Near-surface temperature inversion growth rate during the onset of the stable boundary layer

Near-surface temperature inversion growth rate during the onset of the stable boundary layer AbstractThis study aims to find the typical growth rate of the temperature inversion during the onset of the stable boundary layer around sunset. The sunset transition is a very challenging period for numerical weather prediction, since neither accepted theories for the convective boundary layer, nor those for the stable boundary layer appear to be applicable. To gain more insight in this period a systematic investigation of the temperature inversion growth rate is conducted. A statistical procedure is used to analyze almost 16 years of observations from the Cabauw observational tower, supported by observations from two additional sites (Dome C and Karlsruhe). The results show that, on average, the growth rate of the temperature inversion (normalized by the maximum inversion during the night) weakly declines with increasing wind speed. The observed growth rate is quantitatively consistent among the sites, and it appears insensitive to various other parameters. The results were also insensitive to the afternoon decay rate of the net radiation except when this decay rate was very weak. These observations are compared to numerical solutions of three models with increasing complexity: a bulk-model, an idealized single-column model (SCM) and an operational-level SCM. It appears only the latter could reproduce qualitative features of the observations using a first-order closure. Moreover, replacing this closure with a prognostic TKE-scheme substantially improved the quantitative performance. This suggests that idealized models assuming instantaneous equilibrium flux-profile relations may not aid in understanding this period, since history effects may qualitatively affect the dynamics. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Atmospheric Sciences American Meteorological Society

Near-surface temperature inversion growth rate during the onset of the stable boundary layer

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0469
D.O.I.
10.1175/JAS-D-17-0084.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThis study aims to find the typical growth rate of the temperature inversion during the onset of the stable boundary layer around sunset. The sunset transition is a very challenging period for numerical weather prediction, since neither accepted theories for the convective boundary layer, nor those for the stable boundary layer appear to be applicable. To gain more insight in this period a systematic investigation of the temperature inversion growth rate is conducted. A statistical procedure is used to analyze almost 16 years of observations from the Cabauw observational tower, supported by observations from two additional sites (Dome C and Karlsruhe). The results show that, on average, the growth rate of the temperature inversion (normalized by the maximum inversion during the night) weakly declines with increasing wind speed. The observed growth rate is quantitatively consistent among the sites, and it appears insensitive to various other parameters. The results were also insensitive to the afternoon decay rate of the net radiation except when this decay rate was very weak. These observations are compared to numerical solutions of three models with increasing complexity: a bulk-model, an idealized single-column model (SCM) and an operational-level SCM. It appears only the latter could reproduce qualitative features of the observations using a first-order closure. Moreover, replacing this closure with a prognostic TKE-scheme substantially improved the quantitative performance. This suggests that idealized models assuming instantaneous equilibrium flux-profile relations may not aid in understanding this period, since history effects may qualitatively affect the dynamics.

Journal

Journal of the Atmospheric SciencesAmerican Meteorological Society

Published: Aug 24, 2017

References

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