Guest Post by Bob Tisdale
The topic of discussion is their new sea surface temperature dataset, ERSST.v4. Based on a breakpoint analysis recently promoted by RealClimate, NOAA appears to have reduced the early 20th Century warming rate to agree with the climate models used by the IPCC.
PRELIMINARY NOTES
NOAA introduced its new and improved sea surface temperature reconstruction ERSST.v4 with the papers (both are paywalled):
- Huang et al. (2014) Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4), Part I. Upgrades and Intercomparisons, and
- Liu et al. (2014) Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4): Part II. Parametric and Structural Uncertainty Estimations.
We provided an initial look at the new NOAA ERSST.v4 data, primarily during the satellite era, in the post Quick Look at the DATA for the New NOAA Sea Surface Temperature Dataset. An error was discovered in the November 2014 update of the ERSST.v4 sea surface temperature data supplied by NOAA…a teething problem with the update of a new dataset at NOAA. Subsequent to the correction, KNMI added the new ERSST.v4 dataset to the Monthly observations webpage at their Climate Explorer. After NOAA corrected the error, the new ERSST.v4 data fell back in line with their predecessor ERSST.v3b during the satellite era (November 1981 to present), which means they have a slightly higher warming rate than the NOAA Reynolds OI.v2 satellite-enhanced data.
Regarding the breakpoint years that divide the data into warming versus hiatus/cooling periods in this post, I’ve initially used 1912, 1940 and 1970 from the RealClimate post Recent global warming trends: significant or paused or what? Yes, I realize those breakpoints are controversial. See the BishopHill post Significance doing the rounds. And I also understand (1) those breakpoints are based on GISS land-ocean temperature index (LOTI) data, which includes the ERSST.v3b data, (2) that the breakpoint years are not based on the individual sea surface temperature datasets, and (3) that the breakpoints might change if GISS used the ERSST.v4 data. My use of these breakpoints does not mean I agree with them. I’m simply using them to avoid claims that I’ve cherry-picked them, and to show the impacts of breakpoint years on model-data comparisons.
The headline and initial discussions in this post are based on those 1912, 1940 and 1970 breakpoints. If we were to revise those changepoints to 1914, 1945 and 1975, also determined through breakpoint analysis of GISS LOTI data, then the warming rate of the new ERSST.v4 data during the early warming period of 1914 to 1945 falls back in line with the other sea surface temperature datasets, well above the trend simulated by climate models. We’ll illustrate this also.
I’ve excluded the polar oceans from the data presented in this post. That is, the data are for the latitudes of 60S-60N. This is commonly done in scientific studies because the data suppliers (NOAA and UKMO) account for sea ice differently. See Figure 8 from Huang et al. (2014) for an example.
Unless otherwise noted, anomalies are referenced to the WMO-preferred base years of 1981-2010.
The data and climate model outputs are available through the KNMI Climate Explorer.
For many of the illustrations, as opposed to adding the climate model outputs to the graphs, I’ve simply listed the simulated warming (or cooling) rate of the global sea surface temperatures, excluding the polar oceans, as represented by the multi-model ensemble-member mean of the climate models stored in the CMIP5 archive (historic and RCP8.5 forcings). The worst-case RCP8.5 forcings only impact the last few years and have little impact on the results for the recent warming period. For simulations of sea surface temperatures, there are also more ensemble members (model runs) using the RCP8.5 scenario (73 members) than there are with the RCP6.0 scenario (43 members). Additionally, see the post On the Use of the Multi-Model Mean.
THE EARLY 20th CENTURY WARMING PERIOD (1912-1940)
For years, we’ve been illustrating and discussing how the climate models used by the IPCC do not properly simulate the warming of the surface of the global oceans during the early 20th Century warming period, from the 1910s to the 1940s. They underestimate it by a wide margin. As a reference, Figure 1 illustrates the modeled and observed global sea surface temperature anomalies (60S-60N), without the polar oceans, for the early warming period of 1912 through 1940. Again, those are changepoint years promoted in the recent post at RealClimate. The data are represented by HADSST3 data from the UKMO and by the ERSST.v3b data currently in use by NOAA and GISS. The models are represented by the average of the outputs of the simulations of sea surface temperatures (based on multi-model ensemble-member mean) of the climate models stored in the CMIP5 archive. Those models were used by the IPCC for their 5th Assessment Report.
