How the Met Office uses data assimilation to produce its forecasts

How the Met Office Uses Data Assimilation to Produce Its Forecasts

Data assimilation is central to the Met Office's weather and climate predictions. This advanced technique merges millions of real-world observations with the latest model forecasts to create the most accurate representation of environmental systems like the atmosphere.

Role in Numerical Weather Prediction

Data assimilation is a vital part of numerical weather prediction, ensuring forecasts remain accurate and reliable. It is a key element of the Met Office's Next Generation Modelling Systems (NGMS) strategy, especially with the upcoming introduction of a new supercomputer.

Continuous Forecasting Cycle

Numerical weather prediction happens through a continuous cycle repeated at regular intervals—every six hours for the global model and every hour for the high-resolution UK model. Each cycle begins with a previous forecast called the background, then integrates millions of new observations.

Purpose and Process

The assimilation process aims to adjust the background forecast to create the best possible initial conditions for the next forecasting run.

Key Elements of Each Assimilation Cycle

The background forecast—the previous atmospheric state.
Millions of fresh observations.
Understanding and managing uncertainties that affect the balance of input data.

"Understanding and managing these uncertainties is crucial, as they determine how much weight we give to each ingredient in the final 'analysis,' the word we use to describe the corrected state of the atmosphere."

The final product of data assimilation is called the analysis, representing the best-estimate atmospheric state from which new forecasts begin.

Author's summary: The Met Office uses data assimilation to continuously integrate observations and forecasts, refining atmospheric models to deliver highly accurate weather predictions.

Met Office — 2025-11-05