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| Titel |
Forecasting of radiation fog with a new decision support system based on
automatic LIDAR-ceilometer measurements |
| VerfasserIn |
Quentin Laffineur, Martial Haeffelin, Juan-Antonio Bravo-Aranda, Marc-Antoine Drouin, Juan-Andrés Casquero-Vera, Jean-Charles Dupont, Hugo De Backer |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250150310
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| Publikation (Nr.) |
 EGU/EGU2017-14754.pdf |
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| Zusammenfassung |
| Radiation fog is the most frequent cause of surface visibility below 1 km, and is one of the
most common and persistent weather hazards encountered in aviation and to nearly all forms
of surface transport. Forecasting radiation fog can be difficult, a number of approaches have
been used to integrate the satellite data, numerical modeling and standard surface
observations. These approaches lack generally the vertical and temporal resolution,
representation of boundary layer and microphysical processes. They typically do not
represent accurately the activation processes of fog droplets that depend on the chemical and
physical properties of the aerosols.
The automatic LIDAR-ceilometer (ALC) primarily designed for cloud base height
detection has greatly improved over the last years and now offers the opportunity to analyse
in near real-time the backscatter signal in the boundary layer that potentially contains
major information to predict radiation fog formation or not. During the preliminary
stage of fog formation, the backscatter profile may be influenced by atmospheric
humidity due to the presence in the atmosphere of hygroscopic aerosols that see their
size increase with their moisture content inducing an increase of the backscatter
magnitude.
In the framework of TOPROF (COST-ACTION, http://www.toprof.imaa.cnr.it/) activities,
collaboration was initiated between the Royal Meteorological Institute of Belgium
(RMI) and the Site Instrumental de Recherche par Télédéction Atmosphérique
(SIRTA, IPSL) to develop a forward stepwise screening algorithm (PARAFOG) to
help prediction of radiation fog formation. PARAFOG is a new decision support
system for radiation fog forecasting based on analysis of the attenuated backscatter
measured by ALCs, found at most airports, which provides information about the
aerosol-particle hygroscopic growth process (Haeffelin et al., 2016). The monitoring
of this hygroscopic growth process could provide useful warning to forecasters,
in support of their fog forecast, minutes to hours prior to formation of radiation
fog.
In this presentation, we will describe the methodology used in PARAFOG to derive
pre-fog formation alerts and we will show a selection of several radiation fog events observed
on two different sites to illustrate the efficiency of PARAFOG to detect radiation fog
events.
Citation: Haeffelin, M., Laffineur, Q., Bravo-Aranda, J.-A., Drouin, M.-A.,
Casquero-Vera, J.-A., Dupont, J.-C., and De Backer, H.: Radiation fog formation alerts using
attenuated backscatter power from automatic lidars and ceilometers, Atmos. Meas. Tech., 9,
5347-5365, doi:10.5194/amt-9-5347-2016, 2016. |
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