{"id":51212,"date":"2026-03-10T21:34:16","date_gmt":"2026-03-11T01:34:16","guid":{"rendered":"https:\/\/mjtsai.com\/blog\/?p=51212"},"modified":"2026-03-10T21:34:53","modified_gmt":"2026-03-11T01:34:53","slug":"acme-weather-1-0","status":"publish","type":"post","link":"https:\/\/mjtsai.com\/blog\/2026\/03\/10\/acme-weather-1-0\/","title":{"rendered":"Acme Weather 1.0"},"content":{"rendered":"

Adam Grossman<\/a>:<\/p>\n

\n

Fifteen years ago, we started work on the Dark Sky weather app.<\/p>\n

[…]<\/p>\n

We enjoyed our time at Apple. So why did we leave to start another weather company?<\/p>\n

It’s simple: when looking at the landscape of the countless weather apps out there, many of them lovely, we found ourselves feeling unsatisfied.<\/p>\n

[…]<\/p>\n

Our homegrown forecasts are produced using many different data sources, including numerical weather prediction models, satellite data, ground station observations, and radar data. Most of the time, our forecast will be a reliable source of information (it’s better than the one we had at Dark Sky). But, crucially, we supplement the main forecast with a spread of alternate predictions. These are additional forecast lines that capture a range of alternate possible outcomes[…]<\/p>\n<\/blockquote>\n\n

The main two things I want, which previous apps didn’t provide, are an easy way to see different predictions for the same location (since there can be huge variance, e.g. in the number of inches of snow) and different locations at the same future time (to help decide where I should go). This tries to address the first half, though it doesn’t seem to give a range of alternate predictions for the amount<\/em> of snow, only the likelihood of precipitation and its subjective intensity.<\/p>\n\n

John Voorhees<\/a>:<\/p>\n

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If you see widely separated lines, there’s a greater chance that conditions will vary from what Acme’s model expects, whereas a tight cluster of lines gives you greater confidence as you walk out the door.<\/p>\n

[…]<\/p>\n

Beneath the hourly conditions graph, Acme displays a horizontally scrolling list of weather stats. Swiping between them repopulates the graph with whichever forecast metric you want. It’s a lot of data, and it’s all accessible without scrolling vertically or switching views, which I love. Also, when precipitation is on its way, the app displays an additional graph with minute-by-minute details for the upcoming hour.<\/p>\n

[…]<\/p>\n

Acme Weather includes an unusual emphasis on notifications, too. Instead of relegating the feature to the app’s settings, Acme dedicates an entire tab to it. In a world of notification overload, that’s a bold move, but it works. That’s because Acme puts its users in the driver’s seat, offering fine-grained control over the notifications you receive.<\/p>\n<\/blockquote>\n\n

Chance Miller<\/a>:<\/p>\n

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What strikes me most about the app is how well it takes large amounts of information and distills that into an interface that is actually readable.<\/p>\n<\/blockquote>\n\n

cornchip<\/a>:<\/p>\n

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I’ve thought before that I’d like error ranges in weather graphs. Alternative predictions aren’t quite how I’d imagined it. Showing some detail\/personality\/confidence level for the alternative prediction lines might help. This might also be solved by time with the app to learn how surprising the weather turns out to be when predictions were divergent.<\/p>\n

Cumulative precipitation could use another dimension to the data to show either soon-ness in the next 24 hours or how short of a time period is predicted to deliver most of the rainfall. That’s a hard data visualization problem.<\/p>\n<\/blockquote>\n\n

Previously:<\/p>\n