Guest post by Bob Tisdale:
NOTE: This post contains 5 .gif animations that total 10MB. (below the continue reading line) Have patience. They may take a while to load.
This post is a follow-up to the recent post October to December 2010 NODC Ocean Heat Content (0-700Meters) Update and Comments. I wanted to discuss the ARGO-based period separately.
For those new to ARGO, under the heading of “What is Argo?”, the University of California, San Diego Argo webpage describes Argo as a “global array of 3,000 free-drifting profiling floats that measures the temperature and salinity of the upper 2000 m of the ocean.” The UCSD Argo website provides much more information, including an argo.avi video.
Much of the data in this post is supplied by ARGO for the upper 700 meters.
THE ARGO ERA (2003 TO PRESENT)
The NOAA NCEP webapge that presents the Global Ocean Data Assimilation System (GODAS) Input data distributions (1979-present) (Plots) allows users to plot the number of Temperature profiles at different depths for the globe, or for the Atlantic, Indian, and Pacific Oceans. An example of Global data for depths of 250 to 500 meters is shown in Figure 1. According to it, ARGO floats have been in use since the early 1990s, but they had very limited use until the late 1990s. ARGO use began to rise then, and in 2003, ARGO-based temperature readings at depth became dominant. Based on that, I’ll use January 2003 as the start month for the “ARGO-era” in this post.
http://i56.tinypic.com/1448yo3.jpg
Figure 1
Note the significant drop in samples in 2010. I have not found an explanation for this.
The NCEP GODAS Input data (Plots) webpage also allows visitors to create maps of temperature profile locations. Animation 1 is a gif animation that shows the annual data locations from 1979 to 2004. The measurements made with Expendable Bathythermographs (XBTs) are shown in red (x), the moored buoys that are parts of the TAO/ TRITON (Pacific) and PIRATA (Atlantic) projects are shown in green (+), and the blue (o) are ARGO-based measurements. Note how sparse the data is in the Southern Hemisphere prior to the early 2000s, especially south of 30S.
http://i55.tinypic.com/14ikdxs.jpg
Animation 1
Unfortunately, GODAS switched map formats in 2005 and again in 2006, so an animation that included the three map formats would be difficult to watch. The format used in 2005 is unlike those in use before or after, so I’ve excluded it in both animations. Animation 2 shows the Monthly temperature profile locations from January 2006 to December 2010. Note the decline in sampling in 2009/10, especially in the Indian Ocean. Why? Dunno.
http://i55.tinypic.com/2copg03.jpg
Animation 2
ARGO-ERA TREND VERSUS GISS PROJECTION
In past posts, when I’ve compared the NODC Global Ocean Heat Content to GISS projections, I’ve used the rate of 0.98*10^22 Joules per year for the GISS projection. This value was based on Roger Pielke Sr’s February 2009 post Update On A Comparison Of Upper Ocean Heat Content Changes With The GISS Model Predictions. The recent RealClimate posts Updates to model-data comparisons and 2010 updates to model-data comparisons have presented the projections based on Gavin Schmidt extending a linear trend of the GISS Model-ER simulations past 2003. The linear trends in both graphs are approximately 0.7*10^22 Joules per year. I’ll use this value in the comparison, but first a few more notes.
Gavin writes in the 2009 post, “Unfortunately, I don’t have the post-2003 model output handy, but the comparison between the 3-monthly data (to the end of Sep) and annual data versus the model output is still useful,” and he continues, “I have linearly extended the ensemble mean model values for the post 2003 period (using a regression from 1993-2002) to get a rough sense of where those runs could have gone.”
The only paper that I’m aware of in which GISS presented their simulations of Ocean Heat Content was Hansen et al (2005) “Earth’s energy imbalance: Confirmation and implications”. Science, 308, 1431-1435, doi:10.1126/science.1110252 (PDF). In it, they only presented their data from 1993 to 2003. Refer to their Figure 2 (not illustrated in this post).
For those who might be concerned that extending the linear trend does not represent the actual model simulations, refer to Page 8 of the .pdf file GISS ModelE: MAP Objectives and Results. The graph there presents two GISS OHC Model E simulations, one with the Russell Ocean model, the other with the HYCOM Ocean model. The simulations run to 2010 for both models. Do they extend further into the future? And for those who want to attempt to duplicate that comparison of the Model-ER and Model-EH versus the early NODC OHC data, the NODC OHC data (older version) was based on the 2005 Levitus paper “The Warming Of The World Ocean: 1955 to 2003” (Manuscript). Link for the 0 – 700 meters data.
