How not to measure temperature, part 83: No smoking please

The USHCN Climate station of record in Milton-Freewater, Oregon. Note the beige smoking stand.

The casual way that NOAA treats quality control of the measurement environment of the surface network has been evident for some time. The above photo is of course just one of many examples. Now before anyone jumps to a conclusion thinking that I’m suggesting heat from cigarettes might affect the temperature reading, let me be clear, I am not.

But a couple of guys hanging around the temperature sensor on a cold day shooting the bull and puffing, maybe. Body heat carried by wind to then nearby MMTS sensor “could” be an issue in making Tmax just a bit higher than it might normally be.

But that is likely swamped by the larger local signal near the temperature sensor –

Click for larger image

– the waste heat from the sewage treatment plant.

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69 thoughts on “How not to measure temperature, part 83: No smoking please

  1. Does a modern sewage treatment facility give off methane? If so, on a still day the smokers may warm up the sensor to unprecedented Temps. Call it Gasstemp.

  2. Any idea what the narrow black object on three legs is between the smoke stand and the MMTS is? Could it be a heater to keep smokers warm on cold days?

    REPLY: It is the rain gauge – Anthony

  3. The first five letters of the facility’s name say it all — Waste.

    If that station shows an anomalous warming trend, perhaps it is from the Carbon Monoxide, Carbon Dioxide, and other fun GHGs from the cigarettes and the smokers standing around emitting CO2 with every breath.

  4. The smoking thingy is obviously there to remind smokers not to use the adjacent rainfall gauge as an ashtray.

  5. I think climatebeagle’s onto something important here. That sure looks like a burner for heat to me…what else can it be?

    Good nose – er, I mean eyes – ‘beagle!

    But it would still be swamped out by the waste heat from the plant. The whole place represents another one of the many ways to spell, “duh”.

  6. I assumed it was a rain gauge. It may be an optical delusion but it looks like it is not quite upright and hence the area taking precipitation will be an ellipse rather than a circle.

  7. I think the more important question is….
    Is that thing on the bottom left of the picture one of those round life preservers.
    At the waste treatment plant.
    *shudder*

  8. As a long time smoker, the brown object by the rain guage is for cigarette disposal.

    Thermal sensors would be much more responsive to human body heat, than from a cigarette.

  9. climatebeagle: My guess is that the narrow black cylinder is a precipitation sensor, and also a coffee cup holder.

  10. Maybe the cigarette disposal should be reconsidered as a heat source/release mechanism. Warm air trapped and released at night?

  11. Maybe the butt container is there so that anyone working near the gauge will extinguish their smokes. As far as large, immobile objects influencing readings goes, as long as they are always present, they may influence absolute readings but the trends from the data would be unaffected. This whole project to try to discredit sensor placement is a little too “gotcha” and seems aimed at swaying the opinions of the, how shall I put this…less “analytical” among the population. Perfect example is those who think the rain gauge is a “heater”.

  12. That’s a Standard Rain Gauge, no question whatsoever. But the ones I see are usually silvery, not black. Could a black SRG placed that close to an MMTS have a small heat sink effect?

    REPLY: Bronze, it is, not black.- Anthony

  13. Anti-tobacco hysteria next to GW hysteria: Funny. Both with a common origin. Have you wonder if “they” worried about our health? Or “they” worry about earth´s future? or is it just their political agenda which counts?: First Tobacco companies, now oil companies. What next?

  14. ALERT! ALERT! Sorry Anthony, I know this off topic but does Cryosphere Today use the same satellite as NSIDC because if not Cryosphere is having sever satellite troubles as well…..Take a look:

    http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=02&fd=19&fy=1980&sm=02&sd=20&sy=2009

    REPLY: Cryosphere Today added snow cover to the imagery in recent years. No trouble there, no alerts (if that is what you were referring to).

    Updated reply: here is what they have to say about it, I thought CT was using the AMSR-E sensor, apparently not.
    FROM CT:

    The SSMI sensor seems to be acting up and dropping data swaths from time to time in recent days. Missing swaths will appear on these images as a missing data in the southern latitudes. If this persists for more than a few weeks, we will start to fill in these missing data swaths with the ice concentration from the previous day. Note – these missing swaths do not affect the timeseries or any other plots on the Cryosphere Today as they are comprised of moving averages of at least three days.

