Deep generative nowcasting: Nature publication

Rachel Prudden
Met Office Informatics Lab
1 min readOct 1, 2021
Rainfall nowcasting. Image from the paper showing overview of results from different models.

We are happy to announce that our collaboration with Google DeepMind on applying deep learning techniques to precipitation nowcasting has now been published in Nature.

Skilful precipitation nowcasting using deep generative models of radar

This work has been made possible by leveraging a broad range of expertise from across the Met Office, from Operational Meteorology through Data Engineering, from User Experience researchers to Earth scientists, statistical scientists and many more. This diverse team was paired with Deep Learning and Machine Learning expertise from Google DeepMind to create a highly multidisciplinary team to deliver this groundbreaking research. The paper builds on our earlier review paper in which we summarise the emerging field combining Machine Learning and precipitation nowcasting.

A review of radar-based nowcasting of precipitation and applicable machine learning techniques (arXiv)

We are excited to have been able to contribute to this emerging field, and look forward to continuing to drive forward Environmental Intelligence research, exploring the intersection between machine learning and the Earth sciences.

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Rachel Prudden
Met Office Informatics Lab

Rachel is a researcher in the Informatics Lab. Her current focus is on probabilistic super-resolution of weather models at convective scales.