The Local Storm Report product still has value

Several tornadoes hit central Indiana last month. During the event, a tornado warning was issued for Indianapolis. I saw several local media people tweeting that police had reported a tornado but no Local Storm Report (LSR) had been issued by the National Weather Service. I thought that was rather odd, and mentioned this incongruity in a tweet. It didn’t seem right to me that a tornado could be reported in the 14th-largest city in the United States but have no LSR issued.

Several people replied to tell me that the police report was included in the text of the warning. I did not take kindly to that. While including such information in a warning is great, that’s not what I was after. I specifically wanted an LSR. I was asked if it’s still a relevant product,  so here’s this post.

The Local Storm Report is still a distinctly useful product because it has a defined format. While most people do not consume LSRs directly, the rigid format allows it to be used in a variety of useful ways. For example, a media outlet can parse the incoming LSRs and use the coordinates and type to make a map for TV or web viewing. This can help the audience better understand the type and location of a threat.

Additionally, they’re helpful for downstream experts (other forecast offices, emergency managers, etc.) to know what a storm has produced. I often watch the LSRs issued by the Lincoln, IL or Chicago offices when severe weather is approaching my area to see the ground truth to go along with the warning. Knowing that a storm has (or hasn’t)  produced what the warning advertised can be very helpful in formulating a response to an approaching weather threat.

Apart from the warnings, timely and frequent LSR issuance is one of the most valuable functions of a National Weather Service office during a severe weather event.

But what about social media?

I’m glad you asked. Someone suggested that social media is a better avenue for communicating storm reports, in part because a picture is worth a thousand words. I agree to a point. Seeing a picture of the tornado heading for you is more powerful than words or a radar image. In that sense, social media is better.

But Facebook is awful for real-time information. Twitter is limited in the amount of detail you can include and has a relatively small audience. Plus, social media is hard to automatically parse to reuse the data, unless every forecaster tweets in a prescribed format.

The ideal scenario would be to tie social media into the process of issuing LSRs. As an LSR is generated, the forecaster would have the option of posting the information to the office’s social media accounts (perhaps with a link to the LSR) . If we’re granting wishes, the posting process would also allow for the inclusion of external images.

Until that day comes, I’m going to keep looking to LSRs for verification during severe weather events. And I’ll keep being disappointed when they’re not issued. 

New entry in the Forecast Discussion Hall of Fame

Most entries in the Forecast Discussion Hall of Fame earn the honor with a consistent excellency throughout the entire work. As Hurricane Hermine approached the Florida coast earlier this week, forecasters at the Tallahassee forecast office were focused on the effects of that storm. The fire weather discussion contained a single word, and that’s what landed it as the most recent entry.

It’s worth noting, too, that several subsequent updates to the Area Forecast Discussion left the fire weather section unchanged. I’m glad to see Southern Region Headquarters did not immediately rain bureaucratic hell upon the office. I’m not sure that would be the case in other regions.

Long range heat wave forecasts

What if I could tell you today that we’d have a major heat wave on June 11? A recently-published study could make that possible. Researchers analyzing heat waves over several decades have found a signal that improves the reliability of long-range heat forecasts. Will it be useful for forecasting specific days? I have my doubts, but we’ll see. They apparently plan to use it quasi-operationally this summer.

The more likely scenario is that it will help improve probabilistic forecasts on a multi-day-to-month scale. For example, the one month and three month outlooks issued by the Climate Prediction Center. There’s clear value in knowing departure from normal conditions over the course of the next few months, particularly for agricultural concerns but also for civic planning. I’m not sure I see much value in knowing now that June 11 will be oppressively hot as opposed to June 4.

While this study got a fair amount of coverage in the weather press, I don’t see that it will have much of an impact to the general public for a while. In fact, if it results in gradual improvement to long-range probabilistic forecasts, the public will probably never notice the impact, even if it turns out to be substantial over the course of several years.

To warn or not to warn?

The decision to issue a tornado warning is a difficult one for meteorologists. A timely and accurate warning can save lives, but a false alarm contributes to an already-too-high indifference among the public.

On March 31, thunderstorms moved through Indiana in the mid-afternoon. The Storm Prediction Center had a slight risk for the area, so I had been keeping an eye on them. One cell had shown rotation since it had been in east-central Illinois. After a while, it started to fall apart. Then around 4:40 PM, I happened to glance back over at the radar, and I saw this:

KIND reflectivity and velocity at 4:42 PM Eastern on March 31, 2016.

KIND reflectivity and velocity at 4:40 PM Eastern on March 31, 2016.

Oh yeah, there’s something going on there. I was talking to my friend Kevin and we were wondering why there was no warning. Even if the forecaster didn’t think a tornado warning was justified, a severe thunderstorm warning would have been a good hedge. As it turns out, the storm produced a brief EF1 tornado about a mile east of my house.

