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February 2021 Observations and Discussion


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After the Thursday system, the Euro shows suppression city for the rest of the run.

season snowfall: 52.5"

 

'19-20: 36.2"      '18-19: 50.2"      '17-18: 39.5"      '16-17: 17.9"      '15-16: 20.0"      '14-15: 30.4"      '13-14: 48.3"      '12-13: 34.1"

 

Average snowfall: ~30"

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^^ With that kind of near record CAA- no doubt. It's about time others South see at least something and we get cold and blue.... Jackie Blue comes to mind-- Jackie Blue meaning brutal cold---

sfctapp.us_mw.png

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The two loudest sounds known to man: a gun that goes bang when it is supposed to go click and a gun that goes click when it is supposed to go bang.

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The EC next week gets bomb after bomb. Yikes! They will be stealing our snow chances (hope not), but will have to wait and see on that. Sundays storm "might" not happen, if the energy is transferred off the coast. UGRRRRRRRRGH!

In Brooklyn and East Harlem, some of my homeboys there are digging out as well in over a foot.

Btw: I have been receiving numerous texts and emails of pics showing the beautiful scenery in NYC and other boroughs as well. Central Park at over a foot (b4 all set and done, looking at near 18.0"). Queens, where my location is also sitting at 16.7" and still snowing. I will try to post some pics on here.

 

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Snowfall as of today:  Feb, 2021: 41.2"

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I’ve always found this interesting how the slightest breeze on a clear calm winter night can mix up the atmosphere and do funny things to the temperature.

We had clear skies and a calm wind from sunset on for a couple hours and the temperature was crashing.

Then the wind switched to the south and picked up just a bit and the temperature is rising back up after dark.

60519F56-F663-45BD-AC50-1159473E9DC3.jpeg

B87F3477-055E-4B6A-BC5F-ED2F4D44E825.jpeg

 

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5 hours ago, Clinton said:

18z Euro control coming back with snow on Sunday.

1612720800-7S2m3pDNLCM.png

I'm preparing a storm thread for the Super Bowl weekend storm threat.  Growing consensus and ensemble support is there my friend!

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A good read on Pivotal about snow maps-- lots of info here.

Last updated 25 January 2020

Snow maps — love them or hate them, they're everywhere in the wintertime! When it comes to different snow map algorithms, confusion reigns. Although this is a messy topic with few simple answers, our aim is to clear up some of the confusion in a central location.

What is snowfall?

On Pivotal Weather, "snowfall" refers to snow that reaches Earth's surface over the specified time period. If a particular ground surface is warm enough for melting to occur, then the accumulated pile of snow you see on that surface at the end of a storm may be noticeably less than what we call snowfall. Suppose you had a snow board whose temperature you maintained at well below freezing, and you diligently went outside every hour to measure and clear new snow. Not much melting, sublimation, or compacting would occur during those hourly intervals, regardless of the weather conditions. The sum of all snow you cleared off the chilled snow board over the course of the storm would represent the observed "snowfall" that our 10:1 and Kuchera* snowfall maps attempt to forecast.

To forecast the final accumulation on a ground surface at the end of a long-duration snowstorm is more complex. It will depend on the surface type, in addition to weather conditions at ground level and their evolution throughout the storm. Even solar radiation passing through clouds, and therefore time of day, can have an impact on melting. We do not attempt to forecast any of this explicitly, but our snowfall products are still often a useful proxy for the final accumulation on untouched natural surfaces. However, this may not be true when ground temperatures are warm, air temperatures are above freezing, or when a storm is particularly long in duration and compacting plays a large role.

*The Kuchera method was originally formulated to fit a sample of observed snow depth measurements (e.g., a ruler measurement after a storm), so even our attempt to define “snowfall” has caveats — more below.

Assessing model precipitation type

Our primary snowfall product types, 10:1 and Kuchera, apply certain snow-to-liquid ratios (SLRs) to precipitation in the model we deem to have fallen as snow between data output times. But, hold on… do we really know how much fell as snow?

  • ECMWF, UKMET, and Environment Canada models keep track of precipitation type in a precise way as the model integrates, so we know how exactly much precipitation falls in the form of snow (at least, based on the model’s internal diagnostics). This eliminates any concern about including sleet, graupel, or rain when we compute snowfall for those models.

