Abstract:
The creation of scientific weather forecasts is troubled by many technological challenges
while their utilization is dismal. Consequently, the majority of small-scale farmers in Africa
continue to consult weather lore to reach various cropping decisions. Weather lore is a
body of informal folklore associated with the prediction of the weather based on indigenous
knowledge and human observation of the environment. As such, it tends to be more
holistic and more localized to the farmers’ context. However, weather lore has limitations
such as inability to offer forecasts beyond a season. Different types of weather lore exist
and utilize almost all available human senses (feel, smell, sight and hear). Out of all the
types of weather lore in existence, it is the visual or observed weather lore that is mostly
used by indigenous societies to come up with weather predictions. Further, meteorologists
continue to treat weather lore knowledge as superstition partly because there is no means
to scientifically evaluate and validate it. The visualization and characterization of visual sky
objects (such as moon, clouds, stars, rainbow, etc) in forecasting weather is a significant
subject of research. In order to realize the integration of visual weather lore knowledge in
modern weather forecasting systems, there is a need to represent and scientifically
substantiate weather lore. This article is aimed at coming up with a method of organizing
the weather lore from the visual perspective of humans. To achieve this objective, we
used fuzzy cognitive mapping to model and represent causal relationships between
weather lore concepts and weather outcomes. The results demonstrated that FCMs are
efficient for matrix representation of selected weather outcome scenarios caused visual
weather lore concepts. Based on these results the recommendation of this study is to use
this approach as a preliminary processing task towards verifying weather lore.