    – Anthony

  15. Peter (12:03:43) :

    Unless the site placement is the same now as it was in 1914, there is a significant problem in assuming that microclimate effects are static.

    It may be that the microsite impacts on daily minimum temperatures are exactly the same now as they were in 1914. It may be that the microsite impacts on daily maximum temperature are exactly the same as they were in 1914.

    Without even looking at the data or the metadata on station moves, I’m willing to bet that things are nothing like they were 95 years ago, both in terms of the physical conditions of the temperature monitoring station and in terms of the influence on the temperature measurements from the surrounding environment.

  16. GLOBAL WARMING – Smokers got moved outside in the 90s.

    GLOBAL COOLING – much fewer smokers now than 20 years ago.

  17. RE: Peter (12:03:43) :

    Since the butt container is right there by the door, I would guess it more likely that it would be smokers – not workers – who would be in proximity, Peter.

    And us “less analytical” folks didn’t jump to conclusions like you did. We only “asked” if it was – and observed that it very well might be. We also readily admit our error – if error it be. Perhaps you should read more carefully and conclude a bit less.

    And us “less analytical” folks have seen all the quantitative data presented here and at Surface Stations on these definitely discredited stations. Data that indicate – for the most part unambiguously – that the placement, relocation, and the maintaining of these stations is a serious factor in the accuracy of the data.

    Oh – and BTW – the absolute data from these stations are affected (as has been demonstrated by both experiment and a huge SS data base), and definitely affect the “trends” resulting from the data.

    That’s the whole point.

  18. Holy…er…waste treatment, Batman!

    But seriously, folks, the asphalt is probably the major fly in the punchbowl, here. Any warming trend, from whatever cause, will be amplified by the low albedo surface. UHI is NOT a static phenomenon; the root causes of UHI interact with other trends. Asphalt convective cooling rates will rise by the temperature differential, dT; asphalt heating will rise by a d(T^4) factor.

    Okay, guys. Don’t forget; on March 1st, everybody moves their BBQ another foot closer to the sensor.

  19. Peter (12:03:43) :

    Maybe the butt container is there so that anyone working near the gauge will extinguish their smokes. As far as large, immobile objects influencing readings goes, as long as they are always present, they may influence absolute readings but the trends from the data would be unaffected.

    That’s the problem, Peter. Do you know how long its been there? When they dump it, do they return it to the same place? Look at all the other junk scattered round; pieces of molding, trash container, fertilizer buggy (organic fertilizer?), a white sign or something next to the butt disposal unit, etc. How long have they been there. Granted, they won’t influence the temp as much as the sewage unit, but it’s not proper. Think about this- see how the unit is leaning? I’ll bet you anything the workers lean against it while puffing, maybe even blow smoke rings in it for a laugh. Can that account for some error?

  20. Peter,
    The point is that this reporting location was probably in a site in the past that would not affect the readings like a waste water treatment plant. That kind of environment change would, indeed, produce an incorrect warming trend. Waste water treatment is a rather recent development in a long term temperature record.

    This kind of siting issue could also affect the trend if many well-sited rural locations dropped out of the recent record leaving sites like this to continue reporting. The aggregate trend would increase artificially.

  21. I suspect both body heat and cigarette heat would both be negligible compared to the heat coming of those substantial percolating filter beds.

    Not only is the incoming sewage close to room temperature, percolating filters actually generate heat when the bugs are munching well.

    http://books.google.co.uk/books?id=5lfTnwR1HEgC&pg=PA102&lpg=PA102&dq=trickling+filters+heat+generation&source=web&ots=-Xk-CiudoA&sig=a95jcoF9KvkInZCkz_SVf2F2aMA&hl=en&ei=FDKfSZGbCtrG-Qa_u9m1Dg&sa=X&oi=book_result&resnum=1&ct=result

    Percolating heaters are well ventilated with natural ventilation, so the local micro climate will be both significantly warmer and way more humid than the general surrounding area.

    A very, very poor place to site a weather station.

