Interesting Anomaly By Region By Calendar Month Graphs

For a description of just how the anomaly stuff is done and some comments about why, see my comment here:

https://chiefio.wordpress.com/2019/03/13/anomaly-by-continent-graphs-ghcn-v3-3/#comment-109603

The graphs in the posting are a bit “rough” in that I’m still playing with the scales and colors. I started out “just red” then decided to color code by season but used two different colors for a season and, well, I can either spend a day re-doing them all or just “go with it” for now and describe the Interesting Thing I’ve discovered.

Basically I found that for some Continents (regions) the Winter Data is vastly more volatile than the Summer data. Most (all?) of the “warming” comes out of a reduction of the volatility to the downside of those cool season data. Hot seasons are just not very volatile. Yet they DO have an up tilt at the very end with the advent of electronic thermometers and lots more asphalt around airports.

My conclusion (up here at the top ;-) is that this leans strongly toward “hot black asphalt in the sun” causing the summer “lift” and “loss of high cold volatile places” causing the cool season “lift”. Remove those stations at altitude that tend to have the strongest cold excursions, you get a flatter winter curve with the cold anomalies pruned. Have an airport add 10,000 foot more runway and 20 acres of paved parking for Jet Travel, you get hotter summer readings.

It is my opinion that accounts for most of whatever warming is in this the unadjusted data. (That then gets enhanced with “all one way warmer” adjustments in the adjusted version).

Intro

Remember that this is the average of all thermometer anomalies over all years for all regions:

Average Anomaly All GHCN v3.3 data

Average Anomaly All GHCN v3.3 data

Note that the range is from -3 C to +2 C and the actual data ranges from about -2.5 C to +1.5C or about 1 C of total volatility.

Here’s the graph for Europe:

Europe Average Anomaly GHCN v3.3

Europe Average Anomaly GHCN v3.3

Very similar. (Other continents are not so similar, you can see them here:
https://chiefio.wordpress.com/2019/03/13/anomaly-by-continent-graphs-ghcn-v3-3/

As there are 7 Continents and 12 months, a set of all graphs would be 84 of them. I’ve made them for Asia, North America, Europe, Africa and Australia / Pacific Islands. Missing are Antarctica and South America. I’ll make them later. For now, what side tracked me into this posting was what happened with Europe and Asia (and to some extent North America – though I’ve not redone them to see how much).

The “problem” that popped up was that winter is just way more volatile than summer. Here’s Europe in summer:

Europe August Anomaly -8 +6 range

Europe August Anomaly -8 +6 range

Notice that I have expanded the range to be from -8 C to plus 6 C. That was needed to match winter below. Still, the data overall range from about -3 to +3 (one ‘flyer’ nearer 4 C) or about 6 C. The top end doesn’t get all that much warmer compared to 1850 to date, but the low excursions end recently.

What would happen if post W.W.II airports added more concrete and asphalt and more of the thermometers were placed at airports and inside the “Concrete Jungle” of cities? More solar heated pavement carryover into night warmth, less vegetation transpiration making cool and damp.

Then winter:

Europe January anomaly -8 +6 range

Europe January anomaly -8 +6 range

From -7 to +5 or 13 C of range. The “top end” doesn’t really get hotter. In fact, other than one “flyer” it is on a cooling trend. What DOES happen is that the lower/cold volatility gets pruned greatly.

What would happen with the loss of High Cold Places? Loss of cold directed volatility. What would happen with more stations over pavement (and with snow removal done and with tons of Jet-A kerosene being burned / hour and with constant swarm of “ground transportation” in the cities and at the airports)? Loss of low going anomaly cold.

IMHO, what these two graphs together show is that “altitude matters” in the set of thermometers and that “asphalt matters” especially in summer. Spring and Fall are intermediate between these results.

Very similar things are seen in other regions, and I’ve made a set of graphs by season for all regions that I’m putting in the next posting.

