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Rob Dekker
California
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And also interesting that thin FYI is blamed on "strong divergence and export". Divergence to where ? And export to where ? And how do you know ? As if the record high temperatures during winter had nothing to do with it. Bizarre.
Toggle Commented 8 hours ago on ASI 2016 update 1: both sides at Arctic Sea Ice
Interesting, from the Arcus "Informal Contributions" site : Three long airborne ice thickness surveys were carried out in the Northwest Passage and Canadian Beaufort Sea by York University in early April 2016, and compared to similar surveys performed in late April 2015. Results show that ice thicknesses in the Northwest Passage were similar in both years, although there was less multiyear ice (MYI) in 2016 (Section 2.2). In the Beaufort Sea, the thickness of MYI was similar to 2016 (Section 2.1). However, due to strong divergence and export, first‐year ice (FYI) was much thinner than in 2015, giving rise to expectations of earlier FYI melt and disappearance in 2016 than in 2015. Seems that that (earlier FYI melt) is exactly what has led 2016 to where it is now.
Toggle Commented 9 hours ago on ASI 2016 update 1: both sides at Arctic Sea Ice
Andrew Slater's site is up and running (hat tip to EgalSust and MikeAinOz at the forum). http://cires1.colorado.edu/~aslater/SEAICE/ The projections are impressive and scary : For starters, Dr. Slater projects 7.42 M km^2 by July 15. This is while 2012 at that date was at about 8 M km^2. So he projects that 2016 NOT show any significant 'stall' and will maintain its lead over 2012 (by some 600 k km^2) at least until halfway July.
Toggle Commented yesterday on EGU2016, my impressions at Arctic Sea Ice
Thank you Neven. Very good summary of the unprecedented decline in sea ice going on on two sides of the Arctic. There is a third side that still has instills some hope : The Siberian side. So far, Siberian land snow cover has been holding up (at least better than the American side) and ice in the East Siberian Sea appears to be "average" at least in volume and extent. And the Laptev has been holding up pretty well too. Do you think that this third side of the Arctic will slow down the decline, and possibly prevent the Arctic sea ice from what appears to be an unprecedented collapse this year ?
Toggle Commented yesterday on ASI 2016 update 1: both sides at Arctic Sea Ice
Let me add that luckily there are some clouds appearing over the Beaufort over the past couple of days. Hopefully that will slow down things a little bit.
Toggle Commented 3 days ago on Beaufort final update at Arctic Sea Ice
Neven, The losses in the Beaufort are almost certainly due to melting due to warm (relatively speaking) water. As I reported earlier in this thread, the wide open water area in the Beaufort is absorbing some 50-90 TW. That is enough power to melt out 10,000 - 16,000 km^2 of FYI per day. Now that the winds are blowing a bit, it "stirs the pot" and all that heat is blow into the ice, which then, yes, simply melts. Also note on your animation that the floes that move along the edge of that open water are also disintegrating and melting away, so it is not just that tongue towards the chukchi. All in all, this melting causes the Beaufort to loose some 15,000 km^2 per day over the past couple of days (according to Wipneus' assessment), which is in line with the rate of loss expected given the heat absorbed. Since the Beaufort's open water is now so large, and still growing, the absorbed heat may be enough to melt out the Beaufort entirely under its "own power" so to say. The awesome power of albedo feedback.
Toggle Commented 3 days ago on Beaufort final update at Arctic Sea Ice
Thanks Chris. That makes sense. Regarding your initial findings : Whilst warm air seems to explain a lot of the 2010 to 2012 increased spring volume loss, it doesn't seem to explain much of the rest of the series. that kind of was expected. After all, temperatures in spring only affect melt (melt-ponding) if they are above 0 C. And if they dip below that after a while, ponds freeze over and un-do the melt and the albedo-effect. So there is that non-linear effect of melt-ponds, but beyond that, melt in spring is also affected by open-water close to the ice. Think albedo difference between ice and open water : it warms the water quite nicely, which leads to ice melt later on. And then regarding the "rest of the series" there are a lot of variables that would need to be considered. So I'm not surprised that you conclude : My reading of the evidence suggests that this is far from simple. I couldn't agree more.
