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Rainfall nowcasting on France using the DGMR model from Google Deepmind

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Rainfall Nowcasting in France using the DGMR Model

This repository applies the pre-trained Deep Generative Model of Rainfall (DGMR) developed by Google DeepMind to Meteo-France rainfall data. The goal of this project is to provide real-time, high-quality short-term rainfall forecasts (nowcasting) for France.

Example forecast

Table of Contents

Features

  • Download radar data through the Meteo-France public data API
  • Short-term rainfall forecasting: max lead time 2h, timestep 5min, resolution 1km
  • Utilizes the DGMR pre-trained (UK data) model for realistic forecasts
  • Visualizations of rainfall predictions with GIFs

Installation

Clone the Repository

git clone https://github.com/meteofrance/dgmr
cd dgmr

Install Environment

With micromamba or conda:

micromamba create -f environment.yml
micromamba activate dgmr

Create the API Key on Météo-France's Portal

If you don't already have an account on the Météo-France Public Data portal, please create one.

  1. Once connected, subscribe to the Radar data API (not the "Radar Package" one).

  2. Then click on Configure the API.

  3. Select API Key as the token type, enter the duration (in seconds), and Generate Token.

  4. Copy the token; you will need it in the next step.

Download the Pretrained Model from DeepMind

Go to this Google Cloud Storage link and download the whole folder dm-nowcasting-example-data/tfhub_snapshots/1536x1280 (this folder contains the pre-trained model with a size of 1536x1280).

Note that the AI model is licensed under Creative Commons BY 4.0.

Set Up Environment Variables

Create a .env file in the root directory and add your configuration settings:

METEO_FRANCE_API_KEY="<your_meteo_france_api_key>"
METEO_FRANCE_DATA_PATH="<path_to_save_the_downloaded_data>"
DGMR_MODEL_PATH="<path_to_the_pretrained_dgmr_folder>/1536x1280/"
DGMR_PLOT_PATH="<path_to_save_the_plots>"

If METEO_FRANCE_DATA_PATH is empty, downloaded data will be saved in ./data.

If DGMR_PLOT_PATH is empty, forecast GIFs will be saved in ./plot.

Usage

Downloading Data with Meteo-France's API

Simply run the script ./dgmr/download_data.sh to download the latest radar images.

Setting up a Cron Job for Automated Data Download

For real-time forecasting, we need to download the radar data every 5 minutes.

To automate the data downloading process using a cron job, follow these steps:

  1. Open your terminal and type crontab -e to edit the cron table.

  2. Add a new line at the end of the file to define the cron job. The general syntax for a cron task is:

    */5 * * * * <ABSOLUTE_PATH_TO_REPO>/dgmr/download_data.sh

Making Forecasts

To make a real-time rainfall nowcast, use:

python main.py

This script expects that you have already downloaded the 4 latest radar images.

It saves the forecast as a GIF in the plot folder defined by the DGMR_PLOT_PATH env variable.

Data Sources

This project uses rainfall data from Meteo-France.

The H5 files contain 5-minute cumulated rainfall data over France, with a 500m resolution.

To match the pre-trained model inputs, we convert the data to instantaneous rainfall (mm/h) and downgrade the resolution to 1km.

Model Architecture

The DGMR model is a state-of-the-art generative model designed for weather nowcasting. It leverages a combination of convolutional neural networks (CNNs) and generative adversarial networks (GANs) to produce high-resolution, realistic rainfall forecasts.

For more details, please see Ravuri, S., Lenc, K., Willson, M. et al. Skilful precipitation nowcasting using deep generative models of radar. Nature 597, 672–677 (2021).

A notebook is also available as a supplement to the article: notebook.

The DGMR model is under the terms of the Creative Commons Attribution 4.0 International License.

Licenses

Contributors

  • From Météo-France's AI Lab: Théo Tournier, Léa Berthomier, Frank Guibert, Bruno Pradel
  • From the French National School of Meteorology: Flora Chapelle, Hugo Germain, Paul Lacotte & Ariadna Perello

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