Guest post by Bob Tisdale
SAME INTRODUCTION AS ALWAYS
The National Oceanographic Data Center’s (NODC) Ocean Heat Content (OHC) anomaly data for the depths of 0-700 meters are available through the KNMI Climate Explorer Monthly observations webpage. The NODC OHC dataset is based on the Levitus et al (2009) paper “Global ocean heat content (1955-2008) in light of recent instrumentation problems”. Refer to Manuscript. It was revised in 2010 as noted in the October 18, 2010 post Update And Changes To NODC Ocean Heat Content Data. As described in the NODC’s explanation of ocean heat content (OHC) data changes, the changes result from “data additions and data quality control,” from a switch in base climatology, and from revised Expendable Bathythermograph (XBT) bias calculations.
The NODC provides its OHC anomaly data on a quarterly basis. At the NODC website it is available globally and for the ocean basins in terms of 10^22 Joules. The KNMI Climate Explorer presents the quarterly data on a monthly basis. That is, the value for a quarter is provided for each of the three months that make up the quarter, which is why the data in the following graphs appear to have quarterly steps. Furnishing the OHC data in a monthly format allows comparisons to monthly datasets. The data is also provided on a Gigajoules per square meter (GJ/m^2) basis through the KNMI Climate Explorer, which allows for direct comparisons of ocean basins, for example, without having to account for surface area.
This update includes the data through the quarter of October to December 2011.
Let’s start the post with a couple of looks at the ARGO-era OHC anomalies.
ARGO-ERA OCEAN HEAT CONTENT MODEL-DATA COMPARISON
I’ve started the post with a graph that gets people riled up for some reason.
Figure 1 compares the ARGO-era Ocean Heat Content observations to an extension of the linear trend of the climate models presented in Hansen et al (2005) for the period of 1993 to 2003. Over that period, the modeled OHC rose at 0.6 watt-years per year. I’ve converted the watt-years to Gigajoules using the conversion factor readily available through Google: 1 watt years = 31,556,926 joules. Even with the recent uptick in Global Ocean Heat Content anomalies, the trend of the GISS projection is still 3.5 times higher than the observed trend.
Figure 1
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STANDARD DISCUSSION ABOUT ARGO-ERA MODEL-DATA COMPARISON
Many of you will recall the discussions generated by the simple short-term comparison graph of the GISS climate model projection for global OHC versus the actual observations, which are comparatively flat. The graph is solely intended to show that since 2003 global ocean heat content (OHC) anomalies have not risen as fast as a GISS climate model projection. Tamino, after seeing the short-term model-data comparison graph in a few posts, wrote the unjustified Favorite Denier Tricks, or How to Hide the Incline. I responded with On Tamino’s Post “Favorite Denier Tricks Or How To Hide The Incline”. And Lucia Liljegren joined the discussion with her post Ocean Heat Content Kerfuffle. Much of Tamino’s post had to do with my zeroing the model-mean trend and OHC data in 2003.
While preparing the post GISS OHC Model Trends: One Question Answered, Another Uncovered, I reread the paper that presented the GISS Ocean Heat Content model: Hansen et al (2005), “Earth’s energy imbalance: Confirmation and implications”.Hansen et al (2005) provided a model-data comparison graph to show how well the model matched the OHC data. Figure 2 in this post is Figure 2 from that paper. As shown, they limited the years to 1993 to 2003 even though the NODC OHC data starts in 1955. Hansen et al (2005) chose 1993 as the start year for three reasons. First, they didn’t want to show how poorly the models hindcasted the early version of the NODC OHC data in the 1970s and 1980s. The models could not recreate the hump that existed in the early version of the OHC data. Second, at that time, the OHC sampling was best over the period of 1993 to 2003. Third, there were no large volcanic eruptions to perturb the data. But what struck me was how Hansen et al (2005) presented the data in their time-series graph. They appear to have zeroed the model ensemble mean and the observations at 1993.5. The very obvious reason they zeroed the data then was so to show how well OHC models matched the data from 1993 to 2003.
Figure 2
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The ARGO-era model-data comparison graph in this post, Figure 1, is also zeroed at a start year, 2003, but I’ve done that to show how poorly the models now match the data. I’m not sure why my zeroing the data in 2003 is so difficult for some people to accept. Hansen et al (2005) zeroed at 1993 to show how well the models recreated the rise in OHC from 1993 to 2003, but some bloggers attempt to criticize my graphs when I zero the data in 2003 to show how poorly the models match the data after that. The reality is, the flattening of the Global OHC anomaly data was not anticipated by those who created the models. This of course raises many questions, one of which is, if the models did not predict the flattening of the OHC data in recent years, much of which is based on the drop in North Atlantic OHC, did the models hindcast the rise properly from 1955 to 2003? Apparently not. This was discussed further in the post Why Are OHC Observations (0-700m) Diverging From GISS Projections?
