10/54,000 = .0185 % That’s an impressively small sample size. Apparently Pachauri’s zeal to get back the Himalayagate claim of melting by 2035 outweighs any rational attempts at science. In any other discipline, a sample size this small would be laughed off as ridiculous, but this is climate science, where ridiculous has become the norm, especially when trotted out for the Durban Climate Conference.
Excerpts from the UK telegraph:
Himalayan glaciers are melting, says IPCC research
The Himalayan glaciers are melting after all, according to new research released by the Intergovernmental Panel on Climate Change (IPCC).
The research was released in an effort to draw a line under the embarrassing mistakes made about the effects of global warming on the region in the past.
The IPCC were forced to apologise for claiming that the Himalayan glaciers would melt by 2035.
The 2009 scandal, known as ‘Himalayagate’ led to criticism of the IPCC, a group of scientists convened by the United Nations to warn governments around the world about the effects of climate change.
In an effort to move on from the embarrassing episode, Dr Rajendra Pachauri, Chairman of the IPCC, has now announced that the latest statistics show the glaciers are melting, according to the limited amount of science available.
The reports, presented at the UN climate change talks in Durban were brought together by the the Kathmandu-based International Centre for Integrated Mountain Development (ICIMOD).
…
One three year study, funded by Sweden, found that of 10 glaciers measured in the region all are shrinking, with a marked acceleration in loss of ice between 2002 and 2005.
==============================================================
“…funded by Sweden” Does anyone care to place any bets on WWF and/or Greenpeace involvement in this? I’m sure Donna Leframboise will take a good look into this one.
Meanwhile, here’s all the reason you need not to trust anything the IPCC says. This comment left on our open thread today from Roger Knights is about as growing into Himalayagate 2 as you can get:
Three Strikes Against the IPCC’s Asia Group (By Roger Knights)
(Summary: This post points out the cherry picking of quotations by the IPCC’s Asia group to spice up its widely publicized claim that 3/4 of a billion Asians were at risk of water shortages from glacier-melt.)
Here’s a bone for the gang to gnaw on and flesh out (to mangle a metaphor). I haven’t fully researched the matter, but what I’ve noticed is intriguing.
During a dispute with one of the one-star Amazon-reviewers (T. Bruner) of Donna Laframboise’s Delinquent Teenager book about the IPCC, I wrote:
“She [DL] wrote, at Location 763 in Chapter 14: ‘When the IPCC declared that three-quarters of a billion people in India and China depend on glaciers for their water supply, is it not strange that its only source for this claim was the Stern review?’ The link she supplied there takes one to that section of the IPCC report, 10.4.2, where one can see the single citation for oneself, as I have done.”
(My exchange with T. Bruner starts on the 5th comments page of his review, linked to below, but the most relevant material is on the 6th page. http://www.amazon.com/review/R3D6YKUGYE4WA0/ref=cm_cd_pg_pg5?ie=UTF8&cdForum=Fx2983WIRKIRW6A&cdPage=5&asin=B005UEVB8Q&store=digital-text&cdThread=TxO5HUAZSS2GUT#wasThisHelpful )
Bruner pointed out that the Stern Review in turn had cited, as its authority for that statement, Barnett et al., which, unlike Stern, was a peer-reviewed and before-the-deadline publication. He added that the Fresh Water Group had cited Barnett alone, in Section 3.4.3 (of AR4).
This made me wonder: Why had the Asia group taken the risk of violating the IPCC’s rules by citing Stern alone? Wouldn’t citing Barnett in addition, or instead, have been prudent?
It’s unlikely that the group hadn’t been aware of the Barnett paper, given that it was cited by Stern, and given its relevance, recency, and prominent & prestigious source, which could be found in Stern’s bibliography:
Barnett, T.P., J.C, Adam, and D.P. Lettenmaier (2005): ‘Potential impacts of a warming climate on water availability in snow-dominated regions’, Nature 438: 303-309
So this relevant, recent, and prestigiously published primary source, Nature, which all contributors had access to in their libraries, was omitted in favor of citing a gray, secondary, after-the-deadline (2007, hence unpublished per the IPCC’s rules) source. (It’s not cited anywhere in the Asia Group’s chapter, per its References section.)