Figure 1
The observed warming based on the HADSST3 and ERSST.v3b data, from 1912 to 1940, was more than twice the rate simulated by climate models. Because the mean of the climate model outputs basically represents the forced component of the climate models, logic dictates that the additional observed warming was caused by naturally occurring, coupled ocean-atmosphere processes.
With the new ERSST.v4 data, the warming rate has been lowered almost to the modeled rate for the period of 1912 to 1940. See Figure 2 for a comparison of the ERSST.v4 data with the ERSST.v3b and HADSST3 data.
Figure 2
The ERSST.v3b data warming rate for the period of 1912 to 1940 is +0.056 deg C/decade, which is only slightly higher than the modeled rate of +0.048 deg C/decade.
EARLY COOLING PERIOD (1880-1912)
We’ll define the early cooling period as extending from 1880 to 1912. As we can see in Figure 3, the cooling rate of the new ERSST.v4 data is comparable to the ERSST.v3b data currently used by NOAA…both of which are slightly faster than the cooling rate shown by the HADSST3 data. Of course, the models show a slight warming during this period.
Figure 3
The models don’t simulate the warming from 1912 to 1940 shown by the ERSST.v3b and HADSST3 data because they don’t simulate the cooling from 1880 to 1912. But that doesn’t help to explain the slower warming rate of the ERSST.v4 data during the early-20th Century warming period. We’ll return to that discussion in a little while.
MID-20th CENTURY HIATUS (1940-1970)
The new ERSST.v4 data for the global oceans (without the polar oceans), for the period of 1940 to 1970, are compared to the ERSSTv3b and HADSST3 data in Figure 4. Where the ERSST.v3b data showed a very slight warming during this period, the ERSST.v4 data now show cooling…agreeing better with the models and the HADSST3 data.
Figure 4
LATE WARMING PERIOD (1970-2014)
As shown in Figure 5, the revisions to the ERSST.v4 data have increased the sea surface warming to a rate that is slightly higher than the ERSST.v3b data during the period of 1970 to present, but the ERSST.v4 data still has a slightly slower warming rate than the HADSST3 data. And, of course, the models show a slightly higher warming rate than the observations. We would expect the models to perform best during this period, because some of the models are tuned to it.
Figure 5
LONG-TERM WARMING RATES
Figures 6, 7 and 8 present the long-term global sea surface warming rates (without the polar oceans) of the new ERSST.v4 data and the ERSST.v3b and HADSST3 data, starting in 1854 (full term of the data), 1880 (full term of the GISS and NCDC combined land+ocean data) and 1900 (start of the 20th Century, give or take a year, depending on how you define it). The data in all have been smoothed with 12-month running-mean filters. The trends shown are based on the raw data.
Figure 6
# # #
Figure 7
# # #
Figure 8
As an afterthought, I’ve included a comparison starting in 1915 (the last 100 years). See Figure 8.5. The models, of course, underestimate the warming because they can’t simulate the cooling that took place from the 1880s to the 1910s.
Figure 8.5
YOU MAY BE WONDERING…
How did NOAA manage to decrease the warming rate of its ERSST.v4 data during the early warming period, while maintaining long-term trends that are comparable to the other datasets?
NOAA resurrected the spike in the late-1930s and early-1940s. See Figure 9. The data have been smoothed with a 61-month running-mean filter to minimize the ENSO- and volcano-related volatility. The 61-month filter also helps to emphasize that spike in sea surface temperatures.
Figure 9
Figure 10 presents the three sea surface temperature datasets, for the period of 1854 to present. Again, all data are smoothed with 61-month filters. For the new ERSST.v4 data, NOAA severely limited the warming from the early-1910s until the mid-1930s and then added an unusual sudden warming.
Figure 10
I’ve included the ICOADS source data to the graph in Figure 11. Compared to the ERSST.v3b and HADSST3 data, NOAA appears to have suppressed the pre-1940 “Folland correction” in its ERSST.v4 data. See Folland and Parker (1995) Correction of instrumental biases in historical sea surface temperature data.
Figure 11
Animation 1 compares the new ERSST.v4 and HADSST3 data, for the period of 1854 to present, with both datasets smoothed with 61-months filters. The UKMO Hadley Centre has worked for decades to eliminate the spike in the late-1930s and early-1940s. NOAA, on the other hand, has enhanced it. (Note: If the animations don’t show on your browser, please click the link. Recently, there has been a problem with gif animations on my WordPress posts.)
