Daytime identification of summer hailstorm cells from MSG data
[EN] Identifying deep convection is of paramount importance, as it may be associated with extreme weather phenomena that have significant impact on the environment, property and populations. A new method, the hail detection tool (HDT), is described for identifying hail-bearing storms using multispec...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/23489 |
| Acceso en línea: | https://nhess.copernicus.org/articles/14/1017/2014/ https://hdl.handle.net/10612/23489 |
| Access Level: | acceso abierto |
| Palabra clave: | Física Meteorología MSG data Hail detection tool (HDT) Cumulonimbus clouds Hailstorms Deep convection Extreme weather 2501.14 Física de las Nubes 2501.22 Física de las Precipitaciones 2509.16 Meteorología por Satélites |
| Sumario: | [EN] Identifying deep convection is of paramount importance, as it may be associated with extreme weather phenomena that have significant impact on the environment, property and populations. A new method, the hail detection tool (HDT), is described for identifying hail-bearing storms using multispectral Meteosat Second Generation (MSG) data. HDT was conceived as a two-phase method, in which the first step is the convective mask (CM) algorithm devised for detection of deep convection, and the second a hail mask algorithm (HM) for the identification of hail-bearing clouds among cumulonimbus systems detected by CM. Both CM and HM are based on logistic regression models trained with multispectral MSG data sets comprised of summer convective events in the middle Ebro Valley (Spain) between 2006 and 2010, and detected by the RGB (red-green-blue) visualization technique (CM) or C-band weather radar system of the University of León. By means of the logistic regression approach, the probability of identifying a cumulonimbus event with CM or a hail event with HM are computed by exploiting a proper selection of MSG wavelengths or their combination. A number of cloud physical properties (liquid water path, optical thickness and effective cloud drop radius) were used to physically interpret results of statistical models from a meteorological perspective, using a method based on these "ingredients". Finally, the HDT was applied to a new validation sample consisting of events during summer 2011. The overall probability of detection was 76.9% and the false alarm ratio 16.7 % |
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