• contact:

    Dr. Corinna Hoose
    Dr. Ugur Cayoglu (für SDL ESS)

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The HErZ research group proposal “ICON-SmART” addresses the role of aerosols and atmospheric chemistry for the simulation of seasonal to decadal climate variability and change. To this end, the project will enhance the capabilities of the coupled composition, weather and climate modelling system ICON-ART (ICON, icosahedral nonhydrostatic model – developed by DWD, MPI-M and DKRZ with the atmospheric composition module ART, aerosols and reactive trace gases – developed by KIT) for seasonal to decadal predictions and climate projections in seamless global to regional model configurations with ICON-Seamless-ART (ICON-SmART). Hence, this project will address a gap in Germany’s model portfolio. To allow reliable ICON-ART integrations on longer (climatic) timescales, we will first implement additional processes not considered at weather timescales, in particular coupling to other compartments of the Earth system. The processes considered will include a comprehensive (tropospheric and stratospheric) chemistry scheme, a set of scale-aware parameterizations of aerosol and trace gas processes and a corresponding treatment of emissions from the ocean and land surface. Secondly, we will accelerate the model system by reducing the complexity of comprehensive process representations (only selecting and including the most relevant elements for selected applications and scales), and by employing machine learning methods to speed up process sub-modules of the model. Based on previous work, chemistry is a promising candidate for speed-up by machine learning. In addition, the project will explore machine learning approaches for other processes. The ICON-SmART model system will provide scientists, forecasters and policy-makers with a novel tool to investigate atmospheric composition in a changing climate and allows us to answer questions that have been previously out of reach. Specifically, we will use ICON-SmART to simulate the present-day atmospheric carbon budget and global to regional emission scenarios to determine the future radiative effects of natural and anthropogenic aerosols.