NWMSGuy
Member
just like to see the cold have a little more staying power... it don't have to be 0 degrees for week. lol give me week of highs in the 30 s and let the southern stream continue... than we can talk than...The pattern has changed as far as temperatures go. Just a winter storm isn’t there of course it’s always subject to change
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You can probably understand why most on this board don’t trust anything out past 200hr. I’m speaking of the WAR. What if it never leaves? I’m sure there are some solutions on the ensembles where that ridge hangs out til the end of timeEps continues it’s cold look inside day ten now so it continues to move forward for all you negative people that think things are being delayed cause it’s not showing snow and below zero temps at your house
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You continuously speak of storms being pushed back - there has not been one legitimate winter storm threat this entire winter outside of the December NC storm and the ice storm we just finished with. So I'm not sure what you're referring to - if you're talking about these fictitious D10+ winter storms you're just wasting your time on erroneous model noise. I'm not sure why anyone even looks at an operational run beyond 7 days out for any purpose. Just look at what happens to model performance even beyond D4!The storms themselves are being pushed back, or maybe I should say storms that were showing up before are now rain. So, it is taking longer for storms to show up, at least on the op runs. Hopefully, the ensembles are correct and the ops will start to show them soon and we will have an actual storm to track before the end of the month. The pattern might be coming along, but we still want it to produce winter storms, or it is a waste. When I talk of things being pushed back, I speak of the actual storms showing up to track.
I have nothing to base this on. But I could see this winter going like last winter. We saw December storm followed by a clipper type on system in February which dumped 1-3 inches. I could see something like that happening. Of course I’m in upstate sc so I can’t speak for areas west and east and north
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The storms themselves are being pushed back, or maybe I should say storms that were showing up before are now rain. So, it is taking longer for storms to show up, at least on the op runs. Hopefully, the ensembles are correct and the ops will start to show them soon and we will have an actual storm to track before the end of the month. The pattern might be coming along, but we still want it to produce winter storms, or it is a waste. When I talk of things being pushed back, I speak of the actual storms showing up to track.
What happened last winter, does not have any correlation with this winter. Clippers are always possible every winter. There's always the possibility of clippers during cold northwest flows. Clipper systems can also phase with pieces of energy in the southern stream, which would mean a stronger storm system.I have nothing to base this on. But I could see this winter going like last winter. We saw December storm followed by a clipper type on system in February which dumped 1-3 inches. I could see something like that happening. Of course I’m in upstate sc so I can’t speak for areas west and east and north
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Good post. Brick and I had almost this exact same conversation last night. He thinks because an Op showed fantasy snow and then lost it, but the GEFS mean showed fantasy snow, the Op should start showing it again if you believe it's actually going to snow. What seems to be impossible to grasp is that just because a model or ensemble mean shows fantasy snow, doesn't mean it's actually a high or even medium probability event. If you take a very marginal pattern and run a model 50 times with different initial conditions, doesn't it seem logical that at least a few of the runs will show snow for your area? That will give you at least SOMETHING on the mean. That doesn't mean that snow is likely at all. And the op may never show it again because the pattern REALLY isn't all that conducive. None of that means you can't thread the needle, but that's beside the point.You continuously speak of storms being pushed back - there has not been one legitimate winter storm threat this entire winter outside of the December NC storm and the ice storm we just finished with. So I'm not sure what you're referring to - if you're talking about these fictitious D10+ winter storms you're just wasting your time on erroneous model noise. I'm not sure why anyone even looks at an operational run beyond 7 days out for any purpose. Just look at what happens to model performance even beyond D4!
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I think one thing that may be tripping some people is when we talk about the pattern is supportive of a storm, and then one pops up for a run or two, that somehow that is a legitimate storm threat. Unless it's inside D7, that simply isn't true and I or anyone else who says otherwise has become lost in the hype. Right now we are trying to determine the big pieces of the pattern - the ridge out west, the big vortex over southeastern Canada, and the position, strength and timing of the STJ.
