Snow White Takes a Walk In The Park

Guest Post by Willis Eschenbach

I wrote a post called I Used To Be Snow White (… but then I drifted) a week or so ago about a study titled “Impact of Declining Arctic Sea Ice on Winter Snowfall” (PDF) that claimed to link low arctic ice levels with high snow levels. To recap, their specific claims were:

Abstract

While the Arctic region has been warming strongly in recent decades, anomalously large snowfall in recent winters has affected large parts of North America, Europe, and East Asia. Here we demonstrate that the decrease in autumn Arctic sea ice area is linked to changes in the winter Northern Hemisphere atmospheric circulation that have some resemblance to the negative phase of the winter Arctic Oscillation. However, the atmospheric circulation change linked to the reduction of sea ice shows much broader meridional meanders in mid-latitudes and clearly different interannual variability than the classical Arctic Oscillation. This circulation change results in more frequent episodes of blocking patterns that lead to increased cold surges over large parts of northern continents. Moreover, the increase in atmospheric water vapor content in the Arctic region during late autumn and winter driven locally by the reduction of sea ice provides enhanced moisture sources, supporting increased heavy snowfall in Europe during early winter, and the northeastern and mid-west United States during winter. We conclude that the recent decline of Arctic sea ice has played a critical role in recent cold and snowy winters.

I showed that if there is such an effect, it is not visible using the snow data for the whole US. I thought this would settle it. But folks said, and fairly, that I wasn’t really dealing with their claim. They said I needed to deal with a) the regional nature of their claim, involving northeastern US and Europe, and b) the temporal nature of the claim, comparing only winter snowfall to autumn sea ice. So I decided to take a look at the winter snow data for the northeastern US compared to autumn sea ice.

Unfortunately, I couldn’t find area-wide data for the northeastern US, but I did find something better. This is one of the longest continuous records of snowfall in the northeastern US—the century and a half long record of the snowfall in Central Park in New York City.

Figure 1. Winter snowfall (December/January/February) for Central Park, New York. There is a slight but not statistically significant decrease in winter snowfall over the last century and a half.

So … how well does this correlate with the arctic ice levels? Well, not to put too fine a point on it … no better than my first look at the question.

Here’s the comparison of the snow and ice. I have standardized both of them so that we can compare them directly.

Figure 2. Central Park winter snow (December/January/February) versus Arctic autumn ice (September/October/November). Data have been standardized to allow a direct comparison

As you can see, there is little correlation, and the numbers bear that out. There is a weak statistical relationship (r^2 = 0.13) which is not significant at the p<0.05 level.

I thought that because there is no trend in the snowfall data, perhaps I might get better significance if I detrended the ice data. This would highlight the year by year variations that are theoretically responsible for the year-by-year variations in snowfall. Figure 3 shows that relationship, with the ice data inverted to better illustrate the relationship.

Figure 3. Central Park winter (DJF) snow totals versus inverted, detrended Arctic autumn (SON) ice levels.

Now, this is a very interesting figure, because it illustrates the way that our eyes find patterns when none are there. At first glance, this looks like it is a pretty good relationship. But in fact, that is an illusion. The mathematical analysis says that the r^2 is even worse, only 0.02, and like the previous graph, it is also not statistically significant, in fact the significance is worse (p ≈ 0.4).

Upon closer examination, we can see why that is so. For example, from about 1990 to 1995 when ice decreased, snow generally increased … but not proportionally. When the ice was extremely low there was a little more snow, and when the ice was only a little low, there was a lot more snow. For there to be a relationship, it needs to be proportional. Also, although in general the snow seems to change with the ice, in fact on a year by year basis, there are huge excursions. Look at 2011, for example, very low ice, but in contradiction to their claim, there’s also very low snow.

So I have found the same thing on a regional level using their autumn ice/winter snow claim, that I found when I looked at the data for the entire US for the full year. If there is any association between winter snowfall in the northeastern US and the autumn ice levels, it is very, very weak. There certainly is no sign of it in the Central Park records.

All the best,

w.

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72 Responses to Snow White Takes a Walk In The Park

  1. John A. Fleming says:

    The Figure 2 shows (superficially) that decreasing sea ice destabilizes winter snow towards more extreme variations. Which is at least logically consistent with the often-heard argument that one effects of a warmer world is a higher pole-equator temperature gradient, which causes more extreme weather events.

    So simple correlations don’t seem to show any relationship. Perhaps the next step is to examine the correlations between the derivatives.

  2. Eve says:

    My first thought when I first read in some paper that there was more snowfall and cold because there was less arctic ice, was that it must have been really warm in the LIA. There was much more Arctic ice then. Or doesn’t it work in reverse?

  3. majormike1 says:

    Hi Willis, from your Gualala neighbor,

    Almost a year ago “Climate Audit” linked to a news report from 1958 explaining how an ice-free Arctic (or at least a low ice-cover Arctic) provided humidity that fueled the snow machine resulting in the build up of the huge ice cap over North America during the past ice age. The cause: intrusion of tepid Atlantic water into the Arctic. The cause of the end of the Ice Age: falling sea level eventually stopped the intrusion of Atlantic waters into the Arctic.

    http://strongasanoxandnearlyassmart.blogspot.com/2011/07/scientists-predict-another-ice-age-is.html

  4. AdolfoGiurfa says:

    The jet stream changes and things change too…

  5. John A. Fleming says, March 12, 2012 at 4:15 pm:
    The Figure 2 shows (superficially) that decreasing sea ice destabilizes winter snow towards more extreme variations. Which is at least logically consistent with the often-heard argument that one effects of a warmer world is a higher pole-equator temperature gradient, which causes more extreme weather events.

    Of course, there’s the oft-heard argument that global warming will cause greater polar region warming, decreasing the pole-equator temperature gradient.

    Is there anything global warming can’t do, simultaneously and contradictorily, when there’s gov’t megabucks at stake?

