Your East Coast Winter Storm Run-Up Survival Guide

As a forecaster and communicator, I try and approach my audience a lot like I would my mother. Would my mom understand what I’m talking about? Sometimes I deviate and get nerdy; we all do. But when it comes to the forecast details, it has to be simple, clear, and easy to understand.

So my mother sent me an interesting text message today. She said:

Ok. I’m getting anxious. Or curious. I’ve heard so many maybe this or maybe that’s. I want the truth. I’m sick of speculation.

That’s such a great mom text.

In the run up to this major East Coast winter storm, blizzard, Winter Storm Jonas, whatever you use to describe it, you’re going to get a ton of this speculation.

So today, you’re all my mother, and consider this my survival guide for you.

What’s going on here?

The weather models have been hooked on this idea of a major winter storm in the Eastern US for awhile now. There is good agreement among all the various models we use that something is going to happen. Someone’s getting a major storm.

So how much snow am I getting?

No one can answer that question today unfortunately. What we know is that a number of factors are going to contribute to this storm being loaded with moisture. In other words, someone is going to get a *lot* of snow. It’s just not possible to say who that is yet.

Right, right, I get that, but give me your best shot.

This storm is big, slow, and it has a number of complex parts to it that will make it difficult to peg down until we are closer in than usual. But, some trends have evolved in the last couple days that lead us to believe a few facts about this storm.

First, it will be a *big* storm. That means even if you don’t get snow, you may get impacts. It will be slow moving. It will have wind…lots of wind. It will have major, major coastal impacts. Depending on track, we could be looking at a top 5-10 coastal flooding event for folks from the Jersey Shore into Virginia perhaps. That is a serious issue.

But what about snow? The storm has slowly trended south on the weather models. Additionally, it has a very, very sharp gradient on the north side. In plain English? If you live on the northern fringe of this storm, there’s going to be a razor thin margin between major snow and conversational snow.

Here now, a map of where I think things stand as of Tuesday afternoon. Remember, this is subject to change.

My Own Tuesday Evening Snow Synopsis for the Weekend

The trouble is in New England, New York City, and Northern NJ. The models show a tremendous cutoff in snowfall here. The next map is a weather model’s output for precipitation (liquid, not snow). I’ve focused on the NYC area.

18z GFS Model Precip for New York City area (Weather Bell)

Why am I showing this? Notice how in the Central Jersey area, the model spits out about 1.5″ liquid. Go 50 miles north from there. So, like Orange County, NY? About 0.5″ liquid. A 1″ liquid is roughly equivalent to about 10″ of snow. So 10″ snow difference over 50 miles, and the reality is likely that it will be even sharper than this. You’re talking about (surprise!) a major difference in snow totals likely over a short distance over a major population center.

Bottom line in all this: I have higher confidence in heavy snow hitting Virginia and probably DC right now than I do for the Northern half of NJ, New York, or New England. I don’t focus on North Carolina much since the majority of my family and friends are between DC and Boston. But this has potential to be a big storm in a good chunk of NC also.

Alright, so when does all this unfold?

Snow should start in Virginia as early as later Friday morning, and it probably won’t end until about Saturday night. In Philly, it’s a Friday afternoon start and late Saturday night finish. Add a couple hours to all this as you go north to NYC. I have lower confidence in anything further north, so I won’t speculate beyond this.

What about this coastal flooding?

Yeah, this one goes unchecked sometimes. Snow is way sexier, but this is way more damaging potentially. The NWS office in Mount Holly has done an excellent job highlighting this risk. If you look at storm surge guidance for Cape May, NJ, you’ll see the first high tide cycle impacted late Friday ends up at a water level of about 8.5-8.7 feet. Sandy saw a tide level of 8.9 feet there, October 29, 2011 was 8.7 feet, the December 1992 nor’easter was 8.6 feet. An 8.5 foot tide level would rank in the top 8 all time at Cape May. This one’s big. It’s like a 90’s throwback nor’easter.

011916_Cape May
Cape May Surge Guidance shows a tidal level over 8.5′ Friday night/Saturday AM. This would be a top 10 event without much trouble. (NOAA)

If you live along the coast or Back Bays of New Jersey, Delmarva, Virginia, you should begin planning for the possibility of 2-3 high tide cycles like this. If the storm track shifts a bit or the intensity changes, we could see these values change. It’s a fluid forecast, but it’s a serious issue along the coast. Follow your local NWS office for info and guidance.

So will it be a blizzard?

Maybe for someone. It’s entirely possible, but specific criteria must be met regarding wind speed and visibility. It’s too soon to say exactly where and who or how long, but it’s a distinct possibility.

That’s all for now. Feel free to ask any questions and follow me on Twitter at @mattlanza.