HOW LONG UNTIL THE MODELS ARE SAID TO HAVE FAILED? (STANDARD DISCUSSION)
I asked the question in Figure 1, If The Observations Continue To Diverge From The Model Projection, How Many Years Are Required Until The Model Can Be Said To Have Failed? I raised a similar question in the post 2nd Quarter 2011 NODC Global OHC Anomalies, and in the WattsUpWithThat cross post Global Ocean Heat Content Is Still Flat, a blogger stated, in effect, that 8 ½ years was not long enough to reject the models.If we scroll up to Figure 2 [Figure 2 from Hansen et al (2005)], we can see that Hansen et al (2005) used only 11 years to confirm their Model E hindcast was a good match for the Global Ocean Heat Content anomaly observations. Can we then assume that the same length of time will be long enough to say the model has failed during the ARGO era?
And as noted in a number of recent OHC updates, it’s really a moot point. Hansen et al (2005) shows that the model mean has little-to-no basis in reality. They describe their Figure 3 (provided here as my Figure 3 in modified form) as:
“Figure 3 compares the latitude-depth profile of the observed ocean heat content change with the five climate model runs and the mean of the five runs. There is a large variability among the model runs, revealing the chaotic ‘ocean weather’ fluctuations that occur on such a time scale. This variability is even more apparent in maps of change in ocean heat content (fig. S2). Yet the model runs contain essential features of observations, with deep penetration of heat anomalies at middle to high latitudes and shallower anomalies in the tropics.”
I’ve deleted the illustrations of the individual model runs in my Figure 3 for an easier visual comparison of the graphics of the observations and the model mean. I see no similarities between the two. None.
Figure 3
BASIN TREND COMPARISONS
Figures 4 and 5 compare OHC anomaly trends for the ocean basins, with the Atlantic and Pacific Ocean also divided by hemisphere. Figure 4 shows the ARGO-era data, starting in 2003, and Figure 5 covers the full term of the dataset, 1955 to present. The basin with the greatest short-term ARGO-era trend is the Indian Ocean, but it has a long-term trend that isn’t exceptional. (The green Indian Ocean trend line is hidden by the dark blue Arctic Ocean trend line in Figure 5.)
STANDARD NOTE ABOUT THE NORTH ATLANTIC: The basin with the greatest rise since 1955 is the North Atlantic, but it also has the largest drop during the ARGO-era. Much of the long-term rise and the short-term flattening in Global OHC are caused by the North Atlantic. If the additional long-term rise and the recent short-term decline in the North Atlantic OHC are functions of additional multidecadal variability similar to the Atlantic Multidecadal Oscillation, how long will the recent flattening of the Global OHC persist? A couple of decades?
Note also in the ARGO-era graph, Figure 4, that, in addition to the North Atlantic, there are three other ocean basins where Ocean Heat Content has dropped during the ARGO era: the North Pacific, South Pacific, and Arctic Oceans. We could assume the Arctic data is, in part, responding to the drop in the North Atlantic. But that still leaves the declines in the North and South Pacific unexplained.
Figure 4
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Figure 5
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Further discussions of the North Atlantic OHC anomaly data refer to North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables. And if you’re investigating the impacts of natural variables on OHC anomalies, also consider North Pacific Ocean Heat Content Shift In The Late 1980s and ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data.
GLOBAL
The Global OHC data through December 2011 is shown in Figure 6. Even with the recent correction and uptick in the two quarters of this year, Global Ocean Heat Content continues to be remarkably flat since 2003, especially when one considers the magnitude of the rise that took place during the 1980s and 1990s.
Figure 6
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TROPICAL PACIFIC
Figure 7 illustrates the Tropical Pacific OHC anomalies (24S-24N, 120E-90W). The major variations in tropical Pacific OHC are related to the El Niño-Southern Oscillation (ENSO). Tropical Pacific OHC drops during El Niño events and rises during La Niña events. As discussed in the updates since late last year, the Tropical Pacific has not as of yet rebounded as one would have expected during the 2010/11 and 2011/12 La Niña events. In other words, the 2010/11 and 2011/12 La Niña events have done little to recharge the heat discharged during the 2009/10 El Nino.
Figure 7
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For more information on the effects of ENSO on global Ocean Heat Content, refer to ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data and to the animations in ARGO-Era NODC Ocean Heat Content Data (0-700 Meters) Through December 2010.
THE HEMISPHERES AND THE OCEAN BASINS
The following graphs illustrate the long-term NODC OHC anomalies for the Northern and Southern Hemispheres and for the individual ocean basins.