Why? Let’s get started by looking at what the two sources and the Asia Group said. I’ve emphasized the most pertinent passages. (h/t to T. Bruner for the quotes.):
1. Barnett et al., as summarized by the Fresh Water Group, in AR4 WGII Section 3.4.3:
“Hence, water supply in areas fed by glacial melt water from the Hindu Kush and Himalayas, on which hundreds of millions of people in China and India depend, will be negatively affected (Barnett et al., 2005).”
Go to 5th paragraph, last sentence, here:
http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch3s3-4-3.html
2. Stern Review, 2007, Section 3.2, page 63:
“Climate change will have serious consequences for people who depend heavily on glacier meltwater to maintain supplies during the dry season, including large parts of the Indian sub-continent, over quarter of a billion people in China, and tens of millions in the Andes. (Barnett et al., 2005)”
Go to p. 8 at this link: http://webarchive.nationalarchives.gov.uk/+/http://www.hm-treasury.gov.uk/d/Chapter_3_How_climate_change_will_affect_people_around_the_world_.pdf
4. Asia Group, in AR4 WGII Section 10.4.2.1:
“Climate change-related melting of glaciers could seriously affect half a billion people in the Himalaya-Hindu-Kush region and a quarter of a billion people in China who depend [unqualified] on glacial melt for their water supplies (Stern, 2007).”
Go to the second paragraph, second sentence, here: http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch10s10-4-2.html
Strike one: If the Asia group had cited Barnett at all it would have exposed its claims about three-quarters of a billion and “seriously affected” as being hyperbole. (Barnett et al. had used the less-exaggerated, less-alarmist words, “hundreds of millions” and “negatively affected.”) It’s not a big leap to infer that that was the motive for its omission. What other motive could there have been?
(“Hundreds of millions” suggests the lower end of the one-hundred-million-to-one-billion range. If Barnett et al. had had three-quarters of a billion in mind when they wrote “hundreds of millions,” they’d likely have indicated that they were thinking of the upper part of the range by saying something like “over a half-billion” or “many hundreds of millions.”)
Strike two: The Asia Group lied by omission by omitting Stern’s key qualification, “during the dry season.” Including it would have muted the alarmist impact of their sentence. It’s not a big leap to infer that that was the motive for its omission. What other motive could there have been?
Strike three: The Asia Group’s gray-lit-backed claim of a 2035 melt-by date now looks likely to be a similarly culpable instance of cherry-picking in the service of alarmist hyperbole, rather than clueless unfamiliarity with the dynamics of glaciers. They were likely knaves, not fools, in other words.
One reason it’s “likely” is the context provided by the two “strikes” above. Another reason is the context provided by their refusal to correct the error in their 2035 melt-by date when reviewers pointed it out to them, and their turning a deaf ear to Dr. Georg Kaser’s subsequent attempts to have it corrected.
(I’m skeptical of the IPCC’s excuse that Kaser sent his first complaint to the wrong department—wouldn’t they have forwarded it?—and that his second letter wasn’t received—a “likely story.” It seems more likely to me that the group couldn’t possibly admit to ignoring his letters—so it didn’t.)
Strike four: The three strikes above suggest that the IPCC has been infected by gang-of-green alarmism. The IPCC’s apologists have spun a deceptive damage-control message about the 2035 error by attributing it to ignorance, not malice—to cluelessness, not culpability. In the context of the deceptive pattern described above, that’s hard to believe.
Obviously, it would be awkward for the IPCC if the second interpretation gained traction, because that would raise the questions, “Where did the gangrene start?”, “How far has it spread?”, “Is amputation needed?”, and “Or maybe a mercy killing?”.
Paging Dr. Kevorkian!
========
For a brief history of Himalaya-gate, see my comment here: http://wattsupwiththat.com/2011/06/17/the-wit-and-wisdom-of-real-climate-scientist-dr-ray-pierrehumbert/#comment-683880
=============================================================
It gets even better, commenter DirkH adds in the same thread:
The funniest part is that the IPCC report contains a table of glaciers and the speed with which they retreat or grow. ON THE SAME PAGE AS THE 2035 DATE!
http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch10s10-6-2.html
The only part they left out is the length of the glaciers; in the case of the Gangotri, for instance, 30km. So obviously nobody of them ever did this mental exercise called “computing” where you divide a length by a yearly distance to get an estimate of the number of years that have to pass until the thing is gone. This is, as the media repeatedly told us, the Gold Standard of climate science, and serves as the blueprint for all future international scientific collaborations under the UN.