I Am The Establishment

An editorial comment.

In this winter of incredible discontent thus far, Eastern US weather weenies have become, quite simply, insufferable. I’ve seen name calling, rage, anger, and a serious dose of voodoo weather forecasting. Because the forecast continues to verify warm, despite some prophetic claims of cold coming, the army of ticked off weather weenies grows angrier and more vocal toward professionals in the field on Twitter. Ten years ago, it used to be weather forums, and although there would be ridiculous forecasts and posts from the weather weenie community, there was at least some decorum most of the time. I’ve grown a bit disheartened by the personal direct attacks at those in the meteorology community. Some of these attacks come from budding meteorologists.

Most of those in the weather enthusiast/weenie community are awesome people. But the vocal minority have gotten loud. And I will say: This isn’t limited to the weenies of the East. There are professionals in our field that also engage in this sort of deplorable behavior. I’m not going to admonish anyone specific or stand over here yelling “play nice!” But it would be nice if everyone could play nice and take it easy on one another. Calling someone a name won’t make it snow any more in your backyard. Taunting the weenie community won’t make them realize the snow deficit isn’t ending in the near future. So everyone should step back and chill.

But it got me thinking. Why is the hate so evident and vocal this year? I have a theory. We (collectively the degreed meteorologists or professional meteorologists employed in the private sector, NWS, or media) are “The Establishment.” What’s been a key component of the 2016 presidential campaign? A revolt against The Establishment. We generally go by the book and play by the rules. We fraternize with one another. We’re friendly. We’re employed or between jobs. Most of us have degrees and went through the calculus, dynamics, etc. We believe in meteorology first above modelology. Our forecasts are considered “official.” Most users of our forecasts have no problem with this. Some may seek another opinion here or there, but for the most part, they trust us.

But then you have a subset within the field of voices who have gone their own way and charted their own course. Many of them haven’t done the hardcore math or have degrees in a field even remotely related to meteorology. But many of them have tirelessly studied it as a hobby. Many of them are exceptionally talented weather forecasters and do an extremely good job feasting on the weather niche that exists in social media. The majority are well-intentioned, smart people, and a handful are better at forecasting and sniffing out patterns than some of the best in the field. Yet, a few are full-on weenies that think they use meteorology to make one plus one somehow equal three. These false prophets are the ones that the most vocal and vile of the weenies turn to in times of misery…grasping for hope in a hopeless pattern. To these weenies, we are The Establishment and the false prophets are the grassroots voices of hope. I believe they feel some of the false prophets are marginalized and kicked aside by those of us in The Establishment, and they feel a need to defend their people…similar to how some anti-establishment candidates are supported in politics. Thus, you see a revolt.

I don’t know what it means ultimately. This problem won’t go away, and it’s not something we should completely ignore as a meteorology community. I think better understanding and tolerance all around is needed. But I think if you frame your approach to this divide within the weather enthusiast community as thinking you’re just part of The Establishment, you may be able to devise a different approach to dealing with it. It’s just food for thought.

El Nino Rains: Comparing 2015 so far to other beasts of the past

The fever pitch of El Nino headlines and articles isn’t slowing down. In fact, it’s only growing:

El Nino Fever Pitch

It comes mostly with speculation, preparation, and wonder. Some of the headlines are ridiculous (just go back through photos on my Twitter timeline). Most are reasonable. But it’s news. And it’s clearly a high impact weather phenomenon.

So it begs the question: How’s it doing? Is El Nino behaving like it’s supposed to? Specifically with regard to rainfall. Remember, this El Nino event is a strong one. In fact, it’s the strongest since 1997, and in some respects, it may be the strongest on record. So we have a pretty clear set of analogs to look at and see if this year fits the mold.

Judging by the temperature forecast for the next 10-15 days, the pattern seems to be mostly behaving like a strong El Nino should in December. How about rain? Let’s look back at other actual strong El Nino events and see where 2015-16 is falling relative to those events, specifically in terms of rainfall.

A caveat here: Remember, it’s early. Winter is a marathon, not a sprint. Because something looks one way on December 8th, doesn’t mean one month from now we’re going to be in the same boat. But there are a few interesting nuggets to pull out of this, and I think it’s mostly a good idea to give people some perspective on certain story lines.

Just as a note, my definition for “strong” El Nino events was using a blend from Jan Null’s list post-1950 and Klaus Wolter’s list pre-1950, as well as some “artistic liberty.” Not everyone agrees on the perfect definition of what a strong El Nino is, but hopefully I captured the majority. I’m tracking rain from July 1-June 30.

Southern California

When people think of El Nino, many think of SoCal. You know, mudslides in Malibu, etc. I believe the mayhem of 1997-98 and subsequent personification by Chris Farley has set a level of expectations.

