WeatherNext forecasts on BigQuery

This page provides an overview of how to access and use WeatherNext forecasts in Google BigQuery. BigQuery is a serverless, highly scalable data warehouse that lets you analyze petabytes of data using standard SQL. It is an excellent choice for:

  • Large-scale data analysis: Run complex analytical SQL queries on the entire WeatherNext dataset without worrying about infrastructure.
  • Custom data integration: Easily join WeatherNext forecasts with your own datasets, such as business locations or sensor data, for deeper insights.
  • Scalable machine learning: Use BigQuery ML to train, evaluate, and run machine learning models directly on the weather data.

Available datasets

WeatherNext provides its state-of-the-art weather forecasting models as public datasets in BigQuery, available through the Analytics Hub.

How to access the data

To access the datasets, you will need to fill out the WeatherNext Data Request form.

To query the data, you first need to add the datasets to your BigQuery project from the Analytics Hub listings linked above. Click "Add dataset to project" to subscribe.

When subscribing, you have to set a project name and a dataset name. After which, you can query the tables using those fully qualified names as follows:

WeatherNext Graph: [your project name].[your dataset name].59572747_4_0

WeatherNext Gen: [your project name].[your dataset name].126478713_1_0

WeatherNext 2: [your project name].[your dataset name].weathernext_2_0_0

Starter guide and sample code

For an in-depth tutorial and sample code, check out the WeatherNext 2 Starter Guide - BigQuery notebook.

Things to be aware of

Terms of use

Citations

If you use this data in your research, be sure to cite the appropriate papers and datasets. You can find the citation information on the dataset pages.