  22. Warning: This paper has been rejected by Science and Nature. It May be hazardous to your research grant.

    Satellite Data Show No Warming Before 1997. Changes Since Not Related to CO2

    http://anhonestclimatedebate.wordpress.com/2009/02/20/satellite-data-show-no-warming-before-1997-changes-since-not-related-to-co2/

    Fatal computer errors in IPCC climate models derive from the fact that none of the abrupt warmings and coolings on the record, especially since 1998, can be attributed to the greenhouse effect. Hence, all IPCC models purporting to predict (project??) climate a hundred years into the future are invalid and their predictions/projections must be discarded. To summarize: existing theory used by the IPCC can neither explain the observed climate nor predict the future. Carbon dioxide warming has been shown to be non-existent in the eighties and nineties, and the warming since 1998 is not carbonaceous in origin. It follows that Quijotic carbon dioxide policies like the Kyoto Protocol and the cap-and-trade laws should be abandoned.

  23. As the town grows so does the throughput of waste treatment plant. I would say that the waste treatment plant not only corrupts absolute temperatures but also trends.

  24. Peter (12:03:43) :
    Actually Peter the standard rain gauge can make a great albeit temporary heater by removing the funnel then the inner tube, pouring in a cup of kerosene and voila’, at least 10 minutes of comfort (kids, don’t try this at home!).

  25. I don’t know if it makes a difference or not, but generally I don’t think it’s a good idea to encourage people to stand near the temperature sensor. Just another example of how this system was never intended as a high-quality climate monitor – just local weather. And it’s still treated that way.

  26. Thanks for pointing out it’s a rain gauge. I visit sites like this to understand more about alleged AGW and learn something new with every article.

    As a new question is there any writeup on how global temperature is calculated from all the ground stations? I found Hansen’s original document but didn’t see details there, found one paper that said a global temp is a bogus concept. My real question is from living in the SF Bay area, is the area over which a ground station might represent an accurate temperature taken into account? For example, I would guess that the station in Berkeley represents a valid temp for less than 10 (ten) sq. miles around it (temps can differ by 20F in under two miles here) where a station in the central valley might represent several hundred square miles. Thus a simple average of the two would be meaningless, an area weighted one might have more value related to a global measure of energy in the system.

  27. This brings up a point that has been made before. In the past the temp reading was not so critical. The location at the airport was critical for the power settings on jet aircraft. That was the most important factor for location. 40 years ago if you had told a weatherman that we would be arguing over .01degrees in a temperature average, he would give you a strange look.
    Computer modeling has changed all that, the historical records are not that accurate and weren’t intended to be.

  28. climatebeagle,

    You are right about averaging temps between stations. I apologize if the following explanation is something you already know, but I’ll put it out there just in case. The global mean temperature that gets calculated doesn’t just average temperatures though, it averages what is called the ‘temperature anomaly’. This means that for each temp station the monthly average is compared against the average of all prior monthly averages. The difference is the anomaly. So if the average January temp for a given site is 24.0 degrees F, and the average for last January was 24.8 F, then the anomaly for the station is calculated to be 0.8 F.

    If a site inland has a historic average January temp of 44.0 and the temp there last month was 44.5, then the anomaly for the inland station would be 0.5 F.

    It’s not an ideal way to measure the ‘global temperature’ but it is in common use.

    The GISTEMP metric takes anomaly data and applies some ‘corrections’ to account for urban heat island effects. The code that is presumably used to calculate that metric is available at the GISTEMP web site.

  29. Does anyone know how that (settling?) pond is managed? We have a lot of percolation ponds around here to manage the water table. I think they are alternately filled and drained to interrupt mosquito breeding. In that case the thermal effect of the pond could be highly variable.

  30. Thanks Earle, that useful. I’ve had my issues with trying to get a single value from a set of results in the past when I was trying to automatically determine if a software product had a performance regression based upon nightly results. It’s a similar problem in coming up with a single value of if the product is overall faster or slower based upon N performance tests compared to their previous values.

  31. Interesting how a thread like this attracts very little attention from the merry band of AGWers who visit here such as Joel Shore, Simon Evans, Foinavon, Flanagan, Mary Hinge et al, who are usually all over the other topics. Siting a weather/climate station adjacent to the settling ponds of a waste water treatment plan cannot help but add a warming bias to the temperatures recorded here. And I think rather than argue the unarguable (which they seem fairly proficient at) they then rather skip these threads.

