Guest Post by Willis Eschenbach
We have gotten three more years of data for the CERES dataset, which is good, more data is always welcome. However, one of the sad things about the CERES dataset is that we can’t use it for net top-of-atmosphere (TOA) radiation trends. Net TOA radiation is what comes in (downwelling solar) minus what goes out (upwelling longwave and reflected solar). The difference between the two is the energy that is being stored, primarily in the ocean.
The problem is that according to the raw, unadjusted CERES data, there’s an average net TOA radiation imbalance of ~ 5 W/m2 … and that amount of imbalance would have fried the planet long ago. That means that there is some kind of systematic error between the three datasets (solar, reflected solar, and longwave).
So, the CERES folks have gone for second best. They have adjusted the CERES imbalance to match the Levitus ocean heat content (OHC) data. And not just any interpretation of the Levitus data. They used the 0.85 W/m2 imbalance from James Hansen’s 2004 “smoking gun” paper. Now to me, starting by assuming that there is a major imbalance in the system seems odd. In any case, since the adjustment is arbitrary, the CERES trends in net TOA radiation are arbitrary as well. Having said that, here’s a comparison of what the Levitus ocean heat content (OHC) data says, with what the CERES data says.
Figure 1. CERES and Levitus ocean heat content data compared. The CERES data was arbitrarily set to an average imbalance of +0.85 W/m2 (warming).
I must admit, I don’t understand the logic behind setting the imbalance to +0.85 W/m2. If you were going to set it to something, why not set to the actual trend over the period of the CERES data? My guess is that it was decided early on, say in 2006, when the trend was much closer to +0.85 W/m2 and people still believed James Hansen. In any case, the way they’ve set it doesn’t tell us much. Let’s see what else we can learn from the two datasets. First lets take a look at the full Levitus dataset, and its associated error estimates.
Figure 2. The Levitus ocean heat content (OHC) dataset (upper panel), and its associated error.
I gotta say, I’m simply not buying those errors. Why would the error in 2005 be the same as the error in 1955?
In any case, we’re interested in the period during which the CERES and the Levitus datasets overlap, which is March 2000 to February 2013. To compare the two, we can adjust the CERES trend to match the Levitus data. Figure 3 shows that relationship. I’ve included the error data (light black lines.
Figure 3. Ocean heat content, with the trend of the CERES data re-adjusted to match the Levitus data. Light black lines show standard error of the Levitus data.
Now, I’m sure that you all can see the problems. In the CERES data, the change from quarter to quarter is always quite small. And this makes sense. The ocean has huge thermal mass. But according to the Levitus data, in a single quarter the ocean takes huge jumps. These lead to excursions that are much larger than the error bars.
To visualize this, we can plot up the quarter-to-quarter changes in ocean heat content. Figure 4 shows that relationship.
Figure 4. Quarterly changes in the ocean heat content. Note that this shows the quarterly change in OHC, so the units are different from those in Figures 1 and 3. Standard errors of the quarterly change are larger than those of the quarterly data, because two errors are involved in the distance between the two points.
As Figure 4 highlights, the disagreements between the Levitus and the CERES data are profound. For some 60% of the Levitus data, the error bars do not intersect the CERES data …
Conclusions? Well, my first conclusion is that I put much more stock in the CERES data than I do in the Levitus data. This is because of the very tight grouping of the CERES data in Figures 3 and 4. Here are the boxplots of the data shown in Figure 4:
Figure 5. Boxplots of the quarter-to-quarter differences of the Levitus and CERES datasets.
Remember that the tight grouping of the CERES data is the net of three different datasets—solar, reflected solar, and longwave. If you can get that tight a group from three datasets, it indicates that even though their accuracy is not all that hot, their precision is quite good. It is for that reason that I put much more weight on the CERES data than the Levitus data.
And as a result, all that this does is reinforce my previous statements about the error bars of the Levitus data. I’ve held that they are way too small … and both Figures 3 & 4 show that the error bars should be at least twice as large.
