The last few days on the melt front have been exciting. The melt rate increased prompting Neven to post Flash Melting which is worth visiting and reading to see side-by-side satellite figures of the ice concentration and read comments discussing of whether ice actually melted, was compressed or whether sensors tend to mis-detect ice after water has washed over the top of the ice.
Meanwhile, I’m just going to show figures that put the numerical value of the reported extent loss in context.
One-Day Extent Loss
If I recall correctly, some in Neven’s comments wondered in anticipation if this was going to be a record 1-day loss. I wondered myself, so I added spaghetti to my script and created a graph showing 1 day extent losses:
It turns out the recent losses are not records in the combined JAXA/GSFC record back to 1979. (I could also look back to 1972 but plot only back to 1979 when CT areas are available.) Our pen-ultimate loss rate (i.e. “day before yesterday”) was the 2nd highest single day loss for day 234 since 1979 and the 3rd loss since 1972.
Two-Day Extent Loss Rate
The loss event seems to have persisted, so I decided to add even more spaghetti and plotted the two day loss rate:
The current 2-day losses are also not records. They are high for this time of year, but I didn’t pull out the numbers to see if we are the 2nd, 3rd highest or what not.
Weekly Extent Loss Rate
As it is my intention to post updates roughly weekly, I usually show weekly loss rates. This is the weekly loss rate with a final black “dot” showing the loss rate if the most recent daily loss rate is sustained:
The 7 day average loss rate has been high for this time of year but is not at record levels.
Mind you: My statistical model says 2011 could break the record minimum. Doing so does not require breaking a 1-day, 2-day or 7 day extent loss which are short term. It only requires achieving above averages extent losses or having extent loss persist a relatively late into September.
Current NH Extent values
Despite the recent relatively rapid extent losses, the JAXA 7-day average extent remains above the 2007 record minimum.
(This is the metric our Quatloo bet uses.)
Area JAXA and CT:
In comments, Owen observed that the JAXA area has dropped rapidly; it has. The auto-updating JAXA graphic (currently dated 8/23) is provided below:
Currently, the 2010 Area remains above the 2007 minimum. Not being Mother Nature, I can’t guarantee that won’t change by tomorrow.
CT today’s reporting for area is currently lagging the JAXA extent reporting by one day. Nevertheless, I plotted the daily values up to the final one reported.
Using currently available data, CTs 2010 area remains higher than the minimum in 2007. All agencies show we are in a rapid area/extent loss period; I don’t know if this will change tomorrow.
Also note: Dewitt pointed out that the 2007 rate of area loss was relatively slow during late August resulting in a relatively early area minimum. If an average loss rate prevails this year, we will watch the CT area fall below the 2007 minimum. Laura S. has explained why she thinks the area minimum might well exhibit a slow loss this year. Me? I don’t know. I haven’t focused on looking at factors that most strongly affecting or correlate with area loss in late August and early September. We’ll see.
The bets
If you are wondering how the bets are going: I’m going to show my current estimate of the odds of exceeding the 2007 extent 7-day JAXA extent minimum or exceeding the 2010 value tomorrow. I am deferring because currently, the most likely model in the collection I weight involves the use of the CT 7-day area and I think that might change a lot by tomorrow.
I’ll show histograms and report on the odds of a minimum tomorrow.
Oh… but if I did show the histogram, I happen to be the “front runner” in the sense that my bet is closest to the best estimate of my own model. The ±95% uncertainty range is reported as 4.11 to 5.02 million km2. Both will probably change tomorrow too. Given observed recent loss rates, I anticipate we’ll knock 5.00 out of the ±95% uncertainty window when CT reports their area!
Meanwhile: Mosher said if I write “Jeez, Jeez, Jeez” he will conjure Jeez. We’re hoping for his acclaimed narratives on ‘the baby ice’. So, “Jeez, Jeez, Jeez”!
In terms of area, the current anomaly is already below the anomaly at the 2007 minimum. Ice area loss would have to be below normal (anomaly become less negative) to fail to set a record low area. Of course that could well happen, but according to past behavior, it’s unlikely. The amount of vulnerable ice is still very high. The ratio of CT area to JAXA extent (0.599) is a record low for day 234.
I did this plot myself after seeing Neven’s excited comments on it.
here’s my version.
It breaks one of my rules, because it uses “yellow” for a curve color (all of the pre-2004 curves are yellow in fact). But it does make it visually striking how there seems to have been more of a “step function” circa 2004 than a simple linear trend. This suggests to me that more complex dynamics may be related to the apparent acceleration in ice loss than can be explained by a simple arctic heating model.
Transmission received.
DeWitt–
I’m confused How can the anomaly be lower than the 2007 anomaly if the absolute value isn’t lower? Shouldn’t they be:
Anomaly1=Absolute1-baseline
Anomaly2=Absolute2-baseline
So:
Anomaly1-Anomaly2= Absolute1-Absolute2?
I haven’t done the math, this appears to be correct based on using the “eyeball” method on the area graph.
Re: lucia (Aug 24 09:31),
The anomaly for day 234 of 2011 is lower than the anomaly for day 250 (minimum area) of 2007. If the anomaly for 2011 stays constant (area is lost at the average rate) then the minimum area for 2011 will be lower than for 2007. The anomaly for 2007 increased from -2.0756 Mm2 on day 234 to -1.8063 Mm2 on day 250. If the 2011 anomaly remains constant at -1.9162 Mm2, 2011 area will be below 2007 for the same day in two days.
DeWitt–Ahh! Yes. That clarifies what you mean. (Looking back I can see that you did say it clearly. I must have been skimming…)
@Lucia
I cannot believe you deleted that post I made yesterday. It wasn’t off topic whatsoever, I was simply trying to reinforce the point that the temperatures aren’t changing. It’s truly amazing you find ice melting so fascinating, yet are too afraid to see if the temperatures are changing. So let me get this straight, the temperatures aren’t changing (so obviously the ice loss has nothing to do with global warming) so I guess global warming is affecting the wind patterns. Lucia, do you have a shred of integrity? You act like it is a huge undertaking to simply post the temperatures.
@DeWitt and Mosher
I’m going to pre-emptively tell you 2 guys to go pound sand because I know you’re the resident body guards here. You can’t find the temperatures either or you won’t post links to them because it hurts your narrative. I’ve seen all talk from you but no action.
Side note: does global warming mean the temperature is going up?
Dr. Jay
1) As far as I am aware, I did not delete anything you posted yesterday.
2) A comment by you posted yesterday appears on the 7 day avearge thread. It’s content appears to match the topic you claim was in the comment you think I deleted. It also begins “Who was that comment directed at, Flinch boy?”. This would be sufficient grounds to delete the comments based on the name calling.
3) As you know, you are pre-moderated. Sometimes I will I goof when placing my mouse pointer over either “approve”, “trash” or “spam” when quickly visiting the moderation area. It seems I did so, as I should have moderated you for name calling.
4) If you find discussions of ice melting boring, don’t read them.
Re: Carrick (Aug 24 09:08),
If you plot the monthly averages, you get what looks like a linear trend. I haven’t tested the residuals, but by eyeball, they look i.i.d..
Warning! Bad physics joke.
Does global warming mean the temperature is going up?
Not when we are melting ice. 😉
Warning! Bad physics joke.
DeWitt, the “new residuals” (t > 2005) from your figure are shifted down relative to the previous residuals, which is troubling. This is probably an artifact of using a straight line to perform the fit to, but this type of feature is one thing you really have to look at carefully when you are performing linear fits (the residuals at the end get a higher weighting in the computation of the slope than the center). Errors in fitted models can lead to unrealistic p values.
It’s easy enough to check this….redo the significance calculation without the 2006-2010 and see what p value you get.
That doesn’t mean I’m “right” in my approach (not all estimators are equally good at pulling signal from noise). Usually the mantra is to stay away from smoothed series, like monthly data. For the purpose we are using it for, it may actually be better. I have a meeting, so I’ll comment on why I think that may be the case when I get back.
