Guest Post by Dr. Robert Brown,
Physics Dept. Duke University [elevated from comments]
Dr. Brown mentions “global temperature” several times. I’d like to know what he thinks of this.
Dr. Brown thinks that this is a very nice piece of work, and is precisely the reason that he said that anybody who claims to know the annualized average temperature of the Earth, or the Ocean, to 0.05 K is, as the saying goes, full of [snip] up to their eyebrows.
What I think one can define is an average “Global Temperature” — noting well the quotes — by following some fixed and consistent rule that goes from a set of data to a result. For example, the scheme that is used to go from satellite data to the UAH lower troposphere temperature. This scheme almost certainly does not return “the average Global Temperature of the Earth” in degrees absolute as something that reliably represents the coarse-grain averaged temperature of (say) the lowest 5 kilometers of the air column, especially not the air column as its height varies over an irregular terrain that is itself sometimes higher than 5 kilometers. It does, however, return something that is likely to be close to what this average would be if one could sample and compute it, and one at least hopes that the two would co-vary monotonically most of the time.
The accuracy of the measure is very likely not even 1K (IMO, others may disagree) where accuracy is 
Things are not better for (land) surface measurements — they are worse. There the actual data is (again, in my opinion) hopelessly corrupted by confounding phenomena and the measurement errors are profound. Worse, the measurement errors tend to have a variable monotonic bias compared to the mythical “true average surface Global Temperature” one wishes to measure.
One is in trouble from the very beginning. The Moon has no atmosphere, so its “global average temperature” can be defined without worrying about measuring its temperature at all. When one wishes to speak of the surface temperature at a given point, what does one use as a definition? Is it the temperature an actual high precision thermometer would read (say) 1 cm below the surface at that point? 5 mm? 1 mm? 1 meter? All of these would almost certainly yield different results, results that depend on things like the albedo and emissivity of the point on the surface, the heat capacity and thermal conductivity of the surface matter, the latitude. Is it the “blackbody” temperature of the surface (the inferred temperature of the surface determined by measuring the outgoing full spectrum of radiated light)?
Even inferring the temperature from the latter — probably the one that is most relevant to an airless open system’s average state — is not trivial, because the surface albedo varies, the emissivity varies, and the outgoing radiation from any given point just isn’t a perfect blackbody curve as a result.
How much more difficult is it to measure the Earth’s comparable “surface temperature” at a single point on the surface? For one thing, we don’t do anything of the sort. We don’t place our thermometers 1 meter, 1 cm, 1 mm deep in — what, the soil? The grass or trees? What exactly is the “surface” of a planet largely covered with living plants? We place them in the air some distance above the surface. That distance varies. The surface itself is being heated directly by the sun part of the time, and is radiatively cooling directly to space (in at least some frequencies) all of the time. Its temperature varies by degrees K on a time scale of minutes to hours as clouds pass between the location and the sun, as the sun sets, as it starts to rain. It doesn’t just heat or cool from radiation — it is in tight thermal contact with a complex atmosphere that has a far greater influence on the local temperature than even local variations in insolation.
Yesterday it was unseasonably warm in NC, not because the GHE caused the local temperature to be higher by trapping additional heat but because the air that was flowing over the state came from the warm wet waters of the ocean to the south, so we had a relatively warm rain followed by a nighttime temperature that stayed warm (low overnight of maybe 46F) because the sky was cloudy. Today it is almost perfectly seasonal — high 50’s with a few scattered clouds, winds out of the WSW still carrying warm moisture from the Gulf and warm air from the south central US, but as the day progresses the wind is going to shift to the NW and it will go down to solidly freeze (30F) tonight. Tomorrow it will be seasonal but wet, but by tomorrow night the cooler air that has moved in from the north will make it go down to 25F overnight. The variation in local temperature is determined far more by what is going on somewhere else than it is by actual insolation and radiation here.
If a real cold front comes down from Canada (as they frequently do this time of year) we could have daytime highs in the 30’s or low 40’s and nighttime lows down in the the low 20s. OTOH, if the wind shifts to the right quarter, the temperature outside could reach the low 80s high and low 50s low. We can, and do, have both extremes within a single week.
Clearly surface temperatures are being driven as strongly by the air and moisture flowing over or onto them as they are by the “ideal” picture of radiative energy warming the surface and radiation cooling it. The warming of the surface at any given point isn’t solely responsible for the warming or cooling of the air above it, the temperature of the surface is equally dependent on the temperature of the air as determined by the warming of the surface somewhere else, as determined by the direct warming and cooling of the air itself via radiation, as determined by phase changes of water vapor in the air and on the surface, as determined by factor of ten modulations of insolation as clouds float around over surface and the lower atmosphere alike.
Know the true average surface Global Temperature to within 1K? I don’t even know how one would define a “true” average surface Global Temperature. It was difficult enough for the moon without an atmosphere, assuming one can agree on the particular temperature one is going to “average” and how one is going to perform the average. For the Earth with a complex, wet, atmosphere, there isn’t any possibility of agreeing on a temperature to average! One cannot even measure the air temperature in a way that is not sensitive to where the sun is and what it is doing relative to the measurement apparatus, and the air temperature can easily be in the 40s or 50s while there is snow covering the ground so that the actual surface temperature of the ground is presumably no higher than 32F — depending on the depth one is measuring.
