Guest Post by Willis Eschenbach
Well, in my last post I thought that I had seen nature at its worst … Nature Magazine, that is. But now I’ve had a chance to look at the other paywalled Nature paper in the same issue, entitled Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000, by Pardeep Pall, Tolu Aina, Dáithí A. Stone, Peter A. Stott, Toru Nozawa, Arno G. J. Hilberts, Dag Lohmann and Myles R. Allen (hereinafter Pall2011). The supplementary information is available here, and contains much of the concepts of the paper. In the autumn of 2000, there was extreme rainfall in southwest England and Wales that led to widespread flooding. Pall2011 explores the question of the expected frequency of this type of event They conclude (emphasis mine):
… in nine out of ten cases our model results indicate that twentieth century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
Figure 1. England in the image of Venice, Autumn 2000. Or maybe Wales. Picture reproduced for pictorial reasons only, if it is Wales, please, UKPersons, don’t bust me, I took enough flak for the New Orleans photo in Part 1. Photo Source
To start my analysis, I had to consider the “Qualitative Law of Scientific Authorship”, which states that as a general rule:
Q ≈ 1 / N^2
where Q is the quality of the scientific study, and N^2 is the square of the number of listed authors. More to the point, however, let’s begin instead with this. How much historical UK river flow data did they analyze to come to their conclusions about UK flood risk?
Unfortunately, the answer is, they didn’t analyze any historical river flow data at all.
You may think I’m kidding, or that this is some kind of trick question. Neither one. Here’s what they did.
They used a single seasonal resolution atmospheric climate computer model (HadAM3-N144) to generate some 2,268 single-years of synthetic autumn 2000 weather data. The observed April 2000 climate variables (temperature, pressure, etc) were used as the initial values input to the HadAM3-N144 model. The model was kicked off using those values as a starting point, and run over and over a couple thousand times. The authors of Pall2011 call this 2,268 modeled single years of computer-generated weather “data” the “A2000 climate”. I will refer to it as the A2000 synthetic climate, to avoid confusion with the real thing.
The A2000 synthetic climate is a universe of a couple thousand single-year outcomes of one computer model (with a fixed set of internal parameter settings), so presumably the model space given those parameters is well explored … which means nothing about whether the actual variation in the real world is well explored by the model space. But I digress.
The 2,268 one-year climate model simulations of the A2000 autumn weather dataset were then fed into a second much simpler model, called a “precipitation runoff model” (P-R). The P-R model estimates the individual river runoff in SW England and Wales, given the gridcell scale precipitation.
In turn, this P-R model was calibrated using the output of a third climate model, the ERA-40 computer model reanalysis of the historical data. The ERA-40, like other models, outputs variables on a global grid. The authors have used multiple linear regression to calibrate the P-R model so it provides the best match between the river flow gauge data for the 11 UK rainfall catchments studied, and the ERA-40 computer reanalysis gridded data. How good is the match with reality? Dunno, they didn’t say …
So down at the bottom there is some data. But they don’t analyze that data in any way at all. Instead, they just use it to set the parameters of the P-R model.
Summary to date:
• Actual April 2000 data and actual patterns of surface temperatures, air pressure, and other variables are used repeatedly as the starting point for 2,268 one-year modeled weather runs. The result is called the A2000 synthetic climate. This 2,268 single years of synthetic weather is used as input to a second Precipitation-Runoff model. The P-R model is tuned to the closest match with the gridcell precipitation output of the ERA-40 climate reanalysis model. Using the A2000 weather data, the P-R model generates 2,268 years of synthetic river flow and flood data.
So that’s the first half of the game.
For the second half, they used the output of four global circulation climate models (GCMs). They used those four GCMs to generate what a synthetic world would have looked like if there were no 20th century anthropogenic forcing. Or in the words of Pall2011, each of the four models generated “a hypothetical scenario representing the “surface warming patterns” as they might have been had twentieth-century anthropogenic greenhouse gas emissions not occurred (A2000N).” Here is their description of the changes between A2000 and A2000N:
The A2000N scenario attempts to represent hypothetical autumn 2000 conditions in the [HadAM3-N144] model by altering the A2000 scenario as follows: greenhouse gas concentrations are reduced to year 1900 levels; SSTs are altered by subtracting estimated twentieth-century warming attributable to greenhouse gas emissions, accounting for uncertainty; and sea ice is altered correspondingly using a simple empirical SST–sea ice relationship determined from observed SST and sea ice.
