DeepAI AI Chat
Log In Sign Up

Video Prediction for Precipitation Nowcasting

07/18/2019
by   Yuan Cao, et al.
Copyrights
FUDAN University
7

Video prediction, which aims to synthesize new consecutive frames subsequent to an existing video. However, its performance suffers from uncertainty of the future. As a potential weather application for video prediction, short time precipitation nowcasting is a more challenging task than other ones as its uncertainty is highly influenced by temperature, atmospheric, wind, humidity and such like. To address this issue, we propose a star-bridge neural network (StarBriNet). Specifically, we first construct a simple yet effective star-shape information bridge for RNN to transfer features across time-steps. We also propose a novel loss function designed for precipitaion nowcasting task. Furthermore, we utilize group normalization to refine the predictive performance of our network. Experiments in a Moving-Digital dataset and a weather predicting dataset demonstrate that our model outperforms the state-of-the-art algorithms for video prediction and precipitation nowcasting, achieving satisfied weather forecasting performance.

READ FULL TEXT

page 3

page 10

page 12

03/01/2019

Frequency Domain Transformer Networks for Video Prediction

The task of video prediction is forecasting the next frames given some p...
05/19/2019

FORECAST-CLSTM: A New Convolutional LSTM Network for Cloudage Nowcasting

With the highly demand of large-scale and real-time weather service for ...
08/02/2022

A Novel Transformer Network with Shifted Window Cross-Attention for Spatiotemporal Weather Forecasting

Earth Observatory is a growing research area that can capitalize on the ...
05/24/2021

Taylor saves for later: disentanglement for video prediction using Taylor representation

Video prediction is a challenging task with wide application prospects i...
01/25/2018

Visual Weather Temperature Prediction

In this paper, we attempt to employ convolutional recurrent neural netwo...
03/28/2023

Forecasting localized weather impacts on vegetation as seen from space with meteo-guided video prediction

We present a novel approach for modeling vegetation response to weather ...