I don’t know why no warning was issued. But here’s a different take: should a warning have been issued? No one was injured and the damage that was done couldn’t have been prevented with a 10-15 minute lead time. Should this count as a false negative?

Yeah, probably. Although no one was injured, a small difference in the location could have easily changed that. But it makes me wonder if warning for every tornado is a reasonable goal.

Should meteorologists share velocity images with the public?

This week is Severe Weather Preparedness Week in Indiana. For more information, see the NWS Indianapolis website.

If you’re not sure what I mean when I say “velocity images”, you can learn about how weather radar observes winds here or here.

Meteorologist Joe Moore asked an interesting question on Twitter:

The overwhelming majority of respondents say sharing radar velocity images with the public is okay, at least in certain circumstances. My vote was for limited use.

On the one hand, informing and educating the public is a primary duty of meteorologists in both the public and private sectors. A velocity image can sometimes help make the location of a tornadic threat more clear, particularly in squall line or otherwise messy setups. “This is the bad part and it’s coming right for you” can be a powerful motivator to take shelter. In addition to immediate information, the images can be used to provide more general education. “This is how the radar works” isn’t of immediate value, but it can lead to a better understanding of meteorology in general.

On the other hand, meteorologists tend to be science geeks, which can sometimes lead to giving too many facts with no informative value. In severe weather situations, clear and timely information is paramount. If a television viewer gets confused by the velocity image and focuses on that to the exclusion of the “hey, you should really get to the basement now!” part of the message, sharing the image ends up being harmful.

As Joe said in a reply, “Can you explain it in a tweet? And still be timely/relevant?” Context and information content is key.

Storm chasers as first responders

This week is Severe Weather Preparedness Week in Indiana. For more information, see the NWS Indianapolis website.

Storm spotters have a single purpose: to provide “ground truth” to officials (or media) in order to better protect life and property. Storm chasers have purposes as varied as their motivations. There are no universal rules for chasers, but one comes close: if you encounter injured people, you stop and render assistance.

Knowing that a successful tornado intercept means an increased risk of encountering storm-related injuries, some chasers maintain CPR and first aid certifications. Some carry hefty first aid kits. A smaller number will keep tools in their vehicles. (When I was chasing regularly, I thought about keeping a gas-powered chainsaw in the trunk for such an occasion, but never followed through.)

While preparedness is good, I’m concerned that a small minority will view themselves as first responders. That is an inappropriate role for someone to assume, unless they also happen to be a trained first responder when not chasing. I’ve seen this in others and I’ve seen it in myself. There’s a certain romantic appeal to see yourself as a gallant hero, watching the sky and riding in to save strangers who will never know your name.

That’s a dangerous delusion to buy into. Storm chaser and wizened sage Ams Magliocco wandered aloud about the decisions that sometimes get made by chasers when they come across storm damage:
https://www.twitter.com/amosmagliocco/status/680938771806720000

Amos’s tweet appears to be in response to the attack on Jeff Piotrowski, who was assaulted as he attempted to render assistance (while he happened to be streaming on Periscope). Jeff is an experienced and well-respected chaser, but the decision to live stream attempts to help in the immediate aftermath of a tornado strikes me as attention-seeking and not in the best interests of those who he would assist.

I don’t mean this as a criticism of Jeff specifically. I don’t know him, but I’ve known of him for years and I have a high regard for him. His incident just serves as a dramatic reminder of the possible consequences of chasers as self-appointed first responders.

Too many NWS products?

I’ve written before that the National Weather Service is stuck in a paradigm where the general public isn’t assumed to directly consume most products. NWS text products are largely unchanged from decades ago when most public consumption was filtered through media outlets or emergency management officials. As a result, products are more focused on being technically correct instead of usefully correct.

A prime example is how the National Hurricane Center decided not to issue hurricane warnings as “Superstorm” Sandy made landfall. While technically correct, the decision led to confusion and caused some to minimize the threat.

I suggested on Twitter that people really only want to know three things:

  1. How badly will my stuff be wrecked?
  2. When will be stuff be wrecked?
  3. What should I do about it?

To the extent that the specific threat matters, it only matters as it affects the answers to those three questions. If your roof disappears because of a wind gust instead of a tornado, is it any less gone? Of course, the distinction matters for scientific research purposes, but does the general public care?

When I saw an infographic that Ashley Atney put together, it hit me: the NWS simply has too many warning products. Maps like this drive the point home:

Watch, Warning, Advisory map of Arizona from January 31, 2016. Image capture via Rob Dale (@therobdale).

Watch, Warning, Advisory map of Arizona from January 31, 2016. Image capture via Rob Dale.

This may be heresy, but what if we condensed products? Winter storm, lake effect snow, and blizzard products could all be combined into one, with the product itself describing the details. After all, merely saying “winter storm” versus “blizzard” doesn’t really communicate much anyway. Further heresy would be to combine severe thunderstorm and tornado warnings.

