In forecasting Hurricane Isaias, meteorologists at the National Hurricane Center in Miami have shaped their predictions to closely match an AI hurricane model from Google DeepMind.
What are they used before then? Wasnt it before not just a lot of if … else … .chains or how the frick did they “predicted” it then before? (Okay maybe per hand, but still )
Physical models use physics based simulations to predict wind paths.
Think PV=nRT, Navier Stokes, Finite Element Analysis-type stuff. A mix of fundamental physical equations and simplified engineering math based on historical data.
Different simulations use different assumptions in the underlying models so they give different output.
The catch is there’s often orders of magnitude more variables at play than physical models are designed to utilize, which is where machine learning comes in super handy - drawing statistical inferences from millions of data points to provide a forecast based on statistics, not physics.
What are they used before then? Wasnt it before not just a lot of if … else … .chains or how the frick did they “predicted” it then before? (Okay maybe per hand, but still )
Physical models use physics based simulations to predict wind paths.
Think
PV=nRT, Navier Stokes, Finite Element Analysis-type stuff. A mix of fundamental physical equations and simplified engineering math based on historical data.Different simulations use different assumptions in the underlying models so they give different output.
The catch is there’s often orders of magnitude more variables at play than physical models are designed to utilize, which is where machine learning comes in super handy - drawing statistical inferences from millions of data points to provide a forecast based on statistics, not physics.