Like all human endeavours, the IPCC is not perfect. Despite the enormous efforts devoted to producing its reports with the multiple levels of peer review, some errors will sneak through. Most of these will be minor and inconsequential, but sometimes they might be more substantive. As many people are aware (and as John Nieslen-Gammon outlined in a post last month and Rick Piltz goes over today), there is a statement in the second volume of the IPCC (WG2), concerning the rate at which Himalayan glaciers are receding that is not correct and not properly referenced.
The statement, in a chapter on climate impacts in Asia, was that the likelihood of the Himalayan glaciers “disappearing by the year 2035” was “very high” if the Earth keeps warming at the current rate (WG 2, Ch. 10, p493), and was referenced to a World Wildlife Fund 2005 report. Examining the drafts and comments (available here), indicates that the statement was barely commented in the reviews, and that the WWF (2005) reference seems to have been a last minute addition (it does not appear in the First- or Second- Order Drafts). This claim did not make it into the summary for policy makers, nor the overall synthesis report, and so cannot be described as a ‘central claim’ of the IPCC. However, the statement has had some press attention since the report particularly in the Indian press, at least according to Google News, even though it was not familiar to us before last month.
It is therefore obvious that this error should be corrected (via some kind of corrigendum to the WG2 report perhaps), but it is important to realise that this doesn’t mean that Himalayan glaciers are doing just fine. They aren’t, and there may be serious consequences for water resources as the retreat continues. See also this review paper (Ren et al, 2006) on a subset of these glaciers.
East Rongbuk glacier just below Mt. Everest has lost 3-400 ft of ice in this area since 1921.
More generally, peer-review works to make the IPCC reports credible because many different eyes with different perspectives and knowledge look over the same text. This tends to make the resulting product reflect more than just the opinion of a single author. In this case, it appears that not enough people with relevant experience saw this text, or if they saw it, did not comment publicly. This might be related to the fact that this text was in the Working Group 2 report on impacts, which does not get the same amount of attention from the physical science community than does the higher profile WG 1 report (which is what people associated with RC generally look at). In WG1, the statements about continued glacier retreat are much more general and the rules on citation of non-peer reviewed literature was much more closely adhered to. However, in general, the science of climate impacts is less clear than the physical basis for climate change, and the literature is thinner, so there is necessarily more ambiguity in WG 2 statements.
In future reports (and the organisation for AR5 in 2013 is now underway), extra efforts will be needed to make sure that the links between WG1 and the other two reports are stronger, and that the physical science community should be encouraged to be more active in the other groups.
In summary, the measure of an organisation is not determined by the mere existence of errors, but in how it deals with them when they crop up. The current discussion about Himalayan glaciers is therefore a good opportunity for the IPCC to further improve their procedures and think more about what the IPCC should be doing in the times between the main reports.
Update: This backgrounder presented by Kargel et al AGU this December is the best summary of the current state of the Himalayas and the various sources of misinformation that are floating around. It covers this issue, the Raina report and the recent Lau et al paper.
mircea: “Dhogaza (251) and Fed Up (250) I work in flight simulation (my company has done the first 787 ffs simulator) and everything that we do must be verified by measurements in the real A/C before it can enter in the simulation.”
But the scale size of turbulence is not modelled and therefore when you put your scale in the tunnel you don’t have the same system as the real thing.
You can put a boeing complete wing in the tunnel, but you’re missing the rest of the plane.
You rely on what you KNOW to be wrong not to matter because your simulation says this is good.
Jim: “It boasts of the huge installation at Altamont Pass, which on many sample inspections by me, a large percentage of the rotors are stationary”
And that less than 100% is taken into account, Jim.
It still works to 3-6c/kWh from 1996 technology.
We have bigger better and more effective rotors today.
It’s called “advancing technology” and works just like the progression from the nuclear power tech in the 50’s to the modern pebble bed reactor that has not yet proven itself safe.
” Jiminmpls says:
21 January 2010 at 7:28 PM
#256 CFU
I’m sorry, but you’re wrong on this one. The economics of wind power are always site specific”
And so is nuclear, coal, gas and all the other products:
If you’re near the mine AND the processing plant, your nuke plant is cheaper. If you’re on the coast, tidal power is cheaper.
The UK is windy.
Very windy.
You’re wrong.
Please show how the UK can be more than 5x more expensive for wind than the US.
