Abstract
A statistical inference method known as "-machine reconstruction is introduced as a modeling procedure for turbulent transport processes in a climate model. Observational data on the atmospheric boundary layer obtained with a radar wind proler, a radioacoustic sounding system, and a Raman lidar system was assembled to construct this type of model for use within the unresolved (sub-grid) scales of a numerical climate model. An ensemble of 500 single-column model runs using the inferred sub-grid turbulent transport models demonstrated comparable performance to an identical ensemble of runs using the standard, eddy-diusivity parametrizations for the turbulent transport. The primary advantages of the "-machine models are that they are a less biased modeling framework for complex processes such as turbulent transport, and that they are more memory effcient.
| Original language | English |
|---|---|
| Title of host publication | Agents, Networks, Evolution |
| Subtitle of host publication | A Quarter Century Of Advances In Complex Systems |
| Publisher | World Scientific Publishing Co. Pte Ltd |
| Pages | 347-363 |
| Number of pages | 17 |
| ISBN (Electronic) | 9789811267826 |
| ISBN (Print) | 9789811267819 |
| State | Published - Sep 29 2022 |
Keywords
- Climate modeling
- Machine
- Statistical inference
- Sub-grid parametrization