Derivative of Integral Chaos is AGW

Having gotten the mathematics mood warmed up reading “Is God a Mathematician?”, I started pondering the mathematical nature of Climate, Weather, and Temperatures. This has taken a few days…

Starting with temperatures

Temperatures are a point property. They are a single point at a moment in time. An instantaneous event in time and space for a single property. They are an intensive property and the average of two temperatures is meaningless to heat or energy flow. ( You must know the mass and specific heats to have an extensive property with which to work.) Yet the first thing done with the temperatures is to average the min and max to get a mean, not even allowing for the non-sine wave nature of temperature change over the day.

Weather – More than Temperatures

Weather happens at a point in time, and a place in space, but weather events are spread over many properties.

It may be raining one minute and not the next, or raining on one side of the street and sunny on the other. A single snowflake can fall… But weather incorporates temperatures. It also heavily incorporates the water cycles of the planet. Rain, snow, hail, sleet, dry deserts and saturated dew points. And wind. The movement of the air, fast or slow, vertical or horizontal in any direction. Either straight line or in circles. Density changes and even changes in composition (such as particulates). Upslope and downslope winds can drastically change temperatures with no change of heat content of the air.

Chinook winds have been observed to raise winter temperature, often from below −20°C (−4°F) to as high as 10°C to 20°C (50°F to 68°F) for a few hours or days.

So for each area on our climate surface, we ought to be taking the weather and integrating it.

Integrating in one dimention

Integrating in one dimention

But in both space and time. Each spot on our map ought to have a sample series under it so that we can calculate that surface that flows over all the spots on the map, and over all the time of study. The accuracy of our integral depends critically on the size of those samples. Yet for most of space and time we have no samples and instead use what few we have (making for a very large spot under the curve… and a very very poor model of the curved surface.)

What is “climate”?

Koppen Climate Zones

Koppen Climate Zones

Original larger sized image

To get climate, we take those instances of weather and we integrate them over time and over space.

The “climate scientists” seem to like using the 30 year average of weather as climate, but that is a very broken definition. There are known 60 year quasi-periodic functions in weather, such as the PDO, so any 30 year average will be constantly finding bogus ‘trends’ as that cycle turns. A better definition of climate is the one used by geologists and geographers. See: http://en.wikipedia.org/wiki/Köppen_climate_classification for a review of one of the systems.

Such zones do not change over a 30 year period (the Sahara has been a desert for a while now, though many thousands of years ago it was wet). So “climate science” is broken in it’s core definitions… The Mediterranean has been a “Mediterranean Climate Zone” for thousands of years, even during the Little Ice Age and the Roman Optimum / Warm Period, and will continue to be for thousands of years to come. But that is what we are stuck with as a “climate science” definition for the moment. Just remember that real climate is based on a very very long time base for the integration of weather. Yet “climate scientists” use 30 years instead of 3,000 years.

A “Desert” may have snow or a drenching rain, but over a significant area it has insufficient rain to exceed evaporation. A “Rain Forest” can have a dead dry day, but integrated over time it rains far more than not, and over it’s whole area. A desert can have a pond in it and a swamp can have a dry rock.

So to find the climate of an area, we must take the weather and integrate it over time and over space. Preferably a very very long time.

But then, to get “climate change” we want the first derivative of climate over time…

So if we integrate weather (over too short a time base) then take the derivative of that and find changes over time we have found exactly what again? Have we not found simply that “weather changes”? Both on large scales and on small?

But it’s worse than that!

Weather is chaotic. What is the result of doing an integration on a chaotic domain? Is that not itself a chaotic result? And when we look at climate, we do find it to be chaotic. Just on a longer time scale.

Ice Age Changes

Ice Age Changes

In this chart you can see how much things change during a glacial period and in a fairly chaotic way. The present is that small surprising shelf of stability on the far left. It includes all the ‘extreme’ changes of weather during such periods as the Roman Optimum, the Little Ice Age, and the present Modern Optimum. Our “chaos” is astounding stability in comparison to longer term climate states.

There are Ice Epochs that come and go, snowball earth and tropical jungle dinosaur earth. The present Ice Age earth, with our recent Interglacial Optimum anomaly, but not quite the same as other glacials and interglacials. (There is that nagging problem of the shift from a 40,000 year glacial periodicity to a 100,000 year periodicity, for example, and that the periods are not quite predictable…) Or look during the glaciations, and you find jagged rises and falls of temperatures and ice levels. Climate is every bit as chaotic as weather, just on a different time scale.

