabs” obviously means “gaps,” here. In German context, they sound identical. Great work, Frank. Your English is far better than my Deutsch. Someday I’ll tell you about a conversation I had while waiting for a streetcar in Stuttgart…
But what is GISS’s pretext for extrapolating the ground based land temperature measurements over the oceans instead of using real data? I’m boggled.
I wonder how Hansen will get this one swepped under the carpet, being it NASA who came with it.
The article at hidethedecline.eu (Part 1) certainly puts a fork in the question of why tree-ring data showed declining temperatures after 1960 and thermometers did not. They omitted the thermometer readings that declined!
The AGW charade gets worse and worse as it’s analyzed in the light of common sense. Unfortunately, the phony adjustments are hidden behind a flood of papers and data and, just as unfortunately, the material that uncovers these “blunders” is also scattered and buried. Short of getting the perpetrators to confess, this “trial” will drag on for some time.
But, but the climate scientists are able to adjust (nearly always upwards) for UHI. Enter Dr. Hansen. / end sarc.
Posts here today seem to be producing great one liners ie: made up is better than real life sorry mis-quoted should read ‘“Say what you feel, not what you can prove.”
And then from this post ‘possibly faulty adjustments of data and siting problems’ – now who around thesae parts has identified this many moons ago Mr Watts? Personally i’d crack a beer open and sit there with a knowing smile.
Nobody here should be the least bit surprised that the collection of measuring stations on building roofs, adjacent to parking lots and runways, at sewage treatment plants, etc. produce elevated temperature measurements. Those who have proposed $100 million to improve the land measurement system should not be surprised either. They should not get any of that money until they admit publicly that what they have now cannot be picked up by its clean end.
[REPLY – Ironically, looking at the 100-year trends, the sewage plants have much higher readings, but lower trend increases, possibly because any natural warming is being muted by all that steam. But other than that, badly sited stations do warm faster (during a warming trend), as well as urban and airport stations (well sited or not).]
@article
> The satellite data represents both land and ocean temperatures – and
> yet they resemble only the SST´s. Why ?
Rhetorical answer: The mass of the atmosphere (5×10¹⁸ kg) is only 0.004% the mass of the oceans (1.35×10²¹ kg). And the specific heat of water (4.1 joule/kg) is over 4 times that of air (1 joule/kg). So, no one should be surprised that water, in all of its forms, controls the global temperatures.
Tarpon: you write “But looks like thermodynamics isn’t playing along.”
Exactly! Im very happy that this message came across – i hope many readers can follow my desperate attempt to show this.
Thermodynamics isn’t playing along
but.. for UAH data thermodynamics IS playing along, thats the beauty.
In conventional graound (city) based temperatures we are missing some kind of new force to maintain a claimed still larger and larger distance between land temt and SST. A force that prevents land and sea surface temperatures to align, just as we see it in UAH data.
Thanks 🙂
I would like to see Dr. Spencer comment on this analysis.
This just about obliterates the conjecture that global warming somehow causes colder weather, as the MET has opined is the case in Britain. As has always been the case, Britain’s temperature is largely regulated by the sea around it.
Sorry, a tad off topic, but….
There is definitely some “urban heat” needed on Lake Erie…. smile.
This is absolutely gorgeous:
http://www.telegraph.co.uk/topics/weather/8205402/Ohio-lighthouse-turned-into-ice-by-cold-weather.html
……….Lady in Red
firetoice [REPLY – Ironically, looking at the 100-year trends, the sewage plants have much higher readings, but lower trend increases, possibly because any natural warming is being muted by all that steam
Steam is not quite correct and understates what is happening. Raw sewage flows through a relatively “insulated” system and the time from discharge at a home and entry into a treatment plant is measured in hours. Not a great amount of heat is lost. Unless the plant is located in some very extreme location the incoming year round wastewater temperatures are in the range of 10 to 20C . Important to understand most plants diffuse massive amounts of air into the wastewater to provide the 02 source for microbial decomposition. The aeration process becomes a highly efficient heat exchange between the wastewater and the ambient air. This is very different then simple proximity to a heat sink.
Other heat sources are from solids handling (such as anaerobic digestion and resultant methane flaring), heat from the mechanical equipment operation especially aeration equipment etc.
O/T – what are the chances of the Denmark Strait icing over this winter? The current satellite pics show there’s little clear water remaining.
Hi Bob, please check fig 2 for UAH ocan / direct SST compare. please check fig 6 for global land compare between UAH land and CRUTEM3 (land).
Why NH graphs to begin with? I was writing a complete overview of temperature data pre-global-warming to get unadjusted data. It was in this context i used NH data because these are much more available. I was not aiming to make something on UHI when examining NH data, but… data told a story of UHI. In the present writing i therefore made the global compare fig 6 before doing some rough qualitative calculations.
If I had a full time job doing writing for the climate debate I would remake all graphs for global, but sadly I dont. My writings are made in time i dont have 🙂 But still i think the message comes through and its my hope that peoble with sufficient time will take over where i came to. I would really really love to make 100% peer-reviewable articles (!!!!) but the time… the money.. 4 children… houserebuilding … recording of our third record on label with a rockband (www.beingfrank.net).. i wish there where 3-4 Franks.
btw Bob: Thanks for your KOE-article, i already used it in the Danish debate. it came in handy.
K.R. Frank
Frank Lansnser: Please provide a link to a graph that shows all of the individual SST datasets you have used in your CSST data, not the average.
Some of your choices of datasets to include in your CSST are very odd. If memory serves me well, MOHSST is a database of SST readings. It is included in the ICOADS database. That is, the ICOADS database is a larger, more complete database than MOHSST. And the ICOADS database is the database that the datasets (HADSST2, HADISST, Kaplan, ERSST.v3b) are derived from. Having MOHSST in your average would be like including an incomplete GHCN dataset in an average of NCDC, CRUTEM, and GISTEMP land surface data. Why is it included?
HADSST1 is obsolete and was replaced in 2005/06 by HADSST2. Are they still updating HADSST1? Why is it included?
HADISST1 has been satellite based since the early 1980s. This contradicts your statement that your CSST data is “the directly measured ocean data, SST (‘CSST’)”.
And the Kaplan SST data is globally incomplete, like HADSST2. If memory serves me well, there is coverage difference between the two. HADSST2 reaches into areas with seasonal sea ice, but Kaplan does not, meaning there is very little Arctic and Southern Ocean SST data in the Kaplan dataset. That is, the only Arctic Ocean SST data in the Kaplan is in the area north of the North Atlantic where the ocean remains relatively ice free year round. Also, I believe the Kaplan SST data has been using the Reynolds OI.v2 data since 2003, and like the HADISST data, the Reynolds OI.v2 is satellite based.
Let’s revisit your statement, “There is a good resemblance between the UAH ocean temperature trends and then the directly measured ocean data, SST (“CSST”). This shows that satellite data (and thus also satellite land data) are indeed useful and likely to be correct.”
The following graph compares global UAH Ocean TLT anomalies to global SST anomalies for the HADISST, HADSST2, and ERSST.v3b datasets. I do not see a “good resemblance” between them. The UAH ocean TLT data variability is significantly greater than the SST datasets, and the linear trends can be significantly different. In fact, two of the three SST datasets have lower linear trends than the UAH Ocean TLT data. And the reason the HADSST2 dataset has a higher trend is likely due to the splicing of the two incompatible source datasets in 1998.
http://i54.tinypic.com/2edcpix.jpg
I haven’t read the rest of your post, but I assume you’re blaming UHI effect for the difference between TLT anomalies over land and land surface temperature readings. How then do you explain the significant differences between TLT anomalies and land surface temperature anomalies in inland Africa? Here’s a comparison of UAH TLT anomalies and GISTEMP LOTI with linear trends for northern inland Africa. Not a lot of UHI in the Sahara desert, but the GISS data has a significantly higher trend:
http://i43.tinypic.com/if1oh5.png
And here’s a comparison of UAH TLT anomalies and GISTEMP LOTI with linear trends for central and southern inland Africa. Again, the GISS data has a significantly higher linear trend in a part of the globe that should not have a major UHI component:
http://i40.tinypic.com/1hb5sm.png
Those graphs are from this post:
http://bobtisdale.blogspot.com/2009/06/part-2-of-comparison-of-gistemp-and-uah.html
Basically, any conclusion you’ve reached that UHI is responsible for the difference between TLT and land surface anomalies is based on your assumptions from an incomplete analysis.
Stefan of Perth says:
December 16, 2010 at 3:05 pm
O/T – what are the chances of the Denmark Strait icing over this winter? The current satellite pics show there’s little clear water remaining.
I will tell you just that! Its very very exciting heres prognosis for 27 dec from the SMHI made 12 dec:
http://www.klimadebat.dk/forum/vedhaeftninger/is12dec.jpg
There are newer prognosis available now, but still between Christmas and New year, things are supposed to go baserk.
(“Baserk”?? Nah, I mean Crazy!)
Ice formations like this… im not sure when we had this the last time. Even ice drifting out in the North sea ?! I have seen some historical pictures a little like this from the 1920´ies but they reflected february conditions.
As I say in the Danish debate: If someones lost track of the ice on the north pole, ive found it. Its in Kattegat and the North sea.
For now today we have ice in Øresund, and in many spots 16 dec:
http://www.klimadebat.dk/forum/vedhaeftninger/is16dec.jpg
BUT: I have seen SMHI prognosis like this fail many time, so lets see what actually happens between Cristmas and the new year. Really exciting!
K.R. Frank
“Satellite data, who needs it – we have “peer” reviewed paper covering some Chinese cities that establishes that the UHI is minimal”
Maybe the Chinese UHI study focused on these Chinese cities ;-):
Satellite photos: The ghost cities of China
http://www.businessinsider.com/pictures-chinese-ghost-cities-2010-12?%3Futm_source&utm_medium&utm_term&utm_content&utm_campaign=fanpage#
“(PhysOrg.com) — A new study by scientists in Los Angeles, California has found that bright city lights makes air pollution worse because the glare of the lights interferes with chemical reactions that clean the air of pollution during the night.”
http://www.physorg.com/news/2010-12-city-air-pollution-worse.html
Now that is an interesting twist… not a big surprise since light photons do impact so many chemical processes but interesting if verified. Could it have an impact upon the Urban Heat Island effect? Maybe even a partial cause of it? Hmmm… questions…
http://PathsToKnowledge.net
It is a pity that the old [and current if they still keep them] records from coastal lighthouses could not be used exclusively to get a true UHI-free temperature sample of the earth. This would still show any true background warming.
Even Lady in Red’s Ohio lighthouse above would still show a trend [but may not “play along” as quickly as GISS would like].
Just musing here, but wouldn’t UHI being real and measurable just shift some portion of the A part of AGW from CO2 to UHI?
Stefan, could you link to the satellite picture you mention?
Talbloke and many others, thanks for reading and commenting!
K.R. Frank
As Bob Tisdale I’d like to see the global picture. Given NH is land and SH is ocean you may be missing so detail here. Having said that Fig6 is illuminating.
Has this sort of analysis made it into the peer-reviewed literature?
OT – but ironic
The “Gore effect” shows little respect for Gore’s hometown.
“Coldest December since 1942 grips Nashville”
http://www.tennessean.com/article/20101213/NEWS01/12130320/Coldest-December-since-1942-grips-Nashville
Great! And yet our esteeemed Huhne and Cameron have just previewed UK energy policies (electricity generation) that is so dedicated to expensive and unreliable (in the sense of not always on) Renewables, mainly wind, that I can’t even laugh so I should not weep. “Carbon” this and “carbon” that littered the speech, so I read. Sob.
Sorry mods, bit off thread, but the UHI fiasco is at the root of the over estimation of CO2 effect in the real world…
Good summary, thank you.
But, WWAD?
(What Would the AGU Do?) Would they accept this logical a presentation – that “removes” half of their vaunted funding and importance?
Frank, thank you for a stimulating article.
Eyeballing Fig 8 and assuming a land/ocean anomaly temperature coincidence at 1960 (this may be reasonable given the population growth and urbanisation since that date) gives gives an anomaly difference of 0.5Deg C to 2008.
The IPCC 2007 4th assessment report 3.2.2.2 Urban Heat Islands and Land use effects works very hard at downplaying UHI, a quote……
Hmmm,
I seem to remember a series of papers some time ago that discussed how the satellites were calibrated. If I remember correctly the raw data from the satellites has be processed by an algorithm that was created to get the output to match readings taken directly from “Known” temperatures. I wonder if UHI has been incorporated into this creating an AlGoreithm that shows warming where there is none.
If I am reading this correctly – and please correct me if I have misunderstood any of this ….
UAH from their satellite data are suggesting that this is a more accurate record than the global temperature records because of UHI not being properly allowed for in urban weather stations records (supported by NASA 3 yr research on UHI).
UAH suggest that the satellite data points to an actual global temperature anomaly / rise since 1880 of 0.6 k (celcius) rather than the 1.2k (celcius) claimed by NASA/GISS.
From my reading of them: the Manley CET (central england temperature records) show a mean CET temperature from 1659 to 1973 of 9.6 degrees C. The ‘corrected’ CET now used by CRU / HADCRUT includes stations in warmer areas and shows slightly different temperatures but with a mean average from 1971 to 2010 of 9.9 degrees C.