  • For NCEP models, the bookkeeping for precipitation types is less precise, so mis-categorizing some of the precipitation that fell between data output times is always a risk during mixed precipitation or precipitation that is rapidly changing type. We have adopted an approach that usually avoids erroneously treating sleet as snow for NCEP models, so you should not see a shield of "fake snow" extending well equatorward of the actual snow-sleet line in a large mid-latitude cyclone, for example. Still, it is inevitable that we will sometimes overestimate the fraction of mixed precipitation falling as snow in borderline and transitional environments (usually small in area).

Snow-to-liquid ratio (SLR)

Now, to the topic of the SLR (often informally called “snow ratio” or just “ratio”). After snow falls, we can melt it and measure the liquid equivalent precipitation it comprises. Dividing the snowfall by this liquid equivalent amount gives the SLR. Because current numerical weather prediction (NWP) models predict liquid equivalent precipitation directly, some SLR must be applied to the predicted liquid amount to get a meaningful snow forecast.

For over a century in weather forecasting, a 10:1 SLR (1 inch of liquid = 10 inches of snow) has commonly been used as a default value. A large climatology of SLRs in the United States by Baxter et al. 2005 found a distribution of values centered near 12:1, with values between 10:1-12:1 being more common than any other bin (see their Fig. 9). Values ranging all the way from 6:1 to 18:1 are relatively common in the US, and can occasionally approach 2:1 on the low end and 44:1 on the high end. It is apparent that while 10:1 is a reasonable “default” value if you had to pick one, SLR errors >50% will be seen on a regular basis using that approach!

From a physics perspective, SLR comes down to the structure and density of the snow crystals, the formation mechanisms of which are quite complex (see Takahashi et al. 1991). Like any such pinpoint-small detail, though, current NWP models can only parameterize (estimate) this based on larger-scale variables like the predicted air temperature, moisture, and wind. Within the model, these variables could theoretically be used in a nuanced way to estimate SLR with considerable accuracy, but this is rarely done in current operational NWP. Instead, external users like Pivotal Weather must estimate SLR themselves based on the more limited data provided publicly.

In late 2004, then-graduate student Evan Kuchera of the Air Force Weather Agency developed what has since become widely known as the Kuchera SLR method. It is one attempt to link model-predicted variables with SLR, and is a linear function of just one value at each horizontal grid point: the warmest temperature in the air column from the surface to 500 mb. Describing to us the origins of his approach, Evan said:

“I basically manually curve-fit data from various snow events I was aware of around that time [2004] until I was happy with it. Of note, the bifurcation at 271.16 K was to try to account for melting effects after the snow was on the ground for warmer events. So I really was trying to aim at the storm total snowfall that a COOP observer or member of the public would measure, not a pure, by-the-book snowfall properly measured and cleared from a snow board.” — Evan Kuchera

Shortly after the method was developed, Evan’s colleague Earl Barker (www.wxcaster.com) implemented it for his online NWP graphics, and the rest is history — “Kuchera snowfall” is now part of almost every winter weather enthusiast’s vocabulary and computed by numerous NWP graphics providers! Although this method has not been published in a peer-reviewed scientific journal, it has grown in popularity due to its straightforward formulation and subjective usefulness, and verification work presented at academic conferences has also supported its utility. Air temperature does not exclusively determine SLR in the real world, but several published studies have demonstrated a fairly strong relationship between low-to-mid level temperatures and observed SLRs (e.g., Roebber et al. 2003; Alcott and Steenburgh 2010). If NWP users are looking to implement a simple approximation of SLR that will not grind their data processing to a halt or demand obscure model diagnostics they lack access to, they’re unlikely to do much better than Kuchera.

Although Kuchera may depart from observed SLR significantly in some cases, it should still provide a first-order improvement over assuming a blanket 10:1 ratio. Its benefit may actually be most apparent when temperatures are borderline, a situation where it will correctly reduce snowfall below a 10:1 estimate, as Evan intended. Still, we emphasize that Kuchera is highly imperfect, as true SLRs depend on cloud and precipitation physics far more complex than a single statistic of the column temperature distribution. In the future, we are hopeful that NWP models may begin tracking snowfall internally using more physically sound diagnostics to estimate SLR at subhourly intervals, which could markedly improve snowfall forecasts over those derived from 10:1 and Kuchera SLRs.

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The two loudest sounds known to man: a gun that goes bang when it is supposed to go click and a gun that goes click when it is supposed to go bang.

