You wake up and look at your phone to check the weather—it’s going to be 5°C with a 50 per cent chance of rain. So, you think of wearing a warm jacket, that cozy scarf your grandma made you and consider taking an umbrella as well. And you feel set for come what may.
It feels so easy to get the information these days, with so many devices around us—our smartphones, watches, tablets, and laptops—giving us immediate access to weather forecasts. But we can just as easily forget all that has to happen behind the scenes to get it right.
Accurate weather predictions can mean more than whether you get rained on or can look forward to snow. In World War II, for instance, the weather was a deciding factor in the D-Day landings at Normandy, France.
Good weather forecasting can save lives
In June 1944, the Allied forces needed clear skies, calm waters, and a full moon for their invasion of northern France. But back then, there were no satellites, no radars and no computer models to predict the weather.
The Americans used historical data to predict whether there would be any storms. The original date of the landings had been set for June 5, so the US checked how often there had been storms on that date in the past. And their data told them that June 5 would be perfect.
The British used contemporary data. They checked wind speed, temperature, and atmospheric pressure to make their predictions. And they forecast storms for June 5 and recommended that the invasion wait a day. In the end, the Allies went with the British suggestion, and that was lucky because there were storms, violent seas, and winds in Normandy on June 5, 1944.
A good weather prediction “makes a huge difference, [it can] save lives,” said Florian Pappenberger, who leads the Forecast Department at the European Centre for Medium-Range Weather Forecasts (ECMWF).
How weather forecasting is done
Forecasting is “quite simple,” said Pappenberger. It just involves “huge amounts” of observations. And, same as in 1944, current conditions give forecasters a good idea of how the weather will be tomorrow. “Very complex and sophisticated models, sets of equations, and lines of code ingest all these observations [to] give us scenarios of the future,” Pappenberger said.
But predictions are limited. They rely on how much we know about the initial conditions—how the weather is now—and because “you don’t have observations everywhere, you don’t observe everything and the initial status is always an approximation of what the Earth really looks like,” said Pappenberger.
Weather forecasts are getting better
Our forecasting abilities keep improving, with the development of better instruments and satellites.
Take Europe’s new MTG-I1 satellite that was launched in early December: it promises to provide more accurate data for forecasting severe weather, such as storms, several hours earlier. MTG-I1 will deliver observations of “unprecedented range, resolution and frequency,” says the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), which operates the satellite.
But also, improvements in computer technology and advances in our understanding of weather science have made our predictions much better than they were on June 6, 1944. By how much? Around one day every decade—what we could predict 10 years ago for a three-day forecast, we can now do for a four-day forecast.
But there is still an element of chance.
Everything has a probability in forecasting
You might be familiar with the term “a chance of” precipitation, rain, or snow. It’s a bit hard to interpret. Say it’s a “50 per cent chance of rain”, should you take an umbrella? Cancel the picnic?
It’s hard enough to make sense of probabilities in general and the truth is that this probability of precipitation is something that not even meteorologists seem to agree on—that’s according to a survey of 188 meteorologists done in 2016. The US National Weather Service says “a chance of” refers to the probability that a given place in a forecast area will receive at least 0.01 inches (0.25 mm) of rain in a specified time period.
How they calculate that is by multiplying a number “C”, which is how confident meteorologists are that it will rain in that area, and a number “A”, which is the percentage of that area that they think will receive rain. So, the calculation is C x A = chance of rain.
But that means that a “50 per cent chance of rain” can come from either being 100 per cent sure (C=1) that it’s going to rain in 25 per cent of that area (A=0.25), or that you have 50 per cent confidence (C=0.5) that 50 per cent (A=0.5) of the area is going to get rain—and a number of other combinations as well.
“I can’t give you a recommendation on whether you should take an umbrella at 50 per cent or not,” said Pappenberger. “Everything has a probability.” That goes for rain, shine, snow, temperature—perhaps even the kind of day your particular weather app decides to show you.
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