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February Med/Long Range Discussion Part 2


WinterWxLuvr

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People just don't like to believe in chaos. There is still uncertainty but right now I'd bet against the NAM. Not just because its a less skillful model at those time ranges but because its by itself and doesn't agree with the bulk of the GEFS and Euro ensembles or the parent models. Could be right but probably won't be.

I think it was you who told me years ago about initial conditions and while there have been vast improvements in data assimilation we are still very far away from accurately sampling the entire atmosphere. That stuck with me and made the most sense in my early weenie days.

My brain accepted the fact that models start off with many estimations and inaccuracies from hour zero. Even if the models had perfect atmospheric physics built in they would still be far from perfect solutions. And error growth through time would always be present.

I also learned from you that ensembles do the best job at "averaging error growth" through time.

The expectation of a perfect 10 day weather movie is always present on the board though. I'll be long gone before there's any chance at that. And it would be boring and take the fun out of the hobby anyway. Weenies should root against that type of technology. Lol

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People just don't like to believe in chaos.  There is still uncertainty but right now I'd bet against the NAM.  Not just because its a less skillful model at those time ranges but because its by itself and doesn't agree with the bulk of the GEFS and Euro ensembles or the parent models.  Could be right but probably won't be. 

 

This guy did:

 

170px-DonAdams.jpg

 

KAOS_logo_from_Get_Smart.gif

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I think it was you who told me years ago about initial conditions and while there have been vast improvements in data assimilation we are still very far away from accurately sampling the entire atmosphere. That stuck with me and made the most sense in my early weenie days.

My brain accepted the fact that models start off with many estimations and inaccuracies from hour zero. Even if the models had perfect atmospheric physics built in they would still be far from perfect solutions. And error growth through time would always be present.

I also learned from you that ensembles do the best job at "averaging error growth" through time.

The expectation of a perfect 10 day weather movie is always present on the board though. I'll be long gone before there's any chance at that. And it would be boring and take the fun out of the hobby anyway. Weenies should root against that type of technology. Lol

 

Great post Bob. And it makes it all the more interesting when the models lock on to something far out. Like they did with the blizzard this year. What did they see that makes them so reliable in that event. But so inconsistent with the next. The models to me are an amazing achievement. But knowing your climo and what USUALLY happens for your area is just as powerful IMO. 

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Great post Bob. And it makes it all the more interesting when the models lock on to something far out. Like they did with the blizzard this year. What did they see that makes them so reliable in that event. But so inconsistent with the next. The models to me are an amazing achievement. But knowing your climo and what USUALLY happens for your area is just as powerful IMO.

Models are at their best when blocking is present and at their worst in fast/active progressive flow. We've seen both this year. Lol.

Blocking comes in a lot of forms and effects places differently depending on the setup. Last couple years were pretty tricky for us with no stable ao/nao blocking. But the forecast for the west coast all the way from CA to AK waa nailed 10 days on advance all winter. Lol

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I think it was you who told me years ago about initial conditions and while there have been vast improvements in data assimilation we are still very far away from accurately sampling the entire atmosphere. That stuck with me and made the most sense in my early weenie days.

My brain accepted the fact that models start off with many estimations and inaccuracies from hour zero. Even if the models had perfect atmospheric physics built in they would still be far from perfect solutions. And error growth through time would always be present.

I also learned from you that ensembles do the best job at "averaging error growth" through time.

The expectation of a perfect 10 day weather movie is always present on the board though. I'll be long gone before there's any chance at that. And it would be boring and take the fun out of the hobby anyway. Weenies should root against that type of technology. Lol

All good points Bob, but wild swings while getting closer say that there's more to it than just chaos. Take an exponential function as an example. If you equate its growth with error, then the growth becomes larger in time, thus the error becomes larger in time. But the one thing it does not do is grow erratic in time. The swings in models back and forth can't be explained just by chaos. If you proceed on that assumption then the gfs swing from 12z yesterday to 18z yesterday has to be blamed on the error in the 12z modeling of the initial conditions used for the 18z run. Now I don't think the 12z forecast at 6 hours was so bad that it caused such completely different scenario that in turn caused the 18z run to be so different. Accumulated data has to play a role. The non pros here are told all the time that the data significance is over played, but if that is true I need two things cleared up for me. One, do we use different data collection techniques over the US than we do over the Pacific (I think I already know that answer) and if yes, why if it's not that critical to a model outcome? Two, why do we collect data so frequently, again if it's not that critical.

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what amazes me is, the data is the same, the equations cant be that different,yet big differences.either some programmar has no clue or .....

 

Small errors early in the run can balloon into big differences.  In addition to small errors in the initial conditions, every model is an approximation that introduces new errors at every step along the way.  The good news, as dtk has previously pointed out, is that we've become much better at determining the initial condtions (data assimilation).  In addition to ground observations, we have weather balloon data and extensive satellite data.  One of the biggest problems these days is that sometimes dtk makes a typo when entering the latest satellite data.  That can throw a whole run off.  It's why the 00z run of the GFS, for which data is generally entered after he's had dinner, is better than the 18z run, for which data entry usually occurs before he's had lunch.

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Euro low is about 100 miles southwest of the GFS and 100 miles west of the UKMET at 120hrs. Not that it matters but a pretty good consensus this storm is an upper midwest blizzard, a southeast tornado outbreak and a mid atlantic lame squall line event.

we don't do well with storms as blocking pattern are getting started. We do better as they mature and break down. I'm already moved on to the better threats after.
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The period around the first of March looks interesting. Ensembles have shown a good pattern for that period for a while now, and this is the second run of the GFS with some sort of storm. Looks like we may have a decent block in place.

wont hold my breath, time for outdoor tennis, i,ve heard this too many tmes

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The atmosphere is more than math

With the storage and capability of computers it would be possible to scan into it for a 5+ day forecast, and note I say forecast as I think models are more aligned toward projecting possibilities rather than forecasting, the following:

Moderate+ Nino, low pressure developing tx/la gulf coast, -nao, +pna, month of February, and have all of those parameters combined into a visual graphic as to what has been the dominant result in the past The exacta set of data input I may not be addressing correctly but the method concept would work better than what we have now

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The atmosphere is more than math

With the storage and capability of computers it would be possible to scan into it for a 5+ day forecast, and note I say forecast as I think models are more aligned toward projecting possibilities rather than forecasting, the following:

Moderate+ Nino, low pressure developing tx/la gulf coast, -nao, +pna, month of February, and have all of those parameters combined into a visual graphic as to what has been the dominant result in the past The exacta set of data input I may not be addressing correctly but the method concept would work better than what we have now

mathematical equations are the only way to quantify the atmosphere, at this particular juncture in history. The new gfs, para euro and other models are not being run, from what has been said here, on the newest cray super computer. I,m not a met, just saying what i believe and read

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mathematical equations are the only way to quantify the atmosphere, at this particular juncture in history. The new gfs, para euro and other models are not being run, from what has been said here, on the newest cray super computer. I,m not a met, just saying what i believe and read

Correct. Everything in physics and engineering is explained/modeled by mathematical equations. The atmosphere represents fluid mechanics, heat transfer, energy budget, etc on a very large scale. Its all math. Not sure what he is on about.

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we don't do well with storms as blocking pattern are getting started. We do better as they mature and break down. I'm already moved on to the better threats after.

I was always looking beyond next week, given the pattern we were heading into (in now). I like the general look for around March 1st, although GEFS seems more bullish on the blocking over Greenland than EPS.

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