Interesting choice of things to alter, worthy of some thought … fixed year 1900 greenhouse gases, cooler ocean, more sea ice, but no change in land temperatures … seems like that would end up with a warm UK embedded in a cooler ocean. And that seems like it would definitely affect the rainfall. But let us not be distracted by logical inconsistencies …
Then they used the original climate model (HadAM3-N144), initialized with those changes in starting conditions from the four GCM models, combined with the same initial perturbations used in A2000 to generate another couple thousand one-year simulations. In other words, same model, same kickoff date (I just realized the synthetic weather data starts on April Fools Day), different global starting conditions from output of the four GCMs. The result is called the A2000N synthetic climate, although of course they omit the “synthetic”. I guess the N is for “no warming”.
These couple of thousand years of model output weather, the A2000N synthetic climate, then followed the path of the A2000 synthetic climate. They were fed into the second model, the P-R model that had been tuned using the ERA-40 reanalysis model. They emerged as a second set of river flow and flood predictions.
Summary to date:
• Two datasets of computer generated 100% genuine simulated UK river flow and flood data have been created. Neither dataset is related to actual observational data, either by blood, marriage, or demonstrated propinquity, although to be fair one of the models had its dials set using a comparison of observational data with a third model’s results. One of these two datasets is described by the authors as “hypothetical” and the other as “realistic”.
Finally, of course, they compare the two datasets to conclude that humans are the cause:
The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
Summary to date
• The authors have conclusively shown that in a computer model of SW England and Wales, synthetic climate A is statistically more prone to synthetic floods than is synthetic climate B.
I’m not sure what I can say besides that, because they don’t say much beside that.
Yes, they show that their results are pretty consistent with this over here, and they generally agree with that over, and by and large they’re not outside the bounds of these conditions, and that the authors estimated uncertainty by Monte Carlo bootstrapping and are satisfied with the results … but considering the uncertainties that they have not included, well, you can draw your own conclusions about whether the authors have established their case in a scientific sense. Let me just throw up a few of the questions raised by this analysis.
QUESTIONS FOR WHICH I HAVE ABSOLUTELY NO ANSWER
1. How were the four GCMs chosen? How much uncertainty does this bring in? What would four other GCMs show?
2. What are the total uncertainties when the averaged output of one computer model is used as the input to a second computer model, then the output of the second computer model is used as the input to a third simpler computer model, which has been calibrated against a separate climate reanalysis computer model?
3. With over 2000 one-year realizations, we know that they are exploring the HadAM3-N144 model space for a given setting of the model parameters. But are the various models fully exploring the actual reality space? And if they are, does the distribution of their results match the distribution of real climate variations? That is an unstated assumption which must be verified for their “nine out of ten” results to be valid. Maybe nine out of ten model runs are unrealistic junk, maybe they’re unalloyed gold … although my money is on the former, the truth is there’s no way to tell at this point.
4. Given the warnings in the source of the data (see below) that “seldom is it safe to allow the [river gauge] data series to speak for themselves”, what quality control was exercised on the river gauge data to ensure accuracy in the setting of the P-R modeled parameters? In general, flows have increased as more land is rendered impermeable (roads, parking lots, buildings) and as land has been cleared of native vegetation. This increases runoff for a given rainfall pattern, and thus introduces a trend of increasing flow in the results. I cannot tell if this is adjusted for in the analysis, despite the fact that the river gauge records are used to calibrate the P-R model.
5. Since the P-R model is calibrated using the ERA-40 reanalysis results, how well does it replicate the actual river flows year by year, and how much uncertainty is there in the calculated result?
6. Given an April 1 starting date for each of the years for which we have records, how well does the procedure outlined in this paper (start the HadAM3-N144 on April Fools Day to predict autumn rainfall) predict the measured 80 years or so of rainfall for which we have actual records?