Chris, I'm sorry, but I don't understand what you are doing. But please let me know if I can help.
Chris said Anyone know what proportion of variance a given R2 explains? The definition of R^2 is Explained variation / Total variation. So there you have it : If R^2 is 0.9, that means 90% of the variation is explained with this model. However, that does not mean a lot, and there are lots of 'if's and 'but's to that, as Bill's link explains. Personally, I prefer to look at the standard deviation of the residuals. That typically gives a better way to compare models (including comparing to the super-simple ones like a linear trend). Chris said : : Whilst warm air seems to explain a lot of the 2010 to 2012 increased spring volume loss, it doesn't seem to explain much of the rest of the series. I am not exactly sure what you are trying to do here. Could you explain in more detail ? (Maybe in a blog post) ?
I'm getting concerned now. There is now some 200,000 km^2 of open water in the Beaufort (150,000 wide-open, and 50,000 in large polynia). Average insolation is some 250 W/m^2, which means that even on an average day open that water absorbs a whopping 50 TW. That is twice the amount of heat that the Bering Strait current moves into the Arctic. On a clear day, like what was the case over the past week and what is predicted for the next, insolation goes up to 450 W/m^2, which means absorption goes up to 90 TW. And since that heat has nowhere else to go but to melt ice on the boundary, the Beaufort is in trouble : 90 TW is enough power to melt 23 Gton of ice per day. Which means 15,700 km^2 / day of 1.5 meter thick ice. And that is not even counting the small polynia that do not show up on ice 'extent', nor influence of any melting ponds. So unless the weather turns bad very quickly, I don't see the rate of ice loss in the Beaufort slow down. If at all, it will increase.
Toggle Commented 7 days ago on Beaufort final update at Arctic Sea Ice
Thanks Susan, And I'm having lots of fun with this exercise. Expect more to follow as I work out the sensitivities (such as that "open water" problem I describe above) in my algorithm, and work towards a "temporal" fill-in (using ice observations from prior or subsequent months to better estimate ice extent). After that, I will publish my best estimate of ice-extent for August and September for all the years in the entire 1935-1952 period, and possibly before that too. Diablo, I discovered two additional issues with the Walsh data set : 1) DMI observations in the Walsh data set do not include information about the 'ice-edge' (the red lines next to the ice observations in the DMI graphs) : ftp://sidads.colorado.edu/DATASETS/NOAA/G02203/1935_08.jpg Such ice edge observations should be easy to include in a future Walsh data set by modeling at least a couple of "open water" pixels next to the ice. 2) I found a few "bad apples" in the post-1952 data set : Here is August 1971 : Obviously something went wrong there in the ice concentration estimate for the ACSYS source. Similar problem in the August 1967 map, and there is a curious little "hole" in the central Arctic ice pack in the 1953 map. Could you still send this info to Florence Fetterer for correction in a future version of the data set ?
Correction: Aug 1935 is in the 8.3-8.5 M km^2 area.
On the other hand, here is an example where my algorithm goes wrong. Reconstructing September 1935 is a challenge by itself, since we ONLY have AARI ice observations. No observations from the other side of the Arctic. And even with these AARI observations, there are some issues. For example, AARI observations around the new Siberian islands consist of ONLY open water observations, quite close to the coast, but over a wide longitudinal area. Diablo has a nice animated GIF where the September AARI observations show mostly open water : https://diablobanquisa.files.wordpress.com/2016/03/output_3ax4kh.gif All these "open water" data points along the Russian Arctic coast affect my algorithm, since they best match with .... year 2007. The small patch of ice in the Chukchi does not prevent the overwhelming bias towards a "2007-like" Arctic state, which reflects in my algorithm projecting water across half the Arctic : http://i1272.photobucket.com/albums/y396/RobDekker/result-9-1935_zpskwslzbyb.png and resulting in a 2007-like 4.4 M km^2 estimate for Sept 1935. That is obviously incorrect, especially since we just determined that (based on much more observations) Aug 1935 is in the 5.3-5.5 M km^2 area. So this is a flaw in my algorithm. It appears that my algorithm works best if there is a good mix of ice observations and water-observations in some area, and particularly good if there are a lot of ice-edge observations. But if, over a large area, there are only "ice" observations, or only "water" observations, then my algorithm finds analogs that tend to amplify that. Simply eliminating 2007 as a reference year alleviates much of the problem, but still leaves quite unrealistic swats of open water north of the open-water observations from AARI. I expect that the problem would only be truely solved by adding more diverse (water and ice) observation points, possibly via temporal borrowing from neighboring months. Something that is not difficult to do in my algorithm. So, more work ahead..
