A Three-dimensional Convolutional-Recurrent Network for Convective Storm Nowcasting

by   Wei Zhang, et al.

Very short-term convective storm forecasting, termed nowcasting, has long been an important issue and has attracted substantial interest. Existing nowcasting methods rely principally on radar images and are limited in terms of nowcasting storm initiation and growth. Real-time re-analysis of meteorological data supplied by numerical models provides valuable information about three-dimensional (3D), atmospheric, boundary layer thermal dynamics, such as temperature and wind. To mine such data, we here develop a convolution-recurrent, hybrid deep-learning method with the following characteristics: (1) the use of cell-based oversampling to increase the number of training samples; this mitigates the class imbalance issue; (2) the use of both raw 3D radar data and 3D meteorological data re-analyzed via multi-source 3D convolution without any need for handcraft feature engineering; and (3) the stacking of convolutional neural networks on a long short-term memory encoder/decoder that learns the spatiotemporal patterns of convective processes. Experimental results demonstrated that our method performs better than other extrapolation methods. Qualitative analysis yielded encouraging nowcasting results.


page 3

page 4

page 10

page 11


Convolutional Neural Network for Convective Storm Nowcasting Using 3D Doppler Weather Radar Data

Convective storms are one of the severe weather hazards found during the...

Research on Data Fusion Algorithm Based on Deep Learning in Target Tracking

Aiming at the limitation that deep long and short-term memory network(DL...

Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting

High-frequency trading requires fast data processing without information...

Long Short-Term Memory-Networks for Machine Reading

In this paper we address the question of how to render sequence-level ne...

Radar-based Feature Design and Multiclass Classification for Road User Recognition

The classification of individual traffic participants is a complex task,...

Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach

Reliable 4D aircraft trajectory prediction, whether in a real-time setti...

Discovering outliers in the Mars Express thermal power consumption patterns

The Mars Express (MEX) spacecraft has been orbiting Mars since 2004. The...

Please sign up or login with your details

Forgot password? Click here to reset