7. Given an April 1 starting date for each of the years for which we have records, how well does the procedure outlined in this paper (start the HadAM3-N144 on April Fools Day to predict river flows and floods) predict the measured river flows for the years and rivers for which we have actual records?
8. In a casino game, four different computer model results are compared to reality. Since they predict different outcomes, if one is right, then three are wrong. All four may be wrong to a greater or lesser degree. Payoff on the bet is proportional to correlation of model to reality. What is the mathematical expectation of return on a $1 bet on one of the models in that casino … and what is the uncertainty of that return? Given that there are four models, will betting on the average of the models improve my odds? And how is that question different from the difficulties and the unknowns involved in estimating only this one part of the total uncertainty of this study, using only the information we’ve been given in the study?
9. There are a total of six climate models involved, each of which has different gridcell sizes and coordinates. There are a variety of methods used to average from one gridcell scheme to another scheme with different gridcell sizes. What method was used, and what is the uncertainty introduced by that step?
10. The study describes the use of one particular model to create the two sets of 2,000+ single years of synthetic weather … how different would the sets be if a different climate model were used?
11. Given that the GCMs forecast different rainfall patterns than those of the ERA-40 reanalysis model, and given that the P-R model is calibrated to the ERA-40 model results, how much uncertainty is introduced by using those same ERA-40 calibration settings with the GCM results?
12. Did they really start the A2000N simulations by cooling the ocean and not the land as they seem to say?
As you can see, there are lots of important questions left unanswered at this point.
Reading over this, there’s one thing that I’d like to clarify. I am not scornful of this study because it is wrong. I am scornful of this study because it is so very far from being science that there is no hope of determining if this study is wrong or not. They haven’t given us anywhere near the amount of information that is required to make even the most rough judgement as to the validity of their analysis.
BACK TO BORING OLD DATA …
As you know, I like facts. Robert Heinlein’s comment is apt:
What are the facts? Again and again and again-what are the facts? Shun wishful thinking, ignore divine revelation, forget what “the stars foretell,” avoid opinion, care not what the neighbors think, never mind the unguessable “verdict of history”–what are the facts, and to how many decimal places? You pilot always into an unknown future; facts are your single clue. Get the facts!
Because he wrote that in 1973, the only thing Heinlein left out was “beware computer model results.” Accordingly, I went to the river flow gauge data site referenced in Pall2011, which is here. I got as far as the part where it says (emphasis mine):
Appraisal of Long Hydrometric Series
… Data precision and consistency can be a major problem with many early hydrometric records. Over the twentieth century instrumentation and data acquisition facilities improved but these improvements can themselves introduce inhomogeneities into the time series – which may be compounded by changes (sometimes undocumented) in the location of the monitoring station or methods of data processing employed. In addition, man’s influence on river flow regimes and aquifer recharge patterns has become increasingly pervasive, over the last 50 years especially. The resulting changes to natural river flow regimes and groundwater level behaviour may be further affected by the less perceptible impacts of land use change; although these have been quantified in a number of important experimental catchments generally they defy easy quantification.
So like most long-term records of natural phenomena, this one also has its traps for the unwary. Indeed, the authors close out the section by saying:
It will be appreciated therefore that the recognition and interpretation of trends relies heavily on the availability of reference and spatial information to help distinguish the effects of climate variability from the impact of a range of other factors; seldom is it safe to allow the data series to speak for themselves.
Clearly, the authors of Pall2011 have taken that advice to heart, as they’ve hardly let the data say a single word … but on a more serious note, since this is the data they used regarding “climate variability” to calibrate the P-R model, did the Pall2011 folks follow the advice of the data curator? I see no evidence of that either way.
In any case, I could see that the river flow gauge data wouldn’t be much help to me. I was intrigued, however, by the implicit claim in the paper that extreme precipitation events were on the rise in the UK. I mean, they are saying that the changing climate will bring more floods, and the only way that can happen is if the UK has more extreme rains.
