weatherwiz

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.

Agree, this is a big player I believe. I don't know a whole heck of a lot about the basic blueprints of forecast models (the math/physics, different schemes...I'm hoping that may actually be covered in my advanced forecasting class) but I do know this Data assimilation and being able to properly and accurately parameterize are detrimental to the success and accuracy of a forecast model. This is what made the euro superior for all those years, the euro had superior assimilation and parameterization. This is exactly why I am not sold on AI yet. We need to drastically improve these capabilities and this is where (hopefully) quantum computing is going to come a long ways.

I could see AI being heavily influenced in thinking because you have a nrn stream moving in and srn stream coming up the coast that there will be clean phasing. Like Runnaway said, maybe there is also resolution at play here..or something to this degree? I mean the vorticity field almost seems "too smoothed"...too clean.

Very well could be too expansive.

It will eventually hit one after 1000 tries and then everyone is going to get sucked into it because it finally got a hit and ignore the other 999 misses

The AIGFS doesn't seem too drastically different from the 12z OP run yesterday in terms of the H5 evolution, both srn stream and nrn stream.

nahhh that would be more if we had model consensus for a big hit now, only to see the rug get pulled out from under us as we got closer

Neither did Bears fans entering the 4th quarter. Let's Chicago Bears this thing

He probably prefers to keep his sanity

I enjoy his tweets. He definitely does not hype and is pretty straightforward. I really enjoy his posts during convective events

Yeah I don't think there is any convective feedback issue going on here...hardly any, if any, convection with this anyways in the Southeast

Agreed...I think it's going to be until Friday or Saturday before we have a true gasp on the 500mb evolution.

Sick One of my classes this semester, Advanced Forecasting Techniques will cover winter weather forecasting including long range/seasonal forecasting and teleconnections

Hopefully Tyler Loop isn't kicking

I think at this point we would need to see some sizable adjustments from the Euro (which I don't see happening) with the 0z run tonight if we want to talk about potential for widespread warning criteria. I guess we wait on the EPS now

It was looking *slightly* promising between 90-96 hours then went to hell