Improvement of the numerical modelling of fog formation and evolution

Fog can severely impede road traffic, aviation and many other human activities and can contribute to poor air quality.The total economic losses associated with fog have been estimated to be similar to those of tornadoes and under certain circumstances even winter storms. The physical nature of fog, which is often vertically thin, shows large spatial heterogeneity and has a strong sensitivity on small-scale surface and atmospheric variability, has made it difficult to predict its occurrence, duration and vertical extent accurately. Many field studies in the UK and elsewhere have been designed to improve our understanding of the occurrence and dissipation of fog but large uncertainties remain. It is important to stress that confidence in forecasts arises not only from correct prediction of events such as fog but also from the reduction in false positives i.e. the prediction of fog when it does not develop in nature as forecast users might prepare to mitigate the effects of fog events in vain and lose confidence in future fog predictions.

The Met Office is going to conduct, together with several UK universities, the Local And Non local Fog Experiment (LANFEX) which is intended to run for 18 months from September 2014 until March 2016 in order to encompass two winters maximising the likelihood of relevant data being collected. Measurements will be made at the Met Office site in Cardington and using a distributed network of sensors, automated weather stations, meteorological towers and tether sondes in south-west Shropshire.

This studentship is designed to make use of this unique, long-term data set and to improve the quantitative prediction of fog events using numerical models. To this end, the student will take part in some of the activities of LANFEX to ensure a thorough understanding of the measurements and the locations where the campaign is conducted. The LANFEX data set will be used to compare with model runs and provide a detailed assessment of model performance which will facilitate improvements to the prediction of fog. In particular, it is intended to examine model physics and parameterisations related to initial fog formation and its’ deepening into thick fog, but all aspects of fog evolution, including its breakup will be examined. The project will concentrate on local processes, and hence use three different column models for the study.

This project was instigated by the CASE partner (Met Office) and will be a close collaboration between UEA and the Met Office in collaboration with the project partner University of Bonn. The student will contribute to the data analysis of the field campaign and will use a suite of numerical models to improve our physical understanding of fog formation and evolution as well as contribute to improvements in operational fog prediction.

The main research objectives of this project are:

a. Improved understanding of the sensitivity of fog formation to synoptic forcing, cloud cover and radiative cooling/heating,heat and humidity fluxes from soil and vegetation

b. Improvement of parameterised fog forecast model

c. Specific recommendations as to how to improve the fog forecast in the Met Office Unified Model