CloudBench Statistics Dataset

Creators: Chammas, Sheide¹; Wang, Qing¹; Schneider, Tapio^{2, 1}; Carver, Rob¹; Shen, Zhaoyi²; Parker, Jeffrey¹; Gazen, Cenk¹; Ihme, Matthias¹; Chen, Yi-fan¹; Anderson, John¹

1. Google (United States)
2. California Institute of Technology

Description

CloudBench Dataset

This dataset contains the post-processed statistical output from 10,000 Large-Eddy Simulations (LES) driven by a General Circulation Model (GCM), as part of the CloudBench dataset produced by Google Research.

The data was generated by performing an ensemble of high-resolution large-eddy simulations (LES) covering diverse meteorological conditions across the tropical Pacific. The LES are forced with the large-scale conditions derived from a single GCM model (the GFDL CM4) for 500 locations, 4 representative months (January, April, July, and October), and 5 different climate scenarios.

The simulations were conducted in Swirl-LM, a computational fluid dynamics (CFD) simulation framework that is accelerated by the Tensor Processing Unit (TPU). Refer to the documentation in Swirl-LM for information about installation, required hardware, and instructions on how to run large simulations on TPU nodes in Google Cloud.

Further details on the dataset are available in the README file.

Files

Files (193.3 MB)

Name	Size	Actions
cloudbench_statistics.nc md5:f288c4b7462db3b2a3ce7896a5fd3acc	193.3 MB	Download