    Well done to Anthony and his team of contributors. And the tally of poorly sited stations continues to mount. Anthony, is this a category 4 or a 5 do you think?

  32. The cigarette diposal vessel was placed near MMTS pole and rain guage so smokers could lean against pole and rain guage, which are now leaning to left. That’s killing two birds with stone! No need to buy chair… :)

  33. Earle:

    This means that for each temp station the monthly average is compared against the average of all prior monthly averages.

    I assume that since historically the ground stations have recorded daily max & min that the monthly average is really (at worst):

    monthly arithmetic mean of daily (min +max)/2

    or possibly

    monthly arithmetic mean of daily smartfunction(min, max)

    and better

    monthly arithmetic mean of daily mean of 24 hourly readings

    Though I did find this link that indicated (min+max)/2 is close to 24 hourly readings overall.

    http://www.engr.udayton.edu/weather/source.htm

    Sorry if this is covering basics, but I haven’t been able to find a clear definition of this.

  34. Wonder how the MMTS reacts to regular jarring from smokers leaning on it or ‘falling’ into it on their backsides as they relax and puff away. Probably still not as much as the aromatic bubble of heat such facilities normally generate.

  35. This is near water! Even has a flotation device (and floaters based on the travel brochure). Where is the silver boat turned upside down near by??? Out of compliance. tsk tsk.

  36. climatebeagle (16:32:45) : As a new question is there any writeup on how global temperature is calculated from all the ground stations? I found Hansen’s original document but didn’t see details there, found one paper that said a global temp is a bogus concept.

    The first problem is exactly that. What is a global average mean? There is a high and low for the day that are averaged together (that I suppose tells us a little bit about the temperature for the day, but 60F and fog all day is not the same as 30 at night and 90 at 4pm under full sun …

    Then these ‘averages’ are averaged over larger areas with unequal distributions of thermometers. What does it mean when you average 4 New York City with 3 rural Ohio? If we add 2 more stations to Ohio, did the temperature change? (The average did…) When the jet stream has New York getting gulf air, but Ohio with a Canada Express, does the one with the most thermometers ‘count’ more? (It does to the average…)

    My real question is from living in the SF Bay area, is the area over which a ground station might represent an accurate temperature taken into account? For example, I would guess that the station in Berkeley represents a valid temp for less than 10 (ten) sq. miles around it (temps can differ by 20F in under two miles here) where a station in the central valley might represent several hundred square miles. Thus a simple average of the two would be meaningless, an area weighted one might have more value related to a global measure of energy in the system.

    BINGO! and then some… That Central Valley thermometer can be used to ‘adjust’ the Berkeley thermometer based on the notion that the CV station is ‘rural’ and can adjust out the ‘Urban Heat Island’ in Berkeley. This is clearly so broken that the typical person in California would laugh their self silly, but that is what is done.

    But wait, there’s more: Stations of 1000km away are considered ‘nearby’ for purposes of rewriting station data…

    But wait, there’s even more: An ‘offset’ is calculated based on whatever part of the last 10 years is available. This is applied to all history for all time so the temperature in the central valley from 1998-2008 (when massive growth was happening) can be used to ‘adjust’ the temperatures in Berkeley in 1889 …

    This is taken from reading the GIStemp code directly. I can provide more detail if anyone has the stomach for it. (I don’t advise it…)

    GIStemp pasteurized homogenized processed data food product are useless. (IMHO of course). They contain critical failures such as the above. It would be far better to simply take the UHCN and antarctic data sets and merge them (as is done in the first 1/2 step of GIS) and skip all the rest of their data fantasy processes.

  37. Earle Williams (18:34:15) : The global mean temperature that gets calculated doesn’t just average temperatures though, it averages what is called the ‘temperature anomaly’. This means that for each temp station the monthly average is compared against the average of all prior monthly averages.

