Blogger’s note: Below is an article I submitted to the “The Waynedale News,” a neighborhood newspaper in Fort Wayne, Indiana. If refers to the installation of an outdoor warning siren in a neighborhood that had been without one for years. The newspaper published the article July 7, 2017.
The new outdoor warning siren that’s coming to Waynedale brings with it some true risks that area residents might not have considered. Chief among those risks are over reliance and desensitization. Continue reading →
Amateur (ham) radio operator Steve Haxby, N9MEL, helps a citizen program a weather alert radio
Six Fort Wayne amateur radio operators spent several hours May 23 assisting residents with their NOAA Weather Radio (NWR) receivers.
Tom Baker, N9TB; Jay Farlow, W9LW; Steve Haxby, N9MEL; Joseph Lawrence, K9RFZ; Steve Nardin, W9SAN; and Howard Pletcher, N9ADS worked alongside representatives of WANE TV, the Allen County Office of Homeland Security and the National Weather Service at the Walgreens store on Lower Huntington Road to configure NWR receivers.
Volunteers assured that the receivers’ specific area message encoding (SAME) and receive frequency settings were correct, so users would receive warnings that the NWS issues for their home counties.
WANE TV had promoted the three-hour event, which was duplicated at other locations in the TV station’s market area. The Office of Homeland Security estimates that 100 citizens were assisted.
As Joseph put it, the event “was an excellent example of cooperation between local weather personalities, NWS staff, DHS, and amateur radio operators to support our community. Good PR for amateur radio can go a long way in protecting ham radio bands from public utility spectrum grabs.”
Today is the fifth anniversary of a “derecho” thunderstorm that did widespread damage in northern Indiana and locations to the southeast.
“At the peak of the event,” writes the northern Indiana office of the National Weather Service, “the Fort Wayne International Airport observing equipment observed a peak wind gust of 91 mph.”
“Winds were as strong as an EF-1 tornado over a widespread area,” the NWS web page continues, “which resulted in immense damage along the storm’s entire path.” (Emphasis added by W9LW.)
One of the best lessons of that storm should be that we can have massive damage without a tornado. This was a particularly dangerous severe thunderstorm, but there’s no such thing as a “particularly dangerous situation” thunderstorm warning, so we need to pay attention to all severe thunderstorm warnings, even though such warnings are not uncommon.
College of DuPage meteorology professor Dr. Paul Sirvatka presents at the DuPage County Severe Weather Seminar, March 11, 2017
The title of this post is one of the main points of a presentation I heard at the DuPage County (Ill.) Severe Weather Seminar March 11. College of DuPage meteorology professor Paul Sirvatka reminded spotters that the key to spotting a tornado in a classic supercell is knowing where the updraft is. As Dr. Sirvatka put it, a tornado is a “big sucky thing” that forms under an updraft.
Unfortunately, updrafts are not always easy to find. Depending on your location, important storm features can be obscured, making spotting difficult. And the closer you get to a storm, the more difficult it becomes to identify the important features.
This is a “reprint” of an article I submitted to the March issue of Allen County HamNews, the monthly newsletter of all three Fort Wayne-based ham radio clubs.
An unusually large crowd of 135 people attended SKYWARN storm spotter training at the Public Safety Academy on the south side of Fort Wayne Feb. 21. That compares to 87 in 2016 and 91 in 2015.
This year’s presentation included video and images from the Aug. 24, 2016 tornado outbreak. Some interesting tidbits from the presentation included:
It’s hard to protect yourself and your family from tornados, damaging straight-line severe thunderstorm winds, or large hail, if you don’t know that the National Weather Service has issued a tornado or severe thunderstorm warning for your location.
So, here’s my list of the best ways to get tornado, severe thunderstorm and flash flood warnings.
For 11 years, Alabama broadcast meteorologist James Spann (ABC 33/40, Birmingham) and several of his friends in the weather enterprise have produced a weekly podcast (internet talk show) called WeatherBrains. It was the first in what has become a group of weather-related podcasts that are jointly celebrating the first-annual National Weather Podcast Month in March.
The weather brains normally record WeatherBrains on Monday evenings. Audience members can watch the discussion live on YouTube, watch it later on YouTube or download the program as an audio recording for listening at their convenience.
W9LW’s Ramblings had chance to talk to Spann about the show that started the weather podcast genre and now has an audience in the tens of thousands. Watch the 14-minute interview on YouTube or read it below. The transcript includes a few helpful notes and hyperlinks.