Next, the CERES data doesn’t vary a lot from a straight line. In particular, it doesn’t show the change in trend between the early and the later part of the Levitus record.
Finally, the CERES data provides a very precise measurement of the quarterly changes in OHC. Not only is their overall variation quite small, but they are highly autocorrelated. In no case are they greater than 0.5e+22 joules.
So for me, until the Levitus quarter-to-quarter changes get down to well under 1e+22 joules, I’m not going to put a whole lot of weight on the Levitus data.
Regards,
w.
NOTE: see my previous post for the data and code.
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With regard to Willis’s “trend” chart above, a breakdown by reflected solar and outgoing longwave would be appreciated. It looks to me like there may be some ENSO fluctuations in there, and also it might make sense to compare to atmospheric temps. Have you looked at UAH daily LT over the same period?
Earth is not a barren rock with no atmosphere. Incoming solar energy creates wind (simplification). That equates to electromagnetic energy being converted to mechanical energy. You also have photosynthesis. I wouldn’t expect to have a balance of incoming and outgoing energy equaling zero. The solar energy is utilised someway and not necessarily as heat storage in the system
The central claim of the radiative greenhouse hypothesis is that adding radiative gases to the atmosphere will reduce the planets radiative cooling ability. The critical flaw here is believing that temperatures for moving fluids in a gravity field can be derived from SB equations alone.
If global warming was physically possible, a TOA radiation imbalance as radiative gas concentration was increasing would be the expected signature, however the CERES data is not fit for purpose. The error margin is simply too great to allow any conclusion given the small signal expected. The problem is similar to trying to extract a global temperature trend from surface stations. No amount of adjustment, homogenisation or “correction” will make inadequate data fit for purpose.
However, while new remote sensing instruments could answer the question, AGW can be disproved far more simply.
The radiative greenhouse hypothesis relies on the mis-application of SB equations to moving fluids in a gravity field. Climate scientists incorrectly claim a figure of -18C for surface Tav in the absence of radiative gases, then use down-welling LWIR to add 33C to arrive at the observed 15C surface Tav.
To understand why AGW is a physical impossibility you only need to model the planet correctly. Land, ocean and atmosphere need to be treated as separate bodies, and the ocean and atmosphere need to be treated as moving fluids in a gravity field. This is important because for moving fluids in a gravity field SB equations alone cannot determine their temperature profile. The relative height of energy entry and exit, fluid resistance and conductivity are critical to the pattern of non-radiative energy transports and the temperature profile within the fluid.
But even building a complex model of the planet using CFD is not needed to disprove the radiative greenhouse effect. A few cheap empirical experiments are all that are required.
1. Does the two shell radiative model work for surfaces that are not moving fluids?
http://i44.tinypic.com/2n0q72w.jpg
http://i43.tinypic.com/33dwg2g.jpg
http://i43.tinypic.com/2wrlris.jpg
The answer is yes.
2. Will this work for moving fluids in a gravity field?
http://i48.tinypic.com/124fry8.jpg
The answer is no.
3. Does incident LWIR heat or slow the cooling rate of the oceans?
http://i42.tinypic.com/2h6rsoz.jpg
The answer is no.
Climate scientists have tried to solve for “how cold would the surface be without radiative gases?”. What they should have asked is –
4. How hot would the surface get without an atmosphere?
http://i42.tinypic.com/315nbdl.jpg
Unlike other experiments I have posted in the past, I have not built this one. The need for near instantaneous and precise temperature control of the inflowing dry N2 and the liquid N2 cryo cooling are a significant cost barrier and “dark money” and “big oil dollars” seem only to exist in the minds of AGW believers.
Without an atmosphere our oceans would boil into space. Experiment 4 shows what would happen if a force field stopped that. The oceans would still be heated below the surface by SW and cooled at the surface by out going LWIR. But they can no longer cool by evaporation or conduction. How hot would they get? SB equations won’t provide the answer. SW heating is not an average flux, it is intermittent and occurs at depth. Speed of convection and fluid conduction become a factor.
