Why You Don’t Need Regular, Granular Forecast Updates

I woke up this morning to find the weather chatter centering on rain to snow from Monday night and Tuesday. Depending on what computer forecast model you believe, there’s also the potential for snow later this week, this weekend, and the start of the following week. How much snow and when? What will the impacts be on all of these rounds of precipitation? What about that shot of very cold air coming later this week? Then, as a I reached for my first sip of coffee, I saw this:

This tweet invites several questions about you, but mainly: how often do you – the customer – need forecast updates, on what, and why? This tweet also invites a lot of questions about me, meteorologists, and other forecasters, but mainly: after a review of the data, what do I need to share about the forecast while also being responsible, and what do my customers want?

As a meteorologist, I can confirm there is a lot of computer guidance out there. There are American models, European models, Canadian models, short-range models, long-range models, and even models that attempt to predict what the radar will look like in 15-minute increments. You could spend all day looking at guidance, but the benefit in reviewing all of this information is a forecast, or the best theory on what will actually happen.

The cold, hard reality is that customers don’t need to review all of this guidance. That is the job of a meteorologist. But not all meteorologists feel that way; some have become “model regurgitators.” They will give you a forecast, sure; they will also tell you what every single model run says along the way.

Let me give you an example of how this process plays out using one computer model runs over time. Here are recent 24-hour “snowfall” projections ending at 7am Friday from the GFS model:


Each snapshot here shows a “projection” (I put that in quotes because nearly all computer forecast models don’t directly forecast snow, so this is reality raw computer data with human logic that may or may not be correct layered on top of the data to get to a snow amount) from the GFS model. Each of these runs has different inputs of different quality. So which one of these models is right? If you watch the animation for long enough, you’ll see snowy runs and snow-less runs…and eventually you’ll realize that this model is not very consistent. This happens more often than you think.

Let’s go back to that potential for snow Monday night, and let’s see what type of precipitation the GFS “thinks” will be occurring (again, I’m using quotes here because the GFS doesn’t directly forecast what type of precipitation will occur at a given time. A human logic layer is applied here). Here’s the GFS computer projection for 10pm Monday night:


What type of precipitation will be occurring in Cincinnati at this time? Blue is snow, and green is rain. Well…this is complex. More recent runs are faster with line of precipitation and quicker to change over to snow, but we can’t ignore the fact that some recent GFS model runs suggest rain is more likely. We could broad-brush this and say “rain and snow to snow Monday night” (and there’s nothing wrong with that), but time matters when we’re talking snow. A rate multiplied by time will get you to a snow total. I just posted output from one model here, but the job of a meteorologist is to evaluate all model data, outcomes, and trends then make a forecast on what will happen. This means there is little to no value in posting model data for customers to review unless the meteorologist believes that model data is correct. This also means sharing what each model run “says” as it comes in is pointless.

So why is this happening? I have some theories:

  1. Some meteorologists and forecasters want attention, likes, and shares, and they will share model output to get that attention. The concept of “involving the customer in the process” or “bring them along for the ride” is merely a grab for attention. This can easily be countered by saying “I’m informing my customers,” but you can inform them with a forecast, not an attention-grabbing, knee-jerk, likely conflicting series of updates.
  2. It’s easy or at least becoming easier for meteorologists to share attention-getting weather headlines. Computer graphic machines can print out a snow amount for a city from a given model run to the tenth of an inch out to 5-7 days. Find a model run that generates extreme temperatures, severe weather, or big snow…and you’ve got a social media hit and a watercooler conversation.
  3. Meteorologists and forecasters (including non-meteorologists who have access to raw model data and maps) who gather significant attention for their extreme scenario posts often – over time – get an increasing market share, often drowning out those who are advertising more reasonable, modest, or less extreme scenarios. This often fuels misinformation about weather systems and the misconception that “meteorologists are always wrong.” Just because one forecaster cries wolf doesn’t mean they all do.
  4. Many forecasters lack the experience or education to evaluate model data and forecast the weather. Anyone can make a forecast or post maps, but making an accurate, detailed forecast requires skill. Unfortunately, extreme scenarios – or at least the risk of an extreme scenario occurring – will often win out over the voice of reason. In other words, the source of the forecast (or even raw computer output) doesn’t matter.
  5. Forecasts – partly as a function of inexperience in those who forecast or share computer guidance – are becoming increasingly wishy-washy. There’s a “chance” of extreme weather this week. Snow of 0-10″ is “possible” later this week. A temperature of -5° is scary, but a wind chill of -25° is even scarier. That wind chill could become -30° tonight…check back for updates! It is possible it could get worse! And that potential keeps many hanging on.
  6. The potential for significant weather often surfaces 5-10 days out. That means you’ll be strung along with “updates” for 5-10 days on one or more significant weather events. The scenarios could range from good to bad to worse, and you’ll likely see the scenarios change every 12 hours. There’s a lot of whiplash in the model world, so why are you being taken along for the ride? More importantly, why do you want to be along for the ride?

I’ve had a long standing concern in meteorology: the specifics of the forecast usually don’t matter. Here are some 7 day forecasts from Los Angeles TV stations:


So…a high of 76° and 78° today, and a high of 73° or 74° tomorrow. What’s the real difference here? Does it matter where you get your forecast from the next five days here? It doesn’t. It makes absolute sense that you get it the forecast from the easiest accessible place because there’s no significant difference between these forecasts. Additionally, there’s no need to check back for updates because if tomorrow’s high goes to 75°, who cares?

If there’s no risk for inconveniencing or hazardous weather in the next 24 hours, it doesn’t really matter where you get a forecast from. There are few weather scenarios (i.e. a blizzard, tornado outbreak) where you need to know what the forecast looks like beyond 24 hours. If you check your phone at noon to see what temperatures look like this afternoon and evening and you don’t see anything inconveniencing, that’s about all you need to do weather-wise for the rest of the day. If the forecast temperature for 8pm changes from 45° to 43°, was getting that update worth your time?

The best comparison I can make to this logic is like that of a sandwich shop. Let’s say you’re meeting a coworker for lunch 5 days from now. In reality, you just want a sandwich to be made when you get there. I believe it’s highly likely that you just want a sandwich to be there when you’re ready to eat 5 days from now; you’re not concerned with supply chain logistics, whether there will be a manager present at the store, whether the heater in the building will be working, and whether their shipment of meat and veggies will arrive at 4pm or 5pm on Thursday. I suspect you won’t be calling the sandwich shop every day until you meet your friend for lunch just to make sure everything is on track to get your sandwich. If the sandwich shop had a social media account, I don’t think you’d fine them posting about when their shipment of meat arrived at the dock, when their employees clocked in, and what temperature the thermostat is set at; even if they posted about this, you likely wouldn’t care.

Just like the sandwich, you just want a forecast. You go to a source of information that suggests what is going to happen. I suspect you aren’t going to a webpage and comparing what 5 different computer models say about the timing of precipitation and what the temperature will be for each hour in the next 5 days. I suspect you don’t care what the NAM model trend for the last 5 days has been, or what the median accumulation amount is from the latest SREF model. You just want the sandwich.

When you go to the doctor, you just want to hear his or her diagnosis. When you go to a mechanic, you just want to hear what the recommended repairs are and the associated costs. When your manager at work asks you to turn in a report, you don’t staple a separate sheet with your mathematical calculations to the report.

So why do it with weather? If it’s not a inconveniencing in the next 24 hours, go out and live your life. Forecast accuracy increases dramatically within 24 hours of active weather, so you might as well save your interest for that window and not go “along for the ride” on a computer model wild goose chase for days.

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The Things They Never Told Me: An Open Letter To Penn State And Campus Weather Service Students

To The Students Of Penn State University And The Campus Weather Service:

Odds are good you have no idea who I am, but I was once like you. I graduated from Penn State 11 years ago with a Bachelor of Science in Meteorology from Penn State. I was a member of the Campus Weather Service. I was both on camera and worked behind the scenes at Weather World. I learned a lot at Penn State just like you, and I really enjoyed my last two years there.


I worked in broadcast meteorology for 10 and 1/2 years. I worked in three different cities, and I’ve worked just about every shift there is. I interned every summer during college (once for the National Weather Service and twice at two different Cincinnati TV stations). Additionally, I had a path to a career with the National Weather Service, but the opportunity just wasn’t right for me. I’ve recently earned an MBA (Masters in Business Administration) from Xavier University and work into the business world now as an analyst.

I tell you these things not to brag or boast but to tell you some things I wish I would have known 10 years ago about meteorology and give you a frame of reference. No one sat me down and told me how the meteorology industry works or the good and bad within it. When you’re focused on differential equations, atmospheric dynamics, finding a job, and having a social life…it’s easy to not have a focus on your career or what the next 10 years look like. I’m here to offer some advice with that.

I’ve come up with 15 things you need to know about the future, and they are all important. What I say may not carry a lot of weight with you because you’ve never heard it or experienced it before; take a leap of faith that what I say is more right than it is wrong. Let’s talk.

  1. Your #1 goal in your life and career is to be happy and successful. Happy and successful. Happy and successful. Happy AND successful. It’s so important that it requires repeating. You should always be or be working to be happy and successful. If the job offer you got doesn’t make you happy and successful, don’t accept it. If your first job doesn’t make you happy and successful, move on as soon as possible. If any aspect of your life doesn’t make you happy and successful, it’s time to move on.
  2. Study who is advancing and succeeding in meteorology and figure out why that is. When I graduated from Penn State, the boss of my first job said he hired me because I was a Penn State graduate, and he thought it was a good school for meteorology. What got me my second job? Being a Boy Scouts of America Eagle Scout helped me stand out. What got me my third job? The fact that I interned with my supervisor, and he liked the quality of my presentations and interest in data. Fast forward a couple of years into my third job, and I found myself wanting to advance. I saw people in my industry with half of my experience getting higher-exposure, more senior, and better paying jobs…and I wasn’t moving. I thought that my experience and education would be helpful to advancing.

