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WeatherNext 2: Our most advanced weather forecasting model

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Re: WeatherNext 2: Our most advanced weather forecasting model

#62
Googles weather prediction engine is already very good, and the new hurricane model was breathtakingly good this season when tested against actual hurricane paths. Meanwhile, the US Government Global Forecasting System continues to get worse.

https://arstechnica.com/science/2025/11/googles-new-weather-...

Re: WeatherNext 2: Our most advanced weather forecasting model

#63
post #7

Is anyone aware of good sources of higher resolution models? Hourly resolution like this model provides doesn’t help much now that energy markets have moved to 15-min and 5-min resolution.

Windy allows you to select your model. For that reason it's my go to for accuracy. Different models have different strengths, though. Some are shorter range (72h) or longer range (1-3 weeks). Some are higher resolution for where you live (the size of an area which it assigns a forecast to, so your forecast is more local). Some governments will have their own weather model for your country that is the most accurate fo…

Windy or Ventusky. Both really solid.

Re: WeatherNext 2: Our most advanced weather forecasting model

#64
post #38

Where can I use this? I’ve been trying to find hyperlocal forecasts like darksky used to be.

I never understood the acclaim for dark sky. It never seemed very accurate, and the forecasts changed so rapidly that they weren't of much use. "Rain for next 2 hours" would become "Intermittent rain for the next 30 minutes" 10 minutes later.

Re: WeatherNext 2: Our most advanced weather forecasting model

#65

Reminds me of a funny WWII story: Kenneth Arrow and his statisticians found that their long-range forecasts were no better than numbers pulled out of a hat. The forecasters agreed and asked their superiors to be relieved of this duty. The reply was: "The Commanding General is well aware that the forecasts are no good. However he needs them for planning purposes."

There is a fairly compelling argument that divination in the ancient world was not a useless waste of time, as is commonly assumed, but that having either a process or a person that can make essentially random choices for them allowed people to make hard, consequential decisions where they might otherwise be paralyzed, especially when the penalty for not acting was worse than making a mistake.

Re: WeatherNext 2: Our most advanced weather forecasting model

#66

I find it interesting that they quantify the improvement on speed and number of forecast-ed scenarios but lack details on how it results in improved accuracy of the forecast per: ``` WeatherNext 2 can generate forecasts 8x faster and with resolution up to 1-hour. This breakthrough is enabled by a new model that can provide hundreds of possible scenarios. ``` As an end user, all I care is that there's one accurate for…

For lay-users they could have explained that better. I think they may not have completely uninformed users in mind for this page though. Developing an ensemble of possible scenarios has been the central insight of weather forecasting since the 1960s when Edward Lorenz discovered that tiny differences in initial conditions can grow exponentially (the "butterfly effect"). Since they could really do it in the 90s, all c…

My understanding is that it's an expected value based on coverage in each of the ensemble scenarios, not quite as simplified as "how many scenarios was there rain in this forecast cell".

At least for the US NWS: if 30 of 100 scenarios result in 50% shower coverage, and 70 out of 100 result in 0%, this is reported as 15% chance of rain. Which is exactly the same as 15 with 100% coverage and 85 with 0% coverage, or 100 with 15% coverage.

Understanding this, and digging further into the forecast, gives a better sense of whether you're likely to encounter widespread rainfall or spotty rainfall in your local area.

Re: WeatherNext 2: Our most advanced weather forecasting model

#68

Reminds me of a funny WWII story: Kenneth Arrow and his statisticians found that their long-range forecasts were no better than numbers pulled out of a hat. The forecasters agreed and asked their superiors to be relieved of this duty. The reply was: "The Commanding General is well aware that the forecasts are no good. However he needs them for planning purposes."

There is a fairly compelling argument that divination in the ancient world was not a useless waste of time, as is commonly assumed, but that having either a process or a person that can make essentially random choices for them allowed people to make hard, consequential decisions where they might otherwise be paralyzed, especially when the penalty for not acting was worse than making a mistake.

Fascinating. I suppose it also encourages developing adaptable strategies that accommodate imperfect information, vs. succumbing to wishful thinking or other forms of cognitive bias.

Re: WeatherNext 2: Our most advanced weather forecasting model

#69

Earlier quoted context omitted.

I find that unlikely, my forecasts for much of Europe and East Asia have been consistently accurate.

How do DOGE implemented budget cuts affect European or East Asian forecasts? Those are not the forecasts that someone suspecting departmental DOGEing to be a fault.

But GP said they only USED TO blame DOGE, and blame Google now?

Re: WeatherNext 2: Our most advanced weather forecasting model

#70
post #45
post #39

Earlier quoted context omitted.

> We're now taking our research out of the lab and putting it into the hands of users. 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 Weathe…

Google Maps has... weather predictions?

If you want to accurately predict times for future trips, you need weather predictions.
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