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Spatiotemporal Enhanced Adversarial Network for Precipitation Nowcasting
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPrecipitation nowcasting is a critical aspect of meteorological services, which helps people make reasonable arrangements. Nowadays the methods based on recurrent neural networks are widely employed as the primary solution for precipitation nowcasting ...
Yunlong Zhou +5 more
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Enhancing Rainfall Nowcasting Using Generative Deep Learning Model with Multi-Temporal Optical Flow
Remote Sensing, 2023 Precipitation nowcasting is critical for preventing damage to human life and the economy. Radar echo tracking methods such as optical flow algorithms have been widely employed for precipitation nowcasting because they can track precipitation motions well.
Ji-Hoon Ha, Hyesook Lee
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暴雨灾害, 2022 How to integrate effectively the synoptic characteristics of severe precipitation events based on the experience of forecasters that is not constrained by physical formulas into the deep learning model as a priori information is one of the important ...
Yaping ZHANG +4 more
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Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains [PDF]
Geoscientific Model Development, 2022 Numerical weather prediction models and probabilistic extrapolation methods using radar images have been widely used for precipitation nowcasting. Recently, machine-learning-based precipitation nowcasting models have also been actively developed for ...
S. Choi, Y. Kim
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Quantifying the Location Error of Precipitation Nowcasts [PDF]
Advances in Meteorology, 2020 In precipitation nowcasting, it is common to track the motion of precipitation in a sequence of weather radar images and to extrapolate this motion into the future. The total error of such a prediction consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time.
Arthur Costa Tomaz de Souza +2 more
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Multi‐task framework of precipitation nowcasting
CAAI Transactions on Intelligence Technology, 2023 Abstract Precipitation forecasting plays an important role in disaster warning, agricultural production, and other fields. To solve this issue, some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall distributions.
Zheng Zhang 0046 +4 more
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Precipitation Nowcasting with Satellite Imagery [PDF]
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019 Final KDD 2019 ...
Vadim Lebedev +8 more
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暴雨灾害, 2021 By using network radar, national gridded real-time observation datasets and the hourly precipitation observation data at the automatic weather stations in the Yangtze River Basin, the radar extrapolation precipitation forecast product of the Yangtze ...
Gang TIAN +3 more
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Distributed Deep Learning for Precipitation Nowcasting [PDF]
2019 IEEE High Performance Extreme Computing Conference (HPEC), 2019 IEEE HPEC ...
Siddharth Samsi +2 more
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Nowcasting of rainfall based on extrapolation and evolution algorithms. Preliminary results [PDF]
Acta Scientiarum Polonorum. Formatio Circumiectus, 2018 Forecasts from nowcasting models are increasingly becoming a crucial input to the rainfall-runoff models. A basic approach to the nowcast generation is based on extrapolation (advection) of current precipitation field.
Mateusz Giszterowicz +2 more
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