Animation 1
THE SPIKE LIKELY COMES FROM A NEWER MARINE AIR TEMPERATURE DATASET THAT IS USED AS A REFERENCE FOR THE NEW ERSST.v4 DATA
Sea surface temperature source data for the older ERSST.v3b data are adjusted before 1941 using an older version of nighttime marine air temperature data, like the one shown in Figure 12. This would help to explain the agreement between those two datasets during the period of 1912 to 1940.
Figure 12
One of the features of the new ERSST.v4 data is the use of a newer and improved UKMO nighttime marine air temperature dataset. (It’s not available through the KNMI Climate Explorer, so I can’t include it in a comparison graph.) The source sea surface temperatures for the new ERSST.v4 data are adjusted for the full term by the new nighttime marine air temperature data, not just prior to 1941 like ERSST.v3b.
Huang et al. (2014) includes:
Firstly, ERSST.v3b does not provide SST bias adjustment after 1941 whereas subsequent analyses (e.g. Thompson et al. 2008) have highlighted potential post-1941 data issues and some newer datasets have addressed these issues (Kennedy et al. 2011; Hirahara et al. 2014). The latest release of Hadley NMAT version 2 (HadNMAT2) from 1856 to 2010 (Kent et al. 2013) provided better quality controlled NMAT, which includes adjustments for increased ship deck height, removal of artifacts, and increased spatial coverage due to added records. These NMAT data are better suited to identifying SST biases in ERSST, and therefore the bias adjustments in ERSST version 4 (ERSST.v4) have been estimated throughout the period of record instead of exclusively to account for pre-1941 biases as in v3b.
I suspect the newer nighttime marine air temperature data and its use as a reference for the full term are the reasons for the delayed warming from the early 1910s to the late 1930s and the trailing sudden upsurge in the ERSST.v4 data in the late 1930s.
SUPPOSE WE USED DIFFERENT BREAKPOINT YEARS
It is pretty obvious that the late-1930s to mid-1940s spike in the ERSST.v4 sea surface temperature data would impact the trends of the early-20th Century warming period and the mid-20th Century hiatus period, depending on the years chosen for analysis.
For my book Climate Models Fail, I used the breakpoints of 1914, 1945 and 1975. The changepoints of 1914 and 1945 were determined through breakpoint analysis by Dr. Leif Svalgaard. See his April 20, 2013 at 2:20 pm and April 20, 2013 at 4:21 pm comments on a WattsUpWithThat post here. And for 1975, I referred to the breakpoint analysis performed by statistician Tamino (a.k.a. Grant Foster).
As you might have suspected, because of that spike in the new ERSST.v4 data, using the 1914, 1945 and 1975 breakpoint years does have a noticeable impact on some of the warming and cooling rates.
For the early cooling period, nothing’s going to help the climate models. The models cannot simulate the cooling if we define that period by the years 1880 to 1914. See Figure 13.
Figure 13
The revised breakpoints have a noticeable impact on the early warming period. See Figure 14. Using 1914 to 1945, the warming rate of the new ERSST.v4 data is slightly lower than that its predecessor and in line with the HADSST3 data…and more than 3 times faster than modeled.
Figure 14
NOTE: With that spike, the warming rates of the new ERSST.v4 data during the early-20th Century warming period depend very much on the choice of end year…while the changes in trends are not as great with the ERSST.v3b and HADSST3 data. Refer again to Figures 2 and 14.
With the breakpoint years of 1945 to 1975, Figure 15, the warming rate of the new ERSST.v4 data is considerably lower than the ERSST.vb data, almost flat, during the mid-20th Century hiatus, but not negative (cooling) as shown by the HADSST3 data and the models.
Figure 15
Last but not least, with the 1975 breakpoint, Figure 16, the warming rates of the ERSST.v3b and ERSST.v4 data are basically the same for the recent warming period, which are less than the HADSST3 data, and in turn, less than the modeled rate.
Figure 16
MODEL-DATA DIFFERENCE
Animation 2 includes 2 graphs that show the differences between the modeled and observed sea surface temperature anomalies for the period of January 1880 to November 2014. The model outputs and data are referenced to the period of 1880 to 2013 so that the results are not skewed by the base years. The models are again represented by the multi-model ensemble-member mean of the models stored in the CMIP5 archive (historic/RCP8.5 forcings). And the differences are created by subtracting the data (HADSST3 and ERSST.v4) from the model outputs. The rises from a negative difference (data warmer than models) in 1880 to the substantial positive difference (data cooler than models) in 1910 are caused by the observed cooling that can’t be explained by the models. NOAA tries to recover from that dip in global sea surface temperatures with a sudden upsurge in the late 1930s to early 1940s, which creates the odd looking spike in the ERSST.v4 data.