Here’s the IPCC errata and table 10.9:
Glaciers in the Himalaya are receding faster than in any other part of the world (see Table 10.9) and, if the present rate continues, the likelihood of them disappearing by the year 2035 and perhaps sooner is very high if the Earth keeps warming at the current rate. Its total area will likely shrink from the present 500,000 to 100,000 km2 by the year 2035 (WWF, 2005).
So let’s do the math for Gangotri glacier, which according to Wikipedia: The glacier is about 30 kilometres long (19 miles) and 2 to 4 km (1 to 2 mi) wide.
30 kilometers (30,000 meters) divided by 28 meters/year = 1071.4 years for Gangotri glacier to disappear at the current retreat rate.
That’s a bit further out than 2035.
UPDATE: I’ve updated IPCC table 10.9 and it is shown below with two column additions. I was unable to find a reference for length of the the Ponting Glacier but if someone can locate it I’ll update the table to include it.
Note that the Pindari Glacier does have a chance of disappearing by 2035 if the rate of retreat keeps up. Perhaps that one was the source of confirmation bias. Looking at this photo from Wikipedia though…
…it looks rather “dirty” with a lot of albedo reducing components in it. That might explain why it is melting at a much faster rate than all the others.
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When they talk about anyone “depending on” glacier melt, I would just want to know if they are confusing snow melt and glacier melt – and if they have any standardized method of determining the dividing line between the two.
Also, what is meant by “dry season”? Do they mean when there is no rain or snow? Or do they mean after all the snow melt has ended for the year and before the snow begins accumulating again? These are pertinent points.
Snow melt is what drives all spring and early summer runoff, and this does, indeed, provide a source of water for hundreds of millions. But usually the time between the end of snow melt and the beginning of snow accumulation is only a month or two.
One would really want to see where the monsoons fit into all this, too, with maps and data, captured over several decades.
FWIW: Back in about 1950 it was observed that the uniformitarian view of glaciers as having existed for hundreds of thousands or millions of years is contradicted by the rate of receding of the lower ends of the glaciers, measured from the bottom of their valleys. If I recall my reading from back then, no glacier seemed to have a life longer than about 3,500 years or so. Obviously that is not quite the case, but it points up that the entire issue is more complicated than simply measuring the rate of receding.
While science points fingers at others and accusing them of simplistic reasoning, it has been my own observation that scientists themselves almost always break things down into the most simplistic concepts, and they do very badly on complex or compound issues (such as, say, climate), ones that have too much chaos in them. This appears to me in terms of them trying to come up with simple equations that usually have a number of assumptions. While useful as a stop-gap intermediate measure, as they work to find more solid and true answers, I have yet to see a scientist admit that their understanding is only partial and that there is a long time to go before they know in full.
Claims that underlie Glaciergate are the most simplistic of ideas I’ve seen put out there. I am pretty certain it has to do with turning glaciers into Bambi’s mother, a symbol of the nastiness of modern society as it blasts away at anything and everything in nature. Who cares if it is true, as long as it gets a big tear running down the face of Bambi lovers everywhere?
It might be useful to point out the following about glaciers:
“Ablation zone refers to the low altitude area of a glacier or ice sheet where there is a net loss in ice mass . . .”
In comparison to . . .
“. . . the high altitude accumulation zone.”
Quoted parts are from
http://en.wikipedia.org/wiki/Ablation_zone
Then consider:
low altitude — warmer
high altitude — colder
It should be no surprise, all else being similar, that ablation is rapid following a terminal position and slows at some time after warming starts (think after the LIA) as the topography steepens and the remaining ice is at a higher elevation. Accumulation or lack thereof is important (note MT. Kilimanjaro). Aspect (which way does the ice face) and atmospheric-sourced surface debris (may be natural or anthro) can change the albedo. If a lack of high altitude snow can be attributed to AGW — (How? Maybe wind pattern changes.) — then that is something else to consider.
Generally, then: higher ice ought to not disappear as fast as the lower ice.
——-
My comment at 7:26 pm now seems out of place as the missing not has been added.
“”””” Timo Soren says:
December 4, 2011 at 8:34 pm
Please be careful when leading with an implication of a poor sample when citing a .0185% number. It is not any standard requirement to hit any specific % of the sample. It is the sample type: SRS, convenience, stratified etc.. and the sample size that make an inpact. “””””
Lemme see if I have this correct: “”””” It is not any standard requirement to hit any specific % of the sample. “””””
So we are sampling the sample; is that correct ?