I would like to present two different reconstructions that highlight the strength and weakness of my spatial fill-in algorithm. The first one is August 1952. This is a month where there is ample observation of the ice edge, and it results in a realistic reconstruction of the unobserved data points by my Match-and-Merge fill-in algorithm. Here is the reconstruction that my algorithm came up with : Note that this follows the ample AARI observations of the ice edge along the Russian Arctic, and follows ACSYS observations along the Barents, then nicely projects an ice edge along the Greenland Sea, and follows the DMI observations of ice along the South of Greenland. The interesting projections are the ice in the center Baffin Bay, which looks realistic given the DMI ice observations there, and the ice that my algorithm projects in Fox Basin seems consistent with the general state of the ice observations from the area according to DMI's August 1952 chart : ftp://sidads.colorado.edu/DATASETS/NOAA/G02203/1952_08.jpg Also, the open water in the eastern Beaufort that my algorithm projects is consistent with the surrounding ice conditions in the Chukchi and Baffin Bay. It all seems realistic, and at least an order of magnitude better than the vague ice projections in the original Walsh dataset : http://i1272.photobucket.com/albums/y396/RobDekker/Screen%20Shot%202016-03-13%20at%2012.25.42%20AM_zpshfyb9zau.png I believe that this is the most realistic August 1952 ice extent reconstruction to date. Better than Walsh' dataset, and better than a reconstruction with a "climatology" backdrop, like Diablo's. Note that ice extent is 8.15 M km^2.
Hi Diablo, Good to see you back, and don't worry. I'm just kicking the tires of my new toy over here. I think your note to Florence Fetterer is much more important, since that actually may make a difference in the official ice-extent history by Walsh et al. After all, whatever I'm doing here now is just a different way of doing spatial/temporal filling of unobserved data points, which is by definition inaccurate.
Hi Lodger, I read the Maykut and Untersteiner paper from 1969. And what a magnificent read it is ! I love the loose style of writing that was common in scientific literature these days, and the deliberations about how to remove Arctic sea ice (by means of coal dust or ice-lichens) is sort of offending, ironic and refreshing in a weird kind of way at the same time... The core of the paper discusses their 1D ice growth model. And wow. The amount of detail in that model is astounding. Including influence of brine pockets, temperature profiles, snow cover, penetration of short-wave radiation, albedo changes over the melt season, and very detailed about ocean heat flux. Topped off with a brilliant implementation in a Fortran program that can simulate an entire annual freeze/melt cycle in 15 seconds on an IBM 7094. One of these things : with punchcards optional, since it has tape drives too. Just amazing what these guys were doing while I was just learning how to ride a bicycle at that very same time. Yet the paper has virtually nothing to do with Arctic bifurcation, or assessments of an Arctic free winter. For starters, the model stops if there is zero ice at any time during the year. Later 1D models DID include ice-free conditions, and some of these models did indeed suggest that it may be possible to have the Arctic in two states : One ice-covered, as it is now, and one ice-free, where both could be in energy balance. Wagner and Eisenman explained that such bifurcation in behavior in these simple 1D models is likely not realistic, since if you include lateral heat movement (such as in more complex 2D and 3D GCMs), the bifurcation state disappears. https://scripps.ucsd.edu/news/research-highlight-arctic-sea-ice-loss-likely-be-reversible And that kind of makes sense. After all, imagine an Arctic (in winter) that is warmer (0C) than the surrounding land masses (which are at -20C or so). That sure reverses the heat flow, cooling the Arctic ocean very quickly, and thus the planet as a whole would have to warm up quite a bit (dozens of degrees) before an ice-free Arctic winter would become a reality. And without a bifurcation state, that is not going to happen in the next few decades.
