u/counters

I am a bit surprised by this – it seems rather straightforward to log atmospheric pressure data with minimal missing data.

It's a significantly more challenging problem to collect and curate all of these observations than you're giving credit it.

Just a general question - why do you need full and complete 1-minute data? Except in certain extreme scenarios, pressure doesn't change that fast. You'd be more than fine just linearly interpolating over gaps assuming they're not terribly large.

In the past, similar events have provided transportation. I don't immediately see if those details are available yet for this trip on the Annual Meeting pages.

Kudos to you for trying something new... in this age of AI slop, it's refreshing to see new ideas.

One thing that makes the plots you've shared a bit challenging to read is the density of your latitude/longitude lines. Consider making this thinner (smaller stroke or linewidth), and possibly an off-grey color so they blend into the background. Or remove them when you depict continents or political boundaries.

I like the first plot you shared, with color-filled closed contours to depict high and low pressure areas. The variant that includes the quiver (plot 3) is also nice. One thing to consider there would be that the space between longitudes decreases as you get to higher latitudes, so even though you have denser glyphs, they're not showing more detail. Consider sampling and interpolating against a Gaussian grid to show the quivers - they will look a bit more "scattered" (in a very regular fashion), but will actually maximize the information they convey while minimizing the amount of glyphs on the plot.

Maybe you live in a more chaotic weather area.

Again - all Dark Sky did was interpolate and extrapolate blobs on radar. It has nothing to do with how "chaotic" the weather is.

I can't speak to the absurdly poor performance of Apple Weather. But I can speak authoritatively that every single app you see that offers a precipitation nowcast or minute-by-minute forecast is doing the exact same thing that Dark Sky was doing.

They've never worked well except in trivial cases.

Is there any particular reason you're trying to orchestrate triple or quadruple stops on a violin? It's a pretty advanced technique... you don't often see it in common orchestral repertoire. It's much more common just to divide a chord across a few lines and indicate divisi, that the lines should be distributed across the violinists in a section.

That's because all it was doing was interpolating the motion of blobs on radar. When a storm is five minutes away from you and has been moving in a straight line at a constant speed, it's a pretty easy forecast.

Virtually every single app since the mid 2010's has had the exact same feature. You just don't notice it because the community has rose-tinted glasses towards Dark Sky and grossly embellishes how useful and accurate it really was.

All good points, I appreciate your willingness to share your experience with today's NWS!

It's worth noting that a lot of young talent has been hired into NWS. That's great - everyone deserves a chance to build a career. But the NWS lost a lot of experience and we're going to be talking about that for some time.

Yes and no. There were two activities which led to a diaspora from NOAA:

1. "Probationary" employees were generally fired. In some cases this meant new employees within their first 1-2 years. In practice at NOAA, this impacted a lot of people who took on leadership positions (promotions and lateral moves trigger probationary periods).
2. Early retirement incentives caused many senior folk to opt to leave the government.

So not really "layoffs". Administrative actions which were short-sighted and ill-conceived and led to a significant workforce problem.

The well-known, long-running apps are about as good as they've always been; often a bit improved with new features and better use of available forecast data, including ensembles.

The problem today is that AI tools completely eliminate the barrier to creating an app, and too many people without any knowledge of weather forecasts are just wiring up OpenMeteo's API into these apps. So in all these new apps your'e seeing inappropriate forecasts for the context they intend to show.

DOGE did not cut funding to NOAA. NOAA's budget squeeze has come from the White House itself and partisans in Congress, but on the whole the loss in funding has been a bit below 10%. FY 2024 was funded at $6.72B, FY 2025 was effectively static under a full-year CR, and FY 2026 was down to $6.17B. The White House's proposed deep cuts down to $4.5B were rejected by Congress.

I'm talking about radar storm colors

Different apps use slightly differing color palettes for different types of warning products. On your Google Image search, if i remove "in red", I see significant consistency across products from the same issuer.

Anytime they just mentioned "strong severe storms" I'd see a lot of cells with red in the center

The "red" in the center of those cells is correlated with rain intensity, not with any other hazard. The criteria for a severe thunderstorm in the US is that it must be producing hail at least 1" in diameter and/or winds in excess of 58 mph. Weather radar doesn't directly detect these conditions; they must be inferred from radar products, ground reports, or expert judgment. Monster-looking thunderstorms on radar could be producing piddling impacts on the ground.

Sometimes they also say a tornado is possible in these, but don't issue a tornado watch scenario.

NWS meteorologists can tag additional hazards and how they have been assessed in the official warning text. If a storm is trending stronger, it's common for the warning to be updated with language about expected impacts. This includes tornadoes; a storm may not look like it is capable of producing a tornado on radar but expert judgment could assess that it's a possible outcome. A great example is embedded cells in squall lines; these can rapidly whip up weak tornadoes which might be obscured in rain. It's usually not appropriate to tornado warn every bend kink in a squall line, so often large area thunderstorm warnings which note the possibility of tornadoes covers the bases.

