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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

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

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

As part of the UK Climate Resilience (UKCR) programme, the Met Office has compiled an approach for upscaling climate services. This page introduces climate services providers to this resource.

this means for climate services. We have reviewed existing upscaling literature and resources, and adapted themes and concepts from them to produce an upscaling approach for climate services. We have tested this in three case studies with different services and service providers. A toolkit, to aid

Configurations of the Unified Model for seasonal, decadal and centennial climate predictions run at the Met Office.

These are usually lower resolution than the models used for day to day weather forecasting, and include ocean and sea-ice components coupled to the atmosphere model in order to represent the full coupled climate system. Additional processes associated with atmospheric chemistry and the ecosystem

Climate modelling at the Met Office

As faster supercomputers with more processing power are developed, harnessing this power and speed for the benefit of improving climate projections is the dream of climate scientists. The reality is there will never be enough speed or capability to infinitely improve climate models in all aspects

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

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Climate impacts research investigates the impacts of climate change and variability on Earth and human systems including water resources, agriculture, ecosystems, health and energy.

A key activity is the development and application of impacts models that simulate a number of terrestrial processes interactively. Using the output from these models, in addition to more complex Earth System Models, we can address the increasing requirements for more detailed climate impact information necessary to underpin both adaptation planning and mitigation advice.

Developing observational data; monitoring and interpreting climate variations and change.

Climate information and statistics, based on many types of surface, atmospheric and marine measurements, are produced on national to global scales. Climate models are used to attribute causes of past climate change that are seen within the observations. The datasets produced by our scientists are also used by other science areas. Scientific users throughout the world access the data and statistics via the HadObs website.