Parametrizing the Antarctic stable boundary layer: synthesizing models and observations

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record. The accurate representation of the stable boundary layer (SBL) is a key issue for weather prediction and climate models. The SBL exerts an important influence in controlling heat, moisture a...

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Bibliographic Details
Published in:Quarterly Journal of the Royal Meteorological Society
Main Authors: Walesby, KT, Beare, RJ
Format: Article in Journal/Newspaper
Language:English
Published: Wiley / Royal Meteorological Society 2016
Subjects:
Online Access:http://hdl.handle.net/10871/31190
https://doi.org/10.1002/qj.2830
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Summary:This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record. The accurate representation of the stable boundary layer (SBL) is a key issue for weather prediction and climate models. The SBL exerts an important influence in controlling heat, moisture and momentum fluxes between the surface and the rest of the atmosphere. Some of the world's most stably stratified boundary layers develop on the Antarctic continent. Previous work investigating SBLs has tended to take either a purely observational or purely modelling-based approach. Here, a novel three-way methodology has been developed which uses observations from an Antarctic site, alongside large-eddy simulation (LES) and single-column model (SCM) techniques to examine a case-study. Reasonable agreement was generally achieved between the LES and observations. The choice of stability function is an important decision for column-based parametrizations of the SBL. Four schemes were tested in the SCM, providing persuasive evidence for the use of shorter-tailed stability functions. The LES data were also used to extract implied stability functions. These experiments reinforced the conclusion that shorter-tailed stability functions offered improved performance for the Antarctic SBL. This approach represents a powerful framework for verifying SCM and LES results against a range of insitu observations.