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Climate Risk Reports
Human activities have unequivocally caused global warming, and this is affecting weather and climate extremes in every region of the world, disproportionately affecting the most vulnerable (IPCC AR6 SYR A1, A2). Action to adapt and prevent climate change cannot wait. Improved understanding
Our climate change scientists
Dr Tim Andrews Tim is a climate scientist working on forcing, feedbacks and heat uptake in the climate system. Dr Alejandro Bodas-Salcedo Alejandro works on developing and assessing the Met Office Hadley Centre's climate models. Dr Rob Chadwick Rob looks at changes in the global water cycle related
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
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
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
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
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
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
Quantifying and reducing uncertainty in climate change, through understanding and improving the representation of key processes.
This area of research involves the design, building, evaluation and improvement of climate models informed by knowledge of the mechanisms of past, present and future climates. The scientific focus is on gaining understanding and improving the representation of key processes that are critical for climate variability and change on global and regional scales. Related pages Climate change scientists
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