The data is out for both RSS and UAH, and I’m presenting them both here. Click for full sized graphs.
RSS from Remote Sensing Systems of Santa Rosa, CA. RSS data here (RSS Data Version 3.2)
UAH from Dr. Roy Spencer, University of Alabama, Huntsville. Reference: UAH lower troposphere data
Since Dr. Spencer released the April UAH data first on his own blog, I’ll give him the honor of explaining the data and possible reason for divergence of the two data sets.UAH Data
YR MON GLOBE NH SH TROPICS
2009 1 0.304 0.443 0.165 -0.036
2009 2 0.347 0.678 0.016 0.051
2009 3 0.206 0.310 0.103 -0.149
2009 4 0.091 0.126 0.055 -0.010
Once again there is a rather large discrepancy between our monthly anomaly (+0.09 deg. C.) and that produced by Remote Sensing Systems (RSS, +0.20 deg. C). We (John Christy and I) believe the difference is due to some combination of three factors:
1) we calculate the anomalies from a wider latitude band, 84S to 84N whereas RSS stops at 70S, and Antarctica was cooler than average in April (so UAH picks it up).
2) The monthly anomaly is relative to the 1979-1998 base period, which for RSS had a colder mean period relative to April 2009 (i.e. their early Aprils in the 1979-1998 period were colder than ours.)
3) RSS is still using a NOAA satellite whose orbit continues to decay, leading to a sizeable diurnal drift adjustment. We are using AMSU data from only NASA’s Aqua satellite, whose orbit is maintained, and so no diurnal drift adjustment is needed. The largest diurnal effects occur during Northern Hemisphere spring, and I personally believe this is the largest contributor to the discrepancy between UAH and RSS.
UPDATE: Basil Copeland writes in comments.
And for those who are unhappy with either linear or 4 order polynomial trends, may I suggest Hodrick-Prescott smoothing?
http://i40.tinypic.com/30ngom0.jpg
I like to also keep track of the USA48 UAH anomalies:
The USA48 series appears flatter than the global series. That’s an illusion created by the differences in scale. The global series is not as volatile as the USA48, because it averages out all kinds of regional variation in climate around the globe. The scope of this averaging can be seen by plotting the two together, on the same scale:
http://i41.tinypic.com/2rw8bhw.jpg
The “Average Decadal Change Rate” shown on the chart is calculated as 120 times the average 1st difference of the smoothed trend lines, a number that should be fairly immune to any claims of cherry picking.
Frankly, I was surprised. E.g., on its own, the USA48 chart looks flatter. But it isn’t, really. In fact, it is steeper. Before anyone concludes that the high rate of growth for USA48 somehow demonstrates AGW, do keep in mind that during most of this time frame, the PDO was in a warm phase, and that the PDO warm phase has a strong influence on continental US temperatures.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
I should add re:my last comment that the missing data for ice at the poles may be taken off nadir, so the “hole” size would be different than a nadir pointing instrument. So use the size of the ice “hole” with care.
Just a correction, if I may:
“The USA48 series appears flatter than the global series. That’s an illusion created by the differences in scale. The global series is not as volatile as the USA48, because it averages out all kinds of regional variation in climate around the globe. The scope of this averaging can be seen by plotting the two together, on the same scale:”
REPLY: I updated it on the post above – anthony
tty: You asked, “Do you have any idea how they managed to measure the SST in e. g. Hudson Bay which was entirely ice-covered throughout April?”
I have no idea. I’ve noticed it also.
You asked, “Are they by any chance using the defective SSM/I for SST measurements as well?”
I discussed the satellites they use in the following post. Beyond that, I can’t snswer your question. Reynolds has discussed the efforts they undertake to reduce polar biases and such in one of his papers, but I can’t recall which one. Sorry.
http://bobtisdale.blogspot.com/2009/03/barents-sea-hotspot-isnt-so-hot.html
Of the graphs I generated, the Hudson Bay would only appear in the Northern Hemisphere and Global data. I might pick up a little chunk of it in the North Atlantic data due to the coordinates I use as well.
