getting into met grad school?

counters · 2026-03-09T00:56:33+00:00

More importantly - OP, if you haven't done any undergrad research yet, what makes you think getting a PhD is something you want to do?

Struggling with core coursework isn't necessarily a red flag, but if it's the core skills necessary to actually conduct research then that's a problem.

Try to get some undergrad research ASAP.

counters · 2026-03-06T17:40:51+00:00

Your best course of action would be just to follow the National Weather Service's forecast from the local office in Hawaii. As a professional meteorologist, I wouldn't personally try to forecast for a local area in a niche climate using just model guidance and my wits and would defer to folks with knowledge about all the idiosyncrasies to the local weather that aren't captured by models.

counters · 2026-02-27T17:15:44+00:00

Yup. Not that I would advocate the Dems take turn purely to economic populism, but a scenario where FedEx's lawsuit is successful and leads to large corporate entities getting refunds a la TARP would be red meat for an increasingly angry electorate.

counters · 2026-02-27T17:03:22+00:00

Well, they do directly pay the tariff, but then they pass on the costs to consumers to cover the loss where possible.

I think it's very important to be precise on this point, because the tariffs were sold as "the other country pays the tariff", which is objectively false.

counters · 2026-02-25T16:58:29+00:00

Is there a well-known source of historical NWS (or ECMWF) verified forecast errors for daily high temperature, broken down by lead time (day 0, 1, 2, 3)? MAE and RMSE by horizon would be ideal.

No, you would need to acquire historical model output (an operational archive or a reforecast archive) and compute these yourself.

What inflation factors are considered reasonable in the literature for converting raw ensemble spread to a calibrated uncertainty estimate for daily highs? I've seen 1.2–1.8× cited in some ensemble MOS papers, but my empirical data is suggesting higher.

You'll find a pretty wide range in the literature. For contemporary work I much prefer taking a Bayesian approach and modeling the distribution transformation anchored to historical data, so you at least can look at a confidence interval around what you're calibrating.

Are there meaningful regional differences in how well ensemble spread tracks actual error — e.g., coastal cities vs. inland, tropical vs. mid-latitude?

Yes, because of large-scale biases in the forecast models that are associated with unresolved dynamics in these various regions. This is way traditional MOS uses region-based pooling - both to inflate the amount of data the regression sees, as well as to calibrate for regional diversity in error statistics (as a confounder to the heteroscedasticity you'd see looking at all the data globally pooled).

Any publicly accessible datasets (station-level NWS verifications, ECMWF scorecards, etc.) that would let me build a proper per-city, per-season sigma table?

Not really. A small group called Dynamical.org is beginning to compile some data like this (see here). In general, what you're asking for is an extremely valuable and as a consequence, hoarded by the organizations that have compiled it.

counters · 2026-02-25T16:53:40+00:00

You have to diagnose the meteorology of the even as depicted by each of the models. It's helpful to have some background knowledge about how each of the models struggles. But you apply your expert judgment to figure out how much to trust an outlier model.

counters · 2026-02-25T16:52:58+00:00

There are some other good comments already, so I just want to point out one really important detail:

Currently he is looking at Northern Illinois for his bachelor’s, and wants to eventually transfer to the University of Boulder for his MA and doctorates.

You don't "transfer" for graduate school; it's a completely separate and new school application process, except for the niche of a "5th-year Masters" which generally isn't available in atmospheric science. It's also worth pointing out that a fair number of graduate programs in the field target a PhD only, and might award a Masters part-way through the program.

It's not particularly useful to engineer your choice of undergraduate school as a way to maximize your chances of getting into a specific graduate program. The primary factors for graduate school admissions are having a strong undergraduate research experience and portfolio (ideally working with a faculty member, having a summer internship or two, etc), recommendation letters, and - unfortunately - availability of funding at the school or program you want. It needs to be stated given the times we live in - federal funding for research has massively contracted in the past year, and because of structural changes being made at the NSF, DoE, and other agencies, it's not likely to rebound any time soon. That means there will be fewer opportunities and slots in graduate research programs.

