Current forecasting models are calculated through the use of general circulation models. These climate models, according to the National Oceanic and Atmospheric Administration, “use mathematical equations to characterize how energy and matter interact in different parts of the ocean, atmosphere, land. Building and running a climate model is a complex process of identifying and quantifying Earth system processes, representing them with mathematical equations, setting variables to represent initial conditions and subsequent changes in climate forcing, and repeatedly solving the equations using powerful supercomputers.”
The problem is that this system, while useful for compiling data, falls short in the areas of “simulating atmospheric variables quickly at very short time scales, or accurately at long time scales,” notes one UCLA study.
As such, those in the tech segment are investing heavily in exploring artificial intelligence options, especially as climate change ramps up. As more extreme weather patterns emerge, so too does the need for faster, more accurate prediction of possible destruction.