Skilful precipitation nowcasting using deep generative models of radar

S Ravuri, K Lenc, M Willson, D Kangin, R Lam… - Nature, 2021 - nature.com
Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours
ahead, supports the real-world socioeconomic needs of many sectors reliant on weather …

NowCasting-Nets: Representation learning to mitigate latency gap of satellite precipitation products using convolutional and recurrent neural networks

MR Ehsani, A Zarei, HV Gupta… - … on Geoscience and …, 2022 - ieeexplore.ieee.org
Accurate and timely estimation of precipitation is critical for issuing hazard warnings (eg, for
flash floods or landslides). Current remotely sensed precipitation products have a few hours …

Precipitation nowcasting with orographic enhanced stacked generalization: Improving deep learning predictions on extreme events

G Franch, D Nerini, M Pendesini, L Coviello, G Jurman… - Atmosphere, 2020 - mdpi.com
One of the most crucial applications of radar-based precipitation nowcasting systems is the
short-term forecast of extreme rainfall events such as flash floods and severe thunderstorms …

Skillful radar-based heavy rainfall nowcasting using task-segmented generative adversarial network

R Wang, L Su, WK Wong, AKH Lau… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate and timely rainfall nowcasting is important for protecting the public from heavy
rainfall-induced disasters. In recent years, deep-learning models have been demonstrated …

Experimental study on generative adversarial network for precipitation nowcasting

C Luo, X Li, Y Ye, S Feng, MK Ng - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Precipitation nowcasting is an important task, which can be used in numerous applications.
The key challenge of the task lies in radar echo map prediction. Previous studies leverage …

EfficientRainNet: Leveraging EfficientNetV2 for memory-efficient rainfall nowcasting

M Sit, BC Seo, B Demiray, I Demir - Environmental Modelling & Software, 2024 - Elsevier
Rainfall nowcasting is critical for timely weather predictions and emergency responses,
particularly in flood-prone areas. Existing models, while accurate, often require substantial …

LPT-QPN: A lightweight physics-informed transformer for quantitative precipitation nowcasting

D Li, K Deng, D Zhang, Y Liu, H Leng… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Quantitative precipitation nowcasting (QPN) is a highly challenging task in weather
forecasting. The ability to provide precise, immediate, and detailed QPN products is …

Nowcasting-Nets: Deep neural network structures for precipitation nowcasting using IMERG

MR Ehsani, A Zarei, HV Gupta, K Barnard… - arXiv preprint arXiv …, 2021 - arxiv.org
Accurate and timely estimation of precipitation is critical for issuing hazard warnings (eg, for
flash floods or landslides). Current remotely sensed precipitation products have a few hours …

A spatio-temporal neural network for fine-scale wind field nowcasting based on lidar observation

H Gao, C Shen, Y Zhou, X Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Fine-scale wind field nowcasting is of great significance in air traffic management, power
grid operation, and so on. In this article, an indirect wind field nowcasting scheme based on …

A spatio-temporal graph-guided convolutional LSTM for tropical cyclones precipitation nowcasting

X Yang, F Zhang, P Sun, X Li, Z Du, R Liu - Applied Soft Computing, 2022 - Elsevier
Real-time and accurate Tropical Cyclone (TC) precipitation nowcasting plays an important
role in disaster prevention and mitigation. The strong ability of deep learning has been …