Climate: Difference between revisions
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== | ==Goals== | ||
The climate modelling and weather forecasting community has traditionally very strong computational needs. In particular, the integration of various computational resources such as HPC and Grid jointly with data infrastructure that is addressed in VI-SEEM greatly supports research and operational activity of regional relevance. | The climate modelling and weather forecasting community has traditionally very strong computational needs. In particular, the integration of various computational resources such as HPC and Grid jointly with data infrastructure that is addressed in VI-SEEM greatly supports research and operational activity of regional relevance. |
Latest revision as of 13:29, 20 December 2016
Goals
The climate modelling and weather forecasting community has traditionally very strong computational needs. In particular, the integration of various computational resources such as HPC and Grid jointly with data infrastructure that is addressed in VI-SEEM greatly supports research and operational activity of regional relevance.
The community targeted here is active in a wide range of research activity. Perhaps the largest focus is on regional climate modelling and weather forecasting, where local weather and regional climate phenomena are investigated. This is complemented by global climate modelling where the impact of global phenomena on the regional climate is the focus. The results of both are crucial to predict extreme weather in the region and understand the future trends of the regional climate.
Another strong field of related research is the study of air pollution that includes the influence on the climate and human health. These activities jointly enable the assessment of the impact on regional climate due to climate change. Climate impact studies provide the analysis of the upcoming change on humans, the environment and society that is so crucial for policy makers.
Complementing the research activities above are code development to help improving simulation methods and also visualization, which is crucial for the analysis of the enormous amount of data created in simulations, but also important for the communication of results to policy makers in particular and the wider public in general.
The activities pursued based on tools to be provided through VI-SEEM have strong synergies, both geographically and thematically, and all require a neat integration of data and computing resources.