Its looks like neither NH ice nor Global temperatures (see UAH AMSU) are going anywhere near what the warmistas want and neither are any of their childish theories: read Nature
http://wattsupwiththat.com/2011/08/24/breaking-news-cern-experiment-confirms-cosmic-rays-influence-climate-change/ even they (NATURE) have HAD to publish this (there are 62 authors!). When are they going to give up and stop spending our monies? Pretty sure we now have an extra 62 skeptical scientists from CERN.
Hey, until this stops we should expect it to continue.
-Andrew
Alright well I apologize for the anger, Lucia. I just think its really dishonest of you to not post the temperatures. If you’re going to claim global warming is causing this ice melt, back it up with data. A graph showing the ice going down tells us nothing.
Dr.Jay–
Feel free to find whatever temperatures you think ought to be posted, make a graph, post the graph and provide us the link.
Re: Carrick (Aug 24 12:37),
Picking different starting points ex post facto is data snooping.
I don’t think using non-overlapping averages is the same thing as smoothing, which I think means using some sort of a moving filter. A moving filter leaves the same, or nearly the same apparent number of data points, depending on the length of the filter, the number of data points and the treatment of the end points. But because you have increased autocorrelation, the true number of degrees of freedom has gone down, possibly a lot. With non-overlapping averages, the number of data points more closely reflects the true number of degrees of freedom because short term autocorrelation goes away.
As far as the last four points being below the mean, that’s not enough to declare the process out of control. You need at least six and possibly as many as nine. None of the other Western Electric rules are broken either. Of course this year will likely make it five in a row below the mean. I’d have to construct a CUSUM or EWMA control chart to do better. They will pick up a shift in mean faster than an individuals chart.
Dr Jay,
.
[“Dr.Jay–
Feel free to find whatever temperatures you think ought to be posted, make a graph, post the graph and provide us the link.”]
.
Here you go, mate…
.
http://www.woodfortrees.org/plot/hadcrut3gl/from:2002/to:2011
.
2002 chosen to match the JAXA data.
.
Hmmm, not much warming there…:)
DeWitt:
Actually it’s not…. if you see outliers near the end of your range of data (and there certainly are here), it’s testing for the effect of the outliers on the over-all fit. (Generally this goes under the rubric sensitivity analysis.)
Data snooping is when you are trying to pick a model by trial and error. Sensitivity analysis is used to improve your understanding of the true uncertainty in the model parameters (as opposed to the usually wrong and overly optimistic formulas coming from the OLS framework.)
One of the big problems with assuming linear models (or any other OLS approach) is if the model is invalid, your p-value is meaningless. Since there is no apriori reason to expect a linear trend, trying to extract an uncertainty from this is “ifficacious” at best.
I agree that I used the wrong word when I said “smoothing.” I should have said “filtering”, and there is an argument for doing this: By going to a monthly average, you get rid of weather noise, and this does decrease the overall variance some. [It affects the result here because max and min operators are nonlinear. For direct OLS, high-pass filtering shouldn’t affect the result, nor, if you do it right, correlation introduced by a running average.]
I’m note sure what “process out of control” refers to, it’s not in my parlance. But it is easy enough to check what I am saying: The slope of an OLS line weights end points more heavily than the center, that’s just a standard result, and easily enough seen from the formulas for a least squares fit. It’s the Sxy term that does it.
To illustrate, assume a zero intercept, then you get the formula
$latex m = {\sum_n x_n y_n \over \sum_n x_n^2} = {\sum W_n y_n}$
where
$latex W_n = {x_n \over \sum x_n^2}$.
You just need one bad outlier near an end point to totally throw off the fit.
Unless you really think it’s a linearly varying function, partitioning is probably an improved method of data analysis, since it’s not parametric (it just depends on picking a break point, which we can choose based on where the anomaly method fails), and is much less sensitive in general to modeling assumptions.
By the way, I noticed your units were Mm2. Don’t you mean M km2?
In the mean time, I looked at the metric max_of_year – min_of_year, using the daily versus “monthly” data (I resampled the data at a rate 1/12 years).
Anyway, here’s the results.
As I mentioned before, I am not very comfortable using area rather that extent, because (IMO anyway) it is much more sensitive to the details of the model used to generate it. But that’s just me, YMMV.
The real test of these various methods is to see how robust they are against differing groups data products, and to construct a more realistic noise model, I’ve time for neither of these ATM.