    Until I started an MBA, I didn’t really get business. When you graduate from Penn State with a meteorology degree, you don’t know much if anything about business, and this is unfortunate. Thankfully, I can give you some insight. Successful companies create value for their customers. They do so by having a competitive advantage, and hopefully it’s a sustainable competitive advantage (one that other companies can’t replicate). Companies also care about profit, which is revenue (income) minus costs. How do companies make more profit? They either increase their revenue or decrease their costs. This helps retain their shareholders, stakeholders, and investors (people that own stock or a share of the company and expect a return on their investment).

    So let’s jump back to meteorology and the companies that depend on meteorologists. Take your pick on which vertical you want. Government, public, or private sector? It doesn’t matter. Now assume you’re the boss at one of these companies. Your investors want you to make more profit every year. You can only increase your revenue so much; your budget is only so big. You can cut costs, and you may even be incentivized by your company to cut costs. How can I cut costs? Salaries take up a big part of the budget, so maybe you look there. Experienced employees cost more, and less experienced employees cost less. Is it worth getting people with less experience? Some bosses will say yes, and others will say no. What kinds of people are willing to work for less? Really think about this question, then go back to the original question: why are the people who are advancing actually advancing? What about them gives them a leg up? Then look at yourself against this crowd. Can you have their same success? Can you get the education or knowledge they have…or is it something you can’t change? I remember getting advanced to a second round of a National Weather Service job years ago. I called the meteorologist-in-charge of the office, and he told me I wasn’t likely to get the job because he had two military veterans in the list of candidates. Could I realistically be a military veteran? I couldn’t…at least not easily. Perhaps there were other candidates who – after interviews – were willing to take a lower salary, and I wouldn’t have gotten the job (all veteran qualifications aside). The moral of the story here is that some people advance and get jobs for the right reasons, and some people get jobs for the wrong reasons. Sometimes you won’t get the job even if you’re the most qualified candidate.

  3. METEO 473 is the most important class you’ll take at Penn State. Remember that course you took on processing weather data and transforming it into an analysis? That’s the most important class you take at Penn State. Pick any large company that doesn’t employ meteorologists. If you’re struggling, think of Google, Macy’s, Apple, or Microsoft. These companies spend MILLIONS if not BILLIONS of dollars each year in research and development on products and services. You know what they use to make decisions? Data. Now go back to meteorology and rope in the comments I made about sustainable competitive advantage above. What are YOU going to do to stand out? Present the temperature map with a brighter and bubblier personally than anyone else? Please. Present the same information that everyone else has access to from a vendor? Please. You’re going to stand out because of what you can do with data. You could present the mold and pollen count, but can you automate a process to ingest that data into a computer so you can save time and avoid the potential for typos? Can you predict what tomorrow’s pollen and mold count will be. You can do a statistical analysis on it. Use a linear regression, and you’ll be surprised how easy it is. To stand out, you have to know where to find data that few can find, know how to process it and automate processes, and predict what others can’t. If you don’t know how to get the data you want, figure it out, and don’t give up!
  4. Stop looking like everybody else and be different. One of the worst parts about meteorology today is that everybody looks the same. Here’s your forecast, right?
    I would guess the phrases “good morning”, “those/these temperatures”, “just a few showers”, “weekend is always in view”, and other cliche phrases are peppered throughout the presentation. BORING. When you’re learning to present the weather, you shouldn’t be emulating other meteorologists and just learning to do what they do. You should be learning to talk about the weather in your own words with confidence. What are YOU going to present that isn’t just the same thing as everyone else in town? What’s your trademark? As I stated above, data and analysis is your best and easiest way to stand out.
  5. Minimize your “greenness”. I get it. You’re in college and soon to be entering the workforce. You’re excited. You want to leave out the dream of being a meteorologist. You’ve followed the weather since you were a kid. You’re wanting to hit the ground running, and you’ve got ideas. But don’t be a sucker. Of course your boss wants you to work all of the time and give 150%, especially if it’s not costing your boss a dime. As you get older and especially as you have more commitments (a significant other, a family, a child, etc.), you’ll see the importance of a work-life balance. You don’t want to spend your life at work. Talk to your parents or older mentors about limiting their time at work before you start working. Meteorology is already a industry that essentially requires you to look at the weather when you’re not working. 40 hours a week of meteorology is plenty, especially if part of it is spent in the cold, heat, or elements.
  6. When you graduate, you don’t have to go into meteorology. No one actually tells you this, but you don’t have to take a job in meteorology. You can do whatever you want for a career. A meteorology degree gives you many important life and career skills, including – but not limited to – critical thinking, problem solving, ability to use technology, and programming. Those are the skills you need to get just about any good job. You can market those skills and get into a lot of industries.
  7. The hours of meteorology suck and will have an impact on your life. You may have heard people complain about how “boring” 9am to 5pm Monday through Friday jobs are; I suspect those people have never worked the shifts that a meteorologist does. National Weather Service meteorologists that aren’t in management work different shifts; in other words, you may work overnights one day, evenings for another shift, midday for another shift, and then mornings through early afternoons for another shift. If you work in television and do weekday mornings, you’re likely up at 1-2am five days a week. If you’re working evenings in television, you’re in at 2pm and out just before midnight. If you’re working weekends in TV, your schedule is all over the place; in fact, many weekend meteorologists in TV work all of the morning and evening shifts. As a college student, it is highly likely that you have never had a job that required you to work crazy hours, so you don’t know the impacts it will have. The idea of working the weekday morning shift looks easy, but it will wear on you. Doing double shifts or early morning shifts isn’t too taxing on your body if you only do it a couple of days or even a week. After about two weeks, you’ll be tired. After a month, you’ll be exhausted. After 5 years of doing it (like I did), you’ll likely have health effects. You can cope with coffee and naps, but these are coping mechanisms. Coffee plus an unsettled mind due to getting up in the middle of the night don’t mix well. Your lack of sleep day after day becomes a compound issue; being tired one day makes you more tired the next, and after months and years of doing this, your mental and physical health easily slide. Now layer on the other pieces of life. You’re taking your personal time to nap. You’re tired, so will you make it to the gym? Now say you’re married with kids; you’re going to tell your your significant other and kids you have to go to bed at 5pm or work holidays and weekends? They won’t fully understand your shift or what it’s doing to you, and yet you’re still expected to be there and alert for your family.
  8. Advancing in meteorology often requires moving. This may not be a problem for you, but suppose you take a job then can’t advance. You may have signed a contract with a no-compete clause, so you can’t just work across the street. That means you’ll have to move. Then say you want to work a better schedule in a couple of years. Can you just advance to the new schedule you want because you are the best forecaster statistically? It doesn’t work like that. You’ll have to move. Then suppose your new employer is grooming you for a better job, but then you realize it requires going to a new town. At some point, you’re going to have to ask yourself: is it worth all of this moving? Moving often means finding new friends and moving your family along with you.
  9. Meteorology is a better hobby than it is a career. Meteorology is a public facing job. You get to tell everyone the weather. That means everyone, including the worst of the worst and the best of the best. When you forecast 2-4″ of snow, there will be trolls ready to say they got 4.1″ and “it must be nice to be wrong 70% of the time and keep your job.” Also, forecasting the weather is like drinking from a fire hose. There’s an endless supply of models to review, and you have to make decisions that impact people’s lives. It’s a lot to take on, and there will always be grief. Some people are mean; if you’re in the public eye, some will make fun of your looks, some will insult your knowledge, and some will even attack your race, weight, or gender. You can look at models all you want working out of the weather industry and without the attacks. Plus, how long do you want to spend your mornings, nights, weekends, and holidays away from your family? How long do you want to work in the cold, snow, heat, and other weather elements? Regardless of where you work, you have to think about how your job will impact the quality of your life.
  10. Be careful from whom you take advice. If your mentor is young and inexperienced, they likely haven’t been in meteorology long. You want to talk to mentors to have been in their business for many, many years. They have seen a few things. They’ve worked the shifts, they’ve seen people fired on the spot, and they’ve seen the industry trends play out. People that have been in the business a long time get “the long game.” Also, be careful getting your advice from senior or chief meteorologists that have been in their position for a long time. A chief meteorologist that has been in his or her spot for a long time likely hasn’t worked the more physically demanding early morning or “doubles on the weekend” shifts…or at least remember working them…or did the shift before the layers of mutli-platform demands.
  11. You’ll probably have to get a masters degree down the road. This is not what you want to hear with building student debt, but you’ll probably have to get another degree in the future. I don’t know of a company with meteorologists that will pay for you to get a masters degree, so you’ll likely have to pay for this degree out of pocket. Why do I say you’ll need a masters degree? Because if you want pivot to another career, you’ll likely need to prove to your future employer that you’re qualified and “not a meteorologist.” The National Weather Service also wants the best candidates, and your education matters and increases your odds of getting hired. Budget accordingly, and pace yourself.
  12. Research your employers extensively. Before you sign on the dotted line for a job, you should research your employer. What kind of company are they? What’s the culture there?  What are employees saying about the company? Have they recently gotten in trouble or hot water? Are they ethical? Are they fair? Do they treat their employees well? Do your research so you work for the right employer. Know that your employer may also be acquired or merge with another company. As news of that breaks, research the acquiring company. If they aren’t a good fit, it’s time to move on.
  13. Your looks may matter. It’s not right, it’s not okay, but it’s reality. If you’re in a public-facing role, your “beauty” comes into play. I’m not here to judge you, but some will. You’re far more likely to be judged based on your looks than forecast accuracy.
  14. Your opportunity cost may be better outside of meteorology. Opportunity cost is the loss of potential gain from other alternatives when one alternative is chosen. Suppose you go into meteorology. What’s the average salary of a meteorologist in their first job? I remember getting an offer to work as a broadcast meteorologist in the Midwest for $18,500 a year. As a college student, that may seem like a lot, but that’s not a lot of money. The poverty line for a single person is $12,140. I didn’t take that offer, but know that it takes a while to make a great salary in meteorology.Now consider a career in business or another field. What’s the average salary for a business person in their first job? It’s likely higher than a career in meteorology. Either way, you have to research. It’s not all about money either; which path gives you want you want in life faster?
  15. Your dream changes, not ends. Being a meteorologist is a dream, but the odds that you change careers in your life is high. You need to be prepared for change. People lose their jobs or get fired. What are you going to do if that happens? You likely have rent and loans to pay. How are you going to pay your debts? You’ll want job security once you have a job, especially if you have a family. Do you get your forecast on your smartphone or TV? If not, how many of your friends do? This should tell you about trends in meteorology, where people are getting their forecast, and how much people care about the quality of forecasts. Don’t ride out the storm until it ends; make moves before the storm hits.

