The thread keeps circling around the politics, but almost nobody has dug into what actually goes on in the NWS tornado warning pipeline.
It's worth being specific: the National Weather Service operates some of the most robust automation and radar ingest pipelines on Earth, but the final go/no-go warning call is almost always human—often a single overnight forecaster on a console, monitoring a swath of counties. Automation (e.g., Warn-on-Forecast guidance) can surface threats, but the NWS intentionally doesn't have an 'auto-warn' button for tornadoes, because of the asymmetry of false positives (blow credibility, cost lives in the long run).
Budget cuts reduce redundancy and experience in those overnight shifts. When you have only one person monitoring instead of a team of two or three, you get decision fatigue and coverage holes, especially during clustered, multi-cell outbreaks. We've seen near-misses in the past, and every pro-meteorologist I know says they're playing defense against process errors, not just technology failures.
Before we point fingers or blame 'technology/automation' shortfalls, let's quantify the concrete bottleneck: skilled human decision-makers are the limiting reagent; machine learning warning aids are still years away from majority trust.
>Before we point fingers or blame 'technology/automation' shortfalls, let's quantify the concrete bottleneck: skilled human decision-makers are the limiting reagent
All the automation in the world with useless without a human guide to either transform production into a useful product, or useful knowledge to heed. That's why this act of trying to remove human labor is asinine. Even skilled human can't always get the right readings, so expecting a robot to do it all at this stage is just selling snake oil.
Actually, I'll go a step further - in the long run, we probably won't need human forecasters at all.
The current human-in-the-loop model exists largely because our technology hasn't been good enough yet, not because there's something inherently special about human judgment in this context. Weather prediction is fundamentally a pattern recognition problem. Pattern analysis at scale is exactly what computers do better than us.
Chaos theory and brownian motion make it a herculesn for anything to predict the weather more than a few days out. There's too many micro factors to track leading to weather that constantly shifts. And The data costs to attempt to try to do so is well past even the most well compensated meteorologist.
I'm not too worried about the human factor being replaced as a whole here. Even with AI, someone needs to interpret the output and make sure the the prediction models actually work.
yeah why cannot that guy sit in california or new york in a normal time zone? not like there are tornadoes in every state, its so silly to keep a person at night in an office when weather is good
There's only a 6 hour different between the East coast and Hawaii. You can't entirely avoid a night shift, so you might as well have them all work from the same location.
Fortunately the Kentucky NWS office in Jackson was fully staffed during the recent events. It's still not staffed 24/7, but at least they bring in people when things inclement weather is occuring.
They may have been been "fully staffed" according to the "new" "fully staffed" number which could be not enough to perform all the duties and responsibilities reliably and without disruptions. I've been on teams that ought to have 5-10 people minimally wearing all the hats but are only by budgeted for and allow 3 by upper management. Those teams, according to the decision makers are fully staffed, even though they are inadequate.
Edit: and during death marches those can be worked overtime on weekends to make a deadline. They're "fully staffed" and work for the short-term until burnout and turnover begins. Then those projects are always behind.
This seems entirely plausible, but I'm not sure this article successfully makes this connection with direct evidence. Has anyone seen anything on this with better evidence?
NYT mentioned NWS staffing shortage, but did not say this was connected to body count:
"The office is also one of several left without an overnight forecaster, but on Friday, it stayed open and was sufficiently staffed for the night, issuing 11 tornado warnings. It was “all hands on deck,” Mr. Fahy said."
That's because no one can make that conclusion definitively yet. They want your brain to assume that connection. Conspiracy theorists are the kings at this psychological trick.
> That's because no one can make that conclusion definitively yet.
There's a problem here though: if things do eventually deteriorate (which, admittedly, there is a change will not happen), it may be too late to fix things.
If things get broken they are broken, and in this case you have risk of people's lives. And the people who did the jobs that were fired have probably moved on because they have bills to pay. If you can realize your mistake quickly enough, you can fix it quickly. This is what happened when the Very Stable Geniuses fired the folks who maintained US nuclear weapons:
Perhaps instead of l33t h4ck3rz in DOGE they should hire carpenters or woodworkers: people who, instead of a mantra of "move fast and break things", live more by "measure twice and cut once". Some measure of where the (alleged) waste is could be useful before cutting.
I agree that DOGE is bad. But I also think it's unhelpful to claim evidence of a bad outcome directly caused by what they've done. It muddies the water and bolsters people who want to argue that people are only criticizing them out of bias.
If it's true that they got all the tornado warnings out because they were able to be "all hands on deck" for a night they knew would have high risk, then I think this just isn't the example of DOGE getting people killed that the article wants it to be.
I fully believe that understaffing these offices could get people killed. But we don't need to claim it did until it does.
And that doesn't mean we should wait for something awful to happen to criticize the risky situation!
That's mostly the thing with safety measurements. If they are there you do not recognize them and if they are missing and something happens it's hard to proof if it would have changed anything.