You don't need there to be an active tornado watch for a storm to rapidly and anomalously spin up a tornado. I've personally seen two tornadoes up close that were landspouts which coupled to a nascent cell and induced a mesocyclone. No warnings, no watches - just a landspout-turned-tornado out of the blue. In these types of situations, it's particualrly appropriate for the meteorologist to include a potential tornado hazard if its possible to happen.

I don't have Facebook and can't watch your other link. Unless it's a well-respected professional speaking authoritatively in a venue like a conference, I'm not inclined to take them at their word.

Is this the type of area where a strong personal portfolio can make up the difference?

Possibly. It would go a longer way at start-ups and smaller companies, especially ones that aren't necessarily lead bey veterans in the weather space.

The main data science and machine learning roles you mention, are you pointing towards mainly national forecasting services or small companies such as OpenSnow (with their ML snow forecast) or companies like Windborne Systems?

I would lump companies like OpenSnow and Windborne Systems together. You would be modestly competitive for NOAA / national lab roles; there are several relevant such roles at CIRA right now. A lot of national lab roles are serviced by contract shops; for example, Lynker has a ton of open roles right now that they're recruiting for. Many of these are to staff contracts they have with NOAA to operate different research centers or areas. They can be a great stepping stone if you're looking for a first role but they do not necessarily translate into a full civil service position with long-term prospects.

I am based in Europe but it seems from my research there is more opportunity in the US, does that sound like a fair assessment?

Ah, apologies - I've made assumptions about US/NOAA here. Unless your a US citizen those NOAA roles may be off limits. Unfortunately I'm not as familiar with the European job market. There is definitely an EU weather / climate startup scene though - I just don't know much about prospects there.

Also in junior forecasting roles would you assess it as a good place to start out?

My two cents is that if you have a deep technical skillset, pursuing just a forecasting role may not be the best choice. The technical world is moving so fast right now that stepping away from ML/data science style roles may limit your ability to jump back into that line of work in the future.

They don't.

 the weather media outlets have changed the severe forecast maps.

Prove it. All the weather media outlets I keep tabs with have used the same color palettes for upwards of 20+ years.

f you look at color shaded areas now, storms and forecasts that use to be yellow are now red or pink for example

Do you mean radar reflectivity animations? No one changes these. How are you certain you're not just looking at different types of storms? Darker reds into pinks, purples and whites are typically used for extremely high reflectivity bins where you're likely seeing returns from hail. How do you know you're not just comparing hail storms to other storms?

Issuing Tornado Warnings when they aren't on the ground 

The entire point of a tornado warning is to provide advance notice before it's on the ground. Different WFOs exercise slightly different judgment about when to independently issue a tornado warning or promote a severe thunderstorm warning. But you're complaining about the alerting system getting more accurate and realizing more lead time.

They make out the storms to be worse than what they are.

Prove it. Let's see a semantic analysis of severe weather coverage over time to demonstrate that people are hyperbolizing more.

I'm in Arizona and multiple news reportings of weather groups say "first Tornado Watches issued since 2010"

You're literally experiencing a once-in-a-decade weather setup today. But don't take my word for it. Look for yourself - here is a nice interactive database viewer that lets you pull up any watch/warning product at any WFO. Choose "Arizona", "Tornado", and "Watch". You'll see just how rare those products are for your part of the country.

Planning on writing my thesis around data assimilation and ML.

Cool. Then the good news is you're already specializing in what is pretty much the hottest topic in the field right now. Some headwinds that you should be aware of -

1. With just a Masters, you're not super competitive for model development roles, especially ones that use AI/ML. The more rigorous shops not only look for PhD-level candidates with significant research experience, but they've bended more towards specialists with research in AI/ML rather than generally in atmospheric science.
2. There seems to have been a pretty dramatic pull back in junior or entry level technical roles (other than forecasting) in the field. Depending on how long it is until your complete your Masters, you might be able to wait this out a bit. But just understand that a lot of the entry-level positions that folks would've recommended in the past around atmospheric data science or weather data engineering aren't typically available at the moment.
3. The overall hiring market is challenging.

If you have the bandwidth for it, you should try to see if you can get an internship with an interesting company in the space. The bigger weather companies have usually done blitzes to recruit talent like this around the time of the AMS Meeting in January (recruit for summer interns). You can also reach out to folks on LinkedIn to ask if their organization will have interns. It's not too uncommon to see interns matriculate into full-time hires.

The path is kinda narrow at the moment, but it sounds like you might enjoy some sort of modeling or "data science" role in or adjacent to weather. It probably offers you the most flexibility with what you want. Non-weather companies that have weather-related functions could be a good bet where there may be less competition or more openness to less high-level specialization/certification.

Plan on attending the AMS Meeting if you can to do lots of networking.

They don't.

Well, what do you want to do? It would be much easier to offer practical advice if there are some specific goals our outcomes you're interested in.

Severe weather watches aren't issued via automation from numerical weather models. They're subjective, human-over-the-loop products. Lapses in the quality of these products are indicative of the general staffing issues at NWS WFOs - not a result of degradation of our upper air backbone observations.