All in all, it looks to me like a Fractal function. There are hot spots and cold spots, and hot times and cold times, and sometimes they are mixed in odd ways. But with an overall pattern that LOOKS sort of regular with repeating bits, but never quite the same. Very much like the patterns you see in coastal patterns and mountain ranges, but with peaks and valleys of temperatures and rainfall rather than height or ‘ruggedness’ of the shore.

Temperature Patterns in the SouthWest USA

Temperature Patterns in the SouthWest USA

So what is the integral of a fractal function? And does not the slope of a tangent to a fractal surface (derivative) depend entirely on where you measure it AND the size of the ruler you use?

A coastline is of indeterminant length It is one length if measured with a yard stick, a different length if measured with a millimeter ruler, and yet another length if measured with a speed boat going from one port to another as a sort of ‘unit ruler’.

Thus, the coastline paradox.

Britain Coastline at 100 km

Britain Coastline at 100 km

Britain  Coastline at 50 km

Britain Coastline at 50 km

So we take our fractal weather and measure it at selected odd points, then measure it at other selected odd points in different times, then integrate that, then take the derivative of the integral and that slope means exactly what again?

And we keep changing the size of our “ruler”… (Station drops matter. Especially in a fractal domain).

Take a moment to think about that, please. It is a very important point. We keep changing the size of the ruler being used to measure a fractal surface. Then finding that the result changes.

It Gets Worse

But it is even worse than that. Weather is composed of liquid water, water vapor, solid water, wind and mass transfers, air density changes. Yet we chose to use only ONE of those, temperature, as a sort of a broken proxy for weather. Vast quantities of heat can move with no change of temperature, yet it is temperature we measure.

So now we are not actually measuring weather and integrating it, we are measuring only one aspect of weather and ignoring things like dew point, humidity changes, tons of snowfall as water freezes and more tons of snow melt at constant temperatures. And we take this one broken proxy for weather and treat it as the foundation of “Climate Change” and look for that proxy to tell us what is going on in climate.

Yet even here there is more breakage.

The temperatures are measured on a grid of cells that is far too sparse to capture the true state of the landscape. Look at that map of the Southwest again. California had 4 stations in GHCN for 2009, all on the beach, with 3 in
the LA basin and one in San Francisco. Not nearly enough to capture the texture of the state. In 2009 in GHCN there are about 1200 stations for the whole globe. Yet ‘microclimates’ can be dramatically divergent in a range of miles, or even yards. (Look at those hot spots in Texas cities, for example. Or, as temperatures really are fractal, in millimeters… I’ve had warm black rock in the sun next to cold snow… and frozen snowflakes on a warm tongue…)

We make the assumption that the air a few feet over the ground will somehow act to do an integration of this fractal property over a spacial grid measured in hundreds (or sometimes thousands) of miles or kilometers. And we know that it can not, as it can not even make the snow and rock temperatures match a few feet or meters apart. Stations located at airports (as most are now) can be 5 F or more warmer than nearby well sited stations, so the air is not doing a very good averaging nor integration over space.

Mississippi River in Minnesota in Infrared

Mississippi River in Minnesota in Infrared

Does that look uniform to you?

So we take this broken spacial integration of the point property of temperature, and treat it as a proxy for the point weather. Then to make the integration over time, we average the data. We take a min / max that may or may not have consistent precision, then use a months worth of each to make an average temperature ‘mean’ for a month. In some cases, missing data is ‘made up’ via using ‘nearby’ stations or the averages of them to create missing items. This averaging of nearby ASOS stations is called “quality control”. But quality of what? Then programs like GIStemp take those ‘monthly means’ and via more averaging functions make ‘homogenizing” adjustments. Filling in more missing data, blending some locations with others, and generally smearing the data around to where there are none.

Does sporadic semi-random ironing flat of a poorly sampled fractal surface make for a good integral?

Does it get better if you constantly change what gets ironed flat and what is left intact?

Averaging is a pretty poor way to get the integral over space and time for a highly variable and chaotic natural process, even if done on a proxy for that process (or especially so?) and even if done on the variance from a baseline instead of on the actual datum. Add in the fact that which particular geographic points are being averaged and blended, in any one ‘step’ of our ersatz integral, change constantly (and in their own chaotic way) and I’m beginning to have a distrust that the ‘answer’ really means anything, anything at all.

