No, not even close. You were probably lucky to get one-degree accuracy, if that.
This is one of the first red flags that I noted when I started paying closer attention to climate-related stuff about 15 or 20 years ago. I did a little digging, and it turns out that there is a mathematical theorem (I forget the name of it) that allows you to do things like this (derive a higher level of accuracy than the data would otherwise allow) if you know for a fact that the associated errors pretty much all cancel out. But you have to know this, from prior sampling or whatever; you can't just assume it. But that's what these folks are doing - waving their hands and just assuming that the errors mostly cancel out.
To add insult to injury, for other portions of the data they state that they have the right to make routine, automated adjustments because of systematic errors in the data. But you can't have it both ways - assuming that the errors mostly cancel out on the one hand, while on the other hand claiming you have the right to make adjustments because, you know, those errors don't actually cancel each other out after all.
> I'm not questioning the data per se
You should be! Most of the "data" here is either of remarkably low quality, or just pretty much made up.