This is all the more true on the GEFS which has less than half the members of the EPS. 2 or 3 skewed members can really impact the mean if they are showing insane 20-30" totals and we've seen that countless times already this winter. Additionally, it's important to remember that the ensembles should also be used primarily for patterns -- especially at long lead times -- because they are lower-resolution than the operationals they are derived from. Using lower-resolution models to detect individual storm threats 10 days out - good luck with that too!I think people have a misconception of the Ensemble mean. It is a smoothed combination of all the averages of the individual ensemble member runs. It can be skewed by very strong members and also by timing. So it is very hard to determine storm threats until you get closer and the members start agreeing. It can also mask things because one extreme member skews it. All this can make it appear things are moving back because a number of members may have been a few days too fast.
And to add to the point about the pattern, often, the ensembles do a good job at longer leads depicting the general nature of how the pattern is likely to evolve. But they may shift important features such as, ridge placements, trough axes, location of blocking, etc. slightly enough that the great snowstorm pattern that they showed for your location two days ago doesn't look quite as great now, even though the general pattern they show turns out mostly correct. This is just the nature of the chaotic state of the atmosphere.This is all the more true on the GEFS which has less than half the members of the EPS. 2 or 3 skewed members can really impact the mean if they are showing insane 20-30" totals and we've seen that countless times already this winter. Additionally, it's important to remember that the ensembles should also be used primarily for patterns -- especially at long lead times -- because they are lower-resolution than the operationals they are derived from. Using lower-resolution models to detect individual storm threats 10 days out - good luck with that too!
In summary, beyond D7 the discussion should be PATTERN PATTERN PATTERN focused and what COULD happen. If I go off the rails, someone can feel free to call me out, I'm sure at some point I've been a hypocrite of this advice and guilty of getting too caught up in details beyond a week myself before and should be called out for it if I have!
And for this reason I think it's futile to post 384 hr GEFS snow mean maps (no offense to those who post them and like to look at them), I just think it sets some up for disappointmentI think people have a misconception of the Ensemble mean. It is a smoothed combination of all the averages of the individual ensemble member runs. It can be skewed by very strong members and also by timing. So it is very hard to determine storm threats until you get closer and the members start agreeing. It can also mask things because one extreme member skews it. All this can make it appear things are moving back because a number of members may have been a few days too fast.
And for this reason I think it's futile to post 384 hr GEFS snow mean maps (no offense to those who post them and like to look at them), I just think it sets some up for disappointment
This is what I have never completely understood about ensembles. How can you load different initial conditions into an ensemble model as initial atmospheric conditions, weather observations, measurements, etc. are already measured and defined at a current point in time? It's like taking a snapshot of the current weather conditions, varying or changing them to something different, and then loading them into the ensemble. If the ensembles start out with initial conditions that are varied or possibly incorrect, how the ensembles can be expected to create an accurate forecast further out in time. Are these variations that are loaded into the ensemble being done under the assumption that the current weather conditions may not have been accurately measured or sampled and therefore may actually be incorrect to begin with?
Completely agree..... maybe I should've said those who look at it and take it for gospel that it will snow in their backyard are being set up for disappointment. Fact is when the ens are continuously showing a good snow mean, even if it's one or two members skewing it, it's a good sign just how close we are to something producing. The pattern is such that a small (relatively speaking) difference here or there with a ridge or trough placement or some other feature, as you mentioned above, could have huge implications for sensible weather. Pattern changes always bring chaos which generally is not met with patience LolI agree, but we really need to be smarter than this. Maybe smarter isn't the right term. But maybe we need to learn that there's a difference between something that is fun to look at and something that is realistic. The two are usually not the same in the weather world.
It's essentially scenario forecasting. It's kind of like if you're planning to take your family to the beach this weekend for a nice holiday of fun in the sand. Your initial conditions are that the car works, your boss gives you the weekend off, the forecast is warm and sunny, and you are feeling good.This is what I have never completely understood about ensembles. How can you load different initial conditions into an ensemble model as initial atmospheric conditions, weather observations, measurements, etc. are already measured and defined at a current point in time? It's like taking a snapshot of the current weather conditions, varying or changing them to something different, and then loading them into the ensemble. If the ensembles start out with initial conditions that are varied or possibly incorrect, how the ensembles can be expected to create an accurate forecast further out in time. Are these variations that are loaded into the ensemble being done under the assumption that the current weather conditions may not have been accurately measured or sampled and therefore may actually be incorrect to begin with?
