While everyone watches in awe as comet Gleick smashes into the Lunar bedrock, I have returned my tired head to the sea ice data. We are slowly stepping toward an improved understanding of sea ice melt here. To that end I have been working on improved graphics. In my long-term self employment, I have programmed a wide variety of data visualization softwares. In all cases, the software was of a far lower level than R code. I am an engineer and creation of robotics, vision systems, and fast statistics packages in the past, were written from scratch. Often, these displays plotted individual pixels, vectors or planes to display 3D objects/surfaces as they were morphed and rotated, but due to the low level nature of the display, my control was complete. In R, the display code is pre-written and the challenge is to figure out the limitations and abilities of the functions.
Below is another re-hash of the sea ice video. However it is rendered in what I call pseudo-3D, in that some basic shading is present. I found the shading contrast created a far more intuitive visualization than my previous work. The view is top down, but is 3d and can be rotated off of this visual axis by adjusting parameters which give it a 3D mountain effect. IMO, the best angle was top down.
Please note the differences in the spatial noise frequency as the video progresses. The limitations of the sensor system may be greater than I understood.
In 1979:
vs 2008
You can see instantly that the difference in noise level is not minor by any means. The good news is that we seem to be improving in our ability to measure. The bad news is that it could make for lousy trend analysis.
I have created a video below but the frame rate is a little fast. I will improve it later but it takes several hours to complete the process.
the Air Vent 
Jeff, I had to drag the time control forward at a fast rate in order to see the changes. The video I see goes at such a slow rate that changes are difficult to see. Maybe I am doing something wrong. For a guy my age to say something goes too slow means it is really going slow.
Jeff, just curious, but do you use or have you used your video skills to present information about your products to your customers.
Well done and thanks.
What happens if you subsample the present so resolution is like in old data?
#3 The recent data and old data are presented with the same resolution 25x25km by the NSIDC. What is odd is the increased amount of high frequency noise in the early satellite record.
#1, The speed should be based on youtube now. hmm. And no, I haven’t had to do video for anyone. It seems to be uniquely suited to the massive data collections of climate.
This is great, Jeff. Thanks for all the work.
I think the satellite data are pretty convincing that there has been a downward trend in sea ice since 1979, although the January pictures you post certainly wouldn’t give that impression: a bit more in this bay, a bit less in that bay. Low-point late-summer pictures would show a greater difference.
The video, however, does a great job of letting us see the whole context — massive swings from high summer to deep winter — year after year after year after year. Whenever the topic of the Arctic comes up, one of the first things I explain to people is how dynamic the cryosphere is. There is a general sense among lay people (if I think back several years I guess I probably had the same impression before looking into any of this), that the Arctic is some great, constant mass of ice that just sits there and, if the usual media stories are to be believed, is slowly melting away. Seeing the day-to-day dynamics of the Arctic ice is extremely valuable information for people. It helps one to start thinking of warmth and cold, winter and summer, freezing and thawing, light and darkness, winds and currents, and all the many factors that are involved in such a dynamic system.
Thanks again for sharing this.
Jeff, your video works like a charm now. It would appear that you plan to take these views all somewhere. Care to comment?
I would think the feedback effect of a lower albedo from melted Arctic ice would be the concern for accelerated global warming. Has anyone looked at the time integrated effect on solar reflection.
Kenneth,
I’m glad the video worked now. It still has some weird video compression in the online version which messes things up but my intent was to make a better image of ease grid data so I can start combining other interesting datasets. I have discovered some interesting trend facts but when I saw the high spatial frequency noise in the early record due to the better visualization, it seemed worth putting on line. A fft or simple histogram would probably reveal some real differences in an easy to grasp plot but we can already see the difference just by looking so I’m not sure what the value of it would be.
My real intent was to make a better data visualization and combine temperature/flow information from satellites.
Jeff, I downloaded the video (about 25 MB) using the DownloadHelper add-on in Firefox. it allows you to look at the video without the foibles of the download itself and to enlarge the video (somewhat more blurry).
If one has a video editor of some sort, they can also speed up or slow down the video and view portions at their leisure.
Nice video.
#5
“a bit more in this bay, a bit less in that bay.”
Serious question.
When the professional climatologists and what not do research or papers about “Arctic Sea Ice”, what are the boundaries?
Jeff
As always another great piece of work from you.
Up until now I haven’t paid that much attention to the whole Arctic sea ice debate.
After seeing your video I now know that in future I need to pay far more attention to it.
As is the case with global temperates your video clearly show just how much the extent of sea ice varies throughout any given and from year to year.
I hate it when this clearly natural variability is referred to as ‘noise’. The large year to year (and often step changes) in temperature variations we see measured at weather stations are very often real
and not caused by measurement error, changes to equipment etc. They demonstrate very clearly IMO just how variable the temperature can be at any given point on the surface of our plant. IMO they demonstrate
how ludicrous the whole concept of a mean global surface temperature is. Anyone who has looked at the temperature data to any signifcant level of detail can see just how ludicrous Hansen and Lebedev justification for ‘gridding’
the temperature and ‘filling in’ missing data by deriving it from temperatures measured at ‘nearby’ stations (where nearby is up to 1200km away) is.
After your video I now see that those analysing the sea ice trends with a view to using it as evidence for CAGW and in order to so influence policy are playing at the very same game as temperature data torturers.
Namely they are obfuscating the clearly evident and very signifcant year to year regional variability in the sea ice data within the Arctic region.
KevinUK
I noticed that as the ice comes and goes it seems to flow as if blown by the wind – just wondering.
KevinUK,
Not sure which noise you mean but the noise I was referring to appears to be instrumental. Look at the two still images and you can see the top one has a lot more granularity at the same date when we can be very certain that the whole of the ice cap is filled with ice. In addition, the video shows a lot of sensor noise around shorelines in early years compared to more recent. This was documented in the trend bias post I showed before. I’m thinking about how to compensate for both of these effects in a reasonable fashion. Basically the early record may not be well “knitted” to the more recent data.
Nzrobin,
The flows you see are wind, ocean current, and Coriolis acceleration created by the rotation of the Earth. The Coriolis effect is far more evident in the Antarctic where you can see the sea ice twist around the continent.
Thanks for posting this, it’s one of those dynamic presentations that is fascinating to watch. The viewer [this one at least] feels that they may discover something previously ignored or unknown if they watch it repeatedly.
Jeff, I don’t know if you have bandwidth available, but would it be possible to post a link to a hi-res version of this (assuming you’ve got it in a higher resolution? As others have noted, this is great for viewing on YouTube size, but it would be fantastic if there were a higher resolution version that could be viewed on a larger screen.
I’m not trying to create more work for you, just hoping!
Possibly silly question:
What causes the apparent spatial/temporal correlation in the noise?