I agree that if you don't like getting 5 sigma events against your model's forecast, sure, change your model. But I'm curious whether the model in question is

I agree that if you don't like getting 5 sigma events against your model's forecast, sure, change your model. But I'm curious whether the model in question is even looking at 5-day events, or more at monthly/annual/decadal averages. This may not be 5 sigma at all at those timescales. And, it sure looks like it's not headed to a new mean 5 degrees Fahrenheit higher: https://www.timeanddate.com/weather/antarctica/vostok-station/historic?month=3&year=2022 https://www.timeanddate.com/weather/antarctica/vostok-statio... Please don't get me wrong. Human-generated greenhouse gas emission increase and carbonization of the planet's atmosphere are big problems, that will contribute to overall global temperature average rises. It's just that this is not that. This is more like when the CPU spikes momentarily by +50% on your production observability monitors. Panicky teams might react to it. Mature teams might see it as transient cloud (heh) behavior and know not to even bother alerting. Immature teams will tune it out as alert fatigue. We don't want to give the whole planet alert fatigue about extreme weather events. We want to focus on reducing the long run change to global average temperature.