Research on Prediction of Heavy Rainfall Based on BDS-2/3

With the rapid development of Global Navigation Satellite System (GNSS), the application of GNSS atmospheric inversion technology in the meteorological field has received widespread attention. It has the characteristics of all-weather continuous observation, wide coverage, high accuracy and resolution. Firstly, five different observation stations in Hong Kong were selected for the calculation and analysis of the Precision of Precipitable Water Vapor (PWV) inversion using Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) observation data, the results show that the RMSE of PWV retrieved by GPS, BDS2 and BDS-2/3 are 2.36 mm,4.17 mm and 3.02 mm. Secondly, By calculating the PWV values of five different observation stations in Hong Kong during the 2020 rainy season and analyzing the characteristics of PWV changes during heavy rainfall, the results show that when the PWV value starts to increase from a lower value and the rate of PWV change continues to increase to 1.08 mm/h, heavy rainfall may occur within 12 hours. The PWV sequence and other related parameters obtained from the BDS-2/3 data inversion of five Hong Kong CORS stations were used as prediction factors for the heavy rainfall threshold model. After obtaining the optimal threshold, the heavy rainfall was predicted. The results showed that the CSI (Critical Success Index) of the six-factor threshold prediction model was 82.5%, POD (Probability of Detection) was 92.1%, and PAR (False Alarm Rate) was 11.2%, which was 21.6% higher than the traditional three-factor model in terms of comprehensive evaluation indicators. This provides valuable references for the application of PWV in short-term heavy rainfall forecasting, disaster prevention, and mitigation in related meteorological services. It also further demonstrates the enormous potential of BDS-2/3-based atmospheric precipitable water vapor inversion technology in short-term heavy rainfall forecasting.

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Publication Details

Journal
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Published
2024-10-09
DOI
https://doi.org/10.33012/2024.19860
Primary Topic
Advanced Technologies in Various Fields
Type
article
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article

Research on Prediction of Heavy Rainfall Based on BDS-2/3

Hang Guo, Qun Tian, Ting Ni, Sai Du et al.
1 links
Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
Advanced Technologies in Various Fields
article

Research on Prediction of Heavy Rainfall Based on BDS-2/3

Hang Guo, Qun Tian, Ting Ni, Sai Du, Wenjing Kong, Min Yu, Xiong Jian, Longfei Lv
article en

Abstract

With the rapid development of Global Navigation Satellite System (GNSS), the application of GNSS atmospheric inversion technology in the meteorological field has received widespread attention. It has the characteristics of all-weather continuous observation, wide coverage, high accuracy and resolution. Firstly, five different observation stations in Hong Kong were selected for the calculation and analysis of the Precision of Precipitable Water Vapor (PWV) inversion using Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) observation data, the results show that the RMSE of PWV retrieved by GPS, BDS2 and BDS-2/3 are 2.36 mm,4.17 mm and 3.02 mm. Secondly, By calculating the PWV values of five different observation stations in Hong Kong during the 2020 rainy season and analyzing the characteristics of PWV changes during heavy rainfall, the results show that when the PWV value starts to increase from a lower value and the rate of PWV change continues to increase to 1.08 mm/h, heavy rainfall may occur within 12 hours. The PWV sequence and other related parameters obtained from the BDS-2/3 data inversion of five Hong Kong CORS stations were used as prediction factors for the heavy rainfall threshold model. After obtaining the optimal threshold, the heavy rainfall was predicted. The results showed that the CSI (Critical Success Index) of the six-factor threshold prediction model was 82.5%, POD (Probability of Detection) was 92.1%, and PAR (False Alarm Rate) was 11.2%, which was 21.6% higher than the traditional three-factor model in terms of comprehensive evaluation indicators. This provides valuable references for the application of PWV in short-term heavy rainfall forecasting, disaster prevention, and mitigation in related meteorological services. It also further demonstrates the enormous potential of BDS-2/3-based atmospheric precipitable water vapor inversion technology in short-term heavy rainfall forecasting.

Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
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Advanced Technologies in Various Fields
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