Blog 1: Forecasting Innovation and Bayesian Interference

This week it felt warmer outside. The forecast is for (mostly) warm weather in the coming week, which makes me grateful to have a forecast that gives me something to look forward to.

In recent forecast technology news, the Weather Research and Forecasting Innovation Reauthorization Act of 2026 was approved by the Senate Commerce Committee on March 4, 2026. This bill aims at updating NOAA’s weather forecasting capabilities, modernizing radar/satellite systems, and improving disaster warnings. One of the primary actions this legislation would take is integrating more artificial intelligence into existing weather systems. As a member of the weather-obsessed public, this legislation brings me joy (and also concern because why was improving forecast technology even up for debate, especially in places with extreme weather events (ie California)).

I have continued my background research. I learned that using something called Bayesian interference to understand weather conditions could be a good way to handle uncertainty (Jian et al 2021). Bayesian interference updates the probability of a hypothesis as more information is made accessible. It begins with a set belief (often called a “prior distribution”). It considers new probabilities as they are added and calculates an updated probability (Taboga 2021). Bayesian interference implements something called Bayes’ Rule which I still do not completely understand, but that’s okay. I’m still working on it and will get you all an update next week.

For now, enjoy the diagram from Wikipedia I consulted in an attempt to understand Bayes’ Rule.

By Cmglee – Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=143581610

Sun Jian, Cao Zhuo, Li Heng, et al. “Application of artificial intelligence technology to numerical weather prediction.” J Appl Meteor Sci, 2021, 32(1): 1-11. DOI: 10.11898/1001-7313.20210101.

Taboga, Marco (2021). “Bayesian inference”, Lectures on probability theory and mathematical statistics. Kindle Direct Publishing. Online appendix. https://www.statlect.com/fundamentals-of-statistics/Bayesian-inference.