An accurate weather forecast begins with an accurate weather analysis and diagnosis. A simple surface plot with satellite overlaid, here using AllisonHouse Maps, reveals critical weather features to help you make an accurate forecast.
At AllisonHouse, we have a wide variety of customers with varying degrees of knowledge about the weather. Some are degreed meteorologists. Some are storm chasers. The most enthusiastic of our customers tend to be the latter and both! And all have seen an amazing transformation in our industry over the last few decades.
The technology revolution has spilled over into revolutionizing weather data and how it is displayed and analyzed. In the late 1980s, there were few ways, for example, to see a surface map or radar: on broadcast TV, during newscasts, and that was about it. Unless…if you were really fortunate…working in a National Weather Service office, a University with a weather or research program, or a private weather company. Growing up as a kid, I remember one television station in Chicago that had a live color radar display of our local Marseilles, IL WSR-57 radar. Just to see the “base reflectivity” product at 4 zoom levels of the company choice cost the station $20,000 per month! And people saw those images for less than 2 minutes in a 24 hour news cycle…and only when there was “good stuff” happening! Every bit of data was cherished. Model data was the LFM, the NGM, and, toward the end of my college tenure, something excited called the “ETA” was coming that would blow both models out of the water. And those models were seen only on paper printouts, quite a while after they had been run! When the “Aviation” model came out, you didn’t see the morning run until about 3 PM Central time!
So now, we fast forward to 2015. Computing power has increased light years over the past several decades. There’s a TON more data and model output available. Unfortunately, a disturbing trend as part of the revolution of data and models in meteorology has professors and us older meteorologists very concerned. And, it’s been coined by a very dark term: “meteorological cancer”.
That’s a rather blunt and nasty phrase, isn’t it? Cancer, in the human body, is horrible. It destroys cells, and can leave the patient suffering terribly, or dying a slow death. But the reason why it’s called this awful name is that we can see something horrible coming, and in some cases, already here: meteorologists and forecasters who rely on model data and only cursory analysis of weather data, which leads them to make bad analyses and forecasts. In the long run, they will face the death of their careers, and I believe, without exaggeration, an industry. And, for storm chasers, it can mean that you miss out on a historical event because X model said this…and a simple analysis of current weather data, even by a non-meteorologist, would reveal that the model was going to be wrong. Even emergency managers can easily be misled by pretty looking images on their computer monitors.
Let me be clear: I’m not model-bashing here. In fact, quite the opposite: if we, as meteorologists are not cconssistently better than the models, which are now shockingly good and getting better all the time, we’re in big trouble, without exaggeration. As storm chasers or weather spotters, burying our heads in a model display very frequently instead of looking out the window or at a surface map makes us miss very vital clues as to what the atmosphere or a thunderstorm is doing, or about to do. And, as a member of the general public or an emergency manager, failure to receive emergency or urgent weather information and be able to understand what it means can cause substantial and unnecessary worsening of life and death situations.
Here at AllisonHouse, we provide the data and tools you need to diagnose and forecast the weather, and to keep you on top of dangerous weather situations. Make no mistake about it: we think we do the best at providing you with the best diagnostic and forecasting tools through AllisonHouse Maps, GRLevelx and our other partner products at a great price. But let me be blunt: it does us, and you, no good if you can’t understand what you are looking at. And, if you just mostly look at the models to tell you what may happen, you WILL succumb to meteorological cancer, relying on output on a screen instead of *complementing and enhancing* what you are seeing out your window, and in the atmosphere RIGHT NOW. That’s the key: understand the reality first, then use models as guidance to forecast beyond what the data tells you. You can become a good weather analyst and forecaster without being a meteorologist, though the latter, when done right, will consistently be able to do both better due to better training and education. Even so, you, as our AllisonHouse customers, should strive to be the best weather *analysts* you can be, so that you can become good short-term forecasters. How do you do that? Here are some suggestions:
1. Display what’s going on NOW before looking at ANY models. If you don’t understand what an 850 MB, 700, 500 or 250 MB map is, don’t worry yet. Get the SURFACE right first. Start simple: on AllisonHouse Maps, for example, bring up surface observations, and overlay them with satellite and radar. This lets you see the big picture, which, in turn, will help you to better understand what is happening on a smaller, and more local, scale. Sometimes, weather instruments are are broken, or out of error tolerance or needing calibration. Does a southeast wind at one location mean a significant meteorological boundary is there if all other winds nearby are from the northwest, or is the instrument broken? If you keep doing good analyses, you’ll figure that out quickly, even as a novice. At smaller airports, weather stations have somewhat lower instrument accuracy thresholds than at major airports, and they tend to get somewhat less maintenance annually than the ones at larger airports. But even the weather stations at big airports can sometimes go bad. Anything that looks out of the ordinary should be questioned in your mind.
2. Diagnose what’s going on before looking at ANY models. Models *generally* won’t (not yet, at least) pick up on outflow boundaries from thunderstorms, or other small-scale features. Understanding that these boundaries are there, and where they came from, will help you understand how it will affect the atmosphere in the hours ahead, even without looking at the models.
3. Look at the models with an eye to reality. If they start out bad, they might get a forecast right, but for all the wrong reasons. Models are guidance, and not truth; models are fantasy, not reality; models do an amazingly good AND bad job at forecasting the weather. The more complex or dangerous a situation, the more likely it is to be wrong. By knowing what is going on now, you can see many model errors that occur with each model, in each run, and more or less account for that. Or, throw the model out altogether as being flat wrong.
4. Keep analyzing what is going on with real-time data throughout the day. The atmosphere is always changing; it is never constant. Is your forecast going as expected? If not, why not? It means something is changing now that will be affecting what will happen shortly. And if you see something now that you didn’t before, does that mean you need to change your ideas as to what may happen in the future? Above all: don’t be afraid to admit when you’re wrong. The faster you do, the better it will be for you and everyone else. The best forecasters, analysts and meteorologists sometimes aren’t the ones who get forecasts mostly right. The best are the ones who learn from what they are doing wrong, or diagnosed incorrectly, and make corrections as needed promptly. Then, and only then, they look at the models and see if they support their thinking.
By doing these things, you won’t drool at the supercell with the big hook echo on the HRRR 6 hour model forecast. You’ll have done that earlier in your analysis, making a good diagnosis, prognosticate the short-term conditions based off that, and realize that supercells in the area are expected, and the HRRR or other models are merely confirming it. Otherwise, you’re getting meteorological cancer, which is deadly to the career of a meteorologist, and to the industry. And as a chaser, emergency manager or forecaster, you’ll miss great storms or opportunities to serve your community most effectively. Always remember: data, and an excellent analysis/diagnosis of the weather are your best friends. That’s one reason why, at AllisonHouse, we emphasize data in all our product offerings…which ultimately helps you make an accurate analysis and short-term prognosis. And that makes you a good forecaster, or an emergency manager well-equipped to understand the impacts of what you are seeing. Because if you live by the models…you will die by the models. Stomp out meteorological cancer!