Back to the comparison of the ARGO-era OHC data and the GISS Projection: The most recent version of the NODC OHC data is linked here for 0 – 700 meters. I’ve compared it for the period of 2003-2010 to the GISS projection in Figure 2. Note that I’ve shifted the data down so that it starts at zero in 2003. The GISS projection of 0.7*10^22 Joules per year dwarfs the linear trend of the ARGO-era NODC OHC data. No surprise there.
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Figure 2
NOTE ABOUT THE DATA
The remainder of the data in this post was downloaded from the KNMI Climate Explorer Monthly observations webpage. The NODC OHC data there is presented in Gigajoules per square meter (GJ/m^2), not the units (10^22 Joules) provided by NODC. That’s why the scale and trends in Figures 2 and 3 are different. The NODC also provides their OHC data on a quarterly basis, but KNMI presents it as monthly data, thus allowing for comparisons to other monthly datasets. This is why the OHC data appears in 3-month tiers in Figures 3, 4 and 5.
GLOBAL AND OCEAN BASIN TRENDS
Figure 3 shows the Global NODC OHC data for the period of January 2003 to December 2010. Comparing its linear trend (0.19 GJ/m^2 per Century) to the trend of the long-term data from 1955 to 2002 shown in Figure 4 (0.52 GJ/m^2 per Century), there has been a significant flattening of the Global OHC data in recent years. And this flattening was not anticipated by the GISS models, which show a continuous rise through 2010.
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Figure 3
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Figure 4
Of course, the oceans are not warming uniformly. Refer to Figure 5. The trends for the North Pacific and the Southern Oceans are basically flat. The only two ocean basins with major increases in OHC during the ARGO era are the South Atlantic and the Indian Oceans, while the North Atlantic, Arctic, and South Pacific Oceans show significant declines in OHC.
http://i56.tinypic.com/28qvtqu.jpg
Figure 5
Note: The coordinates for the ocean basins are:
North Atlantic = 0-75N, 78W-10E
South Atlantic = 60S-0, 70W-20E
Indian = 60S-30N, 20E-120E
North Pacific = 0-65N, 120E-90W
South Pacific = 60S-0, 120E-70W
Arctic = 65N-90N
Southern = 90S-60S
ARGO-ERA CHANGES IN NODC OHC
Figure 6 is a map that displays the change in ARGO-era OHC, from 2003 to 2010. It was created by using 2003 as the base year for anomalies, and plotting the annual OHC values for 2010. Much of the cooling in the North Atlantic has taken place at mid and lower latitudes. In the South Pacific, there was also a decline in the lower latitudes, but there appears to also have been a drop there at higher latitudes along the Antarctic Circumpolar Current (ACC).
http://i51.tinypic.com/21crset.jpg
Figure 6
Animations 3, 4 and 5 present the ARGO-era OHC data, using 12-month averages. The first cells are the average OHC from January to December 2003. These are followed by cells that show the period of February 2003 to January 2004 and so on, until the final cell that captures the average OHC from January to December 2010. The 12-month average reduces the noise and any seasonal component in the data. I’ve also included a graph of NINO3.4 SST anomalies (smoothed with a 12-month filter, and centered on the 6th month) since the effects of ENSO dominate the OHC data. The NINO3.4 SST anomaly graph infills with time. Animation 3 presents global maps.
http://i54.tinypic.com/eu4pzq.jpg
Animation 3
Animation 4 is the North Pole stereographic view. Note the warming of the western tropical North Pacific during the 2007/08 La Niña. It’s tough to miss. There also appears to be a lagged decline in the North Atlantic OHC in response to the 2007/08 La Niña. Will we see a lagged increase there next year?
http://i53.tinypic.com/2mo8fuq.jpg
Animation 4
And Animation 5 is the South Pole stereographic view. Note the persistence of the warm and cool anomalies moving southward from the equatorial Pacific in waves, and also into the South Indian Ocean. I believe those would be classified as oceanic Rossby waves.
http://i54.tinypic.com/2v9rqy0.jpg
Animation 5
CLOSING
Watching the animations, it is very obvious that ENSO and the distribution of warm and cool waters caused by ENSO are major components of Global Ocean Heat Content. Refer to ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data for further discussion and illustrations. OHC studies such as Hansen et al (2005), however, do not include ENSO in their models. They assume that Anthropogenic Greenhouse Gases have a measurable impact on Ocean Heat Content. The impacts of the failure of GISS to include ENSO and other natural variables in their analysis was illustrated and discussed in detail in Why Are OHC Observations (0-700m) Diverging From GISS Projections?
Refer also to North Pacific Ocean Heat Content Shift In The Late 1980s and North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables.
