The 2015 melting season

[Pmt111500]

I was so totally expecting to see rounded floes all over the Arctic Ocean by this time. Agree that this is not the 'Year of the Big Melt', what ever happens from here till September. CAB is resisting the inevitable and possibly the constant flow of air from Pacific to Northern Europe packs the remaining rotten ice against the weakened NA drift. Weather during 1987 or 1997 comes to mind wrt to northern Europe.

[JayW]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

[seaicesailor]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

One pic worth 1000 numbers.

[seaicesailor]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Actually this CT comparison reminds me of those projections based on snow cover earlier in the season

[JayW]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Actually this CT comparison reminds me of those projections based on snow cover earlier in the season

Agreed, ultimately I guess it comes down to the weather, but it sure seems like things have softened up. 

2015D


I keep wondering what would happen if we saw a cyclone like the early season one, what that would do to this ice pack?

From Jim Hunt's post on June 6

[ChrisReynolds]

Having twisted my ankle and being off work as a result, I have some free time...

Taking Arctic Ocean extent data, where my definition of Arctic Ocean includes CAA, Greenland Sea, Barents, Kara - a choice made to get a dataset that represents conditions for the regions that set the minimum. I have tabulated day to day losses for 18 July to 15 September for each year 2007 to 2014. This data is then used to do a monte carlo estimate of the probability distribution for the 2015 minimum.

The code written does one million runs. In each run the 18 July 2015 extent is used as the start extent, and for each day a daily loss is chosen at random from the available 8 year dataset. These losses are summed and applied to the 18 July 2015 extent to create a simulated extent for 15 September 2015. The resulting 1,000,000 extent values are then combined in a histogram and normalised to 1 to produce a probability distribution.



92% of the probability lies between 4 and 5 million kmsq.

The peak probability is at 4.5 million kmsq.

EDIT - I used 18 July, the latest date I have in my spreadsheet, not 15 July as originally stated.

[plinius]

Indeed. The "experience" values are based on high ice coverage. There, the temperatures start falling in August because of the high albedo. However, looking into the Beaufort for example, the coverage is rapidly declining. This offsets the equilibrium and we will see such regions to display continued melt well into September...

[Nightvid Cole]

Having twisted my ankle and being off work as a result, I have some free time...

Taking Arctic Ocean extent data, where my definition of Arctic Ocean includes CAA, Greenland Sea, Barents, Kara - a choice made to get a dataset that represents conditions for the regions that set the minimum. I have tabulated day to day losses for 15 July to 15 September for each year 2007 to 2014. This data is then used to do a monte carlo estimate of the probability distribution for the 2015 minimum.

The code written does one million runs. In each run the 15 July 2015 extent is used as the start extent, and for each day a daily loss is chosen at random from the available 8 year dataset. These losses are summed and applied to the 15 July 2015 extent to create a simulated extent for 15 September 2015. The resulting 1,000,000 extent values are then combined in a histogram and normalised to 1 to produce a probability distribution.



92% of the probability lies between 4 and 5 million kmsq.

The peak probability is at 4.5 million kmsq.

Could you do a similar one for CT area?

[Nightvid Cole]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Santa must have decided to re-paint his house (the Pole Hole is a new color...) 

[Gray-Wolf]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Surely there's something amiss with that current image???

 Even 2012 had some 100% cover in the central basin on the 17th???

[ktonine]

It was 2015 +/-3 years wasn't it? Let's just see what happens over the next three years. 

If you're referring to Maslowski's model, it's 2016 +/- 3 yrs.

Frankly I don't know whether it's that or the calculation based on PIOMAS, which I think Wipneus has done. Sorry to be vague on this but as I have never been impressed I have never paid much attention.

EDIT - I do have in my mind 2015 though, that has come from somewhere.

Maslowski made his prediction for a nearly ice-free arctic in 2010.  It was 2016 +/- 3 years.

But people forget (or never realized) that Maslowski's prediction was NOT for < 1Mkm^2 extent, but for *volume*.  His definition of 'nearly ice free' was for *volume* to realize more than an 80% drop from the 1979-2000  summer volume baseline.  By that criteria 2012 came very close - with a 76% decline in volume from the baseline.

For Maslowski's prediction to become true, then we would have to see a 16% reduction in the 2012 volume sometime in the next 4 years.

See more in the Comments on Chris' Dosbat post, Go on, say something outrageous...

