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| Needless to say, there’s plenty of day-after cogitation and finger pointing over the New York side of snowfall forecasts, which the European model did poorly at — along with many meteorologists. Read Henry Fountain’s news story and Eric Holthaus’s great Slate piece on how only the Weather Channel got snow forecasts right.

Original post | In what has, until now, been a quiet winter in the Northeast, nearly 30 million residents are girding for a blizzard that may end up worthy of the National Weather Service list of historic Major Winter Storms. Winds at sea are predicted to reach hurricane strength. A yard of snow is possible in parts of New England.

There are many different concerns, ranging from stocking up on water for those on wells in areas vulnerable to power outages (which was once my situation, but no more) to my teenage son’s swift click last night to the Snow Days Calculator website.

There are also plenty of questions. Here are three that I’m sending to a batch of my favorite extreme-weather watchers (including Marshall Shepherd of the University of Georgia, Cliff Mass at the University of Washington, Ryan Maue at WeatherBell, Andrew Freedman at Mashable, Dave Robinson at Rutgers, Jason Samenow of Capital Weather Gang, Eric Holthaus at Slate and my local go-to guide, Alex Marra of Hudson Valley Weather)*:



1) Unlike some other past winter nor’easters that were forecast many days in advance, this one seemed to pop abruptly into forecasts only on Saturday. What makes the difference? 2) As with some previous potent winter storms and hurricanes (including Sandy), there’s been a consistent focus on the computer model of the European Center for Medium-Range Weather Forecasts (ECMWF, for short) as the best at getting details like snowfall amounts right. Is that simply a matter of more fine-grained resolution or do you see other factors making their model best at predicting North American storms of this sort? 3) The computer upgrades announced earlier this month by the National Oceanic and Atmospheric Administration seem targeted at closing this gap. Do you see that as a decent prospect, or are there other issues at play, as well?

[Answers are appended below.]

While you’re waiting, read the 2013 Peter Miller interview with Cliff Mass discussing how the National Weather Service has been falling behind in this supercomputer push.

Follow that up with Andrew Freedman’s 2013 Climate Central piece with this troubling opener:

With a likely gap in critical weather satellite coverage beginning in 2016, the National Oceanic and Atmospheric Administration (NOAA) has not developed sufficient contingency measures to ensure that weather forecasts remain as reliable as they are today, according to three new federally commissioned reports and lawmakers at a House subcommittee hearing.

I’ll post answers as they come in.

In the meantime, stay safe if you’re in the blizzard zone, enjoy the record heat out in the Pacific Northwest or make the most of conditions wherever you might be.

Update, 10:30 a.m. | Here are Marshall Shepherd’s cogent answers to the three questions:

1. I would have to say that I started hearing colleagues stirring about the possibility of a significant storm last week, so I think perhaps the major players/media started to pick up on its significance by the weekend. I am certain that I heard Weather Channel colleagues or even Capital Weather Gang hinting at this well before Saturday. I even tweeted or messaged a heads up to a few people last week that I knew were traveling to the region. Although, I did place some uncertainty and hedging in my advice. We are in an era of “social media-rology” where every person with a computer is a meteorologist now. So there is quite a bit of long-range hype and messaging in the public space now. I think my community is trying to find the right balance on long-range messaging versus “hype.” This will continue to be an ongoing challenge with messaging, but I think the models did sniff this out a bit earlier than many may think, but there was lack of consensus. 2. Many people discuss the European Model vs GFS [N.O.A.A.’s Global Forecast System], but I find that many of these folks don’t actually understand why the “Euro,” at times, performs better. Europeans apply something called 4-D Data Assimilation; where as our models use a slightly les- sophisticated, but still effective methodologies. I am going to oversimply so don’t hold me to precision here. I am being illustrative. 4-D assimilation basically allows the weather model to be updated/nudged with accurate space-time information as new satellite and other input data is available. It is akin to placing a beach ball in a river and predicting where the ball will be in a few days, except you are constantly updating your prediction with new information on speed of the river flow, its curves, depth, etc. Less precise methods, would simply take the initial condition of the river, make a prediction and then hope :). By the way, our atmosphere is a fluid so it is analogue to the river. What has been lost in all of the Euro vs. GFS discussion are the following points. First, the Europeans are highly-dependent on satellite and other meteorological data from the U.S. We have good understanding, for example from the Europeans, on how poorly Sandy and certain winter storm forecasts would be if certain satellite datasets were with held. I have always been very uncomfortable with the “us” vs “them” narrative because it is a partnership. I had dinner with the head of EMCWF in Reading, England, a couple of years back while AMS President. He laughed at how hyperbolic the U.S. media and public was being in response to the Euro performance with Sandy. Paraphrasing, he said, GFS does better than us all of he time. This leads me to my second point. Yes, the “Euro” model has been show to statistically outperform, on average. Even the Director of the National Weather Service noted this on the Weather Channel’s WxGeeks that I host. However, the GFS (and now the WRF and HRRR) are still world-class performers. The HRRR is a very short term, high resolution model that NOAA is now running that provides neighborhood/town scale forecasts and is assimilating radar and other rapidly available data. The GFS also recently got better spatial resolution (e.g., more grid points). This is like putting more megapixels in your phone’s camera. It makes for a better picture. Sandy did lead to increased funding. It’s not that the U.S. doesn’t know how to do 4-D Data Assimilation. We do. I spent 12 years at NASA Goddard Space Flight Center and its Global Modeling and Assimilation Office was working on pioneering methods for assimilation. The U.S. model is a bit different than the Europeans. NOAA has to take a limited budget and make decisions on faster computers (required for complex assimilation schemes), new satellites (GOES-R, JPSS), upgraded radar systems (Dual-Polarization), Forecast Office personnel, and so on. It is important for the public to understand this rather than frame the problem as if the U.S. has been asleep at the wheel. During my AMS Presidency, I am on record as noting that our policymakers must prioritize weather infrastructure at the same level as national security (because they are actually related). The other thing that the Europeans recently shared with me is this silly notion that weather and climate funding are at odds. They look at the research and operational continuum of weather and climate. Whereas, here in this country, they are politically placed in head-to-head battle. That’s not smart. 3. While some will respond and downplay the recent supercomputing upgrades by NWS, I believe that they are an essential step towards rendering the “Euro vs GFS” debate obsolete. It’s a start. Do we want more? Of course, it is a start, and we must be careful not to be cynical of the step. NWS’s annual budget is smaller or comparable to major University budgets. I believe that is unacceptable. Take a storm like the current blizzard, the combined snowfall, near hurricane force wind gusts, and coastal flooding will lead to property damage and possibly loss of life. 1 Storm. Studies show the value of weather information on GDP (see Lazo in the Bulletin of the AMS) so it simply doesn’t make sense to me that we don’t invest adequately in improving our weather infrastructure. We need better observations in urban environments like the cities under fire today from the blizzard. We need to understand how much more sea level is being shoved ashore compared to a the same storm 50 years ago. We need to make sure that our GOES-R and JPSS programs are fully-funded so that there are no gaps in coverage in a few years. We need to make sure that NWS offices are fully-staffed. Many are not. We need to make sure that our civil infrastructure and cities are designed/planned for extreme weather events. For example, many stormwater or snow management systems may be designed for storms of last century. Now to be clear, I am NOT saying this storm is caused by changing climate. It is irresponsible to do that. However, I am not dismissive of the need to understand the weather-climate continuum that our European counterparts already do (and laugh at us because we don’t).

Update, 10:38 a.m. | Here’s Andrew Freedman on the four questions (including the footnote about gender):

1. The forecast evolved rather suddenly once the weather system moving southeast from Canada was more fully sampled by observing networks, and computer models came around to a more threatening solution. Typically these days we get more advanced notice for a storm of this magnitude, but this illustrates that that’s not always the case. If NOAA experiences a gap in satellite coverage around 2017, this type of scenario may happen more frequently. 2. The contest between the European model and the American models is somewhat overblown in this case, considering that ALL the models are showing a significant storm for the Northeast with differences in where the heaviest snow sets up. In this case, the NWS and others are looking at a wide range of guidance to come up with their forecast. Yes, the European model has been the most consistent in its projections, and the upgraded GFS has danced around a bit, but that doesn’t mean one is right and the other is totally wrong. The NWS is investing in more supercomputing power but it still won’t bring us on part with the Europeans anytime soon, but that doesn’t mean our forecasts will automatically suffer. 3. The NWS is trying to close some of the gap, but the gap won’t be fully closed by any means, given the Europeans’ investments in 4-D data assimilation and other techniques that improve their models. Interestingly, the Europeans rely on our satellite data as an input for their models, so if we lose satellite data for a while, as the GAO is worried about (see: //www.gao.gov/products/GAO-15-47) it would reduce their accuracy as well as ours. [Added: This storm will provide an interesting test of the newly upgraded GFS model, which is now being run at a much higher resolution than it was just a few months ago. It will take forecasters some time to learn its hidden idiosyncrasies, kind of like going on a first date with someone you had a crush on years ago, and you think you know them pretty well. It may well turn out to be right in this situation, which would mean New York City would see closer to a foot of snow, rather than one to two feet.] As for female meteorologists, there are tons. More so than in climatology, I’d argue. Most prominently Ginger Zee, Bernadette Woods Placky at Climate Central, Kate Bilo at CBS in Philly, and others.