Comparing the Manley figures with CRU in sequence :
1971 (M) 9.7 (CRU) 9.68
1972 (M) 9.2 (CRU) 9.19
1973 (M) 9.5 (CRU) 9.54
I do not understand why CRU reduce the first 2 years and elevate the 3rd as I have understood they were both working with the same raw data.
The start date of the global temperatures used to show global warming is 1880 ( a short but very cold period); I think December 1880 was the start of the period used. The mean of Dec 1880 – Nov 1881 from Manley was 8.6 degrees C with a long term mean from 1659 to 1973 of 9.6 degrees showing the year of 1881 as 1 degree below the long term average mean.
The current mean produced from the shorter period of 1971 to 2010 from CRU / HADCRUT is, as above, 9.9 degrees C. That suggests a rise in temperature of 1.3 degrees C or thereabouts from 1880/81 according to CRU/HADCRUT.
Assuming that UAH are correct, and from the NASA data it looks pretty certain that that are, then the actual anomaly/increase since December 1880 is around 0.6 degrees rather than the 1.2 degrees or therabouts suggested by NASA / GISS (and similarly CRU/HADCRUT at 1.3)
CRU/HADCRUT do not seem treat 1880 as a below the long term mean temperature hence their stating the rise in temperature is around 1.3 degrees C.
CRU/HADCRUT use data which I suspect (?) is contaminated by UHI. If that is so and a correction by lowering of 0.6 degrees is in order then that suggests an actual anomaly / rise from 1880 of 0.7 degrees would be correct. Taking 1880 from Manley as 1 degree below the long term mean and adjusting current CRU/HADCRUT figures by -0.6 degrees to correct as suggested by the UAH data / study that brings the CRU/HADCRUT corrected rise / anomaly down to just 0.7 degrees. That is below the long term average by 0.3 degrees and suggests that since 2005 – when temperatures are shown as ‘static’ that we have actually been experiencing a slight drop in temperature since 2005.
As I say at the outset I may be misunderstanding one or more parts of this – so please put me right if I am wrong.
Thanks
“jorgekafkazar says:
December 16, 2010 at 1:11 pm
I always enjoy Frank’s posts, and his little linguistic quirks make me smile. “Gabs” obviously means “gaps,” here. In German context, they sound identical. Great work, Frank. Your English is far better than my Deutsch. Someday I’ll tell you about a conversation I had while waiting for a streetcar in Stuttgart…
But what is GISS’s pretext for extrapolating the ground based land temperature measurements over the oceans instead of using real data? I’m boggled.”
As can be understood from some of Frank Lansner’s comments above he is actually Danish rather than German as suggested in above post. Gap is probably more like őffnung in German.
We Sunny People will be vindicated!!!
They [non-Suns] will find that El Nino and La Nina are coupled to the Sun’s output.
The PO and AO are coupled to the Sun’s output.
The Poles lose heat faster that the Equator due to EUV. The thickness of the Stratosphere, Troposphere [therefore, the insulating effect] is coupled to the Sun’s EUV.
Remember the Sunspot peak predictions?? How they were 1 year, then 2 years, now 3 years late. Since 2005, “Quiet Sun”; maybe we are in a Maunder Minimum…
Again, my simple Solar/Earth Model [based purely on the 10.7 cm Flux] shows cooling at the rate of ~0.1 C/2.5 years [conservative value]. We have already lost 0.2C since 2005. The “Quiet Sun” has the average Flux values at ~85 [lowest value is ~67]; this is a little short of 250 during a Sunspot peak.
So UHI mis-measurement or not, the Earth is cooling; and cooling rapidly.
The melting of the Martian Poles can’t be due to CO2; could it be due to the Sun?? Measured from 1980 until 2000.
From 1670 until now, we have been in an active [ramp up] Sun. Now the sudden decade change [cooling] is upon us; and we aren’t prepared.
CO2, Cosmic Rays, Geothermal Heating, Volcanoes, etc., does one really think that these have a bigger effect than the Variable Sun. Under an Eclipse, the temperature drops 10 to 20C in a matter of minutes.
The Sun Rules, and it has been Quiet. We will be cold, very very cold.
Just reminds me of the climate gate email that is not often discussed where someone (I dont recall who off hand) notes its good that the skeptics at least have not yet made a point yet about the discrepancy between land and ocean temps, as the land should follow the sea and cannot warm at a faster rate for any physical reason. I have noticed this before, as it make no sense to have the land warm faster than the sea, unless there is a UHI influence in the data.
I greatly appreciate Frank Lansner’s wonderful posts and graphs. I also noted Bob Tisdale’s comments(corrections) and hope that Bob can assist Frank with something more complete according to the “raw” data. Thanks to both.
Hey this web site has become a major outlet of information for projects of mine. It’s very informitive.
Robert M says: at 4:59 pm
Go here and read what Dr. Roy S. has to say:
http://www.drroyspencer.com/latest-global-temperatures/
Under Kramer above,
“Anthony, why can’t somebody just calculate the earth’s temperature using data from stations unaffected by UHI? I’d be more trusting of what this data says even if it showed an increase (and I suspect it would). REPLY: Easier said than done- the problem is that only a handful have been identified in the USA that are free from UHI and siting biases, and we haven’t even begun to look at the entire world. – Anthony”
Agreed. Here is a set of plots for about 16 truly rural Australian BOM stations, mostly free of siting biases. The inland ones (which are at slightly higher altitude as well) do no follow the same pattern as the coastal ones. The coastal ones are generally flat over the last 40 years, the inland ones usually show a moderate temp increase. The increase must be from another cause, which I have not identified. The cause must be fairly local to the last 40 years, because if you project back or forwards a few decades you run into implausible numbers.
http://www.geoffstuff.com/SI%20GRAPHS%20AND%20STATS.doc
There’s a lot more explanation of this in draft at
http://www.geoffstuff.com/Final%20draft.doc
I got tired of looking for real effects when there was so much noise. BTW, the airports are not major fire-breating monsters – it’s unlikely that asphalt or engine heat are significant, as a personal view, except maybe at Broome.
Another piling-on rant isn’t necessary. The paucity of the global temperature records are nakedness themselves.
I’ve always been amazed by the observation that the most warming occurs in regions with fewest thermometers.
Old England says:
December 16, 2010 at 5:11 pm
===========================
I agree with everything you posted and think it needs no correction at all.
From a post on Irish temps awhile ago their land temps tend to be the same as the sea temp. Perhaps we should be extrapolating sea t 12000km over land rather than the reverse (Giss). That would get rid of all that unlikely hot orange color.
OT:
Madness at work courtesy of California…
“By JASON DEAREN, Associated Press Jason Dearen, Associated Press – 20 mins ago
SACRAMENTO, Calif. – California regulators on Thursday approved the first system in the nation to give polluting companies such as utilities and refineries financial incentives to emit fewer greenhouse gases.
The Air Resources Board voted 9-1 to pass the key piece of California’s 2006 climate law — called AB32 — with the hope that other states will follow the lead of the world’s eighth largest economy. State officials also are discussing plans to link the new system with similar ones under way or being planned in Canada, Europe and Asia.
California is launching into a “historic adventure,” said Mary Nichols, chairwoman of the state’s air quality board.
“We’re inventing this,” she said. “There is still going to be quite a bit of action needed before it becomes operational.”
California is trying to “fill the vacuum created by the failure of Congress to pass any kind of climate or energy legislation for many years now,” said Nichols.
A standing-room only board chambers featured testimony from more than 170 witnesses Thursday. Outside the chambers, a few climate change skeptics held signs reading “Global Warming: Science by Homer Simpson.” (…)”
+++
These people are crazy!
Looks like a very complex way of saying that the oceans warm up slower than the air over land.
You attribute all that the the urban heat effect, but couldn’t it just be that the capacity of the ocean to absorb heat is so much greater than that of land? Fresh water from lower layers surfaces, heated water disappears to the depth where it no longer heats up the air – which is what you measured in this exercise. On land, no such cooling mechanism.
Furthermore, the UHI effect is hardly a new issue. One previous study that also used satellite data found hardly any UHI effect, and a more recent study in Nature came to the same conclusion by comparing windy and calm nights.
And as always, one should be careful not to conclude too much from studies that have not been published in the peer-reviewed literature. Are you intending to submit your analysis?
Great article, but really I don’t understand the basic premise behind correcting for UHI affects. Aren’t the urban temperature measurements real measurements? Urban areas are warmer than non-urban, so what? How can you go in later and intentionally reduce the temperatures of urban areas, i.e. correcting for UHI. I thought the idea of measuring temperatures was to, well, measure temperatures. By doing UHI ‘corrections’ you’re now presently a false version of temperature. Sure, some urban areas are really warm, but their area is really small too, and I wouldn’t think when properly weighted over the whole earth it would make much difference at all. Bottom line, correcting raw data sounds bad and I just don’t get why it’s done.
Great article, but really I don’t understand the basic premise behind correcting for UHI affects. Aren’t the urban temperature measurements real measurements?
The problem is that c. 1% of the land is urban and 9% of the stations are urban. 17% of the stations are semi-urban and maybe c. 5% of the land is semi-urban. And that’s for just the U.S.
Foreign stations are likely to be much worse (with a disproportionate number in airports).
If you want to avoid bias, the same percentage of stations should be located in cities as there is urban landscape.
Bob, the “CSST” is taken as a raw average of these datra illustrated here:
http://hidethedecline.eu/media/PERPLEX/fig25small.jpg
As you can see, the black CSST is pretty much smack on top of all the CSST I used and I allowed to make this “rough” CSST to work with simply because all the different variations of SST mostly are very similar. Yes, the kaplan ends before the others, and stick out a little but this single outlier in no way makes the CSST move far away from the others as you can see. (there ARE big differences between the various SST trends but this mostly occurs before 1960. Thats why I only use it after 1960. Before 1960 i find the SST trends hopelessly in disagreement).
Bob, except for Kaplan I can use any of the other SST´s in stead of the “CSST” in this article and in wont change the point in the present article. besides, remember i use 5 yr avg.
As i wrote in the article it can all be found discussed and more in the article here (which I asked you to review half a year ago):
http://hidethedecline.eu/pages/posts/part2-the-perplexing-temperature-data-published-1974-84-and-recent-temperature-data-183.php
goto part 2, fig 25.
And here is how close the CSST is to HADISST and Reynolds v2 SST, for example:
http://hidethedecline.eu/media/PERPLEX/fig81.jpg
I just use CSST not to chose one specific SST. And if you had read my original article you would know that im aware the differences.
K.R. Frank
Like I posted earlier. When (in summer) I leave the city, drive home, passing by the airport, then into the country side, the temperature drops 9-10 degrees (courtesy of fancy new car gadgets that just happen to be accurate to at least .5 degrees F). True it is hotter at UHI, however; the total global area of UHI is??? And the rest of the globe is???.
Why attempt to massage UHI when just a few miles away there is data more likely to be accurate. I find the whole scenario a waste of time and energy, meanwhile those with I.Q.s greater than two digits ponderously argue this ongoing insanity.
Sense Seeker says:
December 16, 2010 at 8:09 pm
I’m really keen to hear your explanation as to how warmer water (by definition less dense) disappears to the depth.
The peer review meme yet again. This is an analysis by an amateur submitted to WUWT for discussion. Did you read Franks comments at 3:06pm?
I guess if Frank was sitting around in a GISS office getting paid 6 figure sum plus benefits plus grants for research all the while playing blog games I’m sure he’d refine and tighten up his conjectures and submit to a journal where he had some mates who could peer review it for him. His name is Frank, not Gavin or James.
You know it makes sense.
I’m really keen to hear your explanation as to how warmer water (by definition less dense) disappears to the depth.
Via ocean currents, perhaps?
And I still think that this should be submitted to peer review. There’s all kinds of valid excuses, but I am afraid that outside this blog few people will take it seriously if it isn’t.
Baa Humbug said:
Sense Seeker says:
December 16, 2010 at 8:09 pm
Fresh water from lower layers surfaces, heated water disappears to the depth where it no longer heats up the air
“I’m really keen to hear your explanation as to how warmer water (by definition less dense) disappears to the depth.”
————————————————————————–
That struck me too, Baa. I have an ocean swimmer in the family who is a keen student of sea temperatures and weather conditions around the coast. She assures me that cold water does rise up from the depths in certain wind conditions, which push aside and cool warmer water on the surface. Time to don the wetsuit. But, for obvious reasons, the reverse does not apply.
Now, look at the Southern hemisphere, just to complete the picture.
What about people removing snow? that’s also urban activity that seems natural but it really isn’t…?
Here and there on the globe, there seems to be a necking together of global temperatures around and just after 1990. Not always, just often.
Two things happened then. The WMO marshalled the troops, who seem to have cleaned up their data for international comparisons. Second, the Hg thermometer was widely replaced by thermistors etc and (probably) new ways to determine average temperatures.
Then, after about 1995, the adjusters thought it was time to start working their particular brands of magic again.
What a mess. How many proxy papers should be written again because they were calibrated against a faulty temperature series?
“… cold water does rise up from the depths in certain wind conditions, which push aside and cool warmer water on the surface. […] But, for obvious reasons, the reverse does not apply.”
