Model applications predict fog probabilities at Canberra Airport, suggesting potential for enhanced forecasting.
A statistical model for fog probability at Canberra Airport has been developed, based on local and pressure field data available at 3 pm on the preceding day. Bayesian aggregation of one-dimensional conditional probabilities using principal components enabled the effects of a large number of variables to be combined. Application of the model to independent data gave results comparable with subjective assessment of probabilities by forecasters on the same days. The model appears capable of further development.
No takes yet. Share an insight, caveat, or question.
I. B. Mason (1977) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: