Teaser

Take a look at our amazing teaser!

The dataset

The dataset contains full time series of satellite and radar images, weather models and ground observations.
To keep the dataset at a reasonable size, the data covers two geographic areas of 550km x 550km on the Mediterranean and Brittany coasts, and spans over 3 years, 2016 to 2018.

We have prepared this free dataset to let the data science community play with it.
Explore it today!

Als Scan - Gina Gerson Masturbation And Be Ther... -

Introduction

The episode’s mix of data‑driven analysis and personal storytelling makes it highly shareable on Instagram Stories, TikTok reels, and LinkedIn articles—expanding reach beyond the traditional podcast sphere. Als Scan - Gina Gerson Masturbation And Be Ther...

Gina Gerson: Born Valentina Dzherson in 1991, she is a former adult performer from Russia who gained significant popularity in the industry. Transition to Mainstream Hosts: Gina Gerson (fashion veteran) & Be Ther

Conclusion

Gina Gerson's appearance on "Als Scan" has given us a deeper understanding of her life, talent, and personality. As we continue to follow her journey, we're excited to see where her passion for entertainment takes her. The world of lifestyle and entertainment is constantly evolving, and we're eager to explore more stories, trends, and insights. Stay tuned for more updates on Gina Gerson and the latest happenings in the world of entertainment! AI‑driven mood lighting

Some notable aspects of this scan include:

Hosts: Gina Gerson (fashion veteran) & Be Ther (wellness‑coach/analyst).

Key Topics: Sustainable fashion rentals, AI‑driven mood lighting, micro‑meditations, rise of audio‑only TV.

Takeaways: 1) Try a circular‑wardrobe service (e.g., ReViva). 2) Experiment with smart lighting that syncs to biometric data. 3) Practice a 2‑minute breath reset daily. 4) Keep an eye on audio‑only scripted series as a new entertainment frontier.

Strengths: Engaging host chemistry, solid research, high production quality, actionable content.

Weaknesses: Slightly long tech demo, merch plug timing, lack of guest voices, surface‑level pop‑culture analysis.

New to MeteoNet? Check out our Toolbox!

Have a look at our toolbox which includes data samples from MeteoNet written in python language and our tutorials/documentation which help you explore and cross-check all data types.

Get MeteoNet Toolbox

Download Area

This dataset is yours to explore!

Play with it and if you send us your results, we could showcase them on this website!

Download MeteoNet

Kaggle

The data are also available on Kaggle with notebooks to help you explore and cross-check all data types!
You can contribute to challenges and/or propose yours!
Time series prediction
Rainfall nowcasting
Cloud cover nowcasting
Observation data correction
...etc

Kaggle page Tutorial

The community's work

Featured projects

You did something interesting with our dataset? Want your project to be showcased here?
Write a blog, contact us on GitHub, and we will come back to you!

Your project here!

How did you use MeteoNet?

Support

Need help? Checkout our documentation, post an issue on our GitHub repository or go to our Slack workspace!

Documentation GitHub Slack

Other data

Other data from METEO FRANCE

You can find other data on METEO FRANCE public data website. It features real-time, past and forecast data: in situ observations, radar observations, numerical weather models, climate data, climate forecasts and much more!

Licence

The Dataset is licenced by METEO FRANCE under Etalab Open Licence 2.0.

Reuse of the dataset is free, subject to an acknowledgement of authorship. For example:
"METEO FRANCE - Original data downloaded from https://meteonet.umr-cnrm.fr/, updated on 30 January 2020".

When using this dataset in a publication, please cite:
Gwennaëlle Larvor, Léa Berthomier, Vincent Chabot, Brice Le Pape, Bruno Pradel, Lior Perez. MeteoNet, an open reference weather dataset by METEO FRANCE, 2020