Johanna, maybe I misunderstand you, but I am a bit mystified by your last sentence. What what are those obvious reasons? And if cold water is added to the surface, other (probably warmer) water must disappear to the deep. That, or the total ocean surface expands?
John F. Hultquist says:
Go here and read what Dr. Roy S. has to say:
http://www.drroyspencer.com/latest-global-temperatures/
Thanks John, I had not seen that page before…
Pertinent text…
Contrary to some reports, the satellite measurements are not calibrated in any way with the global surface-based thermometer record
I guess the reports I read were in error… I hate it when bad data gets stuck in my brain. 🙂
Sense Seeker says:
December 16, 2010 at 9:29 pm
Well yes, currents do allow cool waters to rise to the surface (see for example upwelling zones) but this doesn’t explain how warm water could possibly sink.
Deep ocean water is remarkably uniformly cool, be it at the tropics or higher latitudes.
If warm water could sink, deep water would be much warmer by now especially since it’s been 11,000yrs since the last ice age.
There is a natural thermal decoupling between warm surface water and cool deep water, the warmer the surface water, the more it will resist mixing with deep water.
On a related issue, the above is opposite to how the atmosphere behaves. The atmosphere warms from the bottom up creating thermals etc and rapid mixing. Oceans warm from the top, thermal decoupling prevents the ocean from behaving like the atmosphere.
That’s my humble opinion and am open to changing my mind if shown to be wrong.
Dr. Phil says:
December 16, 2010 at 8:18 pm
“Great article, but really I don’t understand the basic premise behind correcting for UHI affects. Aren’t the urban temperature measurements real measurements? Urban areas are warmer than non-urban, so what?”
Hi Dr. Phil!
basically all cities in the world have grown massively from their 1900 size to their 2010 size. Therefore, all temperature stations in or around these urban areas does not just have a warm urban temperature, no theyve gotten a lot warmer during 1900-2010.
This we can measure by simply comparing the temperature trends of true rural areas with urban areas.
read: http://hidethedecline.eu/pages/posts/urban-heat-island-uhi-city-heat-in-global-temperatures-85.php
and exaples of UHI from all over the world:
http://hidethedecline.eu/pages/posts/urban-heat-island—world-tour-155.php
K.R. Frank
So the problem here is really the extrapolation of measurements taken from warmer urban heat islands to non urban (and cooler) areas and also to sea areas. Proabably due to the paucity of actual temperature data from enough non UHI areas? But with satellite data, that shouldn’t be the case, should it? Notwithstanding the limitations of satellite based methods of inferring ground and air temperatures.
Cities are a part of the world. So if a component of (or all of) “global warming” is the UHI effect, it does not mean that it is not real. It only means that it is caused by urbanisation, not atmospheric CO2.
This is about the best approach I have seen to estimate the effect of UHI and the local effect of land use change on global temperature.
(I added land use change, because it has a local effect on ground based temperature leading to a warming bias, in addition to its global effect).
Frank showed that ground based and satellite based temperatures over sea are very similar, while ground based measurements have a significantly higher trend over land. It is hard to explain this discrepancy by anything else but UHI / land use change contaminated data and perhaps flaws in data processing.
He also demonstrated, that satellite measured trends over sea and land tend to converge on longer timescales, while they do not converge for ground measurements. Pretty hard to explain the latter as well with anything else but UHI / land use change contaminated data, especially during multi year periods of temperature decrease.
And finally, he makes estimates of the overstatement of ground based global temperature measurements.
These are extraordinary results. I would really like to hear, if Bob Tisdale has any objections against the data used, and I would really like to see a statistician like McKitrick weigh in and transport this approach and these results into a statistical framework.
Thanks manfred, and yes, from hereof the heavy artillery are welcome to investigate 🙂
I will between Christmas and new year make a “global-edition” though since this has been asked for. However, fig 6 is truly global and tells it all (!)
phlogiston says:
December 17, 2010 at 12:45 am
“Cities are a part of the world. So if a component of (or all of) “global warming” is the UHI effect, it does not mean that it is not real. It only means that it is caused by urbanisation, not atmospheric CO2.”
Dear Phlogiston, the city area is just a tiny fraction of the Earths surface and should only count in the global temperatures as a tiny fraction. The problem is, that in the old days, temperature station where ment to tell peoble temperatures where they lived. Temperature stations rarely had a climate science purpose. Therefore when we just use an average of all these urben and near urban temperature stations we make the grave error that we treat the tiny urban area as if it covered a lot of the Earth. If 50% of temperature stations has urban or near urban sitings, we get urban data for half the land area and not just the tiny fraction we should.
K.R. Frank
Well, your graph plotting “with UHI” and ‘excluding UHI’ is absolute nonsense!
The trajectories diverge only because you somehow decided arbitrarily that the temperature sets coincided in 1981. Why would they be similar that year? If one had decided to do so in 1992 for example, we would be at the same temperature rightnow. This is more or less what happens when one simply CORRECTLY shifts the curves wrt to their basis line.
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1900/offset:-0.15/mean:24/plot/gistemp/from:1900/offset:-0.24/mean:24/plot/uah/from:1900/mean:24/plot/rss/from:1900/mean:24
Er, it really would be a good idea to look at the southern hemisphere data as well, as Steven Mosher suggests, before you all jump to too many conclusions. You can do it if you go to woodfortrees.org, and it will take about 10 minutes with the software there to see that NH and SH do not behave the same way.
Frank, what did NOAA do wrong that they did not find this urban heat effect when comparing good and bad measurement sites in the US, as established by the surfacestations.org project? http://www1.ncdc.noaa.gov/pub/data/ushcn/v2/monthly/menne-etal2010.pdf
Re. phlogiston says:
December 17, 2010 at 12:45 am
“Cities are a part of the world. So if a component of (or all of) “global warming” is the UHI effect, it does not mean that it is not real. It only means that it is caused by urbanisation, not atmospheric CO2.”
It also means you cannot extrapolate it 1200 K, or miles, especially into the oceans. And quite obviously you should not base CO2 CAGW policy on this.
Sense Seeker says: December 16, 2010 at 8:09 pm
“You attribute all that [to] the urban heat effect, but couldn’t it just be that the capacity of the ocean to absorb heat is so much greater than that of land?”
Seems like a reasonable question. Just burnt my feet on the sand before cooling them in the ocean.
Oh, those inconvenient Reasonableness Tests!
My gut reaction to the multipliers applied to human “contributions” to the atmosphere and climate initially was, “That’s just goofy!” But then I always do mental rough order-of-magnitude (or better) guesstimates of anything I’m about to entrust to a calculator or computer. A seriously discrepant result sets off alarm bells.
Apparently Warmists lack this “trick”.
Frank Lansner says: “Bob, the “CSST” is taken as a raw average of these datra illustrated here:
http://hidethedecline.eu/media/PERPLEX/fig25small.jpg”
And you continued, “As you can see, the black CSST is pretty much smack on top of all the CSST I used and I allowed to make this “rough” CSST to work with simply because all the different variations of SST mostly are very similar. Yes, the kaplan ends before the others, and stick out a little but this single outlier in no way makes the CSST move far away from the others as you can see. “
As noted in my earlier comment, Frank, you’ve included datasets in your average that have no reason to be included in an average. And it’s not only the Kaplan data that ends early. The HADISST and HADSST1 data in your graph end in the late 1990s. The MOHSST ends in the early 1990s. Do you think your average would be impacted by the fact that these datasets are incomplete?
You continued, “(there ARE big differences between the various SST trends but this mostly occurs before 1960. Thats why I only use it after 1960. Before 1960 i find the SST trends hopelessly in disagreement).”
I showed you in my earlier graph that there are BIG differences in the trends of UAH Ocean TLT and the HADISST, HADSST2, and ERSST.v3b SST anomalies AFTER 1979. Here it is again:
http://i54.tinypic.com/2edcpix.jpg
You continued, “Bob, except for Kaplan I can use any of the other SST´s in stead of the “CSST” in this article and in wont change the point in the present article. besides, remember i use 5 yr avg.”
A 5-year average does not help smooth out the differences between the SST datasets. There are still significant differences:
http://i53.tinypic.com/o9mmjd.jpg
Also, I’d check the source of your Kaplan SST data. As you can see in the next graph, it does not diverge from the others as your graph portrays:
http://i51.tinypic.com/3090j1i.jpg
I notice you failed to respond to the rest of my comment here:
http://wattsupwiththat.com/2010/12/16/uah-and-uhi/#comment-551893
So let me use another method to show that most of the differences between TLT anomalies and Surface Temperature anomalies are not a result of UHI effect. The following gif animations include two maps. Each represents the temperature anomalies in 2009 compared to a base period of 1979-1980. In effect, they are showing the change from the 1979-1980 average temperature to the 2009 temperature. The first compares UAH TLT anomalies and GISTEMP LOTI. As you can see, there are significant differences between the two datasets in Africa, South America, and in parts of Southern Asia that should not have significant UHI components:
http://i51.tinypic.com/15gcne9.jpg
The same thing holds true if we compare RSS TLT anomalies and NCDC surface temperature anomalies:
http://i56.tinypic.com/oqaybm.jpg
And here’s a comparison of RSS TLT anomalies and HADCRUT surface temperature anomalies. Since the Hadley Centre data is not infilled (actually portrays where readings are taken), it’s tough to determine the differences:
http://i56.tinypic.com/66hfd4.jpg
Returning to the comparison of UAH TLT anomalies and GISTEMP LOTI, I’ve widened the range of the contours to help show the differences at high latitudes in the Northern Hemisphere. As is widely known, the change in the GISTEMP LOTI Arctic data is much higher than the UAH TLT anomaly data for the Arctic:
http://i51.tinypic.com/rif28g.jpg
Again, I will end this comment with the same statement. Basically, any conclusion you’ve reached that UHI is responsible for the difference between TLT and land surface anomalies is based on your assumptions from an incomplete analysis.
@Baa Humbug
“I’m really keen to hear your explanation as to how warmer water (by definition less dense) disappears to the depth.”
You mean that cold water, being slightly denser, must always sink to the bottom?
Totally correct, old chap. This also explains why CO2, being 50% more dense than O and N, always sinks to the lowest levels of the atmosphere and is never found more than a few hundred meters above the ground. Also explains why we are all dead because the CO2 concentration near the ground is almost 100%. Stout fellow, Humbug!
/sarc off
pyromancer76 says: December 16, 2010 at 5:53 pm
Yes. Haha. Was just thinking, we need a paper submitted for peer-review and publication, authors Lansner, Tisdale and McKitrick. Then Manfred (12:48 am) beats me to suggesting it.
Seriously. This looks like being potentially a damn good and important paper. We really need to quantify UHI plus station loss plus siting probs plus sensor biases. And benchmark the crucial input of amateur scientists into regaining integrity – and the potential for cooperation.
One thing I’ve pondered about is why folk talk about anomalies as though there is a standard to be deviated from? Isn’t that the reason we have the AGW farce? If the World’s temperature was zeroed during a cold period of a natural cycle then surely it would appear that over the last thirty years that is has been warming. Likewise before then we had seen science zero the World’s temperature during and warm period and then panicked when it cooled into the 1970s. What is needed are measurements of actual temperatures, not proxies or extrapolations, especially when we are only dealing with a degree here or there. Or do folk really think that there is a standard temperature that the Earth is set at?
Lucy Skywalker says: “Seriously. This looks like being potentially a damn good and important paper.”
Lucy, the post is so error filled it leaks like a collender. I’m considering writing a rebuttal post based on the maps I presented in this comment:
http://wattsupwiththat.com/2010/12/16/uah-and-uhi/#comment-552206
John Day says:
December 17, 2010 at 4:42 am
What are you on about John?
John Day said:
You mean that cold water, being slightly denser, must always sink to the bottom?
Totally correct, old chap. This also explains why CO2, being 50% more dense than O and N, always sinks to the lowest levels of the atmosphere and is never found more than a few hundred meters above the ground. Also explains why we are all dead because the CO2 concentration near the ground is almost 100%. Stout fellow, Humbug!
/sarc off
————————————————————————–
No John, Baa (and I) mean that warm seawater does not sink below colder seawater – other things being equal – just as warm CO2 does not sink below cold CO2.
Try first year high school physics sometime, John. I found it pretty interesting at the time.
Excellent forensic analysis, uncovering the massive error in the GISS data that basically eliminates the claimed global warming.
But I am always struck at the minuscule scale of this feared warming. When I hear alarmist claim nature will collapse if we see a 1° C change over a decade it makes this biology major cringe at the ignorance on display. My local ‘nature’ outside Washington DC experiences annual temperature swings from -9° t0 +39° C, and sometimes even larger swings. Year to year seasonal averages swing by a few degrees all the time. Heck, over the course of a day we see changes of many degrees.
So when I see fractional changes in annual temperature estimates I have to laugh. Few living organisms could even detect such small changes, let alone be concerned with them. If we can handle daily and annual variances an order of magnitude greater than this noise I am confident the end of the world is not upon us.
Maybe instead of a rebuttal we could have some plain science instead.
