Abstract

An innovative set of six observed predictors of fog formation by radiative cooling is proposed, which describes: 1) one of the main processes of fog formation that is the water uptake by aerosols at surface level; 2) the fog development along the vertical up to 30 meters, as well as the cloud cover; and 3) the temporal evolution of the parameters describing the water uptake by aerosols and the cloud cover. The visibility is used as a signal of atmospheric and surface processes affecting the water uptake by aerosols. The vertical fog development is described by the vertical thermal gradient along a 30-m meteorological mast. The cloud cover is described using a ceilometer for low and middle clouds above the instrument, and satellite data for clouds in a pixel and in a larger 9 × 9-pixel region around the site. The set of predictors can be observed in operational conditions, such as on airport fields. Data acquired at the SIRTA platform (Paris, France) during two autumns and two winters were analysed, and the cloud cover classification derived from the SEVIRI instrument on the METEOSAT Second Generation satellite by the EUMETSAT/NWCSAF program was also utilized. The training data set was acquired in November 2011 while the validation data set extended over 12 months. All situations were discriminated between favourable and unfavourable scenarii of radiative cooling fog formation, with a factor of 10 in probability. 246 moderate visibility events (with visibility between 5 and 10 km) were observed under a clear sky in 12 months at SIRTA. While developed fog formed according to one scenario, thin fog formed according to six scenarii. On the contrary to thin fog, developed fog did not form when cirrus clouds were observed above moderate visibility situations. The fog formation probability varied from 12 to 43%, and even reached 100% for one thin fog. As the training data set was acquired in autumn, the predictor set seems more appropriate to nowcast fog in humid autumn conditions, when the fog formation probability was multiplied by ~2. The predictive set could be enriched by predictors proposed in literature, and tests suggest that relative humidity would improve the fog formation probability in winter. Five predictors identify 65 of the 217 no-fog events counted in 12 months, with ~3 h anticipation time. If visibility decreased below 5 km, 88 additional no-fog events were identified. In this case, the formation probability was 35% for developed fog, and 24–60% for thin fog, but with an anticipation time reduced to ~1.5 h. Only one fog, which represents 3% of the fog events, would be missed with such a predictive scheme.

Highlights

  • Numerical weather prediction models are usually not able to forecast the fog life cycle at satisfying spatial and time resolution (e.g., Clark et al, 2008; Zhou and Ferrier, 2008; Román-Cascón et al, 2015)

  • To improve nowcasting of fog formation by radiative cooling, we analysed measurements taken over a 12-month period, when visibility levels were frequently less than 10 km but with contrasted occurrences of fog

  • The measurements described physical processes occurring at both surface level and along the whole atmospheric column: the aerosol hydration and consequent decrease in visibility; the stratification of the lowest atmospheric layer; and the change in the 3D cloud cover

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Summary

Introduction

Numerical weather prediction models are usually not able to forecast the fog life cycle (formation, development, dissipation) at satisfying spatial and time resolution (e.g., Clark et al, 2008; Zhou and Ferrier, 2008; Román-Cascón et al, 2015). Aerosol and Air Quality Research, 18: 145–164, 2018 recent evolution of critical parameters within a few minutes to a few hours, which is a lead-time not covered by numerical weather prediction models (e.g., Vislocky and Fritsch, 1997; Golding, 1998; Wright and Thomas, 1998). This time window is important, as Valdez (2000) calculated that describing the low visibility event 30 minutes in advance could save $500 million annually at an airport

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