A Novel Multi-Input Multi-Output Recurrent Neural Network Based on Multimodal Fusion and Spatiotemporal Prediction for 0–4 Hour Precipitation Nowcasting [PDF]
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
Fuhan Zhang, Xiaodong Wang, Jiping Guan
exaly +4 more sources
Self-clustered GAN for precipitation nowcasting [PDF]
Scientific ReportsThis 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 +3 more
doaj +4 more sources
Precipitation Nowcasting with Weather Radar Images and Deep Learning in São Paulo, Brasil [PDF]
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 +2 more
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Spatiotemporal Feature Fusion Transformer for Precipitation Nowcasting via Feature Crossing [PDF]
Remote SensingPrecipitation nowcasting plays an important role in mitigating the damage caused by severe weather. The objective of precipitation nowcasting is to forecast the weather conditions 0–2 h ahead.
Hao Wang, Weiping Wang, He Jianxin
exaly +4 more sources
LLMDiff: Diffusion Model Using Frozen LLM Transformers for Precipitation Nowcasting [PDF]
SensorsPrecipitation 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 +3 more
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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 +4 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 ReportsAccurate precipitation nowcasting is crucial for mitigating the impacts of extreme weather, especially as climate change increases their frequency and severity.
Khang Ta Gia +3 more
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Precipitation nowcasting with radar data for evaluating multiple horizons using U-Net-based algorithm in Eastern Amazon. [PDF]
PLoS ONESevere 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 +13 more
doaj +2 more sources
Multi-Scale Fourier Temporal Network for Multi-Source Precipitation Nowcasting [PDF]
SensorsAccurate 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 +3 more
doaj +2 more sources
International Journal of Applied Earth Observation and GeoinformationDue to the rapidly changing climate conditions, precipitation nowcasting poses a daunting challenge because it is impossible to make accurate short-term forecasts due to the rapid fluctuations in weather conditions.
Xiaoding Wang +2 more
exaly +3 more sources