Fortunately, we do have another dataset of interest here. Unfortunately it is from the Hadley Centre again, this time the Hadley UK Precipitation dataset of Alexander and Jones, and yes, it is Phil Jones (HadUKP). Fortunately, the reference paper doesn’t show any egregious issues. Unfortunately but somewhat unavoidably, it uses a complex averaging system. Fortunately, the average results are not much different from a straight average on the scale of interest here. Unfortunately, there’s no audit trail so while averages may only be slightly changed, there’s no way to know exactly what was done to a particular extreme in a particular place and time.
In any case, it’s the best we have. It lists total daily rainfall by section of the UK, and one of these sections is South West England and Wales, which avoids the problems in averaging the sections into larger areas. Figure 2 shows the autumn maximum one-day rainfall for SW England and Wales, which was the area and time-frame Pall2011 studied regarding the autumn 2000 floods:
Figure 2. Maximum autumn 1-day rainfall, SW England and Wales, Sept-Oct-Nov. The small trend is obviously not statistically different from zero.
The extreme rainfall shown in this record is typical of records of extremes. In natural records, the extremes rarely have a normal (Gaussian or bell-shaped) distribution. Instead, typically these records contain a few extremely large values, even when we’re just looking at the extremes. The kind of extreme rainfalls leading to the flooding of 2000 are seen in Figure 3. I see this graph as a cautionary tale, in that if the record had started a year later, the one-day rainfall in 2000 would be by far the largest in the record.
In any case, for the 70 years of this record there is no indication of increasing flood risk from climate factors. Pall2011 has clearly shown that in two out of three of the years of synthetic climate B, the chance of a synthetic autumn flood in a synthetic SW England and Wales went up by 90%, over the synthetic flood risk in synthetic climate A.
But according to the observational data, there’s no sign of any increase in autumn rainfall extremes in SW England and Wales, so it seems very unlikely they were talking about our SW England and Wales … gives new meaning to the string theory claim of multiple parallel universes, I guess.
IMPLICATIONS OF THE PUBLICATION OF THIS STUDY
It is very disturbing that Nature Magazine would publish this study. There is one and only one way in which this study might have stood the slightest chance of scientific respectability. This would have been if the authors had published the exact datasets and code used to produce all of their results. A written description of the procedures is pathetically inadequate for any analysis of the validity of their results.
At an absolute minimum, to have any hope of validity the study requires the electronic publication of the A2000 and A2000N climates in some accessible form, along with the results of simple tests of the models involved (e.g. computer predictions of autumn river flows, along with the actual river flows). In addition, the study needs an explanation of the ex-ante criteria used to select the four GCMs and the lead model, and the answers to the questions I pose above, to be anywhere near convincing as a scientific study. And even then, when people finally get a chance to look at the currently unavailable A2000 and A2000N synthetic climates, we may find that they bear no resemblance to any reality, hypothetical or otherwise …
As as result, I put the onus on Nature Magazine on this one. Given the ephemeral nature of the study, the reviewers should have asked the hard questions. Nature Editors, on the other hand, should have required that the authors post sufficient data and code so that other scientists can see if what they have done is correct, or if it would be correct if some errors were fixed, or if it is far from correct, or just what is going on.
Because at present, the best we can say of the study is a) we don’t have a clue if it’s true, and b) it is not falsifiable … and while that looks good in the “Journal of Irreproducible Results“, for a magazine like Nature that is ostensibly about peer-reviewed science, that’s not a good thing.
w.
PS – Please don’t construe this as a rant against computer models. I’ve been programming computers since 1963, longer than many readers have been around. I’m fluent in R, C, VBA, and Pascal, and I can read and write (slowly) in a half-dozen other computer languages. I use, have occasionally written, and understand the strengths, weaknesses, and limitations of a variety computer models of real-world systems. I am well aware that “all models are wrong, and some models are useful”, thats why I use them and study them and occasionally write them.
