Unless I misunderstood what you said, that’s not it either. 50% chance of rain means exactly that: according to their forecast models, there is a 50% change it will rain. Snopes did a writeup of this.
Reading Snopes will give you plenty. Read the articles - and a lot of them use weasel-wording to push the result they want.
I don’t have the exact article on hand at the moment, but an example would be someone claiming that clear-cutting 1000 acres of trees would destroy [X]^3 of CO2 reduction; and then Snopes will “fact check” it by saying they aren’t cutting down 1000 acres of trees this year. Often times they’ll ‘debunk’ something that sounds like the claim, but isn’t the actual claim.
The statement “there’s a 40% chance of rain at any given point at any given time in the forecast area/period” is an average over both area and time.
Many different actual distributions of rain could result in that average, including a 100% chance of it raining 100% of the time in 40% of the are or a 40% chance of it raining in 100% of the time in 100% of the area, and a 100% chance of it raining 40% of the time in 100% of the area. Real distributions are typically messier than that.
For one thing, there’s two competing weather services providing the data to countless apps in the US and one of them has more money to throw around than the other.
The weather channel has better weather predictions overall than Apple’s own weather app, as rated by Forecastadvisor.com, but is not as accurate as Accuweather is although it’s used in more apps.
Weather is about tracking and predictions. It’s never going to be completely 100% correct. But taking a hodgepodge of information from several prediction services means you’re more likely to be less accurate overall despite what people may think.
If all the private company weather services were only getting their info from the NOAA we wouldn’t have such varying results most of the time. Which is basically my point. The results vary because they don’t just use the NOAA’s data and predictions. The second one is actually the US Armed Forces.
Building MakeMKV seems to require a binary, which is unfree. I assume this is the reason it’s not in official distribution repos (except Nix and FreeBSD).
It’s in the AUR and Nixpkgs, both automate building it from “source” (+binary). MakeMKV is in FreeBSDs official repos, according to pkgs.org.
Darksky could do it back in the day more or less. you’d get messages that it would rain in about 15 minutes and stop in the next 30.
Thing is, precep maps don’t work everywhere. You’re probably in a location like me where a thick front rolling through will almost always bring rain. If you get into warmer tropical climates, rainclouds will just poof out of nowhere and drop rain on your ass while other crazy fronts will pass over with nothing but some dark clouds.
I can't really describe to you how angry I was when that shit went through. Like... I knew it was ridiculous to get so angry but, I LOVED THAT FREAKING APP.
Oh, yeah. Not only did they take it away from all Android users, they also killed the API that let other apps access it. I wrote an open-source tool that made Dark Sky data available to Wear OS watch faces. It worked beautifully for several years, until Apple killed it.
The worst of it is that was my second attempt. An earlier version of the same tool worked with Weather Underground data. Then IBM bought it, changed the API completely, and priced it so that only business could afford it.
I haven’t had the heart to try a third time.
Sorry, every once in a while I’m overcome with the need to whine about it.
Weather apps don’t do real time analytics, but show you the forecast some nearby weather station has calculated. Whether that’s based on current data or a couple hours ago depends on the exact provider they use. And hardly anyone of those are done by actual humans, it’s aggregated statistics.
If you look at precipitation maps, you are doing that forecast by yourself based on cloud movements and local knowledge, something no machine-generated forecast can do as good.
Plus, there’s usually one weather station covering a large area, so hyperaccurate predictions would have to be made just for you - which simply costs to much.
Nearby is so highly dependent on where exactly those are located, and what they’re connected to (some are handled by local volunteers that have hardware that reports periodically as opposed to being operated by an agency directly). Various apps don’t all connect to the same data sources.
Official reporting locations may not actually be close to you and weather can be highly localized. A mile can make a massive difference in weather in some regions, and the official recording location for the city is 10 miles away.
I had family from out of town calling me once because the nstional news was reporting the entire area was hit with heavy storms and tornados. The city isn’t even more then 15 minutes down the interstate, but we didn’t get a single drop of rain.
I once experienced a storm where, for a very brief time, my front yard was experiencing a torrential downpour and my back yard was dry as a bone.
My house was not that big - maybe 1700-1800sq ft - and our lot size was less than a quarter acre. Blew my mind. (Obviously storms have edges. It was still weird.)
Sounds like the system is just stuck on old tech. If I can tell that rain will reach my area from a precipitation radar map then I’m fairly certain an ML based system can do this too.
You’ve already received some great suggestions. Another one is Netdata. Personally, I use glances to collect the data and Home Assistant to display the dashboard. But I only do this because I already had Home Assistant running.
I’m getting to the later stages of Jedi: Fallen Order, and bought the ‘Pixels with a Porpoise’ bundle on Humble Bundle, so I’m looking a several weeks of pixelated fantasy fun, I think.
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