This information and analysis is most appreciated. It seems difficult to argue for a large climate sensitivity value unless ocean heat content is rapidly increasing. I look forward to further posts from Bob Tisdale on this topic.
LOL. Can someone mail figure #2 to Gavin?
Beautiful animations. I love data. Animation 5 is astounding.
Fig. 1: The Y-axis is not identified, a must in even elementary math classes.
It is not intuitive what has units up to 20,000.
IanM
Thanks, Anthony.
I am getting very tired of all this talk about models and what they show. In my high school physics class, I learned a central definition of science: it makes successful predictions. For example, Aristotelian physics, produced by “intelligent thought” predicted that a lighter weight would fall at a slower rate than a heavier one. The famous Pisa experiment debunked that one. Newtonian physics predicts that a body in motion will remain in motion unless acted upon by an outside force–such as friction. The measurements on this one can be carried out to three decimal places or more and produce a perfect graph.
The models are notorious for failed predictions, and not just in the new century. They are unscientific.
Calling it “climate science” does not make it so. Only successful predictions make science. It is the skeptics who have that track record. We are the scientists.
A very informative set of animations. Congrats.
“They assume that Anthropogenic Greenhouse Gases have a measurable impact on Ocean Heat Content”
And the mechanism for this is….?
The SST and energy content of the oceans seems to be disconnected, which I think means that as the surface warms, the heat permeates down, increasing the heat content but not “allowing” the surface to get warmer. The CAGW theory has A-CO2 as the reason the heating is happening at all, by warming the air at the air-sea contact. Here is where I see the problem vis-a-vis the CAGW theory:
In order for the sea at depth to get warmer by heat loss from the air, a temperature gradient must continually exist between the air and the sea surface. The tropics have only a 0.24C difference over the last 30 years. The increased power at this stage has got to be about 0.15 W/m2. This is insufficient for the top 700m of high density ocean water to heating up at an accelerating rate as measured. If increased insolation is the cause, however, the 70% surface of the globe that the sea covers, and the ability of sunlight to penetrate the sea surface to >50 m, does give the level of energy the ocean heat content increase represents. AT 1.5% decrease in cloud cover, about 1.4 W/m2 of insolation is added worldwide. A local change in cloud cover of 4.5% over one-third the globe does the same thing. The variation of insolation through the year timed to slight changes in global albedo will do the same with even smaller areas (as Jan-July insolation varies by about 18 W/m2 due to orbital eccentricity alone). Insolation, not atmospheric CO2, seems to have the power to change the oceanic heat content as measured.
So: it seems to me from the above arguments, that the changes in the OHC compared to the changes in atmospheric CO2 and atmospheric temperature demonstrate that insolation, not A-CO2 must be the cause of oceanic warming. The sea is warming the air, not the air warming the sea.
Is the increase in OHC relative to SST and other air temperatures not a fundamental bust wrt AGW?
In your first figure, I don’t understand why you would add the Argo, XBT and TAO data together (your black curve). Surely they were meant to be stand-alone measurements. Secondly, your OHC anomaly graph: with an ordinate in 0.05 Gj/m sqd graduations, it isn’t hard to see why there could be large swings on the graph. What kind of error bars would these figures have.
Perhaps the GISS models are wrong, (assuming that they do model ocean heat content to agree with the AGW theory). ARGO is observed data which shows the expected cyclic nature of heat content.
Ian:
The “y” axis label is the title at the top (i.e., number of temperature profiles / month).
Cheers,
Ian L. McQueen says: “Fig. 1: The Y-axis is not identified, a must in even elementary math classes. It is not intuitive what has units up to 20,000.”
Sorry. I downloaded the graph from the NOAA GODAS website, decreased its size and posted it. Based on the GODAS webpage linked in the post, the y-axis is “number of profiles accumulated monthly”.
Gary Pearse says: “In your first figure, I don’t understand why you would add the Argo, XBT and TAO data together (your black curve).”
Figure 1 is not “my” graph. I had nothing to do with it production. I simply copied it from the NOAA GODAS website:
http://www.cpc.ncep.noaa.gov/products/GODAS/data_distribution.shtml
Mr. Tisdale, in one of your earlier webpage http://bobtisdale.blogspot.com/2008_11_01_archive.html
you published graph(s) for the N. Atlantic Subpolar gyre SST (1854-2008), I would be grateful if you could direct me to the link for the relevant data file.
Thanks.
Hoser says: “Beautiful animations. I love data. Animation 5 is astounding.”
Thanks. Here’s a link to the longer-term version of Animation 3.