Just a thought. 🙂
currently at SEATAC 42 F
currently outside the big city 30 F
Looks like UHI is 12 F higher (at least in that area)
So, while UHI data will very depending on local climate being wet, dry, tropical, desert, etc. So why spend the effort to massage and modify UHI to fit some global climate agenda? $$$$$$$$$$$
By basic GHG theory (ignoring feedbacks), the mid-tropospheric satellite trends should be about 1.2 times the surface trend (both positive & negative trends). So, if UAH trends are 1C/century, then surface trends would be .83C/century.
If there are overall negative feedbacks (which empirical data in fact suggests), the surface trends will be less than .83C.
As a starting point, I think sat-temps are high enough in the atmosphere to eliminate or minimalize UHI “contamination”, but IMO it’s not impossible that UHI could produce plumes of localized warm areas above/downwind of large developed regions at sat-temp elevations, but I don’t know for sure. Convective activity over large UHI areas could quickly transport heated UHI air to the 15,000 ft sat-temp altitude (and above). But “developed” areas are actually only a small percentage of total area.
jimmi says:
December 17, 2010 at 2:25 am (Edit)
Er, it really would be a good idea to look at the southern hemisphere data as well, as Steven Mosher suggests, before you all jump to too many conclusions..
#######
here is a hint. Anytime you see anybody ( micheal mann or Frank Lansner) do a chart where they show the NH, and do not discuss the SH, your warning lights should go on. if only to ask a question
Frank Lansner says:
December 16, 2010 at 11:51 pm (Edit)
Dr. Phil says:
December 16, 2010 at 8:18 pm
“Great article, but really I don’t understand the basic premise behind correcting for UHI affects. Aren’t the urban temperature measurements real measurements? Urban areas are warmer than non-urban, so what?”
Hi Dr. Phil!
basically all cities in the world have grown massively from their 1900 size to their 2010 size. Therefore, all temperature stations in or around these urban areas does not just have a warm urban temperature, no theyve gotten a lot warmer during 1900-2010.
##################
Actually not.
Yes Virginia there is an explanation that hot ocean water rises and it’s not a ‘travesty.’ Really. Actually, Unbelievable.
We now have two converging explanations that may better help us understand natural phenomena comprising global warming. AND COOLING. The key to this understanding are the concepts of a `torque’ and the of natural power of `swirling vortices’ as these phenomena that relate to the role of the atmosphere, the oceans, the Earth’s `molten outer core,’ and formation of Earth’s magnetic field on climate change.
Adriano Mazzarella (2008) for one criticized the GCM modelers reductionist approach. He realized that the reductionist approach fails to account for many of the factors comprise a more robust holistic approach to global warming AND COOLING.
One of these factors is itself just a part but an important part of a larger process that might be described as a single unit comprised of the `Earth’s rotation/sea temperature.’ Holistically, however, we see that included in this single unit are changes in `atmospheric circulation which, like a torque,’ that themselves can, for example, can cause `the Earth’s rotation to decelerate which, in turn, causes a decrease in sea temperature.’
Similarly, UCSB researchers (results to be published in the journal Physical Review Letters) `filled the laboratory cylinders with water, and heated the water from below and cooled it from above,’ to better understand the dynamics of atmospheric circulation and `swirling natural phenomena’ observed in nature.
As applied to Earth science, it won’t be long before it can be conclusively shown that Trenberth is never going to find the global warming that he is looking for in the deep recesses of the ocean. The reason is simple: it’s not there. No matter how much AGW True Believers may wish otherwise, global cooling is not proof of global warming.
Soon, the mathematics of the UCSB researchers will help reveal that given differences in ocean temperature, for example, in an especially a real world example of the Earth rotating on its axis with warm water at the bottom of an ocean of colder water on the top, that the cold water will sink. The difference in the temperature from top to bottom is itself a `causal factor’ that drives the flow downward.
I think we all knew this already as a simple process of convection. But, let’s hope that a sensible mathematical representation will make the process more accessible and hopefully will also make the government science authoritarians stop acting like persecutors of Galileo.
Frank Lasner: You are not showing the UAH/RSS data correctly the way it should be shown: with full resolution and color overlay. Your averaging destroys data so that you don’t understand what is going on. To fully understand what I am saying look at Figure 7 in my book. The super El Nino of 1998 in particular is very important but you can’t even see it in your display. It divides the temperature regime of the last thirty years into two segments which must not be fitted to a single temperature curve. The left half in the eighties and nineties shows ENSO oscillations which in your display simply get lost. The mean temperature of these oscillations is a horizontal, straight line. Which means no warming for the twenty year period involved. In case you have forgotten this is Hansen’s warming about which he said in 1988 that “.. we can ascribe with a high degree of confidence a cause and effect relationship between the greenhouse effect and the observed warming.” The UAH/RSS temperature curve proves it is total bullshit but you simply don’t know how to look at satellite data or how to interpret it. Read my book before you dream up any more dead ends.
I always get a bit wary when I see phrases like
* “they resemble only the SST´s.”
* “seem to yield considerably lower temperature trends …”
* “There is a good resemblance … ”
* “From fig 3 it appears to some degree …”
Could you quantify these relationships? Maybe calculate a correlation coefficient? Maybe do a t-test? People are good at seeing trends — whether or not they truly exist in the data! I for one would like to see a more detailed statistical analysis before accepting the conclusions.
Rob Vermeulen says:
December 17, 2010 at 2:20 am
“The trajectories diverge only because you somehow decided arbitrarily that the temperature sets coincided in 1981.”
No, trends for CRUTEM (land) NH is + 0.108 K/decade compared to UAH land NH.
Globally (some still haven noticed? see fig 6) trend for CRUTEM land is + 0,088 K/decade warmer than UAH land.
Trends are not depening on start year.
K.R. Frank
PS: I can see there is a lot of comments that needs a comment 🙂 I will catch up later in the Danish night. Everythings going Christmas around here 🙂
Bob Tisdale says:
December 17, 2010 at 5:48 am
Lucy Skywalker says: “Seriously. This looks like being potentially a damn good and important paper.”
Lucy, the post is so error filled it leaks like a collender. I’m considering writing a rebuttal post based on the maps I presented in this comment:
http://wattsupwiththat.com/2010/12/16/uah-and-uhi/#comment-552206
Then post your damn rebuttal and save your snark for the Warmist blogs.
And then we drift off into more models, statistical analysis, data handling and before you know it we are talking about obtuse and obscure mathematics not science. But hey, I guess it keeps some folk happy. I have a nasty suspicion it’s a load of BS, but that’s only based on twenty years as an Instrumentation and Control Engineer, before I became an academic. Complex data analysis and the interpretation of instrumentation data are hardly new to me (or the use of it to baffle mere mortals). The high acronym count is always a clue.
The basic limitations of our measurement systems and the lack of long term data that would cover, what would appear to be, long term cycles, really calls into question the ability of anyone, no matter how smart, to determine such small temperature changes over the last thirty years let alone hundreds years.
But then I guess we’ve got to keep those grants coming in and those egos massaged on all sides of the climate debate!
Hi Bob!
As I wrote earlier, i will make some global updates between Christmas and New year.
From your graphs and others i believe global view yields a different result.
K.R. Frank
Bob Tisdale wrote :
“So let me use another method to show that most of the differences between TLT anomalies and Surface Temperature anomalies are not a result of UHI effect. The following gif animations include two maps. Each represents the temperature anomalies in 2009 compared to a base period of 1979-1980. In effect, they are showing the change from the 1979-1980 average temperature to the 2009 temperature. The first compares UAH TLT anomalies and GISTEMP LOTI. As you can see, there are significant differences between the two datasets in Africa, South America, and in parts of Southern Asia that should not have significant UHI components:”
http://i51.tinypic.com/15gcne9.jpg
I found this picture instructive.
First it confirms Frank’s observation, of elevated warming “measured” with GISS over land. Elevated in 2 ways, against warming over sea surface and against UAH satellite data.
Then there is correlation with urbanization, though there are above mentioned areas, where Bob would not expect UHI.
However, South America may be also explained with massive land use changes turning forests into farming areas.
Same for Africa plus African data has long been put into question with the very few stations.
South Asia correlates quite well with UHI and land use change in my view.
I would like to see above graphics extended over a longer time than just 1 year, because we have learned this year (with El Nino) that there are significant multi month lags between ground and satellite data sets.
Colin from Mission B.C. says:
December 17, 2010 at 9:32 am (Edit)
Bob Tisdale says:
December 17, 2010 at 5:48 am
Lucy Skywalker says: “Seriously. This looks like being potentially a damn good and important paper.”
Lucy, the post is so error filled it leaks like a collender. I’m considering writing a rebuttal post based on the maps I presented in this comment:
http://wattsupwiththat.com/2010/12/16/uah-and-uhi/#comment-552206
Then post your damn rebuttal and save your snark for the Warmist blogs.
###############
Colin, I think it’s fair to say that Bob Tisdale and I are on opposite sides of the AGW debate. That said, Bob’s work is always complete and detailed and open. I cannot say the same for Frank’s work. Bob raises a host of valid points which frank will have to address. There are other points as well that need to be adressed ( mistaking ideas about the land records and how to compare them with UAH/RSS data, failure to look at both hemispheres, lack of statistical tests etc )
Still, since I suggested on the other thread that somebody should take a look at UAH and RSS land versus GISS/CRU land, I’ll suggest that Frank start over and keep it simple.
Start with RSS land and CRU Land. The whole globe, and then do three latitude bands. describe the data and the methods completely.
Steven and Bob, at least so far I have not found errors in NH numbers, but the global numbers from my part needs a lot more work, no doubt!!!
When i come foreward with work (now 20 times on watts?) it IS the point that you guys can take a look at it, and im very greatful for this, so thanks to you both.
The “errors” Bob mentioned about the CSST being source of my findings: No, i cant see any difference when changing with the single SST´s. BUT as I said, globally there appears to be a somewhat more complicated picture. If there is a significant difference between SH and NH this needs to be analysed before any conclusions, this is true, Steven and Bob.
BUT 🙂
SH has a LOT LESS LAND with big urbanization! So that the global impact of the “UHI” problems do appear less than NH, and perhaps… this just confirms my findings for NH?
Ok, time will tell 🙂
K.R. Frank
Manfred says:
December 17, 2010 at 10:45 am
Bob Tisdale wrote :
http://i51.tinypic.com/15gcne9.jpg
I would like to see above graphics extended over a longer time than just 1 year, because we have learned this year (with El Nino) that there are significant multi month lags between ground and satellite data sets.
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
and really useful would be a picture with the difference of above pictures, as this is what we are talking about.
Frank, the problem is that folks cant check your work because you need to provide
links to the data and a clear description of methods.
That is why I suggest you start with ONE land surface record and ONE sat record.
When you do that, for example, I could code it up in R for people so they can check for themselves.
kramer says:
December 16, 2010 at 1:09 pm
Anthony, why can’t somebody just calculate the earth’s temperature using data from stations unaffected by UHI? I’d be more trusting of what this data says even if it showed an increase (and I suspect it would).
REPLY: Easier said than done- the problem is that only a handful have been identified in the USA that are free from UHI and siting biases, and we haven’t even begun to look at the entire world. – Anthony
It doesn`t matter, use the best stations you have then compare them with the same number of stations at cities and airports, you are only measuring the microclimate around the stations anyway. This should indicate the temperature trend of those rural micro climates against the urban trend of the micro climates around the cities and airports where the majority of the stations are situated. Steve Mac did this using Petersons data, it showed a 0.7 degree difference and he did not use pristine rural sites.
Steve Mac,
Last week, Peterson sent me a list of the 289 sites used in this study, together with the classification into urban and rural. As I noted previously, there are many puzzles in the allocation of sites to urban and rural with many “urban” sites seemingly being at best very small towns and, in some cases, rural themselves. So, in that sense, it would seem unsurprising if Peterson didn’t observe any difference between the two networks.
Assuming nothing, I downloaded raw daily data for 282 out of 289 sites. (The other 7 sites either had id number discrepancies or were not online at GHCND.) From this, I calculated average monthly TMAX and TMIN temperatures for all the sites and then calculated 1961-1990 anomalies. I then calculated simple averages of the “raw” anomalies for the two networks BEFORE any jiggery-pokery. Even if all the subsequent adjustments are terrific, from a statistical point of view, it’s always a good idea to see what your data looks like at the start. Here is a plot (with a 24 month smooth.)
As you see in the bottom panel, there is an observable trend in the difference between Peterson-urban and Peterson-rural sites. The delta over 100 years is just under 0.7 deg C.
http://i446.photobucket.com/albums/qq187/bobclive/peters26.gif
Comparison of Peterson Sites with Major League Sports Franchises to Rural Network
Same thing,
http://i446.photobucket.com/albums/qq187/bobclive/peters27.gif
It does not matter where in the word this is undertaken the results will be the same.
You might need complex maths to get the exact temperature but you don`t them to get the trend.
How many rural sites give a higher trend from 1900 to 1990-5 than urban, 1% 5%.
IN the 1990s, literally hundreds of Australian stations were deleted from the GISS network. Nearly all of these are still operational, including about 44 rural or semi-rural sites that now form part of the Australian Bureau of Meteorology’s “High Quality” network.
You don`t data after 1995.
Steven Mosher says:
December 17, 2010 at 8:30 am
Frank Lansner says:
December 16, 2010 at 11:51 pm (Edit)
Dr. Phil says:
December 16, 2010 at 8:18 pm
“Great article, but really I don’t understand the basic premise behind correcting for UHI affects. Aren’t the urban temperature measurements real measurements? Urban areas are warmer than non-urban, so what?”
