YanTian: An Application Platform for AI Global Weather Forecasting Models
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Abstract (arXiv)
To promote the practical application of AI Global Weather Forecasting Models (AIGWFM), we have developed an adaptable application platform named 'YanTian'. This platform enhances existing open-source AIGWFM with a suite of capability-enhancing modules and is constructed by a "loosely coupled" plug-in architecture. The goal of 'YanTian' is to address the limitations of current open-source AIGWFM in operational application, including improving local forecast accuracy, providing spatial high-resolution forecasts, increasing density of forecast intervals, and generating diverse products with the provision of AIGC capabilities. 'YianTian' also provides a simple, visualized user interface, allowing meteorologists easily access both basic and extended capabilities of the platform by simply configuring the platform UI. Users do not need to possess the complex artificial intelligence knowledge and the coding techniques. Additionally, 'YianTian' can be deployed on a PC with GPUs. We hope 'YianTian' can facilitate the operational widespread adoption of AIGWFMs.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 13 references that are in the map. First posted on arXiv 6 Oct 2024.
Builds on
8 of 13 references.
References · 8
- 2022FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operatorscited by 748
- 2022GraphCast: Learning skillful medium-range global weather forecastingcited by 261
- 2023FuXi: A cascade machine learning forecasting system for 15-day global weather forecastcited by 237
- 2023Deep Learning for Day Forecasts from Sparse Observationscited by 70
- 2023FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion modelcited by 22
- 2023Towards an end-to-end artificial intelligence driven global weather forecasting systemcited by 20
- 2021Creating synthetic night-time visible-light meteorological satellite images using the GAN methodcited by 2
- 2023The Compatibility between the Pangu Weather Forecasting Model and Meteorological Operational Datacited by 2
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Citing papers per year: 2026: 1.
1 paper.