HackerPapers

arXiv:1905.09932cs.CV

Precipitation Nowcasting with Satellite Imagery

Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Precipitation nowcasting is a short-range forecast of rain/snow (up to 2 hours), often displayed on top of the geographical map by the weather service. Modern precipitation nowcasting algorithms rely on the extrapolation of observations by ground-based radars via optical flow techniques or neural network models. Dependent on these radars, typical nowcasting is limited to the regions around their locations. We have developed a method for precipitation nowcasting based on geostationary satellite imagery and incorporated the resulting data into the Yandex.Weather precipitation map (including an alerting service with push notifications for products in the Yandex ecosystem), thus expanding its coverage and paving the way to a truly global nowcasting service.

arXiv comments
Final KDD 2019 version
Journal reference
in Proceedings of The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2019
DOI
doi:10.1145/3292500.3330762
Subjects
cs.CVComputer Vision and Pattern Recognition

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Nov 2023 to Nov 2023.

Comments linking this paper, per year.

Discussed in comments1 thread

  1. GraphCast: AI model for weather forecasting 1 comment

    • My understanding is that they just use an AI-based precipitation nowcast (see [1]). Very different forecast/modeling problem than GraphCast. [1]: https://arxiv.org/abs/1905.09932

      countersView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.