It starts in 1990 and runs through 2010. There’s no graph to the right, but the red dots in the upper right-hand corner tick off the years. Note: If you’re at work, watch the volume, because the music kicks in around the 2 minute mark.
Best discussion of the Argo data that is available anywhere.
One would have to ask – what changed in the climate in 2003. Nothing really, accurate data became available that is all. A few more La Nina’s? There is no long-term trend in the ENSO so there should be no long-term trend in OHC as a result of the ENSO. (The pre-2003 data was probably subject to the same math that is applied to the tree-ring reconstructions).
vukcevic says: “Mr. Tisdale, in one of your earlier webpage http://bobtisdale.blogspot.com/2008_11_01_archive.html
you published graph(s) for the N. Atlantic Subpolar gyre SST (1854-2008), I would be grateful if you could direct me to the link for the relevant data file.”
The NOMADS website no longer allows long-tern access the ERSST.v2 (obsolete) data. But it’s still available in through the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
And I did list the coordinates in the post…
http://bobtisdale.blogspot.com/2008/11/interesting-correlation-with-north.html
…for the North Atlantic Subpolar Gyre on the graphs as 45N-60N, 60W-30W.
Bob Tisdale writes:
“OHC studies such as Hansen et al (2005), however, do not include ENSO in their models. They assume that Anthropogenic Greenhouse Gases have a measurable impact on Ocean Heat Content.”
You have just blown global warming/climate change/climate disruption/climate whatever out of the water. Brilliant work. Thanks so very much.
CO2 takes public transportation from large cities such as Chicago and Detroit to the beaches. Then it enters the water directly at the beaches. Yes, that is the mechanism. Hansen and Schmidt just haven’t published the paper yet. /sarc – I hope this isn’t necessary.
PS on my biologists diatribe above. I think a survey of biologists’ and biology students’ thoughts, beliefs and policy prescriptions they would like to see concerning CO2-GW would make a very fine post and maybe be a bit of a wakeup call for both biologists, and policymakers.
RE: Figure 3: When ever a simple dataset and its linear regression is shown, I think it is a glorious opportunity to also plot the 80% confidence band of the linear regression. I suspect in the case of Figure 3, that a slope of <=0 is within the 80% confidence.
Showing the confidence bands in Figure 5 would be completely impractical. However, having the 5 trends all pass through the same midpoint give a visual impression that the mean squared error of each sample is small. Maybe error bars at the crossing (or in the left or right margin) could denote uncertainty of the mean to scale.
Raw data placed in an easy-to-understand graphical format on a website that provides widespread distribution and discussion. Thank you gentlemen, you’re doing a real service for the advancement of science.
I had known from previous postings that fluid circulation was a major heat transfer mechanism, but the north and south polar views give a much better idea of just how constrained the flows between the oceanic basins are, and why minor changes in the amount of inflow into areas like the arctic could result in such large ice melt or accumulations.
Compare Figure 1 and Figure 3.
It seems to me, without doing the math, that Figure 3 is a difference of the sample mean at time t – mean of the samples over all time(t).
But from Figure 1, the number of samples N is increasing with time t.
So is the mean sq error of the sample at t=2004 larger than at t=2008 simply because 1/sqr(N(t=2004)) > 1/sqr(N(t=2008)).
Unless the data has been randomely resampled so that N is constant for all time, isn’t homoscedasticity violated? If N changes with time, then Uncertainty in the sampled mean should be plotted on Figure 3 as a trumpet curve opening to the left.
Bob:
Great post!
Has Josh Willis chimed in on your findings? If so and your at liberty to disclose, please do so. If not, will you invite his comments? Thanks.
Brian M. Flynn says: “Has Josh Willis chimed in on your findings?”
Nope. I receive comments from scientists on rare occassions.
This made me think about the recent thread about the lag in the climate system and how that relates to climate sensitivity. I wrote a comment then which argued that the lag due to greenhouse gas forcing need not be the same as the lag due to solar forcing (with the latter probably being much longer). This is because greenhouse gas forcing is in the long wave region of the spectrum which is absorbed within the top few millimetres of the ocean and must therefore leads to immediate surface warming and compensating radiation, evaporation and convection losses . The evidence of these plots is that this is indeed the case and that if the large increase in CO2 since 1955 had any effect it is very small and has already reached equilibrium. There can be no warming in the pipeline if there is no energy to supply it.
