With exascale computing becoming available in the next decade, global weather prediction at the kilometer scale will be enabled. Moreover, the climate community has already begun to contemplate a new generation of high-resolution climate models. High-resolution model development is confronted with several challenges. Scalability of the models needs to be optimal, including all relevant components such as I/O which easily becomes a bottleneck; both runtime and I/O will dictate how fine a resolution can be chosen while still being able to run the model at production level, e.g. at 1-30 years/day depending on the questions to be addressed. Moreover, given various scalability experiments from prototypical runs and additional model data, estimating performance for new simulations can become challenging. I present results achieved in the scope of the Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) using the ICON model for global high-resolution simulations. I give an overview of the project, I show results from multi-week global 5km simulations, and I discuss current features and limits of the simulations. I further link the findings to a new intercomparison initiative DYAMOND for high-resolution predictions. Finally, I discuss performance prediction approaches for existing performance data.

@misc{EPPFSSOTCS18,
	author	 = {Philipp Neumann and Joachim Biercamp},
	title	 = {{ESiWACE: Performance Predictions for Storm-Resolving Simulations of the Climate System}},
	year	 = {2018},
	month	 = {07},
	location	 = {Basel, Switzerland},
	activity	 = {PASC},
	abstract	 = {With exascale computing becoming available in the next decade, global weather prediction at the kilometer scale will be enabled. Moreover, the climate community has already begun to contemplate a new generation of high-resolution climate models. High-resolution model development is confronted with several challenges. Scalability of the models needs to be optimal, including all relevant components such as I/O which easily becomes a bottleneck; both runtime and I/O will dictate how fine a resolution can be chosen while still being able to run the model at production level, e.g. at 1-30 years/day depending on the questions to be addressed. Moreover, given various scalability experiments from prototypical runs and additional model data, estimating performance for new simulations can become challenging. I present results achieved in the scope of the Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) using the ICON model for global high-resolution simulations. I give an overview of the project, I show results from multi-week global 5km simulations, and I discuss current features and limits of the simulations. I further link the findings to a new intercomparison initiative DYAMOND for high-resolution predictions. Finally, I discuss performance prediction approaches for existing performance data.},
}