skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [1];  [4];  [4]
  1. Department of Civil and Environmental Engineering, Center for Hydrometeorology and Remote Sensing, University of California, Irvine CA USA
  2. Department of Civil and Environmental Engineering, Center for Hydrometeorology and Remote Sensing, University of California, Irvine CA USA, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman OK USA
  3. Department of Civil and Environmental Engineering, Center for Hydrometeorology and Remote Sensing, University of California, Irvine CA USA, Center for Excellence for Ocean Engineering, National Taiwan Ocean University, Keelung Taiwan
  4. China Institute of Water Resources and Hydropower Research, Beijing China
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1482741
Grant/Contract Number:  
IA0000018
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Name: Journal of Geophysical Research: Atmospheres; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English

Citation Formats

Akbari Asanjan, Ata, Yang, Tiantian, Hsu, Kuolin, Sorooshian, Soroosh, Lin, Junqiang, and Peng, Qidong. Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks. United States: N. p., 2018. Web. doi:10.1029/2018JD028375.
Akbari Asanjan, Ata, Yang, Tiantian, Hsu, Kuolin, Sorooshian, Soroosh, Lin, Junqiang, & Peng, Qidong. Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks. United States. doi:10.1029/2018JD028375.
Akbari Asanjan, Ata, Yang, Tiantian, Hsu, Kuolin, Sorooshian, Soroosh, Lin, Junqiang, and Peng, Qidong. Mon . "Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks". United States. doi:10.1029/2018JD028375.
@article{osti_1482741,
title = {Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks},
author = {Akbari Asanjan, Ata and Yang, Tiantian and Hsu, Kuolin and Sorooshian, Soroosh and Lin, Junqiang and Peng, Qidong},
abstractNote = {},
doi = {10.1029/2018JD028375},
journal = {Journal of Geophysical Research: Atmospheres},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 19 00:00:00 EST 2018},
month = {Mon Nov 19 00:00:00 EST 2018}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on November 19, 2019
Publisher's Accepted Manuscript

Save / Share: