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Comment by devindotcom

12 hours ago

i think calling it "subjective opinion" is kind of disingenuous. it is a subject matter expert interpreting the data. there is a vast gulf between that and someone else simply offering their opinion on the matter.

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devindotcom

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throwaway27448  10 hours ago

"Subjective" and "objective" are well-defined terms. Perhaps this misleads the reader about expertise, but it is not objective.

Theodores  12 hours ago

I worked in weather for TV as a technician and I was lucky enough to work with meteorologists. I thought they were high priests in the church of science, however, I detected a gambling mentality going on.

I was just surprised at how subjective their work was, with differing opinions regarding the big picture depending on whom you asked and what their background was, as in university, whether they had worked for the navy or whether they had worked for the government.

The big surprise of the gambling mentality reminded me of people that dedicate their lives to losing as much money as possible betting on horses. These people know the form, the weather and so much, yet they do their own bets.

It was kind of the same when working out what the weather would be in Springfield tomorrow. Would it just be cloudy or actual rain? That would be a 'bet'.

The next day the observations would come in and the meteorologists would either win or lose their 'bet'. The guy who has been to Springfield and knows the local geography well would have his own reasons for his 'bet', whereas the guy who was more interested in long term storm development would have another rationale for his 'bet'.

Then there would be 'wrong all the time me', able to look at the low level cloud from contrails (which are really huge in some wavelengths on the satellite pictures) to assume rain every day.

Hence climate and weather is highly subjective even if it is highly educated and vastly experienced professionals that are interpreting the data.

  • HerbManic  12 hours ago

    There is also the additional issue of computer models constantly chasing global changes. About 10-15 years back I used to talk with folks that worked on weather modeling and they were in a state of frustration in that as soon as they could make models that could work on older data sets to do reasonable predictions, the global weather patterns had change just subtly enough that it made them just kind of average on forward predictions.

    This was right before GPU compute started to become a big thing, I do wonder if they now use machine learning models on these to speed up model iteration? I would hope so, but even then there is the human factor as you said. Eventually someone has to make the call on what the data shows and how to present it to the world.