The assertion will be made that “the Reference Station Method using Anomalies” can fix that loss of “high cold places” 100% perfectly. My assertion is that they must fix a 6 C loss and could easily have a 1/2 C residual in that process (or a 1/12 of the anomaly error), or 8%. That’s all it would take. Where are their error bands?

For comparison in Europe, Fall and Spring:

Fall:

This is the same -3 +2 range as the All Europe graph, so you can see what caused me to go WHA? when it first popped up. Just a huge scatter compared to the aggregate.

Europe September Anomaly -3 +2 scale

Europe September Anomaly -3 +2 scale

Here is the same September data on a -8 +6 scale for comparison to the other expanded range graphs:

Europe September Anomaly -8 +6 range

Europe September Anomaly -8 +6 range

Fall is basically dead flat. It isn’t about Fall, it is about Summer a little bit and Winter a lot.

Spring:

Europe May Anomaly -8 +6 range

Europe May Anomaly -8 +6 range

Spring is basically dead flat. A little bit of ‘loss of cold’ at the very far right, but not much. Spring sunshine on the tarmac anyone? Again, it looks to me like it is all about the loss of winter cold excursions from high cold rural places, and a small addition of solar heated tarmac in the summer.

What it is NOT, is a generalize increase in the whole range of temperatures over all seasons from a “well mixed gas” that is ALWAYS present and “working”.

IMHO this is a Giant Dig Here!!!!! Deserving of a lot more looking a lot closer.

I’m going to continue to do my general “look it all over fast” thing first though. If anyone wants to take this and run with it, a footnote in your paper would be appreciated. (Yeah, I’m a “cheap date” ;-)

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About E.M.Smith

A technical managerial sort interested in things from Stonehenge to computer science. My present "hot buttons' are the mythology of Climate Change and ancient metrology; but things change...
This entry was posted in AGW Science and Background, Global Warming General, NCDC - GHCN Issues, Tech Bits and tagged , , , , , , . Bookmark the permalink.

16 Responses to Interesting Anomaly By Region By Calendar Month Graphs

  1. Bill in Oz says:

    EM I agree with your methodology completely. And it’s good to see this work being done.

    But I want to ad another perspective :
    1 : Most of the weather stations are placed where we humans live ( for the obvious reason that we are mainly interested in the places where we live.
    2: The places where we live in dense concentrations are also the places where we use a lot of energy ( electricity, gas, oil, etc ) Energy isGATHERED & CONCENTRATED in these places where we humans live. And after it is used there is residual heat released into the atmosphere.
    3: Yes this is another form of Urban Heat Island Effect. But nowhere in discussions of UHI, have I seen any mention of the impact of gathering & concentrating all that energy in humans settlements.

  2. Erl Happ says:

    In my experience by the month tells the story. The Southern Hemisphere in its entirety has not warmed for thirty years in the month of January. I base this on decadal data with the warmest decade 1979-88.

    Warming occurs in winter. Its associated with enhanced flow of warmer air to higher latitudes. That’s because of change in surface pressure. Secondly, high pressure areas, particularly in the southern hemisphere have gained pressure/lost cloud.

    No warming for thirty years in January…….that should be the end of the AGW hypothesis relating to ‘greenhouse gases’.

    I have just completed a paper on this. if interested erlathapps.com.au.

  3. Pingback: Geeky Data From The Chiefio – sunshine hours

  4. E.M.Smith says:

    @Erl Happ:

    That reference doesn’t seem to work. Can you just paste in the url? I AM interested…

    Or is that an email address and the “at” in the middle is an @?

  5. erl happ says:

    It’s an email address.

  6. Simon Derricutt says:

    EM – by the time you’ve got the other GHCN versions plotted this will give a superb visualisation of how the original data has been adjusted away from reality. The idea of comparing each temperature-measuring instrument only to itself is logically-justified, but bear in mind that at some point the method used at a particular location may change and invalidate the comparison – if they change from liquid-in-glass to thermocouple then it’s no longer like-for-like and such a record would really need to be split at the point when the method changed. Also applies if they changed the time of observation, or changed from a fixed time of day to max/min observations.

