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First Legit Storm Potential of the Season Upon Us


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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.  

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36 minutes ago, ORH_wxman said:

Yeah that’s actually a tick worse than 06z. No difference to us, but at least 06z was getting outer Cape and islands into decent stuff. 

man... this all happened when that relay took place overnight with the GFS. 

this is also about when it finally pulled the plug on this event today, too ... right when I observed the ballast of the S/W mechanics were over land

i'm growing more and more convinced that the data assimilation is getting caught with its pants down.

i'm also beginning to suspect we are exposing an explanation for the mysterious mid range amplitude loss that seems to be pretty dependable - altho i see that in other guidance, too.  

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22 minutes ago, RUNNAWAYICEBERG said:

The AI versions must run on less resolution kind of like what the regular models did back in the day. The precip and qpf fields are broader but to me they may be handling the upper levels better as a result. IDK, just my observation…

Yeah I think it's about 28km depending on latitude. And the lack of model physics would also contribute to smoothing since it's using purely statistics and averaging.

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Just now, Typhoon Tip said:

man... this all happened when that relay took place overnight with the GFS. 

this is when it finally pulled the plug on this event today, too.  

i'm growing more and more convinced that the data assimilation is getting caught with its pants down

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.

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6 minutes ago, eduggs said:

Yeah I think it's about 28km depending on latitude. And the lack of model physics would also contribute to smoothing since it's using purely statistics and averaging.

Aren’t the physics built in?

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3 minutes ago, weathafella said:

Aren’t the physics built in?

I don't believe the AI models use physics equations (mass, momentum, energy etc). But they are indirectly built in based on the training sets they incorporate (e.g., GFS/ECMWF).

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16 minutes ago, Typhoon Tip said:

man... this all happened when that relay took place overnight with the GFS. 

this is also about when it finally pulled the plug on this event today, too ... right when I observed the ballast of the S/W mechanics were over land

i'm growing more and more convinced that the data assimilation is getting caught with its pants down.

i'm also beginning to suspect we are exposing an explanation for the mysterious mid range amplitude loss that seems to be pretty dependable - altho i see that in other guidance, too.  

This makes a lot of logical sense to me. Even though I don’t have any expertise, you’ve explained it in a way that makes intuitive sense. If I had to pick the AI versus traditional models at this point, I would choose the traditional models.

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I don't trust these AI's "know"  ( pun intended ) what they're doing.

Looking at their 500 mb isohypses progressions through the periods they smack to me of the primitive MRF of the mid 1980s.   It could also just be a coincidence, but I'm inclined to wonder nonetheless if that is why they are always optimistic/more so than their operational colleagues.   It's like they are learning ... but they are just in the 1980s middle school, where as the operational runs today are ... freshmen in college say.

Lot of metaphor packed into all that but you get my gist -

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1 minute ago, Sey-Mour Snow said:

GFS and GEFS are 100% unusable .. the flip flopping is atrocious .. sticking with AIs EURO and then hires close in for now.. 

I like the EC-AIFS too. I think it has done well this winter. Under 48hrs I'll be looking at the NAM. That's probably an unpopular opinion, but I think it does well with these trofs that touch the Gulf when the height field along the upstream trof flank is questionable. It often signals how much room there is to come NW. It the NAM stays east in the short term, that usually ends it.

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1 minute ago, Sey-Mour Snow said:

GFS and GEFS are 100% unusable .. the flip flopping is atrocious .. sticking with AIs EURO and then hires close in for now.. 

In a synoptic threat 3-4 days out, it’s going to be extremely tough to defeat the Euro/GFS and their ensembles if they are in close agreement. I’d want to see the 12z euro improve at least…otherwise I’d be more inclined to punt the AIs. 

However, a 70/30 compromise in favor of the OP models will still produce some accumulating snow in eastern zones, but obviously not a big event. 

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1 minute ago, RUNNAWAYICEBERG said:

The AI versions must run on less resolution kind of like what the regular models did back in the day. The precip and qpf fields are broader but to me they may be handling the upper levels better as a result. IDK, just my observation…

 

Good observation. For the ECMWF/ECMWF-AI, the operational ECMWF has a horizontal resolution of ~9km. In comparison, the ECMWF-AI is trained on the ERA5 reanalysis dataset which has a resolution of ~31km (its operational product must be run on the same grid specifications). 

On top of resolution discrepancies, to my understanding, the ECMWF-AI uses its own, statistical relationship (AI and not traditional microphysical/physical schemes) to determine precipitation too. That likely compounds the resolution issue you mentioned, as well.

I'm heavily leaning away from AI models for this event (and likely, for all events until it proves its accuracy for sensible weather).

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AIs have proven to be better outside of 96 hours, but the physics-based models are better inside of that time frame.  It makes perfect sense really, the "math equation" is solvable in the shorter time frames, but too chaotic to be useful in the longer range.  Pretty much can be said for ensembles vs. operational.  The value of pattern recognition is greatest in the longer (mid, really) ranges.

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1 minute ago, Sey-Mour Snow said:

AIFS with a solid move west pretty close with GFS AI now, 

Yep. One of them is gonna crash and burn and it’s prob gonna be the AI guidance. But no guarantees. We wait and see. 

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