However my own view is that surface temperatures are far too closely correlated with the Milankovitch cycles and sun spots for there not to be a strong solar element in climate variation. The fact that TSI is roughly constant is a red herring. A change in solar forcing does not require a change in total energy emitted; a change in spectrum (towards the UV) at the surface could have the desired effect. My hope is that they will publish the energy change at various depths over a whole solar cycle because my hypothesis is that warming at around 100 metres due to variations in solar UV is the real source of the energy inbalance because this energy increase has no compensating energy loss at the surface. This is only corrected when the ocean currents bring the warm pools to the surface where the stored energy can be finally lost to space. The time constant of this is almost certainly much longer (at least decadal) and so I see nothing in these plots that could not be explained by the mid century solar peak.
I am not sayin this is the mechanism but I suggest such a solar forcing is plausible and varifiable. Can someone in the AGW camp please explain the mechanism by which CO2 forcing can produce these results.
Note the decline in sampling in 2009/10, especially in the Indian Ocean. Why? Dunno. Two words: Somali pirates. They are holding the climate data hostage, but what are their demands?
I am having a hard enough time combining multiple data sources that are all under my control. I can appreciate the difficulty in dealing with so many agencies to produce reliable results!
Changes in the ion charge gradient from pole to equator due to interactions of the Earth’s geomagnetic storms, resulting from solar wind variances can change the cloud nebulized droplet size on a global scale, allowing large shifts in the total UV solar power reaching the surface with NO change in TSI.
Synod conjunctions with the outer planets have this effect, and the timing of the passage of these conjunctions as they process through the seasons, shifts the periodicity of the effects leading to the chaotic patterns seen.
http://research.aerology.com/natural-processes/solar-system-dynamics/
Wow! Animations 3,4,5 are breathtaking! I love the coordinate system on the right, telling me where i am in time without having to decipher running numbers. Thanks!
Would someone please give a ballpark figure regarding the significance of Figure 2 and the issues associated with it?
It seems to me that Figure 2 shows that the ARGO data shows no increase in OHC after 2003 yet GISS model projections call for a large increase. So, it seems that the model was way off and expected increase in OHC is non-existent. Isn’t this quite a blow to AGW? How might the GISS people respond? Could they respond by questioning the ARGO technology?
Very well done, Bob. A great read, and excellent graphics. Keep up the good work.
w.
DirkH says:
March 25, 2011 at 2:05 pm
I agree – you do not have to keep looking away and working out numbers.
Tisdale, Sony ATV is claiming copyright on your longer term animation you posted inline in comments…. You may want to deal with YouTube on this…
” The impacts of the failure of GISS to include ENSO and other natural variables in their analysis … ”
Is it ENSO a variable? or it is rather an effect of another variable ? What causes ENSO variations? The ENSO predictions are based on which variables?
Excellent post!
However is one of the titles not wrong where it says: NODC Ocean Heat Content Anomalies (0-700 Meters) Global Jan 1955 to Dec 2010. The graph right below it shows from 2003 to Dec 2010.
[Fixed, thanks.]
Werner Brozek: “However is one of the titles not wrong where it says: NODC Ocean Heat Content Anomalies (0-700 Meters) Global Jan 1955 to Dec 2010. The graph right below it shows from 2003 to Dec 2010.”
Yup. Thanks for noticing the wrong start year in title block of Figure 3. I’ll repair the original. Thanks again.
And the Moderator replied, “Fixed, thanks.”
Moderator: I’m seeing an error in the title block of the graph in Figure 3, that only I can repair. What else was wrong that you fixed?
juanse barros says:
March 25, 2011 at 5:19 pm
“Is it ENSO a variable? or it is rather an effect of another variable ? What causes ENSO variations? The ENSO predictions are based on which variables?”
You are a good scientist, sir. As of now, there is no set of hypotheses that describe the natural regularities that make up ENSO. People extrapolate forecasts (not predictions) about ENSO from various collections of data regarding past ENSOs.
We are approaching a decadal milestone in OHC measurements. Hansen and Schmidt claimed that OHC from from 1993-2003 confirmed their AGW hypothesis (Hansen et al (2005) “Earth’s energy imbalance: Confirmation and implications”. Science, 308, 1431-1435, doi:10.1126/science.1110252).
In 2013 another ten years will have elapsed. Applying the same criteria we can safely conclude that their hypothesis has been falsified if the decadal trend shows little or no warming. Their only alternative is to credibly document the existence and magnitude of the “missing heat.” Otherwise game over.
A masterpiece of data assimilation and presentation Bob.
Such a pity we don’t have data for the Southern Ocean over a longer period. It is in January that the greatest inter-annual variation in surface temperature occurs in both hemsipheres. It would be interesting to compare ocean heat content in mid latitudes with sea surface temperature and cloud cover over daily or monthly intervals.
