> Support for the Dark Sky iOS app will end on December 31st, 2022, and support for the Dark Sky API will end on March 31st, 2023.
So basically them buying then closing the service to make their own seem better
* Climate change is causing problems with forecasting models
* Forecasting models changed, which has introduce unexpected edge cases
I'm not sure this happens on the time scale of 'app got acquired', though. It's absolutely going to increase year by year, and if you'd got used to how it was three years ago and didn't notice some of the outlier events, you might be shocked at the new normal.
Climate change absolutely will cause problems with any conceivable forecasting model because you can't encapsulate chaos, only map its expected potential outcomes: and the nasty truth is that energy is fed into the system, those potential outcomes blow up exponentially. Not even slightly linear. So that's what we're seeing.
So I'd not be surprised if they somehow switched their data source to be not as granular as it once was.
https://www.sciencedaily.com/releases/2020/07/200717101026.h...
While this is confirmation bias, this reflects almost identically with the timeframe in which the forecasts became significantly worse in my area.
As a former paid user of Dark Sky that lost that information when Apple bought them I feel no sympathy for iOS users that Dark Sky has gone to crap
I am sad such an amazing tool for the world was destroyed by a corporation trying to deprive another corporation so they could maybe make a little more money.
Honestly, that's about right here in Florida. :)
Agreed on the local-storage-for-health-data bit, but I'm sure they could argue that the ambient sensor isn't privacy-relevant.
Maybe they are they next to a window or under a sky light.
> or if they could use location data to figure out that 'this Apple Watch is in the middle of a large field, so he must be outside'.
Could be in a tent or other temporary structure.
Don't talk like that, its a self defeating mindset. You are likely as competent as most Apple engineers (the 10x benefit from less inhibitions and tons of energy.
The people working at apple are like most of us here, curious and driven. Apple has a lot of money to throw at people who bring in experience whereas you and I are individuals who do not work in the field of "figuring out where things are using computers." So we obviously are not experts in the field and not familiar with existing and emerging solutions for the problem.
Does Apple Watch have a light sensor for an auto dimming display? If so, that can be used as a proxy for indoor/outdoor. It isn't great, shade and such. Throw barometer in there, and you can do a decent job.
Microsoft Band had a UV sensor, so we were able to get pretty accurate detection of indoor/outdoor when combined with all the other sensors, at least during the day. I'm sad UV sensors didn't take off on smart watches in general, it is a super useful sensor to have, but they are rather large and even the lens material to go over them is different than what is otherwise required for a wearable.
Then, you still have to account for the fact that your thermometer is located right next to a variable ~100W heater, vs. normal weather stations that are normally located away from heat sources. Also, the thermometer and heater are occasionally placed inside a tight-fitting insulated container.
Its a shame that it is locked up inside of apple.
Second, it doesn't give you any additional readings over oceans, which is where the data is lacking in the current network of data.
It does give you more robust surface temperature readings in cloudy areas but that doesn't really help you predict the weather significantly better.
Source: degree in atmospheric sciences
Let’s pretend that data from user portable devices isn’t garbage (it is): then what do you even do with it? In cities you’ll have thousands of readings per voxel none of which are more valuable. Then you have to clean your data, excluding data from inside or vehicles or hot pavement or heated patios and so on. Apple won’t go to the expense of running their own GCM, and I doubt even mesoscale models. All I could see is some sort of correlative AI, doing microscale adjustments to government sponsored models. So all of this work, and maybe you get one degree better at forecasts and a bit of nowcasting. And because it isn’t physics-based, you might occasionally get something very wrong happening.
The oceans are a data hole (technical term, really) as you mentioned, but the real missing data is above the surface. It’s too bad about Project Loon, because that would have been much more helpful to forecasting than a million monkeys wearing watches.
Is there a really no use in having higher resolution for modeling the boundary layer?
It seems like having a mountain covered in tiny barometric and temp sensors could at least validate a lot of what we think we know about the boundary layer.
I personally would love to be able to see what the temperature at the bottom and top of a given topographic feature is, as well as how atmospheric pressure is deviating from pure altitude differences.
I build instruments for gliders so I know that the sensors in our phones are capable of incredibly fine resolution. Is there really no use for billions of high resolution data points in climate science?
Unless you're sick, most people's body temperature is within a fairly tight range.
So they could compensate for that ...
Or, ahem.... "cold winter evenings". ;-)
Air pressure on the other hand...