Hi Dr. Phil!
basically all cities in the world have grown massively from their 1900 size to their 2010 size. Therefore, all temperature stations in or around these urban areas does not just have a warm urban temperature, no theyve gotten a lot warmer during 1900-2010.
##################
Actually not.
++++++++++++++++++++
Actually YES.
Hong Kong’s Urban Heat Island
Fri, 2010-02-05 09:00 — Mr Tall
The theme of my first Hong Kong climate change article was simple: average yearly temperatures here have been going up more less steadily since the Hong Kong Observatory (HKO) starting keeping track of them, but they have skyrocketed in recent decades. Yet over the past 60 years, essentially all of this warming has occurred at night, i.e. the average nighttime lows are much higher than those in the past, while daytime highs are just the same.
This pattern is in fact the signature effect of a phenomenon that has been termed the ‘urban heat island’, or UHI.
http://www.batgung.com/climate-change-urban-heat-island-hong-kong
That the urban area has been warming up much more rapidly than the “countryside” is thus evident’.
Bob Tisdale wrote :
“So let me use another method to show that most of the differences between TLT anomalies and Surface Temperature anomalies are not a result of UHI effect. The following gif animations include two maps. Each represents the temperature anomalies in 2009 compared to a base period of 1979-1980. In effect, they are showing the change from the 1979-1980 average temperature to the 2009 temperature. The first compares UAH TLT anomalies and GISTEMP LOTI. As you can see, there are significant differences between the two datasets in Africa, South America, and in parts of Southern Asia that should not have significant UHI components:”
http://i51.tinypic.com/15gcne9.jpg
ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
Actually this issue has already been solved with sound mathematics by McKitrick and supportive of Frank’s results. McKitrick correlated land temperature trends with economic development / land use change etc. (over longer time scales than 1 year). the result was that at least 50% of warming was due to non GHG causes.
It is also interesting to note that this blog discussion lead into this direction.
The other innovative perspective of the same question was Frank’s postulation of long term equilibrium between sea surface and land based anomalies, not visible in ground based measurements.
Only if we assume a quicker response of land temperatures AND a trend increase over time, a steeper trend on land may be sustained long term.
However, in periods of declining temperatures (or even not increasing trends), this difference should collapse. The steeper land temperature increase would then only be a short term property but not long term.
Manfred says: “I would like to see above graphics extended over a longer time than just 1 year, because we have learned this year (with El Nino) that there are significant multi month lags between ground and satellite data sets.”
The available time periods from the KNMI Climate Explorer for that type of map are one to twelve months. The TLT data of course could be lagged a few months, but it doesn’t make any “heat islands” show up over land. Here it iis with a 3-month lag:
http://i54.tinypic.com/11790e0.jpg
You continued, “and really useful would be a picture with the difference of above pictures, as this is what we are talking about.”
There is an option to create maps of the differences between two datasets using the KNMI Climate Explorer, but, first, there isn’t an option for selecting the base years as I had for these maps, and, second, I haven’t been able to make the option work comparing surface temp (GISTEMP or NCDC) and UAH TLT. The “blink comparator” method will have to suffice for now.
Manfred says: “Actually this issue has already been solved with sound mathematics by McKitrick and supportive of Frank’s results. McKitrick correlated land temperature trends with economic development / land use change etc. (over longer time scales than 1 year). the result was that at least 50% of warming was due to non GHG causes.”
I’m not questioning the the existance of UHI. I’m pointing out that time-series graphs of TLT anomalies and SST anomalies and land surface temperature anomalies cannot be used to conclude that the reason for the differences is solely UHI, and that’s what’s been done in this post. Adding the “Incl. UHI” and “Excl. UHI” to Figure 2 is nonsense. UHI is not the sole reason for the differences.
Frank Lansner says: “Steven and Bob, at least so far I have not found errors in NH numbers…”
Here’s the comparison of Northern Hemisphere UAH Ocean TLT anomalies to Northern Hemisphere SST anomalies for the HADISST, HADSST2, and ERSST.v3b datasets. I’ve used the 5-year smoothing you’ve used in this post. Again, there are significant differences between the TLT data and the HADISST and ERSST.v3b data. Keep in mind the HADSST2 data has the bias from splicing the two source datasets.
http://i53.tinypic.com/2e3oarq.jpg
You wrote, “The “errors” Bob mentioned about the CSST being source of my findings.”
That’s not the only part of the errors in your post that I’ve illustrated for you. You keep overlooking the fact that there are areas around globe where UHI cannot explain the differences between TLT and surface temperatures. In other words, your Figure 2 is implying something that is not supported by the data. You cannot present a graph of TLT, land surface temperature and SST anomalies then assume and imply the differences are caused by UHI.
Bob, its midnight in Denmark and i have a little time to look at your many links etc.
But Bob, is it not a reasonable thing to compare NON-UHI including data from land data with possible UHI including data from ground/cities/airports to evaluate UHI etc?
Please answer this.
The result: If you claim my results are all wrong, I cant see how that should change the general approach I describe. And as a true skeptic, the result is not important, what is important is that we learn the truth about UHI what ever it is, and I think the approach of comparing satellite data with ground data for land can only make us learn more about UHI and other measuring problems. So you and Steven should lighten up, and investigate with curiosity as a driver.
But I will have a look at your links. If your results are true and they shows for example much less UHI than I calculated, then I have learned something about UHI i did not expect.
K.R. Frank
Rephrase:
Bob, is it not a reasonable thing to compare NON-UHI including UAH data over land data with possible UHI including data from ground/cities/airports to evaluate UHI etc?
What ever comes out of this, must be a learning point?
K.R. Frank
Bob… you write to Manfred:
“Adding the “Incl. UHI” and “Excl. UHI” to Figure 2 is nonsense. UHI is not the sole reason for the differences.”
ok, thats a little disappointing Bob. It says more times in the text of the article that the extra heat from ground can be UHI, adjustments and siting problems!!!
Come on! Did you expect me to write all that in the graphic?? I hope the other “errors” are more relevant.
K.R. Frank
Bob this is a nice graph you made thankyou:
http://i53.tinypic.com/2e3oarq.jpg
You compare UAH TLT with some SST´s: Honestly, mostly you confirm that match I would say? that there is a rather good agreement between UAH and SST´s when it comes to the oceans? i can see there is some difference, but certainly not anything that makes my approach irrelevant. I took an averagem the “CSST” to avoid discussing which SST to choose. Is that so awfull?
K.R. Frank
Steve Mosher, you write:
“I’ll suggest that Frank start over and keep it simple.
Start with RSS land and CRU Land. The whole globe, and then do three latitude bands. describe the data and the methods completely.”
Well, theres only ONE reason that you suggest this, and this is because you can D… well see the relevanse in doing UAH – ground based compares 😉 So like it or not, but you reveal that what I did was not that irellevant.
Yours and many other possible ways of attacking this can very well be a good idea. i just presented the main thought.
K.R. Frank
Steve mosher, you write the avreaged CSST graph i used:
“Do you think your average would be impacted by the fact that these datasets are incomplete? ”
Steve I dont have to “think” heres the compare of the CSST with some relevant SST curves:
http://hidethedecline.eu/media/PERPLEX/fig81.jpg
I stated CLEARLY in the article, that my results for now are “obviously qulitative”.
I also have explained Bob in comments, that these graphics comes from an article where i was investigating primarly data up to around 1985, and therefore this CSST was perfectly relevant there. I have RE-USED graphics because they definetely show my point since the CSST just happens to remsemble later SST´s to perfection as you can see. In a context where i only say: UAH Ocean data matches SST´s well, the deviation from CSST to any of the SST you might chose is totaly neglible for the point and the useulness.
I have in no way called this something for peer review at this stage. This IS a qualitative – but good – picture of the situation, and yes to go further it takes more work. I would be very happy to receive a fund to do this to perfection (!) I would love it, dont misunderstand this.
K.R. Frank
On climate changes brought about by urban living.
In tandem with urbanisation in Hong Kong, urban temperature has risen faster than the countryside.
Every time a study looks at a single city and its rural neighbours you see a similar result as above. This 0.05C is utter rubbish.
http://www.weather.gov.hk/publica/reprint/r700.pdf
Athens,
Even through the COOLING period of the 1970`s Athens showed a warming trend in Tmin with a population increase from 1,430,000 to 3,200,000 from 1951-81.
It got warmer when it got colder.
http://journals.ametsoc.org/doi/pdf/10.1175/1520-0450%281985%29024%3C1296%3AIOTUHI%3E2.0.CO%3B2
Steve Mosher, you write:
“I showed you in my earlier graph that there are BIG differences in the trends of UAH Ocean TLT and the HADISST, HADSST2, and ERSST.v3b SST anomalies AFTER 1979. Here it is again:
http://i54.tinypic.com/2edcpix.jpg”
Steve… you present data NOT in 5 yr average as i did. And then because there are more oscillations in the UAH data (yes!) my approach of comparing TRENDS of UAH with SST etc. should be wrong???
Steve, when TREND of UAH-ocean matches SST well, while TREND of UAH-land is considderably colder than ground based land – you just focus on the fact that UAH temps oscillates on very short term more than sea surface temps?
Well, i dont agree. Even though that the type of data on short term has different nature, the TREND is certainly 100% relevant.
This even gets funny: The UAH trend is near the average of the SST´s you have shown.
http://i54.tinypic.com/2edcpix.jpg”
!!
Of course data types are different, but you simply cannot imagine a better match – You should be thrilled by your graph 🙂
K.R. Frank
PS: Steve and Bob: Im not aware of more “errors” from you guys if i have missed something please tell. Ii obviously am fully aware as i said in the article: What i showed so far is “qualitative”. There is room for perfection – especially if the concept is generaly “approved” it would mae sence to go further.
K.R. Frank
Frank Lansner says: “Steve… you present data NOT in 5 yr average as i did. And then because there are more oscillations in the UAH data (yes!) my approach of comparing TRENDS of UAH with SST etc. should be wrong???”
I presented the graph, not Steve Mosher, and I also presented the data with your 5-year smoothing. Please read all of my replies from start to finish on this thread.
You continued, “PS: Steve and Bob: Im not aware of more “errors” from you guys if i have missed something please tell.”
I’ve shown you repeatedly on this thread that surface temperatures trends are higher than TLT anomaly trends in areas of the globe like the Sahara desert where there are no heat islands. Therefore your post is in error. Again, please read all of my replies to you on this thread. It almost appears as though you are purposely avoiding that part of the discussion.
Frank Lansner says: “Steve mosher, you write the avreaged CSST graph i used:
‘Do you think your average would be impacted by the fact that these datasets are incomplete? ‘”
Again, I wrote that reply to you, not Steve.
You continure, “Steve I dont have to “think” heres the compare of the CSST with some relevant SST curves:
http://hidethedecline.eu/media/PERPLEX/fig81.jpg”
You continued, “I stated CLEARLY in the article, that my results for now are “obviously qulitative”. I also have explained Bob in comments, that these graphics comes from an article where i was investigating primarly data up to around 1985, and therefore this CSST was perfectly relevant there.”
I have later in the comments on this thread confirmed that the differences between Ocean TLT and SST are significant. Once again, please read all of my comments to you on this thread.
Frank Lansner replied, “Bob this is a nice graph you made thankyou:
http://i53.tinypic.com/2e3oarq.jpg”
And you continued, “You compare UAH TLT with some SST´s: Honestly, mostly you confirm that match I would say? that there is a rather good agreement between UAH and SST´s when it comes to the oceans? i can see there is some difference, but certainly not anything that makes my approach irrelevant. I took an averagem the “CSST” to avoid discussing which SST to choose. Is that so awfull?”
You miss the point of the graph. The differences are not insignificant.
I’ve had it. That’s it. I’m done playing your games.
Regards.
Manfred: Sorry. Something else occurred to me after I replied to your earlier comment about time lags. This reply:
http://wattsupwiththat.com/2010/12/16/uah-and-uhi/#comment-552615
When we think of time lags in response to an ENSO event, there are different lags for TLT and surface temperature anomalies depending on the part of the globe being examined. Most of the lag between surface temperatures and TLT anomalies occurs in the eastern tropical Pacific (24S-24N, 180-80W). The Surface Temperature anomalies (primarily SST) for this part of the globe lead the TLT anomalies by 2 to 4 months.
http://i55.tinypic.com/2eevry9.jpg
The eastern tropical Pacific represents about 12% of the surface area of the globe that’s presented by RSS for their TLT anomalies (70S-82N). In the next graph, I removed the eastern tropical Pacific data (24S-24N, 180-80W) from the “global” data (70S-82N) by scaling the eastern tropical Pacific data by a factor of 0.12 and then subtracting it from the global data. As illustrated, outside of the eastern tropical Pacific, the TLT anomalies can lead the surface temperature anomalies by about a month.
http://i56.tinypic.com/33u6e80.jpg
The TLT and surface temperature anomalies outside of the eastern tropical Pacific both lag the eastern tropical Pacific, but the two datasets are more in line with one another once the eastern tropical Pacific data has been removed. So I should not have presented the comparison with the TLT anomalies lagged 3 months, unless we were interested in the differences in the eastern tropical Pacific.