  6. Zac says:

    On the NSIDC site they say Air temperatures over the Laptev, Kara and Barents seas ranged from 4 to 8 degrees Celsius (7 to 14 degrees Fahrenheit). That should be 39.2 F to 46.4 ºF or converting it the over way -13.8 C to -10 c.

    Confused ? I am.

    http://nsidc.org/arcticseaicenews/

  7. Zac says:

    Can’t be doing with this font Anthony. It is sending me boz eyed.

  8. Willis Eschenbach says:

    John A. Fleming says:
    March 12, 2012 at 4:15 pm

    The Figure 2 shows (superficially) that decreasing sea ice destabilizes winter snow towards more extreme variations. Which is at least logically consistent with the often-heard argument that one effects of a warmer world is a higher pole-equator temperature gradient, which causes more extreme weather events.

    Thanks, John. The “destabilization” is an artifact of the shortness of the Figure 2 record. If you look at Figure 1, you’ll see that the recent record is in no way historically unusual or “destabilized”. Indeed, there is no record anywhere of “more extreme weather events”, that’s an AGW urban legend.

    This to me is one of the huge problems with the original study. They used only a few years of data … not good.

    w.

  9. BarryW says:

    Without looking at the paper, the hypothesis seems to be that the lack of ice in the arctic should have a similar effect that the lack of ice does on lake effect snow down wind of the Great Lakes. Once the lakes freeze over the snow decreases in the area, so a longer season of open water means more snow in the Tug hill plateau for example. The only thing is that where the effect would be is downwind of open water. Central Park doesn’t seem to be a good test spot.

  10. Steve from Rockwood says:

    Always a great read Willis. If I had to hazard a guess, you could take almost any single weather station and show the correlation between lower Arctic ice and greater local snowfall to be false. But when you throw all the weather station data into a big pot and average them out using Singular Value Decomposition a distinct and scientifically arguable correlation emerges. Climate science is like that and it puzzles me. I like the fractal idea of the universe – what you see on a large scale you also see on a small scale.

  11. Willis Eschenbach says:

    Zac says:
    March 12, 2012 at 4:54 pm

    On the NSIDC site they say Air temperatures over the Laptev, Kara and Barents seas ranged from 4 to 8 degrees Celsius (7 to 14 degrees Fahrenheit). That should be 39.2 F to 46.4 ºF or converting it the over way -13.8 C to -10 c.

    Confused ? I am.

    http://nsidc.org/arcticseaicenews/

    Actually, they’re correct. They said (emphasis mine):

    Laptev, Kara and Barents seas ranged from 4 to 8 degrees Celsius (7 to 14 degrees Fahrenheit) above average

    So they are talking, not about absolute temperatures, but the number of degrees above average, and if something is say 4 degrees Celsius above average, it is about 7 degrees Fahrenheit above average ….

    w.

  12. Zac says:

    Cheers Willis.

  13. John from CA says:

    Snow White takes a Walk in the Park, you’re too funny!

    I posted a comment on Climate Etc. related to this topic figuring that if there was some significant water vapor input from late forming Arctic ice that we’re likely to actually see it from the NOAA Arctic water vapor animations for just about any period of time in the winter.

    I noted that the principal ice loss is from the Barents and Greenland sea ice areas. I also noted the late formation of ice in the Beaufort, Chukchi, East Siberian, and Bering Seas in recent years.

    I got an interesting response from Jiping you might find interesting.

    Jiping | March 7, 2012 at 11:40 am | Reply
    Origin of Arctic water vapor during the ice‐growth season
    http://www.agu.org/pubs/crossref/2011/2010GL046064.shtml

    “This change suggests that the humidity source of Arctic air masses switches in early winter from locally driven to moisture transport from lower latitudes.”

  14. Latitude says:

    Willis, take a look at this…
    James just made an excellent post, pertaining to the same thing.
    Seems there are islands, that should have been covered in ice if we are to believe what Arctic “normal” ice is…..
    ….yet, those islands show up, and are named, on an Admiralty Chart of 1875

    http://suyts.wordpress.com/2012/03/12/how-did-they-know/

  15. Latitude says:

    Does anyone know what the actual air temperature is in the Arctic….when it’s supposed to be holding all this extra moisture?

  16. Mike Wryley says:

    The comments about lake effect snow got me to wondering.
    Does anyone know if salt water evaporates faster or slower than fresh water given identical
    temps, wind, relative humidity and baro pressure ?

  17. Brian H says:

    Sounds like there could be a whole lotta micro-climate things goin’ on. In a not-yet deciphered pattern?

  18. crucilandia says:

    http://www.wrcc.dri.edu/cgi-bin/cliMONtsnf.pl?ak0546

    there is no significant change in snow fall in Barrow, AK from 1949 to 2011

  19. crucilandia says:

    regional issue

    ABSTRACT
    A quality assessment of daily manual snowfall data has been undertaken for all U.S. long-term stations and their suitability for climate research. The assessment utilized expert judgment on the quality of each station. Through this process, the authors have identified a set of stations believed to be suitable for analysis of trends. Since the 1920s, snowfall has been declining in the West and the mid-Atlantic coast. In some places during recent years the decline has been more precipitous, strongly trending downward along the southern margins of the seasonal snow region, the southern Missouri River basin, and parts of the Northeast. Snowfall has been increasing since the 1920s in the lee of the Rocky Mountains, the Great Lakes–northern Ohio Valley, and parts of the north-central United States. These areas that are in opposition to theoverall pattern of declining snowfall seem to be associated with specific dynamical processes, such as upslope snow and lake-effect snow that may be responding to changes in atmospheric circulation.

    Kunkel et al. 2009
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 26

  20. tokyoboy says:

    Heavily OT, but my newest book has just come out:

    The title, literally translated, is “The Global Warming Myth: The Beginning of the End”.
    I owe much to WUWT and many contributors here. Thanks.

  21. Gary Hladik says:

    BarryW says (March 12, 2012 at 5:07 pm): “Central Park doesn’t seem to be a good test spot.”