I’m not saying that these (and other condensations) are necessarily the right way to go. There’s a lot of research that would need to be done first in order to make sure that the net effect on the public is positive. But the current system is in need of improvement.

Forecast Discussion Hall of Fame featured in The Atlantic

On Friday, The Atlantic published an article about National Weather Service forecast discussions and why they are…they way they are. The article prominently featured several entries in the Forecast Discussion Hall of Fame and mentioned yours truly by name. After years of carefully curating the best forecast discussions, my hard work is finally paying off. Time to quit my job and bask in the glory!

Okay, so maybe not. It’s a pretty cool thing to happen, though. If this blog has gained any new followers thanks to that article, welcome!

While snowfall records were falling over the weekend, FunnelFiasco records were falling, too. I took a look at the site stats for weather.funnelfiasco.com over the weekend. As of Saturday evening, just the weather subdomain had nearly 14,000 hits from about 2,700 unique visitors in January, almost all on Friday and Saturday. That’s over six months’ worth of traffic and about half a month’s for all of FunnelFiasco.

January traffic by day for weather.funnelfiasco.com through the evening of January 23.

January traffic by day for weather.funnelfiasco.com through the evening of January 23.

Let’s look at some meaningless statistics. The two largest hosts were both .noaa.gov addresses, which doesn’t surprise me. I have to figure that the article would have had some interest in the halls of the National Weather Service. A caltech.edu address was 18th, which surprises me. I guess my Purdue friends don’t read The Atlantic. The leading operating system was Windows, with iOS, Linux, and OS X following. iOS was 23% of January weather.funnelfiasco.com traffic and it’s normally 1.9% of total funnelfiasco.com traffic.

mPING and charging for free labor

In 2012, NOAA’s National Severe Storms Laboratory (NSSL) partnered with the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma to collect crowdsourced precipitation type data. The “meteorological Phenomena Identification Near the Ground” project (almost always referred to as “mPING”) allows smartphone users to easily and anonymously report precipitation type.

This information can be very valuable to operational forecasters (it is not often easy to tell if it is raining or snowing at a particular location unless someone tells you) and to researchers working to improve radar algorithms. In the slightly-more-than three years since mPING was launched, nearly a million reports have been received, which suggests the public (or at least the members of the public who know about it) find it important to contribute, too.

Which brings us to last week’s announcement that access to the data is no longer free. Apparently the discretionary funding from the NSSL has expired, so it’s moving to OU-funded infrastructure. This means that the University will try to get what money it can for the data. A variety of licenses are available, depending on what level of access is desired.

API access to submit reports will remain free, so it will not cost anyone to contribute a report. But instead of volunteering effort (however minimal) to a public project, mPING reporters are now effectively unpaid labor for the University of Oklahoma. Sources within NOAA tell me that the forecast offices and national centers will continue to receive free access to real-time data, which is good, but not the point. OU thinks this data has value, so why should people provide it for free?

I actually wonder if it has monetary value. Certainly it has utility, but I don’t see too many places being willing to pay for it. One well-known TV meteorologist has already said he will stop using mPING data on-air because purchasing a license is not an efficient use of his limited financial resources. Highway departments may be the most likely to find it worthwhile to pay for a license, as near-real-time precipitation type information could prove very useful to the dispatching of salt trucks and plows. Still, the general effect seems to be that it will put off many people from reporting, diminishing the value of what may be an unsellable product in the first place.

I get that baby’s gotta eat. I spent years working at a large research university, including supporting systems that distributed meteorological data. I understand the reality, but that doesn’t mean I have to like it. I’m pessimistic on what these changes mean for mPING, and the poor example they set for citizen science generally. I hope I’m wrong.

Rating snow storms

It may be January, but with the relatively warm December we had, I’m not ready to start thinking about snow (spoiler alert: I’m never ready to think about snow). But snow is bound to happen at some point, and the Weather Channel will be sure to name the storm. Humans like to assign numbers to things. We have ratings for tornadoes, we have ratings for hurricanes, but we don’t have ratings for snow storms. Or do we?

Paul Kocin and Louis Uccelini developed the Northeast Snowfall Impact Scale (NESIS) in 2014. NESIS considers the snow depth, the area, and the affected population. This last part makes it pretty unique among meteorological numbers. Meteorological phenomena are often considered without thought for population (for example, the National Weather Service will issue a tornado warning even if no one lives in the affected area). Tornadoes are rated based on damage (not wind speed!), which sort of proxies population, but not exactly.

NESIS doesn’t seem to be widely used, and it’s almost certainly unknown outside of the weather community. Maybe because we don’t tend to see snow storms as disasters in the same way that tornadoes and hurricanes are? It would be nice to see it catch on, though.