And then oops — we forgot the Oceans, that cover 70% of the surface of the planet.
What do we count as the “temperature” of a piece of the ocean? There is the temperature of the air above the surface of the ocean. In general this temperature differs from the actual temperature of the water itself by order of 5-10K. The air temperature during the day is often warmer than the temperature of the water, in most places. The air temperature at night is often cooler than the temperature of the water.
Or is it? What exactly is “the temperature of the water”? Is it the temperature of the top 1 mm of the surface, where the temperature is dominated by chemical potential as water molecules are constantly being knocked off into the air, carrying away heat? Is it the temperature 1 cm deep? 10 cm? 1 m? 10 m? 50 m? 100m? 1 km?
Is it the average over a vertical column from the surface to the bottom (where the actual depth of the bottom varies by as much as 10 km)? This will bias the temperature way, way down for deep water and make the global average temperature of the ocean very nearly 4K very nearly everywhere, dropping the estimate of the Earth’s average Global Temperature by well over 10K. Yet if we do anything else, we introduce a completely arbitrary bias into our average. Every value we might use as a depth to average over has consequences that cause large variations in the final value of the average. As anyone who swims knows, it is quite easy for the top meter or so of water to be warm enough to be comfortable while the water underneath that is cold enough to take your breath away.
Even if one defines — arbitrarily, as arbitrary in its own way as the definition that one uses for 
In particular, it is sparse compared to the known and observed granularity of surface temperature variations, for both LST and SST. Furthermore, it has obvious sampling biases. We have lots and lots of measurements where people live. We have very few measurements (per square kilometer of surface area) where people do not live. Surface temperatures can easily vary by 1K over a kilometer in lateral distance (e.g. at terrain features where one goes up a few hundred meters over a kilometer of grade). They can and do vary by 1 K over order of 5-10 kilometers variations routinely.
I can look at e.g. the Weather Underground’s weather map readings from weather stations scattered around Durham at a glance, for example. At the moment I’m typing this there is a 13 F variation from the coldest to the warmest station reading within a 15 km radius of where I’m sitting. Worse, nearly all of these weather station readings are between 50 and 55 F, but there are two outliers. One of them is 46.5 F (in a neighborhood in Chapel Hill), and the other is Durham itself, the “official” reading for Durham (probably downtown somewhere) which is 59.5 F!
Guess which one will end up being the temperature used to compute the average surface temperature for Durham today, and assigned to an entirely disproportionate area of the surface of the planet in a global average surface temperature reconstruction?
Incidentally, the temperature outside of my house at this particular moment is 52F. This is a digital electronic thermometer in the shade of the north side of the house, around a meter off of the ground. The air temperature on the other side of the house is almost certainly a few degrees warmer as the house sits on a southwest-facing hill with pavement and green grass absorbing the bright sunlight. The temperature back in the middle of the cypresses behind my house (dense shade all day long, but with decent airflow) would probably be no warmer than 50 F. The temperature a meter over the driveway itself (facing and angled square into the sun, and with the house itself reflecting additional heat and light like a little reflector oven) is probably close to 60 F. I’m guessing there is close to 10F variation between the air flowing over the southwest facing dark roof shingles and the northeast facing dark roof shingles, biased further by loss of heat from my (fairly well insulated) house.
I don’t even know how to compute an average surface temperature for the 1/2 acre plot of land my own house sits on, today, right now, from any single thermometer sampling any single location. It is 50F, 52 F, 58 F, 55F, 61 F, depending on just where my thermometer is located. My house is on a long hill (over a km long) that rises to an elevation perhaps 50-100 m higher than my house at the top — we’re in the piedmont in between Durham and Chapel Hill, where Chapel Hill really is up on a hill, or rather a series of hills that stretch past our house. I’d bet a nickel that it is a few degrees different at the top of the hill than it is where my house is today. Today it is windy, so the air is well mixed and the height is probably cooler. On a still night, the colder air tends to settle down in the hollows at the bottoms of hills, so last frost comes earlier up on hilltops or hillsides; Chapel Hill typically has spring a week or so before Durham does, in contradiction of the usual rule that higher locations are cooler.
This is why I am enormously cynical about Argo, SSTs, GISS, and so on as reliable estimates of average Global Temperature. They invariably claim impossible accuracy and impossible precision. Mere common sense suffices to reject their claim otherwise. If they disagree, they can come to my house and try to determine what the “correct” average temperature is for my humble half acre, and how it can be inferred from a single thermometer located on the actual property, let alone from a thermometer located in some weather station out in Duke Forest five kilometers away.
That is why I think that we have precisely 33 years of reasonably reliable global temperature data, not in terms of accuracy (which is unknown and perhaps unknowable) but in terms of statistical precision and as the result of a reasonably uniform sampling of the actual globe. The UAH
Hopefully the issues above make it just how absurd any such assertion truly is. We don’t know the actual temperature of the globe now, with modern instrumentation and computational methodology to an accuracy of 1 K in any way that can be compared apples-to-apples to any temperature reconstruction, instrument based or proxy based, from fifty, one hundred, one thousand, or ten thousand years ago. 1 K is the close order of all of the global warming supposedly observed since the invention of the thermometer itself (and hence the start of the direct instrumental record). We cannot compare even “anomalies” across such records — they simply don’t compare because of confounding variables, as the “Hide the Decline” and “Bristlecone Pine” problems clearly reveal in the hockey stick controversy. One cannot remove the effects of these confounding variables in any defensible way because one does not know what they are because things (e.g. annual rainfall and the details of local temperature and many other things) are not the same today as they were 100 years ago, and we lack the actual data needed to correct the proxies.