PS: And it seems that the argument for why it’s not possible to do onshore wind power (despite the evidence of wind farms on land in the UK, with farming going on around it) is that people say it won’t work because people say it won’t work.
I.e. NIMBYs getting the groundwork in/
“265
Tom S says:
21 January 2010 at 8:07 PM
I think a lot of skeptics see the IPCC as an advocacy group with a serious case of group think.”
Which is a serious case of groupthink, don’t you think?
Or are you part of that groupthink, Tom?
“The IPCC is not infallible(shock!). Certainly not.But you, dear members of the group always told us about the highest scientific standards there. You called people with reasonable doubts “denialists”. And now your reaction to this informational desaster is sheer amusement? I wish you lots of readers at Real Climate. You´re turning lots of interested people into skeptics.
259, Don Shor: yes, I even quoted that myself.
In 1993, what was the biggest rotor available?
Now in 1999 you had how many years of operation to work out how much it costs. Do you have an adequate number of years to do the same measurement with modern more effective and efficient turbines? No.
But you DO know how much the smaller ones do, so your error isn’t going to be huge.
Not “yet more expensive than the older tech”.
And 7.5c is still lots cheaper than nuclear.
Again, how can this show that wind power has made nuclear power seem cheap?
“Well actually, you can do all those things in the buffer zones around nuclear power plants, too. ”
Which will have worse problems from the NIMBYs.
“Glowing milk???”
“It is worth noting some of the issues in siting wind farms; they can’t be too close to where people live due to the noise, there is avian mortality, etc”
The noise is a NIMBY complaint.
The avian mortality of sky scrapers are factors larger, yet you don’t see people tearing them down to save the little burdies, do you.
It’s another NIMBY complaint.
NOTE: the early small turbines spun quickly and therefore were hard to avoid.
Larger ones spin much slower (hence some efficiency gain) and massively reduce the mortality.
And we now have raptors using them as perches to wait out the search for food.
PS a lack of sites doesn’t make wind more expensive anyway.
PS re 281: however, do we build 787’s to deliberately kill the passengers? Do we build one complete aircraft merely to crash it and then never build another one?
But the only way to test that CO2 measurements (from real life, not models, even scale) and their emergent result in the computer model is to let the CO2 build up.
Then find another earth and change the CO2 concentrations.
Then find another earth…
But we look at what is happening now, and we see the models verified with THE REAL EARTH. Not scale model earths, but this real one.
We have checked that the models fit well enough to reality as we’ve seen in the past and letting that simulated earth evolve with higher CO2 causes many problems.
And we would rather avoid that on the world we have right now: letting it happen just to prove the model right is not done.
Just like if your scale model showed that a banking turn with a 15 mph crosswind would rip the wing off, you don’t go and build it anyway, just to see if that scale model was right.
Tom S: Another example is satellite data that does not match the existing upward trend.
BPL: Huh??? It does match the trend! Want the numbers?
@230, doubling turbine efficiency comes up against the fundamental physical limit of the Carnot cycle. This is something that comes in the first year of a mechanical engineering degree. I am assuming, by the way, that you mean the efficiency of the whole power generation cycle.
@239, you are correct and there are some problems with Prof MacKay’s book, and I have corresponded with him on one particular point. However, it is a far better source than any currently available and, from an engineering viewpoint, the problems are relatively minor. For those who haven’t bothered to read it the conclusions can be summarised quite briefly. We can deal with climate change without a massive change to our way of life but we do have to re-engineer our energy infrastructure. That means moving to a mainly electric economy. We have to take all the opportunities to be as efficient as possible in our use of energy. Power will have to come from all available forms of renewable and nuclear and in the case of the UK some power will still have to be imported. Key technologies will include the use of heat pumps for domestic heating, electric vehicles, wind, solar, tidal, wave and nuclear power.
@281, you are absolutely right about the fact that engineering models have to be verified. It is, however, worth noting that engineers at Boeing, Airbus, GE, Pratt and Rolls-Royce,as just a few examples, are pretty upset if the results are even 1% away from their models. If you have ever seen the overlay of a computer model and the actual film from an auto crash test, you will see how amazingly accurate the predication of even such a complex event can be. If climate modellers are anywhere near as good, then actual verification is not a big issue.
Garrett Jones: re # 235, this is an easy to find source, http://www.nasa.gov/worldbook/sun_worldbook.html, you will note the core and surface make up of the sun are rather different. I am sure God will also help you with your anger problem.
