Warm Oceans Turned a 3-Inch Forecast into a Record NYC Blizzard
https://umbrellatoday.app/blog/202602-nyc-blizzard-warm-oceans- If I play roulette in a casino today, I might win big, break even, lose a little or lose a lot. If I play roulette in a casino every day for a decade, I can be nearly certain I will lose a lot.
- Consider an ant walking on a rough stone road built up the side of a hill. If you look at the ant at any particular second, its body might be pointing up (head higher than tail) or down (vice versa) or level, depending on what particular angle of rock it's on at that time. But measured over minutes its likely to be at a greater altitude above sea level than where it started. Measured over the hours it takes to get from the bottom to the top, it's definitely higher.
- A random day of the year (pick from 1-365) in England might be sunny or rainy, but the chances of it being sunnier are higher if the day picked is in the summer.
The point is that there's a tremendous amount of noise in short-term measurements which tend to smooth out over longer term where trends are more clearly revealed. That's the counterpoint to your argument and the reason why climate prediction is not the same as weather forecasting. Going back to the casino analogy, climate prediction is looking at your bank balance over decades; weather forecasting is deciding how to bet on a particular poker hand.
(And finally, we actually kind of do mostly know what's going to happen tomorrow, but not a week out; that's not the point you're making though.)
Weather may or may not be random. It could be entirely deterministic for all we know. However, we lack the ability to fully model all the factors that contribute to weather and therefore our predictions are inaccurate.
Now let’s consider long term climate predications. Do you think these predictions are more like coin flips, where we have an extremely accurate model of the process, or more like weather, where unknown unknowns have outsized impact on accuracy?
That’s not to say climate change isn’t real, but your analogy doesn’t make sense.
"Unknown unknowns" aren't the reason weather forecasts are inaccurate.
Weather is path-dependent. Small changes to starting conditions or minor differences between modeled and actual conditions shortly after the simulation begins lead to large differences by the end of the simulation. Errors propagate and magnify.
Over large time periods the errors average out.
Weather forecasts are generally accurate about 90% of the time for a five-day forecast and around 80% for a seven-day forecast. Forecasts beyond ten days are only correct about half the time.