A year with a late frost, for example, can stunt the growth of a tree for a whole year by simply damaging its new leaves or can enhance it by killing off its fruit (leaving more energy for growth that otherwise would have gone into reproduction) completely independent of the actual average temperature for the year.
To conclude, one of many, many problems with modern climate research is that the researchers seem to take their thermal reconstructions far too seriously and assign completely absurd measures of accuracy and precision, with a very few exceptions. In my opinion it is categorically impossible to “correct” for things like the UHI effect — it presupposes a knowledge of the uncorrected temperature that one simply cannot have or reliably infer from the data. The problem becomes greater and greater the further back in time one proceeds, with big jumps (in uncertainty) 250, 200, 100 and 40 odd years ago. The proxy-derived record from more than 250 years ago is uncertain in the extreme, with the thermal record of well over 70% of the Earth’s surface completely inaccessible and with an enormously sparse sampling of highly noisy and confounded proxies elsewhere. To claim accuracy greater than 2-3 K is almost certainly sheer piffle, given that we probably don’t know current “true” global average temperatures within 1 K, and 5K is more likely.
I’m certain that some paleoclimatologists would disagree with such a pessimistic range. Surely, they might say, if we sample Greenland or Antarctic ice cores we can obtain an accurate proxy of temperatures there 1000 or 2000 years ago. Why aren’t those comparable to the present?
The answer is because we cannot be certain that the Earth’s primary climate drivers distributed its heat the same way then as now. We can clearly see how important e.g. the decadal oscillations are in moving heat around and causing variations in global average temperature. ENSO causes spikes and seems responsible for discrete jumps in global average temperature over the recent (decently thermometric) past that are almost certainly jumps from one poincare’ attractor to another in a complex turbulence model. We don’t even know if there was an ENSO 1000 years ago, or if there was if it was at the same location and had precisely the same dependences on e.g. solar state. As a lovely paper Anthony posted this morning clearly shows, major oceanic currents jump around on millennial timescales that appear connected to millennial scale solar variability and almost certainly modulate the major oscillations themselves in nontrivial ways. It is quite possible for temperatures in the antarctic to anticorrelate with temperatures in the tropics for hundreds of years and then switch so that they correlate again. When an ocean current is diverted, it can change the way ocean average temperatures (however one might compute them, see above) vary over macroscopic fractions of the Earth’s surface all at once.
To some extent one can control for this by looking at lots of places, but “lots” is in practice highly restricted. Most places simply don’t have a good proxy at all, and the ones that do aren’t always easy to accurately reconstruct over very long time scales, or lose all sorts of information at shorter time scales to get the longer time scale averages one can get. I think 2-3 K is a generous statement of the probable real error in most reconstructions for global average temperature over 1000 years ago, again presuming one can define an apples-to-apples global average temperature to compare to which I doubt. Nor can one reliably compare anomalies over such time scales, because of the confounding variables and drift.
This is a hard problem, and calling it settled science is obviously a political statement, not a scientific one. A good scientist would, I truly believe, call this unsettled science, science that is understood far less than physics, chemistry, even biology. It is a place for utter honesty, not egregious claims of impossibly accurate knowledge. In my own utterly personal opinion, informed as well or as badly as chance and a fair bit of effort on my part have thus far informed it, we have 33 years of a reasonably precise and reliable statement of global average temperature, one which is probably not the true average temperature assuming any such thing could be defined in the first place but which is as good as any for the purposes of identifying global warming or cooling trends and mechanisms.
Prior to this we have a jump in uncertainty (in precision, not accuracy) compared to the ground-based thermometric record that is strictly apples-to-oranges compared to the satellite derived averages, with error bars that rapidly grow the further back one goes in the thermometric record. We then have a huge jump in uncertainty (in both precision and accuracy) as we necessarily mount the multiproxy train to still earlier times, where the comparison has unfortunately been between modern era apples, thermometric era oranges, and carefully picked cherries. Our knowledge of global average temperatures becomes largely anecdotal, with uncertainties that are far larger than the observed variation in the instrumental era and larger still than the reliable instrumental era (33 year baseline).
Personally, I think that this is an interesting problem and one well worth studying. It is important to humans in lots of ways; we have only benefitted from our studies of the weather and our ability to predict it is enormously valuable as of today in cash money and avoided loss of life and property. It is, however, high time to admit the uncertainties and get the damn politics out of the science. Global climate is not a “cause”! It is the object of scientific study. For the conclusions of that science to be worth anything at all, they have to be brutally honest — honest in a way that is utterly stripped of bias and that acknowledges to a fault our own ignorance and the difficulty of the problem. Pretending that we know and can measure global average temperatures from a sparse and short instrumental record where it would be daunting to assign an accurate, local average temperature to any given piece of ground based on a dense sampling of temperatures from different locations and environments on that piece of ground does nothing to actually help out the science — any time one claims impossible accuracy for a set of experimentally derived data one is openly inviting false conclusions to be drawn from the analysis. Pretending that we can model what is literally the most difficult problem in computational fluid dynamics we have ever attempted with a handful of relatively simple parametric differential forms and use the results over centennial and greater timescales does nothing for the science, especially when the models, when tested, often fail (and are failing, badly, over the mere 33 years of reliable instrumentation and a uniform definition of at least one of the global average temperatures).
It’s time to stop this, and just start over. And we will. Perhaps not this year, perhaps not next, but within the decade the science will finally start to catch up and put an end to the political foolishness. The problem is that no matter what one can do to proxy reconstructions, no matter how much you can adjust LSTs for UHI and other estimated corrections that somehow always leave things warmer than they arguably should be, no matter what egregious claims are initially made for SSTs based on Argo, the UAH
In the long run that record will satisfy all properly skeptical scientists, and the “warmist” and “denier” labels will end up being revealed as the pointless political crap that they are. In the long run we might actually start to understand some of the things that contribute to that record, not as hypotheses in models that often fail but in models that actually seem to work, that capture the essential longer time scale phenomena. But that long run might well be centennial in scale — long enough to detect and at least try to predict the millennial variations, something utterly impossible with a 33 year baseline.
rgb
And yes, that’s true. But who does? I’m not hearing. What’s the number?
Here’s what GISS says:
“For the global mean, the most trusted models produce a value of roughly 14°C, i.e. 57.2°F, but it may easily be anywhere between 56 and 58°F and regionally, let alone locally, the situation is even worse.”
Well, that’s a number. But it doesn’t sound like a claim of 0.05K accuracy.
OK, so I’ll address this one thing again, even though it was part of a really detailed reply with lots of stuff that got turned into randomness by Ifni a big earlier.
Visit here:
http://data.giss.nasa.gov/gistemp/graphs_v3/
Look at the first graph.
Look at the right hand side of the first graph.
Look at the error bar (in green) at the right hand side of the first graph.
Note its magnitude — 0.05 K.
Now look at the first graph again.
Look at the left hand side of the first graph.
Look around 1885, where there is another green error bar.
Note its magnitude — 0.1 K.
Note the website. These are the public graphs for GISS for global average temperature, and this is just such a graph, is it not? If I were John Q. Public I might never read through all of the details of just how this graph were computed — I would just look at it, look at those teensy error bars, and go “Gosh damn, CAGW is real. Look, the world has warmed 0.6K in just thirty year! We’ll all bake to death by 2100, especially if this rate of increase gets even bigger because of all of the enormous feedbacks they tell me are completely true, proven, settled science!”
Consider: In 1885, perhaps a dozen people with a scientific education had actually landed on the entire continent of Antarctica. The Pacific Ocean was mostly Aqua Incognita, visited occasionally by whalers, with a handful of missionaries and plantation owners on a few of its islands. Siberia, China, Mongolia, Tibet were nearly devoid of thermometers, certainly compared to today. The Amazon and much of central Africa was dense jungle, and Burton was still being lionized for having actually having made it to the headwaters of the Nile. Australia and the Western US were still largely a frontier. Many of the ships that plied the waters of the world still did so under sail. Thermometers of the era were generally no more accurate than 1 K, and were sampled enormously erratically compared to 1985. Yet the precision acknowledged in the temperature estimate for 1885 is only twice that for 1985!
Pardon me, it takes me a minute or two to stop laughing. I mean seriously, do they take us all for idiots?
Apparently so.
So when you assert that 0.05 is not indeed the precision that GISS claims for its contemporary global average temperatures, that turns out not to be the case. It is indeed the precision they so claim. 0.1 is the precision implied on the Wikipedia page for the Earth, which lists its temperature as 287.2 K — we do try to teach our students not to put that decimal down unless you mean it, but of course nobody listens. GISS claims a precision of 0.1 for its global average temperature estimates from 130 year ago! It also claims, by virtue of putting these temperature estimates on a single curve, that these are apples to apples numbers, that the numbers derived from 1880 data mean exactly the same thing as those derived from 2012 data, that the temperatures in question aren’t just precise in a defensible way given certain presumptions about the data but that they are accurate in similar ways across that entire range.
Excuse me, I have to wipe my eyes again. Oh, my aching sides.
What amazes me is that no one actually calls them on this. In my opinion without having the slightest regard for their methodology their error estimates for 1885 are absurd. I don’t care, in other words, how the number is derived. The precision claimed fails the mere test of common sense — it isn’t true unless an entire textbook worth of assumptions are all true, none of them directly verifiable, all of them begging the question concerning the very phenomenon that is being tested against the numbers.
As I said — and it appears that we might even agree — the correct ballpark for the accuracy of GISS would be 0.5-1 K for its contemporary numbers, and I’d personally guestimate at least 2-3 times that for number out of the nineteenth century, wouldn’t you? As for precision — if there isn’t at least an order of magnitude worse precision for global temperature estimates from the nineteenth century, there is something seriously wrong, quite independent of what you think the sources of the errors might be at the two ends of the scale.