[vigilius]

The link to obuoy/datatransport has been down pretty much all weekend, does anyone know what's up? (I have been anxiously following the adventures of obuoy #9 as it approaches that conspicuous patch of open water off the northeast of Greenland and am on tenterhooks.) Anyway, just a lurker, you people keep up the good work, I am following every word.

[Greenbelt]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Surely there's something amiss with that current image???

 Even 2012 had some 100% cover in the central basin on the 17th???

Notice the change over only 4 days.  Seems unlikely to me.
http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=13&sy=2015

[Greenbelt]

[Jim Hunt]

Moving on through the list of Ice Mass Balance Buoys, 2014F, 2015A, 2015B and 2015E are already floating in their drill holes if not free of all encumbering ice. From those that remain, here's the temperature profile for 2014I, currently located at 76.04 N, 139.10 W and with a "pinger" based thickness of 130 cm:

http://GreatWhiteCon.info/resources/ice-mass-balance-buoys/summer-2015-imbs/#2014I-Temp

[jdallen]

Having twisted my ankle and being off work as a result, I have some free time...

Taking Arctic Ocean extent data, where my definition of Arctic Ocean includes CAA, Greenland Sea, Barents, Kara - a choice made to get a dataset that represents conditions for the regions that set the minimum. I have tabulated day to day losses for 18 July to 15 September for each year 2007 to 2014. This data is then used to do a monte carlo estimate of the probability distribution for the 2015 minimum.

The code written does one million runs. In each run the 18 July 2015 extent is used as the start extent, and for each day a daily loss is chosen at random from the available 8 year dataset. These losses are summed and applied to the 18 July 2015 extent to create a simulated extent for 15 September 2015. The resulting 1,000,000 extent values are then combined in a histogram and normalised to 1 to produce a probability distribution.



92% of the probability lies between 4 and 5 million kmsq.

The peak probability is at 4.5 million kmsq.

EDIT - I used 18 July, the latest date I have in my spreadsheet, not 15 July as originally stated.

My own less sophisticated analysis is very close to yours.

Edit: my midpoint was 4.57 million.

[ChrisReynolds]

Could you do a similar one for CT area?

Done.

I slipped up in my original posting, the monte carlo is done for data from 18 July not 15 July as originally stated above, I have done the CTArea monte carlo from 18 July as well.



96% lies between 2.5 and 3.7M km^2.

The peak is at 3.1M km^2.

[jplotinus]

Flash melt in Kimmirut today.  Pics are 4 hours apart (7:30am - 11:30am):

[ChrisReynolds]

JD Allen,

I threw a bucket of techniques at the problem this afternoon, but only in terms of NSIDC extent (monthly or daily), all got ranges covering 4 to 5 million kmsq (M km^2).

The monte carlo method may be a more complex technique, but that doesn't mean it is better. A problem is that each year's profile of melt is from a given initial ice/ocean state, mixing up individual years ignores such effect of initial conditions. However what it may be worth doing for is to sort out the impact of weather, as it effectively muddles up all of the possible weather effects from 2007 to 2014. The top end of the distribution of extents (or CT Areas) probably reflects a year like 2013, the bottom end reflects years like 2007 and 2012.

My prediction for SIPN was 5.15M km^2 +/- 0.64M km^2 based on April PIOMAS data, I intend to leave that for the season, as it is merely a test of initial thickness. But SIPN will add a qualification statement in July and August to it to the effect that my expectation given events since April is now for the bottom half of that range, roughly 5 to 4.5, or a low end fail of the prediction. This NSIDC extent monte carlo is for 15 September, but it is reasonable to take it as a ball park estimate of 4 to 5, which suggests I still have a 50/50 chance of success.

I can't wait to find out what happens, part of me would like my SIPN prediction to be successful, but most of me is hoping my April PIOMAS volume SIPN prediction fails and we see something between 4 to 4.5 million for September extent, because it will really piss off the denialists. 

[jdallen]

Could you do a similar one for CT area?

Done.

I slipped up in my original posting, the monte carlo is done for data from 18 July not 15 July as originally stated above, I have done the CTArea monte carlo from 18 July as well.



96% lies between 2.5 and 3.7M km^2.

The peak is at 3.1M km^2.

Intriguing possibility inside the 96% envelope - 2015 passes 2012 in area, but remains higher in extent.  Considering the quality of 2015s ice, more probable than the other way round.

[Paddy]

Personally, I'm not ruling anything out.

http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=17&sy=2012

Surely there's something amiss with that current image???

 Even 2012 had some 100% cover in the central basin on the 17th???