I hope you find what I say relevant and beyond what others have told you. I encourage you to think a lot about your career choices, who you want to work for, who you don’t want to work for, and what will – above all else – make you happy and successful.


Scott Dimmich

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Meteorologists Need To Be Data Scientists And Programmers. Their Future Depends On It.

Data is really, really important to any business that matters. Data is being used to not just get a heartbeat on what customers are buying and using; it’s being used to drive decisions within the business. As I highlighted yesterday, companies are spending large amount of money (and their profits!) to better understand their customers’ behavior and purchasing profile.

Alternatively, meteorology requires quality data. Looking at surface, radar, satellite, and upper-level trends is a very valuable part of creating a forecast, but it will only take you so far…perhaps 12 hours into the future in some but not all situations. Computer guidance is needed to make forecasts that are longer-term. Knowing where severe storms will develop, where that hurricane will go, and how much snow will accumulate requires data and an understanding of it.

Meteorology isn’t a rewarding science unless the results are shared with many; there is little value in knowing where a storm will go and what impact it will have if only you know what the forecast is. If emergency managers, state officials, and the public know where the tornado is moving and what impacts a city will get from a tropical system, the information is far more valuable and can be used to make and inform other decisions.

Unfortunately, meteorologists can’t just download their analysis and knowledge into other people’s heads. The world would be a much smarter, better place (I hope) if we could freely exchange information and insight by installing it directly in a brain…but that isn’t the case. This requires a meteorologist to communicate their insights, conclusions, recommendations, and the data that supports all of these decisions. The conclusions, recommendations, and insights are valuable, but people and decision makers want to see the data for themselves to make sense of it.

The best meteorologists I know use quality data to tell a quality story. With so many options to get a forecast, it’s important to stand out; this unique story requires unique data. So why do so many meteorologists struggle with getting this unique data?

I want to emphasize the word “unique” here. Radar data is everywhere. Satellite data is everywhere. Model data is everywhere. Forecasts are everywhere. I’ve seen the National Hurricane Center’s track of the hurricane, and odds are good most have, too. Basically, if all or most of the weather communicators have access to or use the information, it’s not unique and people have no reason or incentive to choose one source over another.

So let’s go back to the question: why do meteorologists struggle with getting unique data? As someone that knows a fair amount about statistics, data, computers, and weather…programming is difficult. To be a successful programmer, you – among other things – must know:

  1. Where to get the data
  2. How to scrape or gather the data
  3. Format and quality control the data
  4. Know the tools to process and analyze the data
  5. Output the data or insights into a specific format

This process is not easy. There’s a lot weather data out there, and there are many meteorology-specific and non-meteorology-specific tools out there. These tools have a learning curve, and these tools take time to learn.

Secondly, finding the source of the data takes skill, time, and patience.

Let’s look at this problem. What does weather impact? How about rivers? Here’s a recent forecast for the Cape Fear River near Wilmington, South Carolina:


This is a helpful plot of information. It shows past, current, and forecast observations with tide information embedded. As I write this blog, Hurricane Florence is nearing the Carolinas, so flooding and river flooding information is even more valuable. So if I’m in the weather communication world, how do I share this information with my customers? I could screengrab it and share it out, but my bosses may not be happy with NOAA’s brand all over that data.

On the page where I pulled this data, there is an XML and RSS link to the underlying data in the plot above. Within the XML and RSS link, there are observed and forecast data points and corresponding times. We can download this raw data, process it, and export it to a weather communication computer system. So how do we get the data from where is it to where we want it? The answer is: figure it out! Don’t get defeated, don’t get overwhelmed, don’t get angry; instead, research:

  1. What programming languages read and process XML and RSS data
  2. How to use those languages to write code and transform the input data into desired output data
  3. The ways to automate the process.

Next, you have to take the output and use it as an input for your weather communication computer system. That’s where your knowledge of the latter gets used to finish the project and tell a unique weather story.

What else is impacted by weather? Power outages, air quality, river levels, road conditions, and more. Those who source the data (power companies, air quality agencies, etc.) typically publish their data in some form to the Internet. So how do you get that data from their final source to your final source? The answer is: figure it out! You can do this, but you have to have the passion, energy, and time to make it happen. It’s important to note that extra time to make a unique product today may save you a lot of time in the future.

Before you think that you can’t get information from that weather-related data website, you can. If you can get it in a browser, you can get the data. You just have to try harder to get it and transform it.

The ultimate goal here, as I alluded to in my blog post from yesterday, is to create a sustainable competitive advantage and cross-promote your product. If you own product A and B, you tell people on Product A to get a unique forecast on Product B, and you tell people on Product B to get a unique forecast on Product A, you’re likely to keep your company happy while also giving your company value.

Need an example of this in action? Try this:

This WTOL-TV’s real-time school delay and closing map. That’s data from an external source (a school closing/delay crawl system or the backend where schools districts report their delays) being inputted into a broadcast machine and colorized/formatted in the machine’s software. There is no doubt in my mind there is (automated) programming here to both export and import the data from one system to the next and to convert the output of one source to an input for another system. This is impressive work, and this is the only place I know that can show this type of data to customers! This took programming, weather communication system, and local school district knowledge plus time, effort, and – perhaps most importantly – passion.

This tweet from Ryan Hoke at WAVE-TV in Louisville, Kentucky shows rainfall data from Louisville Metropolitan Sewer District rain gauges. The data is freely available here. You could import the data straight into Microsoft Excel (which is NOT a programming tool!) and export it out, but there is likely programming going on in the background here to parse the table of rainfall totals. How did Ryan made this map? He saw the challenge, and he figured it out! It’s not incredibly easy to pull this data; some websites have easy access to data, and this site is not one of them. But you can do it!

These are two (rare) examples of importing unique weather-related data into a weather communications system. The company brand is intact, and the freely (well, seemingly) available data is natively flowing into a system where data is shared. This process took a lot of time, effort, passion, patience, and perseverance…but these data can now be promoted, cross-promoted among platforms, and used in real-time to inform the masses.

But wait; there’s more. You can archive this data and leverage of the power of statistics to model out river levels, air quality numbers, and power outages. I know it can be done because I’ve done it.

As I write this blog post, Hurricane Florence is moving west towards North and South Carolina, prompting people to fill up and move inland. Here’s an impactful tweet:

If you dig hard enough on the Internet, you can find the raw data for this map and bring it into a weather communications system. What a great weather story element!

You have to work hard if you want to tell a better story than everyone else. If customers see value in your product, they will come to you to get that value. But there’s a downside: if you look like everyone else, have the same data as everyone else, and tell the same story as everyone else…you’ll have the same market share as everyone else and be as valuable as everyone else.

The ability to program and use data to drive business decisions and profitability is becoming more important every day. If you can’t leverage weather data to your advantage, your potential as a meteorologist is severely capped.

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Weather Communications Has A Problem And Business Thinking Can Fix It

As a meteorologist, a weather communicator, and someone to aims to be humble, I’ve come to accept and respect that the weather community has a critical issue that needs to be addressed. As a businessperson, I see business problems being solved daily, but I also see a solution to the mounting weather communications problem.

This problem is better shown than explained. It’s worth noting that there is a lot of great weather communication out there, and I’m not going to target specific people or companies as much as the product itself. To show this example, I will use New York City, a place I have never worked and with weather communications companies for which I have never worked.

As I write this, Hurricane Florence is a major hurricane in the Atlantic Ocean. Here’s what the New York City NBC affiliate has to say recently:

When I read this, I think to myself:

“What is the ‘breakdown’ coming up? You just gave me the whole forecast. Why do I need a breakdown?”
“What’s on the app that I can’t get here? You just gave me the current conditions of the storm and earlier you tweaked out the track.”
“What are the latest updates? When are these updates coming? Didn’t you just tell me 95% of what I need to know about the approaching hurricane?”

Here’s some of what CBS in New York has to say:

The screaming message here is it will be a cloudy, wet, breezy day in New York. But I’m left with the following questions:

“I could get this on my smart phone now. Why do I need to see your communication that takes up more than a minute of my time?”
“You just told me what was going to happen today. Why do you need to tell me again?”
“There’s a lot of information about others, but I just want the information about me.”

Here’s some of what ABC in New York has to say:

Again, I’ve grabbed some tweets that showcase local warnings, a snapshot of current conditions, and a link to a website where Florence is likely heading…but I’m left with the following questions:

“When is the greatest risk here and south of here from Hurricane Florence?”
“How is Florence going to impact me?”
“You showed me it’s raining now. When is it going to stop?”
“I see the radar and the warning. Where can I go for more information?”

There are other weather communicators out there talking about New York, and here are some of those tweets:

This is just a sampling of tweets (from Twitter). People can follow and trust who they wish, people can get weather from other social media sources, they can get weather information from non-social media sources, or they can – to be honest – live their live without getting informed on the weather at all.

As someone who used to work as a meteorologist (and still is one per my degree) but now works in business, I see the communications problem more clearly now.

Among other things, successful businesses have:
– A product or service people want to buy or use
– New products and services over time to create growth
– Profitability, especially if it’s increasing
– Good leaders, ethics, goals, and boundaries
– Create unique value, especially compared to others
– Have competitive advantages, especially sustainable competitive advantages

I would argue that the last three are perhaps the most important in business. What good is a company without leadership, growth, a bright future, and a moral compass? What good is a business without giving something valuable to customers? And what good is a company that has a product or service that others can easily replicate and scale?

