Coordinate-RNN for error correction on numerical weather prediction

Chanjong Yu, Heewoong Ahn, Junhee Seok

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    In this work, we present a coordinate-based Recurrent Neural Networks (RNN) for error correction on the Numerical Weather Prediction (NWP) model. We show that the output errors on NWP have spatial and temporal properties, which is collinear with meteorological data. The correction model reflects these characteristics by encompassing the latitude and longitude coordinates as direct inputs to RNN. Examined with the NWP data in Korea, the proposed RNN-based correction reduces the humidity prediction errors by 4.8% and 4.2% compared to the predictions without correction and with simple linear correction, respectively. The overall result highlights the promise of our approach.

    Original languageEnglish
    Title of host publicationInternational Conference on Electronics, Information and Communication, ICEIC 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-3
    Number of pages3
    ISBN (Electronic)9781538647547
    DOIs
    Publication statusPublished - 2018 Apr 2
    Event17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States
    Duration: 2018 Jan 242018 Jan 27

    Publication series

    NameInternational Conference on Electronics, Information and Communication, ICEIC 2018
    Volume2018-January

    Other

    Other17th International Conference on Electronics, Information and Communication, ICEIC 2018
    Country/TerritoryUnited States
    CityHonolulu
    Period18/1/2418/1/27

    Bibliographical note

    Funding Information:
    This work was supported by the National Research Foundation of Korea grant (NRF-2016R1D1A1B03931077, NRF-2017R1C1B2002850) as well as a grant from Korea Meteorological Administration.

    Publisher Copyright:
    © 2018 Institute of Electronics and Information Engineers.

    Keywords

    • Meteorological data
    • coordinates
    • error correction
    • numerical weather prediction model
    • recurrent neural network

    ASJC Scopus subject areas

    • Information Systems
    • Computer Networks and Communications
    • Computer Science Applications
    • Signal Processing
    • Electrical and Electronic Engineering

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