The ARGO OHC is so obviously the elephant in the room you would think that the climate science establishment would be dealing with it. Opining that the ARGO date must just be wrong sounds hollow. It would be good to see somebody from the climate science establishment to deal with this data in an honest way. I like Bill DiPuccio’s suggestion for a new decadal scale analysis.
juanse barros says: “Is it ENSO a variable? or it is rather an effect of another variable ? What causes ENSO variations? The ENSO predictions are based on which variables?”
The following link is to an introduction of ENSO that will hopefully answer most of your questions:
http://bobtisdale.blogspot.com/2010/08/introduction-to-enso-amo-and-pdo-part-1.html
Predictions? I do not know which of the coupled ocean-atmosphere processes scientists base their predictions on (it likely varies per model) or how they attempt to model it. But the models do a poor job of capturing all of the interacting processes.
Bob:
Did anyone calculate the effect on the Argo array data caused by the leaking pressure sensors? Do they even know how many pressure sensors failed? At one point two years ago they were guessing the failure rate as high as 30%.
Thanks
Keith
Bob Tisdale says:
March 25, 2011 at 9:13 am
…….
Thanks.
Keith says: “Did anyone calculate the effect on the Argo array data caused by the leaking pressure sensors?”
I don’t know for certain. But there were changes/corrections to the ARGO-era data when the NODC updated/corrected the dataset back in 2010. On the second page of the following link they state, “1. Changes due to data additions and data quality control, both at NODC and by originators. Substantial quality control has been carried out by the Argo community on the profiling floats, mainly to correct pressure offsets. A substantial amount of data for recent years has been added to the analysis.”
ftp://ftp.nodc.noaa.gov/pub/data.nodc/woa/DATA_ANALYSIS/3M_HEAT_CONTENT/PDF/heat_content_differences.pdf
Are “pressure offsets” corrections for leaky sensors, etc.? Dunno.
Mike Lorrey says: “Tisdale, Sony ATV is claiming copyright on your longer term animation you posted inline in comments…. You may want to deal with YouTube on this…”
Mike, they only hold the copyright to the music that’s included, and they’ve linked a couple of ads to that YouTube webpage.
YouTube advised, “No action is required on your part. Your video is still available worldwide.”
But if push comes to shove, I can simply upload a version without the music.
@Bob Tisdale
YouTube advised, “No action is required on your part. Your video is still available worldwide.”
I’m familiar with this message when you post a video with a sound track from a music CD. In Germany the video will be blocked, but otherwise, indeed, “No action is required on your part”.
Note the significant drop in samples in 2010. I have not found an explanation for this.
Curious indeed, almost like the fall off in surface stations in the 90’s – but then there was the end of cold war and associated cultural rejection of science and objectivity as an explanation. What now – the wrong message, shoot the messengers?
juanse barros says: March 25, 2011 at 5:19 pm
Is it ENSO a variable? or it is rather an effect of another variable ? What causes ENSO variations? The ENSO predictions are based on which variables?
Theo Goodwin says: March 25, 2011 at 7:30 pm
As of now, there is no set of hypotheses that describe the natural regularities that make up ENSO. People extrapolate forecasts (not predictions) about ENSO from various collections of data regarding past ENSOs.
As you may be aware there is close correlation between PDO and ENSO.
I have a good reason to think that PDO has primacy over ENSO. This is based on knowledge of oscillations in the North Pacific currents, which I consider to be the PDO driver. Both de-trended and the first differential (the rate of change) of the PDO driver’s data shows good correlation with the actual PDO.
There is exactly the same type of driver in the North Atlantic correlating with AMO.
More details will be available in a short article I am currently preparing based on my findings as shown here:
http://www.vukcevic.talktalk.net/PDO-ENSO-AMO.htm
Lady Life Grows said @ March 25, 2011 at 8:28 am
“I am getting very tired of all this talk about models and what they show. In my high school physics class, I learned a central definition of science: it makes successful predictions. For example, Aristotelian physics, produced by “intelligent thought” predicted that a lighter weight would fall at a slower rate than a heavier one. The famous Pisa experiment debunked that one. Newtonian physics predicts that a body in motion will remain in motion unless acted upon by an outside force–such as friction. The measurements on this one can be carried out to three decimal places or more and produce a perfect graph.
The models are notorious for failed predictions, and not just in the new century. They are unscientific.”
Galieleo does not state where he conducted his “famous Pisa experiment”, but he did record the height from which his assistants dropped the wooden ball and the cannon ball. It was 300 ft higher than Pisa. Were they extraordinarily tall, or did they use helicopters?
In any event, Galileo recorded that the wooden ball initially fell faster than the cannon ball, before being overtaken by the cannon ball which beat the wooden ball to the ground.