Dr. Jay Cadbury, phd. (Comment #80733)
A real scientist (or an intelligent 6th grader) would know that adding energy to an ice-water mix doesn’t cause temperature change until all the ice is melted.
Are KAP, Jay and Arfur the same person?
In terms of temperatures, we are right at the point now where Arctic air temperatures are switching from slightly positive (+1C to +2C) to slightly negative (-1C to -2C).
The ice melt slows down from now on as the negative air temperatures drop the sea surface temperature into the -2.0C range which usually happens on September 12th.
This is the day that mid-latitude and high-latitude ocean temperatures peak (versus the land temperatures which peak on about July 25th).
The Arctic ocean bouys were recording +1C yesterday, -1C today. It is a pretty good indicator.
http://imb.crrel.usace.army.mil/newdata.htm
Dr. Jay and Arfur,
The Arctic sea ice extent has been measured by satellite since ca 1979 (http://chartsgraphs.files.wordpress.com/2010/01/nsidc_sie_trends.png), and has been decreasing – and the melting rate is decidedly faster than that predicted by the IPCC (http://nsidc.org/news/images/20070430Figure1.png).
The appropriate temperature record, matching the 1979 to present time frame, and including 4 of the 5 major temperature indices shows an average global temperature change of about 0.5C (http://www.woodfortrees.org/plot/hadcrut3gl/from:1979/offset:-.25/plot/uah/from:1979/plot/rss/from:1979/offset:-.1/plot/gistemp/from:1979/offset:-.34).
Bloody h@ll. That NSIDC graphic is terrible.
I don’t think so. Also, I think Kap is trying to explain Jay’s obvious error.
Carrick– Yes. Why they did the funky rotating the horizontal axis off the graph, I don’t know.
Owen– Yes. people have been known the models were poor at predicting ice loss for a long time. I think even before the IPCC published the AR4. It’s just one of the things the models are no good at.
I’m not sure why they don’t use the anomaly method for ice the way they do for temperatures. (Mind you, the models would still be bad at predicting the ice. But I still don’t understand why they use anomalies for one and absolute levels for the other.)
Andrea.
According to the paper TRACE amounts of ammonia are required to see the effect. As little as 1 in 30billion particles. However, I have listened to skeptics preach that trace amounts of c02 can have no effect, because they are… well.. just trace amounts. therefore, the Cern experiment is BS because it proves that a trace amount of ammonia is require to see this effect. And we all know that trace amounts could never make a difference.
( side bet, how many people will get this?)
Thanks Lucia. I’m afraid I can’t even read Jay’s garbage anymore, it’s that bad. So I wasn’t sure if KAP was agreeing, disagreeing or something else.
I think the baseline is wrong in that funky graphic, or maybe it’s a problem with my understanding. AFAIK, they don’t actually predict the “real” amount of ice in the Arctic with the climate models, right?
If so, I’d say they need to scale the blue line so it agrees with the red line from say 1972 to 1980. (Also, most of the models don’t show enough cooling during the 1960s, so it’s plausible that they would underestimate the amount of ice present during that generally cooling period.)
With that funked up rotation, it’s nearly impossible to picture how the agreement with the curves would change if you did a bit of rescaling….
Carrick– I don’t know if they predict the “real” amount of ice. But I assume if they are predicting at all, they predict “real-ish” and not anomalies. The models predict temperature in K, not anomaly.
The funked up rotation makes it impossible to read the graph. You can see the red is outside the spread. That’s about it.
Lucia: these look like yearly temperatures (clearly intended for vulgarization purposes rather than academic presentation), so using anomalies would only shift the whole curve up or down without affecting its shape (right?)
.
Also… if some models over-predict temperatures and under-predict ice loss… could there be a causal link between the two? As in, the heat that causes the excess warming in the poorer models has actually been used up into melting more ice in the real world? (Not sure if the orders of magnitude match though)
Lucia,
I must be missing something. Are you really “claiming that global warming is causing the ice melt”, as Dr. Jay asserts?
Even if you were, would N.Pole temperature anomalies not be a more appropriate measure than global temperature anomalies for identifying a cause?