Thus far, 2015 is behaving pretty much about where other strong El Nino events have done in Los Angeles:

Los Angeles Rainfall

Every strong El Nino event back to the 1800s has had normal or above normal rainfall in Los Angeles. Thus far, thanks mostly to a freak wet event in early autumn, Los Angeles is indeed above normal. It is worth noting, that 2015-16 wouldn’t be the only strong El Nino year to see a “freak” early autumn rainfall event followed by a prolonged period of dryness into December. So if people are wondering where the rain is, wait a few more weeks. We are entering the ramp up period. If things don’t start picking up by late month, then we can start to worry.

Northern California

Northern California is a conundrum during strong El Nino events. Historically, San Francisco is split between above and below normal rainfall, so it’s tough to say too much at this early stage. That said, it is worth nothing, that as of right now, this El Nino is on the lower end of the envelope in terms of rainfall in strong El Nino events in the Bay Area:

San Francisco Rainfall

Like Los Angeles, it’s still early. The ramp should start soon if we’re going to go above normal, so again, if things don’t perk up by late December, it might be time to plan on a normal or drier than normal winter at best.


This is where it gets interesting. For the most part, the El Nino signal in the Pacific Northwest is somewhat mixed. You get dry years and you get wet years. Usually, however, you don’t have a super wet year when there’s a strong El Nino.

In Portland (where the data is only available back to the 1957-58 El Nino) no strong El Nino has been wetter than normal. Seattle is mixed from slightly above normal to way below normal. So far in Seattle? It’s the wettest strong El Nino to this point on record, and it’s not even close. This autumn has been incredibly wet so far.

Seattle Rainfall

If we keep up at this rate (and the current forecast implies this), this will quickly become one the wettest, if not the wettest strong El Nino event on record in Seattle.

Great Basin/Rockies

In Denver, the bend is toward a wetter than normal outcome in strong El Nino years, but it is mixed. So far, Denver has been mid-pack for strong El Nino events.

Denver Rainfall.png

Salt Lake City is a bit more mixed, split almost evenly between wetter than normal and drier than normal (82-83 was a beast there). So far, we’re doing middle of the pack there also.

SLC Rainfall

It will be interesting to follow this as we go through the cold season. I’ll likely be tracking this, as it’s good to establish where this El Nino event falls. For everyone, it will probably be different. But thankfully we have a useful sample in a number of places to utilize.

Texas Deluge & Perspective

I’ll preface this by saying I am not a social scientist. But I am intricately interested in how my forecasts and commentary are perceived by my audience. I want to ensure the message I’m sending is the right one. I don’t obsess over it, but I kind of do. I always go back over emails after an event and ask myself what I could have said or done better, even if the forecast would be considered a successful one.

I received roughly 9.5″ of rain between Saturday morning and this evening in Houston. That’s a thumping. Yet, fortunately in Houston, problems were relatively minor. Yes, there was flooding. Yes, some people lost their cars. But considering what *could* have been, it wasn’t terrible.

But it got me into a conversation. Having forecasted this event, I found myself feeling very familiar for some reason. This was a complex meteorological setup, involving a number of features. The rains south of Dallas were related, but different relative to the rains in Houston. Ultimately, the remnants of monster Hurricane Patricia got involved and we had some sort of hybrid type storm slide up the Texas coast into Louisiana.

I grew up in the Northeast. What I was doing was treating this like a nor’easter without snow. In my forecasting, I said, this is a lot like any old nor’easter you’d see traveling from NC to off Cape Cod…except in this case, it was from Brownsville to about Cameron, LA. The end result to this forecaster was…nor’easter. Treat the banding like a nor’easter. Emphasize gradients. Play up coastal impacts. All of it made what was a really complicated forecast seem somewhat easy to me. It also made it a LOT easier to communicate the impacts to my audience at work.

I had a good conversation about this via Twitter with Taylor Trogdon (@ttrogdon) of NWS Memphis. He had posted this:

So I mentioned to him that I had really approached this as a nor’easter, and we discussed this further:


And it really struck me what was happening here. When you can actually relate to an event or speak to it from some sort of unique perspective, you add a whole new dimension to your forecast. Not only does it liberate you a little from the uneasiness in the meteorology leading into the forecasted event, it allows you to communicate more effectively and speak from experience in a way that maybe people in your audience could relate to better.

