Abstract

The overall depth of a fog layer is one of the important factors in determining the hazard that a fog event presents. With discrete observations and often coarse numerical grids, however, fog depth cannot always be accurately determined. To address this, we derive a simple analytical relation that describes the change in depth of a fog interface with time, which depends on the tendencies and vertical gradients of moisture. We also present a lengthscale estimate for the maximum depth over which mixing can occur in order for the fog layer to be sustained, assuming a uniform mixing of the vertical profiles of temperature and moisture. Even over several hours, and when coarse observational resolution is used, the analytical description is shown to accurately diagnose the depth of a fog layer when compared against observational data and the results of large-eddy simulations. Such an analytical description not only enables the estimation of sub-grid or inter-observation fog depth, but also provides a simple framework for interpreting the evolution of a fog layer in time.

Highlights

  • This manuscript presents an analytical description of fog growth and evolution

  • We present a lengthscale estimate of the maximum depth that a fog layer can achieve, the maximum attainable mixed depth (MAMD), as might occur if there was a sudden mixing event that equalizes the vertical profiles of temperature and humidity

  • The denominator is always positive in the case of fog top, and the sign of the numerator governs whether the fog layer will deepen or erode

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Summary

Introduction

This manuscript presents an analytical description of fog growth and evolution. We do this with two goals: (1) to provide a simple framework for understanding the evolution of fog layers, and (2) to allow for continuous estimation of fog depth and growth rate in otherwise discrete settings.Fog is a hazard to human activities, especially transportation. This manuscript presents an analytical description of fog growth and evolution. We do this with two goals: (1) to provide a simple framework for understanding the evolution of fog layers, and (2) to allow for continuous estimation of fog depth and growth rate in otherwise discrete settings. Fog is a hazard to human activities, especially transportation. Accurate monitoring and forecasting of fog events is essential. In addition to knowing the timing of events, it is important to know the severity of the event, including the depth of the fog layer. The hazard that a shallow fog layer presents to airport operations is much less than that of a deeper fog layer

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