After all, in contemporary weather measurement, we use high precision, precisely calibrated thermometers that typically record temperature with a very high temporal granularity throughout the day and night, in carefully selected locations that still demonstrably suck as Anthony himself and many others have faithfully documented. In the 1880’s the instruments in common use were one to two orders of magnitude less precise, were even more indifferently located, and we have no idea how most of them were sampled by the bored civil servants that took and recorded their temperatures.
I was not attacking GISS per se, mind you, only pointing out that its claimed precision is, in my opinion, absurd on the face of it, independent of methodology. Nor is its accuracy defensible. Nor is its generality across the range of temperatures at hand, not really. Missing Antarctica? We don’t even do that well with Antarctica today, not really.
An honest presentation of errors in GISS would make its error bars far, far larger for the far end of its curves, don’t you think, if you just apply a bit of common sense?
No, now I’ll attack GISS , and indicate why satellite data is so important. Consider the UAH lower troposphere temperature. It is known, both accurately and precisely, apples to apples, from roughly 1979 to the present. It shows almost no statistically significant increase in temperature over that entire period. The temperature anomaly in 1980 was around -0.1 K. The temperature anomaly last month was around -0.1K. Sure, that cherrypicks end points and a linear fit is probably closer to 0.3 K, but the R value of that fit — (without computing it, and assuming point errors on the order of the variance in the data) is going to suck, because the linear trend isn’t very strong compared to no trend at all, noting that the current anomaly on a 31 year average is negative.
That last fact says it all, compared to a purported ~0.6 K increase in GISS, supposedly precise to 0.05 K.
Now if I had to bet on one of the two producing the correct relative anomaly, which one would I choose? In other words, if I imagine that there is such a thing as a global average temperature — in and of itself a bit dubious — and that the changes in GISS or UAH temperatures are an accurate measure of the changes in the global average temperature, we have this pesky factor of two to deal with. That’s a pretty serious thing. It’s the difference between Catastrophe and “Ho, hum.” 0.2 K/decade is in no way comparable to 0.1 K/decade, maybe, if not a lot less.
Personally, I think there is little doubt that the UAH satellite derived lower troposphere temperature is the more reliable number and the more accurate measure of the global mean temperature. For one thing, it is unbiased by things like the UHI effect and sparse sampling that make the GISS result questionable at best anyway! For another, there simply aren’t as many adjustments one can make for things like instrumentation, and one has a variety of controls (e.g. soundings) that are similarly uncorrupted by UHI effects in ground-level air. Simple pictures are the best — there are too many opportunities in GISS to bias the result intentionally or otherwise.
I suspect that this is one of the reasons that the climate science community is “suddenly” becoming a lot more open to the possibility that CAGW is just plain wrong. GISS and UAH LTT are diverging, and of the two GISS is almost certainly the one that is wrong. Wrong by a rather lot. Which makes one look at the graphs a bit more critically, note (perhaps for the first time) how tiny the error is that they are claiming for nineteenth century global average temperatures and say “bullshit“.
This is clearly wrong. If this is clearly wrong, is the entire curve wrong? What’s going on, here?
For some, this comes as a bit of a revelation. They feel betrayed. How could they have ever been so stupid as to believe that we know the global average temperature in 1885 to 0.1 K on the same basis that we now know it to 0.05K? How could they actually be fooled into thinking that we know the global average temperature at all within a half degree now, let alone to within a few hundredths of a degree? They get quite angry and do things like publicly repudiate the IPCC and AR5, because they can’t get anyone to put the right (or at least reasonable) damn error estimates into the data that the public gets to see, lest the public look at them and go “We’re spending a trillion dollars because that is what passes for ‘settled science’ proving Catastrophic Anthropogenic Global Warming?”
It’s enough to make the peasants reach for their torches and their pitchforks, isn’t it?
Once they pick themselves up off the floor and stop laughing.
Not that there is anything terribly amusing about tens of billions of dollars (racing towards hundreds) swindled out of the public by doing the moral equivalent of yelling “fire” in a theater, where the Earth is one big damn theater with no way out.
rgb
Typo: “Now, determine the
averagedensity of the ensemble as a unit.”Mr Mosher,
Sure there is a difference between the trend and the temperature itself, point taken. But…
1. The same raw data that is used to calculate the trend is also used to calculate the average temperature of the earth, a notion that Dr. Brown has shown conclusively is nonsense.
2. The average temperature calculated as per above is then used to try and arrive at an energy balance for the earth against an incoming insolation of 240 w/m2. Since we haven’t a clue what the “average” temperature is, trying to determine if we have any energy imbalance (due to anything, not just CO2) is more nonsense.
3. While the trend from a few thousand thermometers may well be the same as the trend from tens of thousands of thermometers, so what? What does this tell us about energy balance? Nothing! One degree increase in the arctic means a very different thing than a one degree increase in the tropics. Unless we have actual surface temperatures converted to w/m2 and average that, all we have is a bunch of numbers that have a similar trend, but remain meaningless from the perspective of understanding energy balance.
4. Further to Dr Brown’s point, I grew up in a rather harsh climate. One interesting thing I can attest to is that in spring it is quite possible to get a sunburn because you took your shirt off to cool down, but you left your boots on because you were standing in snow. The temperature measured on a day [like] that would be meaningful…. how?
