
Global sea ice records broken again - ablation
http://neven1.typepad.com/blog/2017/01/global-sea-ice-records-broken-again.html
======
spodek
What will _you_ do about _your_ contribution to this effect?

Everyone seems to want to wait for government regulation or something to
change other people's behavior. Governments will follow what voters do.

~~~
egeozcan
TL;DR: I don't know what to do and think most people don't, too.

I mean, private emissions, I heard, are insignificant compared to industrial.
But then, industry exists because, in the end, we consume stuff. Right?

I'm sincerely hoping for someone who I can trust to explain to me how I'm
making the world a worse place by purchasing, let's say, a car, _and_ that as
if I'm a 5-year-old. Not because I'm easily bored, but because (I accept,) I'm
still ignorant and I need to start from the beginning.

A meteorologist (I just googled "scientist who studies weather", not a native
speaker here) telling me "hey, the temperatures will increase by X degrees and
the sea level will increase by X meters so... we are doomed" makes me want to
do something but I can't even begin to predict the effects.

Also there are these false data generated by (IMHO, crazy) deniers but while
easy to catch on its own, they have this side effect of creating many false
positives while trying to identify fake data in this ocean called the
internet.

~~~
fulafel
Private emissions are definitely significant, and it's important that people
know this. Food, heating/cooling and transportation are the big household
ones. And they're straightforward to make improvements in.

~~~
s_kilk
Transportation is the big one, and the one most people are least willing to
cut down on.

Unfortunately the biggest impacts you can have are to stop flying, and stop
driving a car, the suggestion of which many people don't react well to.

~~~
the8472
> and the one most people are least willing to cut down on.

Getting people to eat less meat or meat from less worse emitters or upgrading
existing buildings to low emissions for heating does not seem that much
easier.

Anyway, you can't fix the problem with a single change.

------
vixen99
For the period 1989–2014 this observation is interesting.

"We have analysed observations of the summer sea ice edge from the ship
logbooks of explorers such as Robert Falcon Scott, Ernest Shackleton and their
contemporaries during the Heroic Age of Antarctic Exploration (1897–1917), and
in this study we compare these to satellite observations from the period
1989–2014, offering insight into the ice conditions of this period, from
direct observations, for the first time. This comparison shows that the summer
sea ice edge was between 1.0 and 1.7° further north in the Weddell Sea during
this period but that ice conditions were surprisingly comparable to the
present day in other sectors."

[http://www.the-cryosphere.net/10/2721/2016/](http://www.the-
cryosphere.net/10/2721/2016/) doi:10.5194/tc-10-2721-2016

------
jondubois
Global warming is a natural consequence of capitalism.

Any system which rewards short-sightedness over long-sightedness is going to
create long term problems.

Until we have a single world government, no single country is going to be
willing to spend money protecting the environment while other countries keep
profiting from its pollution.

~~~
masklinn
It's not even short-sightedness, it's failing to internalise externalities[0].
And of course the current profiteers will do everything they can to keep
things as they are, see e.g. the fate of carbon taxes whose entire purpose is
to try and internalise some of the externalities into capitalistic frameworks.

[0]
[https://en.wikipedia.org/wiki/Externality](https://en.wikipedia.org/wiki/Externality)

------
avian
Previous discussion of the same graph with data up to mid-November last year:

[https://news.ycombinator.com/item?id=12992777](https://news.ycombinator.com/item?id=12992777)

------
ablation
More data and charts here:
[https://sites.google.com/site/arctischepinguin/home/global-s...](https://sites.google.com/site/arctischepinguin/home/global-
sea-ice)

------
zaroth
Whatever happened in Jul-Nov last year, it seems like ice is trending toward
recovering back to within 2 sigma?

Of course "records" will continue to be broken through at least July when we
cross over last year's breakaway point.

~~~
the8472
> trending toward recovering back to within 2 sigma?

I wouldn't bet on that. The graphs only show area. The shortened time the
arctic ice has to grow means it will be thinner than previously and thus melt
more rapidly during spring, again driving it away from the historical mean.

------
atemerev
And yet, this chart is a quintessential story of data representation
manipulation, worthy of being included in textbooks (if there are any on this
topic).

1) Lines for years with low ice area are marked bold, when high-ice years
(e.g. 2013 or 2015) are shown with thin lines.

2) Color scheme is deliberately confusing, with some colors are almost
identical (1993 vs 2015, anyone?)

3) The data set is started with 1978, one of the colder years. If it would
have been 1979 or 1974, the story would have been less immediately visible.

While I am not saying there isn't a trend, and 2016 is clearly an anomalous
year (but what about this year _was_ normal?), visible manipulations like
these quickly destroy any remaining trust in climate science, advancing the
other side's cause.

~~~
jawbone3
They show 28 overlapping lines, that many lines simply can't be individually
coloured. To accuse them of deliberately choosing a poor colour scheme is
plain dishonest.

It is a graph comparing the current year to the previous minimum area years,
with the entire dataset for context. The choices they have made are completely
legitimate for this purpose.

~~~
candiodari
Fact of the matter is, the GP is right. Can we at least agree the color scheme
could have been chosen better ?

You are also obviously showing a bias towards one conclusion, and accusing
opposition to this conclusion of being "plain dishonest" is not constructive.
This is data interpretation. Even attributing 100% to your prior (ie. ignoring
the data) is not considered dishonest.

Furthermore, when push comes to shove, let me just say that as someone holding
a masters in statistics, there is zero useful data on that chart. I think the
the point is to show that we are more than 2 standard deviations from the norm
... And then we have a long list of issues with that conslusion. In increasing
importance :

1) there is an obvious reason to pick the start of the time series, and that
reason is NOT independent of the conclusion that is reached here. Needless to
say, that is a huge no-no.

2) more generally the data supporting the conclusion is not randomly drawn
from the distribution. Again, huge no-no.

3) is the relation between time of year and sea ice extent well established ?
For instance, does the minimum drift ? How much ? (Why I pick that one:
because if you ignore the time of year, flatten the data, we are suddenly very
far removed from a 2 sigma deviation, and arrive at a much more sane
conclusion : lowest extent ever, but not hugely different from before. And of
course, seeing 2 extremes of a slowly evolving variable close together is not
exactly strange. When you're climbing the hill, every step sets a "new height
record". Focusing on that is misleading, to say the least).

How often do we hit "lowest ever" because the minimum extent falls at a
slightly different point every year ? (looking at the data: quite often, for
instance, we hit lowest ever and highest ever extents last year. Lines that
hit "lowest ever" at some point: dark red, dirty green, thick bright green,
thin dark green, thin light green, purple, orange and another medium-dark
green. I can't be bothered to look up the years, but I think the point stands:
lowest ever is not a rare occurrence, and therefore "more than 2 sigma below
the norm" is not an accurate way to report that).

You are making assumptions just by choosing which 2 variables to graph against
eachother. Are these assumptions valid ? Why ? If you don't have a reason,
then please, shut up until you've done your homework.

It may make a lot more sense to plot the minima at the same points every year,
to prevent normal noise from generating these extremes, or just only compare
minima and maxima, and even then, smoothing out over 4-5 years seems
necessary. Or perhaps just don't report things like this.

3) more fundamentally, why would the data be normally distributed at all ?
This seems to me unlikely in the extreme.

Technically speaking, the data is contradictory: it leads to a conclusion that
disproves itself. The steps work like this : if the sea ice extent is indeed
dropping over time (the conclusion of the graph), then obviously it's
distribution over time cannot be normally distributed. Unfortunately that is a
necessary precondition for interpreting the data in the first place. If the
data is not normally distributed, then there is nothing strange about a 2
sigma deviation, which at that point is nothing but an arbitrary numerical
value that has nothing to do with the distribution.

If you want to prove that the data is indeed less than the data of the
previous years, there's tests for that. This is not it.

4) that grey band obviously covers 98% of the data in the way years are
reported here. Years are reported as special, when the 2-sigma deviation is
based on days. The time series regularly dive outside of that band, and it's
easy to see why: over (2016-1978)*365 days, we should expect ~2% 2-sigma
events (days). That's a LOT of days.

5) we should keep our heads screwed on and ask ourselves if the data is really
showing what we think it's showing. I would argue no. It looks to me like
something prevented sea ice from reforming between August and December of last
year. It seems to me unlikely in the extreme that such a sudden and big change
would result from the minute temperature change that global warming
contributed this year. Maybe not entirely out of the question, but that's an
extraordinary claim, requiring extraordinary evidence. And frankly, this
article is not off to a good start.

