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Damage In Tolland

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Haha you are certainly right, but that won't keep me from trying ;)

 

What you describe in the second paragraph below are systematic biases. When a model tends to always under-do a certain feature (e.g. subtropical ridging over oceanic basins are often undersampled and as a result get stronger with each successive run). The key thing to note here is how the initial conditions of a model are created. In fact 70-85% of the initial conditions produced through data assimilation are a result of the previous model cycle. Only 15-30% of the new initial conditions come from the inclusion of new observations, both in-situ (radiosondes, planes, surface obs) and remote sensing (satellite observations). So lets say a model tends to dampen out subtropical ridging too quickly. The inclusion of new observations over a 24 hour period slowly modify the initial conditions that are primarily derived from the previous model grid of the GFS. This is why you can often seen small but noticeable shifts which can have a lasting impact in later forecast times.

 

So yes in these instances such a pattern can result in a model trend over a period of time. However, its still difficult to partition the changes in the model due to a common systematic bias vs. semi-random changes of the vast majority of the model's initial conditions. In many cases these changes can trump the typical biases of a model and make it difficult to depict a model trend without serious investigation to which observations drove what.

 

There are sophisticated studies that go into trying to diagnosis which observations end up creating the largest spread in model solutions, and just which regions need to be sampled better in order to reduce model uncertainty. The north Pacific (close to the Gulf of Alaska) is often a space where errors start and grow as they propagate downstream across the globe. The feature we need to be focusing on is currently located in that part of the globe (the shortwave currently over far NW Canada). Instead of trying to diagnosis a model trend happening in the 96-120 hour range, I'd rather focus on what might be happening with that shortwave the next 12-36 hours that might be driving these changes.

Thank you so much for that incredibly illuminating post.

So you take issue with calling it a "trend" because only 15-30% of the data ingested into each run is new, and we can't even discern to what degree the new data has caused the change because it could theoretically be attributed to model biases.

I guess to constitute a trend, the changes must be attributed to new data, and that is difficult to distinguish.

 

Surely, you can see why its much easier to simply dub a sequence of changes in the same direction over a succession of 3+ runs a trend, regardless of their nebulous cause. :lol:

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Think first, I did nothing to provoke 6 people on this board and they immediately attempted to either silence or insult me. That should be more than enough for you to understand the mentality that i am running into here. I am not here to make enemies or to cause a problem, however, people need to realize anything that is said in regards to one person is for that person. Not for them.

Alright, just trying to offer some friendly advice.

Also, the mods here get pretty annoyed when the storm discussion threads get cluttered up with back and forth argumentative posts. When one of them wakes up this morning, they will probably go back and delete about 90% of your posts tonight, along with all of the responses they garnered. There is a general banter thread in the NE subforum and they are pretty adamant that we use it appropriately.

Edit: I see someone is already awake, nice.

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Alright, just trying to offer some friendly advice.

Also, the mods here get pretty annoyed when the storm discussion threads get cluttered up with back and forth argumentative posts. When one of them wakes up this morning, they will probably go back and delete about 90% of your posts tonight, along with all of the responses they garnered. There is a general banter thread in the NE subforum and they are pretty adamant that we use it appropriately.

Edit: I see someone is already awake, nice.

I apologize for that, Was just trying to let people know I dont take well to being bantered. I appreciate your response however.

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Yea, weathertalk, I'm Ray btw, it's important not to take anything on here ppersonally. A lot of sarcasm, and its tough when you can't detect tonality.

I am nick, if you havent already figured out from the wesbite. been doing this kind of stuff for 28 years and loving it. I dont take things personally, just dont like to encourage the behaviors :) Got started during Hurricane Gloria and never looked back. My favorite events are wind events.

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That gradient will not verify. No way. That blows 1978 out of the water

Technically, no it won't. 1978 has a similar gradient max/min. with lowest pressure off coast at 954, was lower out in ohio, but raised a bit offshore. the min/max difference was roughly 68 mb, which this storm would be closer to, maybe a few points lower ( around 60-63mb)

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Aside from the gradients themselves, wouldn't the distance between highest high and lowest low also be a factor? Also, would such an astoundingly low pressure inherently add any dynamics than say, a weaker low pressure buttressed against a stronger high pressure?

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Aside from the gradients themselves, wouldn't the distance between highest high and lowest low also be a factor? Also, would such an astoundingly low pressure inherently add any dynamics than say, a weaker low pressure buttressed against a stronger high pressure?

Technically that has more to do with wind speeds overall than much else. Closer the isobars pack, the stronger winds tend to be.

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Technically that has more to do with wind speeds overall than much else. Closer the isobars pack, the stronger winds tend to be.

 

Aside from the gradients themselves, wouldn't the distance between highest high and lowest low also be a factor? Also, would such an astoundingly low pressure inherently add any dynamics than say, a weaker low pressure buttressed against a stronger high pressure?

This would also affect areas of precipitation and lift, and make a more condensed, and cutoff gradient between between heavier precip would be sharper.

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Aside from the gradients themselves, wouldn't the distance between highest high and lowest low also be a factor? Also, would such an astoundingly low pressure inherently add any dynamics than say, a weaker low pressure buttressed against a stronger high pressure?

yes - gradient is change in pressure / change in distance. no. such a low pressure is result of the extreme dynamics, ie.) combo of factors such as pva (positive vorticity advection) / waa (warm air advection) leading to uvm (upward vertical motion) + latent heat from convection leading to rapid height falls --> surface pressure rapidly falls. I am unsure if i interpreted this part of the question correctly..

a weaker low pressure running into a high pressure would typically result in a nice deformation zone and dependent on the temp grad / airmass associated with the high pressure there could be good frontogensis

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Thank you so much for that incredibly illuminating post.

So you take issue with calling it a "trend" because only 15-30% of the data ingested into each run is new, and we can't even discern to what degree the new data has caused the change because it could theoretically be attributed to model biases.

I guess to constitute a trend, the changes must be attributed to new data, and that is difficult to distinguish.

 

Surely, you can see why its much easier to simply dub a sequence of changes in the same direction over a succession of 3+ runs a trend, regardless of their nebulous cause. :lol:

 

Oh yes I can certainly understand why its easier to call a set of solutions that shift in the same direction multiple times a "trend." I think the problem comes up when people start expecting the trend to continue in that direction just because the model has shifted in that direction multiple times.

 

Phil, one thing that I neglected to add is that individual, OP deterministic solutions become much more crucial inside of day 4. Your point is much more salient at extended leads.

 

I agree with you Ray... in the short term (24-72 hours) I think you start seeing the systematic biases play a larger role in run to run variability rather than uncertainty driven by semi-random error in initial conditions. However, we are still in the time period currently where it would be difficult to distinguish consistent changes. 

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