My point is that until you test, really test your model by comparing the output to reality in the most exacting tests you can imagine, you have nothing more than a complicated toy of unknown veracity. And even after extensive testing, models can still be wrong about the real world. That’s why Boeing still has test flights of new planes, despite using the best computer models that billion$ can buy, and despite the fact that modeling airflow around a plane is orders of magnitude simpler than the modeling global climate …
I and others have shown elsewhere (see my thread here, the comment here, and the graphic here) that the annual global mean temperature output of NASA’s pride and joy climate model, the GISS-E GCM, can be replicated to 98% accuracy by the simple one-line single-variable equation T(n) = [lambda * Forcings(n-1)/tau + T(n-1) ] exp(-1/tau) with T(n) being temperature at time n, and lambda and tau being constants of climate sensitivity and lag time …
Which, given the complexity of the climate, makes it very likely that the GISSE model is both wrong and not all that useful. And applying four of that kind of GCMs to the problem of UK floods certainly doesn’t improve the accuracy of your results …
The problem is not computer models. The problem is Nature Magazine trying to pass off the end results of a long computer model daisy-chain of specifically selected, untested, unverified, un-investigated computer models as valid, falsifiable, peer-reviewed science. Call me crazy, but when your results represent the output of four computer models, which are fed into a fifth computer model, whose output goes to a sixth computer model, which is calibrated against a seventh computer model, and then your results are compared to a series of different results from the fifth computer model but run with different parameters, in order to demonstrate that flood risks have changed from increasing GHGs … well, when you do that, you need to do more than wave your hands to convince me that your flood risk results are not only a valid representation of reality, but are in fact a sufficiently accurate representation of reality to guide our future actions.
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Roy Clark says:
February 24, 2011 at 8:55 pm
I looked at that, and my bad number detector went off. I didn’t have a clue what the real answer was, it just seemed that your answer of 65 microns was way too small. So I ran the numbers. Here’s what I get, check my figures.
Latent heat of vaporization at 15°C ≈ 2,465 kJ needed to evaporate one kilo
Since one joule is one watt-second,
1.7 W/m2 = 1.7 J/m2-sec times 3.16E7 sec/year = 53,648 kJ/yr per square meter from a forcing of 1.7 W/m2
53,684 kJ/m2-yr divided by 2,465 kJ / kilo = 21.6 kilos of water evaporated per square metre per year.
Now, 1 mm of water over 1 square metre is one kg. So that means the evaporation would be on the order of 22 mm per square metre per year.
Of course, that is the maximum, if all the 1.7 w/m2 goes into evaporation.
Another way to estimate the number is like this. The total downwelling radiation (solar + IR) at the surface is about half a kilowatt. This evaporates an average on the order of one metre of water per year over the global surface. This means each W/m2 is evaporating on the order of 2 mm of water. That would give us 3.4 mm evaporated for 1.7 W increase … but the number is likely larger because both wind and Clausius-Clapeyron evaporation rates go up quickly at tropical SST temperatures.
If my numbers are wrong, please let me know.
Regardless of the penetration depth, the IR radiation is in fact absorbed by the ocean. Because of the constant motion of the surface due to wind and wave, some portion of that energy is entrained into the mixed layer. So while more absorbed IR energy is likely to be re-radiated or evaporated quickly compared to solar energy which is absorbed at depth, it is only able to be re-radiated or evaporated because it has been absorbed by the ocean, and by the “basic laws of physics”, in general that warms the ocean.
In addition, since absorbed IR energy is more likely to quickly evaporated away than solar energy, how would that not affect the rainfall?
If only it were entertaining, I’d agree with you … reading it just gives me a headache.
w.
davidc says:
February 24, 2011 at 8:20 pm
Thanks, DavidC. Whether you or I would want to look at the code is immaterial, I have enough trouble reading my own code. The code should be published so that when people have questions that only the code can answer, it is available for their inspection to answer the question.
Note that I’m not referring to the model code, that is done by someone outside the current study. I’m talking about the code and data for what they have done to stitch together their Frankenstein creation.
w.
The Daily Telegraph reported this ‘study’ back on the 16th.
http://www.telegraph.co.uk/earth/earthnews/8328705/Floods-caused-by-climate-change.html
I can only repeat now what I said then.
If climate change has made floods such as we saw in 2000 approximately twice as likely, then we should be able to discern direct evidence of this. A careful study of the frequency and severity of flooding in the UK in recent years, compared to similar periods in the past, should show a significant change.