But wait, there’s more….

From Ersatz Weather Proxy to Climate Change

These poorly measured, averaged, homogenized, and blended temperatures are then turned into “Grid Box” values, and these are compared over long periods of time. A 30 year “baseline” value is found (via more averaging…) and the present yearly value is calculated (via more averaging but using different stations in different geographic locations) and these two are compared to create a “Change Over Time” proxy for the derivative of climate: The Change of Climate Over Time: dC/dt.

But is there really any relationship between dC/dt and the average of temperatures, re-averaged, offset, blended, and summed over time, then differenced from a different average of summed re-averaged, offset and blended temperatures ?

We’re missing all of the water cycle. All of the biological cycle of plant growth and death, evapotranspiration, all of the ocean turnover and heat storage / release processes, all of the ice cap cycles. But we are getting land use changes unrelated to climate. Is a 40 C desert the same as a 40 C rain forest? A 40 C airport in the sun? Is a 0 C desert the same as a 0 C ice cap?

They are treated as the same in the way “climate change” is calculated in programs like GIStemp.

No PDO, no AMO, no Gulf Stream. No hurricanes moving megatons of energy to the top of the sky (hurricanes embody as much energy as atom bombs, but we ignore that, and all the mass flow of water and air…)

Gulf Stream

Gulf Stream

But we have this proxy for weather, calculated from a bad method applied to incomplete data in a sparse field using a method far removed from integration; then we use an equally bad way to find a poor derivative of it, and that is supposed to be a proxy for dC/dt ?

What purpose was served by first integrating then taking a derivative anyway? All you will do is build up and amplify errors and incompatibilities from the two odd methods (proxy methods) used. Would it not be more honest to admit that averaging averages of offsets of averages, then differencing them, makes for a very poor first derivative of anything? And if you are going to do that, why integrate over both space and time first, then take a derivative over only time. Why not just integrate over space and be done?

And it means exactly what again? And to 1/100 C of meaning?

Conclusion

Looked at in this light, the whole process of using temperatures to find “climate change” is just so ersatz and lacking in a rational philosophical basis (in the sense of a ‘philosophy of mathematics’). It’s just an arithmetic game with large error bands and constructed in a clumsy way; and with no relationship to actual climate.

I wouldn’t even make stew with that level of circumlocution and poor choice of ingredients and methods.

Postscript

For purposes of illustration, here is a Mandelbrot or two to contemplate:

Mandelbrot Image

Mandelbrot Image

And at another scale it looks very similar, yet far different at the same time.

A particularly interesting scale

A particularly interesting scale

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, Favorites and tagged , . Bookmark the permalink.

25 Responses to Derivative of Integral Chaos is AGW

  1. Pingback: E.M Smith: Derivative of Integral Chaos is AGW « Co2fan's Blog

  2. Verity Jones says:

    Funny you should mention fractals and that UK coastline example. I wrote ‘Fractals?’ on a page on Friday evening when working though a few ideas about climate, and the thing that brought it to my mind was a programme I had seen the day before about measuring the coastline of Britain. Wierd eh?

    That is a fantastic picture of the Gulf Stream, even if if doesn’t reflect actual temperatures.

    “It’s just an arithmetic game with large error bands and constructed in a clumsy way; and with no relationship to actual climate.”

    So true. Sigh.

  3. Mooloo says:

    Show me that a coastline is fractal. You say it is, but can you prove it? Perhaps it is merely an infinite sequence with r < 1, which means that it CAN be summed for length.

    Moreover, merely asserting that taking averages of temperatures is a poor method without proposing a workable better one is a cop-out of all attempts to understand climate. Give us a better method that we can implement within reasonable cost and political limits.

    I am hugely sceptical of AGW, and I know that the warmists need to stop pretending their methods are robust, but until you show a workable better system it's a waste complaining. They will work with what they have.

    BTW how do you work with economic statistics, given their similar indirect relationship to anything real? Sometimes you can only work with what you have.

  4. Dusty Rhodes says:

    Congratulations Cheifio on an excellent and thought provoking essay.

    I recognise the meaninglessness of the ‘Global Temperature’ as an indicator of climate change however I’m curious to know whether the measured temperatures used to determine the global temperature are dry or wet bulb values.

    Is the type of climate (Köppen Climate Classification System) incorporated into the algorithms used to interpolate/extrapolate temperatures in the empty gridded squares?

