Tony Heller has replied to my previous post. I don’t think he likes me very much.
Apparently he doesn’t believe that increasing temperature can increase the amount of water vapor in the air, or that can affect the amount of snowfall. Perhaps he should learn some science.
He also seems to think that “winters are getting colder in the mid-latitudes.” Perhaps he should look at some temperature data for winters in the mid-latitudes. But wait … Tony believes that the temperature data sets are fraudulent. He seems to think that a lot of climate data is fraudulent. In fact, the header of his blog contains the word “fraud” or “fraudulent” ten times. He only mentions “racketeering,” “garbage,” “collusion,” “corruption,” and “scam” once each. I think he has some issues.
Interesting is what he has to say about year-round snow cover:
Then Tamino tries to claim that for the whole year snow cover is decreasing. This also is complete nonsense. Snow cover has increased substantially since late 1980’s and early 1990’s — and North American snow cover is about the same as it was 50 years ago.
Saying so don’t make it so.
Let’s estimate the trend in yearly-average snow cover anomaly, to get some real evidence whether it’s going up or down. If we start at the beginning of the data, well … sorry, Tony, it’s going down. The decline even shows “statistical significance.”
But Tony wants to start later, in the “late 1980’s and early 1990’s” somewhere. He picks that because, to him, it looks like what he wants. That’s a textbook example of cherry-picking.
We’ll let the baby have his cherry. Here’s the estimated trend rate, with error bars, for every start year from 1966 (when the data begin) through 2000:
There are a few years in the late 1980s when the estimate rises above zero, but you might notice that none of them achieves statistical significance. The fascinating thing is that even if one of them did, that’s still not sufficient evidence because you have to take into account the multiple testing problem. I’ve mentioned this before. Alas, that’s probably too much for a simpleton to deal with.
But, as I said, none of them achieves “statistical significance” anyway. The only reliable conclusion from these data is the overall decline. Which means: maybe it’s time for Tony Heller to call the data “fraudulent.”
What’s most interesting, absolutely fascinating, truly spellbinding, is what Tony Heller has to say about how snow cover has changed during the spring and summer months. What pearls of wisdom flow from his pen? What insightful conclusions follow? What does he say about that, you wonder?
… Nothing.
For those interested in some actual science, here’s how monthly northern hemisphere snow cover has changed over time, for all 12 months of the year:
And, for those interested in rates of change, here they are for all 12 months of the year.
Draw your own conclusions. I’m sure Tony Heller will.
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Open Mind 
Just for completeness, what size are the error bars in the figures. Are these 1 s.d.?
[Response: They’re 2-std.dev. That’s what I usually do.]
Don’t forget the footer: “The Deplorable Climate Science Blog”
The adjective certainly describes the coterie of commenters (Izen aside!) on that thread. Drs Dunning and Kruger seems to be having a profound effect over there.
I’m almost waiting for one of the Denialati there to ‘prove’ that Inuit couldn’t possibly shelter in igloos, because it would be too cold.
Savagely attacked by Tony ‘Steve Goddard’ Heller? Be careful; such matters can escalate. Next thing you know a mouse will be snarling at you.
Tony Heller is Steve Goddard? I am confused. I have heard of the latter, but not this Heller fellow. There are so few above-the-line deniers left that I thought I had at least heard of all them by now. Ah. I see. Tony Heller is indeed the person previously known as Steve Goddard for the purposes of denial. Still claiming that all the data is fraudulent. It’s surreal really.
Interesting that the significant increases in the NH are from November to January when increased albedo matters the least, and the significant decreases are in months from April to August, when decreased albedo matters the most. This looks to me like another positive feedback on temperature.
Indeed.
I’ve always wondered just how much albedo in the arctic matters. The sun is pretty low in the sky, so not much energy is delivered. I’m reasonably sure that the main way of melting the arctic is via the tropical heat that ends up being carried there by air or water.
Does anyone have an order of magnitude calculation of just how significant that change in albedo really is in the big scheme of things?
[Response: There’s this and this.]
Thanks!