Corporations in this country spend BILLIONS of dollars each year to gather insights about their customers that create value and generate sustainable competitive advantages. I work at one of those companies; every day, I look to create a unique product or service – either externally or internally – that gives the company for which I work value and advantage.

I think Kroger (the grocer) is one of the smartest companies out there. They bring groceries you buy to the store, sure…but that’s not half of the value. They were among the first to give you an incentive to have a shopper’s card; they got your information and purchasing profile, and you get discounts and free items. They give you an incentive to download and use their app; they get your information and additional purchase profile data, and you get access to coupons that you don’t have to carry around the store. Kroger also sends you coupons in the mail to incentivize you to go to the store. They have ClickList that, for a fee, has someone shop for you…and you just pick up the groceries outside of the store; the value proposition here is to save time. Then there’s fuel points: you earn them when you spend money at the store. When you’ve collected enough points, you get a discount on fuel at one of their gas stations. Plus, you get extra fuel points when you buy certain items – like gift cards – in the store. They have a large selection of “store brands” in their stores to save you more over name brands.

Kroger isn’t the only one with good ideas, but they have a value stream. They know how to get you in the store, to the gas pump, using their app, and using their services. They make money not because they create value for you, but also because they have many ways to get your money and connect the value from one place they own to another.

Amazon Prime is similar. You pay for Prime and get free shipping, but they also give you free streaming services, too. Other business have big time value, but the goal here – if you’re a business – is to make money ethically and fairly in as many places as possible and have a value stream that others can’t (easily) replicate.

I tell you all of this to highlight the weather communication problem: there is very little sustainable competitive advantage in weather communication right now. ABC, NBC, and CBS in New York (above) didn’t just give the same or similar forecast; they also:

– Have the same look and color scheme
– Have no information I can’t get on a free/ad-free smartphone app, from Alexa, or on the Internet
– Largely lack a link to easily get additional valuable information
– Largely lack a call to action or impact
– Don’t cross-promote
– Don’t incentivize

The other weather tweets :

– Largely lack a link to easily get additional valuable information (or don’t motivate)
– Largely lack a call to action or impact
– Take a significant amount of time to read or process
– Lack the locality of weather
– Don’t incentivize
– Don’t cross-promote

Marketing a weather forecast has accurate or the most accurate will only take you so far when convenience and value are in play. When all horses in the race run the same, the results will be the same. All of the above groups lack differentiation or sustainable competitive advantages.

New York isn’t the only place where this is an issue, and Twitter isn’t the only place where the problem occurs. So how do we beat the lack of differentiation, sustainable competitive advantages, and incentivization? With differentiation, sustainable competitive advantages, and incentivization, of course!

Weather communicators need to create forecasts, products, and services that no one else can easily create and can cross-promote. The “face” or “person” of reliability and accuracy is dying at the successes of convenience, the discovery of a more “reliable” source (perceived or real), and the fact that seemingly “all forecasts look the same, so any weather update is fine for me.”

Whether it’s power outages, river impacts, business closings, school closings, or some other proprietary forecasts/information and a way to communicate that forecast and drive people to that forecast and drive people to other forecasts on other places within the same brand, what unique value is the weather communication community giving customers?

Meteorologists and weather forecasters need to start thinking like a businessperson. If billion dollar companies are investing billions in creating value and finding a sustainable competitive advantage…why isn’t the weather community working to figure out what their customers want and create the intellectual property to give customers something they can’t get anywhere else?

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An Open Letter To Miami University & Its President: Please Share Your Airport Weather Station Data

To Miami University and President Crawford:

I have great respect for Miami University. I applied to your MBA program in late 2015 because I have great respect for your business program. My mother is a three time graduate of your school – a bachelors and two masters degrees in education – so I was raised to respect Miami University. I have been to your campus, and it is beautiful. I was there a couple of years ago to visiting your geothermal plant; as a meteorologist and someone who cares for the environment, it is wonderful to see a university not only take steps to become more sustainable and green but also improve their image through actions over words.

While I recognize your primary focus as a university – as your mission statement highlights – is to have an “unwavering commitment to liberal arts undergraduate education and the active engagement of its students in both curricular and co-curricular life,” your university is among a select few in our area to have an own and airport. It’s 3 miles west of campus and 2 miles west of downtown Oxford:


It’s a very convenient airport for those who want quick access to the university by airplane. With the drive being 56 minutes from CVG and 62 minutes from the Dayton International Airport, it’s ideally located between two major airports and two large cities.

I’m certain you know of this airport, but what you may not know is that there is a valuable piece of equipment sitting just north of your runway:


That fenced in area (with a path leading to it) contains an AWOS – or Automated Airport Weather Station. It’s actually one of the nicer ones out there. More formally known an AWOS III P/T, it can measure and report barometric pressure, altimeter settings for pilots, wind speeds and directions, the temperature, the dewpoint, visibility, sky conditions, cloud coverage, liquid precipitation amounts, precipitation types, and the direction of thunderstorms relative to the airport. This equipment creates valuable information for pilots but also to meteorologists.

This piece of equipment isn’t cheap. While the cost of these varies depending on what an airport wants, can afford, whether they can get nearby parts, and the year purchased, an article in The Leader-Herald in Gloversville, New York from 2017 claims a local airport manager purchased an AWOS for $240,000. I have heard costs for an AWOS closer to $70,000 or “above $100,000.” Regardless, the AWOS at your airport came at a significant cost to the university. Additionally, there are variable costs associated with keeping the AWOS up and running, including electricity to the system and replacement parts.

When I returned home and first started working in the Tri-State as a meteorologist in 2011, I began researching and understanding the processes that allow weather data to flow into various systems, including to the National Weather Service. In the years that followed, I worked with local airport managers to see if funding could be secured to share their weather station data out with the world by using a vendor. I am thankful that the Warren County, Ohio Airport; the Clermont County, Ohio Airport; the Fleming-Mason, Kentucky Airport; the Madison, Indiana Airport; the Fayette County, Ohio Airport; and the Batesville, Indiana Airport have all started sharing their airport weather station data with the Federal Aviation Administration (FAA) through a vendor. We have more local weather data than ever before.

But we don’t have the Miami University Airport’s weather station data. I believe it was 2013 when I first reached out to your airport manager about sharing your weather station data. He informed me at the time that he was interested in sharing the airport weather station data but also addressed cost concerns. I believe he spoke to his manager at the time, but the idea didn’t get much traction from the manager. After some time – perhaps a year – had passed, I called the airport manager again to express my continued interest in getting a feed of Miami University’s weather station data. His position had not changed, but I asked for his manager’s contact information this time. He obliged, and I reached out to his manager by phone. I never received a phone call from that manager, and I believe through an Internet search some months later that he had retired.

In the spring of 2017 and as I mentioned above, I came to your campus to see your geothermal plant and other nearby sustainability operations. I was impressed to see such forward thinking from a university. I also respected the business angle; being more sustainable benefits the bottom line.

While I was there, I connected with your marketing team and also your Director of Planning, Architecture & Engineering. I asked both parties about the possibility of sharing Miami University Airport’s weather station data out with the world. The marketing department responded to me in the days that followed with news that the university was not interested in sharing your airport weather station data. I followed up with the Director of Planning, Architecture, & Engineering in the days after I met him, and he responded saying that any additional operating expenses [at the airport, I assume] would make any additive costs prohibitive.

That takes us to today. I feel the need to clarify, publicly, the importance of your airport’s weather station data:

  1. Safety: Your weather station as measured severe wind gusts many times over the last few years. These measured gusts led to Severe Thunderstorm Warnings, which are issued to keep people safe and informed about dangerous storms. Many of those people placed in these warnings are your students and staff. Many of those people are also residents of Oxford. The National Weather Service has ways of accessing your weather station that the rest of the world does not; they have this ability in an effort to keep people safe, but know that because they do not have a stream of your data, they have to go looking for it. As a meteorologist, I want you to know that meteorologists depend on real-time weather station from local airports, especially during times of active and severe weather.
  2. Quality: Backyard, personal weather stations are not as reliable or accurate as airport weather stations. State-owned weather stations networks – like the Ohio Department of Transportation’s – are not as accurate as airport weather stations. I recognize that you can get real-time data from Oxford area personal weather stations or the ODOT weather station northwest of Oxford near the Ohio/Indiana border. While “close enough” may work for temperatures, visibility and wind measurements are not as reliable or accurate for non-airport weather stations. Airport weather stations also observe precipitation types and intensities; state and personal weather networks don’t measure that kind of weather data. Your airport weather station does. That’s why it’s important to share out your data.
  3. Marketing: Imagine media meteorologists sharing weather conditions from the Miami University Airport. Imagine pilots seeing weather conditions in the cockpit on their iPads and landing there because they know it is safe to land…and then they refuel and increase your revenues.
  4. Cost: There seems to be a misconception of the cost of sharing airport weather station data out to the world through a vendor. Yes, it true; you must use a vendor to share the AWOS data out through either an FAA-certified method or non-FAA-certified method. This process does not cost thousands of dollars. In fact, I’ve done the research on costs on sharing the airport weather station data through a vendor, and I want to share my research:
    • Stanwyck Avionics (non-FAA-certified method, but still flows to NOAA’s secondary data stream where the National Weather Service and media can use it): $1,500 one-time software charge/cost and an annual fee of $300.
    • RSINet (FAA-certified method): $60/month with a one year contract. No upfront costs through this vendor that I’m aware of.
    • AnyAWOS (FAA-certified method): $70/month. No upfront costs through this vendor that I’m aware of.

Based on the price of Jet A and 100LL fuel on the Miami University Airport website, you could fund sharing your airport weather station data each month by selling about 15 gallons of gas. A Cessna 172 – a very common general aviation aircraft – has a fuel capacity of 42 gallons.

