INFERENCE VERSUS IMPRINT IN CLIMATE MODELING

A. J. Palmer, T. L. Schneider and L. A. Benjamin
Additional contact information
A. J. Palmer: NOAA Environmental Technology Laboratory, 325 Broadway, Boulder, CO 80305, USA
T. L. Schneider: NOAA Environmental Technology Laboratory, 325 Broadway, Boulder, CO 80305, USA
L. A. Benjamin: NOAA Forecast Systems Laboratory, 325 Broadway, Boulder, CO 80305, USA

Advances in Complex Systems (ACS), 2002, vol. 05, issue 01, 73-89

Abstract: A statistical inference method known as ε-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 profiler, a radio-acoustic 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-diffusivity parametrizations for the turbulent transport. The primary advantages of the ε-machine models are that they are a less biased modeling framework for complex processes such as turbulent transport, and that they are more memory efficient.

Keywords: Climate modeling; statistical inference; sub-grid parametrization; ε-machine (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S021952590200050X
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:05:y:2002:i:01:n:s021952590200050x

Ordering information: This journal article can be ordered from

DOI: 10.1142/S021952590200050X

Access Statistics for this article

Advances in Complex Systems (ACS) is currently edited by Frank Schweitzer

More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().