How a Weather Forecast Is Made
When you check the forecast for tomorrow or for the coming week, you are looking at the final result of an enormous chain of work that blends real measurements of the planet with computer simulations. Understanding how a forecast is built helps you read it more wisely and know how much to trust it depending on the time range.
It all starts with observations
A forecast is only as good as the data it starts from. Every hour, thousands of sources measure the current state of the atmosphere around the world. The main ones include:
- Surface stations: record temperature, humidity, pressure, wind and rainfall at ground level.
- Weather balloons (radiosondes): launched twice a day to measure the atmosphere at altitude.
- Satellites: observe clouds, water vapour and temperature from space, especially where there are no stations, such as oceans and remote areas.
- Radars and commercial aircraft: add precipitation data and readings from the upper layers during flights.
All of this information is merged in a process called data assimilation, which builds the best possible snapshot of the atmosphere at a given moment. That snapshot is the starting point for the calculation.
Numerical models: physics turned into calculation
The atmosphere obeys known physical laws: how air moves, how it warms, how vapour condenses into clouds and rain. Numerical weather models translate those laws into equations and solve them over a three-dimensional grid covering the whole planet. Starting from the current state, the model calculates step by step how the atmosphere will evolve over the following hours and days.
There are several reference global models, and many of them are available through Open-Meteo:
- ECMWF: the European model, renowned for its high accuracy in the medium range.
- GFS: the American global model, widely used and updated frequently.
- ICON: the German model, with good resolution over Europe and on a global scale.
Because each model uses different methods and resolutions, they sometimes disagree. Comparing several gives a sense of how confident a forecast is: if they all agree, confidence is high; if they diverge, there is more uncertainty.
Why forecasts carry uncertainty
The atmosphere is a chaotic system: tiny differences in the initial conditions can grow and produce very different outcomes as the days pass. This is the famous 'butterfly effect'. That is why no forecast is an absolute certainty, but rather the most probable evolution.
In addition, models cannot represent every detail of the terrain or every individual storm; they work on grids with a minimum cell size. Very local phenomena, such as a mountain thunderstorm, are the hardest to pin down exactly.
Why 7 days works, but 14 days barely does
Up to about 2 or 3 days ahead, forecasts usually do very well for temperature and the general trend. Up to 7 days they remain fairly reliable for the overall picture: whether it will be hot or cold, whether a front is coming, whether rain is likely. It is a good horizon for planning the week.
Beyond 10 to 14 days, uncertainty grows so much that the forecast becomes more of an indicative trend than a firm figure. It is useful for a general idea, but not for deciding the details of a specific event. The further ahead in time, the more worthwhile it is to check again as the date approaches.
How often the data is updated
The major global models run several times a day, typically every 6 hours, taking in the most recent observations. This means the forecast is refreshed continuously, and the same day can change between morning and afternoon, especially if relevant new information arrives.
The practical advice is simple: use the forecast for the coming days to plan, but check it again as the date gets closer. A forecast updated with fresh data will always be more accurate than one from several days ago.