I have conducted similar experiments with water samples and sunlight, however these suffered from conductive losses and were still exposed to DWLWIR. Temperatures easily exceeded 70C.
How hot or cold would the oceans really get without an atmosphere?
Will they freeze like the AGW doom mongers claim?
Or would it be boiled whale time?
(answers may be posted in on the back of a Turney’s Turkeys commemorative postcard)
Why is this question important?
The atmosphere cools the oceans.
Radiative gases cool the atmosphere.
Adding radiative gases to the atmosphere will not reduce the atmospheres radiative cooling ability.
AGW is a physical impossibility.
Perhaps you should publish a paper.
Latent heat is nearly completely ignored by K&T in their ridiculous energy exchange graphic in AR4, some 78W/m2 paired with evapotranspiration a biological process. Latent heat of evapouration of water is the reason why rainforests are cooler than deserts. (predictions using the theory of the GHE would claim the opposite).
I have a question which I hope Willis or somebody else can answer. We all hear regularly about how ocean warming is *bound* to cause sea level rise. I have read that ~52% by volume of the ocean is below a depth of 2000 metres. I also recall reading that this deep ocean water is extremely cold on average, with a temperature of 3 – 4°C. From high school physics I vaguely recall that water is at its densest at about 4°C. So if deep ocean water is, let’s say, 3.5°C, then surely heating it a little bit (ARGO data says 0.065°C) will cause it to contract, not expand, and sea levels to fall, not rise?
I would be grateful if somebody more knowledgeable than I could explain or clarify this.
KRJ Pietersen
What an excellent question.
There is a very useful graph here which shows the effect of water temperature on density. http://www1.lsbu.ac.uk/water/explan2.html
As far as I know there is very little difference in density between say 4C and 20C which would cover most of the oceans layers. What effect that density effect would have on the warm surface layer in the tropics I will leave for others to answer
tonyb
climatereason says:January 6, 2014 at 5:52 am
“KRJ Pietersen, What an excellent question.
There is a very useful graph here which shows the effect of water temperature on density. http://www1.lsbu.ac.uk/water/explan2.html”
Your graph is for fresh water; salt water has different properties near freezing. Salt water does not expand at 3-4 degrees F; but, it starts losing the sodium chloride, salt, heat of hydration of 4 KJoules per mole of sodium chloride. Only after all the sodium chloride to water bonds are broken will the water freeze. It is this heat of hydration that keeps most of the deep ocean at 3-4 degrees F.
In response to KRJ Pietersen
That would be the case if the ocean was freshwater. However, it is saline and does not exhibit the same characteristics. The lower the temperature the greater the density, increased temperature results in reduced density, hence expansion.
This is a little bit off topic, but relevant to the climate debate and also to your skills, Willis.
I know that questioning the GHG effect is not welcome on this site. As a chemistry graduate I know all about the IR activity of carbon dioxide and its characteristic absorption bands. However, there are a number of assumptions involved in the journey from atmospheric absorption of long wave Boltzmann radiation by CO2 to how effective this is in causing the atmosphere to warm up.
I’m referring for example to the question of energy transfer by collision between excited CO2 molecules and non-IR active nitrogen. Another question concerns how sure we are about the values assigned to theoretical earth temperatures with and without GHG and the contribution of CO2.
Your discussion above suggests to me that the Levitus data is too variable to be of any use and the imbalance indicated by the CERES data rather renders that useless too. We think there is an offset, but we don’t know why and we don’t know its true value. I do not know to what extent these datasets are used to underpin “the science” and alleged proof of warming.
I have a suspicion that much of global warming science involves uncertainties, assumptions, guesswork and “settled science” that would not survive objective close scrutiny of the kind illustrated above.
At a time when the CET record shows that temperatures today are similar to those of 23 years ago, we really do need to reconsider the GHG assumptions and calculations and the credibility of the numbers we use to calibrate the magnitude of the effect. A step by step critical review of this important topic is long overdue.
You guys are forgetting that the deep ocean is also under enormous pressure. This will behave differently from water in the ambient environment.
