TRMM Satellite Suggests July 2009 Not a Record for Sea Surface Temperatures
August 26th, 2009 By Dr. Roy Spencer
UPDATE ADDED: 8/26/09 13:30 CDT see below
NOAA/NCDC recently announced that July 2009 set a new record high global sea surface temperature (SST) for the month of July, just edging out July 1998. This would be quite significant since July 1998 was very warm due to a strong El Nino, whereas last month (July, 2009) is just heading into an El Nino which has hardly gotten rolling yet.
If July was indeed a record, one might wonder if we are about to see a string of record warm months if a moderate or strong El Nino does sustain itself, with that natural warming being piled on top of the manmade global warming that the “scientific consensus” is so fond of.
I started out looking at the satellite microwave SSTs from the AMSR-E instrument on NASA’s Aqua satellite. Even though those data only extend back to 2002, I though it would provide a sanity check. My last post described a significant discrepancy I found between the NOAA/NCDC “ERSST” trend and the satellite microwave SST trend (from the AMSR-E instrument on Aqua) over the last 7 years…but with the AMSR-E giving a much warmer July 2009 anomaly than the NCDC claimed existed! The discrepancy was so large that my sanity-check turned into me going a little insane trying to figure it out.
So, since we have another satellite dataset with a longer record that would allow a direct comparison between 1998 and 2009, I decided to analyze the full record from the TRMM Microwave Imager (TMI). The TRMM satellite covers the latitudes between 40N and 40S, so a small amount of N. Hemisphere ocean is being missed, and a large chunk of the ocean around Antarctica will be missed as well. But since my analysis of the ERSST and AMSR-E SST data suggested the discrepancy between them was actually between these latitudes as well, I decided that the results should give a pretty good independent check on the NOAA numbers. All of the original data that went into the averaging came from the Remote Sensing Systems (RSS) website, SSMI.com. Anomalies were computed about the mean annual cycle from data over the whole period of record.
The results are shown in the following three panels. The first panel shows monthly SST anomalies since January 1998, and as can be seen July 2009 came in about 0.06 deg. C below July 1998. At face value, this suggests that July 2009 might not have been a record. And as you can see from the first 3 weeks of August data, it looks like this month will come in even cooler.
Now, if you are wondering how accurate these monthly anomalies are, the second panel shows the validation statistics that RSS archives in near-real time. Out of the 5 different classes of in situ validation data, I chose just the moored buoys due to their large volume of data (over 200,000 matchups between buoys and satellite observations), and a relatively fixed geographic coverage (unlike drifting buoys). As can be seen, the TMI SST record shows superb long-term stability. The 0.15 deg. C cool bias in the TMI measurements is from the “cool skin” effect, with water temperatures in the upper few millimeters being slightly cooler on average than the SSTs measured by the buoys, typically at a depth around 1 meter.
The third and final panel in the above figure shows that a substantial fraction of the monthly SST variability from year to year is due to the Southern Oscillation (El Nino/La Nina), and the Pacific Decadal Oscillation, PDO. Each of these indices have a correlation of 0.33 with SST for monthly averages over the 40N-40S latitude band, while their sum (taking the negative of the SOI first) is correlated at 0.39. I did not look at lag correlations, which might be higher, and it looks like some additional time averaging would increase the correlation.
I will post again when I have new information on my previously reported discrepancy between NOAA’s results and the AMSR-E results. That is still making me a little crazy.
8/26/09 13:30 CDT UPDATE
I computed the monthly global (60N to 60S latitudes) AMSR-E SST anomalies, adjusted them for the difference in annual cycles with the longer TMI record, and then plotted the AMSR-E and TMI SST anomalies together. Even though the TMI can not measure poleward of 40 deg. latitude (N or S), we see reasonable agreement between the two products.
None of this represents proof that July 2009 was not a record warm month in ocean surface temperatures, but it does cast significant doubt on the claim. But the focus on a single month misses the big picture: recent years have yet to reach the warmth of 1998. Only time will tell whether we get another year that approaches that unusual event.
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Paul J. Trimble: Please provide a link to the dataset you posted above.
Thanks.
Flanagan (11:17:49) :This is a bit pathetic, no? When one’s data do not fit the picture one has in mind, oops! Switch to another dataset, and so on until you get a result you like.
No.
It is right and proper to test and validate and Q.A. check any instrument when it has a divergent behaviour. You will, typically, either find an “issue” with the instrument or learn something really really interesting (either about the different things the two instruments are measuring and what that detail means, or about the subject itself.
If my oral temperature and my skin temperature diverge, for example, I might “discover” that the body moves blood to the core when under cold stress. (Or I might discover that one of my thermometers needed a new battery…).
The only “error” is to blindly trust the readings. That seems to be the choice you are advocating.
Does that mean we should not thrust the AMSR-E figures anymore? Adios UAH and RMSS?
“Trust, but verify!”
Or perhaps you would say “Thrust, but verify”…
Lucy Skywalker (11:58:39) :
Roy, thank you for holding the fort of integrity. I’m glad you showed the difference between TMI data and moored-buoy data because therein lies another clue which may solve the mystery. The “cool skin” effect which your graph shows gives an average discrepancy of 0.15 degrees – the buoy readings at 1m depth being warmer. Now in the original chart which was driving you crazy, the discrepancy appears to be of about this order of magnitude.
Here is the hypothesis. Suppose the “cool skin” effect is really a measure of average wind chill at the surface.
There is no such thing as “wind chill”. In fact total ait temperature in moving air is warmer than the same statc air by (TAS/100)^2 °C, where TAS is speed in mph.
E.M.Smith (12:19:30) :
Am I the only one bugged by the notion of a “passive microwave sensor”
You made me remember the contrary: active microwave generation weather experiments…
E.M.Smith (12:19:30) : Am I the only one bugged by the notion of a “passive microwave sensor” being used to measure “warming” in the context of ever higher levels of microwaves being used all over the place (in everything from jet radars to communications satellites to weather radars to..) at ever higher frequencies with lots of power?
It would not take much of a “leakage” or “cross modulation” or any of a few other “issues” to raise the signal level in a highly sensitive antenna…
The satellite data is cross-checked with the buoys as I understand it.
Sandy (12:24:11) :
If there is no enough energy below, in the sea, there is no need of big transfer events from the sea to the atmosphere (tropical storms, hurricanes)…no “terra spots” (earth version of sunspots).
What is strange (about the blue line) is the almost-elimination of the noise seen before 2007. The same noise leel is not seen after 2007 and it almost looks like an amplification of the signal with a filter applied.
Having previously groused about comments going off-subject, I’m about to do just that with the following because those who can probably answer my question are in attendance.
Roy Spencer’s original post got me looking at the ASMU-A plots of global average temperatures at various altitudes. In comparing them I noticed something peculiar
I noted that the annual swings in global average temperature as recorded by satellite follow a curious pattern at differing altitudes. The annual positive and negative temperature swings measured at near-surface (and at 14,000 feet) are mirror images of the annual temperature swings at 102,000 feet. The lower-altitude global average atmospheric temperature invariably peaks in mid-July, within a month of the northern hemisphere’s summer solstice. At the exact same time, the temperature at 102,000 feet invariably reaches its minimum annual temperature. In both cases, that annual swing is roughly in the range of 3.5 to 4.5 degrees F. At the same time, the temperature half way in-between at 56,000 feet shows little annual variation.
This raises the following questions:
1) Why does global average temperature at 14,000 feet and below track northern hemisphere seasons and, conversely
2) Why does the global average temperature at 102,000 feet track southern hemisphere seasons?
I don’t imagine I’m the first to notice this oddity and I’d really like to hear the explanation.
CH
Sure a “funny-looking” El Nino:
http://www.osdpd.noaa.gov/data/sst/anomaly/anomwsc.gif
By the way, it’s not Just This Year’s lack of Hurricane activity. Remember, the ACE has been declining for a while now.
E.M.Smith (12:19:30) :
Am I the only one bugged by the notion of a “passive microwave sensor” being used to measure “warming” in the context of ever higher levels of microwaves being used all over the place (in everything from jet radars to communications satellites to weather radars to..) at ever higher frequencies with lots of power?
It would not take much of a “leakage” or “cross modulation” or any of a few other “issues” to raise the signal level in a highly sensitive antenna…
Man-made microwave radiation would be utterly insignificant even if at 288K wavelength but typical MM microwave is about 4 orders of magnitude longer wavelength; it will not cause error.
Richard (12:12:44) [commenting on Lucy Skywalker (11:58:39)] “Interesting and plausible. But the difference as I understand it is not just in this year. Its in the trends that have been increasing over the years.”
You have to think about how anomalies for a given month are not independent of one another in conjunction with thinking about how x-values further from the x-mean exert relatively higher leverage. We have a climatology based on only n = 7 and we have something ‘unusual’ right at the end of the record (which drives the other end of the record in the opposite direction by definition, yielding a slope – just basic Stat 101 (chapters 1 & 2)). Unless Dr. Spencer & the remote sensing experts come up with something, the jury might have to be out for awhile on statistical grounds (n = 7 – i.e. unstable statistics).
I will repeat here my request (from the related recent thread) for direct links to plain-text monthly-summaries of all anomaly & raw series under discussion. It is to be expected that the discussion might go a little off the rails if the majority of the people commenting have not independently looked at the series (particularly the raw series – pre-climatology & anomaly).
I don’t think the suggestion of a link to lack of hurricane activity holds up, since the past years that were duds for TSs through July i e 02 and 04 don’t show similar divergence. In fact AMSR-E was negative to NCDC by 0.1degree at this point in 2002
“”” E.M.Smith (12:19:30) :
Am I the only one bugged by the notion of a “passive microwave sensor” being used to measure “warming” in the context of ever higher levels of microwaves being used all over the place (in everything from jet radars to communications satellites to weather radars to..) at ever higher frequencies with lots of power? “””
Well E.M. , That is the reason I have asked for some input on the physics of this measurement technique. I have a basic distrust of any remote sensing method that relies on a signal amplitude; when I hear the word “calibrate” it sends shivers up my spine.
The celebrated “microwave background” radiation for example is referred to as the 3K radiation because multi frequency measurments of it spectrally match a 3K black body radiation curve; and I had alwasy assumed that satellite measures of surface temps were likewise based on fitting a BB spectrum.
For example if you can plot enough of the spectrum of a thermal emitter, without serious frequency differential errors, and locate the spectral peak, then Wien’s Displacement law is all you need to identify the radiation temperature , and that is basically what identifies the microwave background temperature.
Off the top of my head, I don’t know if this is correct, but I suspect that the intensity ratio of two different frequencies in a fixed temperature BB spectrum is directly proportional to the Temperature (K). So now I am going to drive myself mad until I get out the formulas and solve that condition.
But even then, I wonder about the contamination of the as recieved signals at the satellite from emissions at other than the surface.
We don’t seem to have too many lurkers here who are familiar with these remote sensing stratgems.
Hopefully Roy or John Christy will chip in with some insight on this; I know it drives me barmy not knowing what the sensing mechanism is. Or Frank Wentz at RSS for that matter. I don’t like data of somewhat doubtful or unknown parentage.
But astronomers seem uniquely good at remote sensing; in my next life I plan to be an astronomer; maybe a Solar Physicist like Leif.
“”” Flanagan (11:17:49) :
This is a bit pathetic, no? When one’s data do not fit the picture one has in mind, oops! Switch to another dataset, and so on until you get a result you like.
Bah! “””
Well Flanagan, you do raise a legitimate issue; but if I understand Dr Spencer’s message the problem is not the accuracy of a data set, but the fact that two sets disagree. I think roy is man enough to accept the result; one it is determined what that result is.
Nothing is more uselesss than two different answers to the same question. Absent additional evidence you can’t have ANY confidence in either of them.
So no need to get your panties in a bunch; if the discrepancy gets resolved, then we’ll know what is going on.
I have a Scientific American article by a well know author that shows clearly two Antarctic ice cores covering the exact same recent (1000 year) period, and they show exactly the opposite trend in the temperature/CO2 story; so neither one is believable.
REPLY: I second that. Roy is definitely “man” enough to post results even if contrary to his project.. Flanagan is just a cowardly university wonk hiding behind net anonymity. When you are “man” enough to challenge Dr. Spencer in the open as he does his posts, then you’ll get some respect. Otherwise, slink off. – Anthony
Flanagan, why not tell us what you do at Universite Libre de Bruxelles ?
http://www.ulb.ac.be/
Then you’ll be on par with Dr. Spencer and your pot shots might actually mean something.
E.M.Smith,
“test and validate and Q.A. check”
Flanagan and his pals don’t need to bother with that sort of thing. If things look like they are not going according to plan they merely need to adjust!
acementhead (12:41:49) :
There is no such thing as “wind chill”.
Come to Saskatchewan on a nice -40 degree day with a stiff breeze blowing and say that. 😉
Hi Bob,
Below are the links:
http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCDC/.ERSST/.version3b/.anom/
http://ingrid.ldgo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/
I used Data Selection (all data and data filter xy mean to compute global average time series
wattsupwiththat (13:48:51) :
Flanagan, why not tell us what you do at Universite Libre de Bruxelles ?
I was under the impression that ex cathedra had no place in science. Isn’t the truth of any scientific statement independent of the origin?
acementhead (13:08:37) :
E.M.Smith (12:19:30) :
Am I the only one bugged by the notion of a “passive microwave sensor” being used to measure “warming” in the context of ever higher levels of microwaves being used all over the place (in everything from jet radars to communications satellites to weather radars to..) at ever higher frequencies with lots of power?
It would not take much of a “leakage” or “cross modulation” or any of a few other “issues” to raise the signal level in a highly sensitive antenna…
Man-made microwave radiation would be utterly insignificant even if at 288K wavelength but typical MM microwave is about 4 orders of magnitude longer wavelength; it will not cause error.
I hold that my above assertion is correct; it depends on fact not credentials. Credentialism is a curse on the modern world; it gives the warmists their power. “I have credentials therefore I’m right.” Well, no.
REPLY: My interest is putting the criticisms of Dr. Spencer on the same level as his discourse. In the open. I have a low tolerance for people like “Flanagan” who say Dr. Spencer’s approach to solving the problem is “pathetic” while hiding behind a mask of anonymity. In a court of law, the accused has the right to face the accuser. This net court of public opinion on AGW should be the same in my opinion. Besides, Flanagan won’t come clean anyway, he’ll deflect. – Anthony
Bob Tisdale (12:29:07) “Paul J. Trimble: Please provide a link to the dataset you posted above. Thanks.”
Bob, it’s not at all straight-forward to find, but I located the data Paul J. Trimble copied/pasted from here:
http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/%5BX+Y+%5Daverage/T+exch+table-+text+text+skipanyNaN+-table+.html
The pathway to there:
1) Start here:
“KAPLAN EXTENDED v2 ssta: SST anomaly data”
http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/
2) Click “Filters”.
3) Choose “Average over _X_Y_” (that’s a line underscoring both X & Y together – i.e. the 4th option in the “Average over” line if you are very careful to note the pattern of hyperlink-underscoring).
4) Click “Tables”.
5) Click “columnar table”.
I actually started further up the pathway at:
“IRI/LDEO Climate Data Library”
http://iridl.ldeo.columbia.edu/
….and then chose “Datasets by Source”, “Kaplan”, “overview”, “Extended v2”, “SST anomaly”.
Very awkward website (but it appears to have a lot of capabilities that might be useful for anyone tolerant of the antiquated software).
More thoughts: the top graph shows a steady increase in (satellite minus insitu) SST. Two possibilities (a) the satellite sensor is faulty and steadily hyping (b) the Smiths’ worst fears are realized: we are cumulatively microwaving our planet (did I understand the gist of that anything near correctly?) and the microwaves are getting into the sensors, so yes it’s AGW but no it’s not GHG…
Not “cumulatively”, I meant “increasingly”
George E. Smith (13:23:34) :
That is the reason I have asked for some input on the physics of this measurement technique. I have a basic distrust of any remote sensing method that relies on a signal amplitude; when I hear the word “calibrate” it sends shivers up my spine.
I put up this link in a comment on another post where you asked this question but you may have missed it, so I’ll try again
http://fermi.jhuapl.edu/avhrr/primer/primer_html.html
It’s from 1996 so the software part is probably obsolete but it does cover the physics and algorithms pretty well, at least as far as I can tell. I hope it helps.
They were in Perfect agreement in Jan-Feb, 2008.
Comeon, a very short period of time (7 yrs.) On one end the in-situ renders higher temps, and on the other end the satellite does.
All the rest of the time the agreement is perfect.
Paul J. Trimble and Paul Vaughan: Thanks for the links. The reason I asked, the ERSST.v3b available directly from the NCDC contradicts the IRI data. Here’s one version from the NCDC, with the base years of 1971-2000:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.ocean.90S.90N.asc
And here’s another version, with 1901-2000 as base years:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.ocean.90S.90N.df_1901-2000mean.dat
The ERSST.v3b data available through the KNMI Climate Explorer also agrees with the above.
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
I’ve plotted the KNMI version against the ERSST.v3b data available through the IRI website. It appears IR adds another level of filtering or smoothing that’s not present in the others:
http://i31.tinypic.com/2hf51ft.png
From the article: “Anomalies were computed about the mean annual cycle from data over the whole period of record.”
Could someone who is a climate scientist please explain what is meant by “anomalies” with as much detail as possible? This seems to be either climate science terminology or statistical but it sure is everywhere and after asking a couple of times and searching The InterTubes with The Google I’ve not found out what it means (no pun intended).
Anthony/moderators, maybe you could add the answer to glossary page along with other commonly used climate science jargon. Thanks very much.