Where were the experiments on “a body in motion will remain in motion unless acted upon by an outside force” conducted? In an alternate universe without gravity?
Learn how to distinguish between Gedanken and physical experiments before pontificating.
The green declining trend are moored buoys for the most part in the Pacific with some in the Atlantic beginning around 2000. One should think these would be the most accurate instruments being fixed in position and few in number. Expendible bathyspheres must be relatively inexpensive (read not as reliable/accurate) if they’re expendible and being towed behind a ship presumbly mostly in shipping lanes and avoiding the worst weather and high seas.
In shipping lanes is an important factor because surface vessels don’t care for the kind of severe weather events that suck heat out of the ocean to power them and will go around or delay rather than go through. Many of you probably recall Anthony posting ocean temperature tracks last hurricane season where we could see the trail of cooler water under the hurricane track. It was basically a map of missing energy the hurricane used to power its winds. Buoys on the other hand will stay put through all extreme weather events and not being expendible and fewer in number are likely much higher quality instruments.
Regarding models…from Hartline, BK; Science 203:246, 1979:
“…the ability to predict is the ultimate test of understanding.”
GISS fails by this criterion.
Dave Springer says: “The green declining trend are moored buoys for the most part in the Pacific with some in the Atlantic beginning around 2000.”
I assume you’re discussing the graph in Figure 1. The legends for that graph and the maps, Figure 2, are confusing. The legend for Figure 1 shows the green as XBT, not moored buoys, and they don’t list the buoys. In Figure 2, the maps, they change color scheme, with the XBTs in red and the buoys in green.
Thanks Bob for another great post.
Good to see some ‘reality based’ OHC data, rather than the stuff modelled using sparse data and dubious supposition. However, I still think we need better data granularity to really understand what is really driving OHC, particularly in the SH where most of the bulk ocean content lies.
Supports with scientific evidence that the oceans are not warming as expected with regards to longwave radiation ocean skin temperature. The observed and predicted are evidence of this and not suprising since longwave radiation warming the ocean to any reasonable depth away from the first 1mm or less is awful science with no observed scientific evidence. Matches the trend in albeo of clouds and changes in shortwave radiation reaching the ocean surface much better.
Conclusion, what little affect longwave radiation has on the the ocean surface is dwarfed by any small variance in shortwave radiation reaching the surface. Thats why the observed and predicted are so far apart because CO2 is only having a minor role at best.
Sorry typo, albedo not albeo. (please correct and delete this – wireless keyboard unreliable yet again)
Bob Tisdale says:
March 26, 2011 at 1:52 pm
Ah… yup. I was reading the text about Figure 2 and still had red = bathysphere in my head. So I’d consider the red line in figure 1 the most accurate although not as great in coverage. Interesting that the bathyspheres show a small opposing trend. The ARGO data is as bogus as Mann’s Hockey Stick. Essentially all these methods are in disagreement which means none of them can be trusted. Back to the drawing board.
This comment is both towards a discussion of reconciling the OHC increases observed with that of supposedly generated by CO2 increases, and a request for expert knowledge on portions of the equations required to do so at a planetary level:
Some back calculations:
Between 1970 and 2002, the OHC increased by 0.31GJ/m2. The oceanic surface area of the planet is 3.35E24m2, meaning the OHC increased by 1.04E23 Joules during that time. Between 1970 and 2002 the SST increased by 0.38C, the land stations by 0.86C and the global mean temperature by 0.52C, according to GISTemp public records.
Between 1970 and 2002 the atmospheric CO2 content increased by about 45 ppmv, according to the Mauna Loa records. The IPCC radiative forcing for a doubling of CO2 at 380 ppmv is 3.75 W/m2; a 45 ppmv increase should translate as 0.444 W/m2. Over the 30 year period the average increase in equivalent thermal forcing would be 0.222 W/m2, as the relationship between radiative forcing and CO2 is linear, at least for small increases. The surface of the oceans being as noted above, the theoretical energy additional to the oceans by CO2 is 1.05E23 Joules for this 30 year period.
The measured OHC change 1970-2002 of 1.04E23 Joules matches well with the theoretical increase above the oceans of 1.05E23 Joules. Since the CAGW theory has the air warming the ocean (not the reverse, which would be the solar-warming way), a 99% heat injection into the oceans would be required, leaving 1% for warming the air above the oceans to the equilibrium-in-a-moment amount of 0.38C. This efficiency is obvious impossible, as well as leaving insufficient energy in the atmosphere to account for the warming.