    Barry’s right, Willis. You should take your cue from dendroclimatology, which sifts through mountains of tree-ring records to identify and use only the “treemometers” that correlate with temperature records. Since Central Park doesn’t correlate with changes in arctic ice extent, it’s obviously not a good “snowmometer”. You should discard it in favor of locations that do correlate with satellite-measured arctic ice extent, and then you’ll finally be able to confirm the model.

    Oh wow, do I have a great idea for a research grant application! Having identified strong “proxies”, I can use these locations’ snow records from the pre-satellite era to derive–with great statistical confidence–figures for historical arctic ice extent that no one else has so far been able to produce. Oh Mann, I smell the mother of all reverse hockey sticks, and it smells like money!

    /sarc for the humor-impaired.

  22. Ian W says:

    Mike Wryley says:
    March 12, 2012 at 5:58 pm
    The comments about lake effect snow got me to wondering.
    Does anyone know if salt water evaporates faster or slower than fresh water given identical
    temps, wind, relative humidity and baro pressure ?

    The delivered wisdom is that fresh water evaporates slightly faster. The presence of ions of Na and Cl (and many other impurities) reduce the number of water molecules at the surface that have the opportunity and energy to leave. Sea water also boils at ~103C presumably for the same reason.

  23. Willis Eschenbach says:

    Well done, Tokyoboy, my warm congratulations on your book.

    w.

  24. Allen63 says:

    A nice analysis. Yet:

    In figure 3, the peaks and valleys do seem to correlate (by eye).

    It may be that other processes work to help determine the total snowfall. But, maybe the autumn ice parameter does impact the final result.

    I sometimes question using “standard statistics” (which implicitly assume some things about underlying distributions and causes) to prove or disprove relationships — when we don’t actually know what’s going on and don’t actually know if the statistic used applies in the specific situation.

    This is a case where I, personally, would ponder what different statistical or numerical methods I might use to confirm the relationship between the sets of peaks. I would also consider other sources of data. Basically, I would try hard to prove my original conclusion (no connection between phenomena) wrong — before I assumed I was probably right.

  25. Willis Eschenbach says:

    Allen63 says:
    March 12, 2012 at 8:10 pm

    … This is a case where I, personally, would ponder what different statistical or numerical methods I might use to confirm the relationship between the sets of peaks. I would also consider other sources of data. Basically, I would try hard to prove my original conclusion (no connection between phenomena) wrong — before I assumed I was probably right.

    That’s great, Allen, report back on your results. I’ll be interested to see your analysis.

    w.

  26. steven mosher says:

    uhi. reduces snowfall.

  27. Gail Combs says:

    tokyoboy , Congratulations!

  28. Hi Willis

    Is there any work done on the Southern Hemisphere?

    I ask beacuse last winter here saw snowfall during mid-August in Wellington down to sea-level for the first time in 20 years, and snow actually fell in Auckland which I think is the first time in living memory

    Also am I to believe Antarctic Sea-Ice to be increasing – so a SH correlation shouldn’t exist – yet we had record snow!!!

    Andi

  29. Thrasher says:

    BOS (Boston, MA) and ORH (Worcester, MA) data in New England both show very large increases in snowfall during the last 20 years despite declining sea ice, so its not just New York.

  30. Congratulations, Tokyo Boy!

    Please let us know how it’s received, what the reviewers and the media have say. Any chance you might submit an English summary to WUWT? Staring at the cover, reflexively (and insipidly) waiting for the text to somehow resolve itself into comprehensible letters and words for me, I came to a better appreciation of the frustration illiterate people must feel.

    Very cool (actually “hot”) Hokusai-like cover, that one. Speaking of whom, I recalled a re-rendering in “warm” hues of one his most famous works from his Mt Fuji series and by some miracle found it again. That one would work for a translated English edition or article, as the image is iconic in the West as well: http://toastified.deviantart.com/art/Hokusai-Revisited-102717156

    All the best and may your book spread far and wide throughout your beautiful island nation!

  31. Gary Hladik says:

    steven mosher says (March 12, 2012 at 9:12 pm): “uhi. reduces snowfall.”

    Which raises the question: If Central Park UHI since 1979 is significant enough to affect snowfall, are the official adjustments–in such temp indexes as GISS produces–adequately compensating for it?

    I’m wondering if it’s possible to remove the UHI/snowfall effect, if any, by tracking winter precipitation instead of snowfall.

  32. Les Johnson says:

    Willis: I agree with Mosh. UHI reduces snow, and especially ice. Rain falls, temps drop, water freezes. For snow, it has to have a greater UHI to affect whetther it remains snow, or falls as rain. UHI would eliminate more ice than snow.

    It might be better to look at winter precipitation, to see if any correlation exists.

  33. oMan says:

    Love the last chart. It does indeed show how we want to see patterns, whether or not they’re present. I might go further and argue that “chartiness” is part of this: whenever we see two lines on a chart, we start trying to figure out how they correlate. Blame it on kindergarten and those learning games: “kids, what is wrong with this picture? Can you see five cats in the tree?”. Etc.

  34. Willis Eschenbach says:

    steven mosher says:
    March 12, 2012 at 9:12 pm

    uhi. reduces snowfall.

    Possible. Got a better data source than the Park?

    w.

  35. Hector Pascal says:

    @tokyoboy

    Greetings from Yamagata, and well done. I will show that to the good lady, and see if she’s interested.

    On snow. We’ve had 20cm over the past 2 days. Unheard of for this late in the winter. Total snowfall this winter is going to be around 16 metres plus.

  36. Agnostic says:

    Good on you for looking at this again Willis.

    My slight problem with this is the “loaded dice” caveat in the paper. They propose that the first significance of low sea ice is the extra humidity in autumn affects the wind patterns in the area. The extra humidity in cold air coming from the arctic region is only of secondary importance.