An straight line as seen through a microscope 🙂
Totally of topic but of critical importance to the free exercise of opinions via the internet: New law will make OFFENDING anyone on line a FELONY. Full details here:
http://futurestorm.blogspot.com/2009/05/hr-1966-offend-someone-online-go-to.html
Let the inquisitions begin.
SL
tty: Also, in the grand scheme of things…The Hudson Bay covers an area of ~822 thousand sq km, while the total surface area of the Earth is ~510 million sq km. The global oceans are about 70% of that. As a departed friend used to say, “It’s chump change.”
Anthony,
I am curious which software you’re using to create the graphs and filters.
Thanks for the continued effort.
Jeff
REPLY: Jeff I’ll email you details. – A
It is appropriate and helpful to have comments from Dr. Spencer here, but how about hearing the views of RSS? I sense that UAH and RSS have a collegial relationship in which they have helped each other out.
Also, regarding using the daily observations on the UAH site to calculate monthly average: Dr. Spencer on his website several months ago explained that such a step is not possible; there are additional algorithms which must be run. Nevertheless, monitoring the daily observations does give us a foretaste of what to expect for a monthly figure.
Frankly, with all of the “adjusting” that’s being done to the data, I don’t know why we are spending so much money on this now.
Hire a high schooler at minimum wage and give him a blank spreadsheet and let him make the temperature numbers up out of thin air. They would probably be closer to reality than what we are getting from Hansen et al.
It would be a good application of resources since high schoolers already know it all.
It is unclear whether RSS stops at 70N latitude as well. In any case, what reason do they give for neglecting between 70-84S?
Sven (05:27:23) :
John Finn (02:12:27)
anna v (02:23:38)
Allan M R MacRae (02:38:23)
Yes, John, I’ve read that on Dr. Roy Spencer’s web site, but the difference is just too big´! If the difference coming from different satellites for AMSU and UAH is really so big, it makes one of them totally irrelevant.
You might have a point, Sven. The UAH numbers are bouncing around a bit. The Feb anomaly was high compared to the others (even to the surface) and now we have a much lower April figure. It does suggest that one of the satellites (NOAA or Aqua) is suspect. The fact that Roy Spencer has commented on it probably means that it will be investigated.
Slightly off topic –
How can anyone rely on any temperature data base that is under the auspices of individuals or organizations who are advocates, be they pro or con AGW?
Should not the governmental officials and scientists who are in charge of maintaining these data bases be objective, detached, and unimpassioned with respect to their results and their ramifications?
Should there not be a firewall a clear separation of duties/offices & organizations – between those whose responsibility it is to advocate and those who are responsible for data collection and data base management?
Doesn’t it serve as a disservice to either side of this issue when data collection and advocacy are intertwined? Doesn’t this result in an immediate questioning of accuracy, reliability and credibility of the data presented?
I suspect that a great number of the folks who are beginning to question AGW, are doing so primarily because of they are skeptical of what they are being told by officials who are obviously strongly impassioned advocates such as Mr. Hansen. Mr. Schmidt, etc. and therefore could not possibly be look upon as reliable or objective sources of information.
The silent-majority, middle of the road, general public, Joe 6-Pack, (name us what you like) does not have much trust for what they hear from government and educational institutions to begin with and they can quickly read between the lines and discern what is going on when representatives of government and higher education implore over-the-top advocacy actions or resort to unprofessional name-calling, character attacks and other illogical diatribes against those who do not see the world in the same way.
While these actions appeal to others with similar strong emotion-driven viewpoints, they simply do not wash with us “common folk” with our common sensibilities. While these approaches can serve to silence dissention within the ranks for short periods of time, it also generates much hidden resentment and discontent that will bubble up and attack with a vengeance once those being repressed no longer feel threatened. (I have seen it happen and it is very ugly and character & career damaging.)
The Climate Science field would be wise to introspect and ask themselves if they are doing more harm than good with the approach that they currently are taking and with the leaders and spokespeople they are currently using.
A more balanced and objective approach to climate change and its consequences will serve this community far better in the long run. Currently they are rapidly losing the confidence of the general public. The confidence of the politicians & media will follow. Once the momentum gathers, their friends in high places will scatter and they will be left high and dry, hanging in the breeze, not fully understanding what happened until it is too late.