This is what research means. Research means learning from nature. When significant results are found in this way then theories can be formed and tested by further research.
In climate science this scientific process has increasingly been turned on its head. People tweak computer models, as apparently in this case, to try to support their chosen theory, and call that research. Computer models are not research. They are at best analysis of data and predictions from theory – at worst mere speculation.
If the authors of this paper can present evidence that flooding is now more frequent or more severe, then they may offer theories to account for this fact which can be tested against future observations. If they can’t, then their computer modelling is just idle speculation. It is in no sense scientific research.
I wonder where they got the sea-ice conditions in 1900 to start the models? The data that far back is very scrappy. There is reasonably good coverage in summer in the North Atlantic sector but practically nothing anywhere else.
The referenced Nature article is beyond bizarre, intellectual bankruptcy at its
“Robust,” eh? We all know what that word means.
“To start my analysis, I had to consider the “Qualitative Law of Scientific Authorship”, which states that as a general rule: Q ≈ 1 / N^2.”
I think you forgot to multiply by the square root of minus one to adjust for Climatological studies. Thus Q = i/N², since we’re dealing with imaginary science by pixillated scientists.
Presumably, the following comment from Lance Wallace means that Nature is now going to cease publishing any more climate scare stories, as the purveyors of this ‘science’ are never prepared to disclose this.
“Willis, Anthony, others–have you noticed that as of Feb 11, 2011, Science magazine will now require that authors provide the computer code and make the data available in a Web-based archive? See Science v331, p. 649.”
The picture is of the River Ouse in the centre of York (in Yorkshire, north of England).
As I child I used to visit there often in the 60’s (excellent museums, including the Rail Museum – essential visiting for small boys).
We used to marvel at the marks painted on the side of the buildings showing the heights of various floods over the years. Heavy rain on the east side of the Pennines (hill ridge down the spine of England) leads to flooding in York. Has done for hundreds of years.
Willis – Thanks for the admirable demonostration of your research methods. I was only one bridge out but ‘trying to help’. Having lived and worked in many countries throughout the globe and having been involved in some instances of natural disasters I can understand your considered reaction to the photo.
Bonne journee
Well if Peter Stott is involved, they’ve probably had access to the Hadley Centre super computer – we already know how accurate that can be.
More Met Office propaganda.
Noticed Stott he of the MetOff model man. I think he is the gardian of the model. I wonder why they buried his name in list of idiots.
Here is the precipitation record for those areas per seasons:
SW England 1873-2010
http://climexp.knmi.nl/plotseries.cgi?someone@somewhere+p+HadSWEP_monthly_qc+SW_England+precipitation+season
Englad&Wales 1766-2010
http://climexp.knmi.nl/plotseries.cgi?someone@somewhere+p+HadEWP_monthly_qc+England-Wales+precipitation+season
And here is annual precipitation for the above, with clear multidecadal pattern
http://climexp.knmi.nl/data/pHadEWP_monthly_qc_mean1a.png
Feel free to recognize the anthropogenic signal.
Mark Nutley says:
February 24, 2011 at 5:09 pm
I am not even reading the comments before hand, excuse the rudeness, But what a load of bollocks. The floods in the north of england was due to the last labour government cutting the budget for river and canal clearing, it was bugger all to do with Co2. and everything to do with incompetence.
//////////////////////////////////////////////////////////
Mark is right.
It is land use and in particular mismanagement, not ‘climate change/disruption’ which has excaserbated flooding. We now build on flood plains and then appear dumb founded when every 15 or so years there is a significant flood in that area. We tarmac over land which would in the past have acted as a natural drain/soak but now causes large run offs. Our drains and suers have not been updated to cope with the extra houses etc.
Water is a valuable commodity. Increased precipitation would be a good thing but it has to be properly managed and when properly managed, there is no significant problems.
The real reason flooding in the UK has increased is that the Environment Agency has decided not to dredge rivers. Rivers naturally silt up and flood onto the flood plane named for this very reason. Dredging would reduce or even remove this risk. Stopping dredging is for money saving and probably to help persuade people that climate change is due to human input. It also means that homes built on flood plane can no longer get any insurance covering flood risk which was obtainable a few years ago.
