A method to diagnose boundary-layer type using Doppler lidar

Harvey, N. J. ORCID: https://orcid.org/0000-0003-0973-5794, Hogan, R. J. ORCID: https://orcid.org/0000-0002-3180-5157 and Dacre, H. F. ORCID: https://orcid.org/0000-0003-4328-9126 (2013) A method to diagnose boundary-layer type using Doppler lidar. Quarterly Journal of the Royal Meteorological Society, 139 (676). pp. 1681-1693. ISSN 1477-870X doi: 10.1002/qj.2068

Abstract/Summary

A new technique for objective classification of boundary layers is applied to ground-based vertically pointing Doppler lidar and sonic anemometer data. The observed boundary layer has been classified into nine different types based on those in the Met Office ‘Lock’ scheme, using vertical velocity variance and skewness, along with attenuated backscatter coefficient and surface sensible heat flux. This new probabilistic method has been applied to three years of data from Chilbolton Observatory in southern England and a climatology of boundary-layer type has been created. A clear diurnal cycle is present in all seasons. The most common boundary-layer type is stable with no cloud (30.0% of the dataset). The most common unstable type is well mixed with no cloud (15.4%). Decoupled stratocumulus is the third most common boundary-layer type (10.3%) and cumulus under stratocumulus occurs 1.0% of the time. The occurrence of stable boundary-layer types is much higher in the winter than the summer and boundary-layer types capped with cumulus cloud are more prevalent in the warm seasons. The most common diurnal evolution of boundary-layer types, occurring on 52 days of our three-year dataset, is that of no cloud with the stability changing from stable to unstable during daylight hours. These results are based on 16393 hours, 62.4% of the three-year dataset, of diagnosed boundary-layer type. This new method is ideally suited to long-term evaluation of boundary-layer type parametrisations in weather forecast and climate models.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/32179
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Wiley Interscience
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