    Any ideas?

  5. RK says:

    To Mooloo, Wikipedia traced fractal coastline to a 1967 by Mandelbrot. Reference is cited here: http://en.wikipedia.org/wiki/How_Long_Is_the_Coast_of_Britain%3F_Statistical_Self-Similarity_and_Fractional_Dimension.

  6. Rod Smith says:

    Bravo! Well said. Absolutely on-target. I couldn’t agree more.

  7. E.M.Smith says:

    Mooloo, it’s pretty obvious that taking the average of the data points under a curve is a poorer version of the integral than actually doing the integration.

    For example, take a semicircle. The average of the areas under the curve will be a straight line. Kind of a long ways away from a curve of semicircular form… It gets worse, rather than better, as you move to shapes like parabolic or hyperbolic… Though you could make a case for log decay curves of high value approaching a straight line. So we take that semicircle, integrate it to a straight line, then take the offset between two such straight lines as the derivative?

    So as soon as we know what the actual function is, and what shape the climate curve has, then we can decide if using an average to represent it is ‘reasonable’. Until then, it’s best to consider it unreasonable (as we have no idea what error band to assign…) And one need not have a good or better way to make a space ship before one says that a Ford Fiesta with a box of dynamite in the trunk is a bad one… it is sufficient to simply show that one will blow up on theoretical grounds…

    Per fractals: As pointed out by RK, that’s pretty well shown in the literature. Just about any google of ‘coastline fractal’ will turn up more than a years worth of things to read.

    “About 703,000 results”

    Finally, per economic data:

    It’s a royal pain in the ass to work with it. Stock prices also look like a fractal. (And no, I’ve not done the work needed to prove that they are, but it sure acts like and looks like one.) It’s very very hard to find methods to use with stock data that yield valid predictions for more than short periods of time. You can have local predictive power, then hit an inflection point, and all bets are off (literally!)

    So what I do is use that as a ‘feature’. I fix my time frame, and make predictions inside that time scope. Then watch for the violation of that regime knowing full well it will happen and that the prediction comes with a shelf life.

    Now if the AGW fanatics want to put a 5 year shelf life on their “Doom and Gloom For All” predictions, I’m ok with them doing flakey mathematics and using unsupportable accuracy and precision. Oh, and they would need to announce that as soon as warming changed to cooling, the whole AGW regime was over and we were in Global Cooling. Kind of like what has happened since 1998…

    In fact, that is in some ways diagnostic of a fractal. You get local predictive power inside one scale of observation, but only for a while, and eventually hit an excursion point to a new pattern. Stare at a mandelbrot for while and this becomes pretty clear. I’ve added one to the posting above.

    I probably ought to add that mountains and rivers are also known to be fractal features. Given that so much of terrain is known to be fractal, it would be reasonable to expect that the weather which is shaped by those features would also be a fractal structure. Yeah, would be nice to have a mathematical proof, but I’m willing to use it as a working assumption until it can be proven. A google of “fractal weather” gives “About 613,000 results” so I’m not the only one thinking along those lines.

  8. Chuckles says:

    Now look what you’ve done, they’re going out to prove it –

    http://www.mercurynews.com/news/ci_15541285?nclick_check=1

  9. oldtimer says:

    The sudden variability of weather was brought home to me on the only trip I have ever made to Saudi Arabia. On a weekend trip out of Jeddah (on the coast) I encountered variously dust, heat, torrential rain, hailstones and highly variable changes in temperature. This all occurred within a few hours on the same day. It was, for me, an entirely unexpected phenomenon.

    On the subject of fractals, I believe that the fern leaf, that is the symbol of New Zealand, is a good example of a fractal in the natural world.

  10. j ferguson says:

    From Chuckles’ URL

    “… Ocean Protection Council, a state agency in Oakland..” California, of course.

    I wonder if there is a Council for the Protection of the Universe?

    I would have thought they would be more interested in the dry side of the coast.

  11. E.M.Smith says:

    Oakland: Their mayor is Jerry Brown AKA “Governor Moonbeam”… kind of covers it.

    Oh, and he has national aspirations so expect them to be all over things that a left wing loon (as opposed to a right wing nut) would vote for on the national level.