    But the paper does explicitly say that low sea ice is not the only factor. Could I suggest taking a look at the correlation with in particular ENSO to see if strong a El Niño will override the tendency to bring more snow in early winter that might normally have come due low sea ice extent.

    A second point is that the spatial distribution of sea ice may also be a mitigating factor. If the sea ice extent is evenly distributed, or not sufficiently open enough, it may not allow for strong enough increase in humidity localised to create a change in the atmospheric wind pattern.

    I think what is proposed by this paper is a piece of a climate jigsaw, that when considered with other pieces may help with seasonal forecasting. Just looking at a straight correlation between sea ice extent and snowfall is not sufficient.

  37. John Marshall says:

    Their Abstract claim ‘Strong Arctic Warming’ over the past few years. I would like their definition of Strong. Oh hang on their models show this warming so the claim must be OK.

  38. George Tetley says:

    majormike1
    Great link, see what you can do without models, if the word logic is still permissible in a scientific discussion I think Ewing and Dunn got it right !

  39. George Tetley says:

    The link to majormike1 was written in 1958,

  40. Agnostic says:

    Actually slight correction to my previous post, it’s the reduced temperature differential that affects the wind patterns. The extra humidity is of secondary importance.

  41. Hector Pascal says:

    @tokyoboy

    The good lady is back from work (8pm). Her translation:
    The Myth of Global Warming
    by: Tadashi Watanabe.

    Watanabe san. Thank you for your effort.

    For those outside Japan, the government has received advice from its scientists that AGW science is too uncertain to inform any meaningful policy decisions. The advice is to do nothing and wait. The Japanese government therefore will enact no policies to disadvantage Japan’s manufacturing WRT industrial competitors. That includes withdrawing from the Kyoto Protocol.

  42. > But folks said, and fairly, that I wasn’t really dealing with their claim.

    I think its good that you’ve realised that your previous analysis was all beside the point, though it was a bit of a shame that you didn’t say so at the time. You’ve made an attempt to do better, but you’re suffering from drunk-looking-for-keys-under-lamp-post syndrome: you’ve found a good dataset, but probably not one that is good for this problem.

    As before, you need to go back to the paper, and look at, say, their figure 7. Where you’ll notice they have plotted land-only, and masked out the coastal grid points. So a dataset from the coast isn’t a good idea. You want somewhere from 70N 60E, say; or maybe 110W 62N ish. You might be better off working with the reanalyses.

  43. Kip Hansen says:

    Willis,

    I’m from NY, both Upstate NY (everything above Westchester County) and the analogous-to-NYC Northern New Jersey Bergen County. Snowfall in Central Park is not a good metric for Northeast US snowfall at all. One can have a foot of snow in Bergen County or Western Connecticut and see an inch in Central Park. Three feet in Albany, NY and nothing in Central Park. It just doesn’t really relate. Central Park is on Manhattan Island, surrounded by warm water–thus has the ‘shore effect’– and a hot city.

    Big mistake — apples for oranges adding up to bananas.

  44. tokyoboy says:

    “Hector Pascal says: March 13, 2012 at 4:16 am ………….”

    Thanks Hector, and thank you friends for your attention.
    But I’m now quite sorry for eating up much space with an off-topic issue, on this fascinating thread by Willis.

  45. D. Robinson says:

    Willis, how about snowfall at Mohonk Lake, NY?

    http://www.wrcc.dri.edu/cgi-bin/cliMONtsnf.pl?ny5426

    There’s a long time weather station there, which has been written about previously. Not sure if the elevation hurts the discussion or not.

  46. Stomata says:

    Be aware of sudden adjustments by CT, NORSEX, NSCD even DMI when ice is like this
    http://arctic-roos.org/observations/satellite-data/sea-ice/ice-area-and-extent-in-arctic
    they basically cannot afford to have ice within the normal area for too long. Its all tripe anyway as we can see they have eecided to not show data from before 1979 and their baseline is therefore junk see real-science http://stevengoddard.wordpress.com/

  47. Vincent says:

    Not being a New Yorker, I’m a bit uncertain, but I think Central Park is in the middle of an urban heat island. So is it really valid to use it as representative of a region?

    The same was true when I lived in London more than 20 years ago – snow in the City was unheard of, but it could occur in the surrounding countryside. (OK, I admit, the Thames is probably a confounding factor !-)

    Regards
    Vincent

  48. Willis Eschenbach says:

    D. Robinson says:
    March 13, 2012 at 7:35 am

    Willis, how about snowfall at Mohonk Lake, NY?

    http://www.wrcc.dri.edu/cgi-bin/cliMONtsnf.pl?ny5426

    There’s a long time weather station there, which has been written about previously. Not sure if the elevation hurts the discussion or not.

    Thanks, D. I took a look. The correlation with Central Park is not bad, about 0.5 for the period post 1979 (p less than 0.001).

    But the Mohonk Lake correlation with the autumn arctic ice levels is actually WORSE than for Central Park. For the non-detrended data, the r^2 is 0.07 (p=0.12), and for the detrended data r^2 is 0.01 (p=0.64).

    So all of you folks that have been claiming that UHI is the reason the effect didn’t show up in the Central Park data?

    Sorry, but you were wrong. Usually, I wouldn’t take pleasure in pointing this out, but it’s been pointed out in an unpleasant fashion by useful idiots like Billy Connolley, who said:

    I think its good that you’ve realised that your previous analysis was all beside the point, though it was a bit of a shame that you didn’t say so at the time. You’ve made an attempt to do better, but you’re suffering from drunk-looking-for-keys-under-lamp-post syndrome: you’ve found a good dataset, but probably not one that is good for this problem.

    Sorry, Billy, but as is becoming a habit with you … you’re wrong again. Perhaps you’re suffering from the old “drunk-looking-for-his-brain-under-a-lamp-post” syndrome …

    Also, you say my previous analysis was “beside the point” … actually, that’s what we’re trying to determine here. It’s called the “scientific method”. I said if there was a serious or significant effect, it would show up in the data for North America. But heck, it didn’t show up there.

