Jump to content
  • Member Statistics

    18,671
    Total Members
    7,904
    Most Online
    dorkchop
    Newest Member
    dorkchop
    Joined

The “I bring the mojo” Jan 30-Feb 1 potential winter storm


lilj4425
 Share

Recommended Posts

As it stands:
Full phase: Canadian, GFS, UKMET(borderline, but just gets it done)
Partial/late Phase: Euro AI, AI GFS, NEXT model
No phase: Euro, ICON

Can you continue this format post? I’d like to keep an archive of this in this style to look back at after the storm
  • Like 4
Link to comment
Share on other sites

18 minutes ago, mstr4j said:

Poor Upstate of SC - Takes a BOMB of a storm to get .4 qpf, which is always over done.  Cut that in half, .2, the half to virga.....We looking at .1 qpf for a bomb phase, maybe we can get 20-1 ratio!!  hahahaha - Here is to hope!

Seriously, what did we do to deserve this multiple years of snow drought?

Link to comment
Share on other sites

2 minutes ago, Tony Sisk said:

Seriously, what did we do to deserve this multiple years of snow drought?

It's incredible - and why in any other profession we would be down and out - but we still here hoping!  Never giving up - just moments of venting weakness - But it is highly frustrating

  • Like 1
Link to comment
Share on other sites

What we are seeing is the ensemble members having decent spread between the three camps, so when we see the OP runs jump back and forth, they are just reflecting that spread. For that reason, I would not be surprised to see the Euro come back West, just be aware that does not mean it is necessarily trending positively, just jumping around within the spread of outcomes

  • Like 1
  • Thanks 1
Link to comment
Share on other sites

6 minutes ago, BornAgain13 said:

History says the Euro will be the opposite of what the GFS is showing so I dont have my hopes up for it. 

For the past few years the UKMET/Euro have often tended to go reverse directions at this range, but this winter so far they've tended to follow each other.

  • Like 1
Link to comment
Share on other sites

16 minutes ago, olafminesaw said:

What we are seeing is the ensemble members having decent spread between the three camps, so when we see the OP runs jump back and forth, they are just reflecting that spread. For that reason, I would not be surprised to see the Euro come back West, just be aware that does not mean it is necessarily trending positively, just jumping around within the spread of outcomes

Yes but you would expect its ensemble 'spread' to consolidate as we get closer as well.  So range of ops 'jumping' becomes noise

Link to comment
Share on other sites

For those wanting to understand the synoptics of the pattern and why the GFS trended better, it's mainly related to the upper low over the northern Atlantic. In the older days, this feature was/is referred to as the New Foundland low or "50/50" low, which forms near the 50/50 lat/lon area. It's a prevalent feature during -AO patterns which features lower heights over the CONUS and northern Atlantic, while higher heights build into the northern latitudes. This upper low acts as a way to slow down the pattern and induce additional cutoff lows upstream (in this case it would be our storm). The problem is if it's too strong it will suppress or shear out any attempts at this feature. This is a common model fault especially during these types of extreme -AO patterns. It's also a reason why commonly see these SECS systems trend NW/more amped as we draw closer. It has screwed us many times in the south. It could benefit us in this case. We want to see this 50/50 low continue to trend quicker and exit faster into the Atlantic. This allows the heights over the east coast to rise and give us a better chance at a cutoff with at least a positive tilt, which will throw back Atlantic moisture. 

 

Ensemble Mean AO Outlook

Trend Gif.gif

  • Like 7
  • Thanks 8
Link to comment
Share on other sites

I don't like seeing the UK go to an almost whiff. It did well last system and from my experience, does well with phasing. 

I definitely do not trust the GFS. Its almost always playing from behind but this is a very tricky situation that all depends on small changes. 

With the last storm I think both GFS and Euro struggled in different aspects. The Euro caught on to the more amped idea earlier but was terrible with CAD. The GFS took way too long to figure out the storm track but modeled the CAD better. 

 

As @BooneWX said, we may have to wait until CAMs range for this one. The upper low will have some smiling and some swearing to never trust a model again. 

  • Like 1
Link to comment
Share on other sites

1 hour ago, DTP said:

This...wait for more metadata to be ingested by all of the globals and mesos....take a deep breath- pretty much the only takeaway from any model run to this pt is an elevated probability of snowfall Friday and Saturday in the Carolinas, as well as some serious cold.  The models are going off the tails of probability on both sides at current without much in the way of ingested metadata- the wild swings will not stop until that occurs....think of the model data in terms of three separate normal distributions that are interconnected.  The middle normal distribution is the ensemble mean.  Robust predictive value will rest somewhere between 50d (the center; 50= 0 SD from mean), and ~37.5d of each wing of the ND. Outside of this envelope- 25d is the middle of the wing, 12.5d and lower the tail.  Now plug in time to the equation- at 96-120 hrs and little meta (actually occurrence) data, you can draw two separate normal distributions with the 50d mark for the separate distributions at 12.5d of the ensemble mean.  This is what you are looking at currently- a really wide range of generated outcomes that form the middle (model) normal distribution  The normal distributions on the tails get pulled inward toward the center of the ensemble mean as more time passes, moving the center of the model data sets inward toward the 50d mark of the main distribution as more metadata is ingested, therefore making the model trends more robust the closer you are to an event.  The ensemble mean will also shift one direction or the other throughout as well as more data is ingested- this creates the final envelope of robust data that can really be drilled down

 

25d is the most susceptible point to model volatility in normal distribution (any predictive model- not just weather) - also why the models tend to "lose" a storm 2 days out (temporarily)- as the 2 semi-predictive data set means (more like a 50d line of best fit amongst solutions) that started on the tails (2 separate normal distributions) cross the 25d (25 standard deviations from the mean) area, they amplify all of the solution sets away from the mean that are not metadata derived.  Just the way the math works....best way I can think of to explain it- just keep this in mind when you are looking at any potential model outcomes  4-5 days (or more) in the future 

Like having a piece of cardboard and shooting 1' left, and 1' right with buckshot at hr 120

Man, this brought back a lot of old memories of when I took statistics, It helps to makes sense of why models "lose" storms as we get closer. 

Thanks for the explanation!

Link to comment
Share on other sites

Create an account or sign in to comment

You need to be a member in order to leave a comment

Create an account

Sign up for a new account in our community. It's easy!

Register a new account

Sign in

Already have an account? Sign in here.

Sign In Now
 Share

×
×
  • Create New...