    I suppose you can’t really get away from the fact that the data is somewhat of a mess, and not that much of it is going to be directly comparable over the history. You’ve already noted that in some locations the local conditions have changed (more buildings and concrete/tarmac) and thus we’d expect a difference in recorded temperatures for the same weather conditions.

    It sure looks to me that the claimed temperature increase (claimed to be accurate to 0.01°C) is a result of the location changes and method changes, rather than a real accumulated change of global conditions.

    What really matters to us, though, is what crops can grow in which locations. Data on that will of course be confounded by the various varieties available for each crop, each of which will have different requirements for sun, water, soil, etc.. Still, finding evidence of vines growing all the way up to Hadrian’s Wall in the UK (when genetic modification wasn’t an option) does pretty-well tell us that an extra 5°C or so won’t be a disaster. Given that I moved from the UK to France to get around an extra 5°C average temperature, the prospect of those extra degrees doesn’t scare me like it seems to scare the AGW crowd…. Having lived through the winter of 1963, I really don’t see any problem with a bit more heat, but definitely see a problem if it gets colder. I also don’t see that we can really change the amount of energy we get from the Sun, either, except reducing it by aerosols (pollution), and volcanoes emit way more than we can.

    Still, showing the data this way makes it pretty clear that there isn’t a problem.

  7. Gary says:

    E.M., last year I did an analysis of artificial structure encroachment at a USHCN paired station site that shows conclusively that nearby paving asphalt definitely compromises temperature records.
    https://wattsupwiththat.com/2018/04/09/infrastructure-encroachment-at-a-noaa-climate-reference-uscrn-site-makes-the-data-warmer/

    Compromised stations are a much bigger problem than has been admitted. Even when they are sited to be unaffected by unnatural influences it still happens.

  8. Ron Clutz says:

    E.M, I did a study that reached similar findings with a different methodology. It focused on a few long service stations with continuous records. To be included, a station needed at least 200 years of continuous records up to the present. Geographical location was not a criterion for selection, only the quality and length of the histories. 247 years is the average length of service in this dataset extracted from CRUTEM4.

    The 25 stations that qualified are located in Russia, Norway, Denmark, Sweden, Netherlands, Germany, Austria, Italy, England, Poland, Hungary, Lithuania, Switzerland, France and Czech Republic. Not surprising given the criteria that all are European, and located in cities. The method was to use station trends as the temperature derivative for comparison rather than anomalies, and that required using monthly averages as basic data to capture seasonal variations.
    The main findings:
    1. A rise of 0.41°C per century is observed over the last 250 years.
    2. The warming is occurring mostly in the coldest months.
    3. An increase in warming is observed since 1950.

    Details are here: https://rclutz.wordpress.com/2015/03/27/analyzing-temperature-change-using-world-class-stations/

  9. E.M.Smith says:

    @Simon:

    Part of the “goal” of this approach is to highly “what actually happened”. To that end, I’m not trying to hide things like instrument changes (in an aggregate average mush) but make them stand out (bin those monthly graphs of a smaller area showing the discontinuity at the ’90s)

    In an early version of this approach (FORTRAN and Tables of Data) I even took it down to individual country reports. I’m going to do the same with the approach, but only for a few countries (USA, Australia, New Zealand, UK, Russia…)

    One thing that can “throw” people is the pre-conception that I’m trying to find “the real Global Temperature”. I’m not. I’m looking at the shape of the data and asking: “what does that tell me about the probably cause of that shape?” Averaging a bunch of things together hides that, thus the desire to average as little as possible and not compare an instrument to some other one.

    @Gary & Ron Clutz:

    Thanks for the pointers to the articles. I’ll “hit the links”…

    Yes, that’s one of the big problems… You can satisfy Nyquist in the time domain or in the geographic domain, but not in both at the same time… Then season that with all the environmental changes and instrumentation changes that happen in 200 years…

    My favorite is the very long life station that was the airport used in the Berlin Air Lift. Started life as a grassy marching field for military drills. Became a grass airport, then a major airport, then a Jet Age Hub – and now converted to a shopping mall. Think any of those are comparable?