Sorry. This : "Over the Russian Arctic, my algorithm appears to determine much of the ice edge, and in fact at some points project more ice than the original Walsh reconstruction. " should read as : "Over the Russian Arctic, my algorithm appears to determine much of the ice edge, and in fact at some points project LESS ice than the original Walsh reconstruction. " In fact, these are quite a few areas where my method shows more water in the Russian Arctic in August 1935 than the Walsh reconstruction.
I finally figured out how to write a NetCDF file, so I can view the results of my fill-in algorithm in Panoply (and share it here). So, here is the results for August 1935, using the Walsh data set for the real ice observations (AARI, DMI and ACSYS), and filling in everything else with my regional Match-and-Merge algorithm (explicitly ignoring Walsh' Kelly fields, which we know are incorrect) : Click on the image for a larger version. Compare that image to the original Walsh August 1935 ice concentration map : http://i1272.photobucket.com/albums/y396/RobDekker/seaice_Aug_1935_zpsh6r5qn9o.png Note that my algorithm leaves real observations alone (reports the original ice concentration) but for all unobserved grid points, uses a 'regional' analog from the 1953-2013 August data set. It then replaces the (unobserved) grid point with either 0% or 90% ice concentration, depending on if the merge of the nearby analogs expect to see (15%) ice at that point. Now, here are a couple of observations : 1) For the Greenland sea and the Barents, August 1935 has ACSYS field observations, and thus (as expected) over these areas my reconstruction leaves the ice concentrations alone in these seas. 2) Over the Russian Arctic, my algorithm appears to determine much of the ice edge, and in fact at some points project more ice than the original Walsh reconstruction. That suggests that AARI observations in August 1935 were mostly of 'ice-free' type, so that the actual ice-edge ended up in 'unobserved' areas. I wonder if that is correct. 3) In Baffin Bay (where there were only a few DMI observations), the ice is sharply reduced w.r.t. the original Walsh Kelly fields. That was to be expected when we ignored the Kelly fields. What is NOT expected is that this reconstruction still puts ice out beyond where DMI projected an ice edge in Baffin Bay. ftp://sidads.colorado.edu/DATASETS/NOAA/G02203/1935_08.jpg DMI clearly projects only a sliver of ice on the west coast of Baffin Bay, and my algorithm should not have projected ice further off the coast. That suggests that the DMI ice observations in Walsh' data set include only "ice" observations, and NOT the fact that there is "water" right next to it. My algorithm is very sensitive to things like that, as can be seen in the next experiment, where I ignore ACSYS altogether : http://i1272.photobucket.com/albums/y396/RobDekker/result-1935-no_ACSYS_zpsoequpr4o.png Here, you can clearly see that my algorithm projects some extra ice right next to the (DMI observed) ice in the Greenland sea. That would not happen unless the Walsh data set forgot to include at least a few pixels of water next to these DMI ice observations to suggest an ice edge. Instead, they project only the ice, and next to it is "unknown". Note that due to this flaw in the DMI observations, the Greenland sea ice is a bit bigger in this (no-ACSYS) reconstruction, and that immediately reflects in more ice in Baffin Bay, and even the regional analogs suggest some extra ice as far as Hudson Bay. This means that in order to do a correct reconstruction of the 1935-1952 time frame, I now need to manually go in an correct the DMI observations to reflect an "ice-edge" rather than just "ice" in some places. It is this kind of issues that make reconstruction of past ice extent quite a hairy exercise....
Diablo, regarding 1) Adjustment for WalshJohnson concentration bias. Yes, I made that adjustment, and it does have some (not much) influence on the 1935-1952 reconstruction efforts. 2) Regarding testing sensitivity to eliminating known observations. Initial experiments suggest that (as expected) by algorithm is quite good in filling in local gaps (created by artificially removing local observations). However, for large scale removal of observations (such as removing all of the AARI observations) it has a very hard to reconstruct such gaps across the Arctic. I believe that that has more to do with the 'independence' that the various corners of the Arctic show variability than with the integrity of my fill-in algorithm. Moreover, one experiment I did to test sensitivity to removing observations (by removing ACSYS) described below, revealed an interesting issue with DMI observations as recorded in the Walsh data set. More in the next post.