Update, 11:00 a.m. | Cliff Mass sent these thoughts on the three questions:

1. There is a difference in predictability among storms for a variety of reasons, particularly since major storms require a number of ingredients to come together in an optimal way for development. In this case, the models honed in to a major storm development late on Friday, three to four days ahead of time. This contrasts with Sandy, a storm with tropical roots, that was predicted skillfully 4-7 days out. 2. The U.S. has caught up in resolution, but still lags in key aspects of modeling such as data assimilation (the ability to use all the observations to describe the state of the atmosphere). This needs to change. 3. The computers are important but are not enough. The European Center has superior data assimilation (the ability to use all the observations to describe the state of the atmosphere) and the National Weather Service needs to catch up in this area. Furthermore, the European Center is closely connected with the research community and the latest research advances; the National Weather Service has not been. The new computers give the National Weather Service the potential to be the best in the world if they tap the large U.S. weather research community and use state-of-the-science technology.

Update, 8:05 p.m. | Here’s Ryan Maue (I included the preamble because it makes an important point even while not making a point):

Thanks for the opportunity to answer your questions — they are right up my alley. I chose to tackle (2) and (3) as I’m not entirely sure why this blizzard was such a “surprise”. Hard to know in retrospect what we were missing before we knew what we didn’t know ;-) Enjoy the wintry mess.

Cheers, RYAN Weather forecast model horizontal resolution is important to achieve an accurate representation of a given storm or phenomena, but high vertical resolution is also critically important. ECMWF leverages its powerful computing infrastructure for one main goal: medium range or 3-8 day forecasting. Global deterministic weather models are “frozen” meaning physics, radiation, boundary layer, and land surface schemes are chosen a priori. These parameterizations or “knobs” are tuned from the bottom up through years of sensitivity testing, trial and error, and experimentation. The end goal is to achieve globally the best possible forecast as verified by dozens of important metrics. ECMWF, NCEP GFS, UK MetOffice Unified Model, and Canadian GEM are the top global weather models and each use somewhat different methods to forecast one atmosphere. The global deterministic forecast process is an initial value problem so the best analysis of time zero is critical for the best skill. As an example, ECMWF uses 4D-Variational data assimilation techniques to optimally combine an astounding amount of satellite and conventional data over a given window in time. This aspect of the ECMWF system is (still) superior to that of NCEP GFS. The ECMWF model physics have also demonstrably performed better especially in the case of Hurricane Sandy. However, 95% of the time, each model is performing at about the same skill level as quiescent weather is not particularly challenging for today’s numerical prediction systems. Of course, extreme events are the most visible and public tests of each model. Part of my job is to produce value-added weather maps for dissemination on social media. The public now has easy access to the same or even better tools (maps, weather data) that trained forecasts in real-time. The Euro and GFS have become part of the public lexicon just like the Polar Vortex and Superstorm. The GFS upgrade is more of a “bunny hop” in terms of expected skill improvements as only horizontal (not vertical) resolution was increased dramatically. The upgraded model so far has received a lukewarm response from experienced public and private forecasters. It is still early in the process of evaluation. Over the next year, using newly acquired computing power, GFS will more easily be upgraded and achieve more pronounced skill improvements. However, the “model wars” will only intensify as ECMWF continues to further upgrade its computing capacity and modeling software. The end result of such heated international competition (and cooperation) is better weather forecasts further into the future. Competition is healthy.

* Footnote | I know lots of highly-respected female climate scientists, among them Jennifer Francis, Judith Curry and Florence Fetterer. But most high-profile, storm-focused meteorologists seem to be men. Please weigh in with names and links to women in this arena to broaden the field of view!

Update, 9:50 a.m. | Some clues on the gender issue are in this post on Kendra Kent of Fox Carolina by a business consultant, Frank Magid: “Women and Weather Jobs — The Big Freeze-Out.”

Updates on women in weather:

Update, 8:18 p.m. | The American Meteorological Society responded to this post with a piece on its Front Page blog tonight on “gender imbalance” in meteorology, alluding to a paper in press in the Bulletin of the American Meteorological Society titled “Women in Academic Atmospheric Sciences.”

@Revkin @dotearth I’m a female weather nerd, and have been professionally for 20.5 years now. Ask @DrShepherd2013. he will agree. :) — Tanja Fransen (@mtwxgirl) 26 Jan 15

@Revkin More hurricanes & tornadoes than blizzards, but these women geek the storms @SarahStrazzo @KelseyNEllis @muld9049 — James Elsner (@hurricanejim) 26 Jan 15

Via Twitter, Marshall Shepherd pointed me to the “winter weather misery index” created by National Weather Service meteorologist Barbara Mayes Boustead (@windbarb).

Another meteorologist, who asked not to be identified because she works for a federal agency, added a vote for Andrea Thompson of Climate Central, in large part for her Twitter feed at @AndreaTWeather. Here’s an example:

How much snow will we get during the #blizzardof2015? Here’s why that can be hard to pin down: //t.co/N5hM6ljk5y — Andrea Thompson (@AndreaTWeather) 26 Jan 15

Here’s another endorsement: