Alternate Title Question: Why Are Global Sea Surface Temperatures Falling Short Of IPCC Projections?
INTRODUCTION
In this post I illustrate and discuss the relatively small rise in the Sea Surface Temperature anomalies (SST) of the East Pacific (from pole to pole) since November 1981 (the start of the Reynolds OI.v2 dataset) and the very obvious upward shifts in the Sea Surface Temperature anomalies of the Rest of The World, which is made up of the Atlantic, Indian and West Pacific Oceans, a subset that represents approximately 66% of the surface area of the global oceans. I’ve illustrated the shifts in this subset in an earlier post, but in that post, I corrected the data for volcanic aerosols and smoothed the data with a 13-month running-average filter. I now present the data without the volcano adjustments or smoothing to assure you that these adjustments have not created the effects.
This post also presents the differences between the Reynolds OI.v2 SST data and the IPCC Climate Model Hindcasts/Projections for the satellite-era. The comparisons are for the East Pacific SST anomalies and the SST anomalies of the Atlantic-Indian-West Pacific Oceans.
Note: My usual links to past posts have been updated to my new home at WordPress. Please update your Favorites and Blog Rolls.
For those new to discussions of ENSO (El Niño-Southern Oscillation), refer to the post An Introduction To ENSO, AMO, and PDO – Part 1. And refer to the post An Introduction To ENSO, AMO, and PDO — Part 2 if you are not familiar with the additional multidecadal variability of the North Atlantic Sea Surface Temperatures.
OVERVIEW
I’ve recently added two graphs to my monthly Sea Surface Temperature (SST) anomaly updates. (February 2011 SST Anomaly Update) I first presented the reason for these additions in the post Sea Surface Temperature Anomalies – East Pacific Versus The Rest Of The World. The first of the datasets to be discussed is the East Pacific Ocean from pole to pole (90S-90N, 180-80W), so it also includes the portions of the Arctic and Southern Oceans encompassed by those coordinates. As shown in Figure 1, its SST anomalies mimic NINO3.4 SST anomalies, a commonly used El Niño-Southern Oscillation (ENSO) proxy. Keep in mind when viewing the variations in SST anomalies in that graph that the East Pacific data represents approximately 33% of the global oceans. (The percentage is based on the NCEP/DOE Reanalysis-2 “Land Mask” data available through the KNMI Climate Explorer).
http://i53.tinypic.com/2zi4ig2.jpg
Figure 1
The second is the Rest of the World, from pole to pole (90S-90N, 80W-180), which is made up of the Atlantic, Indian, and West Pacific Oceans (and corresponding portions of the Arctic and Southern Oceans). The SST anomalies for this portion of the globe have risen in steps in response to the significant El Niño events of 1987/88 and 1997/98. What differentiates these ENSO events from others is that both were significant El Niño events that were followed by major La Niña events. They also were not counteracted by an explosive volcanic eruption, which happened in 1982 when the eruption of El Chichon suppressed the global response to the 1982/83 El Niño event. In Figure 2, I’ve added period average data to highlight the upward steps in the data. Note also that it appears this portion of the globe is preparing to make another upward step in response to the 2009/10 El Niño and 2010/11 La Niña.
http://i51.tinypic.com/1zmf3ev.jpg
Figure 2
But as you will note in the title blocks of those two graphs, the data has been adjusted for volcanic aerosols and it has been smoothed with 13-month running-average filters.
WHAT DOES THE DATA LOOK LIKE WITHOUT THE ADJUSTMENTS?
Figure 3 illustrates the East Pacific SST anomaly data without the Volcano-adjustment and smoothing. The ENSO variations in this dataset are very strong. The trend, on the other hand, is quite low, at only 0.21 deg C per Century.
http://i54.tinypic.com/24goojk.jpg
Figure3
The SST anomalies for the Rest of the World, which is made up of the Atlantic, Indian and West Pacific Oceans from pole to pole (90S-90N, 80W-180), has a significant trend, Figure 4. A trend line on global temperature data tends to give the illusion of continuous rise with noise caused by ENSO and volcanic eruptions, but the two upward shifts in the data are still easy to discern, even with the trend line in Figure 4.
http://i52.tinypic.com/10mtxty.jpg
Figure 4
I tried a number of ways to illustrate those upward steps while preparing this post. One of things I considered: I did not want to be accused of cherry-picking start and end dates of the periods before, between, and after the upward shifts. With that in mind, the way that seemed best was to delete the data during the years in which the Rest of the World SST anomalies were responding to the evolution and decay of the 1987/88 and 1997/98 El Niño events. In Figure 5, the full term of the Atlantic, Indian and West Pacific SST anomaly data is shown in the background, in royal blue. Then the data is divided into three periods. The first, in green, is the period before the response to the 1987/88 El Niño, and it runs from the start of the dataset, November 1981, to December 1986. Recall that the 1982/83 El Niño was counteracted by the El Chichon eruption during that period. The years of 1987 and 1988 are excluded. The mid-period data, green, runs from January 1989 to December 1996. It contains the dip and rebound from the Mount Pinatubo eruption. The years El Niño evolution and decay years of 1997 and 1998 are excluded. The final period, light blue, includes the data from January 1999 to December 2008. The data from January 2009 to present is also excluded, since the Atlantic, Indian and West Pacific SST anomaly data appears to be rising in another step in response to the combined 2009/10 El Niño and 2010/2011 La Niña. Note that the mid and late period subsets both start and end during La Niña events.
I’ve also added trend lines for the three periods in Figure 5. The trends are basically flat. In other words, without the El Niño-induced rises in 1987/88 and 1997/98, there would be little to no trend in the Atlantic, Indian and West Pacific SST anomaly data. It’s really tough to miss the upward steps, once you know they exist. There are links at the end of this post to past posts that discuss the processes that cause these upward shifts.
http://i56.tinypic.com/2gumy3o.jpg
Figure 5
MODEL-DATA COMAPRISONS
The KNMI Climate Explorer Monthly scenario runs webpage allows users to plot the outputs of the IPCC AR4 climate models collected and archived by the Program for Climate Model Diagnosis and Intercomparison (PCMDI). I used the first selection on the table, “all members”, 20c3m / sresa1b, which is a combination of the 20C3M hindcast for the 20th Century and the SRES A1B projections for the 21st Century. And while there are 54 ensemble members shown on the selection table, the output for TOS included 32 of them. I cross checked the mean of these runs against the third selection provided by KNMI, “multi-model mean,” and the differences were insignificant. The linear trend differences for the datasets I’m using were less than 0.01 degree C per Century, so in the future, I’ll save some time and use the “multi-model mean”. The designation “TOS” is Sea Surface Temperature. If memory serves me well, the difference between TOS and SST in the IPCC models is how sea ice is handled.
Figure 6 compares the Reynolds OI.v2 SST data and the mean of the IPCC Hindcasts/Projections for TOS anomalies for the Atlantic-Indian-West Pacific ocean, using the coordinates of 90S-90N, 80W-180. The linear trends are remarkably similar. The trend of the IPCC hindcast/projection is about 9% higher than that of the SST data. Not bad at first glance. However, as shown in Figure 5, between significant ENSO events, the linear trends for this portion of the global oceans are basically flat. The IPCC assumes the Sea Surface Temperatures for this part of the globe rise in response to anthropogenic forcings, where the satellite-based SST data since 1982 indicates they rise in response to significant ENSO events and do not rise between those ENSO events.
http://i53.tinypic.com/2v17o5d.jpg
Figure 6
The portion of the global oceans where the IPCC hindcasts/projections truly fail is the East Pacific. Keep in mind that this dataset represents about 33% of the surface area of the global oceans. As shown in Figure 7, the IPCC hindcasts/projections for the East Pacific are approximately 1.32 deg C per Century, which is in line with the 1.41 deg C per Century for the Rest of the World oceans, Figure 6. But the satellite-based SST data only shows a linear trend of 0.19 deg C per Century. The linear trend of the IPCC hindcast/projections is more than 7 times higher than the SST data trend for 33% of the global ocean surface area. The IPCC assumes that anthropogenic forcings will cause the rise in Sea Surface Temperatures for the East Pacific to be similar to that of the Atlantic, Indian, and West Pacific Oceans. They clearly erred with this assumption.
http://i51.tinypic.com/64qo3n.jpg
Figure 7
BUT SST ANOMALIES RESPOND TO VOLCANIC AEROSOLS
One of the arguments I am anticipating is that the Reynolds OI.v2 SST data for the Atlantic, Indian, and West Pacific Oceans clearly responds to the Mount Pinatubo eruption. This is obvious with the dip and rebound starting in 1991 and ending about 1994. This may seem to some to be proof that the forcings used by IPCC Climate Models are what dictates the rise in sea surface temperature. Unfortunately that train of thought fails to consider the differences in the forcings. Volcanic aerosols reduce the amount of Downward Shortwave Radiation (visible light) that reaches and enters the oceans, and sea surface temperatures decrease in response. But anthropogenic greenhouse gases increase the amount of Downward Longwave Radiation (infrared radiation), not Downward Shortwave Radiation, and there is a significant difference between the two forcings. Downward shortwave radiation from the sun reaches depths of a couple hundred meters, decreasing in intensity with depth, but downward longwave radiation from greenhouse gases only impacts the top few millimeters of the oceans. It has been argued that most if not all of the effects of downward longwave radiation are released by the oceans through evaporation.
CLOSING
Smith and Reynolds (2004) Improved Extended Reconstruction of SST (1854-1997)] stated about the Reynolds OI.v2 data, “Although the NOAA OI analysis contains some noise due to its use of different data types and bias corrections for satellite data, it is dominated by satellite data and gives a good estimate of the truth.” The truth is a good thing. Unfortunately, the IPCC hindcasts/projections show little evidence of “a good estimate of the truth,” for the East Pacific SST anomalies or for the Atlantic-Indian-West Pacific data.
Links to further illustrations and to discussions of the processes that cause the upward shifts in SST anomalies follow.
FURTHER DISCUSSIONS
My first post about the multiyear aftereffects of significant ENSO events was the November 6, 2008 post Another Look at the Saw-Tooth Trends in the Indian Ocean.
The multiyear aftereffects were then discussed in the two-part post Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1 and Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2.
And for those who like visual aids, refer to the two videos included in:
La Niña Is Not The Opposite Of El Niño – The Videos
The impacts of these El Nino events on the North Atlantic are discussed in:
There Are Also El Nino-Induced Step Changes In The North Atlantic
And:
Atlantic Meridional Overturning Circulation Data
More detailed technical discussions can be found here:
More Detail On The Multiyear Aftereffects Of ENSO – Part 1 – El Nino Events Warm The Oceans
And:
And:
SOURCE
The Reynolds OI.v2 SST data is available through the KNMI Climate Explorer Monthly Observations webpage, and the IPCC climate model outputs (hindcasts and projections) are available through their Monthly Scenario Runs webpage.
Bob Tisdale - Climate Observations 
Hi Bob:
All kinds of comments here.
First, I guess you know your Figure 5 has gone missing.
Second, I’ve been playing games with sea-air heat transfer and have concluded that a disproportionate amount of it occurs at the Equator, particularly during El Niño events. I suspect that the difference between SST trends in the E Pacific and the other oceans may have something to do with this, but so far it’s just a suspicion.
Third, as you correctly note there’s no significant difference between surface air and sea surface temperature trends in the model simulations. But according to observations mean global surface air temperature has risen by about 0.3C relative to mean global SST since 1982. The fact that the models can’t replicate this differential suggests that they don’t correctly simulate sea-air heat transfer, which if so would be a major defect.
Fourth, the models show a downward spike in SST after the Pinatubo eruption, but there are some problems with this result too. For example, the effects of Pinatubo were supposedly global, so why isn’t the spike visible in the East Pacific record? And why does the similar spike in the model simulations generated by the 1982 El Chichón eruption (not all of it is visible on your graphs) coincide with an increase rather than a decrease in global SST? And where’s the volcanic eruption that caused the downward SST spike in 2008? The question here is whether we can even identify the impacts of volcanic eruptions from temperature records. (One way of checking is to break out the short-term variations in the SST record by subtracting long-term averages from monthly means, and then look at the results to see whether you can pick volcanic cooling episodes out of the noise. You can’t. They’re indistinguishable from other short-term variations.) The point here is that the models must either simulate all of the factors that cause short-term variations or none of them. Models that simulate only the impacts of volcanic eruptions – and probably incorrectly at that – will give distorted results.
Fifth, I would therefore be leery of trying to “correct” temperature records for volcanic impacts, because I’m not sure it can be done.
Sixth and finally, although it’s widely claimed that climate models do a good job of hindcasting the historic temperature record, there are in fact numerous disconnects between model simulations and regional observations over and above the ones you show. Comparing the KNMI model data against Arctic surface air temperatures should give you a really good one.
Roger: Thanks for letting me know that Figure 5 had disappeared. I had no idea that tinypic had “misplaced” it. That’s happening more frequently now. I upload them. They exist for a few days. Then they disappear. I don’t know why they disappear, but they do.
Regarding volcano adjustments, here’s a link to a revised version of the East Pacific vs Scaled NINO3.4 SST anomaly comparison (Figure 1), but in it, there’s no volcano adjustment. If you were to cycle between the two graphs, you can see how it could be argued both ways whether the volcano adjustment is required.
Without the adjustment, the response of the East Pacific to the 1982/83 El Nino appears to fall short when compared to the 1997/98 El Nino. But then, with the adjustment, the East Pacific data appears to overcompensate for the 1991/92 El Nino–or does it? There’s also an overshoot during the lesser El Nino events in the 2000s.
And of course, the Atlantic-Indian-West Pacific data does appear to need the adjustment.
Thanks again for letting me know about Figure 5.
Regards
Hi Bob,
Your analysis is very interesting. I would like to point out that there is an error in it, which I guess does not affect your conclusion: in Figures 3 – 6 you plotted monthly values so it seems, hence in the trendline equation y = ax + b, factor a should be multiplied by 120 to get the decadal trend and not multiplied by 10 as you did. Is this correct?
Regards
JR: The data is monthly, but trend value in the equation presented by EXCEL is on a yearly basis.
Roger Andrews wrote:
“Third, as you correctly note there’s no significant difference between surface air and sea surface temperature trends in the model simulations. But according to observations mean global surface air temperature has risen by about 0.3C relative to mean global SST since 1982. The fact that the models can’t replicate this differential suggests that they don’t correctly simulate sea-air heat transfer, which if so would be a major defect.”
Why 1982?
Steve Case says: “Why 1982?”
That’s the start year (actually Nov 1981) of the Reynolds OI.v2 SST dataset used in this post.
Regards
I’m interested in this topic and have done some investigation with data that’s available to the public and depending on which one you use, the start dates are 1850, 1880 and 1978.
So I was wondering why 1982 was used.
Here’s some graphs I’ve generated:
They all illustrate that the land temperature or air temperature is gaining on sea surface temperature by a noticable amount.
I’m wondering if that samll change whether it’s 0.3° since 1982 or 0.25° since 1880 is the signature of the increased co² in the atmosphere.
Atlantic region more dynamic due to THC?
Steve Case: I wrote a post a few months ago in which I removed the effects of natural variables since 1982 (the start of the satellite era for Sea Surface Temperature).
Natural factors represented about 85% of the warming.
I wrote a follow-up post that dicussed a few other items and came up with a range of about 70% to 90% for the natural warming since 1982:
Steve Case:
Good work! The periodicity in air temperature-minus-SST on your last graph is undoubtedly real, and it’s important because it shows a) that SSTs aren’t valid long-term air temperature proxies and b) that we don’t understand how sea-air heat transfer works. Certainly climate models can’t replicate the effect.
I recently did a post on this over at http://tallbloke.wordpress.com/2011/02/17/roger-andrews-the-solar-sst-relationship-part-ii/. Turns out that the SAT-SST periodicity is closely correlated with a 110-year solar cycle.
Bruce says: “Atlantic region more dynamic due to THC?”
In theory, yes, but I have yet to find evidence of, for example, SST or OHC anomalies moving from the South Atlantic to the North Atlantic.
It’s the first ocean basin (outside of the eastern Pacific) to be impacted by ENSO through the associated changes in atmospheric circulation, with the Tropical North Atlantic receiving a good portion of it. And then there’s feedback from the additional sea ice melt in the far North Atlantic, during the summer and early fall after an El Nino. Atlantic Meridional Circulation slows during a strong El Nino. Lots of factors that all work togther.
Roger Andrews wrote:
The periodicity in air temperature-minus-SST on
is undoubtedly real, and it’s important because it shows a) that SSTs aren’t valid long-term air temperature proxies and b) that we don’t understand how sea-air heat transfer works. Certainly climate models can’t replicate the effect.”
I’m dealing with folks who believe that oceans follow the change in air temperature. I rather think it’s the other way around.
Yes, the shape of the line snaking across that graph above does not look like the result of random chance. There’s something going on that we don’t understand.
Bob:
If Steve Case and I are right, and SSTs and surface air temperatures really do oscillate around each other (with an amplitude of 0.6C and a period of 110 years, according to my data) then current assumptions as to how sea-air heat transfer works are invalid. Since this is potentially a big deal, I was wondering if you would care to comment?
Roger Andrews says: “If Steve Case and I are right, and SSTs and surface air temperatures really do oscillate around each other (with an amplitude of 0.6C and a period of 110 years, according to my data) then current assumptions as to how sea-air heat transfer works are invalid. Since this is potentially a big deal, I was wondering if you would care to comment?”
I’ll start with a question. When you say, “SSTs and surface air temperatures really do oscillate around each other ,” are you comparing SST to Marine Air Temperature or SST to Land Plus Sea Surface Temperature? If it’s SST versus Marine Air Temp, I’d find your observations surprising and I’d want to know the two datasets you’re working with. If it’s SST versus Land Plus Sea Surface Temperatures, shouldn’t the land plus sea surface temperatures have greater variability?
You continued, “…then sea-air heat transfer works are invalid.”
Are you looking at temperature anomalies or absolute temperatures?
I generated the graph from this website:
http://www.ncdc.noaa.gov/cmb-faq/anomalies.html
by plotting the difference between these two data sets:
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/annual.ocean.90S.90N.df_1901-2000mean.dat
ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/annual.land.90S.90N.df_1901-2000mean.dat
It’s a relatively simple idea, I’m interested in the gradient that exists between sea surface and the atmosphere and how it changes over time.
Bob Tisdale mentions marine air temperature. I should very much like to know if there’s a data file available for public use that documents global marine air temperatures.
One would think that when they threw that canvas bucket over the side that they would have taken the air temperature at the same time. I’d love to see the data.
Bob:
I’m comparing a number of different data sets, almost all of which show the +/- 10-year SST-SAT periodicity.
It’s visible when I compare either the GISS “meteorological station only”, the NCDC Smith et al. or the Lugina surface air temperature series with any one of the following SST series:
ICOADS
HadSST1
NCDC v3b ERSST
Kaplan
It’s also plainly visible when I compare GISS met, NCDC or Lugina against HadSST2 with the 1946 “Thompson discontinuity” removed.
It’s also visible when I compare the HadMAT marine air temperature series against ICOADS, HadSST2 and NCDC V3b.
I don’t compare SST series with “land+ocean” series such as HadCRUT3 and GISS LOTI. Such comparisons aren’t meaningful because the land+ocean series are about 70% derived from the SST series. I also don’t compare SST series with “land” series such as CRUTEM3 because these series also include SST data projected into land areas, particularly in the SH.
Air temperatures do show more short-term variability than SSTs, but this isn’t relevant to long-term periodicity.
I work with temperature anomalies, but if I used absolute temperatures all that would happen is that the SST-SAT difference plot would shift up or down the scale. The shape wouldn’t change.
Steve Case says: “Bob Tisdale mentions marine air temperature. I should very much like to know if there’s a data file available for public use that documents global marine air temperatures.”
ICOADS Marine Air Temperature and the Hadley Centre’s MOHMAT 4.3 datasets are available through the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Roger Andrews: I’ll be interested in seeing the results whe you post them.
Regards
Bob
Bob:
I referenced 18 different comparisons in my comment above, and I think posting 18 separate graphs would be a bit much. And if you wanted the whole story I would have to post thirty or forty. :- (
But if you want to see what these 18 comparisons look like all you have to do is take Steve Case’s graph (http://i52.tinypic.com/24v5umd.jpg), detrend it and multiply it by 18, because this is pretty much what they all look like.
Steve Case:
Comparing GISS surface air temperatures (http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt) with ICOADS SSTs (http://jisao.washington.edu/data/global_sstanomts/sstglobalanom18452008) will give you some interesting results. 😉
Roger wrote:
“Comparing GISS surface air temperatures (http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt) with ICOADS SSTs (http://jisao.washington.edu/data/global_sstanomts/sstglobalanom18452008) will give you some interesting results. ”
Yes, same sort of thing, here it is:
Didn’t show up with my html skills here’s the URL
Bob
Thanks for the KNMI Climate Explorer link, now if I can figure out how to get information out of it, everything should be just grand.
Steve Case says: “Thanks for the KNMI Climate Explorer link, now if I can figure out how to get information out of it, everything should be just grand.”
Refer to:
Steve:
Your ICOADS minus GISSmet graph is exactly what I got.
If you throw out the spike between 1940 and 1946 (it’s a spurious effect caused by wartime distortions in the SST record) you will be able to fit the plot very closely (R > 0.9) using a sine wave with a period of 110 years and an amplitude of 0.63C.
I don’t think this periodicity is an artifact of biases in the data sets a) because a highly improbable combination of cyclic bias effects would be necessary to explain it and b) because the periodicity remains visible when we compare SAT series with “corrected” SST data series that (supposedly at least) remove biases from the SST record. Your earlier NCDC comparison is an example.
The periodicity also isn’t just a global effect. It’s detectable in the NH, the SH and the Atlantic/Indian and Pacific oceans, and also when we compare SST series with “ocean” and “land” SAT data.
In short, it’s hard to escape the conclusion that the periodicity is real.
Bob:
Seems to me that this reinforces the comments you make about the poor job climate models do of replicating marine observations. You note that they can’t replicate SST trends, and to this you can now add that they don’t replicate SST-SAT periodicity either. According to the models SST and SAT in fact march in lockstep, and subtracting one from the other gives a straight line.
Roger Andrews wrote:
“In short, it’s hard to escape the conclusion that the periodicity is real.”
Jumped out unexpectedly at me when I made that first graph. “Wow!” I said:
But what I was interested in and I still am is the upward trend of a little over 0.2°C over the past 130 years. I’m wondering if that’s CO2’s signature after negative feedbacks get done with the calculated climate sensitivity of 1.2°C per doubling.
Steve:
The 0.2C gradient you see has nothing to do with CO2. It’s purely an artifact of the “corrections” NCDC applies to the ICOADS SST record. (If you subtract ICOADS from NCDC you will find that NCDC has actually applied a 0.6C net cooling adjustment to ICOADS, not a 0.2C adjustment.) This is why your NCDC comparison shows air temperatures warming overall relative to SSTs while your ICOADS comparison doesn’t.
Roger.
I get the same result from CRUTEMP
I expect you to say the same thing though.
Steve:
HadSST2 vs. CRUTEM3 actually isn’t a meaningful comparison for two reasons:
1. HadSST2 contains an invalid adjustment that shifts the entire series artificially downwards by 0.3-0.4C after 1945 (you can see it in your graph, and it really sticks out when you subtract HadSST2 from GISSmet). This adjustment was in fact identified as invalid three years ago, but it’s still not been removed (see http://www.atmos.colostate.edu/ao/ThompsonPapers/Thompson_etal_Nature2008.pdf)
2. CRUTEM3 is an apples-and-oranges concoction of heavily-tweaked SATs and SSTs. Any resemblance between it and actual surface air temperature trends over land is coincidental.
So yes, I guess I did say the same thing, but in this case I said it twice.
Thanks for the link.
I do remember this from a few years back and I looked up the reference from your link:
Folland & Parker, Correction of instrumental biases in historical sea surface temperature data 1995
http://onlinelibrary.wiley.com/doi/10.1002/qj.49712152206/abstract
The abstract says:
“The corrections are based on models of heat and moisture transfers from uninsulated (canvas) and partially insulated (wooden) sea temperature buckets exposed on deck.”
“The corrections are compatible with recent measurements made at sea of the errors of canvas buckets.”
“The corrections are fairly insensitive to uncertainties such as the size of the bucket or the details of its exposure on deck.”
I love it, “Based on models” it says. But they did make some measurements at sea. I wonder how thorough that was. And of course the caveat about being “insensitive to uncertainties” And as I recall, if the corrections were made it would push historically recent sea surface temperatures up.
Well, no one likes to have their pet theories pooh poohed, and I’m no different. It fit so well with comments such as those made in this recent popular editorial:
http://opinion.financialpost.com/2011/04/07/climate-models-go-cold/
“Climate Models go Cold”
…
“The climate models amplify the carbon dioxide warming by a factor of three — so two-thirds of their projected warming is due to extra moist air (and other factors); only one-third is due to extra carbon dioxide.”
So I am stuck with data that tells me that sea surface and air temperatures go up and down together more or less maintaining a temperature constant gradient between them and somehow the CO2 greenhouse effect is layered on top of all that.
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