    Nevermind that they are going bankrupt and will have trouble paying the police and fire departments …

    http://articles.sfgate.com/2009-06-09/bay-area/17209200_1_property-tax-budget-shortfall-year-s-property-tax-revenues

    Forget stupid things like fire and police and potholes; embrace Gaia and have positive energy!!! /sarcoff>

    Yeah, it’s “California Disease”…

  12. j ferguson says:

    E.M.
    I think I would be really fried if my local taxing body took on the troubles of the world.

    It’s clear that those folks have no sensitivity to the absurdity of their council’s name.

  13. Chuckles says:

    @oldtimer,
    Yes, I hit weather like that once in Namibia; wind, dust and rain cooperating so that it was raining mud. Some of the most unpleasant driving I’ve ever done.

    @j ferguson,
    To them the name is not absurd, I’m sure they mean it, and not in a good way.
    Always remember,

    1. They have NO sense of humour.
    2. They care, you don’t. You lose.

    The article is very close to drivel, obviously a regurgitated press release or similar.
    It rhapsodises about the resolution and ‘sharpness’ of the images, with a 3 foot sample interval. It can GASP! sometimes even resolve individual boulders and telephone poles.
    I’d say that if you want to resolve boulders and telephone poles, we have this really neat idea. It’s called ‘aerial photography.’ Lasers, not so good.

    There is absolutely no understanding that they appear to be producing a digital elevation model, or of measurement error. Or Nyquist. If they actually want a digital terrain model, rather than an elevation model, they REALLY don’t want to be resolving boulders and telephone poles.
    LIDAR is a great system, but it’s hardly new.
    I worked on some surveys 8-10 years ago and it produces this gigantic cloud of data points, floating in space. This has to be referenced and corrected to known ground control points, and that is a right b*tch to do. The processing would make a saint swear.
    But it will hopefully be a better model than the GSM’s. I love the revelation that laser infrared ‘doesn’t penetrate water very well.’ Right up there with ‘glides like a smooth brick.’

  14. E.M.Smith says:

    I was in a ‘mud storm’ in Phoenix once. Had a dust storm blow through, then rain. A real mess. Wouldn’t have thought it possible if I’d not been in it.

    I’m constantly amazed at the degree to which things I learned in high school chemistry and physics are completely ignored (or worse, misunderstood) by the AGW folks.

    Intensive variables treated as extensive.
    Heat confounded with temperature.
    No error banding for each step of calculation.
    CO2 “cause” following warming “effect”.

    and then things learned after high school, like Nyquist, too.

    So somehow I’m not surprised that they didn’t realize that water is more opaque than air at some colors…

    I’m fairly sure this mathematics discussion will be too abstruse for most folks, and I’m certain it will be completely over the head of the AGW crowd. Mathematics is not their strong point.

  15. Paul Vaughan says:

    “Does sporadic semi-random ironing flat of a poorly sampled fractal surface make for a good integral?”

    Good Q — & let’s not forget turbulence & backeddies…

  16. E.M.Smith says:

    OK, I won’t forget them. But perhaps you could elaborate on why I ought to remember them?

    (It’s early and I’ve not had coffee yet, so maybe it will be more obvious after coffee…)

  17. Ken McMurtrie says:

    Hi EM,
    Enjoy all your musings and impressive analyses and comments.
    This topic seems the most recent relating to AGM so wanted to point out to you that “they” are not lying down, just continuing to lie? Do you agree?
    I refer to an Australian media release:
    http://www.abc.net.au/news/stories/2010/07/29/2967433.htm?section=justin
    “A report on the world’s climate has confirmed that 2009 was one of Australia’s hottest years on record and provides more evidence of global warming.
    etc….”
    The report sounded impressive initially but I realised that it was compiled by none other than
    “the US National Oceanic and Atmospheric Association” and was based on
    ” all relevant data and update information from the Intergovernmental Panel of Climate Change released three years ago.”
    Do you agree with me that this report deserves to be categorised as a continuation of unfounded, unscientific or incorrect propaganda?

  18. E.M.Smith says:

    @Ken:

    Well, it certainly sounds like more “same old same old”…

    But I’m not in the habit of judging something I’ve not seen for myself, so I’ll be a bit more ‘reserved’.

    To me, it could just as easily be just the usual inertia of human nature. Folks stake out a position, then keep pushing it, even if the facts on the ground change.

    And the AGW True Believers do seem to believe what they say.

    So I’m stuck with a Hanlon’s Razor problem when it comes to ‘talking dirt” about them or attributing motivation. I simply can not know what goes on inside some other persons head. And “Never attribute to Malice that which is adequately explained by stupidity.” comes to mind.

    So could continuing to hawk AGW after it stopped in 1998? Well, it COULD just be stupidity. And believing in the broken video game output of the temperature series codes? Very few folks are in a position to validate them or even understand them, including the makers. (I see no evidence of a QA suite nor of a validation suite.) So they could just be “Sucking their own exhaust” and “Believing their own BS” and scaring themselves with their own horror stories. They could be that stupid….

    So is it propaganda (intentional)?
    Or is it chicken little (self deception)?

    Hard to say. But it is looking more and more like stupidity has a very high hurdle to climb to cover that much stupidity…

    As I’ve been known to say, though:

    “Intelligence is limited, but stupidity knows no bounds. -E.M.Smith”

    So maybe there IS enough after all.

    FWIW, I’ve been around media enough to know that they will keep on running what are clearly urban legends LONG after the truth is gone. They must fill the volume with something and the trite trod and shopworn story is easy to write. So they do.

    Sporadically you’ll see the story of this young child dying of cancer asking that a get-well card be sent to him in hospital. Problem is, that particular child was cured some decade plus ago and would really just like the cards to stop… He’s a grown man now… So there is quite a lot of stupidity available for any given news story.

    (And I saw the guy on a TV story about urban legends with before and after photos, so I know that the story of him being cured is itself not an urban legend ;-)

    What I’m more comfortable speaking to is the question of veracity. This is NOT the warmest anything. Ever. It’s just about dead normal. It’s been way hotter in the far distant past. It was hotter in the 1800’s but not dramatically so. And it’s more or less normal now, but a tad cool in much of the world. That the STORY of “hottest whatever since whenever” is flat out wrong is pretty clear.

    As to them “just quitting”. Well, I’ve seen enough FADS to know that they never really end. Just the volume goes out of them. You can still buy a hula hoop, but the fad of the early ’50s where everyone had to have a half dozen has thankfully died. Neru jackets are still available, but no longer trendy. And beehive hair-doo’s can still be seen from time to time… So no. I don’t expect them to just say “never mind” and disappear. I expect it to be a long slow lingering death as the topic ceases to gain “Oh Yes!” responses at cocktail parties and gets more “Oh Groan” responses. Like when Da Pres got laughed at during the State of the Union address to congress when he mentioned global warming.

    I give it about 3 years to become un-trendy. Unfortunately, I think it will take a decade and a New Little Ice Age to kill it off. And sadly, I think that’s what we’re going to get.

    Could it be intentional propaganda? Sure. But without evidence as to motivation, the best I can say is that it sure LOOKS like propaganda…. or stupidity… and that being based on 3 year old ‘evidence’ is a bit daft.

  19. Ken McMurtrie says:

    I appreciate your comments, EM.
    I guess I was more interested in the scientific side, whether they may have some new legitimate evidence to back up their claims, an area that you have well and truly in your grasp.
    I too am not that much into rubbishing them, I just want truth and justice, my usual “hobbyhorse”.

  20. E.M.Smith says:

    @Ken:

    Well my opinion is that many of the folks involved are producing a broken product and that the facts on the ground point to an agenda driven bias in the ‘research’ they are doing.

    I can’t tell if it is from the “true believer” pushing a personal belief / world view or from simple greed (getting more funding comes with each “worse than we thought”…) But I’m no sure that type of distinction matters. Fraud of which flavor? Driven by greed or stupidity?

    It’s very easy for folks to look for something and see it. Look at clouds for a while and all sorts of things will be “seen”. IMHO, these folks are mostly indulging in a very complicated kind of “cloud watching” but with a feedback loop through their software / adjustment codes.

    So they see “warming” and then look at the raw data and see ways to “clarify” what they see. That’s a broken behaviour, but it’s what they do.

    One example. Under a prior posting on “QA or Tossing Data, you decide” I pointed out that the QA process for the USHCN data uses a fixed bandwidth. (IIRC it was 10 C) for the bandpass. Since a tropical island rarely gets more than 1 or 2 C variation it will substantially NEVER have a valid value ‘tosses’ by that filter. Yet a far northern area can easily have 10 C of variance. And winter lows can vary down more than summer highs can vary up. So more valid winter cold days will be tossed than valid summer highs.

    It’s a “sounds reasonable” filter that is, in fact, biased to tossing cold days

    Repeat a few dozen times in other codes and it all adds up…

    So I think they are “finding” what they look for.

