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Clotilde Augros
,
Pierre Tabary
,
Adrien Anquez
,
Jean-Marc Moisselin
,
Pascal Brovelli
, and
Olivier Bousquet

Abstract

An algorithm for the detection of horizontal wind shear at low levels was developed. The algorithm makes use of data collected by all radars from the Application Radar à la Météorologie Infra-Synoptique (ARAMIS) operational network, in order to build a complete mosaic of wind shear over metropolitan France. The product provides an estimation of the maximum horizontal wind shear detected in the low levels, between 0 and 2 km AGL. Examination of the wind shear mosaic for different cases shows that the product is able to retrieve small-scale wind shear signatures that can be linked to either convergence lines ahead of convective cells, which are indicative of gust fronts, or strong convergence areas inside intense cells. A statistical evaluation of the wind shear mosaic was performed, by comparing horizontal wind shear observed inside the area defined by convective objects with wind gusts recorded along their trajectory by weather stations. A link between those different observations was clearly established.

Therefore, the use of wind shear for wind gust prediction was tested in combination with other parameters: an estimation of the energetic potential of density currents, the cell surface with reflectivity over 51 dBZ, relative helicity, and cell propagation speed. Different wind gust warning rules were tested on 468 convection nowcasting objects (CONOs). The results clearly highlighted the benefits of using wind shear for wind gust estimation, and also demonstrated the improvement in forecasting skill when combining different parameters. The wind shear mosaic will be produced operationally before the end of 2013 and will be used to improve wind gust warnings provided to end users.

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Julie Haggerty
,
Eric Defer
,
Adrianus De Laat
,
Kristopher Bedka
,
Jean-Marc Moisselin
,
Rodney Potts
,
Julien Delanoë
,
Frédéric Parol
,
Alice Grandin
, and
Stephanie Divito

Abstract

In the past two decades, more than 150 jet engine power-loss and damage events have been attributed to a phenomenon known as ice crystal icing (ICI). Ingestion of large numbers of ice particles into the engine core are thought to be responsible for these events, which typically occur at high altitudes near large convective systems in tropical air masses. In recent years, scientists, engineers, aviation regulators, and airlines from around the world have collaborated to better understand the relevant meteorological processes associated with ICI events, solve critical engineering problems, develop new certification standards, and devise mitigation strategies for the aviation industry. One area of research is the development of nowcasting techniques based on available remote sensing technology and numerical weather prediction (NWP) models to identify areas of high ice water content (IWC) and enable the provision of alerts to the aviation industry. Multiple techniques have been developed using geostationary and polar-orbiting satellite products, NWP model fields, and ground-based radar data as the basis for high-IWC products. Targeted field experiments in tropical regions with high incidence of ICI events have provided data for product validation and refinement of these methods. Beginning in 2015, research teams have assembled at a series of annual workshops to exchange ideas and standardize methods for evaluating performance of high-IWC detection products. This paper provides an overview of the approaches used and the current skill for identifying high-IWC conditions. Recommendations for future work in this area are also presented.

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