It's a terrible example but the dang funniest thing I've read all day.... again I'm jealous.It's essentially scenario forecasting. It's kind of like if you're planning to take your family to the beach this weekend for a nice holiday of fun in the sand. Your initial conditions are that the car works, your boss gives you the weekend off, the forecast is warm and sunny, and you are feeling good.
If you're like Billy Bob, you don't give it a second thought. But if you're like Geoffrey Von Enrich, III, you think it through. What will my weekend look like if my boss makes me work? Maybe we'll stay in town. So we'll maybe we'll end up eating a nice evening meal and going to a movie. Well, what if the movie is sold out? Maybe we'll buy tickets to a concert. Or, maybe I'll send my family ahead to the beach. Ok. Well, what if it rains? Maybe we'll go to the beach anyway but go to the indoor water park. What if my car breaks down? Maybe I rent a car and go to the beach. Or maybe I stay at home and watch movies and play games instead. What if I'm sick. Maybe I stay in bed or send my family ahead to the beach. Or maybe they stay home with me.
How many scenarios end up at the beach? What's the spread on the other outcomes? There's value in gaming it out. If most scenarios still end up with people going to the beach, then you have a pretty solid idea of how the weekend plays out. But if a couple of key things are changed that cause you to end up in a different place, then there's a pretty solid risk to the beach trip.
Meanwhile Billy Bob has no idea what to do when his car breaks down and his boss asks him to come in. He walks to work in the rain and gets the flu.
Anyway, this might be a terrible example. But the point is, models are imperfect and are prone to large errors out in time. Tweaking the initial state of the atmosphere and observing whether or not those tweaks cause large changes in the outcome downstream, provides a good insight as to whether or not you should have confidence in the general pattern being depicted out in time.
Pattern has already Changed; 5 days in a row below normal at Greensboro;
-6
-6
-4
-6
-4
The days preceding this since Jan1 where all well above normal. So to me the pattern flipped January 10th. We have a few days coming up that may get 2 to 4 above normal possibly with rain, Then Monday will be much BN.
No model is precisely accurate, not even the ensembles. The ensembles are there to work off of to look for trends on the OP models. The physics behind the models, now that I can't explain. Think of the ensembles as a "beta" model of the OP. That's the way I think of it.This is what I have never completely understood about ensembles. How can you load different initial conditions into an ensemble model as initial atmospheric conditions, weather observations, measurements, etc. are already measured and defined at a current point in time? It's like taking a snapshot of the current weather conditions, varying or changing them to something different, and then loading them into the ensemble. If the ensembles start out with initial conditions that are varied or possibly incorrect, how the ensembles can be expected to create an accurate forecast further out in time. Are these variations that are loaded into the ensemble being done under the assumption that the current weather conditions may not have been accurately measured or sampled and therefore may actually be incorrect to begin with?
Hopefully, the amplitude will be low and NOT underestimated by the guidance like it was earlier in the year. And hopefully, it won't stall over there.Thank you, MJO. Any influence it had during the cold period you cited was good. However, that same MJO is now headed toward warm phases for awhile. So, the help that the MJO just gave will be replaced by an MJO whose influence would be bad with it possibly making SE ridging more stubborn. So, unless that is negated strongly enough by other factors, it will be tough to go back to a SUSTAINED cold period throughout the bulk of the SE (not just western SE) like what we just saw until the MJO at least gets out of the solid phases 4-5 that are forecasted. This will almost certainly happen within 10 days from now. So, just a little patience is needed.
When will it become favorable again? Also, I'm assuming we can still score even in the warm phases if lower amplitude and blocking is present correct?Thank you, MJO. Any influence it had during the cold period you cited was good. However, that same MJO is now headed toward warm phases for awhile. So, the help that the MJO just gave will be replaced by an MJO whose influence would be bad with it possibly making SE ridging more stubborn. So, unless that is negated strongly enough by other factors, it will be tough to go back to a SUSTAINED cold period throughout the bulk of the SE (not just western SE) like what we just saw until the MJO at least gets out of the solid phases 4-5 that are forecasted. This will almost certainly happen within 10 days from now. So, just a little patience is needed.
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