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A hole in the stratus / fog overnight (since filled in) allowed KDSM to drop to 9F. Not overwhelming cold at all for early FEB but it appears to be the coldest reading in IA that I can find. Don't recall the last time KDSM had the min for Iowa-- few and far between that's for sure. *** appears to be coldest including  MN as well *** NOW that's very rare.

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The two loudest sounds known to man: a gun that goes bang when it is supposed to go click and a gun that goes click when it is supposed to go bang.

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Well Punxsutawney Phil did see his shallow this morning so it is now official that we will have at least 6 more weeks of winter. Of course we knew that yesterday. This morning there seems to be a big difference temperature wise across the area. While the official low at GRR was in the upper teens here at my house I dropped down to +9.5 and at this time I am at +10 with clear skies.

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6 hours ago, Grizzcoat said:

A good read on Pivotal about snow maps-- lots of info here.

Last updated 25 January 2020

Snow maps — love them or hate them, they're everywhere in the wintertime! When it comes to different snow map algorithms, confusion reigns. Although this is a messy topic with few simple answers, our aim is to clear up some of the confusion in a central location.

What is snowfall?

On Pivotal Weather, "snowfall" refers to snow that reaches Earth's surface over the specified time period. If a particular ground surface is warm enough for melting to occur, then the accumulated pile of snow you see on that surface at the end of a storm may be noticeably less than what we call snowfall. Suppose you had a snow board whose temperature you maintained at well below freezing, and you diligently went outside every hour to measure and clear new snow. Not much melting, sublimation, or compacting would occur during those hourly intervals, regardless of the weather conditions. The sum of all snow you cleared off the chilled snow board over the course of the storm would represent the observed "snowfall" that our 10:1 and Kuchera* snowfall maps attempt to forecast.

To forecast the final accumulation on a ground surface at the end of a long-duration snowstorm is more complex. It will depend on the surface type, in addition to weather conditions at ground level and their evolution throughout the storm. Even solar radiation passing through clouds, and therefore time of day, can have an impact on melting. We do not attempt to forecast any of this explicitly, but our snowfall products are still often a useful proxy for the final accumulation on untouched natural surfaces. However, this may not be true when ground temperatures are warm, air temperatures are above freezing, or when a storm is particularly long in duration and compacting plays a large role.

*The Kuchera method was originally formulated to fit a sample of observed snow depth measurements (e.g., a ruler measurement after a storm), so even our attempt to define “snowfall” has caveats — more below.

Assessing model precipitation type

Our primary snowfall product types, 10:1 and Kuchera, apply certain snow-to-liquid ratios (SLRs) to precipitation in the model we deem to have fallen as snow between data output times. But, hold on… do we really know how much fell as snow?

  • ECMWF, UKMET, and Environment Canada models keep track of precipitation type in a precise way as the model integrates, so we know how exactly much precipitation falls in the form of snow (at least, based on the model’s internal diagnostics). This eliminates any concern about including sleet, graupel, or rain when we compute snowfall for those models.

  • For NCEP models, the bookkeeping for precipitation types is less precise, so mis-categorizing some of the precipitation that fell between data output times is always a risk during mixed precipitation or precipitation that is rapidly changing type. We have adopted an approach that usually avoids erroneously treating sleet as snow for NCEP models, so you should not see a shield of "fake snow" extending well equatorward of the actual snow-sleet line in a large mid-latitude cyclone, for example. Still, it is inevitable that we will sometimes overestimate the fraction of mixed precipitation falling as snow in borderline and transitional environments (usually small in area).

Snow-to-liquid ratio (SLR)

Now, to the topic of the SLR (often informally called “snow ratio” or just “ratio”). After snow falls, we can melt it and measure the liquid equivalent precipitation it comprises. Dividing the snowfall by this liquid equivalent amount gives the SLR. Because current numerical weather prediction (NWP) models predict liquid equivalent precipitation directly, some SLR must be applied to the predicted liquid amount to get a meaningful snow forecast.

For over a century in weather forecasting, a 10:1 SLR (1 inch of liquid = 10 inches of snow) has commonly been used as a default value. A large climatology of SLRs in the United States by Baxter et al. 2005 found a distribution of values centered near 12:1, with values between 10:1-12:1 being more common than any other bin (see their Fig. 9). Values ranging all the way from 6:1 to 18:1 are relatively common in the US, and can occasionally approach 2:1 on the low end and 44:1 on the high end. It is apparent that while 10:1 is a reasonable “default” value if you had to pick one, SLR errors >50% will be seen on a regular basis using that approach!