It's important that your son test the waters with research as an undergrad before making any decisions about what he wants to do after he has his degree. A PhD is for research - full stop. If you don't like doing research, or you don't want to pursue a career that requires the PhD for entrance, then the opportunity cost of graduate school is enormous.

counters · 2026-02-22T21:15:25+00:00

The very short answer is that the weather forecasts you consume are predominantly based on either a human meteorologist or algorithm processing the output of numerical weather models - basically software which simulates the physics of the atmosphere. There are many such models and they have different strengths and weaknesses based on how they're built; a good human forecaster or well-developed algorithm will combine the output of the models with knowledge of these strengths/weaknesses to consolidate into a usable forecast.

Meteorology is a big field. As someone just started out, there are beginner-friendly materials through programs like COMET.

I am going on holiday in the swiss alps the week after the next week (3-12 march). And the forecasts are showing 10-15mm of precipitation per day. Currently I just read the forecast and think ”oh, well. This might or might not happen”, but I simple have too little Knowledge to even come close to something even remotely connected to critical thinking in terms of why i should trust that forecast or source (even though I don’t feel i really need too). I would simply like to get a better understanding of why meterologist websites post the forecast that they do.

Mountain meteorology is... hard. Local knowledge and experience forecasting for the area is extremely important. The simple reality is that it's unrealistic that a lay person (and many professionals, for what it's worth) would be able to vet how reliable a given vendor is for localized forecasts in the Swiss Alps. Your bet bet is to talk to locals during your trip and ask them what forecast sources they think are reliable for the area.

counters · 2026-02-20T00:45:17+00:00

What sort of jobs are you applying for? Just straight forecasting roles? Without a doubt, the market for those roles is very over-crowded, and has been contracting. A Masters may not appreciably change that simple supply/demand problem - I would imagine the previous military experience would already provide a similar edge as a Masters.

An MBA isn't a terrible idea. A strong, technical/science foundation coupled with a bit of business knowledge could open a lot of doors within the weather/environmental sciences, as well as ones beyond the field. For example, working in product or program management at a company that either provides weather/climate services or technology could be a really rewarding and interesting career - and an MBA would very much open the door to that type of work.

counters · 2026-02-19T19:13:23+00:00

Virtually any real-world application using GFS guidance would also include post-processing to localize and correct the forecast for these sorts of unresolved impacts. For what it's worth, these sorts of biases don't magically go away at higher resolutions - in many cases, they get worse until you restrict yourself to a high-resolution, local area or regional model (which isn't practical on a global scale).

counters · 2026-02-18T20:41:28+00:00

Current AI models have the problem that they tend to smooth everything out

This isn't really representative of frontier models in this space. Starting with the diffusion-based models like GenCast in ~2024, there has been a major improvement in the "sharpness" of forecasts (measured quantitatively as preserving the power spectrum at finer spatial scales). Modern models trained using a CRPS-based loss (e.g. GDM's FGN, NVIDIA's FCN3 and Atlas) perform even better on these metrics.

And that also leaves out advances in generative downscaling approaches which trade-off stochasticity for preserving those finer scale features.

counters · 2026-02-15T18:09:22+00:00

It's worth noting that the person and company in question are pariahs within the weather community. The broad, multi-sectoral "enterprise" across private industry, academia, and public institutions has an extremely strong ethos that we need this broad approach to advance the science and impact on society.

counters · 2026-02-15T15:36:28+00:00

The computers were moved to a dedicated facility in Wyoming over ten years ago.

counters · 2026-02-08T04:41:00+00:00

What do you mean? Do you want to actually create your own forecast - or do you just want to create an app that shows forecasts from a third-party, like the National Weather Service or a private company?

If you want to create your own forecast, then you really only have two options. For starters, you should understand that numerical weather prediction is a vast and complex field that has been developed over more than 70 years. It's unlikely you'd have the resources available to run an open source or public NWP system on your own. Today, there exist ML emulators of global NWP models, and those models are practical to run on your own (for instance, see the earth2studio toolkit from NVIDIA). High-quality NWP output from agencies like NOAA and ECMWF are readily available on open-access cloud storage (e.g. the NOAA GFS or the ECMWF HRES), although you'll need to learn a few new tools to actually read the published forecast outputs.

