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Improvement of fog forecasting using atmospheric electricity

Miller, C. S. (2025) Improvement of fog forecasting using atmospheric electricity. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00124950

Abstract/Summary

Since atmospheric electricity was first studied, fog has been known to affect measurements of it. In the 1900s, some researchers attempted to show that measurements of the potential gradient (PG) could be used in order to predict fog, but with inconclusive results. In this thesis, the interactions between fog and atmospheric electricity are studied from three different approaches. First, a method of detecting the start time of fog events from visibility is proposed, which is then used to analyse 47 fog events in Reading. The PG increases in fog by a median of 57.6 V/m compared to pre-fog values. Although the PG does not always increase before the fog events begin, it does begin increasing more than two hours in advance of the fog about twice as often as visibility measurements start changing to the same degree. Secondly, droplet size distribution measurements are used alongside physical theory to evaluate the cause of the changes in the PG. By calculating the expected effect on PG using polydisperse fog droplet measurements as input to a model, it is found that fog droplets explain many of the variations in PG in fog (correlations up to 0.6, and a p-value of down to 0.003) but that other effects are also relevant. A simulation of fog development showed the PG predicting fog 10 minutes earlier than the visibility. Finally, profiles of the vertical space charge in fog are measured on a tethered balloon platform, finding charges of up to ±100 nCm−3 during fog, which was more than expected from past modelling. These highly charged regions in fog could produce changes in the PG. In conclusion, the variations in PG, when used alongside visibility and humidity, show many signs of being an excellent tool to be used in the prediction of fog.

Item Type:Thesis (PhD)
Thesis Supervisor:Nicoll, K., Harrison, G. and Westbrook, C.
Thesis/Report Department:Department of Meteorology
Identification Number/DOI:10.48683/1926.00124950
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:124950

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