Super-cooled liquid water droplets detection using dual-polarization radar

Bernabo, Piercesare; Cuccoli, Fabrizio; Baldini, Luca; Chandrasekar, V.

doi:10.1109/metroaerospace.2016.7573197

Cited by 2 publications

(1 citation statement)

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“…Previously, similar active remote-sensing methods have been tested by NASA (Reehorst et al, 2005(Reehorst et al, , 2006Johnston et al, 2011), using a combination of ceilometer, microwave radiometer and radar, to detect icing layers. Dualpolarization radars have also been used to identify supercooled liquid water droplets in clouds (Bernabò et al, 2016). Furthermore, Harstveit (2009) developed a method to estimate icing from cloud observations using air temperature and wind speed measurements from a mountain site combined with Metar-data from a nearby airport.…”

Section: Introductionmentioning

confidence: 99%

Evaluating atmospheric icing forecasts with ground‐based ceilometer profiles

Hämäläinen

Hirsikko

Leskinen

et al. 2020

Meteorological Applications

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Atmospheric icing can cause severe damage and danger for many different sectors of society, and accurate forecasts of icing can help mitigate this. The aim of the study is to demonstrate how new ceilometer-based icing observations can be used in icing model verification. The study focuses on icing in the lowest 2 km of the atmosphere. The lowest 400 m of the atmosphere is essential for wind energy production and electricity power lines, while the higher elevations are essential from the aviation point of view. For aviation, the most risky situations are takeoffs and landings. The ceilometer observations provide a new way to investigate atmospheric icing. Ceilometers provide vertical profiles of clouds which can be further processed in order to identify in-cloud icing conditions. The new type of ceilometer-based icing observations enables more detailed verification of icing forecasts both in the vertical and in terms of geographical location. Overall, the model shows good skill in predicting clear-sky situations. The verification results show that the icing model performs better for inland areas than for coastal areas, which is attributed to the tendency of the model to forecast clouds, and in-cloud icing, at higher altitudes than observed.

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Section: Introductionmentioning

confidence: 99%