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Predicting Fog in the Nocturnal Boundary Layer. / Izett, Jonathan; van de Wiel, Bas; Baas, Peter; van der Linden, Steven; van Hooft, Antoon; Bosveld, Fred C.

In: Geophysical Research Abstracts (online), Vol. 19, EGU2017-8389, 2017.

Research output: Contribution to journalMeeting AbstractScientific

Harvard

Izett, J, van de Wiel, B, Baas, P, van der Linden, S, van Hooft, A & Bosveld, FC 2017, 'Predicting Fog in the Nocturnal Boundary Layer', Geophysical Research Abstracts (online), vol. 19, EGU2017-8389.

APA

Izett, J., van de Wiel, B., Baas, P., van der Linden, S., van Hooft, A., & Bosveld, F. C. (2017). Predicting Fog in the Nocturnal Boundary Layer. Geophysical Research Abstracts (online), 19, [EGU2017-8389].

Vancouver

Izett J, van de Wiel B, Baas P, van der Linden S, van Hooft A, Bosveld FC. Predicting Fog in the Nocturnal Boundary Layer. Geophysical Research Abstracts (online). 2017;19. EGU2017-8389.

Author

BibTeX

@article{fe482dafd1a9467888fae27bd2ec789e,
title = "Predicting Fog in the Nocturnal Boundary Layer",
abstract = "Fog is a global phenomenon that presents a hazard to navigation and human safety, resulting in significant economic impacts for air and shipping industries as well as causing numerous road traffic accidents. Accurate prediction of fog events, however, remains elusive both in terms of timing and occurrence itself. Statistical methods based on set threshold criteria for key variables such as wind speed have been developed, but high rates of correct prediction of fog events still lead to similarly high “false alarms” when the conditions appear favourable, but no fog forms. Using data from the CESAR meteorological observatory in the Netherlands, we analyze specific cases and perform statistical analyses of event climatology, in order to identify the necessary conditions for correct prediction of fog. We also identify potential “missing ingredients” in current analysis that could help to reduce the number of false alarms. New variables considered include the indicators of boundary layer stability, as well as the presence of aerosols conducive to droplet formation. The poster presents initial findings of new research as well as plans for continued research. ",
author = "Jonathan Izett and {van de Wiel}, Bas and Peter Baas and {van der Linden}, Steven and {van Hooft}, Antoon and Bosveld, {Fred C.}",
year = "2017",
language = "English",
volume = "19",
journal = "Geophysical Research Abstracts (online)",
issn = "1607-7962",
note = "EGU General Assembly 2017, EGU 2017 ; Conference date: 23-04-2017 Through 28-04-2017",
url = "http://www.egu2017.eu/",

}

RIS

TY - JOUR

T1 - Predicting Fog in the Nocturnal Boundary Layer

AU - Izett, Jonathan

AU - van de Wiel, Bas

AU - Baas, Peter

AU - van der Linden, Steven

AU - van Hooft, Antoon

AU - Bosveld, Fred C.

PY - 2017

Y1 - 2017

N2 - Fog is a global phenomenon that presents a hazard to navigation and human safety, resulting in significant economic impacts for air and shipping industries as well as causing numerous road traffic accidents. Accurate prediction of fog events, however, remains elusive both in terms of timing and occurrence itself. Statistical methods based on set threshold criteria for key variables such as wind speed have been developed, but high rates of correct prediction of fog events still lead to similarly high “false alarms” when the conditions appear favourable, but no fog forms. Using data from the CESAR meteorological observatory in the Netherlands, we analyze specific cases and perform statistical analyses of event climatology, in order to identify the necessary conditions for correct prediction of fog. We also identify potential “missing ingredients” in current analysis that could help to reduce the number of false alarms. New variables considered include the indicators of boundary layer stability, as well as the presence of aerosols conducive to droplet formation. The poster presents initial findings of new research as well as plans for continued research.

AB - Fog is a global phenomenon that presents a hazard to navigation and human safety, resulting in significant economic impacts for air and shipping industries as well as causing numerous road traffic accidents. Accurate prediction of fog events, however, remains elusive both in terms of timing and occurrence itself. Statistical methods based on set threshold criteria for key variables such as wind speed have been developed, but high rates of correct prediction of fog events still lead to similarly high “false alarms” when the conditions appear favourable, but no fog forms. Using data from the CESAR meteorological observatory in the Netherlands, we analyze specific cases and perform statistical analyses of event climatology, in order to identify the necessary conditions for correct prediction of fog. We also identify potential “missing ingredients” in current analysis that could help to reduce the number of false alarms. New variables considered include the indicators of boundary layer stability, as well as the presence of aerosols conducive to droplet formation. The poster presents initial findings of new research as well as plans for continued research.

UR - https://meetingorganizer.copernicus.org/EGU2017/EGU2017-8389.pdf

M3 - Meeting Abstract

VL - 19

JO - Geophysical Research Abstracts (online)

JF - Geophysical Research Abstracts (online)

SN - 1607-7962

M1 - EGU2017-8389

T2 - EGU General Assembly 2017

Y2 - 23 April 2017 through 28 April 2017

ER -

ID: 44263638