Inference versus imprint in climate modeling

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 languageEnglish
Title of host publicationAgents, Networks, Evolution
Subtitle of host publicationA Quarter Century Of Advances In Complex Systems
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages347-363
Number of pages17
ISBN (Electronic)9789811267826
ISBN (Print)9789811267819
StatePublished - Sep 29 2022

Keywords

  • Climate modeling
  • Machine
  • Statistical inference
  • Sub-grid parametrization

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