7 ms·

Global sea ice records broken again

50 points by ablation 10y ago

ablation 10y ago
More data and charts here: https://sites.google.com/site/arctischepinguin/home/global-sea-ice https://sites.google.com/site/arctischepinguin/home/global-s...
atemerev 10y ago
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.
- Oletros 10y ago
  If someone talks about "remaining trust in climate science" is because he doesn't believe any data and looks for any miningless thing to try to not believe it like your comments about the graph And it took just 30 seconds of search to know why the data starts in 1978[0]: > Useful satellite data concerning sea ice began in late 1978 with the launch of NASA's Scanning Multichannel Microwave Radiometer (SMMR) satellite. [0]: https://nsidc.org/cryosphere/quickfacts/seaice.html https://nsidc.org/cryosphere/quickfacts/seaice.html
- jawbone3 10y ago
  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.
  - atemerev 10y ago
    I suppose points 2) and 3) can (but unlikely to -- see below) be unintentional, but point 1) is clearly intentional and sufficient to consider this chart manipulative. As for the color scheme choice -- almost any other option would have been better. If the colors were random, it would have removed the ability to recover the trend in any way except of tedious manual comparison, but at least it would be certainly bias-free. If mapped to some color gradient -- well, fitting 28 points is hard, but at least close colors would have matched close years. But this scheme is different. It _looks_ like the gradient map, and invites the reader to mentally build the year-to-year trend, but some colors are nearly repeated in distant areas! This is a cardinal sin of using color mapping for dimensional representation, and it's hard for me to imagine this could be done unintentionally. Not to mention that this is not a good choice for representing YTY trend; 2D color map, like in https://xkcd.com/1410/ https://xkcd.com/1410/, would be so much better.
  - candiodari 10y ago
    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.
- ablation 10y ago
  I don't find it particularly confusing. It's a lot of data, but if you take the time to look at it, not really hard to interpret.
- analogist 10y ago
  I'm not sure where all the aggression and distrust comes from, but if you had done a a simple search, you would easily see that your points are false. 1) a) Every single line shown are thin lines except for the 6 lowest average-ice years, which is clearly marked in the legend (2006-7, 11-12, 16-17). That makes for 34 thin lines and 6 thick lines. b) Also, why would that visual distinction be misleading again? All it would emphasize are when the low-ice time periods are - in the recent decades. It's not like there was a low-ice period in 1979 or something that the author intentionally made thin. 2) It is not visually possible to pick 40 colors that are distinct enough in color space that you can consistently tell at a glance (i.e. when you look away and only compare the next color from memory). Go ahead and try it. Visual perception researchers have tried (http://vis.stanford.edu/color-names/ http://vis.stanford.edu/color-names/) and the best you're going to get is maybe 12 (http://colorbrewer2.org/ http://colorbrewer2.org/) 3) This is so wrong, it's not even wrong: a) the data only existed starting in 1978, because the Nimbus 7 launched in 1978, so this is the whole available data (http://psc.apl.washington.edu/zhang/Global_seaice/ http://psc.apl.washington.edu/zhang/Global_seaice/). b) Global sea ice isn't in perfect lockstep with temperature, but larger temperature trends and currents and other factors, so talking about a handful of warmer or colder years doesn't even make sense. c) Even if it were, I still don't know what you're talking about. See the NASA land-ocean temperature index (http://climate.nasa.gov/vital-signs/global-temperature/ http://climate.nasa.gov/vital-signs/global-temperature/). You could have started in 1977, or 76, or 75... you'd have to go all the way back to 1945 to find a warmer year, and that would be missing the whole point of the overwhelming trend. I'd be very careful to make sure that I'm not the one doing the public a disservice when I openly accuse people of manipulating data. I wish everyone showed a similar courtesy.
vixen99 10y ago
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
avian 10y ago
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
spodek 10y ago
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.
- mikeash 10y ago
  Changing my own behavior won't do anything noticeable. Several billion people need to change their behavior. That's why people want governments to get involved.
  - SixSigma 10y ago
    When I went vegan in 1991 you couldn't buy soya milk in a supermarket. Now every supermarket has its own brand. Political agitation moves the Overton Window [1], if you sit back and wait, nothing will happen. That said, you will need a plan on how a billion Indians can have a fridge and an indoor cooker without impact. [1] https://en.wikipedia.org/wiki/Overton_window https://en.wikipedia.org/wiki/Overton_window
  - bad_alloc 10y ago
    Looking at the makeup of CO2 emissions [1] (ignoring methane and other factors) it seems that it makes the most sense to avoid unneccessary heating and electricity consumption (which most people will already do because it's good for your wallet) and cut back on driving (which most people don't). For agriculture and industry, the two big other factors, you're probably right: There's not much a single person can do. [1]: https://www.epa.gov/sites/production/files/2016-05/global_emissions_sector_2015.png https://www.epa.gov/sites/production/files/2016-05/global_em...
    - fulafel 10y ago
      Agriculture and industry are just producers to your consumption. They produce the meat/dairy and electricity you use. So there is definitely a lot consumers can do by personal choices. But of course regulation is needed too.
zaroth 10y ago
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 10y ago
  > 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.
jondubois 10y ago
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 10y ago
  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

50 points by ablation 10y ago

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

atemerev 10y ago

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.

