Updated: Jun 20
There's no doubt that you have heard a meteorologist talk about a "chance of" this
or a chance of that. Perhaps there's a 30% chance of thunderstorms this afternoon or a 60% chance of snow this evening. Typically it's mentioned in association with specific precipitation events rather than sensible weather elements such as temperature or wind. But what does a 20% chance of afternoon thunderstorms really mean?
Does it mean 20% of the time you'll get thunderstorms this afternoon? Or perhaps it means that 20% of the area will see a thunderstorm? Well, sort of, but not quite. It's a bit more complex and it all comes down to a principle called quantifying uncertainty. Meteorology is not about black and white, but more about shades of gray. Forecasters are rarely 0% or 100% certain about an event. In order to communicate their uncertainty to you they use a probabilistic approach.
The official answer provided by the National Weather Service (NWS) is...
"The likelihood of occurrence (expressed as a percent) of a precipitation event at any given point in the forecast area. The time period to which the probability of precipitation (PoP) applies must be clearly stated (or unambiguously inferred from the forecast wording) since, without this, a numerical PoP is meaningless."
Essentially PoP is the average point probability for any given area and equals the expected areal coverage of measurable precipitation. For a 20% PoP, this means that 20% of the area will receive measurable precipitation at the surface. The key word is expected. It's not saying that the areal coverage equals the PoP, but that the expected areal coverage equals the PoP. Basically if you had a large enough set of cases (during a particular season) with a particular PoP, the areal coverage should equal the PoP. The key point is that a PoP is not the same as the probability that precipitation will occur somewhere in the forecast area during the forecast period. Clear as mud? Probably not!
Here's a better way to think about it. On any given summer day in many parts of the US there is likely a 2 or 3% chance of precipitation, but that's not quite enough to get all that excited about. So the goal forecasters try to achieve is to dial in on those events that have a greater chance of occurring.
How do you interpret a 30% chance of thunderstorms? Let's look at an example. Let's say I was asked to make a forecast of whether or not there would be a thunderstorm reported somewhere in the conterminous US in July. I would likely bet the farm that somewhere in this big country during the month of July that at least one thunderstorm would be reported. So I can be very certain and my forecast would be 100%. What if I was asked to make a similar forecast of whether or not at 8 a.m. on July 14th that the Oklahoma City airport would be reporting a thunderstorm? So I wouldn't bet the farm or even a nickel. I have a lot of uncertainty there would be a thunderstorm at a specific time and place so I might forecast a 0% chance of thunderstorms. It may turn out that I'm wrong, but I have a lot better chance of being right with 0% as my forecast.
So you can see from this discussion, how you interpret the probabilistic forecast often depends on the time frame or period of the forecast (e.g., 1 hour versus 12 hours) and the area the forecast covers such as a county, airport or city. It also may depends on the phenomenon you are forecasting as well (e.g. tornado).
For example, there may be a severe thunderstorm threat this afternoon, but there's only a 2% chance of a thunderstorm that produces a tornado as you can see in the tornado outlook above. You might think, 2%, that's really small when, in fact, it's significant. Here's how the Storm Prediction Center explains...
"The probability values represent the chance of severe weather within about 25 miles of a point, which is about the size of a major metropolitan area. Though severe storms tend to receive a large amount of media coverage, severe weather is uncommon at any one location. Your chance of getting a tornado on any random day are very small, climatologically speaking. Put in that context, even a 10% chance of a tornado within 25 miles of a point means a much bigger threat than usual, and should be taken seriously. Think of how often tornadoes normally happen close to you on any given day, and those small-looking probabilities start to seem large by comparison!"
So the next time you look at a forecast that is based on a probability, you have to ask yourself two questions: (1) how much time does the forecast cover and (2) for what general area? The smaller the time and the smaller the area, the lower the probability numbers will likely be even for a fairly likely event. The bad news is that it's often difficult to answer these two questions. If the local TV broadcast meteorologist is suggesting there's a 40% chance of snow tonight, is that for a 3 hour period, 12 hour period or something else?
Many probabilistic precipitation forecasts are valid over a period of time. For example, this probability of precipitation (PoP) forecast above is valid over a 12 hour period. The valid time on the chart is the ending time of the 12 hour valid period. So it's not unusual for there to be percentages in the 80s, 90s and even 100 when the forecaster has a lot of certainty about a particular weather event. But to really understand what that probability means, you need to do your homework to try to understand a few more details.
Most pilots are weatherwise, but some are otherwise ™
Weather Systems Engineer
CFI & former NWS meteorologist