BPL: The metals fraction is still 2%, and the sun has no fusion processes which produce iron. You don’t get iron except in the cores of very large supergiants just before they go supernova. Having studied stellar astronomy for about forty years, I’m pretty familiar with how stars work. You, apparently, are not. If you think “the sun is made of iron” is in any way a legitimate statement, you are displaying blatant ignorance of the subject. I suggest you review a basic text on it, such as Phillips’s “The Physics of Stars” (1994).
Russell@269, the “averaging argument is bogus, because CO2 is such a long-lived gas, persisting centuries to millennia.
And yes, there are fluctuations of C-13/C-12–we can measure them in the ice cores. They don’t begin to approach the steady decline we’ve seen in the modern era. More half-truths from the denialist community. You can usually tell when the authors of the presentation choose to remain anonymous so as not to reveal their employers.
I merely wanted to give at least two big thumbs up for all the work you are doing. You’re fighting an uphill battle against ignorance, incompetence, disinformation and fast food science. Yet you seem to have oceans of patience. Keep up the good work and let’s hope policies and public opinion change before it’s too late. And let’s hope your estimations are proven wrong over time, however unlikely that seems to be at present.
Being a marketer I sense there are acute needs for improving AGW communication. It may be a political issue, but nonetheless it indirectly affects your everyday situation and the future of our planet. Therefore it needs to be addressed accordingly.
“Lots of reasons why it is not possible to put cheap wind farms on shore in the UK. One of the most important is the cost of land.” Matthew L@233
Tell me Matthew, have you ever been to the Netherlands? Or Denmark? In the latter, you’re scarcely ever out of sight of a wind turbine in the countryside. Yet both have far less land, far less land remote from cities, far less land that cannot be used for arable crops. The key differences are cultural and political. In both there is and long has been a far higher level of environmental concern. In Denmark specifically (don’t know offhand about Netherlands) most wind farms are community-owned: local people profit directly from them.
One uses the simulators/simulations to orient himself but then everything must be measured in real life (at least scaled models). – mircea
I’m interested to know how a scale model of a plane lets you test for several decades of use, bird strike, failure of one or more engines, take-off and landing in poor weather, etc, etc.
““Completely Fed Up”:
Your link doesn’t say anything about global wind costs.”
It does say that the costs in part of the world is much less than nuclear.
Which means your statement that “Both globally and in the UK, nuclear is cheaper than wind.” is wrong. (post #201).
“3.5 cents per kilowatt-hour.” Which seems to say very explicitly that this is not a calculation of actual costs.”
7.5c is a real figure from older and less efficient tech.
And that is less than nuclear.
“Even then, it appears to apply only to the US, and possibly only to California.”
And why would the US or possibly only california be so much cheaper to have wind power?
“I can’t imagine how you think a page entitled “Overview of Wind Energy in California” applies to the UK, far less the whole planet.”
I can’t figure out how you manage to say that the world shows wind more expensive than nuclear when it is definitely not true by a factor of 3 to 5 times to even be equal in cost.
And in the US, nuclear is subsidised to a level of about $7.2Bn a year. Is the UK subsidising nuclear much more than that?
A load of Bosch: “But you, dear members of the group always told us about the highest scientific standards there. ”
Highest doesn’t equal perfect.
Graham Cogley reports that the error can indeed be traced to a misreading of one of the inital references: the WG II claim that total glacier area “will likely shrink from the present 500,000 to 100,000 km^2 by the year 2035” it turns out that “2035” is a misreading of “2350” in Kotlyakov (1996, p66).
“Wind availability seems to be sort-of inversely proportional to the need for it.”
‘course, nuclear power supply has the same problem…
“Windmills can and have come apart in windstorms. The turbine part is wing-like, enabling that 60 ton machine to fly 1/3 mile. Do you want it landing on your head?” – Edward Greisch
This reminds me of a book I used to have: The ’80s: A Look Back – published in 1979 [sic]. Alongside an Arab conquest of Europe (because NATO lacked a counter-weapon to the scimitar), and the “International Year of the Simultaneous Orgasm” (when the Earth actually moved), it included a disaster with IIRC, 3,000 deaths, when a giant wind turbine collapsed. Was that your source, Edward?
Dan (#320) THAT is what I remembered!
Pity I can’t find it on the blogs I read.
Ta.
“Windmills can and have come apart in windstorms.”
They turn themselves off and freewheel with the rotors perpendicular to the wind.
Or did you think the engineers didn’t think of this???