Notice the change over only 4 days.  Seems unlikely to me.
http://igloo.atmos.uiuc.edu/cgi-bin/test/print.sh?fm=07&fd=17&fy=2015&sm=07&sd=13&sy=2015

Seems unlikely to me too, especially since it's very much at odds with the concentration maps that Slow Wing posted about earlier.

Hamburg has updated and we can now do the 'July 19' sea ice area & concentration comparison by years on the excellent display set up by Neven:

https://sites.google.com/site/arcticseaicegraphs/concentration-maps/sic0719


On this comparison, 2015 is looking way ahead of both 2013 and 2014 and somewhat closer to most or all of the preceding years within 2007-12.

[ChrisReynolds]

JD Allen,

Not sure that NSIDC extent and CT Area are directly comparable in that way. In any case. I don't have Arctic Ocean data for CT Area, so that is for all NH, whereas my original Extent was for the Arctic Ocean. I don't think that would matter though, as I include the CAA, Greenland and Barents, aside from Baffin, where would other ice hide after 2007?

[OSweetMrMath]

Taking Arctic Ocean extent data, where my definition of Arctic Ocean includes CAA, Greenland Sea, Barents, Kara - a choice made to get a dataset that represents conditions for the regions that set the minimum. I have tabulated day to day losses for 18 July to 15 September for each year 2007 to 2014. This data is then used to do a monte carlo estimate of the probability distribution for the 2015 minimum.

Interesting. Nice demonstration of the Central Limit Theorem.

I have one criticism and one methodology question.

Criticism: since you haven't said otherwise, I assume you are ignoring day-to-day autocorrelations in extent changes. (That is, you are independently sampling each day's loss, rather than some conditional structure.) Over the period you analyze, if autocorrelations exist they are likely to cause the distribution to have substantially heavier tails.

One way to check for this is to create a histogram (or better, a smoothed density estimate) of the observed changes you are basing this on (compute the extent on September 15th minus the extent on July 18th for each year and use the resulting 35 or so data points). If there are autocorrelations, you should be able to observe the heavy tails in the histogram.

Worse, to the extent that there are autocorrelations between the data in the period you are working with and earlier periods, this is likely to substantially change the mean of the distribution. Even autocorrelations which do not extend more than a week could easily change the mean by 100 thousand sq km or more.

On methodology, when you say you choose a daily loss at random, what do you mean? For example, for the loss on July 20th, do you randomly choose from all observed daily losses? Or do you choose from all losses on July 20th on any year? This is unlikely to substantially effect your results, thanks to the central limit theorem, but the second method is better. The loss distribution in July is obviously different than the loss distribution in September.

Edit: It doesn't feel worth a new post to say that I missed that you were relying on recent data only, 2007 to 2014. That's not enough data to meaningfully test for heavy tailed distributions, so disregard my comments on that point. The general point about autocorrelation still stands.

[jdallen]

JD Allen,

Not sure that NSIDC extent and CT Area are directly comparable in that way. In any case. I don't have Arctic Ocean data for CT Area, so that is for all NH, whereas my original Extent was for the Arctic Ocean. I don't think that would matter though, as I include the CAA, Greenland and Barents, aside from Baffin, where would other ice hide after 2007?

Does make does make direct comparison problematic.  And yes indeed... For the ice, "no rock, no hiding place..."

[Jim Hunt]

The camera on O-Buoy 10 has burst back into life after weeks of being stuck showing an image from June 12th, so here's the latest view together with the temperature profiles for the nearby IMB 2013F:

http://GreatWhiteCon.info/resources/ice-mass-balance-buoys/summer-2015-imbs/#2013F

P.S. And a new image just arrived revealing a second buoy once again!
P.P.S. And yet another new image, perhaps revealing a third buoy?

[seaicesailor]

2013F is kind of relevant being survived winter and started this season with thicker ice over 2 m. So Jim please how do you read the profile? What exactly is ice there and what is not? Thank you!

[jai mitchell]

92% of the probability lies between 4 and 5 million kmsq.

The peak probability is at 4.5 million kmsq.

EDIT - I used 18 July, the latest date I have in my spreadsheet, not 15 July as originally stated.

Chris,

can you add a 1-sigma uncertainty distribution to this curve?  I would be very curious to see what you come up with.

[Nick_Naylor]

Could you do a similar one for CT area?

Done.

I slipped up in my original posting, the monte carlo is done for data from 18 July not 15 July as originally stated above, I have done the CTArea monte carlo from 18 July as well.