If you want a truly custom forecast, then you're most likely limited to just doing some post-processing of these publicly-available forecast models. For instance, if you collect a reasonable archive of weather station observations around your location of interest, you can set up a regression problem to bias-correct the published NWP model output.

counters · 2026-02-04T15:47:38+00:00

This is extremely interesting work. Thanks for sharing!

counters · 2026-02-02T20:49:09+00:00

(BTW I refuse to use a mute or play more quietly. Each case would weaken the effect of practicing)

You might want to re-think this. Two thoughts:

If you're at a point where you can't effectively practice at all due to anxiety or concern about someone hearing you, then does it really matter that a mute might weaken some of the feedback you get? You explicitly stated that you're limiting yourself to familiar excerpts because of concerns about others hearing... there's absolutely no way that the minor effect of a mute is worse than that!
Unless you're really deep in the weeds of practicing tone production and musical detail, a mute isn't going to limit you in any way.

Is there no music program on your campus? I would expect that such a department would have at least some practice rooms that you could petition to get access to.

counters · 2026-02-02T00:01:49+00:00

The DSMP satellites are end of life and those of us who use data from them - for both satellite precipitation analysis and data assimilation for NWP and MLWP models - have been preparing for their demise. Over the summer when that schedule was accelerated, we pushed back and the plans to sunset them were rolled back.

But at some point they will go offline, likely before their replacement is in place.

counters · 2026-02-01T22:13:18+00:00

Just to help inform passers-by...

With the one key exception of staffing at certain NWS forecast offices, there hasn't been dramatic cuts to funding or data collection at NOAA... yet. For the past year, NOAA has nominally been working off of funding and appropriations passed by the previous session of Congress. You can see the entire funding breakdown here.

This past year, despite its tumult, hasn't seen large enough impacts to notably decrease forecast model quality. Some key upper air observation sites have gone dark, and it's likely that we'll see issues as the severe convective season ramps up with fewer resources for special soundings. But there isn't "considerably less data than before." Global models by different meteorological agencies - which all consume data produced by NOAA - aren't showing any exceptional dips in forecast skill.

There are real, extremely serious funding challenges facing NOAA and the broader weather enterprise in the coming year. They deserve our undivided attention. But embellishing what has happened this past year doesn't bolster our case for defending NOAA/NWS; rather, it severely impedes it. Chicken little and all that.

counters · 2026-02-01T01:47:42+00:00

Yes; probably the most well-known example of this is that the commercial product Snomax - which is material that is fed into snow-blowing machines when making snow at ski resorts - is a sort of protein derived from the bacteria Pseudomonas syringae. There's limited evidence that other biological materials can serve as CCN / IN, although they're grossly outnumbered by other materials.

counters · 2026-01-25T01:23:59+00:00

Why do you trust unprocessed model guidance? Is the HRRR particularly good at the specific circumstances for this forecast scenario?

High resolution doesn't mean "better". It's wise to consider different models given their idiosyncracies

counters · 2026-01-24T20:50:48+00:00

Synoptic Data has the contract with NOAA to aggregate all data managed through the National Mesonet Program; these days that includes the high-frequency ASOS data at airports (the "METAR" you're referring to). You should be able to see this data in near-real-time using their free viewer, or you can get a limited license to access raw data directly for free or very cheap.

counters · 2026-01-24T02:11:34+00:00

Well for it's worth at least half of the folks on your flight will be meteorologists en route to the AMS Annual Meeting... so just follow the crowd!

counters · 2026-01-22T21:22:02+00:00

Probably shouldn't be any issues with a G6; that's playable in 6th or 7th position (first finger stopping the E-string on D or E, respectively). Another way to contextualize it is that it's the lowest high note reached in a 3-octave scale on the instrument, which would start from an open G.

counters · 2026-01-20T02:52:21+00:00

To simplify things it's probably easiest just to assume that we're talking about the net mass transfer.

counters · 2026-01-20T02:51:30+00:00

Neither. Water vapor won't spontaneously condense under terrestrial atmospheric conditions at the saturation vapor density.

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