Bob, this is your graphic done transparant and laid over mine from the article:
http://hidethedecline.eu/media/UAHUHI/Bobsoverlay.jpg
The black arrow points the the blus SST-average graph i used to show my point.
From this picture it is clear that my blue average FARILY represents the SST.
My approach is to compare land-ground with land UAH, and then ocean-ground with ocean-UAH.
And im sorry, but your graph does not convince me that there is anything wrong with my approach when trying qualitatively to show my point. How can my average blue SST right in the middle of the SST´s you show not qualitatively represent SST ? ? ?
Bob, I have to go through and understand a storm of “errors” from your part before sometimes reaching a real error. Therefore I would appreciate if you where a little patient.
Then it seems that in all these comments i have missed one of your objections against my writing – not intended, you write: “You keep overlooking the fact that there are areas around globe where UHI cannot explain the differences between TLT and surface temperatures”
And I think I found the graph you think of:
http://i43.tinypic.com/if1oh5.png
So here we have a GISS 1200 smoothed temperature area in Sahara where GISS comes up wit more heat that UAH can support and confirm.
I will repeat again-again what I wrote to begin with in the article:
“This “extra heat trend” seen in the ground based land temperature data may be explained by UHI + possibly faulty adjustments of data and siting problems.”
So I am clearly for all readers 100% aware that the warmer ground based temperatures can be much more than UHI.
The most important point of the article is, that there is “extra-heat” in the ground based temperatures which can be revealed by UAH data. In many cases this would be UHI, but i am clearlyaware that more factors plays a role.
K.R. Frank
Frank.
Just for starters you cannot compare the curves by “pinning” 1981 to zero.
Well you can “pin” them but it gives a misleading presentation.
Frank Lansner says:
December 17, 2010 at 3:56 pm (Edit)
Steve Mosher, you write:
“I’ll suggest that Frank start over and keep it simple.
Start with RSS land and CRU Land. The whole globe, and then do three latitude bands. describe the data and the methods completely.”
Well, theres only ONE reason that you suggest this, and this is because you can D… well see the relevanse in doing UAH – ground based compares 😉 So like it or not, but you reveal that what I did was not that irellevant.
########
actually Frank I trying to understand what you think you did.
1. Which UAH Land did you use. Then find out what area of kand that covers.
2. which version of CRU did you use, which area of land does that cover.
3. Do UAH and CRU use the same land mask ( answer no)
4. How did you pick 1981 as the “pinning point”
5. How does one actually “pin” two different series with different error bars
together.
Basically before you toss 5 different series at a methodology it is good to clearly lay the method out with explicit references to the data and good descriptions of the methods. So when Bob Tisdale does something I can always reconstruct what he does.
That allows me to check his work and ask him intelligent questions and he and I can reason together. I think there is maybe one case where I didnt understand what Bob was doing and he quickly corrected my misunderstanding. ( on GISS delting SSTs) That is why Bob and I can talk to each other without acrimony despite our differing views on AGW. I see that he is diligent and careful and clear and discussions are always about the numbers. So, I’m offering you some advice to help you clarify what you did. That’s it.
Ok ,
Frank, to check your work I did the following
Step 1.
First I downloaded the UAH monthly data.
Then I downloaded the monthly crutem. Variance adjusted data.
Step 2. rebaseline the CRU data. Cru measures are on a 1961-1990 basis.
UAH is a 1979-1998 basis. This means that you have to calculate the
jan,feb march etc averages for CRU 1979-1998. These figures are then
subtracted from the CRU figures. Thus, cru and and uah are now comparable
Step 3. Plot them. for the complete record. 1978 dec to oct 2010.
Step 4. Difference them and plot, you get a result with no trend. This means the Land trend for both is roughly equal.
Step 5. take the mean of the difference. its zero.
Basically, I’m pretty sure your nistake stems from a couple of issues.
1. you dont appear to be rebaselining, instead you describe setting all the values to zero in 1981. your proceedure ( both picking that year and the setting to zero) is
odd. You want the baselines to be normalized. And since using all the data is generally advised ( otherwise u might have cherry picking issues) You should use all the data.
Anyway, I’m showing completely different results than you get
Hi Steven!
Please disregard global because as I wrote these data certainly needs more work from my part.
NH:
Heres Bobs data including the UAH ocean and some SST´s they seem to match mine.
http://hidethedecline.eu/media/UAHUHI/Bobsoverlay.jpg
F.R. Frank
Havt to go to dinner + +
I forgot
http://hidethedecline.eu/media/UAHUHI/Bobsoverlay.jpg
Frank Lansner wrote, “The most important point of the article is, that there is “extra-heat” in the ground based temperatures which can be revealed by UAH data. In many cases this would be UHI, but i am clearlyaware that more factors plays a role.”
Wrong.
Frank, your post is titled “UAH reveals Urban Heat”, but your post does not show urban heat island effect. It only shows that there are differences between land surface and sea surface and TLT anomalies. It shows nothing more. The rest of what you wrote is based on your assumptions. You provide no comparisons of urban temperatures to surrounding suburban temperatures, and that is something one would expect from a post that proved the existence of UHI.
You are now saying that all of the “extra-heat” in land surface temperatures could result from “UHI + possibly faulty adjustments of data and siting problems” as you wrote in the post,
-PLUS-
the methods used to infill missing data,
-PLUS-
the deletion of SST data in the Arctic and Southern Oceans, etc.
In other words, in addition to UHI, there are many more things responsible for the differences between TLT and surface temperatures anomalies. But your post starts with “How UAH (University of Alabama, Huntsville) satellite temperature data supports Urban Heat (UHI) as a real and significant factor when estimating global temperatures.” Again, your post does not support that.
Are you aware that the annual variations in monthly land surface data are at least 4 times greater than the TLT data and about 35 times greater than the annual variations in monthly SST data?
http://i51.tinypic.com/34dr6de.jpg
With differences that large, one might expect the trend of the land surface temperature to be higher than the trends of the other datasets.
One last thing, about six months ago, we discussed that GISS no longer uses the dataset you presented in Figure 7. I thought you had finally agreed to that. But you wrote in this post about Figure 7, “The problem of “extra heat” in land temperatures (likely to be UHI and more) is escalated by GISS because they extrapolate the ground based land temperature measurements over the oceans in stead of using real ocean data.” In their LOTI product, GISS does use “real ocean data” for the global oceans where there is no seasonal sea ice. Yet for some reason, you insist on misrepresenting how GISS handles sea surface temperatures.
REPLY: thanks Bob, – Anthony
Steven here’s my email: fel-at-novonordisk.com if you like we can exchange some info.
One thing though, you write: “you don’t appear to be rebaselining, instead you describe setting all the values to zero in 1981. ”
This is not a potential problem because it’s the trends we are comparing. The trends do not change no matter what value you use as start temperature for the respective graphs (as long as you start all at same time of course).
K.R. Frank
How UAH (University of Alabama, Huntsville) satellite temperature data supports Urban Heat (UHI) as a real and significant factor when estimating global temperatures.
Don`t you trust the real data, if these three and the rest of the worlds large urban areas are included in the global mean no wonder it is increasing. urban bias of 0.05C per century utter rubbish.
http://i446.photobucket.com/albums/qq187/bobclive/UHICities.jpg
http://www.lavoisier.com.au/articles/greenhouse-science/climate-change/vincentgray-scam-2008.pdf
http://climateaudit.org/2007/08/17/brazil/
comment, vincent Guerrini
Posted Aug 17, 2007 at 8:56 PM | Permalink | Reply
This should be the beginning of a worlwide/continent by continent analysis of rural v urban sites (unless this has been done). Answer QUIXERAMOBIM. Have a look at Puerto Varas or Punta Arenas, Chile. You’d think that by now ONLY rural data should be used for world surface data analysis. BTW does anybody know why UH satellite data for July 2007 not posted yet? (CRU3 etc has)
good work keep it up.
One thing though, you write: “you don’t appear to be rebaselining, instead you describe setting all the values to zero in 1981. ”
This is not a potential problem because it’s the trends we are comparing. The trends do not change no matter what value you use as start temperature for the respective graphs (as long as you start all at same time of course).
###
I’ll suggest that you start by using monthly data. Its weird that you pick 1981, so just start at the beginning of UAH. Make sure you use CRUTEM variance adjusted
Hi Steven, you Write: “I’ll suggest that you start by using monthly data. Its weird that you pick 1981, so just start at the beginning of UAH. Make sure you use CRUTEM variance adjusted”
Actually i dont start in 1981 🙂
I start with te very first month available from UAH: 1978, dec.
Starting from this month I take data from 60 months foreward (5 years) , take the average and not this averege with centre after 30 months, june 1981. July 1981 is then jan 1979 and 60 months foreward and so on. Its a running 5 year mean, and most important: All data series has been treated in the exact same manner.
So I simply start out using first available UAH data.
K.R. Frank
Bob, you write:
“Frank, your post is titled “UAH reveals Urban Heat”, but your post does not show urban heat island effect. ”
THIS is true, Bob 🙂 I show extra heat as described and in the text where besides UHI we have also adjustments and siting issues.
So, yes, the headline I made is inaccurate.
Then you write, Bob:
”
about six months ago, we discussed that GISS no longer uses the dataset you presented in Figure 7. I thought you had finally agreed to that. ”
Bob, NASA/GISS still presents the land-projected-over-sea-product map on their official site.
What am I then to think?
(Besides, for both the Arctic and the Antarctic they still use the land-projection method even though you choose Hadcruts ocean data (because they dont cover the Arctic, Antartic) so the land projection method appears alive and well, sadly:
http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2010&month_last=11&sat=4&sst=1&type=anoms&mean_gen=11&year1=2010&year2=2010&base1=1951&base2=1980&radius=1200&pol=reg)
K.R. Frank
And further: For example in the Arctic, do not GISS use land-projected data over see
Bob, i just re-checked the NASA/GISS temperature FRONTPAGE:
http://data.giss.nasa.gov/gistemp/
Yes, look in te right side, there is presented NOT the LOTI you mention but the Tsurf (where GISS project land data over the oceans over the whole world). If you say that in some contexts, this land-temperature projection map is no longer used, I believe you, but i certainly still exists on first class.
Therefore it is obviously also 100,00 % relevant that I show the fig 7 with GISS Tsurf as i do in my article.
K.R. Frank
Frank Lansner says: “Bob, NASA/GISS still presents the land-projected-over-sea-product map on their official site. What am I then to think?” And you wrote, “Therefore it is obviously also 100,00 % relevant that I show the fig 7 with GISS Tsurf as i do in my article.”
Refer to the comment by Zeke Hausfather on your July 27 post here at WUWT:
http://wattsupwiththat.com/2010/07/17/tipping-point-at-giss-land-and-sea-out-of-balance/#comment-434647
Refer also to my rebuttal post to your July 27 post:
http://bobtisdale.blogspot.com/2010/07/land-surface-temperature-contribution.html
It also ran here at WUWT:
http://wattsupwiththat.com/2010/07/23/bob-tisdale-on-giss-landsea-ratios/
Do you recall these discussions? You commented on the WUWT rebuttal to your earlier post.
You’ve been made aware that the dataset you’ve presented in this post is not GISS’s official dataset, yet you continue to treat it as if it is. Not only are the title and introduction of your post misleading, but you intentionally mislead readers here who aren’t aware (as you are) that what you’ve presented is not the GISS official dataset.
You continued, “Besides, for both the Arctic and the Antarctic they still use the land-projection method even though you choose Hadcruts ocean data.”
GISS uses two SST datasets in their LOTI product, Frank. They start with HADISST, and in December 1981 they switch to Reynolds OI.v2 SST data. The minimal differences between the two datasets do not warrant the effort needed for me to splice two datasets together to reply to your post, Frank. And I don’t need to be lectured on how GISS treats the Arctic and Southern Ocean data. I mentioned it in one of my comments above, and as you may recall I wrote a post about it:
http://bobtisdale.blogspot.com/2010/05/giss-deletes-arctic-and-southern-ocean.html
I am not sure why you continue to argue and provide questionable explanations.
Frank It’s not advisable to smooth the data and subtract. Try doing as I suggested,
subtract and fit a line. and make sure you use the variance adjusted data. after you are done you can smooth for presentation only.
Bob, you write:
”
You’ve been made aware that the dataset you’ve presented in this post is not GISS’s official dataset, yet you continue to treat it as if it is. Not only are the title and introduction of your post misleading, but you intentionally mislead readers here who aren’t aware (as you are) that what you’ve presented is not the GISS official dataset.
”
Bob, you think that Nasa can present the Tsurf product on their front page AND in their product catalogue and still, I cant show it on my fig 7. in a blog?
Besides i still see many references to the Tsurf i show in fig 7. this very day. Nasa Still updates the numbers just like allways on tsurf. For example in the Danish debate, the TSurf value november 2010 of +0,95 plays a domintaing role(!!!!)
Bob, many many many times i have used time to investigate all your links etc. to figure out why you claim “error error” everyhere. But often I just dont find significant support for your claims.
Discussions are “irritating” especially when yo dont agree 🙂
K.R. Frank
Steven Mosher says:
December 18, 2010 at 11:17 pm
“Frank It’s not advisable to smooth the data and subtract. Try doing as I suggested,
subtract and fit a line.”
