| Abstract: |
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Weather and climate prediction are high-performance computing applications with significant societal and economic impact, ranging from disaster response and climate change adaptation strategies to agricultural production and energy policy. Forecasts are based on millions of observations made every day around the globe, which are then input to numerical models. The models represent complex processes that take place on scales from hundreds of metres to thousands of kilometres in the atmosphere, the ocean, the land surface, the cryosphere and the biosphere. Forecast production and dissemination to users is always time critical, and output data volumes already reach petabytes per week. Meeting the future requirements for forecast reliability and timeliness needs 100-1000 times bigger HPC resources than today – and towards exascale. To meet these requirements, the weather and climate prediction community is undergoing one of its biggest revolutions since its foundation in the early 20th century. The revolution encompasses a fundamental redesign of mathematical algorithms and numerical methods, the ingestion of new programming models, the implementation of dynamic and resilient workflows and the efficient post-processing and handling of big data. The talk will introduce the history of weather science and share examples of its skill and ambition. The science challenge will be translated into computing and data challenges as well as the current avenues the weather and climate prediction community is taking in preparing for the new computing age.
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