    Long before the zonal averaging of anomalies the temperature data have been so manipulated that they have lost much contact with reality. Before the anomaly stage, the data have had deletions, infills, offset slides and other things done to them. And I don’t remember GIStemp averaging all prior temps… but I’ve only done a rough cut at the zonal steps.

    The GISTEMP metric takes anomaly data and applies some ‘corrections’ to account for urban heat island effects.

    This is far too charitable. The notion used is that a ‘nearby’ ‘rural’ station can be used to correct for the UHI at an urban location. Ignoring the fact that the way urban and rural are picked is fraught with error… This ‘reference station method’ is based on an over generalization implemented badly.

    The assertion is that a ‘correlation’ exists between urban and nearby rural that lets you make an offset. This offset is then used to ‘adjust’ the urban station data.

    The Problems:

    1) The ‘offset’ is calculated as a simple subtraction. The idea of ‘correlation’ has mutated into ‘linear offset’. This is broken.

    2) UHCN and GHCN data are compared. If no GHCN data exists, the UHCN are accepted. If GHCN exists, an ‘offset’ to UHCN is calculated and applied, and this resultant record is used (tossing both original UHCN and GHCN data). The ‘offset’ is calculated from a most recent 10 years data (that portion that is available.) This may be reflecting, for example, recent changes of equipment or time of observation. This ‘offset’ is then applied to all prior data from 1880 onward. (For some unexplained reason, all data prior to 1880 are tossed out.) What does a change of thermometer in 2005 have to do with UHI in Berkeley in 1885 ?

    3) A ‘reference station’ can be up to 1000 km away. What does Reno have to do with Berkeley? How about Lodi? Fort Brag? Pismo Beach?

    4) Only after all this are the anomalies calculated and the zonal averages averaged and offset adjusted some more. In this step, the ‘reference stations’ can be up to 1500 km away. Furthermore, you may have applied the Reference Station Method 3 or 4 times. What possible rational is there for this recursion? Is there any peer reviewed literature for repetitive application? Or is it just a case of bald assertion that it’s ok to keep on passing the data through the grinder because it was shown that ‘nearby’ station data ‘correlates’ as raw data?

  38. climatebeagle (20:43:38) : I assume that since historically the ground stations have recorded daily max & min that the monthly average is really (at worst):

    No, it’s worse than that…

    monthly arithmetic mean of daily (min +max)/2

    This is what is done by NOAA. You get an average of min/max over the month. I’ve not swum up stream enough to be certain, but what I think they do is the:
    summation(((min+max)/2) for each station over month-days)/#days

    Also NOAA applies some corrections (TOB time of day bias for example) and present this to the world. (How to get the data is listed in the comments under the resources tab above).

    GIStemp then concatenates this data with the data from Antarctic stations, stirs in a couple of hand rolled sites (where they have special sauce access to data…) and does a merging of the USHCN data from NOAA with the GHCN data (that originally came from NOAA but has a different ‘correction’ history). In an attempt to merge these two disjoint data sets (Gee: Merging disjoint data.. where have I seen that before!) an ‘offset’ is applied to make things line up nice (but only applied when both USHCN and GHCN exist! Which ought to be very often.) as described earlier.

    Oh, and there are several steps where chunks of data are tossed out, and a couple where things are filled in if missing… often just after you tossed it out… A lot of smoke and mirrors, IMHO.

    Then you get to the anomaly and zonal anomaly stages and finally those zonal anomalies are available to make the One Grand Global Anomaly… Which, IMHO, is absolutely useless.

    Much of the historic data was reported with 1F precision AND accuracy. You can not manufacture 0.1C of accuracy out of 1F precision. It’s just a broken idea…

  39. Jeez… Call me picky….. But it would be nice if someone used a set square once in a while ….. That useless rooftoop data station looks like something outta Dr Seuss.

  40. Don’t focus too much on the cigarettes, they are a minor factor compared to the operation of a waste treatment plant.

    Typical treatment includes an ‘activated sludge’ process – the tank is like a long open top swimming pool with lots of air injected along the bottom to keep the ‘bugs’ working to digest the influent wastes. I think I found the Milton-Freewater treatment plant on Google map, and it looks like they have two such open-top aeration tanks side by side in the middle of the treatment facility. There is also a clarifier (round open top tank) and probably a settling or carbon filtration pond (also large round open top).

