Experiment title 
: Coarsening of fine-scale simulations for cross-scale learning
Summary :
We request resources to enable the building of a database of coarse-grained outputs from high-res (LES and km-scale) numerical simulations.
Scientific motivation:
A fundamental unsolved problem in atmospheric sciences is how to relate behaviour across scales, in particular to quantify and understand how behaviour at small scales (e.g. unresolved by a given model) feeds back onto larger scales (resolved by that model). This applies to atmospheric convection, clouds and general turbulence. ML techniques can now help learn this. However, the bottleneck now preventing progress is a lack of usable CRM or LES datasets. To be usable the data must be stored at much higher temporal resolution (30-60 minutes), and with more output variables, than is typically practical. This storage can however be temporary, as once it is post-processed to obtain the required coarse-grained quantities, most of the original data can be deleted.
The concept follows Shen et al. 2022 but with a broader range of boundary conditions and more complete set of coarse-grained fields.
Experiment Name : Coarsening of fine-scale simulations for cross-scale learning
People : Steven Sherwood, Nathan Lue and others
Model: WRF and others
Configuration: WRFlux 4.3 idealised with periodic boundaries (Gobel et al. 2021)
Initial conditions: Initial and nudging to local evolving states sampled from a GCM
Run plan: Run three days at 1-km resolution to equilibrate followed by two days at 200-m
Simulation details:
Total KSUs required : None requested here
Total storage required : 50 TB
Storage lifetime : Two months
Long term data plan : Cull data
Outputs: Coarse-grained fields and tendencies including fine-scale transports of prognostic variables
Restarts: One required (see above)
Related articles: 10.1029/2021ms002631 10.5194/gmd-15-669-2022
Analysis:
Conclusion:
While the above notes only the Sherwood group’s WRF simulations, we have contacted others in Australia who are interested in a similar approach, and a prime target would be km-scale simulations using the ACCESS model. These simulations would need code development for coarse-graining / post-processing, which we hope could be supported at a higher level above this WG by the NRI via a separate proposal. The goal would be to put outputs in a common format. This proposal will provide enough storage to enable initial testing and development.