I’ve noticed that the “this” I had asked Dr. Brown about wasn’t carried over in the post. Here it is:
http://www.uoguelph.ca/~rmckitri/research/globaltemp/GlobTemp.JNET.pdf
Essex, et al. 2006: “Does a Global Temperature Exist”, J. Non-Equilibrium Thermodynamics
My initial guess at how to define global temperature would be the temperature if you took every molecule in the volume of air between 1.5 and 2.5 meters above the surface, and instantly transported all those molecules to random locations within a cube of equal volume without changing their speed, energy, etc. Of course you can’t measure such a thing exactly, but I bet you could make a pretty close estimate. Probably well under 1K.
ROTFL
But what about the molecules of the actual surface? Should we throw them in? If so, to what depth?
rgb
Max Hugoson says:
March 4, 2012 at 1:40 pm
As I have noted TIME AFTER TIME AFTER TIME…an 86 F day in MN with 60% RH is 38 BTU/Ft^3, and 110 F day in PHX at 10% RH is 33 BTU/Ft^3…
Which is “HOTTER”? HEAT = ENERGY? MN of course, while the temp is lower.
I was at a pro-AWG lecture by a retired U of Wisc “meteorolgy” professor a couple years ago.
When I brought this up, and the example of putting varying amounts of hot and cold water into 10 styrofoam cups, measuring the temps, averaging the result and comparing to the result of putting all the contents in ONE insulated container (AVERAGED TEMP in this case WILL NOT MATCH the temp of all the varying amounts put into the one container!)..he looked (to QUOTE ANOTHER ENGINEER AT THE EVEN) as a “deer in the headlights”…and then finally babbled, “Well, the average temperatures do account for the R.H.”
Ah, like dear (Should be removed) dr. Glickspicable…”My words mean what I wish them to mean, nothing more and nothing less.” Reality BENDS for the AWG group!
Max – I fully agree – but you are wasting your time nobody listens. There seems to be a total lack of understanding of the realities of atmospheric enthalpy so everyone happily goes off using their elastic metric ‘atmospheric temperature’ then compound the errors by averaging…
Your example of MN and and AZ matches one I often use of LA and AZ. But nobody cares; they gather with the climate ‘scientists’ under the ‘temperature lamp post’.
More importantly take the case of a day in AZ that _starts_ at 60% RH and 86F, then during the day the temperature rises to 110F in the late afternoon but the RH has dropped to 10%. The actual ‘heat content’ of the air has dropped, but the temperature has increased. Nevertheless, along come the climate ‘scientists’ and _average_ the temperature and talk about the extra heat that has been ‘trapped’ by GHG when the actual heat content of the AZ air has _dropped_ despite the temperature rise.
I think the reason that enthalpy, latent heat and other confounding factors are avoided is that it is so mathematically simple to use the Stefan Boltzmann equations on the back of an envelope and pretend that everything is understood.
Dr. Glieckenspicable is more user-friendly to the tongue.
KR says:
March 4, 2012 at 4:59 pm
But there is no consistent bias in the temperature estimation. This is the problem. The biases are constantly being changed. And these biases are much greater than 0.05 degrees. Spend some time confirming these arbitrary adjustments and then come back and argue for a 0.05 accuracy in the temperature anomalies.
So the UHI doesn’t show up in the BEST data. This raises red flags already. Are you relying on the power of many other stations not in urban areas to suppress the obvious real effect of UHI? Do they account for UHI and if so what is a typical correction? Do they routinely under-estimate, over-estimate or (within random error) do they get the UHI correction more or less correct? When I drive into town from the country the change in temperature is 3-5 degrees. To suggest there is no DC bias in temperature data is ridiculous.
Robert Brown says: March 4, 2012 at 6:09 pm
Dr Brown,
As KR says, you are conflating global average temperatures with anomalies. Most of your arguments address the question of what is an average absolute temperature. And that is beset with many difficulties, as GISS is able to explain in far fewer words than you use.
Anomalies measure the change from some mean. Their utility relies on the fact that they are correlated between all these different situations that you describe. Correlation means that samples are statistically representative of their regions, and an attempt to spatially integrate makes sense.
Now you may if you wish try to argue that the correlation is illusory. But you need to present the evidence. It’s a different argument. And a much-studied subject.
Robert Brown says:
March 4, 2012 at 6:09 pm
“Which makes one look at the graphs a bit more critically, note (perhaps for the first time) how tiny the error is that they are claiming for nineteenth century global average temperatures and say “bullshit“.”
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[SNIP: Not your decision to make. -REP]
I am curious as to why only UAH is mentioned and not RSS.
This is especially so since Dr. Spencer says:
“Progress continues on Version 6 of our global temperature dataset. You can anticipate a little cooler anomalies than recently reported, maybe by a few hundredths of a degree, due to a small warming drift we have identified in one of the satellites carrying the AMSU instruments.”
No particular reason — the differences between the two is usually small and they provide a valuable check on one another.
Both of them return numbers that should be warmer than GISS surface numbers but in fact are quite a bit cooler, with significant differences in slope/trend. Indeed, if one assumes that the satellite record is accurate and that the relation between lower troposphere temperature and surface temperature is what it is “supposed” to be according to the models (both dubious, the latter more than the former) the surface warming is much smaller than GISS indicates, with an increasing divergence.
