Results 1 to 10 of about 659 (169)

Self-clustered GAN for precipitation nowcasting [PDF]

Scientific Reports
This paper proposes a novel GAN framework with self-clustering approach for precipitation nowcasting (ClusterCast). Previous studies have primarily captured the motion vector using only a single latent space, making the models difficult to adapt to ...
Sojung An, Tae-Jin Oh, Sang-Wook Kim, Jason J. Jung   +3 more
doaj   +4 more sources

Convcast: An embedded convolutional LSTM based architecture for precipitation nowcasting using satellite data. [PDF]

PLoS ONE, 2020
Nowcasting of precipitation is a difficult spatiotemporal task because of the non-uniform characterization of meteorological structures over time. Recently, convolutional LSTM has been shown to be successful in solving various complex spatiotemporal ...
Ashutosh Kumar, Tanvir Islam, Yoshihide Sekimoto, Chris Mattmann, Brian Wilson   +4 more
doaj   +2 more sources

A Novel Multi-Input Multi-Output Recurrent Neural Network Based on Multimodal Fusion and Spatiotemporal Prediction for 0–4 Hour Precipitation Nowcasting

Atmosphere, 2021
Multi-source meteorological data can reflect the development process of single meteorological elements from different angles. Making full use of multi-source meteorological data is an effective method to improve the performance of weather nowcasting. For
Jiping Guan, Wang Xiaodong
exaly   +3 more sources

Skilful nowcasting of extreme precipitation with NowcastNet [PDF]

Nature, 2023
AbstractExtreme precipitation is a considerable contributor to meteorological disasters and there is a great need to mitigate its socioeconomic effects through skilful nowcasting that has high resolution, long lead times and local details1–3. Current methods are subject to blur, dissipation, intensity or location errors, with physics-based numerical ...
Yuchen Zhang, Mingsheng Long, Kaiyuan Chen, Lanxiang Xing, Ronghua Jin, Michael I. Jordan, Jianmin Wang   +6 more
openaire   +3 more sources

Precipitation Nowcasting with Weather Radar Images and Deep Learning in São Paulo, Brasil

Atmosphere, 2020
Precipitation nowcasting can predict and alert for any possibility of abrupt weather changes which may cause both human and material risks. Most of the conventional nowcasting methods extrapolate weather radar echoes, but precipitation nowcasting is ...
SUZANNA Maria Bonnet, Alexandre G Evsukoff, CARLOS Augusto Morales Rodríguez   +2 more
exaly   +3 more sources

STVMamba: precipitation nowcasting with spatiotemporal prediction model [PDF]

Scientific Reports
A lightweight rainfall nowcasting model is required by Sichuan provincial meteorological bureaus. Deep learning methods such as recurrent, convolutional, and Transformer models have been applied to precipitation prediction. However, recurrent models struggle with suboptimal parallel computational efficiency and error accumulation, convolutional models ...
Zou, Maoyang, Wen, Longrui, Huang, Yuanyuan, He, Yuan, Xiao, Jingzhong   +4 more
openaire   +3 more sources

Precipitation nowcasting with radar data for evaluating multiple horizons using U-Net-based algorithm in Eastern Amazon. [PDF]

PLoS ONE
Severe meteorological events are increasingly frequent globally, with intense rainfall significantly impacting well-being, safety, and the economy, including agriculture and mining. Timely emergency alerts are crucial for mitigating losses and preventing
Rafael Rocha, Douglas Ferreira, Ewerton Oliveira, Helder Arruda, Sergio Viademonte, Ana Paula Paes, Edmir Jesus, Claudia Costa, Vania Franco, Ivan Saraiva, Renata Tedeschi, Antonio Nogueira, Ronnie Alves, Eduardo Carvalho   +13 more
doaj   +2 more sources

ThoR: A Motion-Dependent Physics-Informed Deep Learning Framework with Constraint-Centric Theory of Functional Connections for Rainfall Nowcasting [PDF]

Scientific Reports
Accurate precipitation nowcasting is crucial for mitigating the impacts of extreme weather, especially as climate change increases their frequency and severity.
Khang Ta Gia, Hoai Tran Van, An Phan Thanh, Nhat Phan Minh   +3 more
doaj   +2 more sources

Multi-Scale Fourier Temporal Network for Multi-Source Precipitation Nowcasting [PDF]

Sensors
Accurate precipitation nowcasting plays an important role in disaster prevention and hydrometeorological applications, yet it remains highly challenging due to the complex spatiotemporal variability and multi-scale structural characteristics of ...
Jing Huang, Shanmin Yang, Xiaojie Li, Xi Wu   +3 more
doaj   +2 more sources

LLMDiff: Diffusion Model Using Frozen LLM Transformers for Precipitation Nowcasting [PDF]

Sensors
Precipitation nowcasting, which involves the short-term, high-resolution prediction of rainfall, plays a crucial role in various real-world applications. In recent years, researchers have increasingly utilized deep learning-based methods in precipitation
Lei She, Chenghong Zhang, Xin Man, Jie Shao   +3 more
doaj   +2 more sources