W9LW’s Ramblings: What prompted you to get into the podcast business?Continue reading →
The National Weather Service (NWS) plans to change its website, www.weather.gov on March 7. When the change takes place any bookmark you’ve created to a specific forecast will no longer work. You’ll have to go to the home page at the URL above, enter the location for which you want a forecast and create a new bookmark for the page that appears. For more information, see the message below that the NWS sent to all Weather-Ready Nation ambassadors.
Dear Weather-Ready Nation Ambassadors,
As part of our continued effort to modernize weather.gov, the National Weather Service (NWS) is upgrading our point forecast, zone forecast, and product pages. Once these changes go live on March 7, all existing bookmarks to forecast.weather.gov will change. Links to a forecast page will display an error message that includes a URL to the new location. You will need to update your bookmarks to continue to access our forecasts quickly after the upgrade. After March 7, the new URL can also be found by searching for your location from forecast.weather.gov or www.weather.gov. These changes will not impact office pages located at www.weather.gov
If you run an automated process to get NWS data from forecast.weather.gov, you will need to switch to the new developer API by March 7. Specifications for the new API can be found here.
The primary focus of the upgrade is to make the forecast pages more reliable during weather events, but there are some new benefits of new forecast pages that include:
Addition of 7-day hourly forecast information to the point forecast page
A new mobile-friendly landing and graphical/tabular forecast page
Low-bandwidth optimization for all pages, on a partial roll-out at launch
Option to automatically detect your location on a mobile device
A new widget mode that allows you to customize the information on the point forecast
We overhauled the architecture of our application platform to provide a more stable and consistent service to meet the demand of severe weather events. The platform also introduces a modernized API that will make it easier for web developers to create high-quality applications and services to share NWS data. The updated web site now provides a complete mobile-friendly experience with optimizations for low bandwidth and customized weather widgets. We also have new data centers located in College Park, MD, and Boulder, CO, to provide 100% backup capability for the operational data used within the forecast process.
We look forward to providing you with useful and timely information using our improved connectivity and new design.
The amateur radio SKYWARN net based in Fort Wayne will undergo slight changes, effective Feb 1, 2017. Formerly known as the IMO SKYWARN Quadrant Two Net, it will now be referred to as the Allen County SKYWARN Net. The net will continue, however, to accept and relay reports from spotters outside Allen County, including stations in places like DeKalb and Defiance County, which were not officially part of the former quadrant net’s responsibility. Continue reading →
Widely shared snowfall forecast map from the European numerical weather prediction model run on Dec. 16, 2013 for the forecast period Dec. 22-23. What actually happened Dec. 22 and 23 wasn’t even close to this!
Winter weather is just around the corner in Indiana, which means so are authentic-looking but bogus long-range snowstorm forecasts on social media.
It won’t be long before we see claims that a storm a week or more away will bring huge snow accumulations. Many will have official-looking forecast maps, like the one above (which turned out to be wrong, by the way).
But these posts won’t be the work of professional meteorologists. Many will be the creations of school kids, passing themselves off as weather experts.
This is Winter Weather Preparedness Week in Indiana, so it seems like a good time to prepare readers for the ominous-looking but unreliable snow forecasts they’ll soon see.
To understand what amateur weather enthusiasts put on social media, it helps to know something about the computer programs that professional meteorologists use to guide their forecasts. These programs are called numerical weather prediction models. They simulate Earth’s atmosphere by describing it in a complex series of very complicated mathematical formulas.
The programs built on these formulas run several times a day on supercomputers around the world. Much of the output of these programs is available on the Web, in both numeric and graphical form.
The output of computerized atmosphere models is inherently inaccurate for several reasons, including:
It’s not yet possible to completely describe our chaotic atmosphere in mathematical equations and
The programs don’t have access to enough data about what our atmosphere is doing at the time they run (e.g. what the temperature, wind speed and wind direction are 10,000 feet over any given part of the planet).
Nonetheless, these programs kick out predictions of what the weather might be at any location at any time, as far in the future as 16 days, despite that fact that no computer or human can reliably forecast the weather that far in advance.
Now, imagine a young weather enthusiast who craves attention and loves snowstorms (because they get him out of school). When he sees an indication of heavy accumulations in the output of a single computer model, he might paste that model’s map into a Facebook post in which he writes a dire forecast of impending doom. Such an amateur forecaster might not be aware of (or care about) the model limitations described above. But she’ll love all the “likes” and shares her post receives!
So how do I know what to believe? First, I’m automatically suspicious of any social media post that forecasts specific snowfall amounts more than a couple days in advance. Second, I ignore any forecast that doesn’t come directly from professional sources I trust, such as:
