Week 7: The World is Chaotic

This week I have been largely working towards my final product draft 1. I explored more about the specifics regarding the different uses and applications of weather forecasting in various fields. I learned of the specifics of weather forecasting’s importance to agriculture. Anticipation of heatwaves allows farmers to change their irrigation schedules accordingly in order to maintain sufficient soil moisture and prevent heat stress in crops; anticipation of heavy rainfall allows farmers to delay plantation or harvest, intending to avoid seed washout, soil compaction, and spoilage of mature product. Wind predictions are also apparently useful for deciding when to spray pesticide and herbicide, with intention to lessen drift and optimize effectiveness. I also learned of the military use of meteorology; a subfield called military meteorology. Military meteorology is exactly what it sounds like – attempting to use the chaos of the natural world to one’s advantage. I never really considered that weather forecasting could be used for offensive action, but now I know.

In addition, I understood the butterfly effect. I knew before that it was when a small, seemingly insignificant event causes a much larger consequence as a result of little mishaps accumulating over time. In the context of my research, it would be in regards to how the AI-based and ML-based models struggle with long-term weather prediction because little relatively insignificant inaccuracies accumulate over a large time frame to provide us with large and very much significant inaccuracies. However, I now learned that the butterfly effect is the idea that a a distant butterfly flapping its wings creates a miniscule instability in the atmosphere, a miniscule instability which becomes a much larger instability. (side note, chaos theory is really interesting, and it’s great I have an excuse to use it.) The goal of the theory was to explain that weather can not be truly and wholly forecasted, due to the inherent chaos of the atmosphere. I suppose what forecast technology we have now and are trying to develop simply tries its best to forecast.