I’ll tell you what makes by far the largest “impact”. That would be complying with the most fundamental theorem of band limited sampled data systems; that being the Nyquist criterion, which calls for a minimum sampling frequency that is twice the highest frequency of the band limited signal being sampled. Well that is for uniform sampling, which is not absolutely required. But with non uniform sampling, the number of samples has to be increased, since the maximum spacing cannot be longer than one half cycle of the highest signal frequency. Now some would argue that it is not required to reconstruct the continuous band limited function from its samples; since only the average (zero frequency value) is being sought.
Well you only have to undersample by a factor of two to corrupt the zero frequency signal with aliassing noise; so even the desired signal average is not recoverable in the event you undersample by a factor of two or more.
Since the daily temperature cycle is NOT a pure sinusoid, then it contains at least a second harmonic component at a frequency of two cycles per day; so with a min/max Temperature reporting regimen, the temp[oral sampling is already in violation of the Nyquist criterion, by a factor of two so the daily average Temperature is already in error.
And for a good laugh you should estimate just how much undersampled the spatial frequency is.
And fo course Briffa thought that a single Yamal tree, was a perfectly scientific sample.
Thanks for making a topic of my mini-exposé, Anthony, by reposting it from the Open Thread. I’m pleased with the little bit of detective work I did. (I wonder how many other thumbs could be found on the IPCC’s scales by persons who really knew the nitty gritty of the “Impact” sections, where I suspect most of the fudging has occurred.) I’m posting here one of the comments on my contribution from the open thread, by Philip Bradley. I think he may be mistaken in his third criticism, but I don’t want to misrepresent what he said by leaving it out.
I posted this a few hours ago in unthreaded, but it goes to the heart of the glacier issue.
1. Barnett et al., as summarized by the Fresh Water Group, in AR4 WGII Section 3.4.3:
“Hence, water supply in areas fed by glacial melt water from the Hindu Kush and Himalayas, on which hundreds of millions of people in China and India depend, will be negatively affected (Barnett et al., 2005).”
Go to 5th paragraph, last sentence, here:
http://www.ipcc.ch/publications_and_data/ar4/wg2/en/ch3s3-4-3.html
2. Stern Review, 2007, Section 3.2, page 63:
“Climate change will have serious consequences for people who depend heavily on glacier meltwater to maintain supplies during the dry season, including large parts of the Indian sub-continent, over quarter of a billion people in China, and tens of millions in the Andes. (Barnett et al., 2005)”
Go to p. 8 at this link:
Stern was being deliberately deceptive. Barnett says the water supply will be negatively affected (by an unquantified amount), not the people.
Barnett is also saying the dependence of hundreds of millions of people in China and India is on the water supply, not the glacial melt.
Stern is being further deceptive by saying ” will have serious consequences for people who depend heavily on glacier meltwater to maintain supplies during the dry season”, because the dry season in the Himalayas is the winter when there is, for practical purposes, no glacial melt. Stern’s statement is literally true, because the number of people who depend heavily on Himalayan glacier meltwater to maintain supplies during the dry season is zero.
If NGO’s are not subject to FOI, they must be the best place to hideone’s money.
Isn’t it in the nature of claciers that they melt? From where has all that water of the Ganges river been coming for the last milion years or so?
Google ‘glaciers growing back’ and see what pops up. The first item at the top is:
Himalayan Glaciers Seem to Be Growing: In the Western Himalayas, a group of some 230 glaciers are bucking the global warming trend.
“Perched on the soaring Karakoram mountains in the Western Himalayas, a group of some 230 glaciers are bucking the global warming trend. They’re growing.”
So Pachauri manage to find ten glaciers that are to his liking, that is, retreating. But another guy found 230 glaciers that are growing. Pack up, Pachauri, please. Repent, your end is nigh.
Timo Soren says:
December 4, 2011 at 8:34 pm
“Please be careful when leading with an implication of a poor sample when citing a .0185% number. It is not any standard requirement to hit any specific % of the sample. It is the sample type: SRS, convenience, stratified etc.. and the sample size that make an inpact.”
Those are valid points for objective scientific research. But this is IPCC work. Amazing what they can do with a tree, ten glaciers, and four drowned polar bears.
