The local weather forecast helps you plan your day. But if you’re checking whether it will rain, for example, you usually won’t see a “yes” or “no” in the forecast. Instead, most weather reports give precipitation as a percentage. So what does this “percentage” mean?
The percentage chance of rain or snow is called the probability of precipitation (POP). It’s the probability that at least 0.01 inches (0.25 millimeters) of precipitation will fall at a given location, according to the National Weather Service (NWS). For example, a Tuesday weather report in Atlanta of “30% chance of rain” means there’s a 30% chance of at least 0.01 inches of rain falling in Atlanta on Tuesday.
It doesn’t mean it will rain 30% of the day, or that it will rain in 30% of Atlanta. Nor does it indicate how heavy the rain will be. For example, a light afternoon thunderstorm can bring more total precipitation than a full day of misty drizzle.
“If you make that false assumption, it can really come back to haunt you,” Matt Jeglum, deputy chief of the Science and Technology Infusion Division at NWS’s Western Region Headquarters, told Live Science. He added that giving rain and snowfall forecasts as percentages is intended to help people make informed decisions.
So a 30% POP means you can take an afternoon walk without getting wet — or you could get soaked. But if you hate rain, you have to decide if it’s worth the risk. Forecasting POPs The United States began making nationwide probability forecasts in 1965.
Forecasting used to involve a lot of human intuition gained from studying weather maps, Jeglum said. Statistical models helped develop and expand these forecasts during the 1970s, according to a 1998 article in the journal Weather and Forecasting. Now the NWS uses a suite of 30 weather models to make forecasts, Jeglum said.
These models are like “parallel universes” that start out the same but evolve differently, Jeglum said. Precipitation may occur in some models and not in others. In the example of a 30% POP, this would mean precipitation — rain, snow or hail — occurred in three of the 10 models (parallel universes).
Today’s physics-based models are basically equation calculators, Jeglum said. They make their calculations using current temperature, humidity and wind speed information.
This data is collected through satellites, radar, ground stations and weather balloons. These balloons are released into the atmosphere twice every day to collect a snapshot of atmospheric conditions, according to the NWS.
This information is fed into servers on the ground, where models use physics and calculus to forecast weather conditions, Michael Souza, a certified consulting meteorologist, told Live Science.
“Whether it’s right or wrong, that’s up to us to decide,” Souza said. Meteorologists use a variety of models to make forecasts; there’s no single worldwide standard, he said. So they must use their own scientific reasoning to determine which model forecasts are more accurate.
Many times, models are calibrated — using statistics and, sometimes, artificial intelligence — to ensure that their probability predictions are accurate and not biased by variations between the model’s estimates and the actual atmosphere, Jeglum said. Even with these steps to ensure accuracy, forecasts often change because of the dynamic nature of the atmosphere.
Still, models since the 1970s have given meteorologists a huge advantage in predicting the weather several days in advance, Jeglum said. “We have a pretty good skill at answering, ‘Will it rain or not?’,” he said. “Despite the stereotype that meteorologists aren’t very good at their job.”