    People said it didn’t show up, not because it was too small, but because it was a local effect. And yes, it’s possible that it’s a local effect … but we haven’t found that one either.

    That means that my previous analysis, far from being “beside the point”, actually is correct so far. We haven’t found the claimed effect anywhere.

    So … more datasets? Anyone?

    w.

    PS—I also find it quite significant that the claimed effect is more visible in the non-detrended data, and disappears entirely when we detrend both datasets.

    This means that the effect is not operating on a year by year basis … which makes it very likely that the somewhat greater (but still not statistically significant) correlation using the non-detrended data is only an artifact.

  49. Eyal Porat says:

    For a true scientist, the collapse of a theory leads to change of view and abandoning it.
    For the “New Scientists”, it leads to bending of facts and torturing of data.
    It never is an option for them to seek a different direction and alternate options.
    Oh so sad.

  50. Willis Eschenbach says:

    I just tried Lake Placid, New York snowfall as well, still no joy. R^2 = 0.15, p = 0.07.

    w.

  51. Willis Eschenbach says:

    And Rangeley, Maine, came the closest yet, with p = 0.054 … so near, and yet so far …

    Weak. There is a very, very weak association between some sites and the ice, but I haven’t found one yet that is significant at the p less than 0.05 level …

    w.

  52. Vincent says:

    Interesting Willis. I have long been of the the belief that a cold winter would be followed by a warm summer, and that a mild winter was followed by a mild summer. That was my personal observation of how the weather worked for me. Or so it seemed. I didn’t check against records.

    My reasoning was simply that the average does not change much from one year to the next, so to compensate for a high, there had to be a subsequent low.

    In this case it looked reasonable to make the same assumption, but on a regional basis – too little ice here, dump some more snow there to even the balance.

    I wonder if that idea has any merit?

    Regards
    Vincent

  53. Willis in your comment on March 13, 2012 at 11:06 am under your PS you say:

    “This means that the effect is not operating on a year by year basis … which makes it very likely that the somewhat greater (but still not statistically significant) correlation using the non-detrended data is only an artifact.”

    Well said. – Personally, I hope we are not still around at a time when the North Atlantic and The Arctic Oceans get a better chance to “equalibralize”. – Then – we may see one “heck of an “Effect” – Year after year.

  54. Willis Eschenbach says:

    O H Dahlsveen says:
    March 13, 2012 at 1:25 pm

    Willis in your comment on March 13, 2012 at 11:06 am under your PS you say:

    “This means that the effect is not operating on a year by year basis … which makes it very likely that the somewhat greater (but still not statistically significant) correlation using the non-detrended data is only an artifact.”

    Well said. – Personally, I hope we are not still around at a time when the North Atlantic and The Arctic Oceans get a better chance to “equalibralize”. – Then – we may see one “heck of an “Effect” – Year after year.

    No clue what that means, O H. What is “equalibralize” and how do oceans do that? Why would we see an “Effect” from that, and what “Effect” would we see?

    What am I missing here?

    w.

  55. Kip Hansen says:

    Willis,

    You can not seriously be defending the use of Central Park, NY as a proxy for snowfall in the entire NE US. Had Mann or Jones tried any such silly trick, you’d have blasted them off the map. I don’t care what your finding is, you just can’t claim Central Park snowfall as representative of the whole NE US and Europe.

    Monhonk Lake, NY has its own special weather, in a different sort of way. You would have to have visited there to understand why that is. It is kinda like a ‘lost world’ thing. But, I’d say more representative than Central Park, at least.

    Kip

    PS: Anyone REALLY interested in this idea should read the entire original paper, it is only a few pages long, including lots of illustrations and graphs — shorter, I believe, than Willis’ misdirected refutation.

    available at: http://curryja.files.wordpress.com/2012/03/pnas.pdf

  56. Geoff Withnell says:

    “For there to be a relationship, it needs to be proportional.” Ah, not quite correct. For there to be a linear relationship, it needs to be proportional. Of course, witha a noisy signal, and not an enormous amount of data, good luck finding a norlinear relationship.

  57. Sorry Willis I must admit that “equalibralize” is a made up word that does not belong in anybody’s dictionary (I am a sinner).
    I could have said: “should the exchange of heat between the Arctic- and the Atlantic Oceans become more intense than it is at the moment” – Then, if the Arctic Ocean becomes completely “Ice free” and the North Atlantic becomes cooler, it may have an impact on precipitation which may very well come down as snow. –

    Well, after all the “Ice-berg” that sank the Titanic in 1912 was floating around as far south as what is equal to the northern border between Spain and Portugal – (circa). – So, there must be cold water currents flowing southwards from the Arctic.

    I am quite certain it is not CO2 that gets rid of the Arctic Sea Ice and if it is not The Sunshine either, then there is just the “Gulf Stream” or the North Atlantic left to blame. – I know the Gulf Stream runs all along the coast of Norway – so why not all the way to the Arctic?

  58. Hmmm. – I am probably still not making much sense.

  59. Willis Eschenbach says:

    Geoff Withnell says:
    March 13, 2012 at 5:17 pm

    “For there to be a relationship, it needs to be proportional.” Ah, not quite correct. For there to be a linear relationship, it needs to be proportional. Of course, witha a noisy signal, and not an enormous amount of data, good luck finding a norlinear relationship.

    Indeed. What I really meant was that the effect needs to be “dose related” in some linear or non-linear sense.

    w.

  60. Willis Eschenbach says:

    Kip Hansen says:
    March 13, 2012 at 5:07 pm

    Willis,

    You can not seriously be defending the use of Central Park, NY as a proxy for snowfall in the entire NE US.

    Kip,

    You can not seriously think I am defending the use of Central Park, NY as a proxy for snowfall in the entire NE US.

    I always encourage people to quote my words. Not sure where you got that impression, but it’s wrong.