Just my humble opinions.
Basil:
Interesting, Hodrick-Prescott looks identical to the nonparametric roughness penalty smoothing method of Good & Gaskins (1971), which I use frequently. Small world.
Jeff Id (08:26:22) :
Anthony,
I am curious which software you’re using to create the graphs and filters.
Jeff,
If you are asking about the updated figures (I’m thinking possibly so, because of the reference to “filters”), I did those using gretl:
http://gretl.sourceforge.net/
-Basil
Morgan (09:31:40) :
I don’t know that they are identical — I’m not familiar with Good and Gaskins — but from your description they certainly seem similar. Hodrick-Prescott wasn’t really intended to be a smoothing per se. The smoothing is the side effect of isolating a detrended cyclical series. But I find this “feature” to be nicely suited to time series analysis of temperature trends, where we’d like to filter out the “noisy” influence of shorter term cycles (putatively dominated by ENSO). The effect is well illustrated by before and after images of Morelet wavelet transforms of the data. Here is an example of one (not UAH, just something else I had handy) which shows the effect of HP smoothing:
http://i44.tinypic.com/23upnm.jpg
The scale on the left is 2^n months. So we’re basically filtering out everything shorter than ~2^6=64 months. In this sense, HP smoothing is just a low pass band filter allowing periodicities (1/f, where f is frequency) greater than this through the filter.
Not strictly connected with this thread…
A recent article (http://www.theaustralian.news.com.au/story/0,25197,25349683-601,00.html) stated that Antarctic ice thickness is increasing.
A quick calculation suggests that if the thickness of extra ice were half a metre thick it would have released enough latent heat to warm all the atmosphere (up to and including 11kms) by 0.5°C.
I’ve often seen articles about heat stored in oceans, but isn’t this as important?
Well it is nice to see some graphs that are plotted on the same scales, and are reasonably up to date; i suppose very up to date for true climate time scales.
Also interesting to see all the chatter about a couple of items;
1) The discrepancy between RSS and UAH, and Dr Roy’s explanation of same regarding coverage differences for just one effect; and,
2) The back and forth regarding the appropriateness of a 4th order polynomial fit versus a linear fit, and arguments as to the scientific validity of same.
Now if we had as well GISStemp, and HADcrut; which Anthony Kindly once put all together in the same story; nod oubt we would see some additional differences. I’m just taking a wild hip shoot guess that USA48 which somebody likes to follow, might somehow relate to the lower 48 States of America; pehaps somebody could clarify.
So what do I (as in me personally) think of all this.
Well I have many times said that GISStemp is simply the result of Dr James Hansen applying his top secret AlGorythm to some haphazard set of very unscientific outdoor barbecue enhanced owl boxes; some of which Anthony has made world famous, by his revelations. And that is ALL that GISStemp is; it has no other scientific validity or meaning; you move or remove some of those sensors, and your system changes; and so do your reported results.
Well HADcrut, RSS and UAH all have the same problem; but RSS and UAH less so that the other two.
So there’s a very good reason for RSS and UAH to be different; and that is because they are different systems taking different data; and there should be no expectation of them being the same. That would ONLY be expected if RSS and UAH were two DIFFERENT measures of the VERY SAME system.
So what do I mean by that?
Well Dr Roy tells us that they record the anomalies from -84 to +84 deg Lat, and from one baseline period. RSS on the other hand records anomalies for a different baseline period, and for a smaller coverage area, from -70 lat to +82.5; and I am going to take at face value that each of RSS and UAH is a good reporting of the anomalies for those two different systems.
The discrepancies arise because each of these four reporting groups have hoodwinked all of us into believing that their data and reports are in fact a valid representation of planet earth; and they are not. They are anomalies for one thing, and not absolute temperatures, and certainly for GISStemp and HADcrut their sampling regimen violates the Nyquist sampling theorem; if the claimed system is the whole planet, or at least its surface or “lower trposphere” whatever that means.
The satellite sampling regimen, presumably is much closer to validity as representing the whole planet; and I see UAH are cheeky enough to claim the whole shebang since their graph says global. Well I’m not going to quibble too much about that missing 6 degrees at each end of the ball; they are doing about as well as orbital mechanics lets them.
