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.
That wider latitude coverage from UAH might explain the wider swings in variation on the UAH graph when compared to the RSS graph – at least it seems that way from just eyeballing the two.
I think we can expect to see falls for several months, in line with SST’s from a few months ago.
My thanks to John Christy and Roy Spencer, and the RSS team for their valuable work.
It is starting to look really flat…
Or if you check out the trends, almost like a hockey stick (going down, not up)
http://tinyurl.com/cjguzg
Dr. Spencer’s explanation is for the difference between UAH and RSS but UAH is also very different from daily amsu readings. It was aiming more towards 0.19C or 0.2C than 0.09C. Not once in the month did the channel 5 anomaly go under 0.1C?! I think UAH should check and recheck, something is not right…
http://discover.itsc.uah.edu/amsutemps/
So, the question I ask is on whose side is RSS? If they are pro AGW, then the narrower scan would tend to show less of a cooling trend.
Although we have the quietst sun of the century, although al oceanic ocillations are deep negative…still we have a positive temperature anomaly. I am still waiting for that global temperature to drop below the zero anomaly.
They answered me here on this blog before that I have to wait another 5year before all these cooling parameters would become visible in the temperature. The I ask myself the question how it was possible to establish the direct relationship between the sun activity and oceanic oscillations and the temperature. In all these publications I have read only about a lag of maximum 6 months.
Thus if the higher global temperature anomalies are simply explained by natural factors…then one of the next months the global temperature has to drop (far) below the zero-anomalie ?
whats happened to icecap? It seems to be non-existant since yesterday
I did not read Sven’s comment on AMSU-A, before I calculated the AMSU-A difference for April (Ch04) between 2009 and 2008. I found 0.173 Celsius, while the global UAH difference is 0.076 Celsius.
Taking AMSU-A at face value, adding 0.173 to the 4/2008 UAH value of 0.015 is 0.188 Celsius, close to the 4/2009 RSS value of 0.202 Celsius.
Channel 04 is the default value on the AMSU-A website, but to compare with UAH, I probably should have taken Ch05, as Sven did.
Dr. Spencer, please explain.
Sven; I tend to think there also might be a problem this month. But I don’t know if it was in the daily temperatures or the final figures. Maybe we should wait for GISSTemp and HadCrut in order to get a better view. Satellite temps are highly fluctuating, so they’re sometimes misleading. For example, it really looks like the 79-90 period was completely flat on the graph. Maybe they should think about plotting uncertainties?
OT but Just got Ian Plimers book. It will be the “Bible” of truth about AGW. Extremely well referenced and poignant.
I have no difficulty accepting the small differences in these two charts. The suggested reasons for the differences make sense. Thus, the emphasis ought not to be on differences but rather on what this almost identical information is showing. Bob Tisdale has commented that the 1998 El Nino released an enormous amount of warm water from the western Pacific – so much so that after the initial burst of heat it still took several sloshings back and forth to work this heat from ocean to atmosphere.
The recent thread on the non-warming ocean ties in nicely. Now overlay these two charts (or for visual clarity, use their average) with CO2 concentration and a median UN-IPCC temperature projection. Shift these over Medieval Warming and Little Ice Age diagrams. Then add a simple 100 word explanation and zap it everywhere. Overload the internet with it. Something must work, but what?
The problem is that the Administration in D.C., Congress, and the AGW zealots have the characteristic opposite that of a Black Hole. How to penetrate the fog is the overriding question of our time!
Thank you for removing the very misleading, unscientific, and totally in-appropriate 4th order poly fit to the curve Dr. Spencer choses to add to his plot.
http://www.drroyspencer.com/latest-global-temperatures/
What is becoming clear is that for the past 30 years there is no upward or downward trend, global temperatures appear to be cyclical indicating natural forcing.
When you consider that the troposphere is meant to be the business end of man-made global warming, i.e. radiative forcing, these null results highlight that all the IPCC climate models are not just in error but are in serious error.
The SST anomaly update for April is here, for those who missed the link by “Adam from Kansas” back on the May 2nd “Michigan Lake Level” thread:
http://bobtisdale.blogspot.com/2009/05/april-2009-sst-anomaly-update.html
Why not just provide an AGW alarmist-type of explanation? For example:
The divergence arises from the fact that RSS aren’t of real scientists, and that they are in the pockets of Big Wind and Big Solar.
Let’s just say the anomaly is somewhere between 0.10 and 0.20°C. I think one tenth of a degree difference is probably within or near the margin of error.
No matter the result you take, the earth is not warming right now.
Does anyone know why http://climate.uah.edu/ is no longer being updated? Is there a different source showing the geographic distribution of the UAH readings?
tall bloke,
Looking at the latest SST, looks like an El Nino could be in the works later this year.
http://www.osdpd.noaa.gov/PSB/EPS/SST/climo&hot.html
Joe Bastardi of Accuweather also predicts one.
http://www.accuweather.com/world-bastardi-europe-blog.asp?partner=accuweather
Sven (23:09:05)
Dr. Spencer’s explanation is for the difference between UAH and RSS but UAH is also very different from daily amsu readings. It was aiming more towards 0.19C or 0.2C than 0.09C. Not once in the month did the channel 5 anomaly go under 0.1C?! I think UAH should check and recheck, something is not right…
I was with you on this – at first, but it seems UAH may not necessarily using the published AMSU data, but data from NASA’s Aqua satellite. See point 3 above which says
“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”
On the http://discover.itsc.uah.edu/amsutemps/ site it says
“Daily averaged temperatures of the Earth are measured by the AMSU flying on the NOAA-15 satellite .”
So either the daily temperatures are not used by UAH or the home page needs updating.
He’s right. The RSS data is always drifting higher. If your sensing equipment is depending on a time-length return for signal, a decaying orbit will make your data drift with it.
Sven (23:09:05) :
are you referring to ch04 in the link you give? It has been within 1/2 F of the April 2008. This is consistent with the plots above.
tallbloke (22:57:12) :
I think we can expect to see falls for several months, in line with SST’s from a few months ago.
Whereas surface temperatures may start to increase by comparison since they tend to better reflect the ‘current’ situation. This will, of course, trigger the usual nonsense about data fiddling at GISS in particular. Just remember that over the past few months GISS (1979-1998 base period) anomalies have been well below UAH anomalies.
Sven (23:09:05) :
Dr. Spencer’s explanation is for the difference between UAH and RSS but UAH is also very different from daily amsu readings. It was aiming more towards 0.19C or 0.2C than 0.09C. Not once in the month did the channel 5 anomaly go under 0.1C?! I think UAH should check and recheck, something is not right…
http://discover.itsc.uah.edu/amsutemps/
*******************************
Sven – your reference shows actual temperatures, not anomalies.
How do you access the April 2009 anoms?
Are you assuming the “20-year average” is the 1979-98 baseline for the anoms?
Sped (22:58:51) : It is starting to look really flat…
Or if you check out the trends, almost like a hockey stick (going down, not up)
http://tinyurl.com/cjguzg
You know, it looks almost exactly like what is called a “blowoff top” in stock chart terms. The 1998 spike is the “blow off'” with an abnormally hight peak relative to trend, then followed by a lower peak-let then a failure to advance peer peak-let. Classic, darned near.
I wonder what strange parallel can let two such divergent chaotic systems have such similar chart behaviours… Just fascinating. Like having your dog paw print turn out to be almost identical to your hand print… You just have to wonder what the odds could be…
>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).
Anthony how about a bit of balance here – reams and reams on Arctic ice products but not even boo from you about the UAH Antarctic fudge. There is a 3km high reason why you should not go to 84S.
You might also care to report on the linear trends…
UAH trend: +0.13°C/decade
RSS trend: +0.155°C/decade
Don’t forget the sudden stratospheric warming event from January which influenced temperatures. It is clearly visible in the satellite data.
bill (01:26:43) :
“Thank you for removing the very misleading, unscientific, and totally in-appropriate 4th order poly fit to the curve Dr. Spencer choses to add to his plot.
http://www.drroyspencer.com/latest-global-temperatures/”
Anthony – could you please add back Dr. Spencer’s curve fit, as a linear curve fit is entirely inappropriate for modeling a highly non-linear process…Thanks
bill, interesting comment on poly fit to data.
I think single straight lines are misleading because the phenomenon is clearly non linear. Personally, I would choose 4th order as a conservative fit to a clearly cyclic phenomenon — but, then, discount extrapolations at the endpoints.
Nonetheless, a sequence of straight lines might make sense for the data.
That is, a horizontal line (at roughly 0.0) from month 0 to roughly 260, then a higher horizontal line (0.25) from 261 to roughly 350. And, now a third horizontal line from 351 on into the future — almost coincident to the horizontal line from 0 to 260 (looking like roughly 0.0 to 0.1 today).
In other words little net change over the last 360 plus months.
NOAA release US temp data for April 2009
“The average temperature in April 2009 was 51.2 F. This was -0.8 F cooler than the 1901-2000 (20th century) average, the 36th coolest April in 115 years.”
http://www.ncdc.noaa.gov/oa/climate/research/cag3/na.html
I wonder what shade of orange or red the GISS anomoly map will end up showing for the US for April 09?
I think everyone is worrying too much about minutiae of a few tenths of a degree. On both sides of the debate, this is much ado about nothing.
Global warming theory says these numbers should have increased by about 0.6C over this period.
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. AMSU would not even be “a rough guide” and there are not just “some data adjustments”… And then Dr. Spencer could not say: “(Want to see how the current month’s temperatures are shaping up?” as it does not really even indicate how current month’s UAH temperatures are shaping up?
anna v., Allan – no, I’m referring to channel 5. You have to choose either channel 5 from the drop down menu at the bottom of the page or 5 km on the left. Also choose temepratures in Celsius. Then you’ll get the absolute temperatures plus 1979-1998 averages and will thus see the anomalies.
http://discover.itsc.uah.edu/amsutemps/
rbateman (02:20:55) :
He’s right. The RSS data is always drifting higher. If your sensing equipment is depending on a time-length return for signal, a decaying orbit will make your data drift with it.
Who is right? If you mean Roy Spencer – of course he’s right, but diurnal drift is a well understood effect. RSS (and UAH previously) apply ‘corrections’ to the data to compenate for it.
DJ (03:35:18) :
You might also care to report on the linear trends…
UAH trend: +0.13°C/decade
RSS trend: +0.155°C/decade
I reckon the difference in trends is due to the lower RSS temps in the early years. In point 2, Roy Spencer says
“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.)”
There is almost a ‘step’ change in ~1992 when RSS temps moved higher than UAH (Tamino covered this in a post). Since 1992, though, the trends have been almost identical (i.e. 0.22 deg per decade).
I’ve commented on points (2) and (3) so I might as well have my say on (1) which is
“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).”
The area between 70S and 84S only represents ~3% of the earth’s surface (can someone check that) so it would take a pretty big shift in temperatures in that latitude band to significantly affect the global figure. In summary, then
(1) Insignificant.
(2) Possible – but only if Aprils between 1979-1992 were relatively colder than other months in the 1979-92 period, otherwise the “discrepancy” would always be present.
(3) Most likely explanation – and, I’m glad to say, Roy appears to agree with me.
Conclusion: I’ve go far too much time on my hands.
E.M.Smith (03:02:59) :
“You know, it looks almost exactly like what is called a “blowoff top” in stock chart terms. ”
After some googlefu I found a page with some charted examples of a “blowoff top” to illustrate your point. Eerie:
http://www.clivemaund.com/article.php?art_id=1619
Thank Dr. Spencer for the explaination. If indeed all that info is correct, UAH is certainly more accurate and reliable than RSS.
We’ll probably have to wait for the UK Met Office and GISS and then we can say whether it’s UAH that is anomalous or RSS. If it’s RSS, then it’s probably the NOAA satellite drift that is to be blamed (for both RSS and AMSU), otherwise UAH has a problem to solve…
DJ (03:35:18) :
You might also care to report on the linear trends…
UAH trend: +0.13°C/decade
RSS trend: +0.155°C/decade
================================================
Along with the fact that any trend calculated over the span of the data needs to be adjusted for the major cooling impacts of El Chichon and Pinatubo.
Also need to report on the fact of downward trend for 12 years despite monotonically increasing CO2 levels.
C’mon DJ let’s party!
Bob Tisdale (01:36:36) :
Do you have any idea how they managed to measure the SST in e. g. Hudson Bay which was entirely ice-covered throughout April? Are they by any chance using the defective SSM/I for SST measurements as well?
For those looking elsewhere, or wanting the zonal data of UAH, look here:
http://vortex.nsstc.uah.edu/public/msu/t2lt/uahncdc.lt
After staring at these charts for the past year or so, it seems to me that the temperature exhibits, on average, a step function. From 1979 up to 1997 the temp osciallates around zero. Then we have what looks like an anomalous event of the 1998 el Nino, followed by a “relaxation” of the system. Then finally, the temps exhibit a step function up to a value of around 0.2 degrees for the last decade. I would graph it (using the old ASCII trick) to look something like:
As a physicist, and if I didn’t know that the data I was looking at was world temps, I would say the spike induced a “change of state” transition in the system. Definitely not a linear system, and certainly does not show a continuing upward non-linear trend as predicted by the GCM’s.
Wait: RSS is not global? How do the datasets compare if only the areas covered by both UAH and RSS are used?
Oops.. it looks like my ASCII graph got botched… moderator maybe you can snip that section?
Sven (05:27:23) :
anna v., Allan – no, I’m referring to channel 5. You have to choose either channel 5 from the drop down menu at the bottom of the page or 5 km on the left. Also choose temepratures in Celsius. Then you’ll get the absolute temperatures plus 1979-1998 averages and will thus see the anomalies.
http://discover.itsc.uah.edu/amsutemps/
And by what logic is the 5 kilometer height temperature to be compared with surface temperatures? 5 kilometers is the top of the Himalaya.
CH04 is called the “near surface temperature” and I would suppose that would be the one to compare with the other three measures of surface temperature though it does not say what height. -17C makes no sense unless it is higher than the one kilometer plot, which is around the -2 C level? In the 1 kilometer plot the difference with 2008 is still consistent and in the 5 kilometer plot but I do not understand the absolute temperatures and do not know what the anomaly is measured against.
I think we would all appreciate if if there were an explanation at that link of what the temperatures really mean with respect to the surface the we live on.
bill (01:26:43) :
Regarding your statement that a “4th order poly fit [is] . . . very misleading, unscientific, and totally in-appropriate.” No more so than a linear fit. In fact, give volcanic perturbations and well-known oscillations, a polynomial fit might be a better choice for a GMT time series. Consider this example: If in mid-1944 you did a linear fit of German vs. Russian military success, you would give the future to Germany. However, if you did a polynomial fit, you would get a better handle on the future. Of course, Dr. Spencer points out that his polynomial fit is not purported to have predictive abilities, and we should bear that in mind also when we see linear fits.
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.
The lack of data right at the poles is due to the nature of the orbits used to collect Earth Observation data at a consistent observation time across the globe.
The NASA satellites from which the data are generated are not in polar orbits ( even though they are called POES.) They are in specialized orbits called Sun Synchronous, so that their passage over the equator takes place at the same time every orbit all year long. This way the temperature is measured at the same time all of the time, along with the other measurements being made.
In order to accomplish this orbit, it is necessary for the orbit to drift “east” about a degree a day, as the earth moves in its orbit around the sun. This keeps a constant sun angle (beta angle) WRT the orbit plane. The orbits use a perturbation due to the earth’s oblateness to accomplish this. To get the 0.986 degree drift per day necessary, the orbits must necessarily be inclined past the 90 degree polar orbits to inclinations in the 94 to 105 degree range depending on altitude. So satellites in sun sync orbit cannot fly over the poles and cannot collect nadir data over those areas.
