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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

Our climate impacts scientists

Dr Richard Betts Richard leads the climate impacts area, specialising in ecosystem-hydrology-climate interactions but also overseeing work on urban, health, industry and finance. Penny Boorman Penny is a climate scientist working on a framework to study uncertainties in dangerous climate impacts

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

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

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

Improving our understanding of the role of the oceans and the cryosphere (ice) in the climate system.

Key aims Improving ocean and ice modelling capability. Providing advice to government regarding climate mitigation. Understanding how the oceans, sea-ice and land-ice could be affected by climate change and how these changes could feed back onto the climate system.  

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

Providing advice on the impact of climate variability and change for security.

Climate science has made huge progress in understanding the dynamics of climate variability and change over the last few decades, with climate models being a valuable tool for understanding the future climate. However, there remains a gap between the type of information climate projections provide

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

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