I realized I’ve done this before. During Hurricane Sandy, I had responsibility to forecast for company assets in New York City and Jersey City. I, like many others, struggled to grasp the enormity of the storm. So I knew trying to explain it in a simple manner was going to be close to impossible. So I thought it over and said, “OK, think of the worst nor’easter they’ve experienced in the last 15-20 years.” And I instantly went to December 1992, when I remember pictures of the New York City subway system submerged from flooding during a pretty epic nor’easter. Other than Hurricane Donna in 1960, it was the highest tidal level ever recorded in NYC. So what I told people was to expect a surge/tide that was as bad as December 1992…and likely worse. And I constantly emphasized that, because I knew it would likely exceed 1992. I could tell people all day that tidal levels would be 10-12′ or higher in New York, but no one would really be able to truly grasp that. So by inserting a visualization (Hey, remember 1992…we had flooding in the tunnels and subways. Yeah, it’s going to be at least that bad and probably worse.) I was able to get my audience to understand that it was going to do serious damage.

So, what’s the lesson in all this? If you can relate a forecast to something unique that YOU have experienced or witnessed, you can better communicate that information to your audience. We rely on computers so much for our forecast data, but to inject a human element into the whole thing is much more difficult. But it can add so much when communicating the info to other human beings. That’s why I’d advocate you become very familiar with local weather history for where you forecast. Just remember…no two weather events are ever exactly alike. Yes, you can help make a weather event more relatable, but it’s important to make sure the risks are highlighted. Make sure a good balance is struck. If I can do that, I feel like I’ve been successful.

Joaquin: Many unknowns

“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.” – Donald Rumsfeld

The quote often gets made fun of, but it’s pretty brilliant. Joaquin fits about all these categories.

This is my effort to enlighten friends, family, and anyone else who may respect my viewpoint on my thoughts regarding Joaquin. Much gets lost in a Facebook post or Twitter comment…here’s where I stand as of 4:30 PM CT on Wednesday.

What: A prolonged significant weather event from the Carolinas, perhaps as far north as New England, but of particular concern in North Carolina and Virginia. Wind, river flooding, rainfall flooding, coastal flooding, and beach erosion are all threats.

When: Primetime looks to be Friday to Sunday, with some risks on either side of those goalposts for longer duration.

First things first: This is not Sandy 2.0. There are many meteorological differences, not the least of which is that Sandy had a massive footprint over a huge chunk of ocean, able to generate massive waves that just obliterated the Jersey Shore.

Joaquin will not have a 500 mile tropical storm wind field in all likelihood. This is not me writing off Joaquin. There are similarities to Sandy…no question. But I want folks in Jersey to understand that this is an entirely different animal.

Now that we have that cleared up, let’s talk about the main threat first: Flooding.


By far, the aspect of this storm that is probably most concerning to most meteorologists will be the rainfall that will occur…perhaps both because of AND in spite of Joaquin. The clock on the rainfall forecast map from the National Weather Service below starts at 8 PM ET this evening and goes out a week.

093015_WPC Rainfall
7 Day Precipitation Forecast (NWS)

Yes, that’s 7-10″ of rainfall over a broad area. Recent rains have saturated the ground, thus flooding is likely in spots. In fact, some computer models have been hinting at 12-20″ of rainfall in parts of Western North Carolina and Upstate South Carolina. And that particular model is the one taking Joaquin out to sea!

Key point: Joaquin is a point on a map. Joaquin’s impacts (and thus those of the larger weather pattern) cover a massive chunk of real estate, extending from Georgia through Southern New England. Therefore, do ***NOT*** focus on Joaquin, particularly with regard to rainfall risk. It’s going to rain — a lot, regardless of Joaquin’s final outcome.

Coastal Flooding

Let’s talk coastal flooding risk. Here are tidal forecasts for the Chesapeake Bay Bridge & Tunnel, as well as Atlantic City:

Forecast Tidal Surge Chesapeake Bay Bridge & Tunnel (top) and Atlantic City (bottom) (NOAA)
Forecast Tidal Surge Chesapeake Bay Bridge & Tunnel (top) and Atlantic City (bottom) (NOAA)

I want to point out a couple things. Don’t focus too much on specifics here. These charts are complex, but what stands out? Starting tomorrow, tides begin to increase. This is in response to onshore flow between high pressure to your north and low pressure to your south. Notice, we go through 6-7 tide cycles with pretty high tides. This is a problem. What happens is, you have onshore winds that persist, so as each tide cycle passes and gets higher, less water is able to ebb back out, so you end up stacking up water. Particularly in areas with back bays, that water can often get “stuck” there, leading to prolonged nuisance flooding and in some cases moderate to severe tidal flooding.

Key point: Multiple high tide cycles will likely cause considerable coastal flooding issues regardless of the final track of Joaquin. Where Joaquin comes ashore (if it does) will have surge issues to contend with, but even if that does not happen, you need to plan on significant travel disruptions on coastal barrier islands between North Carolina and New Jersey, possibly as far north as Long lsland.