Oletros 10y ago
If someone talks about "remaining trust in climate science" is because he doesn't believe any data and looks for any miningless thing to try to not believe it like your comments about the graph And it took just 30 seconds of search to know why the data starts in 1978[0]: > Useful satellite data concerning sea ice began in late 1978 with the launch of NASA's Scanning Multichannel Microwave Radiometer (SMMR) satellite. [0]: https://nsidc.org/cryosphere/quickfacts/seaice.html https://nsidc.org/cryosphere/quickfacts/seaice.html
jawbone3 10y ago
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.
- atemerev 10y ago
  I suppose points 2) and 3) can (but unlikely to -- see below) be unintentional, but point 1) is clearly intentional and sufficient to consider this chart manipulative. As for the color scheme choice -- almost any other option would have been better. If the colors were random, it would have removed the ability to recover the trend in any way except of tedious manual comparison, but at least it would be certainly bias-free. If mapped to some color gradient -- well, fitting 28 points is hard, but at least close colors would have matched close years. But this scheme is different. It _looks_ like the gradient map, and invites the reader to mentally build the year-to-year trend, but some colors are nearly repeated in distant areas! This is a cardinal sin of using color mapping for dimensional representation, and it's hard for me to imagine this could be done unintentionally. Not to mention that this is not a good choice for representing YTY trend; 2D color map, like in https://xkcd.com/1410/ https://xkcd.com/1410/, would be so much better.
- candiodari 10y ago
  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.
ablation 10y ago
I don't find it particularly confusing. It's a lot of data, but if you take the time to look at it, not really hard to interpret.
analogist 10y ago
I'm not sure where all the aggression and distrust comes from, but if you had done a a simple search, you would easily see that your points are false. 1) a) Every single line shown are thin lines except for the 6 lowest average-ice years, which is clearly marked in the legend (2006-7, 11-12, 16-17). That makes for 34 thin lines and 6 thick lines. b) Also, why would that visual distinction be misleading again? All it would emphasize are when the low-ice time periods are - in the recent decades. It's not like there was a low-ice period in 1979 or something that the author intentionally made thin. 2) It is not visually possible to pick 40 colors that are distinct enough in color space that you can consistently tell at a glance (i.e. when you look away and only compare the next color from memory). Go ahead and try it. Visual perception researchers have tried (http://vis.stanford.edu/color-names/ http://vis.stanford.edu/color-names/) and the best you're going to get is maybe 12 (http://colorbrewer2.org/ http://colorbrewer2.org/) 3) This is so wrong, it's not even wrong: a) the data only existed starting in 1978, because the Nimbus 7 launched in 1978, so this is the whole available data (http://psc.apl.washington.edu/zhang/Global_seaice/ http://psc.apl.washington.edu/zhang/Global_seaice/). b) Global sea ice isn't in perfect lockstep with temperature, but larger temperature trends and currents and other factors, so talking about a handful of warmer or colder years doesn't even make sense. c) Even if it were, I still don't know what you're talking about. See the NASA land-ocean temperature index (http://climate.nasa.gov/vital-signs/global-temperature/ http://climate.nasa.gov/vital-signs/global-temperature/). You could have started in 1977, or 76, or 75... you'd have to go all the way back to 1945 to find a warmer year, and that would be missing the whole point of the overwhelming trend. I'd be very careful to make sure that I'm not the one doing the public a disservice when I openly accuse people of manipulating data. I wish everyone showed a similar courtesy.

vixen99 10y ago

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

avian 10y ago

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

spodek 10y ago

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.

mikeash 10y ago
Changing my own behavior won't do anything noticeable. Several billion people need to change their behavior. That's why people want governments to get involved.
- SixSigma 10y ago
  When I went vegan in 1991 you couldn't buy soya milk in a supermarket. Now every supermarket has its own brand. Political agitation moves the Overton Window [1], if you sit back and wait, nothing will happen. That said, you will need a plan on how a billion Indians can have a fridge and an indoor cooker without impact. [1] https://en.wikipedia.org/wiki/Overton_window https://en.wikipedia.org/wiki/Overton_window
- bad_alloc 10y ago
  Looking at the makeup of CO2 emissions [1] (ignoring methane and other factors) it seems that it makes the most sense to avoid unneccessary heating and electricity consumption (which most people will already do because it's good for your wallet) and cut back on driving (which most people don't). For agriculture and industry, the two big other factors, you're probably right: There's not much a single person can do. [1]: https://www.epa.gov/sites/production/files/2016-05/global_emissions_sector_2015.png https://www.epa.gov/sites/production/files/2016-05/global_em...
  - fulafel 10y ago
    Agriculture and industry are just producers to your consumption. They produce the meat/dairy and electricity you use. So there is definitely a lot consumers can do by personal choices. But of course regulation is needed too.

zaroth 10y ago

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 10y ago
> 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.

jondubois 10y ago

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 10y ago
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