96% lies between 2.5 and 3.7M km^2.

The peak is at 3.1M km^2.

Chris,
It would be very interesting to see the probability distribution for 2012, using July 18 2012 initial conditions and the same methodology.

[seaicesailor]

The camera on O-Buoy 10 has burst back into life after weeks of being stuck showing an image from June 12th, so here's the latest view together with the temperature profiles for the nearby IMB 2013F:

http://GreatWhiteCon.info/resources/ice-mass-balance-buoys/summer-2015-imbs/#2013F

P.S. And a new image just arrived revealing a second buoy once again!
P.P.S. And yet another new image, perhaps revealing a third buoy?

The camera is floating around

[Neven]

It's starting to sound as if a separate probability distribution thread might be in order. 

[Nick_Naylor]

Criticism: since you haven't said otherwise, I assume you are ignoring day-to-day autocorrelations in extent changes. (That is, you are independently sampling each day's loss, rather than some conditional structure.) Over the period you analyze, if autocorrelations exist they are likely to cause the distribution to have substantially heavier tails.

There could be (and probably are) competing autocorrelations.
- Daily measurement uncertainties appear to exaggerate day-to-day melt, such that negative melt on one day is very likely to be followed by heavier than usual melt on the following day. This effect could be reduced substantially by using two or three day periods instead of daily values.
- Some years, like 2012, have higher than median melt rates on lots of days. The probability of four consecutive days in the top quartile is much higher during such a year than 1 in 16. I suspect that running this type of analysis would indicate almost no probability of a year like 2012 - even using years 2007-2012 as the only years in the analysis.

[Jim Hunt]

What exactly is ice there and what is not? Thank you!

Well, starting from the right the ocean is at around -1.2 °C. There's a warm freshwater "lens" that's confusing the bottom sounder between thermistors 27 and 22, and possibly a couple more. The core of what's left of the floe is at -0.5 °C at thermistor 17. Starting from the left hand side thermistors 1-7 are in air. Going back to mid winter the ice surface looked to be between 5 and 6. The top sounder's showing surface melt of 23 cm, which again suggests the surface of a melt pond between thermistors 8 & 9. The bottom of the melt pond could well be between 12 & 13, which would mean there is in actual fact less than a meter of pretty warm ice left, despite the headline number of 211 cm!

[Jim Hunt]

The camera is floating around

Quite so. Here's azimuth over the last week:

[seaicesailor]

What exactly is ice there and what is not? Thank you!

Well, starting from the right the ocean is at around -1.2 °C. There's a warm freshwater "lens" that's confusing the bottom sounder between thermistors 27 and 22, and possibly a couple more. The core of what's left of the floe is at -0.5 °C at thermistor 17. Starting from the left hand side thermistors 1-7 are in air. Going back to mid winter the ice surface looked to be between 5 and 6. The top sounder's showing surface melt of 23 cm, which again suggests the surface of a melt pond between thermistors 8 & 9. The bottom of the melt pond could well be between 12 & 13, which would mean there is in actual fact less than a meter of pretty warm ice left, despite the headline number of 211 cm!

Thanks! It was too twisted, compared to other profiles.
This one seems to go away soon too.
The CT area map is really scary. Anything can happen (even staying at or above 2014, but that'd be a 2-sigma plus outlier as shown today)

[Nick_Naylor]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

[jdallen]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

<laughs> 
OK, unlikely, but not impossible.

In fact, we'll see if the condition of the ice takes us there.  I will grant, it may, but I consider it improbable (less than 5%).

Yah, Neven, we may need a probability distribution thread

-J

[Shared Humanity]

I think what you are,seeing is widespread melt ponding.

[ChrisReynolds]

No seperate thread needed, I don't think there's a great deal more to say...

Nick,

2012, or any other year, would just be a shift in the distribution. In practice the curves change slightly because even with 1,000,000 iterations the results haven't converged totally between runs. With 100,000 runs the standard deviation of the average for each run is around 0.001, 1,000,000 should be good enough.

I have attached a plot of 2012 and 2015 start extent for the 18 July.

You are right about the probability for 2012, see my comment below to OSMM. The probability for the 2015 start extent is 0.012%, for the 2012 start extent it is 0.082%.

OSMM,

For each day there are 8 possible losses from years 2007 to 2014, increment day through 18 July to 15 Sept and randomly select one loss from the 8 losses for that day.