At any rate, you’d need to integrate the effects over the whole of the ocean from top to bottom. I haven’t seen an explicit calculation considering all factors, but the results of these are, apparently, that there is some small overall expansion.
Which is more of a “so what” than “no, that’s wrong!”
Nic Lewis says:
January 5, 2014 at 1:29 pm
Nic, here’s how I did it. I put the CERES TOA mean data into a 3-dimensional array, 180 latitude x 360 longitude x 156 months, called “toa_net_all”.
# the "rearrange" function below extracts the CERES variables and puts them in the # format I prefer, starting at the upper left corner of # a Pacific-centered map (Lat 90, Long -180) rearrange=function(nc,thefile){ aperm(get.var.ncdf(nc,thefile),c(2,1,3))[180:1,c(181:360,1:180),] } require(ncdf) # load ncdf package nc=open.ncdf("CERES_EBAF-TOA_Ed2.7_Subset_200003-201302.nc") # open file toa_net_all=rearrange(nc,"toa_net_all_mon") #extract the TOA dataThen I used the following code to take the area-weighted means
Let me know where the errors might be …
w.
Greg says:
January 5, 2014 at 1:53 pm
The residuals (data minus seasonal swings) are what Levitus is looking at in their OHC data.
The residuals from the energy necessary to melt the ice are quite small. I calculate them at about 0.1e+22 joules per month
And as a result, this is not visible in the TOA budget.
w.
johnmarshall says:
January 6, 2014 at 3:57 am
Say what? Latent heat gets lots of attention in the K/T budget. The paper is here. They estimate evapotranspiration by noting that what goes up must come down, so evaporation must equal precipitation.
Here’s their discussion of their calculations and their likely errors:
w.
KRJ Pietersen says:
January 6, 2014 at 4:18 am
The variation of sea level with ocean temperature is called the “steric” sea level. It’s pretty well understood. You might start with Anne Cazenave’s work here, or google “steric sea level”.
w.
PS—As others said, in the ocean, sea water continues to contract right up until freezing.
Willis Eschenbach says:
January 6, 2014 at 10:17 am
Thank you to Willis and others for taking the time to answer my question. It’s much appreciated.
As a follow up, has anybody looked into the contribution of so-called ‘primary water’, namely water produced by chemical reactions deep underground, to rising sea levels? I know that the prevailing view is that there is a fixed amount of water on Earth, but I have read that under certain conditions the rocks themselves can produce water. For example, super deep boreholes such as Kola in Russia have come up against phenomenal problems from water at levels at which no water is supposed to exist:
“And if the non-existence of an entire layer of the Earth’s crust is not surprising enough, the cracks of the rock many kilometers below the surface were found to be saturated with water. As free water is not supposed to exist at such great depths, researchers believe the water consists of hydrogen and oxygen atoms that have been squeezed out of the surrounding rock by the enormous pressure and retained below the surface due to a layer of impermeable rock above”.
http://www.atlasobscura.com/places/kola-superdeep-borehole
Regarding primary water, about the best review of the topic is here (please don’t be put off by the less-than-user-friendly way the article appears):
http://merlib.org/node/5063
It acknowledges the contributions of Adolf Erik Nordenskjold, nominated for the Nobel Prize for his work, Frank Wigglesworth Clarke, Armand Gautier, Josiah Edward Spurr and especially Stephan Reiss.
I have never seen ‘primary water’ mentioned on WUWT (I am a regular reader) or much anywhere else. Is it nonsense? To my mind (I am not a trained scientist) I can imagine rocks producing water very naturally given hydrogen, oxygen and great pressure.
What comments do others have?
@Willis…..”””””Say what? Latent heat gets lots of attention in the K/T budget. The paper is here. They estimate evapotranspiration by noting that what goes up must come down, so evaporation must equal precipitation…….””””””
So true, but not for everything.