Here’s where Joaquin’s final track comes into play. If Joaquin goes out to sea, yeah, it’ll be breezy. But it likely won’t be severe wind. If Joaquin makes landfall, we will have strong winds in about a 100-200 mile radius from the center of the landfall point…possibly a bit further out. The winds near the center would likely be hurricane force. To the north, they’d be tropical storm force at times I would think. Additionally, inland wind, coupled with heavy rain would almost certainly lead to downed trees and power lines, and thus power outages. If you live anywhere under threat, it would probably be wise to have a few days of provisions in case long-duration power outages occur.

So What About Joaquin’s Final Track?

I hate this. I really do, but we simply do. not. know. where Joaquin is going right now. In the meteorology community, you’re hearing about the Euro vs. GFS. The Euro is the model that nailed Sandy well in advance, so it has a justifiable blue ribbon reputation. The GFS recently underwent a massive overhaul that aims to improve it. Well, here’s the test. The GFS slams Joaquin into the North Carolina coast at an angle that is extremely rare for that part of the world, and it would likely maximize storm surge potential from about Cape Henlopen, DE to the Outer Banks of NC. The GFS has support from other global models (UKMET, Canadian, as well as the majority of the tropical models that you often see in “spaghetti” maps…which I will not show).

Then you have the Euro. Oh, yes…the Euro. The Euro plays a very complex game of meteorological “thread the needle.” Without going into details you won’t care about, processes take place that force Joaquin to exit stage right out to sea. Again, this result still causes major rainfall in SC, NC, and VA, but the hurricane itself goes away.

Which model is right? I wish I could tell you. This has a lot of meteorologists scratching their heads right now (including myself). The best I can do for you is illustrate probabilities. I have the utmost respect for the National Hurricane Center, as there are great people working there. They have to stick to certain guidelines and in certain storms that doesn’t always work best I think. Thus, I wanted to annotate the 5 PM ET NHC forecast with my own thoughts.

KEEP IN MIND: These are my thoughts only. Consider them an opinion. I am a meteorologist, but I am not a source of official information. Regardless of what I say, please follow your local NWS office’s advice, local media, and direction of emergency managers.

National Hurricane Center forecast, annotated with my personal thoughts.
National Hurricane Center forecast, annotated with my personal thoughts.

7 AM ET Thursday Update: I am revising odds to:
A: 10% (-10)
B: 20% (-10)
C: 5% (0)
D: 65% (+20)

As you can see, I have started from Saturday and laid out 4 crude scenarios and how I feel about them. These probabilities are based on my assessment of the weather pattern and models right now, and they will change over time.

Scenario A: A left hook into Cape Lookout or further south. I give that 20% odds right now. That would be a major strike for North Carolina, Virginia, and southern Delmarva.

Scenario B: A left hook into the Virginia Beach area, the Chesapeake Bay, Delmarva. I assign this about 30% odds. This is what the models seem to be clustering toward. This would be a major hit for many areas from Southern NJ through NC.

Scenario C: This is the Sandy II scenario with a left hook into NJ. I give this about a 5% chance. No models are explicitly showing this. It is an ultra low probability right now, but as laid out above, even if this doesn’t directly hit you, it could be a bad storm.

Scenario D: This is the Euro out to sea special. I assign this 45% odds right now. This may seem high, but I like how the Euro has handled this system so far relative to the GFS, and I have more faith in how it’s placing upper level features that will determine the outcome of Joaquin. Still, if you want to be technical, I have 55% risk of a hit and 45% risk of a miss, so.

Final words: Again, it’s critical that you heed your local emergency management office’s advice. These folks know what they’re doing. They plan for this. If they say you should do something, do it. Again, also, when crunching the mountains of information being thrown at you, consider again that Joaquin is much more than a dot on a map. It’s a lead actor in an intricate stage production, with a LOT of supporting cast members, all of whom will determine the final scene’s outcome. Stay alert, prepare, don’t panic, but use good judgment. 

Blizzard 2015: Blame, Modelology, and The Art of Snow Forecasting

Note…my comments here are my own, based on what I witnessed in the forecasts from the Northeast, what I did myself, what I told friends/family that lived in the Northeast, and what I observed on TV and in social media and what I have learned in my 10+ years in the field. I’m not the authority on this. No one is. But I saw enough to feel I can make an informed judgment.

Let’s start with a few things.

There’s no reason to “blame” anyone today. Blame is a pretty harsh critique and implies that one individual or group caused an action. No one should blame the meteorologists, the media, the politicians, or the weather models. No one deserves blame for today because today’s snowtastrophe in New York City/NJ was a combination of a lot of issues we all have to contend with, regardless if we’re in the media, in the private sector, a viewer, a consumer, a decision maker, anyone.