Also, if the IPCC don’t predict the real amount of sea ice, where do the figures shown in the NSIDC graph come from?
By the way, the global HadCRUT3 figure has been published for July and is 0.459c, compared to 0.425c last month.
Ray–
I do happen to think the change in atmospheric radiative properties is likely contributing to the melt. However, the Jay is getting a little carried away because I haven’t made any claim whatsoever about the proportion of natural variability and AGW affecting the ice melt. Also, with respect to the betting: It’s just betting and observing.
Jay/Shoos is the one demanding temperatures. I have no idea what temperatures would be relevant to whatever theory he ascribes to me.
I said I assume the IPCC predicts ice in area. But, that graph didn’t appear in AR4 so there is no reason to attribute it to the IPCC. The IPCC doesn’t run the models, and those predictions they make are based on things done by others. As far as I am aware, the IPCC didn’t make specific detailed forecasts for ice area. (I think they may say when it will be icefree but I don’t think that figure is in the AR4. That said…. I don’t actually know. I don’t read the ice bits much.)
Speculating, this may be because it as obvious the models don’t predict ice area melt well and were already way off in 2007 when the IPCC was making forecasts. But that’s speculating. But as far as I am aware the IPCC didn’t forecast the ice ares.
I’ve been so distracted by ice! I’m supposed to get an alert on when CRU posts. I hadn’t seen it yet! Thanks.
Re: Carrick (Aug 24 15:17),
Mm2 is correct. The unit is square megameters. The prefix is part of the unit so it’s μm², cm², km² and Mm². Multiple prefixes may not be used in SI units. I went through this with Phil a few years back.
This is why I probably would not post on this site again See above
Okay well I guess I’m satisified then. Lucia I thought you were attributing the ice loss solely to global warming. Stay tuned everyone, the good doctor is diligently searching for something new to complain about.
Sure. The causal link could be some parameterizations are wrong. There could be others.
But the difficulties may not be strongly linked. The main problem for ice may be that the models don’t properly account for ice movement.
DeWitt, I’m aware of course about not adding multiple prefixes (I was just being lazy and not typing out “million”).
You mean (million m)^2 = 1 million km^2, which is how most of the graphs I see display it. Took me a second.
Lucia,
The models may not properly account for ice movement! Well do they ‘properly account’ for anything across the whole field of climate change?
My understanding is an emphatic NO, and it is about time climate scientists were open and transparent about this.
Carrick,
The CT area minimum does show a change starting in 2007compared to the 1979-2006 linear trend. 2011 is looking like another point greater than 4x the standard error of the fit below the 1979-2006 linear trend. It’s too early to tell, though, whether there’s a step change and a new trend or a step change and a resumption of the previous trend.
Owen and KAP,
Is it Owen’s assertion that the average 0.5 C rise in temperature since 1979 is the energy which has been added to KAP’s ‘ice/water mix’ in order to ‘melt all the ice’, until which the temperature won’t change?
.
In which case, could one of you tell me how long it would take to melt ‘all the ice’ in the Arctic?
.
Just curious.
Arfur,
The energy used in the phase change is additional to the heat imbalance causing delta T of 0.5C.
Lucia, I think you missed the point of the Flash Melt event; the point is that over 120k sq km of ice extent were lost in a relatively small area (two regions; the Beaufort and the Chukchi). The other regions gained over 20k in ice extent that day. Also, please note, tht these IJIS numbers are two day averaged, so the overnight loss in extent due to the storm in the Beaufort could much higher than 120k. One quadrangle (150W to 165W between 75N and 80N) seems to lose 50k sq km overnight.
This was an extraordinary event, that required a massive heat transfer rate to melt that much ice; so at first, many comments at Neven’s blog questioned whether this ice melt rate was possible. I was one who felt it wasn’t, but the final results show that the event happened, and the ice did melt out that fast.
Unfortunately, your post doesn’t come close to capturing the unique circumstances and results of this “flash melt” event.
Paul K2–
Was that “the point”? You claim the event was extraordinary. I’ve seen absolutely no evidence it was extra-ordinary.