Water (in the ocean) becomes water vapor (in the atmosphere) by gathering up (from the ocean) the latent heat of evaporation (590-690 cal per gram) which is readily available at the high KE end of the molecular energy distribution, thereby cooling the ocean surface. (only the hotter molecules evaporate).
This water vapor laden air, then rises, being lighter, than the dryer air, until it encounters at high altitude, air that is much colder, and dryer, which then proceeds to suck heat (latent) out of the water vapor, until it also is cool enough to condense on any available nuclei, to form water droplets, or if cold enough, give up another 80 cal per gram and become ice crystals.
So the latent heat energy, comes from the ocean surface layer (film if you like), and is deposited at some higher altitude, from where it can ultimately be lost to space by further convection, and ultimately, thermal radiation.
The water droplets or ice crystals (snow), no longer are in possession of the latent heat, so any subsequent precipitation, does NOT return the latent heat energy to the surface.
The latent heat does not heat the upper atmosphere (raise its Temperature). The heat flow is from the cooling water vapor laden air, to the even colder upper air, which is colder, because it is losing heat to even higher air. The Temperature of everything keeps falling as it expands into the emptiness of the upper atmosphere, at higher altitudes.
CERES data pertains entirely to radiative fluxes at TOA, i.e., largely to ATMOSPHERIC inputs and emissions. OHC data, which also has huge uncertainties due to lack of uniform spatial coverage, pertains to STORED thermal energy entirely below the atmosphere. While there is coupling between the two, the physical differences are intrinsic and should not be expected to produce comparable empirical features, such as quarterly variations. Much of the speculation here about the differences is geophysically misguided.
Hi Willis,
It’s nice to see you doing this work – especially since I am about to pick up the CERES data for something. It is a great datacheck. I am still hoping that you can reconcile your values with Nic Lewis.
However, my main comment is that according to my not very accurate eyeball, you appear to have picked up Levitus 0-700m data. Is that correct? If so, then I think you need also to benchmark your “no adjustment to CERES trend” data against the quarterly data for 0-2000m OHC data over recent years. According to most OHC analyses there is still ongoing heat gain below 700m. Conventional wisdom is that the OHC data should then be somewhere around 93% of the net energy gained from integrating the radiative flux imbalance.
To add to Paul_K, Willis – this is a great post. Scrolling through your comments back and forth with Nick, is it as simple as averaging the imbalance over global surface area (0.58) vs global ocean surface area (0.85)? I’ve wondered about the huge changes in quarterly OHC – especially in the 700-2000m range – and just assumed that’s why they still do pentadal averages regardless of what the error bars say.
PS I’ve looked at the energy budgets for other parts of the climate system and I don’t think they come anywhere close to having the capacity to absorb the quarterly jumps in anomalies in the OHC data.
1sky1,
The only way I could agree with your comment is if somehow the absolute OHC doesn’t actually undergo these huge quarterly changes, and they are an artefact of the anomaly process somehow.
bill_c:
The only way your comment makes any sense is if you misread mine.
1sky1,
You say:
I agree with the first two sentences. However, variations in that thermal energy stored in the oceans have to be compensated for by transfers to other parts of the earth system, or to space, for conservation of energy. So where does this energy go, if it is not lost to (or gained from) space? The atmosphere and cryosphere variabilities do not compensate, e.g. the latent heat of arctic sea ice changes at a rate of about 4 orders of magnitude below the quarterly fluctuations in OHC data. The energy content of the dry atmosphere varies at a rate of about 3 orders of magnitude less than the OHC data. There are contributions from land ice, antarctic sea ice, thermal heat storage in the continents, latent heat of evaporation/condensation etc., atmospheric kinetic energy, biomass etc. but nothing close to having the storage capacity required to offset the reported ocean changes. So if these losses and gains don’t show up in the CERES data, where are they?
bill_c:
Thermal energy STORED at significant depths in the ocean doesn’t have to go anywhere that currents don’t take it. Unfortunately, the known currents often take it to totally unmonitored locations, leaving the seasonal imprint of the very sparsely monitored ones. There’s no compelling physical reason why the truly global CERES data should manifest similar variability.