I still miss Dark Sky. Nothing I’ve tried works as well, and Apple’s Weather app is one of the worst. I know they said they would integrate Dark Sky into their own app, but I’m not seeing it. I live in a small mountain town with considerable elevation changes, so I know it’s challenging to predict the weather, but I grew to trust Dark Sky and I’m still bummed it’s gone.
“They” say that Dark Sky was unscientific. It didn’t predict local weather so much as it tracked the weather. It would look at radar, identify precipitation, and calculate when it would arrive at my location. It was great. I only use the Apple Weather widget to display the temperature. When I need to know the weather I use Windy
I was watching the Buffalo Bills game on TV last night. Before the game I looked at the Apple Weather app and it didn’t predict any snow until after the game was over. Then after it started snowing, I’d keep looking at it and it would say “snow stopping in 10 minutes” or “snow stopping in 20 minutes”. It snowed the entire game 3+ hours! What a joke that it can’t even figure out the weather for the next hour??!!
Buffalo winter weather is extremely localized thanks to Lake Effect. If you were looking at the forecast for the city of Buffalo, it was probably correct - there was minimal snow downtown and the airport (where many official weather reports originate) is 12 miles north of the stadium and 8 miles NE of downtown. The stadium may as well be in the next area code over as far as weather is concerned.
The only way to get accurate weather reports and predictions for that region is to follow the local meteorologists and check out their detailed maps. Something working at the macro level, like Apple Weather, is not going to give you the local detail.
If we had a Time Machine (thanks Apple auto-correct for capitalizing that for me), we could try looking at the Orchard Park forecast and see if that’s any better.
I have not experienced any major gotchas with any of the weather apps I use, which are BBC Weather, MetOffice, OpenWeatherMap, and Apple Weather maybe this is because my location is the UK rather than US. There are minor occasional differences between the four or five, if you count me looking out the window, but generally there is agreement especially between those that include rain radar graphics.
I was looking at the Orchard Park forecast.
I use the Swiss Weather Service app and it’s pretty darn accurate. I use it to avoid rain showers when deciding what’s the best time to walk the dog, for instance.
Moreover, they share the data with Apple, AFAIK, so the Apple weather app is also accurate.
Good for those few who, like myself, live in Switzerland, that is. 
All weather radar in the UK is run by the Met Office. Others (including Apple) buy that data, but it means that “nowcasting” rainfall and radar maps are pretty much identical whichever app you use.
General forecasting is much more diverse. Everyone starts with the same data (in terms of current conditions) but some forecasters use MUCH more data (and much more local) than others. Then there are multiple computer models applied to the current data to make forecasts.
The UK Met Office has by far the most extensive sensor network, and the best computer models for the UK and the biggest supercomputers to run them, followed very closely by the major European models (e.g. ECWMF). Unfortunately, the Met Office was subjected to “free market” ideology which made it into a commercial operator in an artificially created competitive market rather than a government agency. If you pay for the best forecasts (e.g as aviation does) they are remarkably accurate and reliable (at least for the next 48 hours) but increasingly broadcasters and app makers are buying forecasts from whichever weather company convinces them to do so (and price is often involved). We all used to get the best forecasts for free via our taxes.
One alternative is to use an app like Windy that allows you to choose a whole variety of forecasts in the same app.
I may be really lucky, but Apple Weather is usually spot on for me. I live in southern Europe so that may be a factor. Whenever it says it’s going to rain in the morning, it’s right - for me at least - and I always check about 12 hours in advance (the night before). We don’t see much fluctuations though (there is blue sky 90% of the year) so I imagine it’s more challenging is less stable climates.
I’m curious, did anyone read the article and agree with its claims? Or are we all just commenting on how accurate weather apps are?
I’m guessing the article’s main point is that predicting the weather is tough, but also location dependent?
I didn’t read it because it’s behind a paywall and there was no context about what it’s saying provided.
I’d like to read it but it’s paywalled.
@RunningBoris @Alevyinroc and anyone else who hasn’t read the original piece because of a paywall it was picked up by various news agencies/papers. A quick DuckDuckGo search should find a non-paywalled rewrite. (In the UK I recall seeing similar pieces in The Guardian and on BBC News.)
Here is an AI summary of the article. The summary seems accurate as I did read the article.
Weather apps on smartphones often provide inaccurate forecasts, leading to inconveniences like unexpected rain and, in severe cases, posing safety risks. Despite technological advancements, several factors contribute to these inaccuracies:
Complexity of Weather Systems: Weather forecasting involves analyzing vast amounts of data from sources like satellites and ocean buoys. Global models, such as those from U.S. and European agencies, process this data to predict weather patterns. However, the atmosphere’s inherent unpredictability and reliance on historical patterns can result in errors, especially when weather systems behave unexpectedly.
