How the Met Office uses data assimilation to produce its forecasts

How the Met Office Uses Data Assimilation to Produce Its Forecasts

Data assimilation forms the foundation of the Met Office’s weather and climate predictions. It is an advanced method that blends millions of real-world observations with the latest model outputs to create the most accurate depiction of environmental systems such as the atmosphere.

Core Role in Forecasting

Atmospheric data assimilation is a key element of numerical weather prediction, ensuring that forecasts remain accurate and consistent. This process is central to the Met Office’s Next Generation Modelling Systems (NGMS) initiative, supporting future advancements, including the enhanced performance of a new supercomputer.

Continuous Forecasting Cycle

Numerical weather prediction operates as a continuous cycle. Data assimilation occurs every six hours for the global model and every hour for the high-resolution UK model. Each cycle begins with a previous atmospheric forecast—termed the “background”—which is then refined by incorporating millions of new observations.

“The goal is to correct the background to produce the best possible initial conditions for the next forecast run.”

Key Components of Assimilation

Combining model forecasts with observational data
Updating atmospheric states to minimize forecast error
Balancing uncertainties to optimize the final analysis

Understanding and managing these uncertainties is essential, as they determine the weight assigned to each data source in the final analysis, which represents the corrected state of the atmosphere.

Author’s Summary

By merging massive streams of observational and model data, the Met Office continuously refines atmospheric analyses to enhance the precision and reliability of its weather forecasts.

Met Office — 2025-11-05