Animation 2
That spike in the new ERSST.v4 data cannot be explained by the models and stands out like a sore thumb.
CLOSING
Quite remarkably, if the breakpoint years of 1912, 1940 and 1970 are used, the warming and cooling rates of the CMIP5 models and the new NOAA ERSST.v4 sea surface temperature dataset agree reasonably well for the early and late warming periods and for the mid-20th Century hiatus period. That’s three out of four periods. See Figures 2, 4 and 5. On the other hand, if the breakpoint years of 1914, 1945 and 1975 are used, the models can only simulate the warming after 1975 shown in the new ERSST.v4 data. See Figures 13 through 16. During the period of 1945 to 1975, the ERSST.v4 data are closer to the models, which show a slight cooling. Prior to that, with the ERSST.v4 data, the models fail miserably at simulating the cooling of global sea surfaces from 1880 to 1914 and the rebound from 1914 to 1945.
When NCDC starts to include the new ERSST.v4 data in its combined land+ocean surface temperature data, and if GISS uses it, we’ll have to keep an eye on the breakpoints used by climate scientists in their model-data comparisons. In an effort to make models appear as though they can simulate global surface temperatures, I suspect we’ll see breakpoints that flatter the models…and all sorts of arguments about those breakpoints.
Then again, they can argue all they want, but the models still can’t explain that curious spike in the ERSST.v4 data. See Animation 2.
Happy New Year, Bob!
And thanks for the database excursion. Food for thought.
“Has NOAA Once Again Tried to Adjust Data to Match Climate Models?”
Of course! The left lives by the lie and the ignorance of those who support them.
But, Happy New Year, anyway!
I appreciate the work that people like Watts, Tisdale and Eschenbach perform for this site. Their constant focus on data quality and meaning, add badly needed ties to reality and sanity for this debate.
I have been paying pretty close attention to the global warming debate (I refuse to use the latest approved names) for 35 years, since sticking my toe into the borehole-measured climate record efforts, and I have two general observations that are constants.
First, models are inadequate to supply unbiased guidance for much of this debate. The modeling community have great regard for themselves and their models despite the fact they they continually have to improve their latest and greatest efforts. I am not saying they should never improve their models; I am saying that history and the current model deficiencies ought to be a source of humility and they are not.
Second, observational data, which should drive the debate, is highly suspect because those in charge of this data keep applying more and more “corrections” many of which seem wrong and suspiciously move the observations in the direction of models and preconceived notions. Every data set contains deficiencies, even the satellite data. The data involved here, whether it be temperature measurements or observations of animal populations, is highly confounded by interpretation, bias, and adjustment.
When one has neither a complete theory nor trustworthy and sufficiently accurate data, one does not have science. I’ll bet 35 years from now that the debate over global warming will be right where it is now.
Happy New Year, all.
kevin,
I can’t agree with you more when you said:
In a sane world, data is king and theory is refined to match the data.
Basby, in the real world, which is not sane, data are the unwashed masses and need to be cleaned up before consuming.
What you describe is what Goober tried to pass off with Obobocare.
Babsy, Modest Proposals are often the best.
Except when there’s opportunity for graft, don’t you think?
Babsy,
Naw, eating children is ever so much more fun.
Never met a leftist that wouldn’t pass up toddler du jour to feed at the public trough. It’s what’s for dinner!
Who said anything about public trough? This is haute cuisine for we the elite I’m talking about here. Have you ever tried to make blanquette de veau with regular old cow meat? I’d rather have deep-fried horsemeat with okra.
Yes, yes! I can see that being an elite makes you blind to the concept of feeding at the public trough. When all you have is a hammer, everything looks like a nail.
If they won’t eat each other, let ’em eat cake I always say.
being more conspiratorial, doesnt work
Depends on the end goal, Mosh.
Mosher, being more conspiratorial is certainly working for the warmist alarmists !!
Ya got data to prove it ?
Bob,
Is it just too early for me on New Year’s Day, or have you gone and confused “changepoint analysis” with linear trend endpoints?
He sets the trap, was it the right bait ?
