As a bike commuter and with all the snow in the news, I had an itch I had to scratch: How cold has this winter been compared to previous years?

Shown are 3 cities for my home state of California: San Francisco, Los Angeles, and San Diego. All values are daily low temperature reported at the location.

-Green is this winter season (ok, Autumn too).

-Black and shaded gray are fitted quartiles. Like the min/max values, the discrete view is less than helpful.

-Red and blue are observed min/max over the data period.

Nits: I didn't want to end up with a line plot for non-continuous data, but daily data for the year ends up being too dense for something like points, bars, etc. What points of interest deserve labels without being too cluttered?

data source: Iowa State Mesonet

tools: Python, matplotlib in Jupyter Notebook source

fun!

wherever the green line matches or exceeds a record, maybe circle or dot that spot.

Since we’re in February 2023 now, I’m confused if the green “winter ‘22” means that the green in January is actually January ‘23? If that’s true, it seems like it would make more sense to start June at the left. If the green data is “2022,” then it would make more sense to label it “2022” not “winter 2022” and just have it go all year.

It’d be even more telling to see the daily avg & median plotted against the current year’s data, or last few years avg & median

It would be interesting to look at a metric for beta/volatility. The mean may be largely unchanged vs historical norms, but it feels like the swings are significantly more dynamic than when I was a kid.

Confusing when it wraps around the right to the left of the graph. Should make it continuous

I would love to see the last few years in different colors!

May be a bit misleading, thinking "all ok we're within normal range". Would be interesting to see if the max values tend to be more recent than the min values.