From a physics perspective, SLR comes down to the structure and density of the snow crystals, the formation mechanisms of which are quite complex (see Takahashi et al. 1991). Like any such pinpoint-small detail, though, current NWP models can only parameterize (estimate) this based on larger-scale variables like the predicted air temperature, moisture, and wind. Within the model, these variables could theoretically be used in a nuanced way to estimate SLR with considerable accuracy, but this is rarely done in current operational NWP. Instead, external users like Pivotal Weather must estimate SLR themselves based on the more limited data provided publicly.

In late 2004, then-graduate student Evan Kuchera of the Air Force Weather Agency developed what has since become widely known as the Kuchera SLR method. It is one attempt to link model-predicted variables with SLR, and is a linear function of just one value at each horizontal grid point: the warmest temperature in the air column from the surface to 500 mb. Describing to us the origins of his approach, Evan said:

“I basically manually curve-fit data from various snow events I was aware of around that time [2004] until I was happy with it. Of note, the bifurcation at 271.16 K was to try to account for melting effects after the snow was on the ground for warmer events. So I really was trying to aim at the storm total snowfall that a COOP observer or member of the public would measure, not a pure, by-the-book snowfall properly measured and cleared from a snow board.” — Evan Kuchera

Shortly after the method was developed, Evan’s colleague Earl Barker (www.wxcaster.com) implemented it for his online NWP graphics, and the rest is history — “Kuchera snowfall” is now part of almost every winter weather enthusiast’s vocabulary and computed by numerous NWP graphics providers! Although this method has not been published in a peer-reviewed scientific journal, it has grown in popularity due to its straightforward formulation and subjective usefulness, and verification work presented at academic conferences has also supported its utility. Air temperature does not exclusively determine SLR in the real world, but several published studies have demonstrated a fairly strong relationship between low-to-mid level temperatures and observed SLRs (e.g., Roebber et al. 2003; Alcott and Steenburgh 2010). If NWP users are looking to implement a simple approximation of SLR that will not grind their data processing to a halt or demand obscure model diagnostics they lack access to, they’re unlikely to do much better than Kuchera.

Although Kuchera may depart from observed SLR significantly in some cases, it should still provide a first-order improvement over assuming a blanket 10:1 ratio. Its benefit may actually be most apparent when temperatures are borderline, a situation where it will correctly reduce snowfall below a 10:1 estimate, as Evan intended. Still, we emphasize that Kuchera is highly imperfect, as true SLRs depend on cloud and precipitation physics far more complex than a single statistic of the column temperature distribution. In the future, we are hopeful that NWP models may begin tracking snowfall internally using more physically sound diagnostics to estimate SLR at subhourly intervals, which could markedly improve snowfall forecasts over those derived from 10:1 and Kuchera SLRs.

Evan’s colleague Earl Barker (www.wxcaster.com) implemented it for his online NWP graphics.
I think I’m also going to like this link from the above article. Thanks 

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A couple weeks late to the party, but...

 

20210202 GRR Cold Wave graphic.png

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Winter 2020-21 Snow Total = 35.1"  Largest Storm: 10.2" (2/15-16)        Oct: 0.0 Nov: 1.5 Dec: 3.6 Jan: 10.0 Feb: 20.0 Mar: 0.0 Apr: 0.0

 

Annual avg for mby = 49.7"  Avg for last 10 seasons = 58.4" (118% of normal)

2019-20 = 48.0"  2018-19 = 56.1"  2017-18 = 68.3"   2016-17 = 52"   2015-16 = 57.4"   2014-15 = 55.3"   2013-14 = 100.6" (coldest & snowiest in the modern record!)  2012-13 = 47.2"   2011-12 = 43.7"

 

Legit Blizzards (high winds and dbl digit snows): Feb 2011, Dec 2009, Jan 2005, Dec 2000, Jan 1999, Mar 1998, Nov 1989, Jan 1982, Jan 1978, Jan 1977, Apr 1975, Mar 1973, Jan 1967, Feb 1965, Jan 1918

 

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As a winter weather enthusiast, I can't help but marvel at the idea that this month could very well deliver a tremendous amount of snow and sustained cold for the heart of this Sub Forum.  It is not fantasy anymore, the robust pattern flip which we have all been waiting for (I know some on here don't care...) is underway.  The story of how the Winter of '20-21 will be written may not just be remembered by the warmth that inundated the majority of met Winter but in my opinion, it will be remembered by one of the most incredible back-loaded periods in history for some locals (not all). 