Willis Eschenbach at February 24, 2011 at 11:13 pm commenting upon a comment made by Roy Clark at February 24, 2011 at 8:55 pm
Clark: “The penetration depth of LWIR radiation into the ocean is also less than 100 micron, so it is impossible for a 100 ppm increase in atmospheric CO2 concentration to have any effect on ocean temperatures or rainfall extremes.”
Willis: “Regardless of the penetration depth, the IR radiation is in fact absorbed by the ocean. Because of the constant motion of the surface due to wind and wave, some portion of that energy is entrained into the mixed layer…”
//////////////////////////////////////////////////////////
My understanding is that 90% of the LWIR penetrates no more than 10 microns. The remaining 10% may penetrate upti a further 10 or so microns but for all practical purposes, the LWIR is fully absorbed within about 15 microns.
Willis, I consider that your rebuttal comment to be pure speculation. Where is the empirical data proving your assertion? What experiments have been carried out substantiating this vital point?
This is a vital point (and in my view one of the main failings with the AGW conjecture/hypothesis) since if this LWIR cannot heat the oceans, there can be no AGW (given that the oceans represent about 70% of the surface area of the Earth and given the substantial difference between the latent heat energy of air and water; ignoring the heat capacity below the cantle/crust, the oceans store probably about 99.9% of the heat energy of the Earth).
It is extremely difficult to see any mechanism whereby this energy can become entrained in the ocean. It is probable that this energy simply evaporates the top 10 to 15 microns of the ocean and if anything has a cooling effect.
Willis, I await to see your data and its sources.
richard verney says:
February 25, 2011 at 1:49 am (Edit)
Willis Eschenbach at February 24, 2011 at 11:13 pm commenting upon a comment made by Roy Clark at February 24, 2011 at 8:55 pm
Clark: “The penetration depth of LWIR radiation into the ocean is also less than 100 micron, so it is impossible for a 100 ppm increase in atmospheric CO2 concentration to have any effect on ocean temperatures or rainfall extremes.”
Willis: “Regardless of the penetration depth, the IR radiation is in fact absorbed by the ocean. Because of the constant motion of the surface due to wind and wave, some portion of that energy is entrained into the mixed layer…”
//////////////////////////////////////////////////////////
My understanding is that 90% of the LWIR penetrates no more than 10 microns. The remaining 10% may penetrate upti a further 10 or so microns but for all practical purposes, the LWIR is fully absorbed within about 15 microns.
Willis, I consider that your rebuttal comment to be pure speculation. Where is the empirical data proving your assertion? What experiments have been carried out substantiating this vital point?
Well, there is realclimate’s writeup on Minnet’s theory and the experiment carried out using the Aeri pyrgeometer.
lol.
But the real point is that that the amount of energy from back radiation mixed down when the wind ruffles the ocean surface is negligible compared to the extra cooling effect caused by that same wind breaking the surface up and permitting additional convection and radiation of heat from the ocean to the air.
The greenhouse effct doesn’t work by the direct warming of the ocean by back radiation. It works (to whatever extent it does) by thickening the atmosphere and causing the ocean to cool at a slightly slower rate relative to the insolation which actually does warm it.
As a Yorkshire resident who once lived in a flat in the building on the bottom left of this picture, and as regular frequenter of the pub on King’s Staith, I can assure you all that flooding occurs there almost every year and has done so for a very long time.
The pub itself is fitted out for a quick evacuation when the waters rise. The beer cellar is upstairs. All the electric points are also up above. The floors and benches are stone flagged. The soft furnishings quickly moveable.
I suppose the lesson to be learned is that, rather than wasting money trying to stop the floods, it is perhaps wiser to accept that they happen and adjust accordingly.
Thank you – a masterclass in pure logic.
When I saw this study reported on the BBC I nearly threw a brick through the telly. The problem is that the “bloke down the pub” may think that if all of these clever people used thousands of computers to show this it must be true. I asked one bloke “if all of these conditions applied in 2000, why did we not have severe floods in 1999 and 2001 as well?” I am still waiting for an answer. This was the worst example of “cherry picking in hindsight” I have ever seen!
