Presentation
Machine-Learning Emulation of the Radiative Transfer Module in a Surface Continental Model ORCHIDEE
Presenters
DescriptionThe ORCHIDEE land surface model is one of the IPSL's Earth System Model components. The radiative transfer portion of the land model calculates reflected, absorbed and transmitted light at multiple canopy levels. This calculation is crucial to the climate system, but is also the most time-consuming in ORCHIDEE. To solve this problem, we show the results of our random forest-based emulator to represent the calculation in a fast and accurate way. This emulator closely mimics the original numerics-based model with relative errors of < 10% and correlations > 0.9, while taking ~50% less computational time. The second challenge describes the process of integrating this emulator in an online-way within the context of ORCHIDEE. We describe the process of integrating using the SmartSim open-source, machine-learning tool into the Fortran-based model and will show initial results and performance benchmarks that demonstrate the future viability of hybrid HPC/AI climate modelling.
TimeTuesday, June 412:00 - 12:30 CEST
LocationHG E 3
Session Chair
Event Type
Minisymposium
Chemistry and Materials
Climate, Weather, and Earth Sciences
Engineering
Computational Methods and Applied Mathematics