## What’s the chance of an April shower?

How probability helps our understanding of weather events

Springtime in the UK can be fickle. Longer, warmer days create anticipation of summer, yet the extra heat from the sun can fuel the development of clouds leading to April showers. By their very nature, these showers are hit and miss events, leading to misconceptions about the accuracy of the weather forecast.

The chaotic nature of weather with its many variables means that there are unavoidable limitations to what we can predict. Showers are a particularly challenging weather phenomenon to forecast, falling as sporadic bursts of rain from cumulus clouds. By calculating the confidence in a weather forecast, and providing probabilities we can give a clearer picture of any uncertainties. In doing so, we give both individuals and businesses a greater opportunity to plan their activities around the weather.

But what is probability?
Many people are familiar with expressing the uncertainty in the outcome of a horse race in terms of odds, and we can do something very similar with weather forecasts using probability, which expresses the chance of particular weather occurring.

Probability is a way of expressing the uncertainty of an event in terms of a number on a scale. One very common way of doing this is on a scale going from 0% to 100%, where impossible events are given a probability of 0% and events that will certainly happen are given a probability of 100%.

Other events that are as likely to happen as not are given a probability halfway along the scale, at 50%. An event that is pretty likely to happen, but could possibly not happen, might have a probability of 95%.

Understanding probability
Probability can be understood better by thinking about playing heads or tails. If a coin is tossed and the probability that it will come up Heads is 50%, this means that a Head is as likely as a Tail. If the coin is tossed again and again 1000 times, you’d expect something close to 500 Heads – not necessarily exactly 500, because coin tosses are always uncertain. But the 50% probability means Heads should come up on about half the tosses in the long run – if they don’t, the probability of a Head wasn’t 50% after all.

Probability and weather forecasting
If the probability of rain tomorrow in your region is 80% it doesn’t mean that it will rain in 80% of the land area of your region, and not rain in the other 20%. Nor does it mean that it will rain for 80% of the time. What it does mean is that there is an 80% chance of rain occurring at any one place in your region.

If you don’t see any rain the 80% forecast wasn’t wrong, because it didn’t say rain was certain. But, if you look at a long run of days, on which the probability of rain was 80%, you’d expect it to have rained on about 80% of them.

Probability, accuracy and the Met Office

We check our probability forecasts against what really happened and they verify well. Probabilities are just one of the tools that we use to help us forecast the weather. The Met Office is consistently one of the top two performing weather forecasting centres worldwide, with our four-day forecasts now as accurate as a one-day forecast in the 1980’s. Extensive observations, complicated computer models, world-leading scientific techniques, supercomputer technology and the input of highly qualified meteorologists have all helped this advancement.

This means that people and businesses using our forecasts to take weather related decisions can make choices with more confidence, whether it’s you deciding whether or not to hang out the washing before going to work or retailers moving their umbrellas at the front of the store.

Despite the advances in forecasting, tomorrow’s weather can never be completely certain. However, we can be more certain on some days than others and can communicate this by using probabilities, rather than just saying “there’s a good chance of rain”. Knowing how certain we are that it will rain can help you decide whether to change your plans or take a chance on dodging that April shower!

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