The Development of a Python-Based Model for the Prediction of Low-Level Cloud Formation

Low clouds and ground fog are two meteorological variables that forecast models find generally difficult to forecast. Many of these models are heavily reliant on relative humidity in some form such as Sundqvist’s equation for the ETA model (Sundqvist et al 1989). However, for my Bachelor’s thesis, I formulated a modification of Slingo’s equation for cloud coverage (Slingo 1987) in order to improve the forecasting of airport delays at San Francisco International Airport as well as predict the burn-off of the stratus that causes the delays. The goal of this presentation, in support of another submitted to this year’s Annual Meeting, is to examine the usage of Python in the modeling of my equation, and to investigate how the equation might be used to develop a new forecasting Python-based forecast model.