Preprints
https://doi.org/10.5194/amt-2021-99
https://doi.org/10.5194/amt-2021-99

  23 Apr 2021

23 Apr 2021

Review status: this preprint is currently under review for the journal AMT.

PARAFOG v2.0: a near real-time decision tool to support nowcasting fog formation events at local scales

Jean-François Ribaud1, Martial Haeffelin2, Jean-Charles Dupont3, Marc-Antoine Drouin4, Felipe Toledo1, and Simone Kotthaus2 Jean-François Ribaud et al.
  • 1Laboratoire de Météorologie Dynamique, Ecole Polytechnique, 91128 Palaiseau, France
  • 2Institut Pierre Simon Laplace, Ecole Polytechnique, Centre National de la Recherche Scientifique, 91128 Palaiseau, France
  • 3Institut Pierre Simon Laplace, Université Versailles Saint Quentin-en-Yvelines, 78280 Guyancourt, France
  • 4Laboratoire de Météorologie Dynamique, Ecole Polytechnique, Centre National de la Recherche Scientifique, 91128 Palaiseau, France

Abstract. An improved version of the near-real time decision tool PARAFOG (PFG2) is presented to retrieve pre-fog alert levels and to discriminate between radiation (RAD) and stratus lowering (STL) fog situations. PFG2 has two distinct modules to monitor the physical processes involved in RAD and STL fog formation and is evaluated at European sites. The modules are based on innovative fuzzy logic algorithms to retrieve fog alert levels (low, moderate, high) specific to RAD/STL conditions, minutes to hours prior to fog onset. The PFG2-RAD module assesses also the thickness of the fog. Both the PFG2-RAD and PFG2-STL modules rely on the combination of visibility observations and automatic lidar and ceilometer (ALC) measurements. The overall performance of the PFG2-RAD and -STL modules is evaluated based on 9 years of measurements at the SIRTA observatory near Paris and up to two fog seasons at the Paris-Roissy, Vienna, Munich and Zurich airports. At all sites, pre-fog alert levels retrieved by PFG2 are found to be consistent with the local weather analysis. The advanced PFG2 algorithm performs with a hit rate of about 100 % for both considered fog types, and presents a false alarm ratio on the order of 10 % (30 %) for RAD (STL) fog situations. Finally, the first high alerts that result in a subsequent fog event are found to occur for periods of time ranging from −120 minutes to fog onset, with first high alerts occurring earlier for RAD than STL cases.

Jean-François Ribaud et al.

Status: open (until 18 Jun 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on amt-2021-99', Philipp Körner, 28 Apr 2021 reply
  • RC1: 'Comment on amt-2021-99', Anonymous Referee #1, 05 Jun 2021 reply

Jean-François Ribaud et al.

Jean-François Ribaud et al.

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Short summary
PARAFOG is a near-real time decision tool that aims to retrieve pre-fog alert levels minutes to hours prior to fog onset. The second version of PARAFOG allows to discriminate between radiation and stratus lowering fog situations. It is based upon the combination of visibility observations and automatic lidar and ceilometer measurements. The overall performance of the second version of PARAFOG over more than 300 fog cases at 5 different locations present a good perfomance.