Minisymposium Presentation
Global Storm Resolving Simulations in a Python Framework: An (early) Perspective from EXCLAIM
Presenter
As the Director of Science for EXCLAIM, Anurag Dipankar provides strategic direction to achieve the project's scientific goals and coordinates the national and international activities related to the project. Anurag Dipankar has extensive experience in climate and weather modelling, large-eddy simulation, and convection research. He led the weather model development activities at the Centre for Climate Research Singapore, Meteorological Services Singapore (MSS). As MSS representative, he provided guidance to the WMO study group on Integrated Urban Services and participated in the committee overseeing the Urban Heat Island related research in Singapore (2016-2021). Between 2013 and 2018 he led the development of the large-eddy model ICON-LEM and also contributed to the development of the atmospheric general circulation model ICON-A at the Max Planck Institute for Meteorology in Hamburg. Prior to that, he worked as a postdoc at the Max Planck Institute towards the development of a heterogeneous multiscale modelling capability for ICON.
Presenter
Description
Within EXCLAIM (EXtreme scale Computing and data platform for cLoud-resolving weAther and clImate Modeling), we are developing a performance-portable weather and climate model that resides within a Python framework. The model is based on the German global non-hydrostatic modeling system ICON. Significant progress has been made in the last two years. Model components (i.e., dynamical core, tracer advection, and cloud microphysics) responsible for the model physics have been rewritten using an embedded DSL called GT4Py. The Python driver code that combines these physical components with the model infrastructure for a successful simulation is demonstrated to perform satisfactorily for a standard dynamical core test. Work is ongoing to expand the Python framework by including other model components. While there were several challenges along the way, the challenge that remains open is the missing connection with the conventional model developers which, by and large, is acting as an observer.