But that’s the bottom line; the two results differ (not a lot) because they are two different systems that are being reported on, and not two different reports of the same thing.
If they were observing the same system, and if they both obeyed Nyquist, then their results would be the same, within experimental limitations.
As to the curve fitting; linear versus 4th order. To me the only objection one can make to either approach is if there is no valid physical reason for the outcome to be one or the other. Clearly the curve fitting is done within a certain interval; that being the only region for which data exists to fit to the curve; and if the formula goes out of whack outside that interval as someone claimed; that seems to be prima facie evidence that the polynomial formula is wrong; it has no scientific legs to stand on, but is a purely mathematical exercise in running a smooth curve through some noisy data.
Well of course the same goes for the linear fit; there is also not a shred of physical basis for believing the function is a linear one. Well there could be in Projective Geometry where the very first axiom says that”two points define a line”. Voilla ! QED.
So just what is the point of doing these “smoothings”. They amount to throwing away valuable and expensive real data, and replacing it with false and meaningless faux data which tells us nothing new. But the smoothing mentality is in keeping with the idea that “Climate” is the long term average (the smoothed value) of weather. Hurricanes aren’t important once you smooth them out over five or 30 year time scales; but the mechanisms that drive hurricanes might be very important for explaining some aspects of climate.
It is these smoothings and regressions, and trend lines, that create the fiction that 100 years from now we will be at a point obtained by extending one of these trend lines.
For my money RSS and UAH are remarkably close; and I don’t attribute ANY climatic significance to whatever discrepancies there are between these two curves.
So just how wacky are HADcrut, and GISStemp these days compared to UAH and RSS ?
“It is these smoothings and regressions, and trend lines, that create the fiction that 100 years from now we will be at a point obtained by extending one of these trend lines.”
George,
I always enjoy your postings, and pay close attention to what you have to say. If I may, I would in retrospect add what Dr. Spencer adds to his graph showing a 4th degree polynomial trend: nothing should be taken from his, or mine, as implying a trend than can be extrapolate from the end point.
Smoothing has its place, but not as a founding for extrapolation or prediction. So if that is your beef, I’m in your camp. It is those who are fitting linear trends to the historical time frame who usually do the extrapolation. The role of smoothing is to show just how non-linear, or cyclical, the underlying data really are, and that fitting a linear trend through cyclical data is fraught with all kinds of opportunities to make mistakes…or worse, intentionally misrepresent the data.
Basil
So just how wacky are HADcrut, and GISStemp these days compared to UAH and RSS ?
Since 1992 the trends are:
UAH +0.22 deg per decade
RSS +0.22 deg per decade
Hadley +0.20 deg per decade
GISS +0.24 deg per decade
I use 1992 for a specific reason.
George E. Smith (10:14:42) :
Well it is nice to see some graphs that are plotted on the same scales, and are reasonably up to date; i suppose very up to date for true climate time scales.
Also interesting to see all the chatter about a couple of items;
1) The discrepancy between RSS and UAH, and Dr Roy’s explanation of same regarding coverage differences for just one effect;
The trouble is there’s a good reason for not including the Antarctic which is interference in the microwave signal from ice. RSS exclude the Antarctic, Himalayas and Greenland for that reason. Also the UAH data shows an annual fluctuation wrt RSS which Spencer did not cover.
“”” Basil (10:44:41) :
“It is these smoothings and regressions, and trend lines, that create the fiction that 100 years from now we will be at a point obtained by extending one of these trend lines.”
George,
I always enjoy your postings, and pay close attention to what you have to say. If I may, I would in retrospect add what Dr. Spencer adds to his graph showing a 4th degree polynomial trend: nothing should be taken from his, or mine, as implying a trend than can be extrapolate from the end point.
Smoothing has its place, but not as a founding for extrapolation or prediction. So if that is your beef, I’m in your camp. It is those who are fitting linear trends to the historical time frame who usually do the extrapolation. The role of smoothing is to show just how non-linear, or cyclical, the underlying data really are, and that fitting a linear trend through cyclical data is fraught with all kinds of opportunities to make mistakes…or worse, intentionally misrepresent the data. “””
Basil,
There is nothing wrong with “curve fitting” when it comes to fitting a smooth curve to what is in reality a “noisy” function; by which I mean the results of measurements where the experimental data taking is a noisy process, so each measured data point is uncertain by some random noise process.