    I had used central park because it was the data I had. A couple of people said the reason why it didn’t correlate was UHI. So I showed a several other sites, and they didn’t correlate either.

    My response was to say that people were wrong when they said UHI was the problem with central park. Clearly, other sites don’t correlate either, so UHI is not the explanation.

    You accuse me of being “misdirected” … you should check your own compass before issuing those kinds of unsubstantiated allegations, you’re way off the path yourself.

    w.

  61. Kip Hansen says:

    Willis,

    ‘I had used central park because it was the data I had’. Previously, you said: ‘Unfortunately, I couldn’t find area-wide data for the northeastern US, but I did find something better. This is one of the longest continuous records of snowfall in the northeastern US—the century and a half long record of the snowfall in Central Park in New York City.’ This use of the ‘I was searching under the streetlight because that’s where the light is’ excuse for using Central Park is not logically strong. Reading the original study shows clearly they are not talking about single site snowfall, but snow cover–snowy winters–over large areas of the Northern Hemisphere (in the US, northeastern and mid-west), Europe, and East Asia.

    It is your refutation that is misdirected (‘…..Willis’ misdirected refutation.’ ), not you personally.

    The misdirection is that you are trying to refute a study that finds:
    ‘The results of this study add to an increasing body of both observational and modeling evidence that indicates diminishing Arctic sea ice plays a critical role in driving recent cold and snowy winters
    over large parts of North America, Europe, and east Asia. The relationships documented here illustrate that the rapid loss of sea ice in summer and delayed recovery of sea ice in autumn
    modulates not only winter mean statistics (i.e., snow cover and temperature) but also the frequency of occurrence of weather events (i.e., cold air outbreaks).’
    by finding non-correlation(s) with single-site snowfall records in a very small part of the area reportedly affected by the effect claimed, instead of area-wide on a sub-continental basis, which is what the study is about.

    So now you have done two analyses on two data sets (Whole US and Central Park) neither of which was the subject–or point–the original study–and and claim to find the study wanting?

    For other readers, the original study is at available at: http://curryja.files.wordpress.com/2012/03/pnas.pdf

  62. Willis Eschenbach says:

    Kip Hansen says:
    March 14, 2012 at 3:04 pm

    … So now you have done two analyses on two data sets (Whole US and Central Park) neither of which was the subject–or point–the original study–and and claim to find the study wanting?

    Thanks, Kip. You’re not following the story. So far I have looked at 1. The Northern Hemisphere as a whole, 2, Just North America, 3. Just Europe and Asia, 4. Central Park, 5. Mohonk Lake, 6. Lake Placid, and 7. Rangeley, Maine.

    In not one of these is there a statistically significant relationship between autumn (SON) Arctic ice and winter (DJF) snowfall, whether detrended or not. Not one.

    I have also made a call for information on some other snowfall datasets. You have not provided one.

    You are also not following the paper as to which areas are supposed to be affected. The claim is supposedly valid for the “northeastern united states”. I’m not finding it. If you know where it can be found, please enlighten us. Their figure 1 shows the putative effect as existing as follows:

    So I’m calling BS on your statement that I haven’t investigated enough datasets. Look at their claims! When I first looked at that, I started out by saying that with that amount of red, surely, surely it would be easily visible in the datasets on a global level … but it’s not. Not even close.

    So I figured the North America dataset should surely show it … but it doesn’t, not even close. And so on down the line. All of New England is bright red, it should show up there … but I can’t find it.

    Now, if you have another snow dataset that you’d like me to look at, trot it on out, I’m your man. If not, I stand by my conclusion—arctic ice cover is only a minor player in the question of winter snowiness.

    w.

    PS—Curiously, if they are right, it reduces one of the oft-made feedback claims. This is the claim that reducing the arctic ice reduces the albedo, and thus warms the world.

    But if reducing ice area results in increasing snow area as they claim, that will tend to balance out the albedo effect. Gotta love the climate, it’s weird either way.

  63. David A. Evans says:

    tokyoboy says:
    March 12, 2012 at 6:51 pm

    Good luck with the book. :-)

    Hope you win some converts.

    DaveE.

  64. Kip Hansen says:

    Willis, Willis, Willis — ‘Central Park, 5. Mohonk Lake, 6. Lake Placid, and 7. Rangeley, Maine.’ all = single site snowfalls. Your article says: ‘ …it is not visible using the snow data for the whole US’ so maybe that’s what you mean by one of your first two ‘1. The Northern Hemisphere as a whole, 2, Just North America,’ . I think it’s neat that you’ve looked at ‘just Europe and Asia’ as well. In efforts to replicate a study, isn’t it important to look at the same or equivalent data? Have you actually looked at the data that Jiping Liu, Judith A. Curry, Huijun Wang, Mirong Song, and Radley M. Horton used in their study? (They say it is available at http://climate.rutgers.edu/snowcover ) Do you have reason to doubt their data? Have you asked Liu, Curry, Wang, Song or Horton for clarification?

  65. Willis Eschenbach says:

    One more thing. I object to the kind of maps shown above as their Figure 1B. Here’s the problem. When you look at the map, it says “regions within contours denote the regression above 95% confidence”.

    The difficulty is, on a purely random but fairly smoothly varying map like Figure 1B, you’d expect about 5% of the total area to be a “region within contours” which is above 95% confidence.

    What is usually not noticed is the underlying significance question has changed, it is different for maps.

    For a single result, the relevant question is “Is this result significant at p less than 0.05″, that is to say the 95% level.

    But for a map, the corresponding question is, “Is the amount of ‘significant’ area significantly different from 5% of the total area”. That’s a more subtle and harder question to answer.

    So I’m willing to look at a map like their Figure 1B, but in my head I’m asking “Is the “significant’ area more than 5% and if so by how much?”.

    w.

  66. David A. Evans says:

    I posited some time ago, (over a year,) that reduced Arctic ice cover was a negative feedback.
    The paper under discussion seems to validate that posit.