I can't add anything more to what Nick has said about autocorrelation. I think the major issue here however is not autocorrelation but dependence on initial conditions. 2012 appears to be a very unlikely event with this monte carlo approach. In reality it was not. Initial (April) volume (or thickness) provided conditions conducive to high loss due to extensive thin ice and a low export from the central arctic of MYI. This manifested as very low compactness by July, which in a different approach could be used to add priming information to a prediction. However this information, which suggested strong August losses was not available in the monte carlo approach, as I have implmented it. So it gives an unrealistically low probability of the 2012 minimum.

Note that in the approach used now I have deliberately chosen Arctic Ocean (which includes CAA, Barents & Greenland Seas), this is because of my reading of ice state in the peripheral seas (Beaufort round to Latpev) which suggests to me that overall extent is giving an inaccurate impression of ice state. Like 2012 I expect above average losses in August due to state in the peripheral seas. However the choice of Arctic Ocean rather than whole Arctic does itself reflect my bias (or prior).

Jai,

The standard deviation of the 1,000,000 'predictions' is 0.308M km^2, which can be applied to the peak value of 4.5. However due to the autocorrelation as mentioned by OSMM using the probabilities normally associated with the standard deviations is not really sound.

[Nightvid Cole]

No seperate thread needed, I don't think there's a great deal more to say...

Nick,

2012, or any other year, would just be a shift in the distribution. In practice the curves change slightly because even with 1,000,000 iterations the results haven't converged totally between runs. With 100,000 runs the standard deviation of the average for each run is around 0.001, 1,000,000 should be good enough.

I have attached a plot of 2012 and 2015 start extent for the 18 July.

You are right about the probability for 2012, see my comment below to OSMM. The probability for the 2015 start extent is 0.012%, for the 2012 start extent it is 0.082%.

OSMM,

For each day there are 8 possible losses from years 2007 to 2014, increment day through 18 July to 15 Sept and randomly select one loss from the 8 losses for that day.

I can't add anything more to what Nick has said about autocorrelation. I think the major issue here however is not autocorrelation but dependence on initial conditions. 2012 appears to be a very unlikely event with this monte carlo approach. In reality it was not. Initial (April) volume (or thickness) provided conditions conducive to high loss due to extensive thin ice and a low export from the central arctic of MYI. This manifested as very low compactness by July, which in a different approach could be used to add priming information to a prediction. However this information, which suggested strong August losses was not available in the monte carlo approach, as I have implmented it. So it gives an unrealistically low probability of the 2012 minimum.

Note that in the approach used now I have deliberately chosen Arctic Ocean (which includes CAA, Barents & Greenland Seas), this is because of my reading of ice state in the peripheral seas (Beaufort round to Latpev) which suggests to me that overall extent is giving an inaccurate impression of ice state. Like 2012 I expect above average losses in August due to state in the peripheral seas. However the choice of Arctic Ocean rather than whole Arctic does itself reflect my bias (or prior).

Jai,

The standard deviation of the 1,000,000 'predictions' is 0.308M km^2, which can be applied to the peak value of 4.5. However due to the autocorrelation as mentioned by OSMM using the probabilities normally associated with the standard deviations is not really sound.

I think Nick was asking about the result you'd get if included only pre-2012 years in computing the distribution for 2012 (i.e. forecast, not hindcast).

[ChrisReynolds]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

Again, here I rely on wider data. The Drift Age Model and ASCAT show that this year has more multi year ice than 2012 had in Beaufort and behind Chukchi. I wouldn't rule out a re-run of 2012, but I think it's a low likelihood.

ftp://ccar.colorado.edu/pub/tschudi/iceage/gifs/
(Week 27)

And in ASCAT, e.g. Day 100 of 2012 and 2015.
http://manati.star.nesdis.noaa.gov/ascat_images/ice_image/
ASCAT shows multi year ice as brighter than the first year ice growth.

[ChrisReynolds]

I think Nick was asking about the result you'd get if included only pre-2012 years in computing the distribution for 2012 (i.e. forecast, not hindcast).

I thought that too initially, but it wasn't what was written.

Graph attached. probability of 2012 rises to 0.3% (for the individual date, apply a reaonable range and the probability will increase - any spot figure is rather improbable, some are less improbable than others).

The disrtibution for 2007 to 2012 drops notably, showing the role of 2013 and 2014 in the preceding 2012 and 2015 distributions based on 2007 to 2014 data.

So the graph shows 2007 to 2012 applied to 2015 and 2007 to 2012 applied to 2012.