Depending on where and how you fit, UAH gives a trend of less than 0.14 K/decade (dropping at the moment, because a negative anomaly at the end tends to pull best fit down pretty agressively just like a negative anomaly at the beginning tends to push it up). That would correspond to an actual surface temperature anomaly of maybe 0.1 K/decade, instead of the nearly 0.2 K/decade seen in GISS over more or less the same period.
That’s a pretty serious problem — for GISS. Even if it does nothing else, it makes GISS numbers uncertain by at least the difference, and biases that uncertainty down not up. It makes it very likely that GISS overestimates the warming.
The interesting thing is that it somehow manages to overestimate the warming systematically, so that the two curves have different slope, different trends. That makes no sense at all. The same trend and different absolute temperatures would be understandable. Different trends means one curve or the other (or both!) have time dependent biases or the assumption that they are somehow connected to the same global average is not only wrong, it is wrong on average which again makes no sense whatsoever.
As I’ve already said, I personally consider the UAH/RSS results to be more reliable than the GISS result. They have multiple instruments, several ways to check for and correct for systematic biases by comparing their results, and the two series are themselves at least somewhat independent and yet closely commensurate most of the time. If you simply averaged the two you’d get a result hardly distinguishable from either one at a glance.
Indeed, GISS is up against a rock. If it continues going up as the UAH says that the lower troposphere is at least holding its own if not actually cooling, that rock will break it. Although truthfully, a glance at their error claims from the 19th century make it clear that it is broken already. You can’t squeeze blood from a turnip, and there are some pretty strict limits on the possible precision of our knowledge of temperatures as one goes back in the instrumental record. At the moment their claims have the look of a bloody turnip.
rgb
Steve:
“So the UHI doesn’t show up in the BEST data. This raises red flags already. Are you relying on the power of many other stations not in urban areas to suppress the obvious real effect of UHI? Do they account for UHI and if so what is a typical correction? Do they routinely under-estimate, over-estimate or (within random error) do they get the UHI correction more or less correct? When I drive into town from the country the change in temperature is 3-5 degrees. To suggest there is no DC bias in temperature data is ridiculous.”
That is not exactly true. First very few people in this debate understand how variable UHI is.
Typically, they draw from very small samples to come up with the notion that UHI us huge: huge in all cases, huge at all times. It’s not. Here are some facts:
1. UHI varies across the urban landscape. That means in some places you find NEGATIVE
UHI and in other places you find no UHI and in other places you find mild UHI and in other
places you find large UHI. You really have to understand the last 100 meters.
2. UHI varies by Latitude; Its higher in the NH and lower in the SH.
3. UHI varies by season. Its present in some seasons and absent in others depending on
the area.
4. UHI varies according to the weather. With winds blowing over 7m/sec it vanishes.
in some places a 2m/sec breeze is all it takes.
So you can find UHI in BEST data, the tough thing is finding pervasive UHI. Several
things work against this. most importantly the fraction of sites that re in large cities is very small.
Basically, you are looking for a small signal (UHI is less than .1C decade ) and many things can
confound that.
There are no adjustments for UHI.
Your anecdote is interesting, but the problem is that studying many sites over long periods of
time does not yield a similiar result.
Dr Brown,
Please keep these enlightening talks going. It is wonderful to hear words that reflect the views of countless engineers with practical experience of the “real” world and how inadequate models are.
As far as I am concerned, the very concept of a “global average temperature” is completely and totally flawed from any practical perspective. However, it does make a useful simplified ‘concept’ for an excellent thought experiment when describing basic radiative physics at the undergraduate level, as I recall learning in third year physics.
A tragic mistake was made in the 70’s and 80’s when Physics professors dumbed it all down and began teaching non-Physics (humanities) students some of the most basic elements of this science, without the students ever being capable of grasping the REAL complexity behind it. These students grasped very quickly the political & journalistic implications of warming from man-made CO2 without ever realizing they were being presented a mere slice of a dumbed down over-simplified picture of what was in reality an utterly overwhelmingly complex system.
A “little knowledge” is such a dangerous thing!
Nick Stokes says:
March 4, 2012 at 2:52 pm
Frank K. says: March 4, 2012 at 2:18 pm
“Please state this rule for us.”
No, Frank, I want an answer to my question first. Who are these people who claim to calculate the Earth’s “global annualized temperature” to 0.05K? Seen a graph?
But OK, the rules are in Gistemp. Or even TempLS.
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Oh – I see. You gone from “consistent rule” to rules, and more than one set of rules to boot! Very interesting. I thought it was so easy…
You still didn’t address my second question. Here it is again:
“And the temporal variation of that process is much more meaningful than the notion of a global average temperature.”
Please discuss your reasoning for this conjecture.
You also brought up yet another good question…
Nick Stokes says:
March 4, 2012 at 6:31 pm
“Anomalies measure the change from some mean. Their utility relies on the fact that they are correlated between all these different situations that you describe. Correlation means that samples are statistically representative of their regions, and an attempt to spatially integrate makes sense.”
Can you please provide quantitative justification for the good correlation of the temperature anomalies?
Thanks.
If the anomoly is currently negative – it implies that ALL EXTRA HEAT is no longer in the system.
