Smoke predictions in San Francisco have reported with a footnote stating that due to limitations of weather prediction models they cannot accurately predict whether smoke would remain elevated above the city, or come down to ground level.
It makes sense from consideration of model development that only the most important parameter features would be included. Important meaning shows a statistically significant impact on what the weather would be on a given day in the future. Smoke is a rare event thus there is less data available to dial in on. Location and severity of the blaze need to be considered.
A rapid development team could cobble together a model enhancement, but the accuracy would be pretty low improving over time.
In short, shitty models, shitty data in the shitty models, shitty people putting shitty data in shitty models. When it's shitty across the board you don't even get a footnote explaining why predictions may be inaccurate.
Smoke predictions in San Francisco have reported with a footnote stating that due to limitations of weather prediction models they cannot accurately predict whether smoke would remain elevated above the city, or come down to ground level.
It makes sense from consideration of model development that only the most important parameter features would be included. Important meaning shows a statistically significant impact on what the weather would be on a given day in the future. Smoke is a rare event thus there is less data available to dial in on. Location and severity of the blaze need to be considered.
A rapid development team could cobble together a model enhancement, but the accuracy would be pretty low improving over time.
In short, shitty models, shitty data in the shitty models, shitty people putting shitty data in shitty models. When it's shitty across the board you don't even get a footnote explaining why predictions may be inaccurate.