[Neven]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

Despite the past few weeks, I don't think the lack of preconditioning can be fully compensated, and thus melting momentum will not be sufficient to keep the rate of decrease as high as it has been the past 2 weeks. But we'll see when the weather switches.

If it switches. 

[Bob Wallace]

"No seperate thread needed, I don't think there's a great deal more to say..."

+3 and counting....   

[Nightvid Cole]

I think Nick was asking about the result you'd get if included only pre-2012 years in computing the distribution for 2012 (i.e. forecast, not hindcast).

I thought that too initially, but it wasn't what was written.

Graph attached. probability of 2012 rises to 0.3% (for the individual date, apply a reaonable range and the probability will increase - any spot figure is rather improbable, some are less improbable than others).

The disrtibution for 2007 to 2012 drops notably, showing the role of 2013 and 2014 in the preceding 2012 and 2015 distributions based on 2007 to 2014 data.

So the graph shows 2007 to 2012 applied to 2015 and 2007 to 2012 applied to 2012.

"Pre-2012" would have to be 2007-2011, not 2007-2012 as you show.

[Nightvid Cole]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

Despite the past few weeks, I don't think the lack of preconditioning can be fully compensated, and thus melting momentum will not be sufficient to keep the rate of decrease as high as it has been the past 2 weeks. But we'll see when the weather switches.

If it switches. 

Both GFS and ECMWF are predicting High pressure dominance for a full week....transitioning away from dipole and more towards "centered" High. The latter is the best weather for viewing the ice more-or-less cloudfree. Since clouds interfere so much with observation, even in microwave data, I am very much looking forward to this clear weather spell.

[seaicesailor]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

Despite the past few weeks, I don't think the lack of preconditioning can be fully compensated, and thus melting momentum will not be sufficient to keep the rate of decrease as high as it has been the past 2 weeks. But we'll see when the weather switches.

If it switches. 

I think so as well. also to answer Nick, i meant I feel this year will not be a rebound year anymore (forget linguistics, I mean bye bye 2013 2014) after looking at that map and the nice Montecarlo sims presented today, just as improbable as this year smashing 2012 record. Ok (well, not exactly hehe, 0.01% to being nearly equal to 0.1%, but both very small wrt 100% tbh). But nothing of that still strictly impossible as jdallen says. Lol

[Nightvid Cole]

So what's to keep area from falling as much as 2011 did for the next two weeks, and then as much as 2012 did for the rest of the way? Surely that's not impossible?

Despite the past few weeks, I don't think the lack of preconditioning can be fully compensated, and thus melting momentum will not be sufficient to keep the rate of decrease as high as it has been the past 2 weeks. But we'll see when the weather switches.

If it switches. 

I think so as well. also to answer Nick, i meant I feel this year will not be a rebound year anymore (forget linguistics, I mean bye bye 2013 2014) after looking at that map and the nice Montecarlo sims presented today, just as improbable as this year smashing 2012 record. Ok (well, not exactly hehe, 0.01% to being nearly equal to 0.1%, but both very small wrt 100% tbh). But nothing of that still strictly impossible as jdallen says. Lol

Nothing is truly impossible in a Gaussian distribution. 

[Buddy]

Some people are throwing the "impossible" word around a little too freely.  Something can be very difficult...and very unlikely to happen....but not be impossible.

Getting down to 1 million is VERY...VERY....unlikely.  But it is NOT impossible. 

[Peter Ellis]

Well, with the centre estimate around 4.5 million, then hitting 1 million is about as possible as bottoming out at 8 million.  Sure, it's still technically possible since we're currently at ~8.27 million.  Something might happen to prevent all further melt this summer.  It's possible.  Just... not likely.

[Mark Tough]

I think what you are,seeing is widespread melt ponding.

It's been a while since I posted but lurking as always! The Cryosphere today site was my first portal in to wonders of Arctic Ice and still like to view even though Neven has their graphs and data pretty much covered. The site was down for four days last week, as it has been periodically this year, and came back with these huge changes which I don't believe melt ponding alone can explain.

You may notice that they've also changed their mask and the snow has finally gone - I'd say this mask has also effected the Colour Palate but I may be wrong. An even more dramatic change in four days has been the Antarctic anomaly - now that's a cliff 

http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.recent.antarctic.png

Keep on keeping on everyone - a brilliant site and love all your contributions. I think we'll go low, perhaps third but it's all to play for - however if Cryosphere Today is correct it's a very, very good bet for first.