Google DeepMind and Google Research a Weather Forecast Model Family

Google WeatherNext.

Research forecasts and published datasets from Google

4.33 / 5Directory score
Official website

WeatherNext gives access to a set of model predictions. For analysis, you can select a variable, a point, a release time and a horizon, then check the options.

Official Google DeepMind repository with WeatherNext materials
The official Google DeepMind repository with WeatherNext materials. Open the source

Compare predictions for one moment

For a point on the map, you can open two WeatherNext releases and get different values for the same hour. First, write down the time of each release, the predicted moment and the variable. The comparison is useful only after checking the units and geographical reference. In the ensemble, several options describe the possible development of weather. The scatter helps to see the uncertainty of the model, which one number on the screen hides.

Training analysis of one place

Choose a location and a variable available in both forecast runs. Save values from the ensemble members. Inspect their central value and spread, then repeat for another forecast horizon. Compare a forecast with an observation from a compatible source when one is available. Keep local and universal time distinct and compare like periods. Accumulated precipitation, for example, depends on the interval length.

What to write next to the schedule

Record the dataset, time, and sampling method. If one forecast run is missing, leave a gap and explain it. Access and costs vary by platform, so begin with a small extract. Use the chart to study model behavior. For decisions that rely on severe weather warnings, consult the official warning source. Google describes a different purpose for WeatherNext. Keep links to both sources alongside the chart.

Suitable tasks

  • Compare forecast releases for one point
  • See the spread of forecasts within the ensemble
Features

Strengths

  • Google publishes data with several forecast options
  • There are official guides on access to the kits
Things to consider

Limitations

  • For comparison, you need to agree on units and time coordinates
  • The model forecast does not replace the official warnings

Selection and conditions

Free access
Not confirmed
Trial period
Not confirmed
No sign-up required
Not confirmed
Russian interface
Not confirmed
Local installation
Not confirmed
API
Yes

“Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms.

Input formats
Data
Result
Data, Table

Terms

The cost of the request and processing depends on the selected infrastructure and the conditions for its use. Check the limitations of a specific set and service. For comparison, you need to agree on units and time coordinates.

From task to first result

Practical example

Task
Compare forecast releases for one point
What to prepare
One training point, weather variable and multiple saved WeatherNext releases.

Task brief or prompt

Compare the forecast for the same period from different issues. Show the centrality and dispersion of ensemble members in the same units.

Expected result

Checkable table with release time, horizon and set of values.

How to check the result

  • Check the time zone and units.
  • Do not mix the different variables and horizons.

An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted.

Check details

Official sources

  1. WeatherNext official page from Google DeepMind
  2. WeatherNext Access Documentation

This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use.