WeatherNext 2 data now in Earth Engine, BigQuery; Vertex AI early access opens
Google just pushed its newest forecasting engine out of the lab and into production-grade tools, and that move could shake up how we pull weather signals into our pipelines. The model, WeatherNext 2, gets billed as the company’s most advanced forecast effort, but the real twist is its home inside Earth Engine and BigQuery, two services already humming with massive geospatial and analytics workloads. In practice, analysts can now ask for hyper-local predictions right from a familiar SQL-like console, while satellite-data scientists seem able to mash those forecasts together with imagery in a single workspace.
There’s also an early-access program on Vertex AI that promises custom inference, so teams could fine-tune the model for niche use cases, though it’s still unclear how broadly that will roll out. By slipping WeatherNext tech into Search, Gemini and Pixel Weather, Google appears to be nudging richer meteorological insight into both consumer and enterprise products. The details follow.
WeatherNext 2's forecast data is now available in Earth Engine and BigQuery. We're also launching an early access program on Google Cloud's Vertex AI platform for custom model inference. By incorporating WeatherNext technology, we've now upgraded weather forecasts in Search, Gemini, Pixel Weather and Google Maps Platform's Weather API.
In the coming weeks, it will also help power weather information in Google Maps. Predicting more possible scenarios From a single input, we use independently trained neural networks and inject noise in function space to create coherent variability in weather forecast predictions. Weather predictions need to capture the full range of possibilities -- including worst case scenarios, which are the most important to plan for.
WeatherNext 2 can predict hundreds of possible weather outcomes from a single starting point.
Will developers take up the new data streams? WeatherNext 2 shows up boasting an eight-fold jump in forecast speed, and Google has already pushed the output into Earth Engine and BigQuery. The early-access Vertex AI program says it can do custom inference, but right now it’s only open to a handful of partners.
By slipping the model into Search, Gemini and Pixel Weather, Google seems to be nudging higher-resolution predictions into the tools we use every day. Still, the piece doesn’t give us any third-party benchmarks, so it’s hard to say how much the speed gain will matter in practice. Companies that live on Google Cloud might find the built-in datasets a nice shortcut for their pipelines; others will have to weigh the unknown migration cost.
The announcement talks about efficiency, yet it leaves out details on energy use or model size. As the service rolls out, teams will have to test whether the promised gains actually help logistics, aviation or even your commute. Until we see broader usage numbers, the real benefit of WeatherNext 2 stays a question.
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Common Questions Answered
What new services now host WeatherNext 2 forecast data?
WeatherNext 2 forecast data is now available in Google Earth Engine and BigQuery. These platforms enable analysts to query and integrate high‑resolution weather signals directly into existing geospatial and analytics workflows.
How does the early‑access Vertex AI program extend WeatherNext 2 capabilities?
The early‑access program on Google Cloud's Vertex AI allows select partners to run custom inference using WeatherNext 2 models. This enables developers to tailor forecast generation to specific applications, though the program remains limited to a small group of participants.
Which Google products have already incorporated WeatherNext 2 technology?
Google has integrated WeatherNext 2 into Search, Gemini, Pixel Weather, and the Google Maps Platform Weather API. In the coming weeks, the model will also enhance weather information displayed within Google Maps.
What performance claim does Google make about WeatherNext 2 forecast generation?
Google claims that WeatherNext 2 can generate forecasts up to eight times faster than its predecessor. This speed improvement is intended to deliver more timely and detailed weather predictions across Google services.