I think that computer modelling is a valuable tool in science and engineering, but only with proper safeguards. In the 1980s we were told that computational fluid dynamics (CFD) would make wind tunnels and flight test a thing of the past – but they were wrong (for one thing, CFD can not model turbulence (or chaos)). However, when CFD codes are validated with wind tunnel and flight test data they are extremely valuable. The key word, IMHO, is VALIDATED!
We seen a lot of these studies coming through…..
Steve M talks constantly of watching the pea under the thimble.
We are watching the construction of AR5 in real time……. it’s like the predictable script of a soap opera.
This stuff isn’t science, it’s a script being written before our eyes. Nature magazine is just a part of the production crew.
Wouldn’t it be great to use those supercomputers for something useful and constructive………
What a waste
Willis, another in your series of beautifully-crafted scientific deconstructions.
This paper, of course, was promoted in the UK Guardian by George Monbiot as further irrefutable proof of CAGW and fiercely defended by his usual team of aggressive believers. The Daily Telegraph also featured a similar piece by Louise Gray, but that was pulled within twent-four hours without explanation.
When I read the abstract of this paper, I found it impossible to believe that multiple model runs constitute any kind of ‘evidence’. As I read it, the countryman in me came to the fore and I pulled out my mental checklist of the causes of flooding and NONE of those causes featured in the paper.
These are:
1 Care and upkeep of all waterways, down to and including roadside drains
2 Additional buildings and roadways for new subdivisions, etc, on floodplains
3 Unusually heavy rains over a short period of time
Growing up and spending most of my life in a mountainous country with high rainfall in most areas (average rainfall is over one inch per day in the Fiordland area), one tends to look at how well kept waterways are and how much of the area of historic floodplains are conserved for their natural and essential purpose. I have observed over almost a decade in the UK that central and regional government see ‘the countryside’ as a picturesque irrelevance which is largely ignored; regular and sensible maintainence of it is avoided, a practice which tends to store up perils.
The UK will always be prone to severe follding while the locals persist in building in ancient watercourses, covering floodplains with concrete, bricks and tarmac and ignoring the need to keep every watercourse, no matter how insignificant, free of of impediment to flow.
Sorry should have typed We’ve
My crappy proofreading!! ‘flooding’, not ‘follding’. *&*&^&^%^!!
Sorry!
richard verney says:
February 25, 2011 at 1:49 am
Gads, sir, take a deep breath. If you don’t know if I have citations for them, how can you possibly say that my claims are “pure speculation”? Our word for today is “pre-judgement”. Can you say “pre-judgement”? I knew you could …
You could start by reading Part 1 of scienceofdoom’s excellent discussion of this very topic. Then Part 2. Then Part 3. At the end of that, you should be able to at least talk lucidly about the question … whether you agree with scienceofdoom or not.
Then consider the following question. The oceans receive on average about 170 W/m2 from the sun. Given their temperature, we know from Stefan Bolzmann that they are radiating about 390 W/m2 of IR upwards. We also estimate that they are losing about 70 W/m2 via evaporation, and another thirty or so to convection.
So if the oceans are not receiving any IR as you claim … why are they not frozen solid? Warmed by 170 W/m2 from the sun, cooling at the rate of about 500 W/m2 … what’s wrong with this picture?
w.
This paper isn’t even handwaving the science anymore, it is wildly flapping its arms to distract casual observers from the facts.
Well written, Mr. Eschenbach!
Another likely reason is that environmentalists recoiled from imposing man’s hand on nature. “Don’t touch it!” is their basic attitude. Dredging probably strikes them as an instance of Mastering Nature, a real no-no (to them).
starzmom says:
February 24, 2011 at 5:02 pm
Thank you Willis. And soon coming to another journal somewhere near you, is a different author quoting this stuff as gospel.
It has already been quoted with approval by Australia’s new Commissioner for Climate, a Prof Tim Flannery, palaeontologist. ABC TV, Q&A, 21 Feb 2011.
My surmise is that he had not read the paper, but knew the spin. C’mon Tim, ‘fess up. Had you read the paper?