Tony doesn’t get out much. Anyone who’s spent time outdoors knows that “winters” start later and end earlier. And he certainly has not spent time in the Canadian Rockies:
Click to access SOTM.pdf
The question that recurs in my mind is this: “Is this really the best these guys can come up with? Really?” I mean, they spend half their time arguing with established facts and the other half looking for some fluctuation large enough that they can lie with it without being laughed at. Tony Heller would have to up his game considerably to make a bid for idiot.
Somewhere, our education failed the Tony’s (Willard Tony and Steve Goddard Tony) and left them with the misapprehension that they have the analytical chops to make sense of data. Once again: Stupidity sent to college (well, not in Willard Tony’s case)…
One does wonder at the patently absurd levels of ignorance and misrepresentation that afflict the small group of people who promulgate this anti-scientific nonsense.
Sadly, this small group of science-denying propagandists is all that it took to reinforce the bias of Rupert Murdoch’s global media empire, and the prejudices of the next PotUS. It didn’t matter that they didn’t convince a majority of people, only that they convince the swinging voters in the middle and the agents that facilitated the levering into power of a denialist.
@Syd – You have that right!
DaveW
Is there anything about the reliability of these data, particularly the first two years? They seem awfully divergent in many months (March thru Sept). I’m not suggesting a cherry pick, but rather I think there is probably a statistically legitimate way to evaluate the validity of data points and possibly ignore those two years (if there isn’t already a meta-data reason to ignore them, such as being the first and most methodologically naive estimates in the series).
As can be seen in the second figure with trends and different start dates, excluding the first two (or even five) years does not change much.
Thanks. I see what you mean in the second figure: the trend in the average won’t be affected much. And now looking at the last figure, the uncertainty for some of the months I noted (July-Sept) is actually lower than most (no significance test on that…), so probably no real impact there either. But I was more interested in the statistical treatment of such data in general. Sometimes I learn stuff here that can be applied elsewhere, to other topics. There may be many time series in which the first (or last) data collected are questionable, but detailed documentation is lacking.
Throwing out/ignoring data is fraught with problems unless it can be pinned on instrumental problems. If something actually occurs, well, it actually did. It cannot be ignored. Should we ignore the temp dips after Krakatoa or Pinatubo? No. Better to try to incorporate those years into what’s happening ) as Tamino and other have done in peer reviewed work.
Even the startling 5.7 sd drop in Antarctic ice shouldn’t lead one to ignore it. For now the overall trend is still up. All that can and should be said statistically is that something extreme seems to be happening well in excess of previously observed variation and try to figure out what that extreme thing is.
Heller is simple, very simple to understand. I a previous post of his, He claimed scientists lied when they say Greenlands losing mass. To show this he cites half the data and even gives a source. His own source states “Satellite observations over the last decade show that the ice sheet is not in balance. The calving loss is greater than the gain from surface mass balance, and Greenland is losing mass at about 200 Gt/yr.” and yet he only uses half the numbers from his source and accuses scientist of lying.
AKA his source points out the number he used is not the whole picture but apparently be disbelieves in the existence of calving glaciers and so doesn’t count those. Not only is his position simply lies he assumes we are simpletons too.
I don’t know if it is still true, but in previous iterations, Heller/Goddard’s blogging was heavily salted–I first started to type “dominated”–with political cheap shots, such as unflattering photos of President Obama.
IMHO, it’s ideology all the way down–or better stated perhaps, political tribalism. Either way, it’s nothing to do with science, despite his protestations.
Yes that Greenland lie is one of Heller’s favorites. In post after post, he references the Danish Meteorological Institute’s Greenland web page and ignores its main conclusion. Judging by the comments, his rubes eat it up.
There’s subtle tribalism as well, possibly no more malicious than self-aggrandizement. There is a case I wrote about a bit back reacting to papers like this, which are embraced by people like Lindzen, essentially arguing we have no need for a greenhouse gas explanation.
What’s relevant here is that sometimes authors of these papers, like Tsonis, forgot what was said in other papers they appeared as co-authors. Perhaps Tsonis and Swanson are sincere and it’s people like Lindzen or Michaels, Balling, and Davis who are taking them out of context.
In any case, it seems denialists consider scientific papers to be like the Bible: They can quote bits and sections as they like, ignoring the rest.
That’s alright. We don’t like him much either.
Unrelated, but I thought I’d draw your attention to some very nice graphs at Bloomberg’s:
https://www.bloomberg.com/graphics/2015-whats-warming-the-world/
Interesting for Heller would be to read a recent study by the University of Neuchâtel, the WSL Institute for Snow and Avalanche Research SLF and the Swiss Federal Research Institute WSL. They show a.o. that (…) at all stations the average date for the onset of the snow season is now 12 days later, and the season ends around 25 days earlier than in 1970…..
So the Swiss are losing 37 days of their snow season since 1970. Any reason to be fraudulent about that??
Particularly since advertising the reduction in snow would likely cost the Swiss ski tourism industry (which is fairly large) significant sums of money. Although most skiers are aware the the alpine ski season generally is reducing in length, even the extensive snow production infrastructure.
Have you checked the CMIP5 expected monthly snow cover changes? I haven’t found papers looking at all months individually.
Increased snowfall doesn’t necessarily mean greater snow extent, it might mean thicker snow in fewer places. Iirc Kosaka & Xie showed some wintertime cooling over parts of NH land, which might be related.
MarkR,
Depends on Circulation-Pattern, since arctic ice loos prefer or likely force a negative Autum AO-Index (while Winter AO is not so clear connected). This and more water vapour would mean increased snow extent also snow mass
Implicit in the rejection of conclusions drawn from “fraudulent” data, is the existence of credible data that support a contradictory conclusion. When a denier alleges that climate data is fraudulent, I’ll sometimes ask them what data they do consider reliable, and why. I don’t recall ever getting a satisfactory answer. One is led to conclude, as Doc Snow has, that for AGW-deniers
You must not be paying attention. His whole point is that the Rod data shows no out of the ordinary warming. It is the fraudulent adjustments that create the illusion of greater warming.
Well, Wjax, I confess I pay as little attention to “Steven Goddard” as possible, because life’s too short to waste time on AGW-deniers who are obviously motivated by political tribalism, not science.
Wjax, he simply shows the data before correction and the data after correction in the same graph and proclaims the corrected data is fraudulent. But he doesn’t even show any evidence that the new dataset is incorrect, let alone evidence of fraud. So he doesn’t actually have a point. He simply proclaims that the change is fraudulent. His proclamation is based on nothing but the fact that the new dataset is different from the old one.
Rejection of climate science by garden variety ideological obsessives is driven by their deep hatred of the green movement. No matter how much the evidence mounts they are compelled to continue with the dishonest charade for which they seem to expect a special dispensation.
Sorry, meant to say “raw” data
You should be sorry for posting garbage here in the first place.
Wjax–fraudulent adjustments? Seriously?
All this bruha about something Tony Heller, aka Steven Goddard wrote?
The wanker who also wrote that it snows CO2 at the top of the Antarctic ice dome?
The wanker who also wrote that the reason Lake Super is cold is that it “remembers” the last ice age?
Seriously?
And Wajax, you have much more to be sorry for than mistyping the word raw.
Yep, *that* guy…
Also the guy who so spectacularly miscalled the end of the 2012 melt season–and as resolutely refused to own the gaffe. Only “pop-sci”–is he still operating?–is so ‘immune’ to error.
Who’s the patron saint of patience-with-wackos?
A relative of Cassandra’s, I think.
This will bring them out in force:
http://iopscience.iop.org/article/10.1088/1748-9326/11/8/084011
Quantifying expert consensus against the existence of a secret, large-scale atmospheric spraying program
Christine Shearer1,2, Mick West3, Ken Caldeira4 and Steven J Davis1,2
Published 10 August 2016 • © 2016 IOP Publishing Ltd
Environmental Research Letters, Volume 11, Number 8
errata at
http://iopscience.iop.org/article/10.1088/1748-9326/11/12/129501
I just saw this being posted. I suspect it has been set up to be insoluble with the available information, but don’t have the stats background to debunk it.
http://www.informath.org/Contest1000.htm
[Response: Yes, it was set up to be insoluble, using a ridiculous model to generate the series — one which does not emulate temperature data.]