I looked at Miami University’s 2016-2017 operating budget, and found $70 a month would take 0.4% of the airport’s annual budget. Unfortunately, the revenue and expenses for the “airport services” segment of the operating budget are equal:


The Director of Planning, Architecture & Engineering was correct in saying that additional costs would make this segment unprofitable. Of course, the nominal cost of sharing AWOS data out with the world through a vendor can be budgeted. I am quite surprised – as a business person – that the “airport services” segment is the only one in the “Auxiliary Enterprises” umbrella that doesn’t generate a profit.

The marketing budget for the Farmer School of Business alone in 2015-2016 was $3.78 million. With an annual budget in the hundreds of millions, can Miami University not afford $840 a year to spend on sharing airport weather station data out through a vendor? This small expense is an investment in weather safety and awareness while also increasing marketing for the university. Your asset that costs tens of thousands of dollars next to the runway holds valuable data that only a select few can see now. For a fraction of the cost of that asset, you can share that quality data that comes from that asset with students, staff, the community, the media, meteorologists, pilots, and everyone in the world…and they will know what the weather is like at Miami University.


Scott Dimmich


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A Meteorologist’s Guide To Get More And The Best Quality Weather Station Data

Data matters in meteorology. Some of the most underrated data in the country, in my opinion comes from personal weather stations, groups of weather stations called mesonets, and airport weather stations. While satellite, radar, and model data can highlight and suggest threat areas, weather stations can directly observe, quantify, verify, and sample conditions.  Surface observation data that is shared with NOAA (the National Oceanic and Atmospheric Administration) and the NWS (National Weather Service) is also used in computer forecast models and for verification of weather conditions – including rainfall totals and wind gusts in active or severe weather situations.

It can take years to get existing and new points of information on the map integrated into one place, but it can be done. Official weather records are great, but there is often an incredible amount of space between these sites, and daily, comprehensive weather records (including those with wind, snow depth, and snowfall totals) are almost entirely limited to airports in larger cities.

This blog post focuses on three things: 1) how the data flows, 2) how do get data into the data streams, and 3) how to fix errors in data points flowing into the data streams.

All of this information is publicly and freely available on the Internet. There is nothing propriety here, and I link to public sites throughout the article. The data streams themselves are public, and that’s the way they should be. The more weather data that is public, the more that is accessible to those who need it. My hope is that more data will be added to the streams over time so that the weather can be better understood and verified.

How The Data Flows

The ultimate goal is to get weather data to NOAA and NWS.

Before we start pushing data into the streams, we must first understand how the streams work. There’s are two main NOAA data streams: the ADDS and MADIS. It is important to know the difference:


ASOSes are controlled cooperatively in the U.S. by the NWS, FAA, and DOD, and the data from them flow to ADDS. AWOSes can be controlled by the FAA, local or state governments, or private groups. Data from an AWOS can go to ADDS or MADIS, and not all AWOS data goes to MADIS or ADDS. ASOSes are superior in some, but not all, ways to AWOSes. You can verify which ASOSes and AWOSes share their data with ADDS by putting in an airport code or ICAO here:


MADIS’ website shows the flow of data through MADIS looks like this:


This process is very similar to that of ADDS data except FAA certified data is the only input to ADDS. MADIS takes just about everything else that’s left (that doesn’t flow to ADDS). Here are some example inputs to MADIS:


While not “official,” MADIS is very important. As of the writing of this blog, there are 34,191 points of surface weather data flowing through MADIS from 74 different networks or mesonets. About 25.4% of those observations come from the Citizen Weather Observer Program (CWOP), where personal weather stations share their data to NOAA (more on this below).

NOAA’s MADIS map shows all of the publicly available MADIS sites and ADDS sites. MADIS sites are the ones that do not appear on the ADDS map. You can verify this by looking at the MADIS and ADDS maps. Not all data collected by MADIS is redistributed to the public; you can review what MADIS data goes where here.

Much of the discussion below focuses on CWOP, Roadway Weather Information Systems (RWIS), Weather Underground, AWOS, and WeatherLink IP data. These are all low-hanging fruits compared to growing the other weather networks.

How To Get Data Into The Streams – CWOP

First, let’s focus our efforts on CWOP and how it works. Some, but not all, personal weather stations – through either hardware, software, or both – will share data to CWOP.

The basic steps to get personal weather station to CWOP are:
1) Get a CWOP ID unless you’re an amateur radio operator
2) Configure the weather station software to share data with CWOP
3) Verify CWOP is getting the data
3) Register the station with NOAA by e-mail

Visually, this is the goal:


It’s important to note that just because data goes to CWOP doesn’t mean it goes to MADIS! The weather station owner must register their station with NOAA for the data to flow to MADIS. Please see the note on checking to see if their are unregistered sites for a given state in the “How To Fix Errors In Data Points Flowing Into The Data Streams” section below. 

Like I said above, not all weather stations can share data with CWOP. These can’t:

– AcuRite Pro Weather Center
– Neatmo
– Ambient Weather WS-1000
– Ambient Weather WS-1001

To repeat, if an owner of one of these weather stations wants to share data with CWOP, it can’t be done and you should give up trying immediately!

With this considered, let’s move to step two. How do you share data to CWOP? It’s easy if a weather station owner has a Davis WeatherLink, WeatherLink IP, or popular weather station software (MeteoHub, MeteoBridge, Virtual Weather Station, Cumulus, WeatherSnoop, or WxDisplay) because all of the directions, produced by the National Weather Service in El Paso are here:


There are the step-by-step directions for sharing the data with the world. Add it to your bookmarks if you need to! Click here for more information on sharing data from weather station software.

Once we’ve configured the software, we need to verify that CWOP is getting the data. CWOP should have an inventory of the data in no more than 30 minutes, but it may be there in as little as 5 minutes. Weather reports on CWOP’s page will surface here: http://www.findu.com/cgi-bin/wx.cgi?call=XXXXX, where XXXXX is the CWOP ID or amateur radio handle. Also, once the data starts showing up on this page, please check to make sure the weather station latitude and longitude are correct here: http://www.findu.com/cgi-bin/find.cgi?call=XXXXX, where XXXXX is the CWOP ID or amateur radio handle. A minus sign may be needed on the longitude to get you into the western hemisphere.

If the weather data makes meteorological sense and the location on the map is correct, we are in good shape. If these items are wrong. check the settings in the weather station software. See my note on the minus sign for the longitude above.

Important: we are not done yet! We still need to register the weather station with NOAA. When the settings are right, have the weather station owner send an e-mail to CWOP support (cwop-support@noaa.gov) requesting to register the  weather station with CWOP; in the e-mail,  include the CWOP ID, the closest town to the weather station (use a specific community), zip code, and the weather station’s elevation in meters (not feet). If the weather station owner gets an e-mail from NOAA CWOP support, verify the date that they will add you to the MADIS map…along with the CWOP ID. This is an important step because registering the station ensures the data will flow to the world through MADIS.

It’s important to note that the siting of the weather station matters! More on proper siting for this can be found here. You can share this PDF with weather station owners to help them correct weather station data biases.

How To Get Data Into The Streams – RWIS

Roadway Information Systems (RWIS) are weather networks owned and operated by state departments of transportation (especially in colder climates). Some networks are robust, and others are weaker. The data that comes from these networks are still very important!

Odds are good that the state is already sharing the data from all of their RWIS sites, but you should check because you might be surprised! MADIS don’t always configure their redistribution systems to share all RWIS data as new RWIS sites come online.

The goal here is to:
1) Find the state’s official RWIS website
2) Compare the sites on it to NOAA’s MADIS map and make sure none of the RWIS sites are missing

If all of the RWIS sites are there, you’re good to go. If not, e-mail madis-support@noaa.gov and bring it to their attention. They are there to help you and can work with a state’s RWIS contact about sharing data and troubleshoot errors.

If there are problems with the data coming from a specific RWIS site, that falls under the responsibility of the state department of transportation. Contact them directly to fix individual RWIS site issues.

How To Get Data Into The Streams – AWOS

Most AWOSes are located at airports, and some AWOSes don’t share their data with MADIS or ADDS. The first step here is to find the airports that have an AWOS that aren’t sharing their data with MADIS or ADDS. You do that by:

1) Using the FAA’s ASOS map to see where there are ASOSes and AWOSes
2) See if those same sites are on NOAA’s MADIS Map

Once we’ve found a site that is on the FAA’s ASOS map and not on the MADIS map, we need to get the airport identifier (ICAO) for the site. Next, we need to get in touch with the airport manager. Legally, the airport manager’s name, address, and contact number must be listed in FAA records. You can get this contact information by putting the airport ID or ICAO into this website:


It is now your goal to convince the airport manager to share their AWOS data – through a vendor – to either ADDS or MADIS. Googling “AWOS vendors” will give you a list of the vendors. Sharing data with MADIS is cheaper, and sharing data with ADDS is more expensive (because it’s FAA certified). If you’re a member of the media, saying you’ll share their airport AWOS data with the community on-air helps persuade them to pay a vendor to share their data. If you’re a pilot, saying you’ll use the data for safety will help. If you’re member of the community, you can say you just want to put the community on the map.

Precipitation type and intensity sensors are not required on FAA certified AWOSes (all ASOSes and nearly all AWOSes themselves are FAA certified, but the feed out of them does not have to be). Having this precipitation information in a weather report is helpful, but the sensors cost money. This can be a hard sell to an airport manager, but it can be done. Keep in touch with them, and be persistent, and you’ll eventually get the sensor.