Or to put it more technically : it looks 2016 is drawn from a different
distribution than the other years. That means you should find out what
happened using other means, and stop using statistics. It cannot help you in
this case.

Conclusion: there is something weird happening, true, but based on intuition
alone. And let's be honest : chances are very good it's not global warming.
Something changed, and it was not a 0.2 degree temperature change. This is way
too big for that to be a valid explanation.

~~~
Oletros
Yes, the one obvious reason to pick the start of the time series is the launch
of the instruments to measure it

~~~
candiodari
Exactly. And that launch was done because of the problem to be analysed.
Feedback loop closed. Disastrously wrong results to follow.

~~~
Oletros
> And that launch was done because of the problem to be analysed. Feedback
> loop closed.

Oh, yes, the Planck satellite was launched because of the problem to be
analysed. Feedback loop closed.

Meteo satellites were launched because of the problem to be analysed. Feedback
loop closed.

GPS satellites were launched because of the problem to be analysed. Feedback
loop closed.

Are you aware that you have arrived to a cnoclusion and you're trying very
hard to bent reality to adapt to your conclusion even when your arguments are
absurd?

>? Disastrously wrong results to follow.

And exaclty why the results are disatrously?

~~~
candiodari
Look you're attacking the weakest of the points. I think you're being unfair
in your comparison.

But pedantically the point stands. The planck satellite studies a phenomenon
that exists independently of the satellite or the humans studying it. This
satellite was launched to study climate change by people who claim they're
causing it. There's a clear difference.

> And exaclty why the results are disatrously?

Because using data about something you're doing yourself to study that
phenomenon invalidates the basic axioms of statistics. If you do that, all
your conclusions about the data become wrong. Why ? Because you yourself are
now a factor in the phenomenon under study. At that point, and I've seen this
many times, there is no longer any real hope of being correct, as there either
a big gaping hole in the model, or circular reasoning. Both obviously
invalidate the model.

~~~
Oletros
The satellites where launched to study the ices and is independent of who or
what makes them change. As I said, you clearly have a conclusion beforehand
and even if facts kickball you will deny it like you're doing.

You don't have provided any rational argument for you criticism, when you were
proved wrong anon when the time series started, you changed the goalposts.

As I'm very tired of deniers like you, have a nice day.

~~~
candiodari
Enjoy your feedback-based data. We'll see how correct it is.

Funny how your criticism of me consists of 2 things :

1) I have a predetermined conclusion

2) and it's the wrong one (obviously you have a predetermined conclusion as
well and it doesn't seem to tolerate people of different opinions)

My big argument is this : why don't we look at the main point ? Obviously that
last year of data doesn't fit the data series. Obviously it's an outlier (just
freaking look at it). That means it should be treated as an outlier : don't
base conclusions on it, and figure out what has changed.

And it's an outlier so let me tell you: the effect seen here is NOT (directly)
related to a very slow change that started in 1850. It is something else.

This also means, don't use statistics to analyse it. It won't work.

~~~
Analog24
Could you please explain how the satellite observing the arctic sea ice
affects climate change? As far as I can tell, until this past year (the paris
climate agreement) that hasn't been a significant effort to reduce carbon
emissions on a global scale, which almost certainly wouldn't have an
appreciable affect on the extent/surface area of arctic sea ice (carbon cycles
through the atmosphere very slowly (the fastest processes take about a year
and the slowest take millions of years[0]) so it will take a while before the
affects of human intervention actually propagate to the scale of global
climate).

Also, you can certainly study outliers with statistics. In fact, most
scientific discoveries (these days) all start out as outliers or statistical
anomalies. The Higgs boson, Top quark, J/Psi,... every single particle
described by the Standard Model (the most accurate scientific theory by far)
all started out as anomalies and outliers. The fact that this years sea ice
measurements are outliers doesn't mean they are necessarily a large
statistical fluctuation, it could be that there is a new climate phenomenon
taking place (look up the runaway greenhouse effect). I'm not saying that is
what is happening here but we have no idea a priori which is the truth at the
moment: it's a statistical fluctuation or it's a sign of a new climate
phenomenon. Clearly all we can do is continue to study it using, among other
tools, statistics.

[0] -
[http://earthobservatory.nasa.gov/Features/CarbonCycle/page2....](http://earthobservatory.nasa.gov/Features/CarbonCycle/page2.php)