Thanks! The information here is why I think it's extremely plausible that staffing shortages were disastrous here. But it also doesn't make the direct link. I think it's probably just too soon to know whether all the warnings went out as they should.
But another problem with our current government is that I'm skeptical any investigation to answer those questions will ever happen.
Sadly anyone with a a half of a brain saw this coming. To add to this, FEMA cuts probably means these poor people will live through what Puerto Rico did when the island was wiped out years ago by that hurricane :(
I wish they could sue Trump and Musk personally for making dumb decisions.
>The FEMA report found that its warehouse in Puerto Rico was nearly empty when Hurricane Maria hit last September, without cots or tarps, and very low levels of food and water, as most of the supplies had been rerouted to the U.S. Virgin Islands following Hurricane Irma.
Yeah, so how did a massive agency with plenty of money (over $30 BILLION annually) not immediately begin work to restock their Puerto Rico warehouses immediately after some of the supplies were sent to help with hurricane Irma?
That's roughly $1.5 million per employee of FEMA, so they should have plenty of funds after personnel costs for buying and transporting whatever emergency supplies they need.
That's a good point. Have you tried to get an answer to that yet? For me it works out quite often to look for a reasonable explanation when something sounds unreasonable in first sight.
Part of me doesn’t feel too much sympathy. The majority of Americans voted for Trump. Even more so in the conservative states that are more likely to be impacted by there events.
Trump campaigned on cutting government services.
Everyone is okay with cutting a public service (at the expense of others) until they need that particular service
---
To clarify, I'm not cheering on this disaster or hoping that those who voted for Trump "get what they deserve"
In states like Kentucky a d Oklahoma? Think again. These places are overwhelmingly trumpy. The nation as a whole barely voted him in, but in many red states his numbers are very high. My home county in Tx voted 80% Trump.
But you're focusing on small counties, essentially "land that votes".
One metro area generally outweighs 90% of the counties in a state.
Take Oregon for example. Look at eastern Oregon where trump ran away with like 80% of the vote. But then you look at population numbers for those counties and you'll quickly realize that ONE NEIGHBORHOOD in Portland has 5x as many residents as that entire county. One neighborhood in Portland actually has more people than most of Oregon counties. It's kinda wild how empty they are.
The fact is that conservatives are pretty outnumbered. Which is why conservatives disenfranchise voters and rely on gaming the electoral college. It's also why conservatives tend to move to where other conservatives live, among other reasons. If people showed up to vote then Republicans would lose elections way more often.
But looking at a map and seeing red counties is not "more people voted trump". It's just "sparsely populated counties voted trump" which is not the same thing.
There's a subreddit called "People Live in Cities" that makes fun of this misinformation tactic. It's just maps that show where people live, but cite other metrics.
Every county in Oklahoma, including the ones containing their cities, went for Trump in 2024. What you’re saying is often true, but GP is exactly right about some of the midwestern states.
Of all the states Oklahoma is certainly one of them, however its 4 million people aren't even 2% of the total US population.
Cherry-picking aside, the victory margin in the 2024 election was the smallest in over five decades, only the 2000 and 2020 elections (where the loser of popular vote was able to seize power on technicalities, they had negative victory margins) were smaller.
Politics aside, it’s odd how often the entire debate misses the real bottleneck: assigning blame doesn’t restore operational capacity or re-architect the warning pipeline. If the system depends on 24/7, highly skilled human decision-makers, and you cut those positions, the outcome is predictable—slow, brittle responses.
ANY critical pipeline that can be broken by one missing seat is overdue for technical reinforcement
Unfortunately, a lot of liberals live in these states too. This entire country would be blue if we didn't have the electoral college.
But if you're in the mood for not feeling sympathy, because most cities have heat domes that tend to "push" storms away from them, storms tend to leave the more-liberal cities alone and instead wreak havoc through more rural towns.
Welcome to 2025, where we gather the family around a glowing laptop watching Ryan Hall Y'all and his YouTube channel telling us when it's time to take shelter.
Right up top. The service for alerts no longer works 24/7 so this happened when they were down for their daily window. Therefore the cuts are directly responsible.
It's worth being specific: the National Weather Service operates some of the most robust automation and radar ingest pipelines on Earth, but the final go/no-go warning call is almost always human—often a single overnight forecaster on a console, monitoring a swath of counties. Automation (e.g., Warn-on-Forecast guidance) can surface threats, but the NWS intentionally doesn't have an 'auto-warn' button for tornadoes, because of the asymmetry of false positives (blow credibility, cost lives in the long run).
Budget cuts reduce redundancy and experience in those overnight shifts. When you have only one person monitoring instead of a team of two or three, you get decision fatigue and coverage holes, especially during clustered, multi-cell outbreaks. We've seen near-misses in the past, and every pro-meteorologist I know says they're playing defense against process errors, not just technology failures.
Before we point fingers or blame 'technology/automation' shortfalls, let's quantify the concrete bottleneck: skilled human decision-makers are the limiting reagent; machine learning warning aids are still years away from majority trust.