How To Fix Errors In Data Points Flowing Into The Data Streams

– As I alluded to earlier, there are registered CWOP stations and unregistered CWOP stations. The data from the latter does not flow to MADIS. Think of the latter as a TV that doesn’t have the cable connected correctly into the back of it; you just want to complete the transmission.
– The easiest way to view registered and unregistered CWOP site is on the CWOP website and by state. You can find the page for a given state by clicking on the map under the “Data Time History Displays” here. Clicking on Texas, for example, will bring you to list of registered stations hereNotice the e-mail contact information for each weather station owner is listed on this page. Clicking on “WxGraph” for each site will allow you to see recent trends in weather data or show you that CWOP hasn’t received data from that site in a while; if there’s no recent data for a site, you can reach out to that weather station owner via e-mail to notify them they haven’t been sharing data in a while, ask them to check their weather station, or ask them to look at a sensor if their data is inaccurate. If you scroll down the page, you’ll see a link that says “UNREGISTERED XXX MEMBERS WITH UNVERIFIED STATIONS,” where XXX is the name of the state. An example for the unregistered Texas page is here. This is a list of people that registered for a CWOP IP but they didn’t register their station with NOAA. Just because they didn’t register their station with NOAA doesn’t mean they aren’t sharing their data with CWOP! Clicking on the “WxGraph” link for a site will show you recent data CWOP has received from that weather station owner. You might find a site that has site that you want to flow to MADIS; if you encounter this, e-mail the weather station owner and ask them to register their station with NOAA (see e-mail to cwop-support@noaa.gov directions above). Even if a unregistered weather station owner isn’t sharing data to CWOP, you know they are at least interested in sharing data with CWOP and probably own a weather station; you might as well get that data! E-mailing them and seeing what their situation is will helpful. You might find they just hadn’t gotten around to getting their weather station setup and may be excited you’re using their data (especially if you’re in the media or another public setting). The CWOP site gives you their first name, which is a good start for relationship building and networking.

Weather Underground
– Weather Underground (WU) data does not flow to MADIS. They are actually kind of jerks about it when you do some research.
– There is, however, a workaround for most but not all weather stations: contact the weather station owner and ask if they will share their data to MADIS and WU (actually, I prefer they do because WU has good weather archives). First, find a site on Weather Underground that you would like to see on MADIS. I’d suggest using the Wundermap. Here’s an example from Kaufman, Texas:


If I click on the Station ID link (the KTXKAUFM4 part), I’m taken to this website. If I click the “About this PWS” link here in the top of the page, I see this window pop-up:


The first thing to notice here is that it not on my list of forbidden, dead end weather station brands and types above, so there is hope we can get this weather station into MADIS. So how do we contact them? We could message them if we have a WU account, but this is a dead end. We want to convert their latitude and longitude to an address and mail them a letter. Go back to the Wundermap and zoom in down to street level on the weather station; also, turn the “Map Types” in the upper-right corner to “Hybrid”:


Once these settings are set, we see the map looks like this:


There’s a really good chance here that that homeowner owns that weather station. If this was a densely populated neighborhood, we might have to get in closer and try to figure out if the weather station is in the backyard of one house or the front yard of another.

So how do we get their address? Take their latitude and longitude and put into Google Earth and see where they are and what county they are in. This station is in Kaufman County, Texas. The easiest way in the modern era to get an address is through GIS, or Geographic Information Systems. If you Google the name of the county, name of the state, and “GIS,” you’ll likely get a government website that can use to get you to an address. In the example, Google searching “Kaufman County Texas GIS” gets you to an interactive map where you can get an address.
– Have the courage to contact someone. I know it’s weird to send someone a letter in the mail out of the blue, but you can do it…and if you want their data, you’ll have to.
– Once the person e-mails you, you can greet him or her, and explain that you’re trying to direct their weather station data to MADIS, and send them step-by-step directions to configure their software using this page that I linked to above. You may have to Google directions for other weather station software types.
– Most weather station owners, with the right approach, will share their data with MADIS. Some will not; for those that don’t want to share, you might try asking again in a year or so.

– When there’s an error in data, call the airport manager. They don’t want bad data from their airport being broadcast to the world. 
– It’s worth noting that the clocks inside AWOSes tend to drift. If the clock drifts into the future, NOAA will reject the observation (observations don’t come from the future), and you won’t get the data through ADDS or MADIS. You fix this issue by calling the airport manager, telling them this, and convincing them that their AWOS technician needs to check the AWOS clock once a month (they can adjust this remotely).

Davis WeatherLink IP Stations

Once you get the hang of how to get WU stations into MADIS, try your hand at getting Davis WeatherLink IP weather stations online. Davis’ WeatherLink IP website is here:


There are many weather stations on here that you won’t really be able to find anywhere else. Here’s a snapshot of Davis WeatherLink IP weather stations (dots) in the Tampa area:


Before we start contacting everyone on this map, remember that:

1) WeatherLink is not the same as WeatherLink IP. In a WeatherLink setup, data flows from the Davis weather station to a computer and then to CWOP. In a WeatherLink IP setup, data flows from the Davis weather station to CWOP through Davis’ servers; WeatherLink IP owners still must have a CWOP ID so they can push their data to CWOP!

2) Some WeatherLink IP owners are already sharing their data with CWOP and/or MADIS. You can verify whether the data are flowing to MADIS on NOAA’s MADIS map.

3) There will be obvious cases when the position of the weather station is wrong (in a field, over water, etc.). Clicking on each of the dots on the map may give you clues about a location (a business or organization name), an address (123 Easy Street), or someone’s name (J. Richardson). If you only get a name, use the location (latitude/longitude) on the Davis WeatherLink IP map and county GIS webpages to find the address in the latter and see if the name makes sense. You might find a John Richardson two houses down from where you thought on the GIS maps, and that is likely the person you want.

Human Processing Still Required

There will be times when weather stations go offline or report information that is clearly wrong. It is up to you to find ways to – over time – remedy the problems or find ways to quality control – either in your own mind or with a computer – the errors included in the data. Don’t get burned presenting a 0.00″ rainfall total from MADIS on a rainy night or a -40° temperature on a spring day!

Here To Help

Questions? Comments? Issues? Concerns? I’m here to help. You’re welcome to contact me at the “Contact Me” link near the top of the page.

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10 (Relatively) Easy Steps I Recommend For Being A Better Meteorologist And Communicator

As I transition away from a chapter of my life centered on meteorology, I’ve realized I’ve learned a lot about what methods work in weather and which ones don’t. There are no hard-and-fast rules for success in meteorology or weather communication (and I’m continuously learning every day). After more than 10 years of weather, I wanted to share what I believe are 10 relatively easy ways to be a better meteorologist and communicator

1. Look to see what is going on. It is a huge mistake to just jump into the model world without reviewing recent weather trends. Where are the clouds, which way are they moving, and what altitude are they at? Where are the upper-level troughs and ridges? Where is their surface convergence and upper-level divergence of air? How fast and in what direction are showers and storms to the west moving? Computer forecast models frequently suck, so blindly depending on them will get your feet to the fire frequently. You should be spending at least several minutes each time you forecast looking at radar, satellite, water vapor, weather balloon, and surface report data before you even look at a computer model. While it is a mistake to expect models to match reality (they shouldn’t match), you can better gauge a given model’s strengths and weaknesses if you know what has occurred recently. As my father told me when I was a child, “You’ve got to know where you’re at to know where you’re going.”

2. Stop being everyone else. Just because there are many meteorologists in the country using 4-panel computer forecast guidance plots doesn’t mean you have to. Just because there are many meteorologists in the country that frequently say “those temperatures” and “these temperatures” does not mean you need to. Just because there are many meteorologists in the country that make heavy use of the terms “tracking,” “watching,” and “alerting” doesn’t mean you need to. Just because someone found success in forecasting an event or communicating the impacts of that event effectively doesn’t mean you’ll have the same success nor does it mean he or she will have the same success during the next event. There’s nothing that says you can’t dress for the job you want even if everyone else is wearing business casual. There’s nothing that says you can’t use forecast tools that the veteran in your office refuses to use. There’s nothing that says you have to put your forecast slides in a specific order. You don’t have to and you shouldn’t forecast and communicate like everyone else. You have to respect the spirit of the previous forecast (see below) and the ideology of where you work, but part of what you gets you a meteorology gig is your technique and individuality (at least I hope that’s how you’re measured). Your time is best spent maximizing your potential – whether it’s telling a weather story through explainer graphics, using long-range forecast analogs to give your customers insight beyond the week ahead, or developing unique data sets that can augment weather coverage – and not comparing yourself to other people. If everybody looks the same, success (pick your metric) is more likely to be evenly distributed.

Think of it this way: if you really like a store that’s 10 miles away, and a new company opens nearly the exact same store 5 miles away, odds are good you’ll start going to the closer store and – over time – both stores will have about the same number of customers (all other factors equal). A third and fourth store may open up, and the pattern repeats. Now suppose the store that’s 10 miles away has the special sauce, the secret weapon, and the sustainable competitive advantage that their competitors can’t reproduce; odds are good you’ll continue going to or start going back to that store. The moral of the story here is that the store 10 miles away from you dared to be unique and not like everyone else and got the customer base, attention, and income they earned and deserved.

3. Look at the previous forecast. If a previous forecast is available, you should be looking at it every time you forecast. The last forecaster – hopefully – spent hours looking over information before you showed up; they probably saw a few things in model guidance that you don’t see in the first few minutes of being in the forecast chair. Additionally, when every forecaster in the group reviews the previous forecast, there is more consistency, which benefits the customer and reduces the amount of work (in the form of updating) for forecasters. Refusing or simply not being interested in the current, persistence forecast signals arrogance and ego, and these elements of your personality will surface in time whether you try to hide them or not.

4. Make an actual forecast, and don’t be wishy-washy. Models suggest fog late tonight; odds are good many meteorologists will forecast “patchy fog” or “fog possible.” One computer model says showers are coming Thursday, but another says we’re dry. What’s the forecast? “Showers possible.” Showers are on the far outer-edge of an area of low pressure are approaching. In these scenarios, I often hear “there’s a slight chance for a few scattered showers.”