Ice extend has disappeared that fast — and at this time of year. That’s clear from comparing to past melts. You can claim there were “unique circumstances” to capture, but it would be nice if you found even one “unique” thing about the recent melt and showed it was unique in any meaningful way.
As far as I can tell, the only “unique” thing is that a bunch of guys who are unfamiliar with what’s happened in the past were looking at graphs and making wide claims in all sorts of direction.
Owen #80752,
Fair enough, the loss of Arctic sea ice is faster than what the IPCC (AR4) projected.
Still, I wonder about if a) you think this difference is significant, and b) if you think the shortfall in the IPCC projection of ~0.2C warming per decade (it is in fact closer to half that) is equally significant. There is no doubt that warming causes ice to melt. There is also little doubt that the details of what controls sea ice melt rate and surface temperature changes are complex and far from clearly understood. I urge great caution in assigning significance to all manner of climactic data where there is not a large existing data base to use as a basis of comparison.
If observations fall outside the forecast range of the models then it seems the only safe conclusion to come to is that the models are not doing their job. It doesn’t really matter if the observations are above or below the line the fact is future model predictions look somewhat suspect.
DeWitt, yes that was the change I was noticing.
It is visible in the anomaly data too, as a left-over annual fluctuation,
ATMOS version
this is over perhaps 60 data points, so there really isn’t any question that some sort of “state change” has occurred.
What’s the link you use for sea ice area, by the way?
Lucia, you replied with such a great comment, it bears repeating:
Paul K2–
Was that “the point� You claim the event was extraordinary. I’ve seen absolutely no evidence it was extra-ordinary.
Well, I tried to point out that to look for the impact of a storm in the Beaufort and Chukchi, one really needs to look for the regional impact on the ice extent where the storm was, not over the entire Arctic. I stand corrected (why I was wrong I don’t know, but I will let you bury this point).
My comment discussed the heat transfer rate needed to melt out that much ice overnight, and I felt the required heat transfer (about 2000 W/sq meter ice loss) was too high and thus felt the melt result was impossible. Regarding the possibility, I admitted that “I was one who felt it wasn’t, but the final results show that the event happened, and the ice did melt out that fast.”
Your reply:
Ice extend has disappeared that fast — and at this time of year. That’s clear from comparing to past melts. You can claim there were “unique circumstances†to capture, but it would be nice if you found even one “unique†thing about the recent melt and showed it was unique in any meaningful way.
Again, there is nothing in this post looking at regional extent losses, so I don’t know how you drew this conclusion.
Then you closed with this zinger:
As far as I can tell, the only “unique†thing is that a bunch of guys who are unfamiliar with what’s happened in the past were looking at graphs and making wide claims in all sorts of direction.
In my experience, I have often encountered that “unique” thing on this site, so much so, that it seems to be commonplace. Such it is with the internet.
However, the relevant information is still there, for someone who wishes to accurately interpret the analysis and conclusions. You haven’t presented any information here that shows the extensive loss of over 120k sq km of ice extent in a small region, with the ice edge receding over 100 km in a single night, as commonplace in the Arctic Ocean. In the Hudson’s Bay, or some of the southern regions during July, it is possible, and your data might catch that, but overnight in the Beaufort and Chukchi in late August, you don’t show any data here relevant to that issue.
You completely missed the point of Neven’s post.
Here is my original comment from Neven’s blog, pointing out how high the heat transfer rate had to be, to melt out the ice that fast:
Ian and Chris, just to give you an idea of the heat transfer rate needed to melt out 30 cm (one foot) and 60 cm (two feet) in 12 hours: For each square meter of ice, the 30 cm melt loss is about 300 kg of ice, which at 334 kJ/kg latent heat, needs a heat transfer rate of 2320 watts per square meter for 12 hours. For 60 cm (two feet) of ice melt, the heat transfer rate is twice that. For comparison, the heat transfer rate would be about 8x to 16x a reasonable Arctic summer surface solar insolation rate of 300 w/sq meter.
Even if the melt took 24 hours, the heat transfer rate required is 1160 watts to 2320 watts per square meter to take out ice this fast; which is an impressive heat transfer rate. The 100,000 kJ transferred in these 12-24 hours in order to melt 30 cm, would be enough to raise the water under the ice one degree C to a depth of 25 meters! (It takes about 4000 kJ to raise one cubic meter of water one deg C). To melt 60 cm, the water is raised one degree to 50 meters. To do that over an area of approximately 100,000 square km is very, very impressive; perhaps too impressive! On this issue, call me a skeptic.
Commented 3 days ago on SIE 2011 update 17: unfulfilled potential at Arctic Sea Ice
Steve Fitzpatrick (Comment #80787)
August 25th, 2011 at 6:50 pm
“Still, I wonder about if a) you think this difference is significant, and b) if you think the shortfall in the IPCC projection of ~0.2C warming per decade (it is in fact closer to half that) is equally significant. ”
—————————————-
The climate system appears to be incredibly complex, and I am not surprised the IPCC is off on the sea ice projections nor am I surprised that they are off on the warming rate. I did not really expect them to be perfect at this early stage of climate science. I do expect that models will get much better as we go forward.
Nonetheless, I am surprised to see such a dramatic change in sea ice (and in the Greenland ice pack) in such a very short time. Dramatic is hardly the word. The lesson that I am beginning to take from this is that it is dangerous to minimize the impact of even small global temperature changes. My big concern, and I admit that I am a worrier, is the impact of even a 1C change on global agriculture. The speed of the present climate change may leave insufficient time for human assisted adaptation.
PaulK2–
You seem to be under the impression that “the point” of a Neven’s post with numerous comments by many people is whatever you were thinking and saying at the time — quoting yourself to prove what “the point” was. That’s an odd point of view.
Also, I don’t know why you are complaining that I missed the point of Neven’s post. I said it was worth reading. I also commented on the tone in comments etc. The tone in comments is not “the point” of Neven’s post.
There is no evidence anything that happened was extra ordinary. If you have it supply it.
I found the link I was looking for. I believe it’s this one (which is up to date in spite of the title.)
Oddly I didn’t find it on cyrosphere, but on Neven’s excellent reference page. Good show Neven, ching!
lucia, I thought I just did, but I guess I should just let the ice do the talking. Right now its screaming to people who follow the Arctic ice.
Bye for now, see you again when the August UAH anomaly report comes out.
Paul K2–
I’m seeing things like you though it was impossible but it happened. You estimate a certain heat transfer rate, which you don’t put in context of any that might happen when ice is in water in the arctic. Then you decree that you think this is impressive. I don’t see how this is evidence of anything extra ordinary. As in: It’s not evidence this isn’t something of an event that one would expect to witness when one is watching the ice melting for months at a time.
If we put the available extent loss statistics in context of what has happened before, the extent loss isn’t even extra ordinary for the specific day. That extent loss rate has been exceeded on a “matching days” in 2 years since 1972 and 1 since 1979. So, it was a fast melt day– but it wouldn’t even be outside the ±95% confidence intervals if it was a day picked at random as a sample of what’s happening.
As for focusing on an area: If you are going to claim that is extra ordinary, you are going to have to dredge up sub-areas and see if this melt was somehow remarkable for sub-areas– preferably doing that without weird cherry picking. You haven’t done that.
All I see in all your ramblings above is evidence that if you don’t know what has happened historically, you can get all excited by seeing something that is new to you, but not necessarily all that remarkable.
Re: Carrick (Aug 25 20:34),
The date range refers to the period used for calculating anomalies. Previously it was 1979-2000. If you delete the .1979-2008 from the URL you get the data with the anomalies calculated from the 1979-2000 average. William Chapman gave me the links a while back. I’m betting that Neven got them from one of my posts. CT has Antarctic ice area and global ice area archives as well.
Re: Paul K2 (Aug 25 20:44),
Ice doesn’t have to melt, it just has to be dispersed to below 15% concentration in a given pixel. A storm will do that. Especially if the ice concentration was low to start with.
DeWitt Payne: First, it wasn’t that low to begin with, likely at least 50% average ice concentration, and perhaps over 60%.
Secondly, the USS Healy sailed right up the middle of the area that melted out the day right after this melt out. You can look at the Healy hourly photos and judge for yourself. The Healy position is shown on each photo, and the quadrangle that had the greatest ice pack loss is 150W to 165W from 75N to 80N. The ice retreated over 100 km overnight in this quadrangle back to about the 78N latitude.
