3 ms·

I get your point, but there is another angle here. People have a strong tendency not to trust forecasters, despite relative accuracy. This article implies a lac

by jsight 7y ago

I get your point, but there is another angle here. People have a strong tendency not to trust forecasters, despite relative accuracy. This article implies a lack of accuracy that wasn't actually the case. It would be incredibly easy to come away from this article with the wrong lessons.

nightski 7y ago
Where do you see the article implying the forecast was inaccurate? To me the author is only saying that how people interpret it is inaccurate which is the entire point of the article.
- albertocairo 7y ago
  Yes, exactly. The cone is as accurate as it can be, by which I mean: accurate but with a huge degree of uncertainty. The challenge is that some readers tend to read it as deterministic, and get it wrong by: 1. Thinking "If I'm inside of the cone I'm in danger, if I'm outside I'm good" (wrong! 1/3 of the time the storm will be outside of the cone!) 2. If I'm inside of the cone AND under its center line/dots of I'll worry a lot, but if I'm inside and in between the center of the cone and its boundary, I can relax (I'd be VERY careful with this, as it isn't true either).
  - spectramax 7y ago
    And your article drives this point home really well. I honestly don't understand the criticism - the hurricane example you picked from 2017 is just to make a point - which people in this thread are unnecessarily complaining about.
flukus 7y ago
> People have a strong tendency not to trust forecasters It's possible a lot of this bias is just outdated, up until very recently most hurricane (cyclone in my case) warnings came with a disclaimer like "cyclones or notoriously unpredictable and can make sudden, unexpected course changes" and for the most part this was true even in the short term. I don't think I've seen a wildly incorrect forecast in my area in 20 years but my mother still believes in this inherent unpredictability.
- albertocairo 7y ago
  The challenge is that, eventually, the forecast of one storm will be wildly off. This is inevitable. But that doesn't mean that the forecast was necessarily incorrect. I think that this is what it's crucial to explain to the public: the general meaning of uncertainty. We need to learn to deal with it.
spectramax 7y ago
I don't understand - what are the wrong lessons that this article teaches? The author isn't a forecaster. The author is exemplifying a problem with the chart by using a 2017 hurricane example. Unless I am missing something?
- dmix 7y ago
  Why use a real-world example if it's not going to be based on data? Surely if the numbers are correct that there's 60-70% accuracy with the cone (on any particular day? or possibly early on) then they could use real data. It also starts with "The National Hurricane Center publishes graphics like this one" (with "graphics" directly linking to a different graph than the one shown [1]) which would lead one to believe it was an actual NHC example being challenged. The general point can still get across but its just important to choose your anecdotes carefully if you want to be taken seriously. Especially in the hyper-critical social media age when everyone is looking to kick anything popular down a peg or two, for their own personal satisfaction of being smart (or w/e the motivation is). [1] https://www.nhc.noaa.gov/refresh/graphics_at5+shtml/174008.shtml?cone#contents https://www.nhc.noaa.gov/refresh/graphics_at5+shtml/174008.s...
  - spectramax 7y ago
    This is extreme. Why use a real-world example? Because people can relate to it. People have seen these types of plots. It could have been a completely fabricated example of an arbitrary hurricane in Florida or Canada or whatever - the point would still be the same. I feel like people are completely missing the point of the article. Also, my question is : what are the wrong lessons that this article teaches?
    - dmix 7y ago
      A whole lot of people who are the target market for this article would likely have experienced the same hurricane. Not giving the peanut gallery easy reasons for dismissal is something to be considered. It wouldn’t hurt but it’s not urgent like I said.
  - 7y ago

by jsight 7y ago

nightski 7y ago

Where do you see the article implying the forecast was inaccurate? To me the author is only saying that how people interpret it is inaccurate which is the entire point of the article.

albertocairo 7y ago
Yes, exactly. The cone is as accurate as it can be, by which I mean: accurate but with a huge degree of uncertainty. The challenge is that some readers tend to read it as deterministic, and get it wrong by: 1. Thinking "If I'm inside of the cone I'm in danger, if I'm outside I'm good" (wrong! 1/3 of the time the storm will be outside of the cone!) 2. If I'm inside of the cone AND under its center line/dots of I'll worry a lot, but if I'm inside and in between the center of the cone and its boundary, I can relax (I'd be VERY careful with this, as it isn't true either).
- spectramax 7y ago
  And your article drives this point home really well. I honestly don't understand the criticism - the hurricane example you picked from 2017 is just to make a point - which people in this thread are unnecessarily complaining about.

flukus 7y ago

> People have a strong tendency not to trust forecasters It's possible a lot of this bias is just outdated, up until very recently most hurricane (cyclone in my case) warnings came with a disclaimer like "cyclones or notoriously unpredictable and can make sudden, unexpected course changes" and for the most part this was true even in the short term. I don't think I've seen a wildly incorrect forecast in my area in 20 years but my mother still believes in this inherent unpredictability.

albertocairo 7y ago
The challenge is that, eventually, the forecast of one storm will be wildly off. This is inevitable. But that doesn't mean that the forecast was necessarily incorrect. I think that this is what it's crucial to explain to the public: the general meaning of uncertainty. We need to learn to deal with it.

spectramax 7y ago

I don't understand - what are the wrong lessons that this article teaches? The author isn't a forecaster. The author is exemplifying a problem with the chart by using a 2017 hurricane example. Unless I am missing something?

dmix 7y ago
Why use a real-world example if it's not going to be based on data? Surely if the numbers are correct that there's 60-70% accuracy with the cone (on any particular day? or possibly early on) then they could use real data. It also starts with "The National Hurricane Center publishes graphics like this one" (with "graphics" directly linking to a different graph than the one shown [1]) which would lead one to believe it was an actual NHC example being challenged. The general point can still get across but its just important to choose your anecdotes carefully if you want to be taken seriously. Especially in the hyper-critical social media age when everyone is looking to kick anything popular down a peg or two, for their own personal satisfaction of being smart (or w/e the motivation is). [1] https://www.nhc.noaa.gov/refresh/graphics_at5+shtml/174008.shtml?cone#contents https://www.nhc.noaa.gov/refresh/graphics_at5+shtml/174008.s...
- spectramax 7y ago
  This is extreme. Why use a real-world example? Because people can relate to it. People have seen these types of plots. It could have been a completely fabricated example of an arbitrary hurricane in Florida or Canada or whatever - the point would still be the same. I feel like people are completely missing the point of the article. Also, my question is : what are the wrong lessons that this article teaches?
  - dmix 7y ago
    A whole lot of people who are the target market for this article would likely have experienced the same hurricane. Not giving the peanut gallery easy reasons for dismissal is something to be considered. It wouldn’t hurt but it’s not urgent like I said.
- 7y ago