First, let’s get this out of the way. This was a glowing success for forecasters in Eastern New England. The models did well there for the most part, and we saw a ferocious monster of a storm, as was predicted. But we need to stop saying that this was a “good” forecast that only missed a city by 40 miles. Once the weather model data locked in on this storm, the fate of Eastern New England really wasn’t in doubt. But the fact is, the forecast failed over a city of 8.5 million people, and the nation’s largest metropolitan area, the nation’s most densely populated state, and pretty much the epicenter of the country. We shut it down for a glorified nuisance storm. The negative reaction is warranted because for the largest urban center in America, the forecast failed.

Let’s not blame politicians. I am almost always on the side of my fellow meteorologists when the old battle of a politician blaming the meteorological community comes up. It happens far too much because of selfishness, blame deflection, and poor judgment of politicians. But they do not deserve blame in NY or NJ today. The official forecasts that were posted by the National Weather Service called for over 18-24″ for a large chunk of the NYC metro area, if not all of it, and they stuck to their guns til the end. My question to people blaming politicians is “what would you do if you saw that forecast?” We can argue all day about probabilities and risks to the forecast being mentioned to officials, but the simple fact of the matter is…if the NWS or broadcast TV meteorologists are issuing a forecast for 24-30″+ of snow, the presumption is going to be that the folks issuing that forecast are confident in it. Any forecast I issue, I assume is the most likely outcome in a particular situation. That will fail at times for sure. But when I issue it, I have to be confident that I’m putting forth my best effort. If I am a politician or decision maker, I’m going to make decisions based on the best available information, which is presumably a forecast and conversation with NWS*, who will have the best available information at the time. So we can argue if we overreact to snow in general, but in today’s world, the decisions made by the politicians were probably the right ones at the time based on the forecast data as it was presented to them.

*Note: I have an assumption (based on instinct alone) that there may have been a lot of pressure on some folks to pull the trigger and go with something to allow officials to make a decision on what to do. I strongly disagree with that, and I think there needs to be push back on theses elected officials to be realistic. But, we know where our bread is buttered, so I guess there’s not much that can be done there. But if I were NWS in NYC, I’d force a pow wow with government officials and explain to them realities of weather forecasting. This isn’t going to get any better.

Let’s not blame the media. Most of the same points above can be made. We know how the cycle works today. It will be hyped, it will be blowout coverage, it will be ridiculous. But that’s only if the forecast being fed to the “suits” justifies that. And in this case, a forecast of 2-3 feet of snow and potential risk (and explicitly mentioned one) for the largest snowstorm in the history of the largest city in America justified media going all out. Did you expect anything different? We shouldn’t have. Again, the decision the media made was probably the right one at the time, based on the forecast data as it was presented to them.

Let’s not blame the National Weather Service. The people who work at NWS (including good personal friends of mine) are good people. They try hard to do the right thing, and like any meteorologist, they’re going to have a miss sometimes too. So they do not deserve all out blame here. There were a few contrarian voices during this storm, but for the most part, we all went down together on this one.
Don’t blame the models either. I could go back through all the runs of the GFS, the NAM, the Euro, the SREF, etc. during the duration of the storm’s modeled life cycle and probably find at least one run of each that had the right idea. This isn’t a Euro vs. GFS thing. We joke so often that the GFS sucks. Sure, it does a lot. But guess what, so does the Euro. The Euro has been flawed frequently for a long time. It’s considered the gold standard of weather modeling, but maybe it should be considered the bronze standard instead. There is no gold standard. None performed particularly well, but models are models. It’s our job to scrutinize if they may be right or wrong, which brings me to my next point….

Modelology must die. Repeat. Modelology must die. This point is intertwined with another which I’ll make. I’m very guilty of this sometimes too. But we have to stop leaning on models like the Euro or the NAM or the GFS. Models aren’t meant to be gospel. They’re meant to guide a human into using their experience to create what is ideally an objective forecast based on a large amount of evidence to support it, coupled with that personal experience. Throughout this event, we saw Eastern New England getting clobbered run after run. But NY/NJ were getting clobbered, then nothing, clobbered, then nothing. In my experience, that means there’s a problem and you need to dig beyond the models and start blending ideas and throwing in a more subjective “gut” factor (that is real in meteorology and frankly, that’s why some of us get paychecks whether anyone wants to admit to it or not). For my friends and family I started sounding the alarm Sunday night that this might not pan out quite as expected. I got suckered back in Monday morning after looking at the Euro and saying, “Well, this sure has been mostly consistent.” I think most of us felt uneasy about this on Sunday. We need to really try hard to let go of the models, even if they have a good/bad reputation and blend some, fudge some, and use our experience. The message was great for Philly and Southern NJ that this was going to be a close call. I think people there understood it. But in Northern NJ/Central NJ and NYC a lot of people just saw bulled up NWS forecast and the support it received elsewhere and thought this was going to happen, and it was going to be big. Which brings me to…