“Completely Fed Up”:
I’m very sorry that you can’t get your head around these ideas. You are guilty of wishful thinking.
If wind were the panacea you seem to think, then we would be there already. Sadly, we have many miles yet to travel.
You just keep repeating the same thing, very loudly, in the vain hope that it will become fact by repetition. Doesn’t happen when deniers do it, doesn’t happen now.
Comparing costs of energy across different markets is *difficult*. You seem happy to take the first number you find. Again, that’s just wishful thinking. Find a meta-analysis that includes all energy types, and all countries – then, and only then, will you have a foundation to make claims and begin speculation about future trends.
And your claim, lost somewhere among your flood of posts, that “nuclear needs land, too!” made me laugh. Go on – just for your own education, calculate the power density for different forms of energy (in W/m²). Yes, we know wind doesn’t require dedicated land – but it requires land all the same. Landowners tend to demand something in return.
[Response: This discussion is very poor. Simple assertions without cites and repetitions of the same are pointless. If commenters want to continue this thread, find some actual sources of data. No more argument by personal belief please.- gavin]
Rod and Garrett,
Afraid BPL is 100% right on the composition of the sun. Sol is about a 3rd generation star, the condensation of ejecta from previous supernovae. All the elements from Li to Iron were produced in those previous stars (via the CNO cycle, not the H-H cycle). All the elements heavier than iron were made during the supernova collapses. This is well known science and uncontroversial.
Saying that “the Sun is iron” is absolute, bat-shit crazy.
Nick Gotts:
Nobody is claiming it can’t be done. The point is, it can’t always be done cheaply.
Wind in Denmark is cheaper than the UK, but more expensive than the US.
Wind in The Netherlands is significantly more expensive than some other countries – double the US, for example*.
Don’t be confused by “Completely Fed Up’s” made up magnitudes. The costs of energy do vary, but they don’t vary by all that much. When I say that one form of energy is cheaper than another, I am not claiming a huge difference. In some cases, it is really marginal. And always, always, always site-specific.
Simple economics (not to mention common sense) should indicate that energy production has to be competitive, so has to be at least comparable, in terms of cost.
* Why? I have no clue. If it interests you, why not try to find out?
“Go on – just for your own education, calculate the power density for different forms of energy (in W/m²).”
Easy.
http://www.awea.org/faq/basicwr.html
150 – 200 w/m2 at 15kts.
Climate Modeling:
SKEPTIC
I have been an engineer for over 25 years and have dealt with signal processing, neural networks, and various algorithm development projects in software. With a system as complex as the climate, it is very unlikely this will be accurate on the first many model revisions.
FUNDAMENTAL PROBLEM
The fundamental problem that is faced is one of validation, nobody knows whether it is accurate or not for 25+ years. When it becomes inaccurate, science is typically good at determining why it is inaccurate and making the model better. Science is great at explaining why things happened, but not so great at predicting the future.
EXAMPLES
Examples of this type of algorithm development are hurricane tracking (been living in FL for 25 years). The current spaghetti tracking models used in hurricane tracking are now pretty accurate at two to three days out and rarely leave the tracking “cone”. It used to be 12 hours or less 20 years ago.
A second example is weather forecasting. (I am not comparing weather to climate!) Weather forecast now is good 3 to 5 days or so, and it used to be one day, and not very accurate at that. It took 50 years.
The algorithms are constantly improved and will continue to get better. But it takes time to understand the causes and scale of the effects.
CURRENT PERFORMANCE
It is just not credible to me that these models are reliably accurate without ever been validated. The Hansen Rev 1980’s model was significantly too high, and the IPCC AR4 models are tracking too high currently, but more time is needed for any kind of judgment (the fundamental problem). Notably the error margins are very large.
INSTABILITY
The positive forcings placed in these models which allow them to accelerate temperature increases are inherently unstable. They are prone to run aways, high or low, when shown at much larger 5000+ year time scales.
BOTTOM LINE
I’ll believe it when I see it. I’d like to hear directly from the guys who wrote the algorithms and coded the models on how they believe they overcame the validation problem (and no, training and validating on past data is not sufficient).
[Response: Well that would be me, and I’ve explained it dozens of times (FAQ). But even if you don’t think that what we do is worthwhile, I fail to see that uncertainty in projections is your friend. Without model-derived constraints, the risk of really bad things happening is larger, not smaller. – gavin]
This (admittedly record holding) turbine:
http://en.wikipedia.org/wiki/Enercon_E-126
a 7MW rotor that, from the picture, seems to be taking up 10mx10m square.
