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\begin{document}

\title{A multi-disciplinary characterization and forecast of a unique fog
event: microphysics measurements, mesoscale modeling and machine
learning.}



\author[1]{Anton Gelman}%
\author[2]{Ayala Ronen}%
\author[3]{Pavel Kunin}%
\author[1]{Tamir Tzadok}%
\author[4]{Eyal Agassi}%
\author[5]{Rong-Shyang Sheu}%
\author[6]{Adam Pietrkowski}%
\author[7]{Dorita Rostkier-Edelstein}%
\affil[1]{Hebrew University of Jerusalem}%
\affil[2]{Department of Environmental Physics, Israel Institute for Biological Research}%
\affil[3]{Tel Aviv University}%
\affil[4]{Hebrew Unibersity of jerusalem}%
\affil[5]{Unknown}%
\affil[6]{Forecasting Center}%
\affil[7]{Department of Environmental Physics, Environmental Sciences Division, IIBR}%


\vspace{-1em}



  
  \date{May 24, 2024}


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\begin{abstract}
We present a multidisciplinary study of the microphysics, mesoscale and
synoptic conditions of a rare radiation-fog event in the central and
southern regions of Israel during January 3-6, 2021. The fog developed
during nighttime from south to central coastal areas and dissipated at
morning. The synoptic conditions were dominated by Red Sea Troughs at
the surface without cyclonic upper air circulation, suitable for
radiation fog development. In-situ measurements were combined with
satellite imagery, high resolution (1-km grid size) Weather Research and
Forecast model (WRF) with Real-Time Four-Dimensional Data Assimilation
(RTFDDA) forecasts and post-processing algorithms including machine
learning (ML) to analyze this event and to evaluate its numerical
forecasting. The micro-physical analysis involved measurements of
droplet size distribution and visibility range, allowing the calculation
of liquid-water content and effective diameter of fog droplets. The
measured visibility range was 90 m. The droplet diameter main mode was
1-2 micrometers, followed by another one around 6 micrometers. Typical
liquid-water content values were 0.01-0.025 g/m3. WRF-RTFDDA mesoscale
forecasts, post-processed by simple thresholds-based and ML algorithms,
largely succeeded in predicting the temporal and spatial development of
the dense fog. They proved useful in distinguishing between near-surface
fog and elevated fog/low clouds, a distinction not possible from
satellite imagery only. Clear patches at coastal areas covered in part
by urban landuse were observed both in satellite imagery and model
forecasts. WRF-RTFDDA forecasts proved their usefulness in forecasting
this massive fog and low clouds events and in providing alerts to
operational users and field campaign deployments.%
\end{abstract}%



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\textbf{Hosted file}

\verb`JGR-Gelman et. al.docx`  available at \url{https://authorea.com/users/749973/articles/721079-a-multi-disciplinary-characterization-and-forecast-of-a-unique-fog-event-microphysics-measurements-mesoscale-modeling-and-machine-learning}

\textbf{Hosted file}

\verb`Supporting materials - Table1.docx`  available at \url{https://authorea.com/users/749973/articles/721079-a-multi-disciplinary-characterization-and-forecast-of-a-unique-fog-event-microphysics-measurements-mesoscale-modeling-and-machine-learning}

\textbf{Hosted file}

\verb`Supporting materials description.docx`  available at \url{https://authorea.com/users/749973/articles/721079-a-multi-disciplinary-characterization-and-forecast-of-a-unique-fog-event-microphysics-measurements-mesoscale-modeling-and-machine-learning}\selectlanguage{english}
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