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Journal Article: BibTeX citation key:  Redl2015
Redl, R., Fink, A. H. & Knippertz, P. (2015) An objective detection method for convective cold pool events and its application to northern Africa. IN Monthly Weather Review, 143. 5055–5072.
Added by: Andreas Fink 2016-01-02 21:41:20
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Categories: Weather to Climatic modelling and forecasting
Keywords: Clouds - Convection, Dynamics, Modelling
Creators: Fink, Knippertz, Redl
Collection: Monthly Weather Review

Peer reviewed
Number of views:  254
Popularity index:  18.75%

 
Abstract
Convective cold pool events in (semi) arid areas have significant impacts on their environment. They reach horizontal extents of up to several hundred kilometers and the associated turbulence and shear can cause dust emissions and threaten aviation safety. Furthermore, cold pools play a major role in the organization of deep convection and in horizontal moisture transport. They have even been proposed to have impacts on larger-scale monsoon dynamics. Cold pools are not well represented in models using a convective parameterization. To test and improve these models, it is necessary to reliably detect cold pool occurrence from standard observational data. Former studies, however, focused on single cases or short time periods.

Here, an objective and automated method for the generation of multiyear climatologies of cold-pool events is presented. The algorithm combines standard surface observations with satellite microwave data. Representativeness of stations and influence of their spatial density are addressed by comparison to a satellite-only climatology. Applying this algorithm to data from automatic weather stations and manned synoptic stations in and south of the Atlas Mountains in Morocco and Algeria reveals the frequent occurrence of cold pool events in this region. On the order of six cold-pool events per month are detected from May to September when the Saharan heat low is in its northernmost position. The events tend to cluster into several-days-long convectively active periods, often with strong events on consecutive days. The algorithm is flexible enough to be applied in comparable regions around the world.
Added by: Andreas Fink