Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy
This study utilizes a low-cost Global Navigation Satellite System (GNSS) buoy platform, combined with multi-system GNSS data, to investigate the impact of GNSS signal quality and multipath effects on the accuracy of atmospheric precipitable water vapor (PWV) retrievals. It also explores the methods...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/9/1630 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850278496235945984 |
|---|---|
| author | Maosheng Zhou Pengcheng Wang Zelu Ji Yunzhou Li Dingfeng Yu Zengzhou Hao Min Li Delu Pan |
| author_facet | Maosheng Zhou Pengcheng Wang Zelu Ji Yunzhou Li Dingfeng Yu Zengzhou Hao Min Li Delu Pan |
| author_sort | Maosheng Zhou |
| collection | DOAJ |
| description | This study utilizes a low-cost Global Navigation Satellite System (GNSS) buoy platform, combined with multi-system GNSS data, to investigate the impact of GNSS signal quality and multipath effects on the accuracy of atmospheric precipitable water vapor (PWV) retrievals. It also explores the methods for oceanic rainfall event forecasting and precipitation prediction based on GNSS-PWV. By analyzing the data quality from various GNSS systems and using the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 dataset as a reference, the study assesses the accuracy of PWV retrievals in dynamic marine environments. The results show that the GNSS-derived PWV from the buoy platform is highly consistent with ERA5 data in both trend and characteristics, with an RMSE of 3.8 mm for the difference between GNSS-derived PWV and ERA5 PWV. To enhance rainfall forecasting accuracy, a balanced threshold selection (BTS) method is proposed, significantly improving the balance between the probability of detection (POD) and false alarm rate (FAR). Furthermore, a Random Forest model based on multiple meteorological parameters optimizes precipitation forecasting, especially in reducing false alarms. Additionally, a particle swarm optimization (PSO)-based BP Neural Network model for rainfall prediction achieves high precision, with an R<sup>2</sup> of 97.8%, an average absolute error of 0.08 mm, and an RMSE of 0.1 mm. The findings demonstrate the potential of low-cost GNSS buoy for monitoring atmospheric water vapor and short-term rainfall forecasting in dynamic marine environments. |
| format | Article |
| id | doaj-art-5c47d9cecdc142bcb0e9c853bf7bb29c |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-5c47d9cecdc142bcb0e9c853bf7bb29c2025-08-20T01:49:28ZengMDPI AGRemote Sensing2072-42922025-05-01179163010.3390/rs17091630Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System BuoyMaosheng Zhou0Pengcheng Wang1Zelu Ji2Yunzhou Li3Dingfeng Yu4Zengzhou Hao5Min Li6Delu Pan7State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaState Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaState Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaState Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaState Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaAcademician Workstation of Shandong Province, Shandong Academy of Sciences, Jinan 250014, ChinaState Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, ChinaAcademician Workstation of Shandong Province, Shandong Academy of Sciences, Jinan 250014, ChinaThis study utilizes a low-cost Global Navigation Satellite System (GNSS) buoy platform, combined with multi-system GNSS data, to investigate the impact of GNSS signal quality and multipath effects on the accuracy of atmospheric precipitable water vapor (PWV) retrievals. It also explores the methods for oceanic rainfall event forecasting and precipitation prediction based on GNSS-PWV. By analyzing the data quality from various GNSS systems and using the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 dataset as a reference, the study assesses the accuracy of PWV retrievals in dynamic marine environments. The results show that the GNSS-derived PWV from the buoy platform is highly consistent with ERA5 data in both trend and characteristics, with an RMSE of 3.8 mm for the difference between GNSS-derived PWV and ERA5 PWV. To enhance rainfall forecasting accuracy, a balanced threshold selection (BTS) method is proposed, significantly improving the balance between the probability of detection (POD) and false alarm rate (FAR). Furthermore, a Random Forest model based on multiple meteorological parameters optimizes precipitation forecasting, especially in reducing false alarms. Additionally, a particle swarm optimization (PSO)-based BP Neural Network model for rainfall prediction achieves high precision, with an R<sup>2</sup> of 97.8%, an average absolute error of 0.08 mm, and an RMSE of 0.1 mm. The findings demonstrate the potential of low-cost GNSS buoy for monitoring atmospheric water vapor and short-term rainfall forecasting in dynamic marine environments.https://www.mdpi.com/2072-4292/17/9/1630global navigation satellite systemmarine buoyprecipitable water vaporrainfall amount prediction |
| spellingShingle | Maosheng Zhou Pengcheng Wang Zelu Ji Yunzhou Li Dingfeng Yu Zengzhou Hao Min Li Delu Pan Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy Remote Sensing global navigation satellite system marine buoy precipitable water vapor rainfall amount prediction |
| title | Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy |
| title_full | Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy |
| title_fullStr | Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy |
| title_full_unstemmed | Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy |
| title_short | Research on Monitoring Oceanic Precipitable Water Vapor and Short-Term Rainfall Forecasting Using Low-Cost Global Navigation Satellite System Buoy |
| title_sort | research on monitoring oceanic precipitable water vapor and short term rainfall forecasting using low cost global navigation satellite system buoy |
| topic | global navigation satellite system marine buoy precipitable water vapor rainfall amount prediction |
| url | https://www.mdpi.com/2072-4292/17/9/1630 |
| work_keys_str_mv | AT maoshengzhou researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT pengchengwang researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT zeluji researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT yunzhouli researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT dingfengyu researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT zengzhouhao researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT minli researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy AT delupan researchonmonitoringoceanicprecipitablewatervaporandshorttermrainfallforecastingusinglowcostglobalnavigationsatellitesystembuoy |