Thanks for the compliments, Chris. Volume is one of the (may be THE) most important indicators of the health of the Arctic, and thus warrants close analysis. And you, in countless, detailed blob posts, have been an inspiration in that respect. Thanks again for all your work, and your insights, and let hope that the 'slowdown' you expect will develop soon during this melting season. We could sure use it.
Chris said I would be interested to see hindcasts for your method (I think your method has merit). I'm not sure about 'hindcasts', but here is the June forecast of my "albedo" method for 1992-2015 and how it panned out : http://i1272.photobucket.com/albums/y396/RobDekker/June-14_zps7336859b.jpg The June 2015 forecast for September was 4.6, right on target.
Chris said : if April volume loss stalls then summer loss extent stalls. This does not make any physical sense to me. If summers keep on warming (due to global warming), then more and more ice (volume) will melt out during the summer. So physics suggest that even if April's volume stalls (which is not clear at all at this point) then the final amount of ice left over in September will keep on going down. There appears to be no physical reason that decline would slow down, and thus it will go right down to zero (ice-free) and beyond. Chris said : I agree that albedo is important, I just think you're expecting too much of it. Check out this graph of ice volume anomaly over the months : https://14adebb0-a-62cb3a1a-s-sites.googlegroups.com/site/arctischepinguin/home/piomas/grf/piomas-trnd3.png?attachauth=ANoY7cpmN74ti-eQpKHAQ8q5v8g3_kUDhPTZcN54jJy2IJsDIVrGWYy1D4QzLNGOigVHgzFYG9V3XUW-sA5yvzgQe59uRll_VciM1H8godviXzoxAuo1V62qpnTuifmMDyjGBgZu0d4GRmk9WtU_nhpPWxLtAC_Nk-v1XlBoS9DYsBv-18fARBh539qM0kQsBgFR8qN9enu3nkUYF0DaQG7NeM9AYftFoDwRgjFKw-t5-Yd1FZ4cdrWFrhR3y6hso04mt-V771to&attredirects=0 That dip in June that has been developing over the past decade is exactly the effect of albedo-feedback. And it is quite substantial.
Hi Lodger, That article appears to be behind a paywall. Can you summarize its findings and how it relates to the statement of "an essentially ice free Arctic winter" over the next couple of decades.". But even without that : Yes, there is an astounding amount of heat built-up under the Halocline, and if that were to be released, we sure can sustain a couple of winters without ice. But what happens after all that heat is lost ? You stated earlier that an ice-free summer (after an ice-free winter) would accumulate enough heat to keep the subsequent winter ice-free as well, essentially suggesting that the Arctic appears in a "bi-furcation" state, where it either can appear with or without ice, and still be energy-neutral. But is that really true ?
Sam, With all due respect, but I have not seen any physics, or any study that project "an essentially ice free Arctic winter" over the next couple of decades.
Chris, thank you for your perspective, your analysis and your insights. Regarding curve fitting, yes, you sure have a point that they should be grounded in physics, but I am not convinced that you have the physics on your side. The remaining ice volume in September is simply the difference between the starting (maximum) volume (which is determined by winter) and the amount of volume that melts out (which is determined by summer). There is no physics that somehow, magically, cause a "slow down" as that remaining September volume approaches zero. Regarding your 2016 September extent projection (of a 2015-like 4.6 million km^2), I respect your opinion, but I think you grossly underestimate energy-input, and you grossly underestimate albedo-feedback during the summer months. So I think your are WAY too optimistic with that projection, and I put more trust in my "albedo" method, which has a lower SD, and suggests a September extent of 3.2-3.5 M km^2. But time will tell. Incidentally, I'd like to run some numbers, to see how well my "albedo" method is in predicting September Volume minimum. But that is something for a different thread than this one.