I can’t tell, still too dizzy from the switch.
Brandon Gates asked: “Is it just too early for me on New Year’s Day, or have you gone and confused ‘changepoint analysis’ with linear trend endpoints?”
There’s no confusion on my part at all, Brandon. Maybe you need to go have a cup of coffee or two.
Bob, that’s definitely true of me today having flubbed some simple addition twice on a different thread. But I did review your post again yesterday and still didn’t find much evidence of any change point analysis as described as recently topical over at RealClimate here: http://www.realclimate.org/index.php/archives/2014/12/recent-global-warming-trends-significant-or-paused-or-what/
They’ve got a real pretty graph of the technique as applied to temperature time series, in this case GISTemp:
http://www.realclimate.org/images//TempCP3.png
What it looks like you’ve done is eyeballed the charts and manually selected endpoints for the purposes of calculating linear trends. Which is not a problem per se, but unless you did the kind of analysis as described by the links above let’s just say that invoking the term “change point” analysis to what you appear to actually have done is somewhat confusing.
The title of your post, Has NOAA Once Again Tried to Adjust Data to Match Climate Models? is even more disorienting. Stokes put his finger on it quite well in this comment: http://wattsupwiththat.com/2015/01/01/has-noaa-once-again-tried-to-adjust-data-to-match-climate-models/#comment-1826353
Enquiring minds are curious for an answer because my sense is that Nick drinks pretty some strong Java relative to me.
Annndd …. while we’re talking about hand-selected linear trends, now that you’ve actually calculated them for some of my own periods of interest you may now be better equipped to handle these two questions I had for you some few weeks ago:
1) Why do the hiatuses from 1890-1915, 1940-1975 and 1998-present each successively have a more positive slope than the last?
2) Why does each hiatus begin and end at a higher temperature than the previous one?
The ranges I specify aren’t exactly what you’ve selected in this post, but they’re close enough to be relevant.
The spike in ocean temperatures is a huge problem for climate science. Huge. It shows that temperatures can change naturally by a large amount in a very short period of time without any change in forcings. or that the data is crap.
Not really. What matters is the long-term increase from 1910 to 2014.
This ^^^ is the result of a failed and broken education system.
And the first irony meter of the year dies in CodeTech’s honor. Hip hip huzzah!
What matters more is that there are no meaningful Global SST data until 2005, and even that is suspect.
The long term increase you speak of is nothing more than a “Settled Science Myth”.
Reg Nelson,
Um … what?
http://climexp.knmi.nl/data/iersstv4_-180-180E_60–60N_n_1p19862005a.png
Ah yes, the last line of defense: cry conspiracy and claim to know what’s really going on without a shred of evidence to support it.
Barry says: “Not really. What matters is the long-term increase from 1910 to 2014.”
In a discussion of anthropogenic versus natural global warming, it’s the cause or causes of the long-term increase in surface temperatures that matter. If climate models cannot explain two-thirds of the warming during the early warming period from the 1910s to the 1940s, there’s no reason to believe that manmade greenhouse gases were the primary cause of the warming from the mid-1970s to present. Simple.
Reg Nelson, I suspect the year 2005 you’ve used is based on ARGO floats, but ARGO floats are used to measure subsurface ocean temperature and salinity, not sea surface temperatures. Sea surface temperatures have been measured reasonably accurately using ship inlets, fixed and drifting buoys (not ARGO) and satellites since the early 1980s. Before then, sea surface temperatures are “reconstructed” primarily from bucket (different types) and ship inlet temperature measurements (with some fixed buoys along the coasts starting in the 1970s if memory serves).
Bob,
Yup, causes. Plural. Complex system here.
Why would you of all people look to a GCM to explain what happened over a period of time when observational data exist? Use the observations to explain what happened when they’re available.
The model runs you reference in this post are intended to project future climate based on a slew of assumptions about unknown future emissions, land use changes, ice sheet dynamics and the ever-unpredictable coupled atmosphere/ocean processes you’re so fond of studying. Based on their hindcast performance between 1860-1910, 1940-1980 and projection performance from 2006 to present, I can with much confidence tell you that they’re not presently going to tell us what AMO, PDO, ENSO and other Os will do with any great fidelity for periods of up to 50 years. For all I would know looking only at the historical record, we’re due 30 more years of pause.