You can see this effect in the lack of UAH data above 84 degrees north and south. You can also see this in the Cryosphere today plots of icecaps. There is a hole in the data right at the poles. If you look at the polar ice plots, you can get a sense for the size of the missing area.
http://arctic.atmos.uiuc.edu/cryosphere/NEWIMAGES/arctic.seaice.color.001.png
anna v (06:15:15):
“And by what logic is the 5 kilometer height temperature to be compared with surface temperatures? 5 kilometers is the top of the Himalaya.
CH04 is called the “near surface temperature” and I would suppose that would be the one to compare with the other three measures of surface temperature though it does not say what height.”
No, anna v., we are not talking about absolute temperatures but anomalies. RSS and UAH are measuring mid troposphere and their only measure for comaprison is their own average (1979-1998, Met Office is 1961-1990 and GISS is 1951-1980). As MetOffice-GISS and RSS-UAH are measuring different different things (heights) and reference periods are different, they can not be directly compared as figures. But we can look at their anomalies compared to their own average and look at their how they “behave”. So – RSS stayed pretty much the same while UAH went sharply down. Now, if MetOffice and GISS would behave either like RSS ior UAH, we can see which one is having trouble.
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:
http://i44.tinypic.com/2vxn3u9.jpg
The UAH 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 UAH48, 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.
Anybody know what’s going on with the Icecap website?
REPLY: server failure
Frank K. (04:44:13) :
I’ve come to hate seeing polynomial curve fits in climatological graphs. They’re okay when the important data is in the middle, but they diverge wildly outside of the data, and you can see the beginnings of that divergence at the edges. Since people are always looking for where the climate is going, they’re a bad choice.
I looked for, and failed to find, a web page showing the problem.
If someone has some graphing software handy, please create something showing a 4th order poly fit of the middle part of the UAH data but showing the curve over the entire history. The result would likely silence any fans of Spencer’s curve.
Also, a 3rd or 5th order fit would be interesting – I think the slope at the endpoints would have a different sign than even order fits.
REPLY: See the update to the post for the curves fitted with Hodrick-Prescott smoothing, I think it is most representative. Linea nd 4thord polynomial fits both have their problems. We’ve covered HP smoothing last year on WUWT. – Anthony
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!
“”” DJ (14:19:15) :
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. “””
The RSS graph says right on it -70 to +82.5, so that is pretty clear.
I gather from your second paragraph, that everyone takes MSL as the datum rather than the local land surface.
That would mean no lower troposphere over some other areas of the globe either. So how does the atmosphere know that there is land there or not.
Well to me, surface data is more important than atmospheric; after all humans generally live on the surface; or pretty near so; except in Coober Pedy.
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”.
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From: http://www.biocab.org/Heat_Stored_by_Atmospheric_Gases.html#anchor_62
The problem with the AGW idea is that its proponents think that the Earth is isolated and that the heat engine only works on the surface of the ground. They fail to take into account that incoming heat from the Sun is transferred by conduction from surface to subsurface materials, which store heat until the incidence of direct solar radiation declines, explicitly during nighttime.
At nighttime, the heat stored by the subsurface materials is transferred by conduction towards the surface, which is colder than the unexposed materials below the surface. The heat transferred from the subsurface layers to the surface is then transported by the air by means of convection and warms up. The upwelling photon stream affects the directionality of the radiation emitted by the atmosphere driving it upwards, i.e. towards the upper atmospheric layers and, from there, towards deep space. This process is well described by the next formula:
FSH = -ρ (Cp) (CH) (v (z)) [T (z) – T (0)]
Where FSH is for Sensible Heat Flux, ρ is for density of air, Cp is specific heat capacity of air at constant pressure, CH is the heat transfer coefficient (≈ 0.0013), v (z) is the horizontal wind speed across z, T (z) is the temperature of air at 10 m of altitude, and T (0) is the temperature of the surface.
The “minus” sign means that heat is absorbed by the colder system. For example, the sensible heat flux for a region where the temperature of the surface is 300.15 K, the temperature of air is 293.15 K and the horizontal wind speed is 40 m/s, is 0.443 kJ s/m^2.
I want to make clear that this formula applies to both ocean and land heat transfer, although on land it is more appropriate introducing CD instead of CH. However, CD ≈ CH ≈ 0.0013.
The sensible heat flux (day and night) is directed upwards, that is, from the surface to the atmosphere (Peixoto & Oort. 1992. Page 233).
Concluding, atmospheric gases do not cause any warming of the surface given that induced emission prevails over spontaneous emission. During daytime, solar irradiance induces air molecules to emit photons towards the surface; however, the load of Short Wave Radiation (SWR) absorbed by molecules in the atmosphere is exceptionally low, while the load of Long Wave Radiation (LWR) emitted from the surface and absorbed by the atmosphere is high and so leads to an upwelling induced emission of photons which follows the outgoing trajectory of the photon stream, from lower atmospheric layers to higher atmospheric layers, and finally towards outer space. The warming effect (misnamed “the greenhouse effect”) of Earth is due to the oceans, the ground surface and subsurface materials. Atmospheric gases act only as conveyors of heat.
TOP OF PAGE ^^
11. FURTHER READING
Bakken, G. S., Gates, D. M., Strunk, Thomas H. and Kleiber, Max. Linearized Heat Transfer Relations in Biology. Science. Vol. 183; pp. 976-978. 8 March 1974.
Boyer, Rodney F. Conceptos de Bioquímica. 2000. International Thompson Editores, S. A. de C. V. México, D. F.
Haworth, M., Hesselbo, S. P., McElwain, J. C., Robinson, S. A., Brunt, J. W. Mid-Cretaceous pCO2 based on stomata of the extinct conifer Pseudofrenelopsis (Cheirolepidiaceae). Geology; September 2005; v. 33; no. 9; p. 749-752.
Manrique, José Ángel V. Transferencia de Calor. 2002. Oxford University Press. England.
Maoz, Dan. Astrophysics. 2007. Princeton University Press. Princeton, New Jersey.
McGrew, Jay L., Bamford, Frank L and Thomas R. Rehm. Marangoni Flow: An Additional Mechanism in Boiling Heat Transfer. Science. Vol. 153. No. 3740; pp. 1106 – 1107. 2 September 1966.
Modest, Michael F. Radiative Heat Transfer-Second Edition. 2003. Elsevier Science, USA and Academic Press, UK.
Peixoto, José P., Oort, Abraham H. 1992. Physics of Climate. Springer-Verlag New York Inc. New York.
Petit, J.R., J. Jouzel, D. Raynaud, N.I. Barkov, J.-M. Barnola, I. Basile, M. Benders, J. Chappellaz, M. Davis, G. Delayque, M. Delmotte, V.M. Kotlyakov, M. Legrand, V.Y. Lipenkov, C. Lorius, L. Pépin, C. Ritz, E. Saltzman, and M. Stievenard. Climate and Atmospheric History of the Past 420,000 Years from the Vostok Ice Core, Antarctica. Nature, Vol. 399, June 3, 1999 pp.429-43.
Pitts, Donald and Sissom, Leighton. Heat Transfer. 1998. McGraw-Hill.
Potter, Merle C. and Somerton, Craig W. Thermodynamics for Engineers. Mc Graw-Hill. 1993.
Schwartz, Stephen E. 2007. Heat Capacity, Time Constant, and Sensitivity of Earth’s Climate System. Journal of Geophysical Research. [Revised 2007-07-16]
Van Ness, H. C. Understanding Thermodynamics. 1969. McGraw-Hill, New York.
Wagner, Friederike, Bohncke, Sjoerd J. P., Dilcher, David L., Kürschner, Wolfram M., Geel, Bas van, Visscher, Henk. Century-Scale Shifts in Early Holocene Atmospheric CO2 Concentration. Science; 18 June 1999: Vol. 284. No. 5422, pp. 1971 – 1973
Wagner, F., Aaby, B., and Visscher, H. Rapid atmospheric CO2 changes associated with the 8,200-years-B.P. cooling event. Proceedings of the National Academy of Sciences. September 17, 2002; vol. 99; no. 19; pp. 12011-12014.
Wilson, Jerry D. College Physics-2nd Edition; Prentice Hall Inc. 1994.
http://www.uah.edu/News/newsread.php?newsID=210 (Last reading on 25 August 2007)
http://www.atmos.uah.edu/data/msu/t2lt/tltglhmam_5.2 (Last reading on 25 August 2007)
http://www.cgd.ucar.edu/cas/papers/bams99/ (Last reading on 25 August 2007)
http://scienceandpublicpolicy.org/monckton_papers/greenhouse_warming_what_greenhouse_warming_.html
(Last reading on 25 August 2007)
http://www.ipcc.ch/SPM2feb07.pdf (Last reading on 25 August 2007)
http://www.gsfc.nasa.gov/topstory/20011212methane.html (Last reading on 25 August 2007)
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“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.”
I do not share your pessimism, obviously. The series are not entirely chaotic, or random. There are some periodicities in the various series observable with spectrum analysis, or periodograms. Smoothing, and then differencing, reveals these periods, or cycles, in the time domain.
I’ll more to say about that in the future. 😉
Basil
DJ – please can you provide some evidence for this statement and explain what you mean by the assertion regarding “extrapolation”?:
“This is important as ozone depletion is cooling the Antarctic mid/upper troposphere and stratosphere. Extrapolate this and you’ll get persistent fake cooling.”
All:
If you are monitoring the daily data at our Discover web page, to get the best idea of how the monthly anomaly will end up you should monitor ONLY channel 5, and compare the current month with the same month from ONLY the previous year.
The difference between the two months, one year apart, will then be only an approximation of the year-to-year difference in anomalies. This is because the Discover data are only from the AMSU on NOAA-15, while our official UAH product trends & interannual variability are from the AMSU on the Aqua satellite. Aqua is kept in a stable orbit, and so has no issues with orbital decay and diurnal drift corrections. That’s why we use only it, and no NOAA satellites (which all have drifting orbits), for trends.
We then use NOAA-15 for the geographic patterns of the anomalies, and constrain the NOAA-15 anomalies in zonal bands to be equal to those from Aqua. I need to spend a week at some point making limb correction equations for the Aqua AMSU, too, so that we can use it to help out on getting the spatial patterns. If you check the daily imagery for channel 5 at the Discover web site, you will see they have great fidelity and few artifacts, so we trust the monthly regional patterns the come from NOAA-15. My only concern is that the diurnal drift in NOAA-15 is probably causing a spurious component of the land-sea temperature differences.
Re: Roy Spencer (17:25:35) :
Dr. Spencer, thank you for this clarification. This makes sense.
Curiosity question: Why is it that the data from the NOAA satellites seems to degrade so quickly, often from the very beginning, but the AQUA satellite is so stable? Is it due to a difference in satellite technology or orbital positions or something else? The NOAA-## series of satellites seems rather cr*ppy in comparison to AQUA.
Joseph:
All satellites at the altitude of these satellites (700 km for Aqua, 830 to 850 km for the NOAA sats) experience a slight amount of atmospheric drag. This causes them to slowly fall towards the Earth over a period of years, which then changes the orbital characteristics. The orbit will not longer be sun-synchronous, as was originally intended, but will slowly drift through the clock hours.
The NOAA operational satellites did not carry extra fuel to keep them in the same orbit…the newer NASA satellites (Terra, Aqua, etc.) do. There are periodic orbital altitude and inclination maneuvers to keep them in a pretty constant orbit.
All of the major problems we have experienced in putting together a stable long term temperature record have stemmed directly or indirectly from orbital decay. The Aqua satellite data started in mid-2002, and hopefully we will never have to deal with those problems again.
Re: Roy Spencer (17:59:23)
Thank you for your response, Dr. Spencer. How long might the AQUA satellite last, before it needs to be replaced?
Those of you complaining and saying “something is wrong” because UAH dropped sharply this month and RSS stayed steady…did ya miss February? That month, RSS dropped sharply but UAH rose. Where were the accusations against UAH then?
Drop the bias…RSS and UAH may not match up perfectly month to month, but year to year they are generally pretty close.
Dr Spencer, Thanks for the clarifications above.
May I ask: are there any plans to continue providing the diagrams and commentary that used to be posted to http://climate.uah.edu ?
If the NOAA satallites have decaying orbits, I wonder if that means the NOAA SST data is somewhat innacurate as well, after all that data is on a NOAA website.
The differences seem small to me, the month-to-month deltas seem to have a random variance. While RSS may well have a degrading orbit, it seems adequately adjusted for. I keep an eye on this relative to Bill Illis (05:14:50) of where the AGW hypothesis say we should be. If each of the data sets are averaged for the past two years, UAH=.135C, RSS=.169C, not a big difference. Further averaging those two=.152C. If the past two years are indicative of the change for the past thirty years we’re looking at .51C/century, not a big deal. Overall, the temps change +/-.2C all the time, and the changes over the past thirty years hardly seem like a trend to bet anything on. Even going back to the 2001-7 period and averaging a couple of years would still give less than 1C/century change by eyeball. Thanks Dr. Spenser and Anthony.
“Bill Illis (05:14:50) : Global warming theory says these numbers should have increased by about 0.6C over this period.”
I think that’s why they call it “climate change” now because that ‘climate’ ‘changed’. 😉
Those of you complaining and saying “something is wrong” because UAH dropped sharply this month and RSS stayed steady…did ya miss February? That month, RSS dropped sharply but UAH rose. Where were the accusations against UAH then?
Stop being so sensitive – no-one’s making accusations. The UAH anomalies have been a bit more “variable” than the RSS anomalies in recent months, it’s perfectly reasonable to be curious about that.
Re: trend lines
Any trend line or smoothing algorithm that assumes that the trend value at t=Tn (now) is dependent on Tn+1 (future) is fundamentally un-physical and thus meaningless from a scientific perspective
The same goes for algorithms that imply that the trend value at t=Tn changes at times after t=Tn.
The above disqualifies e.g. Hodrick-Prescott.
So, in the absense of physical models, a LP IIR filter seems to be the best, and most scientifically honest, method to show any underlying long term trend.
One can then suppress signals of shorter wavelength (e.g. shorter than 1/6/12/whatever years) and thus only see the longer wavelength signals (i.e. the “trend”), which then might be interpreted as the variations in energy content in the total system, without the insignificant shorter term disturbances.
(Of course this, like with all methods, is sensitive to garbage data. Does anyone really think it makes sense to state the global mean temperatures with an accuracy of 1/1000 degree?)
Re George Smith:
“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.”
I agree with you when it comes to sea water freezing, but what about snow landing on Antarctica and building up there? If the snow landed instead in the ocean or on land and melted, it would absorb heat. By not doing so it effectively raises the temperature of the rest of the planet.
Where is the error in the logic?
Andrew above – Not sure if this helps but where has the snow come from?
It seems a hard concept to grasp that as ice accumulates in antarctica it warms the air. Try this though. As the ice thaws, does it not cool the air, sucking heat energy from the air to make the ice-water transition? That’s how my cooler works anyway. A little ice ‘cools’ a lot more air (or diet coke) better than the same amount of water because it takes a lot of heat to make the thawing transition. So if melting ice cools the air, then the exact thermodynamicly opposite process must heat the air. Putting it another way, if the atmosphere was to heat up enough to start melting Antarctica, that thawing process will suck a lot of heat out of the air and act as a buffer to global temp rise.
MattE (03:19:24)
Methinks you might want to consider the Second Law of Thermodynamics in the ice melting analysis.
John Finn-
Wasn’t being sensitive, just pointing out the hypocrisy displayed by some of the comments here. Things even out over time, but those with a bias are looking skeptically at UAH anomalies now…even though a couple months ago they were running warmer than everyone else. Go figure.
I think it’s perfectly reasonable to point out that in February, there was an equally large divergence between RSS and UAH, but in the opposite direction.
slowtofollow & MattE
The snow can come from anywhere; it’s simply a change of wind direction. If it lands in the sea and melts it absorbs back the heat it gave up when it froze.
If it’s building up on Antarctica then it isn’t thawing and isn’t absorbing heat back, so the effect is one of warming.
Imagine putting a refrigerator in a room, warm, then turning it on. The insides get cold, but it puts heat into the room from the convector panel on the back. There is no NETT heat change, but people in the room are warmer.
Andrew Chantrill
Your example is not a closed system, the energy to power the refrigerator must come from somewhere and thus cause additional heating. If you were talking about a hypothetical 100% efficient heat pump, then your example has some meaning, although I’m not going to step into this.
Andrew Chantrill (14:48:05)
So what is the “snow” in this analogy?
I have just decided to educate myself on this topic 1st hand. Funny how the prospect of a multi thousand $$$ increase in gas, heating, oil etc bills from a carbon based tax system will focus one’s attention. Having read all of the above posts, and being a simple (albeit well educated) guy, several truisms seem to be apparent to me.
First, the various climate data all seem to measure different things and/or use different measurement methodologies. This is important because of inherent study design limitations. No one can reach a single definitive scientific conclusion (at least in terms of multiple teams being able to manipulate the same datum and achieve the same result).
2) That said, it seems pretty clear that global temperatures have been on a slight (at most) rate of increase over the last 30 years. More importantly (and in context with my comments below), the observed temperatures seem (by all accounts) well below the predicted levels spit out by various models. Only in the realm of emotionally driven / pseudo religious “movements” do you get away with continuing the “cause” when every time go your predictive limb gets chopped off.
3). The last 30 years or so worth of data observations seem to require some context. I agree with the comments about not extrapolating trend lines and other related geek comments. More than that (and I know all you Ph.D. loving freaks will rip on me, but that’s OK): I cannot help but wonder what the nature of the debate would be if the precious data set started in 1998…. suffice it to say I am confident we would be hearing (again) about “global cooling” (the 1st being college in the early 80s). In a similar vein, I was assured over the years that “we” were all going to die from 1) starvation, 2) swine flu 3) AIDs 4) moral corruption, 5) etc. I am not an idiot and I realize we are warming up as we come out of the last ice age. However, the bigger point here is the complexity of the system folks are trying to measure and analyze. Oh how sweet the seduction is – pretending to predict (let alone even understand) the global / universal climate. Want to know what takes real emotional and intellectual fortitude? As this really cute 29 year old pharma rep told me in the bar one night…. “I have finally gotten old enough to realize that I don’t know [snip] and you know what – I am OK with that!”
Which brings me to #4 – some of the dismissive rhetoric by posts that seem to be pre-disposed to 1 accept global warming, and how they wrap it in pseudo-science. Take the last posts about ice forming / melting and how this warms / cools the planet. Correct me if the law of physics has been revoked (which is possible, given all the bad things I did on the 70s 80s & 90s).. oh who am I kidding, also the 2000s. That said, I think E still = M*C squared. In other words, energy is neither created nor destroyed, it only changes form. So, all this nonsense about snow, ice and melting is a bunch of hooey (a technical term). What is obviously much more important is the El Sol… how much energy stays within our eco-sphere and how much goes back into space. When we get to this level of intellectual consideration, who among us has any real idea of what is going on and what is important and/or unimportant in explaining stuff. I personally would never deign to say the polar regions were “chump change” (unless I was pre-disposed to a point of view).
Finally (and no doubt thankfully to all of you): Where is any of the usual social science stuff… you know, cost benefit analysis, etc. . I found it really telling when the press, a few months ago, started saying (with drool down their chin – oops, I sorry, it was a tinlge up their leg) “how important it is that the 1st studies have been done that show that there are real costs to doing nothing.” How sad and pathetic the once proud profession of journalism has become! At the risk of sounding like Dennis Miller, let me say this: I really don;t give a crap about some latte sipping limousine liberal in Malibu whose house slides into the sea. And as far as the poor schlub living in boongo boongo whose tiki hut is going to go underwater, I say this: have O’Bame add another $10,000 to my great childrens’ tax bill, what the he*l do I care!
Cannot wait to hear what the people who post on this site think of me… I am sure I will be painted as an ignorant, sexist, bigoted [snip]. LOL
Reply: No implied profanity either ~ charles the moderator
Jared (12:11:10) :
“… it’s perfectly reasonable to point out that in February, there was an equally large divergence between RSS and UAH, but in the opposite direction.”
Of course it’s reasonable. I can speak only for myself, but I really do not have any bias. In February there was actually not only divergence between RSS and UAH, but UAH was clearly the “odd one” also compared to HadCrut and GISS. We’ll see pretty soon, as HadCrut and GISS will come out in a week or so, whether it’s RSS or UAH that is behaving strangely.
Anywayn the anomaly is much larger than last year, same time. Must be the 7th warmest ever or so…
Based upon comments I have read here and elsewhere, I have removed the 4th order polynomial fit to the UAH global temperature graph at my website, drroyspencer.com. I considered reverting to just a simple linear trend line, but it too would have the same fundamental problem that any statistical fit to the data has: people tend to mentally extrapolate that smoothed curve (or line) into the future.
Flanagan (02:39:53) :
“Anywayn the anomaly is much larger than last year, same time. Must be the 7th warmest ever or so…”
It’s the 15th actually…
Flanagan, do you know why the anomaly in Apr 2009 is warmer than last year? What might have been happening globally to produce this jump this year or the decrease last year? And don’t say weather. Be specific. There are cyclic reasons for colder or warmer months when compared to one another from year to year. In fact, with archived jet stream data and SST’s, there are reasonable, definable, solidly based in atmospheric science, demonstrable, repeatable, natural cyclic explanations for every spike up or down and every point in-between on this graph, much of which is now available to the public on a daily basis. If every spike up or down can be explained thusly without any left over heat or cold to explain using man-made warming theories, at the very least, AGW is one of many theories out there that are competing for the more plausible natural cyclic theory.
Let’s just start with a simple one. What might be causing the pumping nature of the line graph? It is quite clear that there is a beat to the measure. Is that artifact? Seasonal heating and cooling? Some oscillation somewhere? It certainly does not coincide with the regular and fast beat of CO2 measures from Mauna Loa. What is making this slightly irregular and noisy but obvious beat? Can all the up beats and down beats be explained by the same set of circumstances?
jeez and slowtofollow
In my analogy, the refrigerator is ‘ideal’ and the motor adds no heat.
And by snow, I mean any precipitation that is frozen (i.e. has given up its latent heat).
Pamela:
The large month-to-month temperature variability is dominated by tropical intraseasonal oscillations in the transfer of heat from the ocean to the atmosphere. It’s not a radiative effect, but a non-radiative one. Higher than average surface winds over the tropical oceans lead to greater than average evaporation rates (cooling the surface), and then higher than average precipitation rates, heating the atmosphere.
Note that they would not exist if we did not have two very different heat reservoirs — the ocean and the atmosphere — exchanging energy in an episodic fashion.
As large as those fluctuations seem, they represent only about 1% variations in the average rate of infrared energy loss to space (or solar energy gain from the sun).
-Roy
Where will it have given up its latent heat and what effect would this have had on its local surroundings at the time?
It will have given up its latent heat the same place as it always does – the atmosphere.
Exactly where I don’t know and it doesn’t matter; conservation of energy says if it has given up heat that heat’s gone somewhere!
“”” Andrew Chantrill (01:10:27) :
Re George Smith:
“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.”
I agree with you when it comes to sea water freezing, but what about snow landing on Antarctica and building up there? If the snow landed instead in the ocean or on land and melted, it would absorb heat. By not doing so it effectively raises the temperature of the rest of the planet.
Where is the error in the logic? “””
Andrew, first of all, in order for snow to fall, it must first form; i.e. freeze, so it has already given up its latent heat to the atmosphere; at whatever altitude the snow formed.
If it Lands on Antarctica; most of the time it isn’t going to melt, given the typical Antarctic surface temperature.
If it lands in the ocean, hwether it melted or not would depend on the ocean surface temperature; which could be below zero; in which case the snow would persist, and could from into sea ice.
But let’s say it lands in the ocean and does melt. Well then it certainly is going to take up the latent heat of freezing (80 calories per gram); and that energy is most likely to come out of the sea water, given the relative thermal properties of water and air. So the melting snow is no different from melting sea ice; it is going to cool a large amount of sea water, and cause it to shrink; so the sea level will go down. Presumably the water that formed the snow originally came from the ocean, so the total ocean water content isn’t changing; but the warmer ocean water evaporated taking lots of energy into the atmosphere (about 545 cal per gram latent heat of evaporation, and then it dumps out another 80 cal per gram in turning into snow; and all that energy is delivered to the upper atmosphere for radiation to space.
So the whole cycle of evap/snow formation/ocean precipitation, and snow melting, is a huge transfer of thermal energy from the ocean to the atmosphere to be lost to space.
Let me repeat what George E Smith said:
Further, evaporation, formation of water dropplets and precipitation (rain) is another form of this …
You got that right Richard ! Just missing the 80 calories is all; but I’ll settle for the 545 anyway.
George
It’s nice to see Dr Roy himself drop in here to comment. I’m glad he decided to remove his fourth order curve fit.
The key point is NOT that the curve goes wonky when extrapolated outside of the data series time limits; but of course it is equally wonky inside; so interpolation doesn’t work either, to derive values for unmeasured points; there being no underlying physical cause for the shape. I do applaud his attempt to show some shape to the data; because my eye says there does seem to be some shape to at least the second half of the time frame (1998 excepted and understood); But Roy, it is just natural variability.
And my intent was not to jump heavily on the good Dr’s toes. We need to see the data as it comes out of the oven; after all there is no way for us to predict what the next plotted point will be; or even its direction from the latest; so we need to see the numbers as they are released.
George
It’s not on the front page any more, so I doubt that anybady still reads this thread, but GISS is now out for April – 0.44C ( a slight drop from 0.47C in March). Waiting fot HadCrut It still seems that this month again UAH is the “odd one”, as RSS is a slightly up (o.194 to 0.202), GISS is slightly down (0.47 to 0.44) and UAH has a huge drop (0.206 to 0.091)…
NCDC is out as well and puts UAH in even more of a minority.
HADCRU should be out in the next day or two.
I have to admit UAH definately seems to have a problem somewhere.