    As someone mentioned, the influent waste stream from underground pipes is likely about 55 deg F, and of course you don’t want the ‘bugs’ to get too cold or they stop working. So all that air injected at the bottom of the sludge tanks comes out the top of the tanks at around 50 deg F and saturated with humidity. That concrete ‘wall’ with the metal stairs in Anthony’s first picture looks like the clarifier, so the activated sludge tanks are either behind us in that view, or on the other side of that building. Either way, close enough for all that pre-warmed air from the treatment process to affect the climate station results.

    Some treatment facilities might also have an ‘anaerobic’ process (closed and no air injection). Anaerobic process gives off methane, which is then burned to provide the heat to keep the anaerobic process going. Hard to say if Milton-Freewater has one of those, but a larger municipal waste treatment facility might very well have both types of processes.

  41. The picture is very clearly a percolating / trickling filter.

    This provides the biological treatment.

    It is a high rate filter, the concrete and access stairs both look new (cf the more rickety yellow stuff). All of which suggests the treatment has been built recently.

    This means it is highly unlikely they also built an activated sludge plant at the same time, so it is highly unlikely there will be aeration tanks.

    Trickling filters do give off modest amounts of heat, this particular filter might warm the air by a couple of degrees.

    It will give off lots of humidity, as will the primary and secondary settlement tanks.

    If the site has a sludge plant it will also have generators and or a flare stack to get rid of the methane, which will produce a significant amount of heat.

    Long and the short of it, a sewage works is a completely inappropriate site for measuring temperature of humidity.

    • kagiso,
      I went back to the Google satellite picture, and agree with your comment that it is probably a percolating / trickling filter. So the other ‘tanks’ are probably the settling basins (no aeration), as you describe.

      We are in agreement that, with all that liquid surface nearby, “a sewage works is a completely inappropriate site for measuring temperature or humidity”.

  42. That is not a rain gauge. It is a urinal. (KIDDING! ☺ )

    Keep up the good spying on the wx stations.

    Clive

  43. “Peter (12:03:43) : ….as long as they are always present, they may influence absolute readings but the trends from the data would be unaffected. This whole project to try to discredit sensor placement is a little too “gotcha” and seems aimed at swaying the opinions of the, how shall I put this…less “analytical” among the population”

    You need to step back and be more “analytical”. The date that this station was placed there is important. It looks like a fairly modern station. I think you could agree it is less than 150 years old, and that it was placed there less than 150 years ago. The time period under the microscope for AGW believers is the last 150 years. And the temperature increase under that microscope is measured in tenths of a degree. The influence from the surrounding heat sources would skew temperatures upwards and could account for more than those tenths of a degree in this station.

    But you say “trends” are still intact. Let’s take a quick look at that :

    Skewing of temps would be higher on days when wind blows heat from the wastewater treatment plant directly to the station. Wind is a random variable. Winds cannot be relied upon to follow “trends”. Temps would be skewed higher, and then even higher, in a random pattern. Trends may not stay intact at this station.

    This station is just one example of many where temp stations have been placed (I would say in almost all cases unintentionally) near heat sources in the last 150 years.

    I still am looking for an explanation for this station :

    This “project” may be more “analytical” than you had at first thought Peter.

    I should have been more detailed but I don’t like to see looong posts (like this one :( ).

    But one last thought : in the last few years data shows a cooling “trend” in the earth. So the manmade co2 hypothesis doesn’t work. (data are ;) )

  44. “Hank (15:00:18) :

    As the town grows so does the throughput of waste treatment plant. I would say that the waste treatment plant not only corrupts absolute temperatures but also trends.”

    Interesting.

  45. Just want truth… (09:05:25) : “Winds cannot be relied upon to follow “trends”.

    Yes they can. These trends are called “prevailing winds.” Most airfields depend on this information to construct runways in the right direction. I would also suspect that most sewage treatment plants are constructed, if possible, downwind of nearby population concentrations.

    Winds also affect climate even though these ‘climate history’ installations apparently neither measure nor record it. Worse yet, the climate models don’t even consider winds, or moisture, or clouds, or pressure, or for that matter anything but max/min temperatures. I find that extremely strange.

