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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
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
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
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
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
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
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 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
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 and minimum
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