Question I’d be asking if I were you is what then? Over 155 years, the CMIP5 RCP8.2 hindcast + 12 years of projection is 33% higher than ERSSTv4 by my calcs (0.22 K over the estimated observed increase of 0.70 K). What’s your over/under bet for the next 85?
It’s the long-term increase in surface temperatures, and their causes, which matter. Simple.
So why do we use ocean temperatures, instead of air temperatures above the ocean? They are most definitely not the same thing. There can be huge differences between ocean temperature and air temperature.
Why don’t we use the temperature of the ground 6 feet down instead of air temperatures 6 feet up, if we are going to use ocean temperatures at engine inlet depth? And what is the standard engine inlet depth? It changes from ship to ship, so that isn’t any sort of a standard.
It looks to me like “global average temperature” is nothing of the sort. It is a combination of apples and oranges, sold to the market as peaches. And every year they adjust the mix of apples and oranges, to improve the taste of the peaches.
we hear that 2 million readings for ocean pH data, going back 105 years had to be thrown out. Instead what had to be used was only “high quality” data. yet we don’t hear the scientific community saying we need to throw out 150 years of low quality thermometer readings in favor of high quality satellite data.
scientific hypocrisy. use only the data that supports your theory. ignore any other data. it is obvious wrong because it doesn’t match theory.
+1
…and add in a dozen or so “past” adjustments, and different measuring methods, throw out 70 percent of the readings, ignore 30 to 40 percent of the data base and replace with in-filling, and pretty soon you have adequate FUBAR in the data, a necessary ingredient to baking the cake you want.
Hike the Spike to Hide the Decline?
“we hear that 2 million readings for ocean pH data, going back 105 years had to be thrown out. Instead what had to be used was only “high quality” data. yet we don’t hear the scientific community saying we need to throw out 150 years of low quality thermometer readings in favor of high quality satellite data”
This was my take away from the pH story. My holiday wish would be an official audit of all temp data quality from all the data sets. Warps my mind that every ordinary company gets external audits done but the claimed proof for transforming our economy gets a pass on external auditing?
Happy New Years to our host and to all the mods, contributors and wise commentors who continue to educate me. Special thanks to the polite and civil contributors who lead the way in an emotional and politically charged atmosphere. I think I’ve learned the most from these people.
So you trust satellite data more than thermometer readings? Do you realize that satellite data has to be calibrated based on thermometer readings?
so we should throw out both the thermometers and the satellites? and every other piece of measuring equipment on the planet? how else can know the 1 foot ruler you are manufacturing is truly 1 foot long, unless you calibrate it against something you know to be 1 foot long.
I thought satellites were calibrated to On-board platinum RTD’s, not thermometers.
Might want to check that.
Ah Barry you are a little clued out here, satellite data is calibrated based on high altitude balloon measurements not 1 foot off the ground surface measurements (this is actual science where the satellite measurements are independently replicated). Barry could you tell us who is independently replication and verifying the surface data ?
You see Barry surface measurements are only measuring continental weather where as Satellite measurements are measuring climate,
That depends on what you mean with “thermometer readings”. The satellite data is completely independent of any “earthly” thermometer readings. The radiometers are calibrated against
a) An onboard “warm target” which is monitored by a number of Platinum Resistance Thermometers, the mos exact temperature measuring devices existing and:
b) The cosmic microwave background at 2.7 K, the most stable temperature in the universe.
Warps my mind that every ordinary company gets external audits done but the claimed proof for transforming our economy gets a pass on external auditing?
=================
not only companies, but individuals as well. nothing like a notice from the tax man asking to see your books for the past 10 years to make your day. please explain why in 2009, on May 5 you deducted 0.3C, but in 2010 on Jun 7 you added 0.3C. Doesn’t this artificially make it look like your income increased from 2009 to 2010?
Adjusting the data to fit the models is certainly one way to settle the science. I wonder what percentage of the 97% consensus scientists agree that adjusting data to fit models is criminally fraudulent and an affront to the scientific method.
Google “why the blip wigley”. The spike is really important, so important that the scientists involved were desperate to get rid of it. Even so, Wigley was enough of a scientist to wonder why it existed.
First the data: from 1940 to ’45 there was a huge and unexplained excursion of temperature. Then the speculation, what could it be? Then the experiments to confirm or deny the various speculations. Then the explanation.
rgb@duke, have you been out on your boat with a litre (OK, one and three quarter pints) of light oil and/or light oil and surfactant mix? Go on, it’s science, they’ll never arrest you for that… I bet you find the coverage and the effects to be intriguing, especially if you do it in a force 4 wind.
