Ag Weather Forum

It's kind of like that old saying, "A butterfly that flaps its wings in Brazil can cause a tornado in Texas," or some other iteration of the same idea. The focus is that small changes in one part of a system can lead to big changes elsewhere. That describes the concept of chaos -- systems or events we tend to think of as random and disorderly. In physics, though, chaos isn't random at all but rather unpredictable change that appears random.

There are some great demonstrations about what chaos is and why it is so interesting but watch this Youtube video from my favorite scientific content producer, Veritasium, to get a better understanding of chaos and its true unpredictability. He even goes into the meteorology that has inspired it, so I am partial to it. https://www.youtube.com/…

What is described in the video as chaos is that systems like weather are completely deterministic -- or predictable. It's why computer models and meteorologists can exist in the first place. But weather can never be truly predictable for any serious length of time before chaos takes over and the actual weather becomes much different than its prediction -- or forecast. Variables like temperature, which are modestly variable across space, can be accurate for about a week. Precipitation, which is highly variable across space, is less accurate and through about two or maybe three days. And your tolerance for what "accurate" means changes how long forecasts can be trusted.

Another interesting point in the video talks about the "three body problem." No, it's not a new Netflix show. It shows that when we add more variables to a deterministic problem, the more chaotic it becomes. The interaction between all the points feeds on itself to produce varying results if we slightly change the initial conditions of even one of them.

In meteorology, we cannot truly know the initial conditions of the entire atmosphere. Some of the finest resolutions have a grid point every kilometer. But as we know from our own experience, the weather we experience can be different than the other side of town or our neighbor's. How many of us have discussed snowfall accumulations with our neighbors or have seen maps that display these differences? Sometimes within the same town, these can be off by a couple of inches.

Lots of varied weather occurs between the grid points. To go along with that, the ways we measure variables, like temperature, pressure and rainfall, are to the hundredth of a degree or inch, but the atmosphere works with decimal points well beyond that. These small differences add up over time.

The more we know about it, the better our forecasts become, but even slight variations in temperature, pressure, wind speed and direction, and moisture can quickly create different results, even if we run them through a model multiple times.

Using that idea, we can understand why a busy and active pattern, like we are in now, can make our local forecast change multiple times a day. With so many disturbances and their interactions to keep track of, chaos inevitably increases. This is why meteorologists often use model ensembles in their forecasts, especially at range. An ensemble forecast is just a collection of many forecasts together to try to understand the bigger picture of how weather patterns will evolve. An ensemble generally takes the average of many models as its one forecast. That can give a good idea of the overall expected pattern, but it generally does a terrible job at producing specifics. Therefore, they might not be very useful for your local forecast. They tend to overspread and smooth out precipitation to too many areas, often producing too little rain for areas that receive heavy amounts, smoothing out temperature differences along fronts and obscuring timing. But they can tell meteorologists whether your forecast is reliable. If the forecast varies significantly from the ensembles, it might not be very reliable, even if it turns out to be closer to the actual outcome than the ensemble suggested. In many other areas, the ensemble likely outperformed an individual model's forecast.

Currently, two jet streams loaded with upper-air disturbances are traversing North America, which are expected to continue through next week. With all these disturbances, their interactions will undoubtedly sow chaos across your forecast. We may see slight changes from day to day, or dramatic ones, especially as you look further out into the future. Seeing the picture as a whole, with the ensembles, shows us the pattern will continue to be active with multiple rain chances and rises and dips in temperature as the systems pass through. The chaotic -- and unpredictable -- part of that forecast will be how much rain you receive and when, as well as the temperatures each day. In other words, expect the specifics in your forecast to change, and the accuracy of your forecast to be lower for the time being.

To find more weather conditions and your local forecast from DTN, head over to https://www.dtnpf.com/…

John Baranick can be reached at john.baranick@dtn.com

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