But when it is done to to a data set that is actually reasonably accurate measurement of what is really chaotic data from a chaotic system; then it seems to me inappropriate, because the whole idea of smoothing or filterng is to reveal some underlying actual relationship. In the case of these temperature anomalies there is no underlying relationship to be revealed; that is no physical reality will be revealed by such processing.
It is often the case, when experimental measurments over a range of values are connected by some underlying (but perhaps unknown) law that curve fitting can reveal the mathematical nature of what such a law might be.
For example, if one takes differences of a long data set, and repeats the process (n) times and ends up with a constant nth difference; it is reasonable to infer that the original data set follows some nth power polynomial function; which might eventually lead to discovery of the underlying Physics.
When noisy data are in fact represented by some simple mathematical function which is presumably smooth, then of course that smooth function would enable the calculation of values of the function that were never measured.
No such thing of course is possible in the case of these temperature anomaly data sets; since they do not in fact fit any real math function, since the system being observed is far too complex and chaotic.
So even interpolation is invalid, as well as extrapolation. That is really my whole point.
“”” Andrew Chantrill (10:14:12) :
Not strictly connected with this thread…
A recent article (http://www.theaustralian.news.com.au/story/0,25197,25349683-601,00.html) stated that Antarctic ice thickness is increasing.
A quick calculation suggests that if the thickness of extra ice were half a metre thick it would have released enough latent heat to warm all the atmosphere (up to and including 11kms) by 0.5°C.
I’ve often seen articles about heat stored in oceans, but isn’t this as important? “””
Well Andrew, I think you have the cart before the horse.
The sea water cannot freeze until it gets down to the freezing point temperature, and also until the latent heat of freezing is removed as well; and the only place for it to go, is into the atmosphere, and out into space.
So the freezing doesn’t raise the air temperature; the colder air sucks out the excess thermal energy so that freezing can occur.
I don’t believe anybody ever observed the air temperature to rise while the ocean freezes.
Pamela Gray (06:34:37) : “One thing I will have to say for CO2 theories is that it is understood that greenhouse affects are of a long-term nature and will not reflect in month to month data. Where I diverge on this statement alluding to the slow response of Earth’s atmosphere to CO2 is that I think it also takes a while for the Earth to respond to all sources of heating and cooling, with the possible exception of sudden intrusions of massive amounts of aerosols that stay suspended. Due to the seasonal nature of our atmosphere and the slow turning of our ocean conveyor belts, it takes a few seasonal/oscillating turns to buildup or release heat. The beating nature of the noise seems to follow this kind of natural oscillating method of cooling off and heating up.”
Yes, and my understanding is that since CO² is totally suspended, the buildup of any resulting heat would be monotonic and atmospheric. CO² warming is so minuscule that it’s indetectible against background noise. I strongly suspect that natural diurnal-thru- decadal oscillations provide several heat-shedding mechanisms that are ample to dispose of the extra heat without breaking a sweat.
Gallup Poll Editor Frank Newport says he sees no evidence that Al Gore’s campaign against global warming is winning. “It’s just not caught on,” says Newport. “They have failed.” Or, more bluntly: “Any measure that we look at shows Al Gore’s losing at the moment. The public is just not that concerned.” What the public is worried about: the economy.
He adds: “As Al Gore I think would say, the greatest challenge facing humanity . . . has failed to show up in our data.”
It is unclear whether RSS stops at 70N latitude as well. In any case, what reason do they give for neglecting between 70-84S?
The lower troposphere does not exist over the Antarctic. The UAH data is fictional extrapolated kilometers under ice.
This is important as ozone depletion is cooling the Antarctic mid/upper troposphere and stratosphere. Extrapolate this and you’ll get persistent fake cooling.
The “professional” sceptics know this, but don’t see fit to do anything about it because the data are – well – convenient. Of course, feel free to prove me wrong Anthony!