JF
I am probably WAAAY of the mark but the variations are tiny ~ 0.5C but remember the human race in the 40-45’s were involved in probably the largest expenditure of energy for that period of time all over the planet, WWII. Could that have any effect on surface temps? Just asking.
The models can explain anything if you guys would just listen and nod your heads. http://grouchyoldcripple.com/wp/wp-content/uploads/2014/12/more-global-warming.jpg
Clearly and without doubt, that spike is the result of Nazism. I asked some of my friends and they nodded their heads, so my theory passes peer review.
Conclusion: Nazism causes ocean temperature changes on a global level. Because, as everyone knows, in climate science all you have to have is a small stretch of correlation in order to prove 90 TRILLION dollars worth of causation financing.
Clearly and without doubt, that spike is the result of Nazism. I asked some of my friends and they nodded their heads, so my theory passes peer review.
Gee and I only asked myself, nodded my head so mine passed peer review as well! Oh right that’s how Gore does it!
The cooling years 1914-1918 and 1939-1945 match with the years of U-Boat wars (see title at http://www.uboat.net/ ). Maybe that has something to do with measured temperatures.
It’s the ozone from them chargin’ all them batteries… at’s wut caused it.
Perhaps the Kaiser and Hitler had a policy of iron-seeding the oceans to cause global cooling.
More to do with the lack of fishing that was prevented by the navel action allowing fish to multiply and rapidly changing the oceans biodiversity, those extra fish had to eat something.
I’ve wondered if the spike could be connected to the fact that most shipping travelled in convoy 1939-45 (1942-45 for the US). Convoys normally consisted of a number of columns of about 5 ships each. This means that most samples during WW II would have been from water that had ben churned up by sevaral other ships and where surface water was probably mixed with water from deeper layers.
Now that is an interesting hypothesis!
I agree that the apparent surface temperature spike happening during the movement of the greatest convoy and fleet maneuvers in history can hardly be a coincidence. Far more tonnage has moved in the SW Pacific than before or after the WWII period It is far more a measurement of the non-random sampling error that is hidden in the data than it is a reliable indication of the earth’s climate change.
Bob,
This post doesn’t make sense. It is headed:
“Has NOAA Once Again Tried to Adjust Data to Match Climate Models?”
and ends
“Then again, they can argue all they want, but the models still can’t explain that curious spike in the ERSST.v4 data”
So ERSSTv4 has introduced a spike which isn’t in model results and isn’t in HADSST3 (or v3b). How is this adjusting data to match modes?
You would think that climate science and modelling being “mature”, and the collection of good data such a priority after about 1990, that we would see very little significant changes in the climate projections or hindcasts. That all we’d see is tweaking of details.
Such things like the “spike” coming and going say that the analysts are still thrashing around with fundamental parameters, both what they do and what they are.
It still comes down to predictive skill. The “hiatus” disappears only if you agree that in 5 years the global temperatures will be at least 0.2C higher than they are (to account for the lack of rise recently plus the “normal” C02 rise).
But in political circles, 5 years is a lifetime. Lots of unnecessary things can be made to happen that the regular guy wouldn’t be happy about.
I have seen simmilar gaps in some sea data – thought to be due to WW2 machinations. Failing to take this into account when formatting data will produce all sorts of weird outcomes.
WW II must definitely have had some effect on ocean chemistry and life in the ocean. For example ocean life is often iron-limited. 1939-45 more than 30,000,000 tons of merchant shipping alone was sunk into the oceans. Including warships the total must have been at least 35,000,000 tons. That is actually about 70 kilos per square kilometer of ocean. Also many millions of tons of other metals and organics from the contents of the ships, plus who knows how many million tons of metal, organics and nitrogenous compounds from aircraft, bombs, rockets, torpedoes, depth charges, sonobuoys, liferafts, paravans, oil, mines, shells and bullets that were lost, blown up or dumped in or over the oceans.
In total it must have amounted to well over 100 kilos per square kilometer, probably a very significant quantity, particularly in nutrient-poor tropical oceans.
I think that the next few years are going to be more informative in how the climate models compare to reality.Solar activity is likely to start falling in 2015 and if we see a fall in global temperatures will the climate models continue to predict increased warming because of rising co2.I am not going to be convinced that climate models can hindcast warming in the past if they don’t forecast correctly from the present.