    Think a major jet port might be a degree warmer than a grass field in a rural area?

  10. Simon D with a thermocouple one needs an additional thermometer to measure the ambient temperature where the voltage is being measured. A thermocouple measures the difference from the point at the end of thermocouple where the two different wires are joined (eg inside a furnace or kiln) and the temperature where the voltage is measured (eg outside the furnace or kiln in an instrument case). If the thermocouple and the instrument case are both in ambient air in the same location one should get zero. In most high temperature applications the ambient temperature is assumed (eg 25C). I suggest that the electronic thermometers are resistance thermometers -the resistance changes with temperature. However, each instrument needs to be calibrated in situ. They need to be powered (eg a battery) which can result in errors. WiFi can also give errors particularly with low signal strength. Response time is a big issue with electronic instruments. In industrial applications thermometers are sheathed for protection (wear, corrosion etc). This increases the response time but on the other hand for control the response can not be too rapid. I believe that the World Meteorological organisation requires one or two minutes of averaging for signal transmission. I believe in Australia there is no averaging and surges of about 10 secs. go into the record (eg hot air from a passing jet at an airport) BOM are continually claiming record high temperatures based on false signals in cities and airports.

  11. Simon Derricutt says:

    cementafriend – yep, I didn’t think about that, and of course they generally use Pt resistance thermometry which doesn’t need a reference. Those drift with age, and will be subject to contact problems. There, we’d need to know when they are recalibrated, since the recorded temperature may show a step-change at that point in the record.

    For the Wifi transmissions, they should be error-corrected and checked, though it’s possible (though pretty dumb) to use simpler transmission protocols. Might be a problem, but I wouldn’t expect it. Short temperature excursions can come from passing jets, idling vehicles, air conditioning etc., and each location would need to be verified that such things can’t happen.

    Measuring temperature accurately and reliably for a long-term comparison isn’t that easy, and I’d be somewhat surprised if the basic accuracy is much better than 0.5°C over decades.

  12. H.R. says:

    Another thing about chasing after some mystical magical one number global average temperature (GAT) is that temperature is not climate. The question I’d be asking regarding “Climate Change” is in how many places has the Koppen climate classification changed?

    Just based on my impressions of indoctrinated and propagandized people demanding something be done about “Climate Change,” the underlying FUD factor is still catastrophic man-made global warming caused by CO2. SO… we chase temperatures in order to “prove” global warming.”

    What E.M. is doing is showing how the record is being distorted in favor of the CAGW narrative, and properly examining the temperature portion of the Koppen classification of climate where each of the recording stations is located, i.e., given this thermometer in this location, what are the temperature trends at this location?

    It always amazes me that most thinking people will readily acknowledge that there is no Global Climate and a Global Climate cannot be represented by the average temperature of the Earth, and then go right back to arguing about what is the correct number for the average global temperature as though it actually does represent the Earth’s climate.

    The GEBs through their political magicians, backed by lackey scientists, have been totally successful in getting most of the Western world to “See? Look at this hand. Nothing in it but a Global Average Temperature. Nothing up my sleeve. Now watch carefully. Focus… watch… watch…focus… watch…” and that’s the whole act. Meanwhile, with the other hand, they are picking the World’s pockets on a wholesale basis and implementing otherwise unpalatable curtailments on individual freedoms where the end result will be global serfdom, assuming there are any serfs left.
    .
    .
    Now the counterargument is that GAT is important and if temperatures do rise or drop on a global basis, and that includes the far more important ocean heat content (about which we have no clue whatsoever!), then the Koppen classifications of regions everywhere will necessarily change.

    Again, E.M. (and others) are pointing out the miserable job being done to actually arrive at a GAT and that anyhow, current GAT estimates are more driven to support a political narrative than to attempt to find a useful number.