Let me know how many photos you see that showed the missing ice.
I should suggest starting with this photo marked 20110822-0501 which apparently was taken at 5:01 AM on August 22nd.
Enjoy watching the current state of the Arctic ice; like they say, a picture is worth a thousand words.
Lucia,
echo chambers breed certain forms of thinking and rhetoric that dont survive in an environment where beliefs are challenged. K2 likes his echo chamber.
K2. You miss dewitts point. Not surprising. If you spend all your time talking with people who agree with your way of seeing things, this will happen to you repeatedly. It’s why your mom suggested that you go outside and play
PaulK2–
Some pictures are worth a thousand words, and some require words to make any point. I clicked several pictures near “this photo marked 20110822-0501”. What I see is a ship whose latitude and longitude were changing and which very little ice in the specific photo you marked, but saw more ice in other locations.
I have no idea what message you think this is supposed to convey. In the context of previous discussions of ice melting in one day, unless an eager beaver– possibly you– goes to the trouble to go through all the pictures time stamps etc. and explains how they think these images demonstrate whatever it is you are claiming, right now I don’t see this as any evidence of an extra-ordinary amount of ice melting on that one particular day.
For example: I could drive around town, show pictures of shopping mall followed by corn fields. This would not be evidence that the shopping malls vanished and were quickly replaced by corn fields.
Similarly, I can take pictures of a park full of people, and come back 2 hours later and find no people. This doesn’t mean all the people died and were carried away. They might have just gone elsewhere. That’s what “dispersed” can mean.
Paul_K2,
Try this sequence of satellite maps:
8/21/11
8/22/11
8/23/11
There may have been some dispersion, but it looks like mostly wind and current driven movement to me. You can also lose extent when dispersed ice becomes more compact. Note the change in color of the main ice pack from grayish to solid white between 8/21/11 and 8/22/11. Obviously there was also considerable melting as CT shows a loss in are over two days of 0.173 Mm². But the loss in area on 8/14/2007 was greater than that at -0.177 Mm². That sort of thing happens this time of year. Given that this year the ice is more dispersed than normal, I would expect more of the same. Big jumps up also happen this time of year. 8/24/2007 had an increase of 0.129 Mm² followed by a drop of -0.097 Mm² the next day.
Now that CT area has increased by 0.14 Mm² in two days, do you suppose Neven is talking about flash freezing?
DeWitt–
I’ll be surprised if Neven starts talking about flash freezing. Still, I haven’t reading that blog very long, so you never know. 🙂
deWitt, Neven’s crowd is funny. Especially Paul K. I dont think they like to be challenged or questioned. Somebody linked to goddard in his comment and the reaction was funny.. AHHHH dont link to Goddard, you go blind!
More melting – 59 Mm2 today, 100 yesterday (JAXA extent). Now only 131 behind 2007, which actually added ice in the next two days. I think the horse race is entering the straight…
Shoot! I just ran my figures. Did they update while I’m writing?
Well.. the post is going to use the nearly 100 yesterday!
Nick–Ok. I misunderstood, Where is the 59Mm2 melting from?
I put up exploded graphs for the area. I’d be surprised if we don’t set an area minimum, but I didn’t catch that last bit. Dang CT updates while I’m writing!!
Lucia,
From Jaxa:
The latest value : 4,737,969 km2 (August 31, 2011)
But I don’t think it invalidates anything you wrote. It does create an interesting situation, though. The last three days have been in the 59-100 range. 2007 is 131 Mm2 ahead, but for the next two days actually added ice. So 2011 could catch up.
I found it. It tweaks my numbers and the front runner. :).
One of the reasons I liked 7 day average is it changed so little on the update. But using 7 day average this close can lead to some weirdness. It’s nice to not have the current days values inside the 95% confidence intervals. (Though, oddly, they are starting to belong there based on data. After all: we are predicting 7 day minima and we are going to start having single days that fall below the 7 day minimum average. Negative ‘loss’ rates defined as “todays extent – min. 7 day avearge” have happened this early. Only once. But still.