• Title/Summary/Keyword: 천정방향 대류권 습윤지연

Search Result 2, Processing Time 0.017 seconds

Estimation of GNSS Zenith Tropospheric Wet Delay Using Deep Learning (딥러닝 기반 GNSS 천정방향 대류권 습윤지연 추정 연구)

  • Lim, Soo-Hyeon;Bae, Tae-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.39 no.1
    • /
    • pp.23-28
    • /
    • 2021
  • Data analysis research using deep learning has recently been studied in various field. In this paper, we conduct a GNSS (Global Navigation Satellite System)-based meteorological study applying deep learning by estimating the ZWD (Zenith tropospheric Wet Delay) through MLP (Multi-Layer Perceptron) and LSTM (Long Short-Term Memory) models. Deep learning models were trained with meteorological data and ZWD which is estimated using zenith tropospheric total delay and dry delay. We apply meteorological data not used for learning to the learned model to estimate ZWD with centimeter-level RMSE (Root Mean Square Error) in both models. It is necessary to analyze the GNSS data from coastal areas together and increase time resolution in order to estimate ZWD in various situations.

GPS PWV Variation Research During the Progress of a Typhoon RUSA (태풍 RUSA의 진행에 따른 GPS PWV 변화량 연구)

  • 송동섭;윤홍식;서애숙
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.21 no.1
    • /
    • pp.9-17
    • /
    • 2003
  • Typhoon RUSA, which caused serious damage was passed over in Korea peninsula during 30 August to 1 September, 2002. We estimated tropospheric wet delay using GPS data and meteorological data during this period. Integrated Water Vapor(IWV) gives the total amount of water vapor from tropospheric wet delay and Precipitable Water Vapor(PWV) is calculated the IWV scaled by the density of water. We obtained GPS PWV at 13th GPS permanent stations(Seoul, Wonju. Seosan, Sangju, Junju, Cheongju, Taegu, Wuljin, Jinju, Daejeon, Mokpo, Sokcho, Jeju). We retrieve GPS data hourly and use Gipsy-Oasis II software and we compare PWV and precipitation. GPS observed PWV time series demonstrate that PWV is, in general, high before and during the occurrence of the typhoon RUSA, and low after the typhoon RUSA. GPS PWV peak time at each station is related to the progress of a typhoon RUSA. We got very near result as we compare GMS Satellite image with tomograph using GPS PWV and we could present practical use possibility by numerical model for weather forecast.