Bob Tisdale:
http://wattsupwiththat.files.wordpress.com/2015/01/animation-2b.png?w=460&h=260&crop=1
That spike in the new ERSST.v4 data cannot be explained by the models and stands out like a sore thumb.
Mr. Tisdale
In 1940’s the Earth’s magnetic field went through unusual magnetic volatility. I think there may be a natural reason ( See HERE ) for this, but Dr. Svalgaard insists that the geomagnetic data for the 1940s epoch is wrong.
@vukcevic
The three maps at the bottom of your See Here link are showing gradients of the annual change of the vertical intensity. So between the maps we need to infer changes in the dZ/dx = f(x,y) between 20 year epochs has some meaning that affects temperature. Tenuous at best. Even if they are not wrong, so what?
Hi
there are numerous sets of data pointing to correlations (coincidental or causal) between solar activity, secular variability of the earth’s field and climate indices, one example you can see HERE
HNY
“Even if they are not wrong, so what?”
Despite Dr. Svalgaard’s assurances I doubt that there is any reason to suspect the NOAA’s geomagnetic maps; there is no good reason why they would alter geomagnetic data, unlike may be the case with the temperature’s data
Change for 1940’s epoch was sudden, going strong in 1945’s, trailing off by 1955’s. The effect is clear
ftp://ftp.ngdc.noaa.gov/geomag/images/Z_map_sv_1935_large.jpeg
moving in 5 year steps (alter 1935 in the link above to 1940 and so on)
With regards to the change point analysis by Niahm Cahill for the break points, I haven’t looked at what she has done because I’m unfamiliar with the technique. I have, though, had a guess as to what the complicated analysis is hiding.
The waffle in the media about most of the hottest years being in this century sort of gives it away that the CPA was done on the rankings of the years/months. Apparently, this is the best way to do it rather than to use the actual values.
Here is a plot of the months ranked from hottest to coolest, as estimated by GISS LOTI.
http://s5.postimg.org/5w8uhb8iv/LOTI_rankings.jpg
Here are the slopes from moving 20 year linear regression.
http://s5.postimg.org/j1ocnf2ef/derivative_loti_rankings.jpg
The slope over the whole period is about -10/year (-9.5) and where there is a significant cross over from higher to lower than this, or lower to higher, is at about 1913, 1940 and 1970. It crosses again at 2003 but only just before the data runs out.
It really does look like an attempt to shift the goal posts and say that the pause/hiatus/its-effing-stopped-warming needs to be another 10 years longer to be significant.
What it really says is that we can not say for sure that things have changed since our use of fossil fuels has become significant enough to contribute to rising CO2 levels (ca. 1950 or 1970 from the change points). Isn’t that the null hypothesis?
@Robert B
Your first chart is interesting, but since it is a Rank from highest temp =1 to Lowest = 1600, a reverse scale with 0 at the top would have been more appropriate.
But why deal with ranks? Why add more processing to the garbage in?
Scatter Plot the monthly anomalies vs time and be done with it.
Its a technique used by economists so I’m guessing that they see the actual values as containing undecipherable noise. I thought about ranking them the other way but it doesn’t really matter.
I’m also guessing that it was used to get people to look at the thimble with ‘there is no evidence of a pause’ on it when the pea is under the thimble with ‘there is insufficient data to claim a pause using this technique’, rather than being scientifically more robust.
I fully expected NBC News to trumpet 2014 as the “hottest year on record” two days early because of the frigid Arctic air coming in the last two days of the year and due to blanket the country. Sure enough, Lester Holt got it out on Monday night, and of course the reason was “climate change.” Question: Did the year actually finish the hottest (by the alarmists’ records)?
Before we deal with breakpoints, their validity and causes, perhaps we should remember that the error bars are missing.
Come on! Sea Surface temperature anomalies of less that 1 deg in the period 1850 to 1940? It would be hard to justify we know the average temperature of the North Atlantic to 0.2 deg C. But the South Atlantic? The South East Pacific Ocean?
Having no data is no justification for no uncertainty.
Why would we believe anything they say any longer? They are proven frauds.
Dr. Lazardo / Lord John Whorfin cannot connect the dots: http://www.realclimate.org/index.php/archives/2006/11/amqua_aapg/
Ladies and Gentleman please buckle up your safety belts and extinguish all smoking materials.
http://www.ipcc.ch/
Ha Ha