Calculation of sample size is a standard tool of statistics, and is as valid for climate science or even politics as anything else. Basically what the authors of the report should do is say to themselves “With a population size of 54 000, what sample size do I need to achieve a confidence level of x with a confidence interval of y” (where x is normally 95% and y is the error).
Which leads to answers of the form “I’m 95% certain that my results, + /- the error, did not arise out of pure chance variation”.
With a very quick search in google (which I’m sure the authors could also have done) I found this sample size calculator
http://www.surveysystem.com/sscalc.htm
which shows that the sample size ought to be like 400 or so to meet the usual 95% criterion. Not 10.
Philip Bradley says:
December 4, 2011 at 11:03 pm
“Stern is being further deceptive by saying ” will have serious consequences for people who depend heavily on glacier meltwater to maintain supplies during the dry season”, because the dry season in the Himalayas is the winter when there is, for practical purposes, no glacial melt. Stern’s statement is literally true, because the number of people who depend heavily on Himalayan glacier meltwater to maintain supplies during the dry season is zero.”
That’s a beauty Philip. Well done. And i would guess that Stern did not even realize how decepetive that was. He’s not that swift. His line just sounds like it is from the eco-crisis template and it is hard to scare people about water in the ‘wet’ season.
Here’ are a few posts I found in my offline collection of “Bests of WUWT” that point the finger at other causes than heat:
Here’s a post I made last year:
From what I recall of prior threads on this matter:
1. The Himalayan glaciers (which are the ones that large numbers of people rely on for meltwater) can’t melt back much further, because most of them are so high that the temperature hardly ever gets above freezing. They aren’t analogous to glaciers elsewhere.
2. Even if they did vanish, river flow would not be much affected, because rivers are fed by an annual snow-melt that is stretched out over most of the year. It is summer snow-melt, not glacier melt, that “2 billion people” (including me) rely on for water, not glacier-melt.
3. Himalayan glaciers (like many other glaciers alarmists cite) have been retreating since long before 1950, which tends to largely exculpate manmade CO2.
4. Soot, aerosols, infra-red solar variation (in the Alps), and precipitation-variation may be responsible for some of the glacial retreat.
This on Chinese glaciers supports my point above.
http://www.hceis.com/chinabasic/Glacier/Glaciers_of_China.htm
runoff from June to August contributes 90% to that of ablation season.
Which is the Monsoon season.
Glaciers do play a role in moderating interannual river flow variability.
The glacier melting runoff plays a role in regulating the interannual stream flow variation. This can be explained that the former, being mainly controlled by temperature, will be lesser than normal during wet years with lower temperature and large amount of solid precipitation stored in mountain glaciers, while for dry and warmer years, vice versa. Therefore, it leads to the fact that rivers with larger portion of glacier melt water supply are characterized by runoff being not so insufficient in dry years and having smaller interannual variability.
But this is not what Stern and The IPCC claim.
Interesting read while I’m sitting here in Sydney Australia after the coldest first week of summer for 44 years!! Bring on global warming.!
MIchael Kelly
‘It is a great and sad irony that most of the big foundations in America were originally funded by large, successful capitalistic ventures but are now run by socialists who do all they can to undermine capitalism’.
Actually the climate scam is about making trillions of pounds through dodgy deals and daft science. Does that not sound more like a classic capitalist scam than socialist control?
When the IPCC declared that three-quarters of a billion people in India and China depend on glaciers for their water supply, is it not strange that its only source for this claim was the Stern review?’
What is strange is that the IPCC would claim that the water supply for a billion people depends on melting glaciers. Guess we better not do anything that might stop them melting, huh?
Good thing it isn’t really melting glaciers that supplies the water to Asia (it is annual precip instead), or GreenPeace would have to demand that everyone drive SUVs.
S@gareth Phillips
re: “capitalist scam” or “socialist control”
I don’t think what is going on is such a binary either/or. There are enormous elements of both. Vast governmental take-overs sought via “carbon taxes” and “cap and trade” etc. are paralleled by enormous “rent-seeking” (as economists term it) of companies and individuals seeking to get in on the gravy train.
There is so much “crony capitalism” and state-driven economic change going on under the rubric of urgent response to devastating CAGW (sic).
With all the corrupt connections (Solyndra etc. is just the snowflake on the iceberg) there is a vast and growing set of financial beneficiaries from the CAGW scam.