(8) Northern Hemisphere
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(9) Southern Hemisphere
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(10) North Atlantic (0 to 70N, 80W to 0)
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(11) South Atlantic (0 to 60S, 70W to 20E)
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(12) North Pacific (0 to 65N, 100 to 270E, where 270E=90W)
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(13) South Pacific (0 to 60S, 120E to 290E, where 290E=70W)
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(14) Indian (60S-30N, 20E-120E)
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(15) Arctic Ocean (65 to 90N)
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(16) Southern Ocean (60 to 90S)
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
ABOUT: Bob Tisdale – Climate Observations
SOURCE
All data used in this post is available through the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
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nice graph, Bob
No doubt about it Bob, the oceans are one of the most beautiful things in our ecological sphere.
We really should be caring for them, ultimately, without them, we wouldn’t have an atmosphere.
Markus Fitzhenry.
Think about the magnitude of the heat increase, about Six Watt-Years per square meter over one decade.
This is only .6 W-yr/yr
Average insolation is about 350 Watt-Years per Year.
In other words, the net increase of heat influx to the oceans was about one tenth of one percent. This is trivial.
You all know me by now…a bit slow on the uptake…so please explain to me very gently how all the alleged melt water from the melting ice pack and ice sheets is gently warming up the oceans?
“HOW LONG UNTIL THE MODELS ARE SAID TO HAVE FAILED?”
I was always under the impression that if the observations strayed outside the error bars of the model then the model had failed.
I notice, however, that very few CAGW predictions come with error bars…
Bob asks:
“If The Observations Continue To Diverge From The Model Projection, How Many Years Are Required Until The Model Can Be Said To Have Failed?”
“There you go again.” (R.R., 1980)
Expecting “the team” to capitulate will likely mean a long wait. Many scientific debates do not end until the elderly, with much invested, have left the scene.
Lew Skannen says:
“I notice, however, that very few CAGW predictions come with error bars…”
And I notice that no CAGW predictions come true. Ever.
Charles Gerard Nelson says: @5:25.
You are supposed to use ‘sarc’ on things like that.
Nevertheless, I will still suggest a two-part exercise. Find a globe. Put your cusped hand over the Arctic and then do the same for Antarctica. Now put the heal of your palm on the globe near Peru and step by step move it until you have covered the ocean to the east coast of Africa. Part 2: Find a true color photo of the ocean from space with the sun directly above the camera’s viewpoint. What color does the ocean appear? With respect to solar energy, what does that “color” imply?
with limited memory ( before ) in my laptop, the Argo tools and data set produced graphs that convinced me of the fact that the Pacific ocean was really holding trivial, if any, heat.
now, that I have a full 2 GB, will have to re explore with the tools. with Argo, more memory is better ( much more ).
thanks for your post.
Without uncertainty estimates on both the models and the observations, you cannot meaningfully compare the two. You show no uncertainty estimates at all in this post. You don’t even use the word “uncertainty”. Ergo, nothing meaningful here.
Steptoe Fan says:
January 26, 2012 at 5:55 pm
“ . . . holding . . . heat.”
Put some of that 2 GB to good use and store the meanings of heat and enthalpy.
Seriously Bob, you need some advice on how to present information with impact.Those first two paragraphs are turgid waffle of virtually no interest to most readers, followed by a long data dump. Most of it reads like an appendix to some report. This isn’t some hidebound old scientific journal where you are trying to impress a handful of readers with your erudition.
Come up with two or three succinct talking points, supported by one or two critical graphs or summary tables. For those who want to study the detail, append it after you state your findings, or better still link to it somewhere else.
Actually, you just need to keep expanding the error bars around the estimates to accommodate the latest reading. That way, the models are always right, just more and more dubiously! Simples.
1st let me protest the use of heat content. It’s energy content in Joules.
Correct me if I’m wrong. For whatever reason, the energy content of the Equatorial Pacific is not recharging as it should during this La Niña. What does this mean for the energy content after the next El Niño?
Surely a further reduction in overall Ocean energy content.
As most of the retained energy in the system is in the oceans, this must imply cooling!
DaveE.
Alan Statham says:
Without uncertainty estimates on both the models and the observations, you cannot meaningfully compare the two.
So you will believe Bob if he puts uncertainty bars on?
Or are you just looking for any excuse to fail to see the obvious divergence of model and reality?
What is eleventy billion standard deviations Alex?
Lew Skannen says:
I notice, however, that very few CAGW predictions come with error bars…
Not true, Lew. All CAGW predictions come with error bars. They just dont let people see them, until the discrepancy between their scare mongering and the unfudgable observations becomes so large as to be laughable. THEN they start talking about error bars, and using the term “consistent with” as if it means “proof”. This guy is halfway there already:
Alan Statham says:
Without uncertainty estimates on both the models and the observations, you cannot meaningfully compare the two.
Yes, Alan, you can. And you can also point at them and laugh.
