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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
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.
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
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 We do not quote highest/lowest maximum/minimum day-time and night-time records separately.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
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
when: “The colour of the new green leaves is just visible between the scales of the swollen or elongated bud” (https://www. woodlandtrust.org.uk/visiting-woods/natures-calendar/). Phenological records, when combined with climate observations, provide long-term indicators of how plants and animals
). PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies. Bulletin of the American Meteorological Society, 96(1), 69–83. https://doi.org/10.1175/BAMS-D-13-00068.1 Bai, L., Shi, C., Li, L., Yang, Y., & Wu, J. (2018). Accuracy
. In addition to the main site, three outlying screens were erected to help record the micro-climate of the area during the Antarctic winter. Further to these base observations, still more were made on the ‘‘sledging’’ journeys away from base to either explore specific geographic areas or when in depots
Office and the Met Office logo are registered trademarks. © Crown copyright 2021, Met Office 01604 FOOD SECURITY PACK – Future Climate - Northeast Farming Region Current drought risk Drought is the dominant climate risk in the NFR. Climate models show that the observational record (blue line
AI4 Climate explores and applies cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) techniques to advance climate science and deliver improved climate information more efficiently.
AI4 Climate is funded by the UK Government’s Department for Science, Innovation and Technology (DSIT) through the International Science Partnerships Fund (ISPF) and sits within the Met Office’s National Capability AI (NCAI) Programme. The NCAI Programme demonstrates our commitment to embedding AI
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