These are not strong forecasts. These are the meteorological equivalents of a punt in football. If you spend some time in the models or know your climatology, you’ll know where the fog will be favored and – with time and the right education – you’ll be able to forecast what the visibility will be at several spots. Fog is more than possible; it’s something every meteorologist should be able to forecast. When it comes to clouds and showers, you have more than just the latest model runs to look through; you can look the runs before them and the previous forecast. You can review the model trends for a given forecast hour. You can look at ensemble models. You can look at individual ensemble models members. You can look at satellite and radar trends.

Regardless of what you use, you should always make a forecast and run the risk of being wrong just like every other meteorologist in the world. You’re far more likely to gain credibility and respect from a customer if you give them the information they want to hear and be as specific as you can.

In a world where all the forecasts are “chances,” “possible,” “something to watch,” or some other form of hedging a bet, you want to be definitive, honest, and to the point. If you want to stand out from the crowd, don’t be wishy-washy.

5. Be conversational. It’s easier said than done, but communicating a forecast is just talking…so just talk. Talk in the same way you would to a friend sitting next to you on the couch about the weather; if you do this, you’ll avoid all of the terrible forecast crutch phrases. I’ve never had a meteorologist talk to me about the weather and say “those temperatures are going to fall through the 50s overnight;” instead, they say “we will fall through the 50s overnight.” You don’t talk to your mother about “windy conditions,” but you will say “it’s windy, but the wind will relax this evening.” Have you ever seen two people describe the weather for the “nighttime hours tonight?” I haven’t, but I’ve seen meteorologists do it. Have you ever looked up outside and thought the skies were beautiful? You said the sky was beautiful. I still don’t know what a thundershower is. If a cell produces lightning, it’s a thunderstorm; if it doesn’t, it’s a shower. Did you ever learn about thundershowers when you first learned about the weather in grade school? I didn’t because they don’t exist.

Important parts of communication are subject matter knowledge and relaxing. If you’re using crutch phrases, you’re either nervous or not as familiar with current weather and upcoming changes as you should be. Treat the camera as a neighbor. Treat your customer in the forecasts you draft as a friend you’re standing next to.

6. Review recordings of what you communicate, and work to improve what you didn’t like. When I was early in my broadcast career, I would record weathercasts from different television markets off of TV station websites. Of the ones I liked most, I would transcribe what the meteorologist said to text. I found several great weather phrases just by reviewing and typing out these recordings. I got in the habit of doing that in my next two jobs for at least a couple of months. I learned a lot, and I realized something important:

In my opinion, the best weather communicators spoke in complete, full sentences that flowed together and connected their content back to the forecast.

When you speak to another person either in person or in writing, you write in full sentences that flow together and often tie back to a central theme. That’s what communicating a forecast is all about: flow and emphasizing key points with inflection.

Whether you produce written, audible, or visual forecasts, record it and watch it. See what you did well and what you could have done better. Do this process for your presentations until you strengthen the good and eliminate the bad. Use pauses in your presentation. Inflect your voice when you’re highlighting what is important. If nothing else, avoid cliches and replace them with something better.

7. Don’t just be a “latest model” forecaster. When you forecast only using the “latest models,” you’re forecasting more of the noise and less of the signal. There will be anomalies, there will be large model shifts, and there will be situations – especially when a system comes ashore and is finally sampled by a weather balloon – when the forecast needs to be changed. Realistically, though, changing a low or high temperature by a degree gives your customer no additional value in most situations. What is the difference between 61° and 62°? Absolutely nothing. 31° versus 32° is a different story, however. Even with this acknowledged, though, remember the previous forecaster – assuming he or she reviewed the last forecast – carried over elements of the forecast before him or her.

Being a “latest model” forecaster can prove costly. Here’s an example from this past Sunday using the NAM model. The latest model at the right shows a lack of clouds (tan, low relative humidity amounts) at 850mb or 5,000 feet above the ground. The model run before it had a significant amount of cloud cover (green, higher relative humidity amounts):


So which one is right? Of course, the real answer is a function of the previous forecast, what other models and their trends suggest, and what satellite and observed trends suggest (if anything at all). Blindly following the latest model here means you’ll likely remove and decrease clouds from the forecast. If this “latest run” isn’t a true trend, the next forecaster will just revert back to the cloudier solution; this will leave your customers are confused, show a lack of collaboration, and show your inability to make a reliable, accurate forecast.

8. Don’t be a “mandatory pressure level” forecaster. Weather doesn’t just happen at 850, 700, and 500mb. When you’re first learning to forecast and getting introduced to models, you’ll see the classic 4-panel map like this.


There it is: 500mb (18,000 feet) vorticity, sea-level pressure, 700mb (10,000 feet) relatively humidity, and precipitation. In reality, this is not that helpful for forecasting. How about boosting this up to 6-panels?


The lower-middle panel showing 850mb relative humidity and the lower-right panel showing accumulated precipitation doesn’t really help us beyond what we had above. What if a shallow layer of clouds forms at an altitude of 3,000 feet developing in the afternoon? What if upper-level winds to the west carry a copious amount of high-level clouds to your forecast location? You’ll likely never see them if you are just focused on clouds at 700mb and 850mb.

You need to know temperature and dewpoint profiles in the atmosphere. You need to know the magnitude of shear and instability to see if thunderstorms will form. You need to look at more than just the temperature at 850mb and the surface to make a snow forecast.

If you’re only focused on the main pressure levels, you’re missing most of the atmosphere. Find ways and tools that can give you a more comprehensive view of the atmosphere.

9. Stop saying – or never start saying – “um,” “uh,” “like,” “you know” and other crutch words. These words may be “conversational,” but they make you look unintelligent, unprepared, and immature in presentations. I have seen people “um” and “uh” through life-threatening weather situations, and it’s not just painful to watch; it’s suggesting the speaker can’t handle the situation and don’t take people’s safety seriously. When you present weather information, you should be able to pivot. If you speak a sentence with words in an order you didn’t intend, can you still complete the sentence? If not, I encourage you to master and refine this skill. Can you explain the same weather in more than one way? Doing this will help you avoid the killer crutch phrases. Instead of saying “uh” or “um,” just don’t say anything. There is nothing wrong with 1 or 2 seconds of silence. If you’re reading weather bulletins, make sure you know where the key information is so you are not tripping over words.

10. Don’t idolize communicators. Being the best forecaster you can be means being the best version of yourself. If you’re good at using metaphors when explaining how weather works, refine and perfect that unique craft. If you’re good at connecting current or future weather to climatology, make that your thing. If you’re good at tailoring the forecast to people’s lives and events, do that. With any forecasting job you have, there will be rules to follow and guardrails for which you’ll want to stay inside. If you’re a National Weather Service forecaster, you’ll have to make aviation forecasts to fit certain specifications. If you’re in radio, you’ll have to use company taglines and only give forecasts for certain times of the day. If you’re in television, you’ll have to cover certain types of forecasts and make relevant graphics. While you should follow the rules, you should do everything you can inside of the guardrails to make a unique, interesting, and captivating presentation that showcases your best talents and skills. If you look like every other forecaster and forecast the same way, where is your value? Do everything you can to do what you love and highlight your value add. What got someone famous isn’t necessarily what will work for you. Focus on building what you already have.

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Scott Dimmich, MBA

I try to be a modest person, but today I want to share with you something for which I am tremendously proud and required months of hard work.

For the last 2 years, I’ve been very quiet about my accomplishment, but with a career transition imminent, now is the time to share my story.


I am a proud graduate of Xavier University’s Williams College of Business. From January 2016 through early July 2017, I began and completed a Masters in Business Administration with a concentration in Business Intelligence.

In the fall of 2015, I looked at my career options for the future. My choices were: 1) stay where I am at and hope to advance, 2) stay in broadcasting and look for advancement opportunities elsewhere, including in other cities, or 3) choose a new career path. Someone I knew suggested I consider pursuing a master’s degree – specifically an MBA – in late 2015. It took less than an hour of research to realize that I would need to take about 15 courses to complete an MBA, and if I wanted to get an MBA and both start and complete a job search in 2 years, I would have to get moving. I immediately applied to two MBA programs, and ultimately chose Xavier. I’m glad I did.

I took 2 to 4 classes (usually 3) per semester from the spring semester 2016 through the first summer session of 2017. For a year and a half, I essentially had one night each week away from classes and coursework. Most of my vacation days in 2016 were spent studying, writing papers, or in a library. Some classes – like marketing and managerial strategy – were manageable; others – like operations management, managerial accounting, and data mining/statistical analysis – were quite difficult, mathematically intensive, and time consuming.

Balancing a full time job and school was challenging, and it was even more difficult to mix in the other facets of life. After a while, I ran out of “100 percents” to give. Some people fell away as I pursued a degree that I knew would make me stronger and increase my likelihood of career options. I have a new level of respect for how difficult business decisions can be and how much impact they can have.

I didn’t have a concentration when I first started at Xavier, but a professor of mine – who I now consider a friend – saw my love for data and gathering insights from it. He encouraged me to pursue a Business Intelligence track, where I could learn everything I could about data, the systems that handle it, and the techniques used to understand it.

In the summer of 2017, I finished my last two classes and began a job search. At the end of that search, I found a job that was a perfect fit and allowed me to merge my business intelligence acumen with my work experience in communication and forecasting. This job will also enhance my quality of life and work-life balance; working regular business hours is a sharp contrast to waking up at 1am for work, working holidays, and working weekends. Lastly, there will be many opportunities to grow, advance, and learn in my new job; growing and advancing in a sustainable company and industry is important to me.

My job search confirmed the things I believed to be important to me two years ago; most importantly, I wanted to stay in Cincinnati where my friends and family are. I worked hard to come back home to Cincinnati in 2011 after years working elsewhere and at college. I’m thankful that I will be living in Cincinnati – my hometown – for the foreseeable future.

I think it is best that I not share specifically where I’ll be working. This is not for lack of pride, but – instead – in an effort to make elements of my life more anonymous. I’m not one that needs to be in the limelight to be happy. I have never been interested in being an on-air “talent” or “personality” (the terms make me cringe); I chose to be a broadcast meteorologist so I could forecast and communicate the weather. After all, it was the Blue Ash/Montgomery/Symmes Township tornado of April 9, 1999 that caused be to revisit my career path.

