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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
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
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 We do not quote highest/lowest maximum/minimum day-time and night-time records separately.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 temps
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
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
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
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
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
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
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
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