Microclimates and Geographic Variations: Areas with microclimates, such as San Francisco, or regions with significant elevation changes, present challenges for models that divide the globe into grids. For instance, the American model spaces grid points 18 miles apart, which can overlook localized weather variations, leading to less accurate forecasts in those areas.
Interpretation by Weather Apps: Weather apps simplify complex model outputs into user-friendly icons and summaries. This simplification can lead to discrepancies; one app might display a partly cloudy icon, while another shows rain for the same forecast period. Additionally, the accuracy of predictions decreases for longer-term forecasts, with a seven-day forecast being about 80% accurate, dropping to 50% at ten days.
Impact of Climate Change: The increasing frequency of extreme weather events due to climate change complicates forecasting. Models often struggle with predicting these outliers, making it challenging to provide accurate forecasts during such events.
Improving Forecast Accuracy: To enhance the reliability of weather information:
• Consult Multiple Sources: Using various weather apps can provide a broader perspective. Tools like ForecastAdvisor rank the accuracy of services based on location, helping users identify the most reliable options.
• Focus on Short-Term Forecasts: Short-term predictions, especially those within three days, tend to be more accurate than longer-range forecasts.
• Utilize Radar and Human Expertise: Engaging with radar apps and seeking insights from human meteorologists can offer a deeper understanding of imminent weather conditions.
• Understand Probability Metrics: Clarifying terms like “chance of rain” is crucial. A 30% chance indicates there’s a 30% likelihood of at least 0.01 inches of rain in the specified area, not that it will rain over 30% of the area.By adopting these practices, users can better navigate the limitations of weather apps and make more informed decisions regarding weather-related plans.
As per @Glimfeather recommendation, various other places have published it, some are still paywalled, others are not. MSN’s is not paywalled.
The relevant part of the article:
Weather models’ predictions are partly based on historical patterns. So when weather systems move unexpectedly, forecasts can change.
We don’t have perfect knowledge of the atmosphere,” said Eric Floehr, founder of ForecastWatch, which is a company that assesses weather-app accuracy.
Models don’t do as well in areas with microclimates, distinctive weather patterns that vary between neighborhoods in places like San Francisco. They also struggle with large changes in elevation, such as mountain towns.
The location your app uses (either zip code or city) might be an issue. Where zip codes are huge—like 89049 in Nevada, which covers some 10,000 square miles—typing in the city might produce a better result, Floehr said.
Climate change makes the task more complex, forecasters say. Models have trouble predicting extreme weather outliers. “Those extremes seem to be occurring more frequently,” Floehr said, pointing to what are called thousand-year events, such as recent, deadly floods in Valencia, Spain.
I’d bet on weather reports being generated for increasingly precise locations. The 18 mile or whole zip code reporting points will feel archaic.
Moving to more precise forecasts will raise a lot of questions, though. E.g., when four blocks down, there’s a 2% higher chance of rain, and you two get the same rainstorm or don’t, that’s not going to be well understood.
Accuracy at those points will continue to increase slowly aside from windfalls like gaining access to orders of magnitude more computing power or something wild like generally useful weather data from Mars. 
Right now, if you need the very best forecast information, IMO you need to pick the forecast model that is best for your location.
The website windy.com and app is free, an annual subscription to Windy Pro is $19/year.
CORRECTION: I just noticed the price of Windy.com Pro went up a couple of years ago to $24.99
Windy is a great app. As simple or as complicated as you want it to be. I often find myself going in and looking at different overlays and it’s pretty cool to watch during storms. Still, when I want quick and easy I use Weather or Weather Strip.
+1
I use the radar 1 hour forecast feature to see how fast precipitation is approaching.
As I reflect upon this thread, it occurs to me that over the years, I’ve come to realize that I don’t need precise weather forecasts. I only need a good, general “in the ballpark” forecast that helps me decide if I need a coat, sweater, or just a shirt. Or, in extreme cold, it helps me determine if I need to take precautions to prevent pipes from freezing. None of this requires the level of precision that some people desire or may need. I carry umbrellas in all my vehicles, the office, and at home. Regardless of whether it rains or not, or when it rains, I’m covered (pun intended 
). Would I prefer a precise weather forecast? I suppose so, but would it significantly impact my daily life? Probably not.
I’m not suggesting that what works for me is adequate for others. I’m simply sharing that as time goes on, I’ve become less concerned about the level of precision, as long as the forecast is “accurate enough.”