    What to do, what to do? In my barely competent, ignorance laced, simple-minded – but humble! – opinion, I think we should set up stations to monitor the components of the Koppen classifications in thoughtfully selected regions and then infer what the GAT trends might be. For the Continental U.S., only one or two stations might need to be placed in each state.

    Now a boatload of meteorologists have actually been collecting all the local constituent data of the Koppen classifications for their area for quite some time. However, all I see is money being spent on worthless computer models designed to support the paymasters’ chosen narrative. What I’d like to see instead is money spent on gathering up the data which comprises a particular climate type and then an effort to create some understanding of what is going on and what may transpire in a particular region.

    “But, but… H.R.! The climate models already do that. You plug in the CO2 level and you get the output of what will happen in various regions; rainfall, temperature, etc.”

    No they don’t. We find out from time to time that this or that or the other is not included in “the models” so they can’t possibly predict project what will happen to the climate of a particular region. Roger Pielke Sr. has repeatedly pointed out that regional climate models cannot (reasonably) accurately model regional climate; forget about global models.

    So for anyone who has hung in there to this point, I think that if we want to know what will change in the climate in a particular region, complete climate data for the region should be analyzed and after that is understood, stitched together with adjacent regions. After success on a regional basis, well, that’s all you need to know, right?
    .
    .
    .
    Note: Way too much left has been left out in the babbling above to inform readers of all the points I’ve contemplated in greater depth than what I’ve presented, and all of what is actually being done to study climate, which is also more complex than I’ve represented, but it should be enough to get my two general points across; we’re going about things bass ackwards and E.M. is doing his part to reveal the fools errand and trickery involved in producing a GAT.

  13. E.M.Smith says:

    @HR: Well, you pegged me :-)

    BTW, we already have fully integrated “devices” measuring each climate region. They integrate peak, minimum and average temps along with frost and wind (drying and velocity) along with water a sunshine. Fire prevalence too..

    There are still digger pines in the foothills, Douglas fir in the Sierra Nevada, saguaro cactus in the Sonora desert, ash trees in Oregon, etc etc. That is why I used “dumber than a tomato” to describe GIStemp. It said we are warmer, but I was still having trouble getting tomatoes to set fruit. Had night temps been over 50 F earlier in the season I would have more tomatoes. I had less… it was cooler.

    So one simple way to track things is just map what plants grow where. But watch out for maps based on the “temperature record” as it is corrupted. Look at reports of success and failure. Especially at the edges. Oranges grow well in southern California. Marginally in the Central Valley. The limit is about Oroville (of dam fame…)

    So when Oregon starts exporting oranges, then you have something…

  14. H.R. says:

    E.M.: “BTW, we already have fully integrated “devices” measuring each climate region.”

    Yes, I was aware there are some such stations, probably set up and maintained by every TV station there is as well as some by the NWS. But I don’t see “Big Climate Change” making use of them in any significant effort. The money all seems to be largely going into global climate models (General Circulation Models)..

    And your point about tomatoes, which you’ve mentioned before, was actually one of those “points I’ve contemplated in greater depth than what I’ve presented” in indicting the current state of “Big Climate Science.” If you stayed in your current location for 20 more years and found you had to permanently change to a few degrees more cold tolerant tomato, that would tell us more than any thermometer.

    By far, the best indicator of climate is what grows where. When we have more lengthy records of what grows where and when, then we will see meaningful climate trends. Heck! A good project right now would be to catalogue the changes in information on the back of seed packets over the years and look for changes. The recent discussion on veggie plants in the “Today I Started My Garden” thread is more useful for developing public policy than the GCMs.

    Anyhow, I see you got the general point I was trying to make about the importance of studying regional climate and why (so we don’t all starve!) over studying some meaningless single global number that is nearly impossible to represent accurately, particularly as we currently go about it.

    I forgot to mention that it is entirely possible for dramatic regional changes in climate to occur and yet the GAT might not change a whit. That’s another big reason why the focus on regional climates is much more important than some mythical GAT.

  15. Pingback: GHCN v3.3 Continents by Season | Musings from the Chiefio

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