this post was submitted on 02 Oct 2024
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The National Oceanic and Atmospheric Administration (NOAA) cannot reveal weather forecasts from a particularly accurate hurricane prediction model to the public that pays for the American government agency – because of a deal with a private insurance risk firm.

The model at issue is called the Hurricane Forecast Improvement Program (HFIP) Corrected Consensus Approach (HCCA). In 2023, it was deemed in a National Hurricane Center (NHC) report [PDF] to be one of the two "best performers," the other being a model called IVCN (Intensity Variable Consensus).

2020 contract between NOAA and RenaissanceRe Risk Sciences, disclosed in response to a Freedom of Information Act request by The Washington Post, requires NOAA to keep HCCA forecasts – which incorporate a proprietary technique from RenaissanceRe – secret for five years.

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[–] hessenjunge@discuss.tchncs.de 25 points 1 month ago (1 children)

Sorry, what a shit, rage bait article is this?

… it was deemed in a National Hurricane Center (NHC) report [PDF] to be one of the two "best performers," the other being a model called IVCN (Intensity Variable Consensus).

OK, what about IVCN? Is this available? We can assume it is as is not mentioned any more in the article. Also skimming the report it’s not like the other reports are wildly inaccurate/unusable.

Asked whether the NOAA deal affected the release of information about Hurricane Helene, Buchanan said, "HCCA is one of many computer models that forecasters use at the National Hurricane Center. NHC forecasters use a variety of model guidance, observations, and expert knowledge to develop the best and most consistent forecast, along with watches, warnings and other hazard information for use by the emergency management community, the public, and other core partners and decision makers."

So the outrage is hot air over nothing. Got it.

[–] crapwittyname@lemm.ee 20 points 1 month ago (2 children)

It seems the outrage is over this part:

the public that pays for the American government agency – because of a deal with a private insurance risk firm.

Which is, on the face of it, outrageous. American public pays for the modelling but isn't allowed to benefit from it because an insurance company wants to keep the data secret.

[–] Atrichum@lemmy.world 9 points 1 month ago

The public does benefit from it because the people who's jobs it is to protect the public have access to the data.

We're getting our monies worth, especially if you've paid attention to how accurate hurricane tracking and intensity models have become over the past 10+ years.

[–] hessenjunge@discuss.tchncs.de -5 points 1 month ago* (last edited 1 month ago) (1 children)

Sorry, did you mean to reply to another comment? There is no reflection whatsoever to the comment you are replying to.

Edit: As this comment has whooshed at least 6 people:

it is very very very obvious that the article tries to manufacture outrage over one prediction model that is not publicised but avalable to the agency.

I pointed out that there is one other, equally good model unrestricted and there are about 20 other models that are equally not listed as restricted. Again, the restriction refers to publicising, not to government usage.

I hope this helps the understanding of crapwittyname@lemm.ee and his friends as I don't think it makes sense to break this down simpler.

[–] crapwittyname@lemm.ee 0 points 1 month ago* (last edited 1 month ago)

The above comment is more applicable to itself than to the comment to which it refers, weirdly. It's a sort of extra-ironic, self unaware recursion.
Edit: your edit doesn't fix anything. You claim the outrage is over nothing. I then explain what I think the outrage is over, you then claim that my explanation is somehow unrelated. You then edit, saying that people shouldn't be outraged, because of an opinion you have. I'm getting an aggressive vibe from the way you are writing, so maybe it's better not to engage with you, but at the same time I'm curious why this fairly dry, non divisive topic has you so vehement.