That would be 70kW/sq m.
@KenW #260. Thanks for the link to the lectures.
Just in case a non-scientist thinks they might be too difficult, IMO they are more mid high school level (at least here in Australia). They are for non-science undergrads who I suspect did no science subjects in high school. (Also a revision for people like me who haven’t looked at a physics text for a few decades.)
I’ll be giving the reference to others who express an interest in an introduction to the basic science.
ERRORS
“With a system as complex as the climate, it is very unlikely this will be accurate on the first many model revisions.”
This isn’t the first revision of models.
See https://www.realclimate.org/index.php/archives/2010/01/the-carbon-dioxide-theory-of-gilbert-plass/
FUNDAMENTAL PROBLEM
“The fundamental problem that is faced is one of validation, nobody knows whether it is accurate or not for 25+ years”
Except they do:
https://www.realclimate.org/index.php/archives/2009/12/updates-to-model-data-comparisons/
NON-EXAMPLES
“Examples of this type of algorithm development are hurricane tracking (been living in FL for 25 years).”
Which isn’t a climate feature.
I guess since this modelling of hurricanes is so bad you didn’t manage to get any of your modelling work done “with signal processing, neural networks, and various algorithm development projects in software.”
CURRENT PERFORMANCE
“It is just not credible to me that these models are reliably accurate without ever been validated.”
Currently, Tom hasn’t looked.
INSTABILITY
“The positive forcings placed in these models which allow them to accelerate temperature increases are inherently unstable.”
Tom still insists that a positive feedback always goes to infinity and that there’s no such thing as a converging series.
Seriously unstable.
BOTTOM LINE
“I’ll believe it when I see it”
And to ensure he avoids all peril, will have his eyes closed.
Tom also makes this strange constraint: “(and no, training and validating on past data is not sufficient).”
So when micea puts his model plane in a wind tunnel to see if it breaks, he can’t use that information to make the models better?
He can’t even use the successes to see if his models are right? If so, why bother wasting time on that?
It’s expensive, Tom, so why do the aeronautical industry (and car industry and pretty much EVERY engineering industry today) use computer modelling to help their processes when they can’t use validation to see if the models they use are right and can’t weed out model results that fail a test in real life to improve the modelling?
Tom S. says, “Science is great at explaining why things happened, but not so great at predicting the future.”
OK, Tom, stop right there, because you are 100%, flat-out wrong. The whole point of science is to develop models with predictive power. Otherwise, why not just say GODDIDIT–‘splains everything.
Another howler: “It is just not credible to me that these models are reliably accurate without ever been validated.”
Tom, really, you can look this stuff up, as Hank would say!
http://bartonpaullevenson.com/ModelsReliable.html
Then: “The positive forcings placed in these models which allow them to accelerate temperature increases are inherently unstable.”
Bullshit. I would think you’d want to document this. In any case, do we need 5000 years?
Tom again, ” I’d like to hear directly from the guys who wrote the algorithms and coded the models on how they believe they overcame the validation problem (and no, training and validating on past data is not sufficient).”
Tom, given the level of ignorance and arrogance you display in this post, why should anyone talk to you.
Google “Dunning-Kruger effect” for an education.
#329
Gavin, thanks for the link, I haven’t seen this before. I probably am avoiding it because I like living in my own denial bubble…ha ha. I read it and I’ll read the comments on the FAQ post later and see what else I can.
A butterfly flaps it wings in Hong Kong and the weather changes in New York. Quite the dopey oversimplification but somewhat relevant.
I can’t get past validation. Just like you can’t judge climate change by short term weather patterns, you can’t judge climate models in small time scales. Right now every model is no better than a straight line (linear interpolation) over the past 50 to 100 years. It would be encouraging if the current models followed the flattening of the past 10 years.
And the actual measurements of the physical processes you want to model on long time scales (500 years?) is just not available. So you have to go synthetic (physics). Now here you have super complicated models with lots of knobs and levers (weightings etc.). And you tweak these until they match past data somewhat reliably and then turn them loose.
With the limited data you have, you do the best you can do. I’m just not confident the data we have is sufficient for accurate modeling at this time. It’s probably the weakest link in AGW story.
Different models with matching results is not too useful to me. The funniest thing I ever read in a climate post (and these threads could use a little humor) was “I measured the temperature at 8am and again at 4pm and by my calculations we will all be dead in two weeks”. If models only had 8am to 4pm data available, they would all match, but be quite wrong. We may be missing critical components.
[Response: But there is longer term validation data available. The Last Glacial Maximum, the mid-Holocene, the PETM, the 8.2 ky event, the responses to volcanoes (not just Pinatubo), the response to solar, orbital forcing, the Pliocene etc. etc. Now none of these are perfect, but the models provide quantitatively reasonable simulations of all of them – and they are all ‘out-of-sample’ tests. Models may indeed not be complete (and fixing this is what we spend most of our time on), but nothing we’ve seen indicates that there is some huge missing factor that is going to change everything. – gavin]
He did say first *many*, not first alone.
Did you post as “Mark” in the past?
Didactylos,
I was simply countering the claim that land prices made onshore wind too expensive in the UK, Denmark and Netherlands being obvious counterexamples. Interestingly, the UK government has just committed to a large-scale expansion of offshore wind – and a little longer ago, to one of nuclear.
329 wrote: “With a system as complex as the climate, it is very unlikely this will be accurate on the first many model revisions.”
You’re saying that Fourier’s efforts at climate modeling weren’t very accurate? I’m sure you’re right although it hardly seems relevant now.
Although the nuclear plans aren’t offshore…
;-)
We may be missing critical components. – Tom S.
…and you’ll still be able to say that however accurate the models become. It is, literally, impossible to satisfy your demands for validation, which as has been said, would demand multiple Earths to experiment on. This is, of course, precisely why you formulate them as you do.
@247 @252 @267 — I am not a denialist (or Tom S), but just because some people deny via models qua models does not mean any discussion of the models fits into this category. Controlled experiments do make an enormous difference in verification. The spectacular crashes of rockets and planes in their early history are great examples of how it was not “adequate to the task of engineering”. Yes they give guidance, but it is in a decidedly distinct epistemological category.
One can turn these things around. Defending conclusions via excessive confidence in the models (as opposed to uncertainty is not your friend arguments) rapidly leads to geoengineering plans. Such plans are risky precisely because we don’t want to be playing Wright Brothers or von Braum style “try and crash” with the planet. Those risks are real in part *because* the models (and in some ways the system being modeled) are in a different style of validation realm.
I’m only advocating a bit more caution in one’s analogies. A tack that all modeling qua modeling is the same is about as naive as any tack a denialist takes that attacks models qua models.
INSTABILITY
The positive forcings placed in these models which allow them to accelerate temperature increases are inherently unstable. They are prone to run aways, high or low, when shown at much larger 5000+ year time scales.
I think there were a very small number of models from the climateprediction.net experiment that were unstable, although that was over a much shorter timescale of ~20 years.
I think only a small number of the flagship models have been run for anything near ~5000 years, due to computational cost, and I think they have all been stable when this has been done.
My understanding was, but I am willing to be corrected, that the models don’t quite manage the full decrease in temperature for Last Glacial Maximum or start of ice-age simulations. This could indicate that the models were *too stable*; that the amplifying feedbacks were not strong enough.
Tom S., regarding instability, see the new Skeptical Science post The Chaos of Confusing the Concepts.
CFU
Wow… you do like to flog a point hard!
One more point;
# 330
The base may only take up, say 10m x 10m but the rotor has a diameter of 126m. The general rule is that in order to be efficient, and to avoid eddy currents from surrounding windmills, they have to be placed
“…between three to seven rotor diameters from any other turbine in order not to effect the operation of another too much”
http://www.drysdalewindfarm.com/faq2.html#anchor10
So let us very charitably say “between 3 and 7” means 3. These turbines need to be spaced roughly 3 x 126m = 378m apart. At its most compact, a grid 25 turbines (5 x 5) spaced appropriately would take up (4 x 378m) squared = 2,286,144 sq m and produce 25 x 7 Mw = 175 Mw.
175 Mw / 2,286,144 sq m = 0.077 Kw (77 watts) per sq m energy density. Or to put it another way each Gw of energy will need around 13 million square metres or 1,300 hectares or 3,200 acres.
Our largest coal fired power station is Drax in Yorkshire which generates 4,000 Mw. To replace that with 7 Mw wind turbines would take an area of around 52 million square metres, or 12,800 acres.