Give a specific example of a failed watch/warning process and I'll untangle it.

There is no evidence that current forecasts are suffering in skill or have reduced accuracy.

Ok. Then the short and very honest answer is that you would need a 4-year BS from a an accredited program whose meteorology or atmospheric science curriculum meets the GSA 1340 series. You are not eligible to apply for a meteorology role within NOAA unless you have a degree that meets that standard. The good news is virtually any reputable 4-year program will meet those requirements. The American Meteorological Society maintains an authoritative list of such programs. Note that a 2-year program likely won't suffice unless you have significant prior coursework in upper level mathematics and physics.

Unfortunately, getting a degree is the easy part. It's very difficult to get a job at the NHC or SPC. There simply aren't many positions available, turnover is slow, and the jobs are highly competitive because practically everyone wants those jobs. To bolster your chances of being competitive, you'll almost certainly need to pursue research experience in a topic relevant for the forecasting you want to do, which means at least another 2 years for a Masters degree.

It's also worth mentioning that modern meteorology is really critically dependent on computer simulations of the atmosphere. Meteorologist don't really "track conditions that are going to create a storm" - they see what the numerical models are saying about how the conditions will evolve, and then they use their judgment to discern across the different solutions they'll see across the modeling suite.

I expect this isn't really the answer that you wanted to see, but it's better to be informed before you make a significant decision that could impact your livelihood.

It's just a movie. But if you really want to play this game -

First off, those pipes would instantly snap from the force of a F5/EF5

How do you know the final twister was an F5? Are we inferring this on video-photogrammetry from the vehicles that it lofts or pushes over? Are those acceptable damage indicators to validate F5 strength? In fact - what damage indicators at all are we ever presented that indicate F5 strength? Surely, the outhouse structure that Hunt and Paxton shelter in would fail in far weaker in winds. Is aerial lofting of a fully laden tanker truck a damage indicator, or has someone done the calculation on the estimated wind speed that would be needed for that? I'm guessing it would be substantial, but I'm also guessing it would be horrifically unrealistic at all.

And we can't use the damage in Wakita as our DIs - in the continuity of the movie, Wakita was hit by a different storm. But that's definitely not F5 damage we see in Wakita as our protagonists are collecting aluminum cans to augment Dorothy.

If we take the film at the screenplay's word and assume the tornado was truly an F5, then I would expect that Hunt and Paxton would've had pretty gruesome industries related to airborne debris. Probably not something I'd have wanted to see in a movie theater.

What do you actually want to do as a meteorologist? More importantly - how do you know that's what you want to do? It might be much easier to find your way into meteorology-adjacent work (e.g. working at a company or an organization that deals with weather-related issues in some capacity) than to actually become a degreed meteorologist. And as an educator, you likely have a strong background and skillset that is transferrable to communications, project management and other things.

If your heart's desire is to be a forecaster, then the answer to your question is quite blunt - you almost certainly need another 4-year BS, unless you have a lot of coursework in advanced levels of mathematics and physics. You might make the requirements cut-off for one of the handful of online Masters programs in the domain (e.g. at Mississippi State University there is a geoscience masters), but I don't know how well a 2-year degree would prepare you for a job in this domain if you're truly coming from entirely out of left field.

But start at the top. What is it you actually want to do within meteorology?

Ryan is picking and choosing his words carefully and his also burying the truth here. "Re-focusing" here means "dramatically decrease the scope that GeoXO had taken on for climate and atmospheric composition monitoring to offset other programs (especially at NASA) that had been deeply cut in the first Trump admin."

I'll give Ryan credit for calling out the "decade setback" in forecasting skill. That's gross hyperbole.

But other aspects are just silly and bely his credibility. Like calling out Steve Volz, who headed NOAA/NESDIS until he was unceremoniously fired in the DOGE purges - you literally cannot find an individual more committed to advancing US weather forecasting and modeling than Steve. He's broadly mis-representing the sequence of events over the GeoXO planning period and mis-attributing who made specific decisions and when.

To be fair, the CNN article is also really bad. I'd expect a much higher standard from Andrew Freeman.

In this case, no, that's only part of the story. The Biden Administration hemmed and hawed a bit as the GeoXO and related missions really went into their critical planning phases, and gave inconsistent feedback about the scope of missions that ought to be supported. This was a major pain for both NOAA and Congress who really needed clearer long-term strategy.

The Trump Administration absolutely made things significantly worse, but the ball was already being fumbled before they came in.

EDIT TO ADD - I'm not sure why you're downvoting me. My day job involves working in and around these NOAA programs. There has been significant uncertainty since the early 2020's about how GeoXO and NEON would evolve given trends in industry capabilities and expected gaps in existing agency plans. You don't have to agree with the solution that NOAA is landing on - I certainly don't - but the time to register complaints about this was 5 years ago. Hell - I'm glad there is going to be any primary geostationary weather satellite mission, because I fully expected NOAA to cancel GeoXO entirely and completely switch to procurement of commercial weather data. I'm very glad that's not happening, but that was absolutely an outcome on the table here.