How the Met Office uses data assimilation to produce its forecasts

How the Met Office Uses Data Assimilation for 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, creating the most accurate possible representation of environmental systems like the atmosphere.

Role in Numerical Weather Prediction

Data assimilation is a vital part of numerical weather prediction. It ensures forecasts remain accurate and is a cornerstone of the Met Office’s Next Generation Modelling Systems (NGMS), especially as new supercomputer capabilities are introduced.

Continuous Forecast Cycle

Numerical weather prediction is not a single event but a continuous process. For the global model, data assimilation repeats every six hours; for the high-resolution UK model, it happens every hour. Each cycle starts with a previous forecast, called the ‘background’, and integrates millions of new observations.

Key Steps in Assimilation

Managing Uncertainties

Understanding and managing uncertainties is essential. These uncertainties determine how much weight is given to each input in the final “analysis”—the term used for the corrected state of the atmosphere.

“The goal is to correct the background to produce the best possible ‘initial conditions’ for the next forecast run.”
“Understanding and managing these uncertainties is crucial, as they determine how much weight we give to each ingredient in the final ‘analysis’.”

The Met Office relies on data assimilation to continuously refine forecasts, ensuring accuracy by blending real-world observations with advanced modeling and careful uncertainty management.

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Met Office Met Office — 2025-11-05

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