  46. On this cold February we are focusing on the warming effect of the local environment. However, in the summer that same 55 degree waste stream will cool the area of the plant.

    Any trend will be moderated by the constant temperature of the waste water.

    Although not a temperature effect the chemicals in the air around a sewage plant are corrosive. After a few years exposed to that smell exposed copper gets a black non-conductive coating.

  47. “Rod Smith (10:16:40) : Yes they can. These trends are called “prevailing winds.” ”

    I understand prevailing winds. And I suspected someone would say something about that. That’s why I said “I should have been more detailed”. I didn’t want to add more to that comment because it was so long already.

    My point was that winds will carry warmth to that station more on some days than on others within the prevailing winds. Also the winds that will come from other directions on various days will have varying speeds, with no reliable trend. There will not be a constant wind speed. The trend caused by prevailing wind would not correlate well enough with the temperature trend to say the temperature trend at the station would be the same as temperature trend a distance away from the treatment plant.

  48. Looking at the lower photo there is new construction going on too, judging by the reinforcing rods poking up.

  49. E.M. Smith,

    Your points are all valid. I just wasn’t willing to wade into them in my earlier response!

    :-)

    I’m trying to convince myself that there is a better way to construct a global mean temperature (whatever that is) than by abusing already abused time series. I’m thinking instead that one should construct a grid of the actual temperatures, not the anomalies. Using a method like kriging you could generate a grid of the temperature field and also create a matching grid of uncertainty values corresponding to each grid cell temperature estimate.

  50. Peter, you make me smile. Keep the faith!

    As a AGW believer years ago, it was my son asking questions that got me digging into the detail. I was surprised by what I saw. I’m not beholden to one answer, I’ll gladly switch sides when I see I’m wrong. AGW theory looks like a castle built on sand. That’s why I read the comments and look for what an AGW beliver says about the lot of sand shown in this post. I was mostly looking forward what Ms. Hinge might have to say – there are times when she’ll provide links to facts that are worth considering.

  51. I’m trying to convince myself that there is a better way to construct a global mean temperature

    Take the temperature records from the best locations you have and simply average them.

    The main problem with approach is that the locations are a non-random sample, but then any use of existing stations would suffer from the same problem.

    IMHO, the whole concept of gridded temperature data is wrong (has no statistical validity). The gridded dataset was originally developed to provide data to validate the climate models. The grid sizes correspond with the precision of the climate models. Or at least they used to.

  52. At last something I can speak on with authority, smoking.

    Every experienced smoker knows that external smoking areas must be supplied with a source of heat in cold weather, otherwise we have to smoke three cigarettes at once, two to keep warm and one for the vitamins and other benefits. Hence the placement of the ciggy-end bin right next to the thermometer.

    It’s obvious really. We have all been getting colder over the last few years, yet Dr Hansen and his friends tell us it’s actually getting warmer. Where does he get that information? Answer: from thermometers. Therefore it must be the thermometers that are getting hotter. It follows from this that the ashtray must be placed next to the thermometer so that the smokers can warm themselves while doing their duty and ensuring a future flow of tobacco tax revenue.

    You scientist chaps just don’t think these things through.

  53. Philip_B (19:25:18) :

    I’m trying to convince myself that there is a better way to construct a global mean temperature

    Take the temperature records from the best locations you have and simply average them.

    The main problem with approach is that the locations are a non-random sample, but then any use of existing stations would suffer from the same problem.

    If you were starting with a blank sheet of paper, to measure a property of the surface of a sphere, I would think you would want to measure a specific number of uniformly spaced points on the surface of the sphere and then take an average of them.

    For a concept, suppose you were to construct an icosahedron where the surface of the earth was its intersphere. You would then have 20 uniform triangles that touched the surface of the earth at their centroids. Use a satellite to measure those points and average the readings for a weeks time.

    I know 20 data points would be a bit slim for a statistically significant sample but you could construct a similar geometric solid with more uniform faces (or multiple icosahedra ) if you needed higher sample counts.

    At least that would have some rational plan to it. An icosahedron would give you approximately 15 of the triangular faces centered on an ocean and 5 centered on a land mass.

    Larry

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