The proposed CO2 warming is, of course, global, while the ocean-air surface is only 70.1% of the planet. So an additional portion, the 29.9% of the surface, of 0.46E23 Joules from CO2 as calculated must be involved in heating the oceanic air. If we take the global air all together, the increase of 0.52C of global air temperatures results from the infusion of the 0.46E23 Joules, but not all of it. The land station data shows an increase of 0.86C; taking the surface of the planet to be in instantaneous equilibrium with the air above it, a portion of the 0.46E23 Joules is responsible for the land warming up, too.
If the OHC measurements and the IPCC CO2 radiative forcing assumptions are to be reconciled, the reconciliation to be found is in the reasonableness of an air mass with an area of 4.78E14 m2 (the entire planet) being warmed by 0.52C, and a non-ocean, surface mass with a surface area of 1.43E14 m2 (29.9% of the entire planet) being warmed by 0.86C with a total of 0.46E23 Joules.
At this point I need help. First, the air:
To calculate the air mass changed by global warming (0.52C) one needs to know not just the area (4.78E14m2) but the height and average density of the air that has warmed. I can’t find that. To find the amount of energy required to heat that mass one also needs to know the heat capacity of the air involved; I also don’t know that. But with those two pieces of information, the global air mass warmed and the number of joules needed, the atmospheric chunk of the 0.46E23 Joules retained between 1970 and 2002 can be calculated.
Second, the non-ocean, “land” surface:
Northerners know that about 2m below the surface at the US/Canadian border the “dirt” rests at a steady local average temperature (about 55*F/12.8C), as neither the summers heat nor the winter’s cold penetrate deeper. It takes 4 months of only about 18*F/-10C to accomplish this, due to a its thermal conductivity. The temperature below this is determined by the geologic-time stable geothermal gradient, one thing not affected by AGW. (The temperature increase at the surface of 0.86C globally should be noticeable several meters down locally by now, but that is a separate point.) This increase occurs at a fixed rate dependent on the heat capacity of the ground material, while the depth of temperature change depends on the material’s thermal conductivity. These are two other numbers I can’t find to use.
There will be greater certainty in calculation of the mass and heat capacity of the air and, therefore, the total Joules needed to heat the planetary atmosphere 0.52C than the numbers needed to figure out how many Joules are needed to have heated the surface 0.86C. If the calculation is made for the air and subtracted from the 0.46E23 Joules remaining after taking account of the increase in OHC, then we will have a maximum amount available for the heating of the land. That will give us ranges for what is possible, and whether it is enough to account for the non-ocean “land” heating observed based on estimates of thickness of material heated and its heat capacity.
What I expect is that there will be insufficient heating from 3.75 W/m2 radiative forcing to account for observed and calculated increased heat content of oceanic, atmospheric and surface masses. This will not be a sign that CO2 warming is greater than 3.75 W/m2, but that the number is different from 3.75. This means that whatever the situation is, the current IPCCs assumptions and calculations must be wrong.
There is, I expect, much more, not less, energy coming into the system than the IPCC can account for by CO2 forcing or water-vapour feedback. An increase in insolation must be involved, possibly by a change in the timing of cloud cover variations through the year and position on the globe, if not by a simple total cloud cover/decreased albedo over the planet.
As noted, this comment is partly a request for help. First to check the math and the concept! and second, to be advised on the probable mass, heat capacity and (by consequence) the energy retained by the atmosphere between 1970 and 2002. The AHC, by comparison to the OHC. Third, from earth scientists or engineers working with buried structures, the what the heat capacity of various ground and plant materials might be.
All we are working with is 0.46E23 Joules, 30.7% of what 0.222 W/m2 of CO2 induced radiative heat retention is supposed to have occurred between 1970 and 2002 by IPCC dogma. If we can see that it is not enough, the 3.75 W/m2 of radiative forcing by a doubling of CO2 is, by another direction, busted.
Bob,
Very good post. Figure 5 was especially interesting. Do you plan to submit this analysis to a journal? I highly recommend that you do.
Ron Cram says: “Figure 5 was especially interesting. Do you plan to submit this analysis to a journal?”
Nope. I’m just a blogger.
So for those pub-style arguments, do I say
“the Warmists say the oceans should be heating up rapidly, but the ARGO data shows they have hardly warmed up at all”
or
“the Warmists say the oceans should be heating up rapidly, but the ARGO data shows they haven’t warmed up at all”
Bob,
Ryan O’Donnell was just a blogger when he became lead author of the paper refuting Steig 2009. Perhaps you can convince an often published author to help you tighten up the analysis for publication. I would suggest Roger Pielke or Criag Loehle. Seriously, Bob, I think you have made a contribution here.
For those interested, I’ve moved my blog to WordPress.
http://bobtisdale.wordpress.com/