On a general point, a very good source of information is the British Wind Energy Assoc. web site, particularly their FAQ. They have mapped the UK’s wind resources:
http://www.bwea.com/images/misc/noabl_c.gif
I read the presentation by Kargel, et al. in the “Update” above. So it won’t be as bad as soon for Northern India and the Himalaya watershed as I had thought (my thinking was within 100 years it could be very bad, but it will be just a bit worse, I guess, and only potentially much worse well beyond 100 years from now — which still is a strong call for us to mitigate AGW).
One Q I had re #10 on pg. 42 was about the increased precip due to warming sea surface balancing or exceeding the glacier retreat. Would that precip be coming down as rain in winter (in which case it would contribute to greater flooding and not help with irrigation in summer), or would it be coming down as snow, which stays put in winter, and melts in summer, helping with their irrigation-dependent agriculture.
What really shocked me back to a harsh reality, however, was #10 also mentioned the possible heat pump effect could shift precip away from the Southern India northward.
It should be noted that a lot of people also live in Southern India, and they are already experiencing increasing droughts in summer and extreme floods in fall. Farmers are committing suicide due to crop failure.
My nieces and nephews, grandnieces and grandnephews (in Tamil, grandchildren, and since we don’t have children, they ARE my grandchildren) will be suffering because of these problems.
These are the storms of MY grandchildren, and it makes me mad and sad. So please please please reduce your GHGs as much as possible. Please do what you can, at least what saves you money and is no skin off your nose. Please please please.
“The base may only take up, say 10m x 10m but the rotor has a diameter of 126m.”
Please tell me how many crops crow 100ft high.
“but just because some people deny via models qua models does not mean any discussion of the models fits into this category”
But it doesn’t make it OK to make stuff up about how models can’t do anything based on you not liking the result. If you ARE going to try that, at least be an expert in the field.
“Defending conclusions via excessive confidence in the models”
Please show where the scientists who use models do this.
Go ahead.
I’ll wait.
“So let us very charitably say “between 3 and 7″ means 3. These turbines need to be spaced roughly 3 x 126m = 378m apart.”
Let us charitably say that you’ve forgotten that this land isn’t being used for generating wind power, so you can, say, grow crops or feed cattle on it.
Or, indeed, generate solar power.
286 Rod B,
I tend to believe them about that contract price but is there a tax credit for the up front costs lurking under the story? But wait!!Let me check what actually happens in California.
For Hank, Reference for the following is Bullis utility bills for Dec. Apr.
At $.125 to $.132 in California there is something missing from the story. For a $.12 per kWhr billed to “baseline” customers the PGE generation cost, they say, is about. $.05 and that breakdown has to include an allocation for everyone’s profit along the line. About 5% of the $.12 is for “Public Purpose Programs.” So that helps cover some of the shortfall; maybe all since there is not much actual production from wind or solar. Of course, if we had been home all month we could have had the privelege of paying $.26 per kWhr like most people with full families still at home have to pay. I then went on to check what PGE says is generation cost.
But there is always a special surprise in California. When electricity comes to me for $12 it costs PGE $.05 to generate it and when it comes to me at $.26 it costs PGE about $.08 Apparently they send a different kind of electrons that cost more to generate to rich folk. Now we have discovered that some electrons are more equal than others and we can attach labels to them. In California we continue to lead the world in scientific discovery.
So back to the point, whether generation costs charged to customers is $.05 or $.08 per kWhr, that is a lot less than the rate paid to wind and solar producers, even at the lowest of these rates. At $.25 per kWhr the ‘small producers’ are getting hugely overpaid. That has to count as free money from the public, even in California. It is a good thing there is not much of it.
Did I mention this already?
http://blogs.nature.com/climatefeedback/2010/01/ams2010_data_gaps_and_errors_m.html
–Olive Heffernan
“New analyses provide preliminary evidence that temperature data from the UK Met office may under-estimate recent warming. That’s the conclusion of a talk given here today by Chris Folland of the Met Office Hadley Centre. Folland says that there is a very good chance that there has been more warming over land and over the ocean in the past decade than suggested by conventional data sets, but he says that the issues with land and ocean data are entirely unrelated.
For land, the problem of underestimating warming stems from data gaps in the average monthly temperature data set of the Met Office Hadley Centre, known as HadCruT3. Temperatures over the past decade were recently re-analyzed using a european climate model by Adrian Simmons of the European Centre for Medium-Range Weather Forecasts in Reading, UK and colleagues, and are soon to be published in the Journal of Geophysical Research ….”