WeatherNext 3

Weather 2 doesn't seem to have been an ensemble model. Weather 3 is, so theoretically it can get more accurate outcomes by taking the probabilistic analysis of several models concurrently to determine the most likely weather conditions.

I'm building a tool right now that uses an ensemble to determine wind gust likelihood, which is useful for safety critical work on construction sites and the like.

The Google daily and hourly forecasts aren't great, but the weather map forecast is excellent. Where does that come from? What's generating the predicted movement of the storm clouds?

Same experience.

As a former Googler, I wouldn't at all be surprised if this is an integration that is "planned" -- but just not done yet.

And some good handful of people are planning to wring a promo out of work. "Implemented weather UI in Android that is 63% more accurate." ;)

I see the same sentiment any time any weather app is posted. Especially when Dark Sky comes up

Same experience. I moved to Windy and I just look at the weather radar and make my own prediction.

I guesstimate that it has less than 50% accuracy for my area

Dark Sky is still one of my all time favorite app. The accuracy of the forecast within the coming hour is to this day unmatched. It constantly reminded me of Back to the Future 2, where Doc says the rain will stop in “in exactly 5 seconds”

The only forecasted rainfall for local areas within a very short timeframe. This made it possible to utilize simple factors to predict the near future.

It is built into Apple Weather after Apple purchased them.

I disagree.. Feels very sloppy to me:

- Time is UTC rather than local by default.

- Units are imperial rather than metric (i.e. not basing it on users locale)

- The concept of init time is not initially clear at all, so it's confusing when you click the calendar icon to see the weather forecast for a future date only to see it isn't an option, you have to use the slider.

- When changing the sidebar to the "detailed" view, most of the hovering element is cut off by the container so you can't actually read it.

And it took longer to write this comment than it did to find these issues. It's fine since it's clearly marked as experimental, but I disagree that it's "really easy to use" :p

I'm not seeing that kind of demo. I just see a video, a bunch of future-tense words about what could be done by someone, and the requisite hype.

Link?

edit: The link for the demo is as thus, https://deepmind.google.com/science/weatherlab

I searched a bit and seems like the answer is no besides this web app https://deepmind.google.com/science/weatherlab

> WeatherNext 3 will power weather features in Google Search, the Gemini app and Google Maps, as well as the Google Maps Weather API and Google Earth Engine.

https://dataconomy.com/2026/09/04/weathernext-3-ai-forecasts...

So I assume the main way would be googling "weather Los Angeles" and it will be powered by the WeatherNext 3 models

They also open sourced the last one and are doing B2B/enterprise arrangements so maybe other weather apps are experimenting with it.

Last time they have only shipped the model on web in mobile...

I agree but this seems like a demo for the underlying data set. The data is the product and they want to sell or use it downstream.

Why should they be such a boon? High-resolution, regional NWP with fast refresh has been a standard tool for over a decade.

A few weather forecast sites in Europe have them on their websites. It's just another forecast you can select and compare in an ensemble.

Problem is that the WN3 grid is still quite rough (5km) - but a that's a brutal improvement for many places compared to many other global models.

Quite a few country-scale models go down to a 1-2km grid nowadays. This is very helpful in complex geography like mountains and alleys.

We'll put that link in the toptext as well. Thanks!