Steven, since you want me to do this i will and I can mail you the result between Christmas and New Year.
But-but-but Steven, statistically the odds that this will change the big trend difference between landbased lanf temp and UAH-based land temp is 0,00%. Therefore this is somthing I do exclusively only for you 🙂
K.R. Frank
Frank Lansner: You can use whatever dataset you wish. But when you write in a post here at WUWT, “The problem of “extra heat” in land temperatures (likely to be UHI and more) is escalated by GISS because they extrapolate the ground based land temperature measurements over the oceans in stead of using real ocean data,” I will remind you that GISS notes the errors in the dTs data on their webpage:
“LOTI provides a more realistic representation of the global mean trends than dTs below; it slightly underestimates warming or cooling trends, since the much larger heat capacity of water compared to air causes a slower and diminished reaction to changes; dTs on the other hand overestimates trends, since it disregards most of the dampening effects of the oceans that cover about two thirds of the earth’s surface.”
So the next time someone on a Danish blog uses the dTs dataset in a post, refer them to that quote.
Bob, thanks for the last answer.
In the climate debate I have often seen ONE thing presented to the audience with a rather alarmistic message and then you have to read some deeper notes to get the full picture. This is smart propaganda because most peoble get the fast message and never ever reads the “notes”.
So when NASA presents the Tsurf on their front page (and NOT LOTI) and then have a note as you show, then they can send the Tsurf warm – message, and we are not allowed to critisize because they have a note. How convenient.
I think that as long as NASA promotes the Tsurf as they do, it is important that we critisize it. But! The fig 7. would stand stronger noting that NASA has this note.
And Bob, dont forget that even the LOTI uses the GISS-land-over-ocean projections over the Arctic and Antarctic, so the procedure I question is still alive and well even in their LOTI product.
Ok, The overall total Critic that I have seen you able to defend:
1) The header only mentions the UHI while in the article it appears that the “extra heat” besides UHI is likely to contain adjusting problems and siting problems.
2) fig 7. – The Tsurf NASA product used on NASA´s GISS-temperature front page is shown, allthough NASA has a note that they considder the LOTI product more precise. Yet its not the LOTI product you see on their front page, and for some reason they keep updating their Tsurf product. The article would have been stronger if I had used the GISS LOTI product that ALSO use the problematic land-projections over sea around the Arctic and Antarctic.
And?
So, Bob, what do you think of the main contents of the Article????????????????????????
1) What do you think of my new thinking concerning the equilibrium tendency seen inUAH data but not in conventionel data?
2) Dont you find it relevant to examine UAH land vs ground based land data to explore the extra heat from land stations??
My article is in fact not only useful for skeptics… it also indicates an upper limit of problems with land stations: If UAH is correct, problems from UHI (and edjustments etc.) should not be bigger that the difference between UAH-land and the land based stations.
I think there is SO much exciting to discuss here and it would be nice with some reflections of this kind too.
K.R. Frank
Frank Lansner says: “And Bob, dont forget that even the LOTI uses the GISS-land-over-ocean projections over the Arctic and Antarctic, so the procedure I question is still alive and well even in their LOTI product.”
If you use the LOTI dataset, then you can discuss the “land over ocean” problem in the Arctic and Southern Oceans. Using the dTs dataset does not allow you to do so because they extend the land surface data out over the oceans everywhere.
You asked, “What do you think of my new thinking concerning the equilibrium tendency seen inUAH data but not in conventionel data?”
SST and land surface temperature data are different variables. The TLT ocean and TLT land are the same variable and they are not isolated from one another.
You asked, “2) Dont you find it relevant to examine UAH land vs ground based land data to explore the extra heat from land stations??”
Your 5-year smoothing hides the facts that the divergences are caused by the different responses to ENSO, volcanic eruptions, and the KOE.
You wrote, “If UAH is correct, problems from UHI (and edjustments etc.) should not be bigger that the difference between UAH-land and the land based stations.”
That’s an assumption on your part. As noted in my earlier reply, the annual variations in monthly global land surface temperatures are 4 times higher than those of TLT.
http://i51.tinypic.com/34dr6de.jpg
With differences that large, one might expect the trend of the land surface temperature to be higher than the trends of the other datasets.
Bob, you write: “Your 5-year smoothing hides the facts that the divergences are caused by the different responses to ENSO, volcanic eruptions, and the KOE.”
Nonsense. 5 year smoothing does not account for 30 year trend difference (!). How can yo even think this for a second is amazing.
you write more: “The TLT ocean and TLT land are the same variable and they are not isolated from one another.”
So where do you think i got the TLT land vs TLT ocean data from?
http://www.atmos.uah.edu/data/msu/t2lt/uahncdc.lt
And then you DEMAND that everyone here at WattsUpWIthThat must not critisize the NASA Tsurf product Even after I have showed you that NASA gisstemp has it on their very front page still. “ohh they have a note, then they can continue showing Tsurf to peoble for ever”.
You and I both now the Tsurf stinks, and you should not help silencing critic of it. The day NASA take Tsurf maps and update data O F F their product catalogue, that day you have a point.
(But im happy that we can agree that the land-over-ocean bizarre method is also used in the LOTI.)
Frank
Frank Lansner: You quoted me, “Bob, you write: ‘Your 5-year smoothing hides the facts that the divergences are caused by the different responses to ENSO, volcanic eruptions, and the KOE.'”
Then you replied, “Nonsense. 5 year smoothing does not account for 30 year trend difference (!). How can yo even think this for a second is amazing.”
You are misunderstanding what I wrote. I was not discussing trends. I was discussing your Figure 3, which does not include trend lines. Your 5-year smoothing in that graph hides the reasons for the “gabs between the UAH land and ocean data.” (That should be “gaps” by the way, not “gabs”. Gab is a verb that means to talk.) If you smooth the data you used in your Figure 3 with a 13-month filter to remove the seasonal noise…
http://i52.tinypic.com/ejx5pt.jpg
…you can see that the land TLT data diverges from the sea TLT data due the volcanoes and ENSO events (which also carry over into the TLT response to the KOE). And since you can’t see that in your Figure 3, I wrote, “Your 5-year smoothing hides the facts that the divergences are caused by the different responses to ENSO, volcanic eruptions, and the KOE.”
Then you quoted me: “The TLT ocean and TLT land are the same variable and they are not isolated from one another.”
And you replied, “So where do you think i got the TLT land vs TLT ocean data from?
http://www.atmos.uah.edu/data/msu/t2lt/uahncdc.lt”
You excluded the first part of my reply. Here it is in full. “SST and land surface temperature data are different variables. The TLT ocean and TLT land are the same variable and they are not isolated from one another.” The point I was trying to make is that there are shorelines that separate the oceans from the land and that SST data and land surface data are measuring two completely different variables. One is land surface temperature and the other is sea surface temperature. But the TLT data over the oceans and over land are not separated by shorelines. UAH isolates them by the coordinates of the data, but in the real world, they are not isolated from one another. Atmospheric circulation is constantly mixing them.
Hi Bob and thanks for answer, honestly I was looking foreward to the latest answer(!!)
The GaPs 🙂 are visible in all graphs for land data, also conventional land data and they are of dimilar magnitude. Or to put it more precisely, all the land-graphs 5 year smoothed shows these shorter term changes.
But its the long trends that does the difference. The long (30 years) trend of conventional ground/city based land data is so warm that the gaps/peaks never reaches back to equilibrium, in fact they go further and further from equilibrium which at some point is difficult to explain thermodynamically. But the long term trend of UAH land data is so close to the UAH ocean data that equilibrium is reached every time tempertures generally pauses from rising.
Therefore Bob, its the long trends that does all the difference, not what ever 5 year averaging i have done to all graphs.
And then, Bob, the different type of data: Its likely that different data type it self can be responsible for different degree of variation etc. but certainly not a long ever ongoing change of trend.
K.R. Frank
And Bob, we should take care not to make the following error:
Its widely accepted that difference between UAH and conventional temperature trends are small and thus, “everythings OK”.
Now when we realise that trend difference specifically for land (NH) is significant, the we should say “its different data types, everythings OK” ?
One of the most central issues in the climate debate is the quality of exactly ground/city based land data. Therefore the clear message that ALSO UAH does not support ground/city based land data is important.
K.R. Frank
Oof. Frank, take some time and check your posts as best you can before sending. When you get excited your English grammar “goes to pot” (deteriorates to the point it becomes very hard to follow).
There is a “weasel word” I like to watch for in official (and other) pronouncements, by the way: “slight” or “slightly”. Sez who? After what fiddles and fudges? Excluding what inconvenient data? Etc.
Frank Lansner says: “But the long term trend of UAH land data is so close to the UAH ocean data that equilibrium is reached every time tempertures generally pauses from rising.”
The green curve in Figure 3 is the difference between the Land and Sea TLT data. It is not detrended data. The actual land and sea TLT may be rising or falling when the green curve is at or near zero. When the green curve is at or near zero it only means that the land and ocean surface temperature anomalies are equal, not that the absolute temperatures are equal. So I do not understand how you can write, “equilibrium is reached every time tempertures generally pauses from rising.”
You wrote, “But its the long trends that does the difference. The long (30 years) trend of conventional ground/city based land data is so warm that the gaps/peaks never reaches back to equilibrium, in fact they go further and further from equilibrium which at some point is difficult to explain thermodynamically.”
I have no idea how you can look at a graph of Northern Hemisphere surface temperature anomaly data and discuss equilibrium and thermodynamics.
Frank Lansner: As you can see by my last comment, I’m not sure what point you are trying to make. Please find other words for equilibrium and thermodynamics to express what you are talking about.
Frank Lansner, regarding your entire December 20, 2010 at 8:24 am comment. I will repeat a comment I have made twice before on this thread.
the annual variations in monthly global land surface temperatures are 4 times higher than those of TLT.
http://i51.tinypic.com/34dr6de.jpg
With differences that large, one might expect the trend of the land surface temperature to be higher than the trends of the other datasets.
Hi Bob!
I think we are the only ones following this debate by now, and for the moderators i´d say: Mail me on fel@nnit.com If you like.
K.R. Frank
Frank Lansner: There’s no need to discuss this outside of this thread (via email).
You are assuming that comparisons of Land TLT and Ocean TLT anomalies somehow indicate that they come into equilibrium for periods. And what I was working towards showing you was that you can’t make those assumptions using anomalies. Here’s a graph of the TLT anomalies for a TLT Ocean dataset in the North Atlantic (15N-25N, 50W-20W), and it’s compared to a TLT anomalies for a TLT Land dataset in North Africa (15N-25N, 10W-20E). They’re the same size in area at the same latitudes, and they are separated by 10deg longitude, which includes the western Africa coastline. I used your 5-year smoothing and have also shown the difference. The graph is similar in format to your Figure 3. And based on how you describe the data in your post, those two datasets are in equilibrium in the 1980s and early 1990s.
http://i54.tinypic.com/fnbr89.jpg
In reality, they are not.
If we look at the TLT data (not anomalies) for those two datasets, either in their monthly form…
http://i51.tinypic.com/vnh55k.jpg
…or in the way you present data, with a 5-year filter, we can see that the ocean and land surface TLT data is not in equilibrium at those times.
http://i53.tinypic.com/25p0hdu.jpg
I could do the same thing for land surface and sea surface to illustrate the same thing. So your post is in error in that description also.
Bob, I think it is unfair that the moderators have to use time on our internal discussion, but since you insist to keep our dialog here, let’s continue until moderators say stop.
You write: “The green curve in Figure 3 is the difference between the Land and Sea TLT data. It is not detrended data. ”
I know what it is Bob (!) and that its not a “real” detrend (!) however trend is of course minimized by just looking at the difference, so there’s not much juice in your comment, I don’t know want you want to prove. Please stick to few essential things so we can end this.
You ten write: “The actual land and sea TLT may be rising or falling when the green curve is at or near zero. When the green curve is at or near zero it only means that the land and ocean surface temperature anomalies are equal, not that the absolute temperatures are equal.”
Yes, that obvious Bob, the point is that at some temperature levels (probably very different mechanisms around the world) the land vs. ocean surface temperatures acts as an equilibrium, then its not our worry in this context to figure out at what temperatures etc this occurs at. All systems will seek a situation where energy is distributed as evenly as possible. You are correct that this does not necessarily mean that they have exact same temperature, but in this context this exact temperatures are not whats interesting.
No, what IS interesting is that UAH data land vs. ocean again and again reaches the same temperature difference (!!!) This is the thermodynamically logical behaviour. We do not need to now exact temperature etc. as you for some reason talk about. We can see that a specific temperature land vs. temperature ocean is repeatedly returned to. And this appears exactly when global temperatures are taking a pause or a little reverse.
It appears we are near an equilibrium, ho so? Take a look at fig 4. You can see that the sequence and pattern of the big cooling is very similar to the warming – but just opposite direction. So temperatures in both cases react pretty much the same on a change, and this the 2 start situations must have been close to an “equilibrium”.
Of fig 3, i cannot say if my “0” line is the quantitatively perfect estimate of the equilibrium, but that’s not the point. If the “real” equilibrium should have been a little lower on fig 3 it changes nothing, this system acts as if it seeks equilibrium.
