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- W4200299148 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> 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 PFG2-STL modules is evaluated based on 9Â years of measurements at the SIRTA (Instrumented Site for Atmospheric Remote Sensing Research) 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 100â% for both considered fog types and presents a false alarm ratio on the order of 10â% (30â%) 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 <span class=inline-formula>â</span>120âmin to fog onset, with the first high alerts occurring earlier for RAD than STL cases." @default.
- W4200299148 created "2021-12-31" @default.
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- W4200299148 date "2021-10-04" @default.
- W4200299148 modified "2023-10-01" @default.
- W4200299148 title "Reply on RC1" @default.
- W4200299148 doi "https://doi.org/10.5194/amt-2021-99-ac2" @default.
- W4200299148 hasPublicationYear "2021" @default.
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