Published: 2015-01-27 20:24:00
Updated: 2015-01-28 06:19:34
Posted January 27, 2015
Updated January 28, 2015
Have you seen a graphic circulating on the internet that shows a foot of snow forecast for Raleigh this weekend? You are not alone.
But there's no need to lay in the bread and eggs just yet. The difference is in deterministic versus ensemble models of forecasting.
First, what are ensembles and why are they so important?
Let's start with what we call a "deterministic model." That is a single computer model, with mathematical equations that describe all the laws of physics and thermodynamics, along with some algorithms (estimates) of processes that cannot be modeled explicitly. We call them deterministic models because they, in effect, are saying to us "This is the way the atmosphere will change over the next week, period! End of discussion!"
Well, no computer model can do that, and one of the biggest reasons why is our inability to observe the atmosphere perfectly. The initial conditions we feed into these models are critical, and even very small errors in the analysis can cause big problems just a few days out.
Now that computing power is so much more robust, we can take those initial conditions and tweak them ever so slightly, to 20, 30 or even 50 different extents. Then you run all those models to see how much variance those small initial changes cause.
If there is enough similarity in the solutions, you have high confidence in the forecast. But if the solutions look like a fingerpainting exercise, then the message is this: The atmosphere is in a highly volatile state, so do not hang your hat on any one solution. Multiple models can present the two or three most likely solutions, and you need to prepare for all three until the situation resolves itself.
During the past week, the European deterministic model produced one forecast last Sunday night indicating nearly a foot of snow for Raleigh this coming weekend. That forecast was circulated all over the internet, even though every forecast before and since has shown next to no snow, and the ensembles together have never indicated a big snow.
Take a look at the graph. These are snowfall forecasts from the European Ensemble Mean (top) and the European deterministic model (bottom). The times along the bottom represent the time the forecast was made for the upcoming weekend. As you can see, the ensemble mean is consistently low while the deterministic has a spike of 9 inches.
There are a lot of folks out there who want to be heroes, and they take that one forecast, circulate it as their own forecast, hoping that it turns out to be right, promoting them to an iconic status. It rarely works, but when the blind squirrel finally finds the nut, all is forgiven.
In the forecast earlier this week for New York City, ensembles outperformed the deterministic models, and that they appear to be performing better again in the case of whether we will get slammed on Sunday.
Yes Virginia, there is uncertainty, and it's not going away anytime soon. The best we can do is explain to you how we arrive at our forecast.
A meteorologist's job is to take the best science available to him or her, combining real observations with computer-model guidance to produce the best forecast possible. And yes, there are times when we have low confidence. It is our duty to be honest with you and tell you that, just like it's your duty to realize that weather forecasting is not an exact science.
Do you see this as being wishy-washy? I can see how you would. After all, you never heard about levels of uncertainty 10, 20, 30 or even 40 years ago.
Why now? The truth is, the level of uncertainty was even higher back then than it is now. It's just that nobody wanted to talk about it.
Nobody likes uncertainty, but it is a fact of life, and we all need to deal with it.
Here in the WRAL Weather Center, we'd rather be right than promote the hype. We will never be the first ones to call for a huge snowstorm or a massive tornado outbreak, unless of course no one else talks about it.
In the meantime, honest communication is our only hope.