And another thing in regards to measurement is reading intervals. Ideally temperature would be ready digitally and continuously and the 24 hour daily heat pattern would be and total 24 hour heat gain/loss would be easily usable with cloud cover data to determine the insulating effect or otherwise.
resolution in both space and time is going to be the holy grail of accuracy. At the moment we are working with giant grids and hourly temperatures. Until we can work with fractal chaotic systems we won’t be close to measuring or modelling reality at any great sigma level,
Robert Brown wrote:
Mindbuilder wrote:
My initial guess at how to define global temperature would be the temperature if you took every molecule in the volume of air between 1.5 and 2.5 meters above the surface, and instantly transported all those molecules to random locations within a cube of equal volume without changing their speed, energy, etc. Of course you can’t measure such a thing exactly, but I bet you could make a pretty close estimate. Probably well under 1K.
“But what about the molecules of the actual surface? Should we throw them in? If so, to what depth?”
No, the molecules of the surface haven’t been historically measured. Since air temperature records of the past have historically been measured about 2m from the surface, maintaining that height makes for easier comparisons of changes. Of course my proposal could be refined. Maybe 1.5m is a more common average historical height. Mabye you should consider 2m +/- 10cm instead of +/- .5m. You would also have to account for current and historical sampling or lack of sampling in odd places like atop mountian ranges. But again, I expect you could get within +/- .2K of the theoretical value, possibly even with historical records. 0.05K seems optimistic though, even for modern measurements.
Robert Brown says: March 4, 2012 at 6:44 pm
“That would correspond to an actual surface temperature anomaly of maybe 0.1 K/decade, instead of the nearly 0.2 K/decade seen in GISS over more or less the same period.”
The main reason why the satellites show a lower slope in the shorter trends is that they reacted very strongly to the El Nino of 1998. That downweights trend when it sits at the back end in time. But if you compare GISS with UAH from 1985 to 2011, so 1998 is in the middle, then there isn’t much difference.
Frank K. says: March 4, 2012 at 6:56 pm
“Can you please provide quantitative justification for the good correlation of the temperature anomalies?”
No. This post is about people who claim something about temperatures are full of something. You can lead with some evidence.
u.k.(us) says:
March 4, 2012 at 6:34 pm
Robert Brown says:
March 4, 2012 at 6:09 pm
“Which makes one look at the graphs a bit more critically, note (perhaps for the first time) how tiny the error is that they are claiming for nineteenth century global average temperatures and say “bullshit“.”
=============
[SNIP: Not your decision to make. -REP]
Just for the record, it was only an observation.
Steve from Rockwood says: March 4, 2012 at 6:30 pm
“Spend some time confirming these arbitrary adjustments and then come back and argue for a 0.05 accuracy in the temperature anomalies.”
I have done that. So have others. That is, we did calcs with no adjustments at all. And we got essentially the same answers.
Its not about average temperatures or average anomolies. Its about whether the data shouts ‘catastrophe coming!’ clearly enough to be giving up huge chunks of liberty and wealth to politicians supposedly ‘saving’ us. If it weren’t for the money this argument, if it took place at all, would be in an obscure journal somewhere. In a general sense I think Dr. Brown has it right: the data shouts “We just don’t know”.
Frank K. – “Can you please provide quantitative justification for the good correlation of the temperature anomalies?”
Yes. Read http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9839&rep=rep1&type=pdf – In particular Fig. 3. This shows correlations between “annual mean temperatures for pairs of randomly chosen stations with at least 50 common years in their records”, and shows strong correlations of temperature anomalies, with a correlation >50% up to 1200km distance.
A valley and an adjacent mountain will have very different absolute temperatures, but given the size of weather patterns, they will have closely correlated anomalies from their average temperatures.
I’ve gone hiking at night when a cold (62F) air-current was going down one side of a hill-street and a warm (77F) air-current 20 feet away going up the other side. What’s their ‘average’?
I’ve hiked up and down night-time temperature inversions with 88F at 1200 feet and 62F at sea level. Which one of those was doing the radiating to space?
Steve from Rockwood – “But there is no consistent bias in the temperature estimation. This is the problem. The biases are constantly being changed. And these biases are much greater than 0.05 degrees. Spend some time confirming these arbitrary adjustments and then come back and argue for a 0.05 accuracy in the temperature anomalies.”
If the biases are constantly changing back and forth, they become another random variable with a mean of zero.
If you don’t trust the adjustments, then calculate the temperatures without them. You will find that you see essentially the same results – that we’re seeing warming at around 0.15-0.16ºC/decade right now.
This is something that I’ve never understood – these complaints about adjustments. For each station these are a compilation of the best information about changes at that station – time of day for observations, changes in siting, in replacement thermometers, etc. They should act to reduce uncertainty. But even with no adjustments whatsoever to the raw data, you see just about the same results. The climate is warming, and quickly, and it correlates to our emissions.
And yet the adjustments are waved about as some kind of reason to ignore the issue entirely. That just doesn’t make any sense…
“Not that there is anything terribly amusing about tens of billions of dollars (racing towards hundreds) swindled out of the public by doing the moral equivalent of yelling “fire” in a theater, where the Earth is one big damn theater with no way out.”
rgb
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I nominate this for quote of the week…