    DaveE.

  67. Kip Hansen says:

    Willis,

    Just to wrap this up….I usually admire your work. In this case, I felt you’d wrong-footed yourself with Central Park–representative ONLY of snowfall in NYC.

    To address Lui et al, or any other study carefully done by seriously intelligent scientists, it is first necessary to attempt to replicate what they have done–using the exact same data sets, the exact same methods, and see if you derive the same results, then determine if their conclusions follow from those results.

    Instead, you have used different data sets that measure different phenomena, applied different analytical methods, and not-surprisingly, arrived at different results. This is fine and good if you wish to present your study for perusal/review/publication to be considered alongside of Lui et al.

    What you can’t do though is to claim to have done something scientific regards to Lui et al. With what you have done so far, such a claim is improper–the attempt at this claim is what I privately refer to as ‘slash and hack’ criticism, a wholly unscientific endeavor, usually seen at other venues (RC and JR come to mind).

    It suits you better to either do a professional job or leave it alone.

  68. Willis Eschenbach says:

    Kip Hansen says:
    March 15, 2012 at 6:05 am

    Willis,

    Just to wrap this up….I usually admire your work. In this case, I felt you’d wrong-footed yourself with Central Park–representative ONLY of snowfall in NYC.

    I gave results for three widely separated stations in NYC—Central Park, Mohonk Lake, and Lake Placid. Not only that, but I JUST POINTED THAT FACT OUT TO YOU, saying you weren’t following the story … so now, when you repeat your incorrect statement, it is no longer an innocent error.

    I have no problem being busted for what I’ve done. But stop trying to bust me for things I haven’t done.

    To address Lui et al, or any other study carefully done by seriously intelligent scientists, it is first necessary to attempt to replicate what they have done–using the exact same data sets, the exact same methods, and see if you derive the same results, then determine if their conclusions follow from those results.

    Thanks, Kip. At your suggestion, I’ve written to the Rutgers snow extent folks requesting gridded data.

    However, I disagree with your claim that to address a study one needs to first replicate it. If there are obvious mistakes, then is more than sufficient to point them out. For example, the authors appear to have ignored autocorrelation in their calculations of significance … which in itself invalidates the entire study.

    In this case, they claim (see their figure 1 above) that the effect is a) very widespread, and b) at its strongest in New England.

    So far, I’ve shown that a) the effect is not widespread, and b) four widespread sites in New England, which is supposed to be strongly affected, show NO AFFECT AT ALL.

    You seem to think that this is meaningless. It is not. Yes, as you point out, none of this falsifies the effect.

    But as Thoreau noted, “Sometimes circumstantial evidence is very strong, as when you find a trout in the milk.”

    So, many thanks for your push for me to actually take the final step. I will be surprised to find anything. You comment about studies done by “serious intelligent scientists”. There are three assumptions in there, and in climate science I find that the usual case is that at least one of those three assumptions is not met.

    In the current example, for instance, I find no mention of autocorrelation in their work. I also find no mention of the fact that in a mapped continuous variable, we expect to find a spurious “significant” result over 5% of the map.

    Those are huge lacunae, Kip, but they are depressingly common errors in climate science. Here’s another one:

    By examining observational data for the period 1979–2010, the fraction of winter (December, January, February) climate of the extratropical Northern Hemisphere that is linearly congruent with the interannual variability of autumn Arctic sea ice is found by regressing winter anomalies of snow cover and atmospheric fields from the National Center for Environmental Prediction reanalysis II (NCEP2) onto the detrended autumn Arctic sea ice area.

    They claim they are “examining observational data”, but in fact they are doing no such thing. They are regressing observations against climate model output (NCEP2). Claiming that the output of climate models is “observational data” is deception, Kip—either they’ve deceived themselves or they are deceiving us … and neither one is a good sign.

    So you want to tell me again about how these are “serious, intelligent scientists”? Because serious intelligent scientists don’t claim to use observations and then use model results. Serious intelligent scientists adjust for autocorrelation …

    So I make no assumptions about the quality of the work. I’ve been disappointed too many times. And no, sometimes it’s not necessary to replicate an entire study if there are obvious errors … like ignoring autocorrelation, for example.

    I’ll report back when I hear from the Rutgers folks, and thanks again for your support,

    w.

  69. Kip Hansen says:

    Willis — Sorry that you feel hassled and or ‘busted’. I was trying to smooth things out a bit but it seems you are sort of beside yourself this late in the thread.

    I am only trying to steer you to what I consider a more scientific, and thus less emotional and less ‘slash and hack’ approach, which, in the end, I fully believe would save a lot of time, unnecessary calculation, and a lot less attack-and-defend rhetoric in the comments.

    If you suspect–‘For example, the authors appear to have ignored autocorrelation in their calculations of significance’–an obvious egregious error in calculation or method, the more usual collegial action would be to query the corresponding author. The matter could be settled in a quick email exchange.

    Such statements as ‘four widespread sites in New England, which is supposed to be strongly affected, show NO AFFECT AT ALL.’ are not useful. In a medical study that found a widespread general improvement in a cohort of ten thousand individuals, calling out four individual’s personal results as examples of the whole would be meaningless. We have already discussed that one of the ‘individuals’ (Central Park) you have picked is already strongly suspected to be unrepresentative of anything except itself.

    Your hubris and your disappointment–‘either they’ve deceived themselves or they are deceiving us … and neither one is a good sign.’– seem to have clouded your better judgement.

    I recommend the Caribbean–I am on my 42′ cat in Honeymoon Bay, Water Island, St Thomas, USVI. Come for a visit, we’ll put you up in the spare cabin.

  70. Willis Eschenbach says:

    Kip Hansen says:
    March 15, 2012 at 2:58 pm

    Willis — Sorry that you feel hassled and or ‘busted’. I was trying to smooth things out a bit but it seems you are sort of beside yourself this late in the thread.