If the NGO is operating with government money, you send the FOIA request to the government agency providing the funding. They would, in turn, compel the NGO to provide the information to them and then on to the requester.
asmilwho says:
December 4, 2011 at 11:18 pm
Calculation of sample size is a standard tool of statistics, and is as valid for climate science or even politics as anything else. Basically what the authors of the report should do is say to themselves “With a population size of 54 000, what sample size do I need to achieve a confidence level of x with a confidence interval of y” (where x is normally 95% and y is the error).
Which leads to answers of the form “I’m 95% certain that my results, + /- the error, did not arise out of pure chance variation”.
With a very quick search in google (which I’m sure the authors could also have done) I found this sample size calculator
http://www.surveysystem.com/sscalc.htm
which shows that the sample size ought to be like 400 or so to meet the usual 95% criterion. Not 10.
————————————————————————————
Nope. A sample of 400 glaciers in the Himalayas would not necessarily give anything like that confidence. As I mentioned in my PP, it is not just a numerical function. It depends what you are dealing with. For example, opinion polling can be accurately done on very small population samples. Studies of plankton can be done on even smaller ones. Geographical features in a very large area are much trickier, because there are so many variables. You could not use your suggested approach to extrapolate anything useful about all the rivers on a continent, for example, especially when you are only taking a snapshot of one variable (in this case, glacier length).
It’s total junk science, and measuring another 390 glaciers out of 54,000 wouldn’t improve it to a noticeable degree.
Regarding the question of sample size. Political pollsters falsely claim a level of accuracy. The level of accuracy would be correct if the underlying assumption of the mathematical calculations were met. The assumption is that the sample is truly representative which is difficult to achieve.
A frequently used example is the abject failure of US. Presidential polling which used telephone polling when only the the richer voters had telephones. Obtaining a representative sample is very difficult when there is a diverse population.I suspect the glacier population is very diverse not to speak of the diverse climatic conditions other than just temperature. Lies damn lies and statistics is not just a smart quip.If you change the assumption you change the result.for most of us statitical mathematics is too hard so we are easily fooled.Just don’t waste your time trying to fool Steve Mc Intyre.
Garth from Oz.
The point about sample size is that cofidence intervals depend on the absolute size of the sample, not the percentage sampled. 10 is too small, but not because it’s a small percentage. Note confidence intervals also depend on how the underlying data is distributed _ normality should not be just assumed.
@gareth Phillips:
Actually the classical way of making trillions through dodgy deals are through pseudo-socialist / corporatist measures of state protected monopolies. And those usually failed.
This is the standard format of AGW alarmist mainstream research:
1. Some measured parameter or other has changed in the last 20-30 years indicating warming…
therefore
2. Humans and CO2 are 100% responsible (climate never changes without human cause, no evidence needed for this, its the post-modern null hypothesis) and we are all going to DAAAAIIIIIIYYYYYYEEEE (die)
unless…
3. All world governments hand over 100% political power to a global watermelon dictatorship.
asmilwho says:
December 4, 2011 at 11:18 pm
Which leads to answers of the form “I’m 95% certain that my results, + /- the error, did not arise out of pure chance variation”.
Based on the sample size, you can be 95% confident that 10 +/- 13 out of 95000 glaciers are retreating.
Also note that the Pindari Glacier has the highest retreat rate, but that this was BEFORE 1966, BEFORE the main rise of C02 in the atmosphere.
All the glaciers recorded in more recent shorter periods have MUCH SMALLER retreat rates.
WWF and Greenpeace get the bulk of their monies from frightened little old ladies who believe their hyped up lies. When the coffers run low the lies get bigger.
Glaciers also melt from below by geothermal heat. So annual snows are important for glacier replenishment. Summer surface melt, forming moulins which the BBC latch onto for their Frozen Planet alarmism, does not remove a large proportion of the ice despite IPCC concerns. Geothermal melt is an all year event which keeps rivers running at their dry season levels. High water level flows, and flood levels, come from snow melt.
Anthony
Please note apparent error in table 10.9
John says:
December 4, 2011 at 9:38 pm
Regarding the rate of the Pindari glacier…if you divide 2840 m of retreat by 21 (i.e. 1945 to 1966 and NOT 1845 to 1966!!) you get 135.2 m/yr. Either the date is wrong or the rate is wrong.
Also noted by Willie B at 9.23