    As to if that is agenda driven propaganda vs stupidity; I don’t know that it matters much… I’d not want to be in either category…

  21. JPeden says:

    Mooloo:

    They [ipcc Climate Scientists] will work with what they have.

    Exactly that is an astoundingly obvious critical defect of their way of doing their “science”, right from the beginning.

    That is, it made no scientific sense for them to proceed if they were not going to design a system to adequately measure what they wanted to measure in the first place – completely apart from the question of the physical meaning of ‘what they wanted to measure’.

    But proceed they did anyway, which then assured that they would end up with exactly nothing – except, of course, for the bizarre way they did the measuring.

  22. E.M.Smith says:

    @JPeden: You got it. I am fulfilled. One down, 6 billion to go…

    They start from a borken premise and find broken results, and sing their own high praises. Yet it all is based on less than a Gilbert and Sullivan “opera”…. and now to confound them “we Have A Solar Major Minima” … If only the real world were as entertaining… no, wait, it IS!

  23. John F. Hultquist says:

    Very well done. Thanks.

    Finally someone recognizes the real meaning of climate! Thanks for highlighting the Köppen-Geiger map. I’ve pointed others to this body of research (initially based on vegetation, a natural integrator) but the CO2-temperature thing has derailed rational thought.

    The 30-year averages have been used as “normal” because a person (again using your term) integrates a notion of weather (not climate) from about ages 10 on and “remembers” what things were like. Thus, what the weather was like in the 1880s is not relevant to me – a very long record is of little personal use. Having said that, the 30 year business was and is standardize for reporting purposes with the stipulation that it is recalculated only after a year that ends in zero. So, in 2011 all these numbers presented as ‘normal’ should be renewed.

    If you plan on a wider distribution of this article there is a spelling change you should make. Namely, under the IR photo of Minnesota you use the term ‘spacial’ which is usually considered a variant of ‘spatial’ from the Latin spatium. There could be a national bias about this about which I am not aware but the spelling checker in MS-Word prefers spatial.

  24. E.M.Smith says:

    You are most welcome. I do think the ‘math part’ matters more than is being recognized. But most folks are not keen on abstruse math issues.

    And that “30 years makes a climate” is just so broken at the definitional level. It is the basic lie on which the rest is based. It’s not climate, its just 30 year weather cycles. A very critical point. Getting ‘worked up’ about the weather changing is just not very easy to sell…

    Per spacial vs spatial. I straddle 2 Englishes and sometimes 3. Standard American is what my Dad spoke, while my Mum was English. I also grew up immersed in Spanglish and that, ya-know, like California stuff folks talk here… It’s lucky I can keep any of it straight. I actually spent a minute or two trying to decide which was right. Then which was American. Then gave up and just picked one. The spell checker in WordPress likes them both. (And I think I managed to set British spelling in my editor, so it won’t help much ;-)

    Google finds them both and finds dictionary entries for both (though with a 3/72 ratio of spacial to spatial. At that point I quit caring and picked one. I decided to support the underdog (even though I’m not sure if this is the British or Americanism or some other ism…)

    Yes, I really do that kind of process when a word might go either way. Silly, but it’s what I do. I also like to use behaviour vs behavior though wordpress doesn’t like it and don’t mind colour at all either. Then again, mod and Maud sound different to me (thanks Mom…) even though Americans typically can’t hear the ‘caudal au’ (or something that sounded like that when my linguistics teacher said it…)

    So in the end I’m from both sides of the English divide and neither. Heck, half the time I spell things phonetically when I feel like it. I love old writings partly just for the liberty they felt from, the modern strictures of spelling and grammar. And sometimes I start a sentence with “and” just because I want too…

    So if this ever gets formal distribution somewhere I’m sure some anal retentive over trained grammarian with an English degree will have lots of things they want to change about it. Swapping a c for a t being the least of them. Until then, I’m most likely to just pick something I like and move on. Heck, if I’ve got a couple of chances to use a bi word, I’ll often swap back and forth between them just because it’s fun and I can. So you are likely to find me freely intermingling the two spacial spatial words. And I’d not be surprised if sometimes I even toss in a spactial just for fun ;-)

    Languages are never static, and never fully defined. So why ought I to be?

  25. P.G. Sharrow says:

    You do an excelent job of creating clear word pictures. A pleasure to read. That is all that counts. pg

Comments are closed.