Snow forecasting is not a pure science. It’s truly an art. And it should be treated as such. When I worked in lake effect country, we dealt with sharp gradients constantly, periodically in the larger cities in that area. I recall one instance that I went all in and went with a 12-18″ forecast for our main city. The band stopped just north and never got its act together. It was 6″ if we were lucky. I learned then never to go all-in on a snow forecast. Someone might argue with me that “well all the best data said feet of snow.” That’s fine. But snow forecasting is as much about managing and communicating a message as it is about getting it right. We’re never going to get it perfectly right. Snow is incredibly difficult to forecast, especially when it falls on a gradient like the one east of NYC. We can’t jump from “maybe at most” 6-10″ to 20-30″ in one day. You have to be gradual and emphasize those risks, both upside and downside. This prevents a “whipsaw” effect like going 8″, 30″, 28″, 24″, 12″. And it gives you so much flexibility as a forecaster.

So this is a lot of words. What is this one person’s opinion on what we should take from this?

  • We live in a new social media reality. We can’t complain about these “weenie” sites making bogus forecasts all the time. Hopefully the fall out from this helps people realize the next time we have a borderline situation and someone shows a BIG SNOW map that they’re just showing models and there’s a good chance it doesn’t evolve that way. In a sense, this storm may help that cause a little. But we need to learn to live with this, and rather than complaining about it, work through it and deal with it.
  • We need to stop talking about research on communication methods and how to do it better and start actually doing it. I think this conversation has been ongoing since Katrina, maybe longer, maybe shorter. I’ve seen a number of mets show simple visual graphics that explain impact risks to different areas and from different variables. Those are tremendously effective in my opinion, and there needs to be more of that.
  • I think the NWS needs to break this regimented product setup. I think at times their hands get tied. They can’t be nimble. And they need to be. Products should target impacts and be able to highlight those impacts and risks above anything else. There needs to be less meeting of a checklist or formatting something under specific guidelines.
  • The NWS and others need to also focus a little less on Twitter. As of last September, 23% of the American adult population used Twitter. Is Twitter great? Yes. But less than 1/4 of the US population uses it! Having awesome graphics on Twitter doesn’t substitute for having a good forecast and successfully communicating the risks to the forecast. Lots of people (over 70%) use Facebook, but the reach is so wonky because of their news feed algorithm. I like a lot of the stuff the NWS produces on Twitter and Facebook, but I’m questioning how much value it ultimately adds.
  • We all need to learn to stop speaking meteorology and speak English to people and be simple. Throwing in cool terms like “bombogenesis” is great, but if I’m the average viewer or consumer, I just want to know what’s going to happen, when. Maybe tell me about how it might change, but I mostly want to know what, where, and when. That’s it. Science lessons are wonderful, but I’m not sure they’re particularly valuable. I used to be vehemently anti “dumbing it down.” As I’ve worked more, I’ve learned that when you “dumb it down,” you’re not actually dumbing it down. You’re providing simple, useful information for a person. And that’s a wonderful thing.
  • I wish respected meteorologists would stop showing model maps at all. I think it plants seeds that can’t be dug back up and creates a preconceived notion no matter how often you caveat it.

There are a number of lessons to be taken from this storm I think. I just hope we’re all humble enough to accept that, take them, and apply them.

Will 2014 Have the Coldest MLB All-Star Game Ever?

Major League Baseball’s All Star Game is Tuesday in Minneapolis. How convenient it should coincide with one of the most significant cool summertime air masses we’ve seen in some time. The obvious question people will ask is, “Will this be the coldest All Star Game ever?”

The answer is a solid “maybe.” There are a number of ways we could analyze which MLB All Star Game was the coldest, but because historical weather information isn’t always easy to come by, it’s somewhat challenging. I’ve decided to sort each game by the daily average temperature, pick out the coldest, see how their hourly observations were, then cross check it vs. any games on days where the low temperature was colder than the coldest hourly temperature in the original group of games.

For 2014, I have followed the National Weather Service forecast for Minneapolis on Tuesday, which suggests 68/53 for a max/min temperature. Let’s see how it stands up (click to enlarge).



The forecast average in Minneapolis Tuesday is 60.5°. At least on a daily average basis, the 2014 All Star Game probably wouldn’t be the coldest. I’ve identified seven previous All Star Games to average 65° or cooler. The games?