Unlike UAH data, conventional data land vs ocean does NOT at all seems to return to a equilibrium state between land and ocean. In stead the land goes higher and higher and higher compared to the ocean temperatures.
Bob, the real discussion here is : Can there be a natural explanation that land temperatures should rise more and more and more compared to ocean surface as city based land temps suggests?? How can this be? What should enable such a growing distance in temperature?
THIS, Bob, is what we are talking about.
You can easily argue, that land changes temperature faster than ocean surface, i showed just that in fig 4. BUT! The problem is, that when temperatures then stop rising, city/land temperatures don’t return to equilibrium with ocean – if we believe land/city temps. UAH land do.
Then Bob, I see you once again tell me that variance in the one set is difference from the other set. I don’t know what to say to you Bob. Variance does not make the overall trends. We are talking about trends. Do land trend loose contact with ocean trends or not. This is not and will never be a variance issue.
Then finally you show a specific limited land area vs a specific limited ocean and show that these areas are not exactly equilibrium with one another. Bob, we are talking about an immensely complex system. I certainly did not respect some ocean square to be in equilibrium with some other square of land. Of course the ocean square you show will interact with all areas all around the square and in fact in turn with the whole globe. So to expect an equilibrium between these to squares as you do is it self a misunderstanding.
By looking at the NH (which is rather slowly interfering with the SH) THEN we have a system where we all together see land totals in equilibrium with ocean totals. Certainly not some random fragment in a complex system.
But again Bob, the real discussion here is : Can there be a natural explanation that land temperatures should rise more and more and more compared to ocean surface as city based land temps suggests?? How can this be? What should enable such a growing distance in temperature?
K.R. Frank
Frank Lansner says: “I know what it is Bob (!) and that its not a “real” detrend (!) however trend is of course minimized by just looking at the difference, so there’s not much juice in your comment, I don’t know want you want to prove. Please stick to few essential things so we can end this.”
It is essential. It was a part of your post and it is wrong. You wrote this in the post, “The green curve represents a de-trended version..” But it is not detrended.
You wrote, “No, what IS interesting is that UAH data land vs. ocean again and again reaches the same temperature difference (!!!) This is the thermodynamically logical behaviour.”
But you are looking at anomalies not temperatures.
You wrote, “Unlike UAH data, conventional data land vs ocean does NOT at all seems to return to a equilibrium state between land and ocean. In stead the land goes higher and higher and higher compared to the ocean temperatures.”
There is no equilibrium. Only YOU believe there is equilibrium.
You wrote, “But again Bob, the real discussion here is : Can there be a natural explanation that land temperatures should rise more and more and more compared to ocean surface as city based land temps suggests?? “
I have repeatedly shown you why with this graph but you fail to acknowledge it, like you failed to acknowledge earlier comments I made to you.
http://i51.tinypic.com/34dr6de.jpg
You wrote, “How can this be? What should enable such a growing distance in temperature?”
There is no growing difference in temperature. Since annual land surface temperatures are on average less than sea surface temperatures, the temperature difference between land and ocean is decreasing, not increasing, but don’t let the facts get in the way of your evaluation.
Good bye, Frank. All I’m doing is repeating myself.
Bob you write: “But you are looking at anomalies not temperatures. ”
Im looking at temperature anomalies.
If temperature anomalies for UAH allways tend to return to the same distance between land and sea , this means that temperature allways tend to return to the same distance between land and sea. (!!!!!!)
Only thing missins when working with anomalies and not absolute temperatures is… the nowledge of absolute temperatures for a given time. But in NO way does this affect the picture of how the temperauter TRENDS behave.
A simpler picture is, that the long trend UAH land resembles UAH ocean. Yes, this goes for temperature anomalies.
So there is a BOND between land vs. sea in UAH. This BOND is not seen when you compare direct surface water temperature with mostly city based temperatures. The latter keep growing and growing and growing compared to the sea surface temperatures. This missing BOND is NOT a result of using Temp anom in stead of temp. It is NOT a result of one data type having more monthly oscillation than the other data type, thats completely irrelevant.
I dont know what more to write to make you understand these things too. I have come to that conclusion earlier, therefore i suggested we did not bother WUWT with it anymore. I think we can agree that we dont agree. However, I have shown this to several extremely good heads, and they have just no problem understanding the clear message in data i present here.
A look at fig 2:
http://hidethedecline.eu/media/UAHUHI/UAHurban2.jpg
says it all. We have TREND differences that suggests that city-land data trend goes warmer than the other data can support, including UAH land. UAH land is much more bonded to ocean temps than city-land, and thus the discussion is as I said: Should city-land temps be bonded to ocean temps to some degree or can they fly off like city-land suggests. Thats the question.
To me, your constant focus on more monhtly variation to explain trend difference, your focus on absolute temperatures in stead of temp anomalies when focusing on trend differences etc etc simply shows that you are fundamentally missing the point and seak where you should not be seaking. Claim errors when its your logic that errors.
K.R. Frank
And, Bob, to your wish to prevent critique of GISS Tsurf even though its still on NASA GISStemp frontpage:
As we talked about GISS still has this product up. Keeping Tsurf maps available and updated for all to see and use.
But more:
The Tsurf is the “identity” of GISS/Hansens products. This is what they did in 1981, and especially from 1986 and foreward. The Tsurf is the “pride” of Hansen.
If GISS one day takes this xbdsjbckjxb Tsurf back and OFF, then what does this due to Hansen?
Have you seen the NASA GISS page where Hansen is described like this legendary hero, then Hansen did this, then Hansen did that? Can you see why they can never take the Tsurf off?
No, GISS only has the option to write some note to avoid too much critic, and then Bob, some sceptics plays along, some dont.
The errors in Tsurf are a huge blow to GISS, and off course we sceptics should scream out about this at any chance we get. Why not reveal the nakedness of the GISS´s major “achievement”??
K.R. Frank
Frank Lansner says: “So there is a BOND between land vs. sea in UAH.”
They are measured the same way, from the same satellites. There are no boundaries separating them. Maybe this is why you think there is a bond between them.
You continued, “This BOND is not seen when you compare direct surface water temperature with mostly city based temperatures.”
First, based on your post and this comment, it appears you have analyzed land surface datasets. I say that because you wrote, “mostly city based temperatures.” I assume you are talking about the land surface temperature data and that you are claiming that it is made up of “mostly city based temperatures.” What percentage of the land surface data are categorized in your analysis as urban and what percentage are rural?
Second, why would you expect to see this “bond” between land and sea surface temperatures? Unlike the UAH land and ocean TLT anomalies, sea surface and land surface temperature data are not measured the same way, and there are boundaries between them.
Your December 23, 2010 at 1:19 am reply starts with, “And, Bob, to your wish to prevent critique of GISS Tsurf even though its still on NASA GISStemp frontpage…”
I have not asked you not to critique GISTEMP data, Frank. You can critique it all you like, but the GISS dTs data is not the “current” GISTEMP dataset. And since it is not the “current” GISTEMP dataset, your critiques have little to no meaning in discussions of land plus ocean datasets. I’ve quoted the word “current” for a reason. Here’s a link to the recently published Hansen et al (2010):
http://pubs.giss.nasa.gov/docs/2010/2010_Hansen_etal.pdf
In it Hansen et al write, “[15] The current GISS analysis employs several independent input data streams that are publicly available on the Internet and updated monthly. In addition, the analysis requires a data set for ocean surface temperature measurements in the presatellite era. In this paper and in the monthly updates on our Web site, we now show results using alternative choices for presatellite ocean data and alternative procedures for concatenating satellite and presatellite data.”
In other words, their current analysis uses sea surface temperature data and they present two different datasets. One is based on HADISST SST data before the satellite era, and the other based on ERSST.v3b data. If their “current” analysis uses SST data, then the dataset you referred to in the post is “not current”, meaning it is outdated, or obsolete.
Hi Bob
You write: “the GISS dTs data is not the “current” GISTEMP dataset. And since it is not the “current” GISTEMP dataset, your critiques have little to no meaning in discussions of land plus ocean datasets”
(You then describe the well known components of LOTI)
Bob, when I show a potential problem for land ground based data measurements, this is a problem for the official GISS online Tsurf product where land data are used for both land and ocean.
You then personally define that we are talking about “land+plus ocean datasets” and that I somehow therefore cannot mention the Tsurf problem using land data over sea in the end of my article. Bob, I am not 100% sure that its not my fault but I simply just cant follow your logic, I really wish I could.
(We are going in circles. You find It irrelevant to criticise Tsurf because GISS don’t define it as their current dataset. I find it relevant to criticise because its still on their GISStemp front page still and they still update maps and values and Tsurf is in their product catalogue for all to see every month.)
Bob lets move on: Why do you think that GISS keep the Tsurf available online with fine maps and data updated every month? Why this constellation with a Tsurf product online that is not “the current” ?
(Bob, im now writing a post for hidethedecline.eu only with all the odd claims of “errors” here at WUWT for reference when needed.)
And Bob, please read the text from fig 7. It says:
“Fig7. In the case of Hadcrut temperature series they use around 35-40% land data when calculating global data, but GISS have a temperature product using roughly twice this fraction for land area as fig 7 shows.”
So i actually to begin with wrote “GISS have A temperature product using….”
I did not just write “GISS temperatures says…”, i was actually rather carefull even with this detail that you attack so much?!
Bob, is not Tsurf a GISS product?
?
The problem is, Bob, that is this level of “errors” is enough for you to drown the whole debate with your error claims, I think you could attack pretty much all other stories the same way.
Frank Lansner says: “And Bob, please read the text from fig 7. It says…”
Don’t change the subjecy. We are discussing what you wrote in the preceeding paragraph, Frank. You wrote, “The problem of “extra heat” in land temperatures (likely to be UHI and more) is escalated by GISS because they extrapolate the ground based land temperature measurements over the oceans in stead of using real ocean data…”
You wrote, “Bob, when I show a potential problem for land ground based data measurements, this is a problem for the official GISS online Tsurf product where land data are used for both land and ocean.”
But I just discussed with links to the GISS paper that the GISS dTs is obsolete: If their “current” analysis uses SST data, then the dataset you referred to in the post is “not current”, meaning it is outdated, or obsolete.
You asked, “Why do you think that GISS keep the Tsurf available online with fine maps and data updated every month?”
It is not used in their official proclamations about what year is warmest, so it does not concern me. Again, it is obsolete.
Hi Bob, I think our discussion ( mainly about the GISS dT/“tsurf” product ) is caused by the fact that GISS sends a mixed message to begin with.
Either,
1) The dT/Tsurf product has been ditched, 100% obsolete by NASA it self: Then it makes no sense to criticize that GISS uses it, but in stead sceptics could and should trumpet and celebrate that the crown juvel of Hansens scientific work through times has exactly been ditched by NASA.
Or
2) The dT/Tsurf product is just not the preferred product by GISS, but they still update and mae public the Tsurf Maps and data for the public and thus can and should be criticized for the problems the tsurf has.
Bob, if you are 100% correct, that dT is “obsolete” and I can quote you for this, it is one of the corner stones in Hansens work and scientific standings that is finally withdrawn. This is of course something that would deserve a nice sceptic headline if 100% true. But what would happen if we made an article at WUWT, for example saying “Hansens methodic used and promoted since 1981, 86 has been withdrawn and ditched by NASA” or similar? Then very fast, the counter argument would be: “Oh no, GISS still find it relevant to update the dT/Tsurf and they even bring it on the front page of GISStemp homepage, so they still find it scientifically relevant!”
So this semi-withdrawel of the dT by NASA – in my view has a purpose. They cant defend it, but cant really ditch it 100%.
The “note” you refer to goes:
“Note: LOTI provides a more realistic representation of the global mean trends than dTs below; it slightly underestimates warming or cooling trends, since the much larger heat capacity of water compared to air causes a slower and diminished reaction to changes; dTs on the other hand overestimates trends, since it disregards most of the dampening effects of the oceans that cover about two thirds of the earth’s surface.”
“The dT overestimates trends…” says NASA. ( What year did note start to sound like this??) I recently argued on WUWT that the very method of dT/Tsurf used over Artctic and Antarctic where indeed overestimating trends. I just compared to DMI/ERA-40 data 80-90N, and the error was obvious.
What happened?
Over at SCEPTICAL SCIENCE they went bananas!! They DEFENDED the dT as if this was a goldmine of correct methodic. So I guess, the message, that NASA now says that the dT method overestimates trends should have some more spotlight? And the fact that they still use the method over Arctic/Antarctic and on this ground claims huge Arctic warming… while admitting that the method overestimates? Hmm, it’s a story.. ?
K.R. Frank
Ps, i made a resme of this discussion here: http://hidethedecline.eu/pages/posts/discussion-of-the-article-uah-reveals-urban-heat-210.php – i can imagin you might have some say, and im ready to adjust if I have not refered correctly.
Actually, it was obsolete when shiny new.
Heh.
Frank Lansner says: “Bob, if you are 100% correct, that dT is “obsolete” and I can quote you for this, it is one of the corner stones in Hansens work and scientific standings that is finally withdrawn. This is of course something that would deserve a nice sceptic headline if 100% true.”
Not sure why it would. They don’t use it in their recent reports or press releases, so it’s non-news.