Locally speaking, I posted an interesting stat a few weeks ago where Chicago ended up with 3 out of 3 winters that started off very slow in the snow dept through early January, that eventually, the city ended up above avg by seasons end.  I gotta say, it sure is looking like we are on the way towards an AN snow season.  A number of places across the MW are doing extremely well in the snow dept and nature is showing us a pattern.  Check out the current U.S. snow depth and it likely tells the story of what lies ahead.

Feb 2nd U.S. Snow Depth.jpg

 

Feb 1st GL's snow depth...

Feb 1st Snow Depth GL's.jpg

 

IMHO, the big missing link for those of us who have missed out in the snows in recent years has been the lack of any blocking up near Greenland.  This season, however, it has brought forth a massive change to the storm track and has benefited those farther south across our Sub instead of recent years of having to deal with cutters that tracked NW of here and delivered, literally, historic snows in a handful of those years.  Is nature balancing things out this year???  What lies ahead for this month may be some thing written in the history books in terms of duration of sustained cold and storms.  The pattern setting up for the central CONUS could very well mirror what happened in Boston during FEB '15 (prob not to that extreme).  Interestingly, while I was flipping through the models, I couldn't help but "see" something whereby the models could be providing us a clue.

The last run off of the TTB site, the CFSv2 was showing this temp forecast for Feb....this run was on Jan 28th so about 6 days ago when it stopped updating.

cfs-mon_01_T2ma_us_1.png

 

Coincidentally, or not, the temp profile looks rather similar to the snow depth map I posted above!  Wouldn't you agree the model may be sniffing out where the storm track will be setting up???  The jet is going to remain very active this month and there are multiple hits, I mean, it is concievable we will be tracking waves/storms every 2-3 days this month.  I foresee a spectacular winter pattern setting up for our Sub.  I'm tickled with excitement as this pattern that is forthcoming has tremendous possibility for a historic finish to met Winter.  TBH, full disclosure, I'm delaying my trip to Arizona bc I feel that I have a personal responsibility to stay here this month and track winter storms!  I sure as heck don't wanna miss out on this opportunity!

If the 00z GEFS are correct, the saying, "The Midwest is Best" comes to mind...whats even more eye popping, quite sadly actually, is the lack of snow in the Dakotas and the prairies of SW Canada.  This snow mean map is quintessentially what I think mother nature has been showing us already.  It is fascinating to see how the model world lines up with the pattern that has set up.  For example, it is the exact opposite of what happened during the historic Feb '19 season where the heaviest snows fell NW of here.

384

 

Over the next 2 weeks, the models are suggesting a hyper active wave train coupled with long duration cold across the eastern 2/3rd's of the nation.  As a snow lover, you can't ask for a better outcome...to have it snow, on top of snow, has been very rare around these parts....until now.  I'm anticipating a couple more storms for later next week (9th-10th and around Valentine's Day).  I'm diggin' what the GEFS are sippin'....

1.gif

2.gif

 

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2 hours ago, Tom said:

As a winter weather enthusiast, I can't help but marvel at the idea that this month could very well deliver a tremendous amount of snow and sustained cold for the heart of this Sub Forum.  It is not fantasy anymore, the robust pattern flip which we have all been waiting for (I know some on here don't care...) is underway.  The story of how the Winter of '20-21 will be written may not just be remembered by the warmth that inundated the majority of met Winter but in my opinion, it will be remembered by one of the most incredible back-loaded periods in history for some locals (not all). 

Locally speaking, I posted an interesting stat a few weeks ago where Chicago ended up with 3 out of 3 winters that started off very slow in the snow dept through early January, that eventually, the city ended up above avg by seasons end.  I gotta say, it sure is looking like we are on the way towards an AN snow season.  A number of places across the MW are doing extremely well in the snow dept and nature is showing us a pattern.  Check out the current U.S. snow depth and it likely tells the story of what lies ahead.

Feb 2nd U.S. Snow Depth.jpg

 

Feb 1st GL's snow depth...

Feb 1st Snow Depth GL's.jpg

 

IMHO, the big missing link for those of us who have missed out in the snows in recent years has been the lack of any blocking up near Greenland.  This season, however, it has brought forth a massive change to the storm track and has benefited those farther south across our Sub instead of recent years of having to deal with cutters that tracked NW of here and delivered, literally, historic snows in a handful of those years.  Is nature balancing things out this year???  What lies ahead for this month may be some thing written in the history books in terms of duration of sustained cold and storms.  The pattern setting up for the central CONUS could very well mirror what happened in Boston during FEB '15 (prob not to that extreme).  Interestingly, while I was flipping through the models, I couldn't help but "see" something whereby the models could be providing us a clue.

