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Precipitaion Nowcasting using Deep Neural Network

arXiv 2203.13263 ↗First posted 24 Mar 2022cs.LG cs.AIcited by 0

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Abstract (arXiv)

Precipitation nowcasting is of great importance for weather forecast users, for activities ranging from outdoor activities and sports competitions to airport traffic management. In contrast to long-term precipitation forecasts which are traditionally obtained from numerical models, precipitation nowcasting needs to be very fast. It is therefore more challenging to obtain because of this time constraint. Recently, many machine learning based methods had been proposed. We propose the use three popular deep learning models (U-net, ConvLSTM and SVG-LP) trained on two-dimensional precipitation maps for precipitation nowcasting. We proposed an algorithm for patch extraction to obtain high resolution precipitation maps. We proposed a loss function to solve the blurry image issue and to reduce the influence of zero value pixels in precipitation maps.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 39 references that are in the map. First posted on arXiv 24 Mar 2022.

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14 of 39 references.

References · 14

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2016Xception: Deep Learning with Depthwise Separable Convolutionscited by 2,320
  4. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,428
  5. 2014Striving for Simplicity: The All Convolutional Netcited by 983
  6. 2018Stochastic Video Generation with a Learned Priorcited by 244
  7. 2017Deep Learning for Precipitation Nowcasting: A Benchmark and A New Modelcited by 180
  8. 2015Delving Deeper into Convolutional Networks for Learning Video Representationscited by 146
  9. 2018PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learningcited by 122
  10. 2020SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecturecited by 71
  11. 2019Machine Learning for Precipitation Nowcasting from Radar Imagescited by 56
  12. 2020TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfallcited by 19
2 more
  1. 2019Distributed Deep Learning for Precipitation Nowcastingcited by 6
  2. 2019Precipitation nowcasting using a stochastic variational frame predictor with learned prior distributioncited by 4

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