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Our research into climate variability and predictability is aimed at improving the skill of the Met Office monthly to decadal forecasts.

Some physical processes that affect the climate system, such as El Niño and the global oceanic circulation, provide potential sources of climate predictability from a month to decades ahead. Our work involves the study of these processes in order to improve their representation in our prediction

Artificial intelligence (AI) and machine learning (ML) have demonstrated potential for their application in weather forecasting, the crossovers with climate science suggests that similar progress is possible in climate modelling.

Climate models are numerical representations of the Earth system (including components such as the atmosphere, ocean and land) that are used to explore long-term changes to the underlying statistical distributions that govern day-to-day weather. Developments in climate models have typically come

A link to view monthly regional climate anomalies

What is the Seasonal Climate Outlook? Following the El Nino event in 2015, the Met Office worked with the UK Government’s Foreign, Commonwealth and Development Office (FCDO) and the University of Reading to design a new service which would provide insights into the upcoming season and enable more

Developing models and techniques to produce regional climate information for climate change impacts and adaptation assessments.

The primary tool used in this work is the regional climate model, a higher resolution limited area version of a global atmospheric model. It simulates high-resolution climate skilfully through its improved resolution of a regional physiography and atmospheric motions. Work is undertaken to assess

Description of research and applications of the impacts of climate variability on monthly to seasonal timescales.

Predictions and climate model output often refer to large-scale phenomena (e.g. ENSO, NAO) or give information on large-area averages. The variables for which predictions are made are most often meteorological (e.g. temperature, rainfall). Users' needs are typically related to their economic

Met Office climate science webinars

In 2023 the Met Office ran a series of climate science webinars following on from a number of events ahead of COP27 in 2022.  Below you will find details of these past events including video recordings and written summaries. Details of upcoming events will be added below including registration

Understanding and quantifying the most important feedback processes operating in the climate system.

An important aspect of this work is to use both models and observations to try to establish links between physical processes operating in past, present and future climates. This involves the development and refinement of diagnostics and metrics for assessing model performance, and for isolating

This page displays airfield climate statistics for 48 UK airports including occurrences of Low Visibility Procedures, temperature, low cloud base, significant weather, visibility and wind.

from 1990 to 2021 has been used to allow comparison to the most recent climatological reference period (Charting the UK;s changing climate - Met Office). Where this full period is not available, the maximum range is used using data from METARs recorded at each airfield. The number of observations

be higher than the day-time maximum. In either situation this makes a comparison with the daily records invalid. We do not quote highest/lowest maximum/minimum day-time and night-time records separately. The main reason is that manual climate stations only report daily 0900-0900 UTC maximum