    Say what? I said nothing about being hassled, not one word. And I said I don’t mind being busted for what I’ve done, but not for what I haven’t done. For example, you claimed that I had only looked at two sites when I’d looked at seven and offered to look at others. So you busted me for what I didn’t do … nor did you ever apologize or even acknowledge your error.

    To the contrary, you repeated your untrue claim after I had pointed out that it was untrue … and now you think I’m out of line for protesting about that?

    I am only trying to steer you to what I consider a more scientific, and thus less emotional and less ‘slash and hack’ approach, which, in the end, I fully believe would save a lot of time, unnecessary calculation, and a lot less attack-and-defend rhetoric in the comments.

    If you suspect–’For example, the authors appear to have ignored autocorrelation in their calculations of significance’–an obvious egregious error in calculation or method, the more usual collegial action would be to query the corresponding author. The matter could be settled in a quick email exchange.

    I appreciate that you are trying to assist me, Kip, it is appreciated, and your idea sounds reasonable. However, I have been alternately ignored and flat out lied to by so many scientists that I’ve given that tack up. No matter whether they say yes or no or just don’t answer, I can’t gainsay them. They have not released their code, which would make it easy to tell what they’ve done, so I can’t even check their statements. So what’s the point in asking?

    You say it would be more “collegial” to query the corresponding author … but that assumes that I can trust their word, and in the climate world, that’s a sucker’s bet. However, let me give it one more time, the “old college try” … I’ll report back with my results. No response yet from the Rutgers snow folks …

    Such statements as ‘four widespread sites in New England, which is supposed to be strongly affected, show NO AFFECT AT ALL.’ are not useful. In a medical study that found a widespread general improvement in a cohort of ten thousand individuals, calling out four individual’s personal results as examples of the whole would be meaningless. We have already discussed that one of the ‘individuals’ (Central Park) you have picked is already strongly suspected to be unrepresentative of anything except itself.

    First, no way there are ten thousand snow measuring sites in New England, there are maybe fifty or a hundred.

    Second, this is not a medical study. It is a claim that the snowfall is affected over the entire area, a type of claim that is rarely made in medical studies. Yes, I agree, four widely separated sites don’t prove anything … but they definitely send up a red flag. You see, although human beings show little correlation person-to-person, one dies and the next one is fine, precipitation is much more highly correlated. I may get sick and the guy next to me may not. But it would be unusual for the snowfall records to be uncorrelated in that manner. That’s why all of New England is red, and it is why you never see that kind of thing in a medical study.

    For example, the correlation 1979-2011 of Central Park (DJF) with Mohonk Lake is 0.70. The correlation of Mohonk with Rangeley, Maine is 0.57.

    Not only that, but the correlation of Central Park snow amount with North American snow area is 0.49, and that of Rangeley amount with North American snow area is 0.52. Mohonk is a bit lower at 0.33, but still respectable.

    So your medical example is not a parallel at all, because people are not correlated like snowfall is. As you point out, it’s certainly possible I picked four of the stations in the area that are NOT correlated with New England snow area … but given their high correlation with each other and with North American snow area, the odds are not good that somehow I’ve picked four total outliers.

    Your hubris and your disappointment–’either they’ve deceived themselves or they are deceiving us … and neither one is a good sign.’– seem to have clouded your better judgement.

    Again, I fear you read things into my words that are not there, and you misquote me in the bargain. What I said was:

    Claiming that the output of climate models is “observational data” is deception, Kip—either they’ve deceived themselves or they are deceiving us … and neither one is a good sign.

    So is your point that claiming that the output of climate models is “observational data” is not self-deception, but in fact is good, solid scientific practice?

    Or do you agree that they are deceiving themselves and others by calling model output “observational data”?

    In either case, I’m not “disappointed” by that in the slightest, I’ve been playing this game far too long for that. Actually, I’m not even surprised in the slightest that they can’t tell climate model output from observational data, that’s far too common these days to even merit comment.

    I recommend the Caribbean–I am on my 42′ cat in Honeymoon Bay, Water Island, St Thomas, USVI. Come for a visit, we’ll put you up in the spare cabin.

    Can’t tell you how much fun that sounds to this landlocked sailor, and I can’t thank you enough for your most generous offer, Kip. It would be great, perhaps some other time, I do love to sail catamarans.

    But my next tropical excursion is already scheduled, and it is going to be for surfing purposes, so regret greatly that I have to pass until I can build up more vacation time.

    All the best to you,

    w.

  71. Willis Eschenbach says:

    Kip Hansen says:
    March 15, 2012 at 2:58 pm

    I am only trying to steer you to what I consider a more scientific, and thus less emotional and less ‘slash and hack’ approach, which, in the end, I fully believe would save a lot of time, unnecessary calculation, and a lot less attack-and-defend rhetoric in the comments.

    If you suspect–’For example, the authors appear to have ignored autocorrelation in their calculations of significance’–an obvious egregious error in calculation or method, the more usual collegial action would be to query the corresponding author. The matter could be settled in a quick email exchange.

    To which I replied:

    I appreciate that you are trying to assist me, Kip, it is appreciated, and your idea sounds reasonable. However, I have been alternately ignored and flat out lied to by so many scientists that I’ve given that tack up. No matter whether they say yes or no or just don’t answer, I can’t gainsay them. They have not released their code, which would make it easy to tell what they’ve done, so I can’t even check their statements. So what’s the point in asking?

    You say it would be more “collegial” to query the corresponding author … but that assumes that I can trust their word, and in the climate world, that’s a sucker’s bet. However, let me give it one more time, the “old college try” … I’ll report back with my results.

    I’m back to report that, as I said I would, I sent the following email to the corresponding author on the 15th:

    Dear Dr. Liu;

    In reading your study, I see that you make no mention of autocorrelation in the ice and snow datasets and its effect on the results.

    Have you adjusted your significance figures for autocorrelation, and if so, how have you done so?

    Many thanks,

    Willis Eschenbach

    So far … crickets.

    w.

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