News

GRAiCE: reconstructing terrestrial water storage anomalies with recurrent neural networks

Climate change : nature.com subject feeds · last updated

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Palazzoli, I., Ceola, S. & Gentine, P. GRAiCE: reconstructing terrestrial water storage anomalies with recurrent neural networks. Sci Data 12, 146 (2025). https://doi.org/10.1038/s41597-025-04403-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41597-025-04403-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

View full article

here today, more tomorrow

We’ve launched briefing.center with a focus on the press and media.

And we’ve added Citizen Cartwright, a daily quick-read news summary by veteran Washington journalist Linda Cartwright. We’ve also created a new voting rights knowledge center for Citizen Cartwright subscribers. (You can sign up for a dedicated morning email at citizencartwright.com.)

You can sign up here for full access to press and media and Citizen Cartwright on briefing.center.

You can use briefing.center as the center of your information management, or just one of your tools. We’re happy to discuss your information needs.

Sign up