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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.

Analysing climate change and its impacts in the urban environment.

Urbanisation results in significant modification of local climates, the most apparent expression of this being the urban heat island. The global urban population now exceeds the rural population, and the urban population may exceed six billion by the 2050s. Therefore, society and our urban

The Hunger and Climate Vulnerability Index aims to paint a regional picture of how much climate change may affect life across the planet

Experts from the World Food Programme (WFP) have worked closely with our climate scientists to devise a measurement of vulnerability to climate change. Taking its definition from the Intergovernmental Panel on Climate Change (IPCC), 'vulnerability' describes the relative degrees of climate stress

Climate Data Challenge hackathon series During the first half of 2021 the Met Office and Met Office Academic Partnership (MOAP) universities led a series of virtual hackathon events with the aim of using a variety of skill sets and data products to tackle challenges related to climate change

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

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

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

Skip to main content Menu Weather & climate Research programmes Services About us Careers Met Office Search site Search x Back Weather & climate Everything you need to know about the forecast, and making the most of the weather. Find a forecast Warnings & advice Warnings & advice UK weather

Skip to main content Menu Weather & climate Research programmes Services About us Careers Met Office Search site Search x Back Weather & climate Everything you need to know about the forecast, and making the most of the weather. Find a forecast Warnings & advice Warnings & advice UK weather