Why Meteorological Department is Always Wrong on Weather Prediction
Meteorology attracts criticism and jokes like few professions. Sometimes, research supports the humour. Three weeks ago Kenya Meteorological Department predicted that there was a 100% chance of rain in three days to come – it didn’t rain at all – followed by last week report that it wouldn’t rain this season.
According to a source from their website it stated “Wet weather is expected over the North Eastern parts the country from Tuesday evening 26th to 28th March, 2019.Heavy rainfall of more than 30mm in 24 hours is expected on Wednesday 27th March 2019 over several places in Wajir, Garissa counties and over parts of Mandera, Isiolo and Marsabit Counties. The heavy rainfall is likely to continue on Thursday 28th March 2019 over the northern parts of Wajir and Marsabit counties. Moderate wet weather is also expected over the Western parts of the Country and the Central Highlands.”
So why can’t the weatherman get it right every time, given this era of 24/7 weather data, dozens of satellite and sophisticated computer models? Click To Tweet
The science of weather forecasting falls to public scrutiny every single day. When the forecast is correct, we rarely comment, but we are often quick to complain when the forecast is wrong. Are we ever likely to achieve a perfect forecast that is accurate to the hour?
There are many steps involved in preparing a weather forecast. It begins its life as a global “snapshot” of the atmosphere at a given time, mapped onto a three-dimensional grid of points that span the entire globe and stretch from the surface to the stratosphere (and sometimes higher).
Using a supercomputer and a sophisticated model that describes the behaviour of the atmosphere with physics equations, this snapshot is then stepped forward in time, producing many terabytes of raw forecast data. It then falls to human forecasters to interpret the data and turn it into a meaningful forecast that is broadcast to the public.
Forecasting the weather is a huge challenge. For a start, we are attempting to predict something that is inherently unpredictable. The atmosphere is a chaotic system – a small change in the state of the atmosphere in one location can have remarkable consequences over time elsewhere, which was analogised by one scientist as the so-called butterfly effect.
Any error that develops in a forecast will rapidly grow and cause further errors on a larger scale. And since we have to make many assumptions when modelling the atmosphere, it becomes clear how easily forecast errors can develop. For a perfect forecast, we would need to remove every single error.
Forecast skill has been improving. Modern forecasts are certainly much more reliable than they were before the supercomputer era.
Accurate weather forecasting depends on how many eyes there are in the sky. Over 11,000 observation stations across the world take hourly measurements of temperature, air pressure, humidity, wind speed and direction, rainfall and other conditions. Aircraft, merchant ships, weather balloons and satellites do the same thing and transmit data to weather stations on the ground. Joining the dots, supercomputers generate weather maps and spew out forecasts by matching them with similar weather patterns recorded in the past. Meteorologists interpret the computer-generated forecasts by comparing with different mathematical models and tweak them by relying on the torrent of real-time data coming from the field.
So will we ever be able to predict the weather with 100% accuracy? In short, NO. There are 2×10⁴⁴ (200,000,000,000,000,000,000,000,000,000,000,000,000,000,000) molecules in the atmosphere in random motion – trying to represent them all would be unfathomable. The chaotic nature of weather means that as long as we have to make assumptions about processes in the atmosphere, there is always the potential for a model to develop errors.