There was a hank green video about this a year back. Video link here, the tldr was that container ships used to use a type of fuel that was both bad for the environment but also really good at cloud seeding. More clouds shielded the oceans surface from the sun, artificially reducing its temperature. But in 2020 regulations made container ships move to a fuel that didnt seed clouds as much, so fewer clouds, higher temperature.
So i guess one potential take away from that, if its right, is that the temperatures are not “suddenly” getting worse, but rather have been artificially depressed and we are only now going to what it should be.
Actually it’s currently being looked at. The basic idea is to add sulfur to kerosine for airplanes to spray that into our atmosphere.
Bad side is it will cause acid rain, but the good side is that it will buy us a few decades that totally won’t be abused to speed even more CO2 in the air
I kinda feel like we hit the point where its either our global production infrastructure or our species seeing this graph.
This is not a news article, it’s a picture of a graph.
In the interest of discussion here, I’ll leave it up this time.
Please report this to us earlier, or, if you think our rule about articles only is unfair, I would like to hear your thoughts on if this should be allowed in the future.
He he, I’m in danger.
HELP US
A lot of us want to make change but a lot of people are trying to stop it…
God, Gods, someone!
^help…
How can standard deviation be negative?
It’s deviations from the mean, so if the deviation were “3” for example, values of 6, 3, 0, -3 and -6 would be 2, 1, 0, -1, and -2 deviations away from the central line, respectively.
Deviation != standard deviation
Standard deviation is square root of sums of squared deviations divided by number of samples. Only complex numbers can result in negative values when squared. Negative amout of samples makes even less sense.
Deviation from mean is
x - μ, standard deviation is this abomination:The standard deviation is not negative, that data was just that many standard deviations below the mean. Think “this data point is below the mean by 0.5 standard deviations” not “the standard deviation is 0.5”. They are using standard deviation as a unit rather than, say, degrees Celsius.
Then why yellow line doesn’t touch time axis? Function cannot always be bigger than its own mean. If there is point above mean, than there should be at least one point below mean. I’m assuming here mean is of temerature in that year.
The chart could stand for some clarification, but it looks like the mean and standard deviation refer to statistics covering all the years from 1982 through 2011. However, it does not explicitly state the dataset over which the standard deviation is calculated, but it seems reasonable to assume that the same aggregate cited for the mean is also the same aggregate used for the standard deviation.
Each line in the graph represents a single year of data. It’s kind of messy and only two of the years are actually labeled, 2023 and the partial data for 2024. So that bottom-most line represents some unspecified year that was consistently 1.5 to 2 standard deviations below the mean for the 30 year analysis.
The data is at https://climatereanalyzer.org/clim/sst_daily/json/oisst2.1_world2_sst_day.json, but alas, I’m too lazy to try to reproduce this sort of analysis to verify my guesses.
I will say it’s a peculiar approach and visualization. Including a subset of the data in the mean/standard deviation and then plotting the entire data. Also impossibly jumbled line graph visualizations of most years instead of something easier. I’d imagine you could convey the point with each year consolidated to a single data point and have a much easier to follow graph.