The last run off of the TTB site, the CFSv2 was showing this temp forecast for Feb....this run was on Jan 28th so about 6 days ago when it stopped updating.

cfs-mon_01_T2ma_us_1.png

 

Coincidentally, or not, the temp profile looks rather similar to the snow depth map I posted above!  Wouldn't you agree the model may be sniffing out where the storm track will be setting up???  The jet is going to remain very active this month and there are multiple hits, I mean, it is concievable we will be tracking waves/storms every 2-3 days this month.  I foresee a spectacular winter pattern setting up for our Sub.  I'm tickled with excitement as this pattern that is forthcoming has tremendous possibility for a historic finish to met Winter.  TBH, full disclosure, I'm delaying my trip to Arizona bc I feel that I have a personal responsibility to stay here this month and track winter storms!  I sure as heck don't wanna miss out on this opportunity!

If the 00z GEFS are correct, the saying, "The Midwest is Best" comes to mind...whats even more eye popping, quite sadly actually, is the lack of snow in the Dakotas and the prairies of SW Canada.  This snow mean map is quintessentially what I think mother nature has been showing us already.  It is fascinating to see how the model world lines up with the pattern that has set up.  For example, it is the exact opposite of what happened during the historic Feb '19 season where the heaviest snows fell NW of here.

384

 

Over the next 2 weeks, the models are suggesting a hyper active wave train coupled with long duration cold across the eastern 2/3rd's of the nation.  As a snow lover, you can't ask for a better outcome...to have it snow, on top of snow, has been very rare around these parts....until now.  I'm anticipating a couple more storms for later next week (9th-10th and around Valentine's Day).  I'm diggin' what the GEFS are sippin'....

1.gif

2.gif

 

Wow the 0z Euro is non stop snow over the next 7-8 days.  The storm showing up next Monday could go bigly!

1612893600-cPCMr47koWc.png

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@Tom

Peeps were being snarky last week when JB was quoted as calling this "Snowmageddon Jr" (Snowmageddon Sr was in 2010 on the EC). Saying this would be similar but more spread the wealth instead of the same region hit over and over (DC to NYC). Looking more like he'll have the last laugh. I know you've been "on this" since early in the season and I remember one of the monthly outlooks (thinking Euro) did show very little around here until February. I didn't save those because I wasn't thrilled by that idea, lol. But, here we are at the threshold and while this won't be the winter here it's already been for IA/NE/MN crew, I'll be glad to get in the game finally. I think Feb 2010 (coincidence??) is a great analog for this region. That prior January was cold and dry by contrast to warm and dry as the track was SE of here delivering history to the EC cities.

There were 2 major storms that month around here, and numerous other events.

Feb 2010 stats near Marshall:

Charlotte (20 mi N) 28.2" with a max depth of 16"

BC5NW (15 mi NW) 38.6" with a max depth of 14"

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Winter 2020-21 Snow Total = 35.1"  Largest Storm: 10.2" (2/15-16)        Oct: 0.0 Nov: 1.5 Dec: 3.6 Jan: 10.0 Feb: 20.0 Mar: 0.0 Apr: 0.0

 

Annual avg for mby = 49.7"  Avg for last 10 seasons = 58.4" (118% of normal)

2019-20 = 48.0"  2018-19 = 56.1"  2017-18 = 68.3"   2016-17 = 52"   2015-16 = 57.4"   2014-15 = 55.3"   2013-14 = 100.6" (coldest & snowiest in the modern record!)  2012-13 = 47.2"   2011-12 = 43.7"

 

Legit Blizzards (high winds and dbl digit snows): Feb 2011, Dec 2009, Jan 2005, Dec 2000, Jan 1999, Mar 1998, Nov 1989, Jan 1982, Jan 1978, Jan 1977, Apr 1975, Mar 1973, Jan 1967, Feb 1965, Jan 1918

 

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With this forecasted prolonged cold and snow- one month comes to mind rather easily. Dec 2000. If you lived in IA in DEC 2000 you know what I'am talking about. 2nd coldest ever and #1 snowiest at DSM.

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The two loudest sounds known to man: a gun that goes bang when it is supposed to go click and a gun that goes click when it is supposed to go bang.

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