I make this career transition with my head held high and with a lot more self-confidence and self-worth that I had years ago. I am working in my hometown with more than 10 years of experience and as an American Meteorological Society Certified Broadcast Meteorologist. I have the honor of being recognized, interning with, and being hired directly by Cincinnati’s greatest meteorologist. I’ve worked alongside some talented people who genuinely want to make the people around them better. I’ve worked some severe weather events I will remember for the rest of my life – most notably the deadly tornado outbreak of March 2, 2012. As an MBA graduate, I see businesses differently. I appreciate the impacts of business strategy. I see the difficulty and value in creating a sustainable competitive advantage. Perhaps most importantly: I see the ethical side of decisions and know when to spot poor ethics, unfair practices, and caustic behavior.

The weather will always be a part of life. I assure you I am still very connected to meteorology and will not be abandoning it. I still love the weather, and I always will.

I am thankful for the relationships I now have as a Xavier MBA graduate and for the friends I have made in the program. I am thankful to my friends and family for being patient and supportive of me in my career transition. Having the people I love, trust, and respect standing with me means a lot. I hope my late father is proud of me.

This is not a goodbye. This is simply a fresh start, and I hope you’ll celebrate with me.


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When A Tornado Debris Signature (Apparently) Isn’t A Tornado


This is a mind bender. Imagine you’re nearly certain something is happening and is a threat to someone’s life…then after an additional investigation, nothing happened.

There was a rotating thunderstorm in northern Brown County Sunday night around 1am. It needed a Tornado Warning, and it got one. Shortly after the warning was issued, there was a tornado debris signature, which essentially confirmed a damaging tornado was occurring (based on radar).

I put my own credibility on the line to highlight what I saw on Facebook:

I did the same on Twitter…once to highlight the original warning:

…and the second to emphasize the radar confirmation of a tornado:

This is the “usual” shower and thunderstorm mode of radar – formally called reflectivity – during the warning:


If you look carefully and near Buford (north of Mount Orab), you might see a hook-like feature, signaling a possible tornado. This isn’t easy to see, so let’s look at the Doppler part of Doppler radar, which will tell us how winds are moving relative to the radar:


In pink, I’ve circled what is called a couplet, or an area where winds are moving towards and area from the radar in close proximity. Red here means winds are moving away from the radar, and green colors means winds are going towards the radar. The environment around this storms has to be supportive of tornadoes in order for us to see this as a tornado; in this case, there was support for strong, severe, and tornadic storms. Let’s subtract out the overall motion (speed and direction) of the storm so we can see the storm relative motion. If you’re still confused, think of it like this: it’s easier to assess the rotation of a toy top on a table if it’s nearly stationary versus moving rapidly across a table. Here’s the storm relative velocity animation:


Again, I’ve highlighted a couplet with a pink circle. That’s strong rotation slowly weakening as it goes east.

Modern, dual-polarization radar can tell a meteorologist about the size and the shape of objects it scans, relatively speaking. If a radar scans a “bin” of the atmosphere and finds objects of varying shapes and sizes, that bin’s targets will have a low correlation. If a radar scans a “bin” of the atmosphere and finds objects of similar shapes and sizes, that bin’s targets will have a high correlation. To quantify this, we’ll turn this correlation into a correlation coefficient. Here’s the animation of this correlation coefficient just after 1am Sunday night:


I’ve circled a consistently low correlation area moving east. This area is basically the same area with strong rotation and a strong thunderstorm. As a meteorologist, this area low correlation coefficient within the area of a strongly rotating thunderstorm signals that a damaging tornado has occurred. The higher up in the atmosphere this low correlation coefficient goes, the more likely there is a damaging tornado and the more likely the tornado is to be strong. That low correlation coefficient area went up to about 5,200 above radar level:


The actual altitude is greater when you consider the height of the radar and the curvature of the Earth.

This signature (the combination of the storm, strong rotation, and low correlation coefficient) is called a tornado debris signature. Now you see the reasoning for my Facebook post and tweets above. This is clearly a dangerous situation.

The Tornado Warning ends in about 30 minutes. The storm weakens, and order is restored.

Let’s fast forward to this morning. The National Weather Service plans to survey the area for damage. The damage is surveyed, and the NWS has a verdict:


What? What happened here? We had a tornado debris signature last night.

I asked a radar expert for a second opinion:

Professor Matt Kumjian of Penn State makes a good point: it’s a blurry area. A low-level circulation with leaves in it is not a tornado. Another broadcast meteorologist – Ryan Hanrahan – suggested a drone may be helpful in a damage survey. Joey Picca of the Storm Prediction Center also has some thoughts:

I don’t know how “exhaustive” the search was by the NWS, but apparently they didn’t see anything of interest. Maybe it is a false positive. But the radar in this case is like a camera witnessing a crime where police later find nothing at the scene. Or the radar shows a series of facts but the jury says not guilty.

What do you think? I think I’m frustrated.

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Let’s Talk About The Severe Weather Threat Late In The Weekend

It’s November in the Tri-State, which means we are entering a secondary severe weather season. 11 tornadoes have been confirmed in the Tri-State during November since 1950. On average, 7 Severe Thunderstorm Warnings and 2 Tornado Warnings are issued in the Tri-State each November. The jet stream is getting stronger this time of the year, and the amount of instability in the air is getting lower as temperatures and dewpoints drop.

There’s a threat for severe storms late in the weekend, specifically Sunday night and early Monday, as a cold front sweeps into and through the Ohio Valley. While the Storm Prediction Center does not issue severe weather categories (marginal, slight, etc.) 4 or more days out, they have highlighted an elevated risk for severe storms in the Ohio Valley Sunday night:


Think of the yellow area as a “slight risk” of severe storms and the orange area as an “enhanced risk” of severe storms. Cincinnati is – more or less – in a slight risk for severe storms Sunday night and early Monday.

The environment that these storms develop and evolve in is important. It will be warm Sunday with high temperatures in the 70s:


Low temperatures Monday will be around 60°, and it appears we’ll hit our low temperature at least a couple of hours after sunrise Monday:


Temperatures will likely fall through the 70s and 60s Sunday night. This is warm enough to support thunderstorms.

Moisture is another important ingredient for storms. Dewpoints will be in the 60s ahead of Sunday’s front:


This is sufficient moisture for thunderstorms, including severe storms. Wind shear, the change in the direction and speed of the wind with increasing altitude, supports organized storms and the threat of severe storms. Here’s what the Thursday morning’s NAM model thinks for effective speed shear Sunday evening:


Numbers over 40 (knots) here support thunderstorms and severe storms. How likely are storms to rotate? Here’s what the same run of the NAM thinks for helicity (storm relative, indicating the likelihood for storms to rotate):


Number of 200 (m2/s2) here are significant, but we need other ingredients present. We need bubbles of air near the ground to rise rapidly if severe storms are to form; one way to do this is having a high low-level lapse rate, or a fast drop in the temperature going from the ground to a few thousand feet above the ground. Here’s what the NAM model thinks of that for Sunday night:


Those are low values, working against the thunderstorm and severe threat. How are the mid-level lapse rates looking?


These higher numbers are supportive of storms and severe storms if bubbles of air close to the ground are able to get higher up in the atmosphere. 

How about instability and layers of stable air aloft? Here’s what the NAM model thinks:


The warm colors are instability, and the blue colors are stability. If severe storms are to form we want a lot of the former and less of the latter. Instability is modest, and stability is generous here. This works against the likelihood of storms and severe storms, but these ingredients are less important in the colder months of the year and more important in the warmer months of the year. 

For lower-instability, higher-shear scenarios, I review what is called the SHERB parameter. As I discussed back in 2015:

While instability can often have a big influence on the chance for thunderstorms, it isn’t as important this time of the year. If thunderstorms are likely […], the SHERB parameter or index can be very helpful to a meteorologist in the colder months when looking a threat for severe weather. The SHERB parameter is helpful for getting a handle on a severe weather threat in the colder months because it focuses on temperature changes near the ground, lift in the atmosphere, and wind shear instead of instability (instability tends to be low in the winter even when we get severe weather).

Why is SHERB important? Unlike summer severe weather events which are driven by high instability and less of everything else, cold season events are driven by everything else and not often by instability. SHERB is a special blend of “everything else” that is important when gauging a severe weather threat…which makes it valuable when we don’t have summer-like heat and humidity. When SHERB values are high and the chance for rain and storms is high, severe weather is often a concern.

So what does the NAM model think of SHERB Sunday evening?


I’m looking for values of 1 or higher, which are focused northwest of Cincinnati. The 0.5- 1.0 values west of Cincinnati at this will likely drop slowly and translate east later Sunday night.

Wind speeds 5,000 feet or so above the ground are important, too; heavy rain can drag these winds aloft down to the ground. What does the NAM model think of these wind speeds?


These are significant, but not off the charts. If you’re of the math variety, these values are about 2-3 standard deviations above normal. This is enough wind to support storms and severe storms.

The positioning and strength of the jet stream is very important in the colder months of the year. Where does the NAM have the jet stream Sunday evening?


This is not ideal for thunderstorms and severe storms. The highest wind speeds are to the west (but still moving east) at 8pm Sunday night. Divergence (rising air) is in purple and positioned west and north if Cincinnati. What does Thursday’s morning’s GFS model say?


It has a lot more lift Sunday evening, and it has it stronger compared to the NAM model as it progresses east. There are clearly some strength and timing differences to resolve.

In summary, here’s what I’m thinking for Sunday night and early Monday:


This is still a wishy-washy threat at this point. We have good mid-level cooling, plenty of wind shear, and sufficient lift…but the lift timing and positioning are uncertain, instability and stability forecasts work against the storm threat, and we’ll need sunshine (even if filtered) to get the storm threat maximized.

There is plenty of time for conditions to change. Stay tuned!

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