Those scaremongering model predictions do not come anywhere close to the observations. And those observations are known to be far more accurate than the data that the scaremongering model predictions are based on. If the $#!^^y model based on the $#!^^y data is a factor of 3.5 off the better data, then we have no reason whatsoever to place any weight on those $#!^^y model predictions. If they are correct it will be by dumb luck, not knowledge and reason. And that is a very meaningful comparison.
You show no uncertainty estimates at all in this post. You don’t even use the word “uncertainty”. Ergo, nothing meaningful here.
LOL. NOW you guys have discovered the concept of “uncertainty”.
Now, follow the talking points and claim “consistent with”. C’mon. We know you want to.
Bob, since Hansen said the missing heat which is stuck in the pipeline since the OHC graph
turned flat in 2000 is not really stuck but hiding……
below your 700 m ocean depth ….. too bad……my question would be in which of the oceans
(and your graphs) would the hiding place of the heat be located…. since your graphs
stay flat…..? I always thought warm water comes up to the surface but now it goes down……
I never see this point discussed, but it does relate to ocean heat content, so please bear with me in what will need a long explanation.
Suppose, for example, that the surface and oceans were to rise to some “equilibrium” of, say, 5 degrees warmer in say 200 years. You simply could not have a situation whereby temperatures, say, 100 metres underground (and under the floor of the oceans) remained at current levels. Unless those temperatures also rose by about 5 degrees you have no long term equilibrium.
Over the course of the life of the Earth its surface has reached its current temperatures at various points on the globe. Underground, coming from the core (about 5,700 deg.C) down to the surface we have a fairly linear temperature plot. At least we know from measurements what happens in the last few kilometres anyway, the deepest borehole being about 9Km. The lapse rate underground is about 30 deg.C per Km but my point is that the plots in numerous boreholes that I have analysed all extrapolate approximately to a “base” temperature which we would expect on a calm winter night at that point on the surface.
So we have a continuous temperature plot from the core to TOA with a kink in the gradient at the surface. But it’s only a kink in the gradient – not a 5 degree step, and never could be. (Of course there are daily variations as thermal energy on a sunny morning flows into the surface – and then back out again at night, and some hangs around from summer to winter. But there is a tendency to come back to the base at any particular location on calm winter nights. Think of the base as a sloping rock platform onto which we pour a bit of sand in the day which slides off in the night.)
Thermodynamics tells us that the underground plot would have to rise by 5 degrees at the surface end, assuming the core temperature stayed constant. This may seem strange to some, because it seems to imply that we need to send thermal energy uphill so to speak. But in fact it takes time – a long time – and the gap under the (new) line would be filled in by thermal energy coming from the core. This is a slow process. It may take thousands, or perhaps millions of years, I don’t know, but it would not happen in 200 years, that’s for sure.
Hence there would be a propensity for thermal energy from that wrongly named “ocean heat content” to flow under the floor of the ocean in an “effort” to equalise the temperatures. And that would lead to cooling of the oceans – a natural stabilising effect due in essence to the far greater thermal energy under the surface than anywhere in the oceans or land surfaces.
There is more detail on this stabilising “support mechanism” on this page of my site http://climate-change-theory.com/explanation.html
What do others think?
Models should come in boxes or wear skimpy dresses – other than that, reality is destroying them every day.
Hey, Anthony – you have an Ozero campaign ad on this site? WUWT? You have officially ‘arrived’ – the Bamster’s campaign has figured out that this site has more traffic than UnRealclimate! 🙂
What Bob has clearly show is these very expensive models are not better then any other prediction methodology based on inductive reasoning. Inductive logic is the hallmark of a priori reasoning not of the deductive logic of reasoned science. To those suffering from a massive attack of Cognitive Dissonance they will hold to their mythology for a very long and painful time.
Thank you Mr. Tisdale. And excellent update as always.
Where in heck did “watt-years” come from? SI units like kWh and GWh I understand, is this some new fudge-factorable Hansenian unit?
No wonder that graph gets people riled up. How many seconds are there in a year?
January 2nd, February 2nd, March 2nd… so 1 watt-year = 12 joules, right?
Oh! wait … I get it now. A watt-year is the amount of energy Anthony and gang expend running this blog for a year. Well, that’s way more than 31,556,926 joules, Bob. Better fix that graph, I think you’ve just found Trenberth’s missing heat and it’s worse than we thought! 🙂
The poles are still frozen. From the above synopsis, the oceans are not even 1 C warmer in the time frame given. So, it the Arctic average temperature goes up by such, what effect is it going to have??? Just move the Arctic temperature graphs up one degree ( http://ocean.dmi.dk/arctic/meant80n.uk.php ). The change is insignificant. The poles are still frozen.
Bob, forget about what Alan says and keep posting those charts, as they help to visually understand your stated points.