I'm finding it a little hard to work today with this in my head.
Antarctic ice extent is now 6.4 standard deviations below the mean. That is, I'm reliably told, a one in 13 billion year event.
We're about to see a lot of shit hit a lot of fans. And we are far from ready.
Business as usual is over. Politics as usual is over. We need to be putting our effort into building systems that can help us survive what greed and power and wilful blindness have wrought.
@timhollo Not discounting the severity of this data at all ...
Keep in mind that using standard deviations to measure for expected occurrence rate relies on both a normal distribution and some defined sampling basis.
Both of these assumptions are ... challenged here. Should we be considering this as an annual event or a monthly one?
And we do know that Antarctica, all of it, not merely the seas surrounding it, has been ice-free in the past. And that Earth has likely been entirely entombed in ice ("Snowball Earth"), probably multiple times. So the data record we have is at best partial.
I'd be comfortable saying that this is far outside all previous measured data. I'd caution on drawing inferences based on statistics alone, and would strongly urge that previous geological / climactic evidence (and the associated atmospheric and other conditions influencing climate) be considered.
Stats get really hairy on the thin margins, especially with comparatively small samples. We're looking at 34 years of data here, not hundreds, thousands, millions, or billions. In statistics, n ~=30 is just where "large sample" methods start becoming applicable, but typically not for drawing inferences at the 1:1,000,000,000 scale.
@stooovie Absolutely, I'm not contesting that AT ALL.
The point I'm drawing is of using a very limited amount of highly-correlated time-series data to extrapolate over 10 billion+ years. That's simply ... indefensible.
We have other data series which are sufficiently, and quite genuinely, alarming: atmospheric CO2 levels from ice core data, correlated geological evidence of atmospheric temperatures, ancient sea levels (parallel to your comment, a huge number of pre-modern human / hominid settlements are now under water due to previous sea-level rise), patterns of plant growth and distribution (particularly from lake sediments), etc., etc. etc.
All of which are really solid data.
One problem with many present highly-relevant measures especially those based on remote-sensing data is that they extend back at most to the early 1960s and satellite observations, many far more recently than that (e.g., this series, to 1989). The current awareness these measurements give is extremely valuable, and the fact that we can now make measurements over the entire planet (and hence avoid objections based on potential local human influences as with, say, urban heat-island effects).
But as a long-term data line ... not so much.
What would be useful is to correlate these data with other long-term measures, as has been done with some of the examples I've given above.
Tim Hollo
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