1963: Cleveland, OH (Avg 56°)
1983: Chicago, IL (Avg 58.5°)
1984: San Francisco (Avg 61.5°)
1987: Oakland (Avg 64°)
1991: Toronto (Avg 65°)
1999: Boston (Avg 63°)
2007: San Francisco (Avg 64°)

Minneapolis would rank 3rd coldest on that metric, if the current forecast verifies. From this list, we can eliminate Toronto right away, as that was at the SkyDome, which is obviously an indoor event. Let’s look at the others.

I learned that the 1963 game, thanks to some Google sleuthing, was played at 1 PM in Cleveland. According to Weather Underground’s wonderful data archive (unofficial, but usually good), temperatures went from 66° at 1 PM to 67° at 2, back down to 65° at 3 PM, and finished at 66° by 4 PM. The game took 2:20 to play, so it was over by 3:30 PM. So, with gametime temps of 65-67°, despite averaging the coldest, the 1963 Cleveland game was probably not the coldest ever.

The 1983 game in Chicago began at 7:30 PM and took 3:05 to complete. The hourly temperatures from 7-10 PM read: 66, 64, 62, 61°.So Chicago beats Cleveland.

The 1984 game in San Francisco began at 5:30 PM and took less than 2:30 to complete. Temperatures went 65, 63, 60, 57° from 5-8 PM. Assuming the game ended around 8 PM local time, then the 57° in San Francisco bests Chicago the year before.

The 1987 affair in Oakland also began at 5:30 PM. That game took a more liberal 3:39 to complete. Weather observations from Oakland cut out early in the morning that day, so we’ll look across the bay at San Francisco. This isn’t the most ideal methodology (as someone who forecasts for California, I am well aware that the Bay Area can be different worlds from one side to the other at times), but it will work for our purposes. Temperatures read: 67, 65, 62, 59, 58° from 5 to 9 PM during that game. So we can assume that either Oakland or San Francisco hold the coldest temperature thus far.

Let’s jump to 1999 in Boston. The game started at 8:50 PM and went 2:53. So, just under 3 hours. Let’s look at a 9 PM-Midnight temps in Boston: 61, 61, 61, 61°. So Boston falls short.

We’ll jump back to the Bay Area for 2007. That game began just before 6 PM local time and went just over 3 hours. So the 6-9 PM obs in San Francisco? 66, 65, 64, 64°. So this missed the 1980s temps in both San Francisco and Oakland.

So now to ensure that we didn’t miss anything by looking exclusively at average temperatures, let’s look at all other MLB All Star Games that featured a low temperature the day-of that was under 57°.

1959: Pittsburgh (53°)
1961: San Francisco (56°)
1994: Pittsburgh (55°)

From the “Did You Know?” files: Two All Star Games were played from 1959-1962. But, hey, an All Star Game is an All Star Game.

The 1959 contest at Forbes Field was the first one that season. First pitch was a cool 1 PM. The game lasted about 2:30, and with temperatures in the 70s throughout, it was a great day to be in Pittsburgh and not in the running for coldest.

In 1961, the San Francisco game was also the first of the two played that year. Anecdotal evidence suggests that game was a 1:30 first pitch. It went a bit under 3 hours. Looking at the 1 PM through 4 PM obs in San Francisco, they stayed in the upper 70s. Of course, with 25-30 mph winds, that clearly made things entertaining. But, it falls well short on the cold scale.

Lastly, 1994 in Pittsburgh again, the only All Star Game I own a program from. Game began at 8 PM, and temperatures fell from the 80s into the 70s. A warm night in Pittsburgh.

So, thus, by deductive reasoning, the 1984 All Star Game in San Francisco likely marked the coldest temperature in an All-Star Game at 57°F. Arguably, it could have been matched by Oakland in 1987, but for our purposes, that’s not vital at the moment.

In order for the 2014 All-Star Game to be the coldest ever, we’ll need to see game time temperatures hit 57° or lower. I mentioned the Tuesday forecast above. It’s going to be a close call. Raw weather model data suggests temperatures in the mid 50s or even low 50s by Wednesday morning. We would want to have somewhat ideal radiational cooling conditions in Minneapolis Tuesday evening to get a quick, steady drop in temperature from the forecast high of about 68° during the afternoon. Ideal radiational cooling in summer would be clear skies and light winds (in winter, you would add fresh snowpack to the equation). I think those conditions may exist Tuesday night. It’s possible that you see temperatures drop faster on Tuesday evening than they do Monday, but have a cooler low temperature Tuesday morning instead of Wednesday. Regardless, I think it’s a good bet we see gametime temperatures in the 50s at some point, and a 57° or lower reading can’t be ruled out. If I had to assign odds, I’d go about 30% right now. Time will tell!