weatherwiz

If non AI models were a big hit and AI models were a non hit, would the mindset be the same?

It's also probably start time to prepare for May 1st. You all may laugh but there is alot of mental and physical preparation that goes into getting ready for May 1st. Preparing the mind and then getting in touch with the inner soul.

blah not was I was hoping for. Well I guess this system has about as much shot as any team not named the Dodgers of winning the World Series for the next 5 years

Agreed, a shift to that extent is going to be a very difficult task if we don't see some significant improvements by 0z tonight. If I were in eastern areas though I think I might feel a bit better about this because the shifts needed will be much less. It's really hard to go one way or another with this because we have seen some pretty drastic shifts with the handling of that northern stream energy and how it interacts with the southern stream

I actually wonder if we may see a few decent hits on the GEFS...I think if we can at least see some decent hits that should be enough to keep the idea alive that we could see some favorable trends in the next day. If the GEFS is pretty meh though...that combined with a subpar Euro might be enough to make for a nearly flat heartbeat on this

Yeah this isn't going to do it, however, should get at least light snows across a chunk of the region. Would have preferred to see a much better look here but I don't think it's a bad enough look to lean in the direction of not happening.

Just looked at 0z/6z models for second half of the week and holy hell what a disparity. I will say though and I think I mentioned this the other night...that is one powerful Arctic front slated to drop South and I would find it hard pressed not to see at least one major winter weather event impact a large geographical area. I think the biggest question is going to be the timing...does this happen during the second half of the week (similar to the 6z GFS) or does this get pushed back say 2-3-4 days? I would definitely watch anywhere from the mid-South into the Northeast.

In reality, I would not put much stock into any meso model and not just because we're outside of the range they are useful for, but they are not particularly good with phasing events and aren't really designed for them anyways.

Just thinking to myself...is it a precursor the one model you would expect to go bonkers not doing so

Wow pleasant surprise with the overnight guidance. Given the time frame we're entering hopefully those trends are an indication of where we're headed. Definitely want to see the Euro with a bit of a bigger shift at 12z. Still need a bit of work but its doable at this range.

This is how I feel with the severe weather threads

What is this obsession with Nemo

Was the one high risk…feels like forever now but maybe 2019? People were going insane because the HRRR was going bonkers with these warm sector supercells and I think a high risk was issued and virtually nothing happened. I think after this it became apparent the HRRR had a bias for supercells south of the warm front well away from any forcing

Meh I used to kick my feet up on the desk and fall asleep and fantasize

Probably results in a few inches of snow within GA and parts of the Carolinas and at least mixing into the FL Panhandle

Agreed on this

Precisely, developed to model exactly what's possible in the atmosphere, a skilled forecaster will use fundamental knowledge of meteorology, principles, and historical knowledge to make an educated forecast on how likely "possible" is

Yeah that would probably be a big ask given the Nina state. I guess what we could hope for is a big storm as that pattern developed and then something else as it reverted back...then take our chances with the gradient.

The other thing too is there is a ton of money in AI...lots of money. When it comes to technology, it's so easy to sucker people in...I mean look how so many people go bonkers when the new iPhone comes out or some new high tech gadget. But if you're in the development of AI...you can easily sucker people in and make a boat load of money.

Wouldn't mind seeing that moving into February. You want to talk about the prospects for a big February, there is the look right there. Ultimately, I'd like to see that ridge axis shifted east a bit and tilted a bit more directly poleward...but this is an ens mean so that detail is a bit minute but something to watch for when we get into OP range

Excellent post. Understanding models (strengthens and weaknesses) is vital to forecasting success. Ultimately, forecasting is much more than just looking at the output of a model or comparing a few products. A forecaster should always be asking themselves, "does this output makes sense given the pattern"...obviously when dealing with a time range beyond 3-4-5 days there is always, always going to be a degree of uncertainty, however, asking yourself that question and working through the details to answer that question can provide enough of a basis for a forecaster to determine with confidence, the likelihood of a scenario occurring. I'm with you, the ceiling for AI should be that of current NWP and I think it should be thought of as AI being a compliment to current NWP. For example, if AI can do a better job at assessing the current state (initialization) and more quickly, integrate this into NWP. I believe this has always been done (again, a reason Euro was superior for a while) but with the advancement in technology this could vastly improve NWP. For your response to Scott, that is a very underrated understanding regarding re-analysis datasets. I think we take them at too much of a face value but need to understand there are limitations with them as well. For example, if you look at the ERSSTv6 and compare it to v5 and previous versions, you can see there are some large discrepancies in various areas of the globe, particularly earlier days when much of the re-analysis outside of ship routes was created via extrapolation methods.

As stated the idea of they're supposed to "learn" is totally overblown. Traditional models already have some AI built into them and already do this to an extent. From what I understand (and this may not apply equally to AI models) is AI assists with the initializing scheme whereas it combs through ingested data and will "remove" what it believes to be bad data or an outlier based on a slew of historical information. The goal here is, or the idea is, this will lead to a more accurate initialization which is important because once you move forward in time you start to introduce error and that error becomes compounded over time...that is why forecast models (OP) are generally useless beyond D7-10 and can even be relatively useless past D5 if there is alot going on. Error also occurs because of rounding and approximations, especially approximations. AI models are built on a wealth of historical data where it runs and looks for similarities, both to the initialized field and then forecasts based on how these similarities evolved in the past. The challenges in all of this is, there is still a lot we don't understand about weather, particularly when it comes down to processes which occur during storm evolution and it becomes even more of a challenge because for forecast models to ingest this data we have to be able to parameterize it. There is much more to this then just verifying a specific level or variable and even that leads to a lot of questions. Probably in a tame weather pattern that is not hostile, AI will outperform but what good is that or what value is that really adding?

This should be pinned at the top of the board As I've also mentioned before, AI can probably be very useful in the nowcasting department or short-term (6-12 hours) but beyond that...a very long ways to go

Yup...like I mentioned the other night it will be active upcoming. May not see stuff pop up on the SLP charts but its an active look with plenty of shortwaves

I don't believe all of the AI models have physics built in. I would think the NCEP AI models do, but that is how some of them are able to process more quickly and roll out much faster, the model doesn't have to perform calculations.