Wu Jizhong, Ma Hongyang, Wu Wei, Cheng Dashuai
School of Geomatics Science and Technology, Nanjing Tech University, Nanjing, 211800, China.
Suqian City Planning Surveying and Mapping Institute Co., Ltd, Suqian, 223800, China.
Sci Rep. 2025 Jul 6;15(1):24095. doi: 10.1038/s41598-025-10603-z.
Water vapor plays a vital role in weather variations, making it essential to monitor atmospheric water vapor content for reliable weather forecasts. This study investigates the feasibility of utilizing a low-cost GNSS network to monitor water vapor transport during a heavy precipitation event. The zenith wet delay (ZWD) products are retrieved in GNSS data processing and then transformed to integrated water vapor (IWV). In addition, the impact of various factors, including near real-time products, weighted mean temperature ([Formula: see text]) estimation models, and the sensitivity of the conversion factor to [Formula: see text] variations are investigated in this study. Results demonstrate that: (1) Phase center variation (PCV) corrections, often unavailable for low-cost antennas, are crucial for accurate ZWD estimation, and the absence of these corrections may result in underestimations of the ZWD by several millimeters. (2) Near real-time GNSS products demonstrate comparable accuracy to final products, enabling timely IWV monitoring. (3) ZWD estimated from low-cost stations exhibit strong agreement with those from geodesic-grade stations, demonstrating their reliability. (4) GPT3, GTrop, and GGNTm models could effectively convert ZWD to IWV, with negligible differences despite slight variations in [Formula: see text] estimation accuracy. (5) The network effectively captures the spatio-temporal evolution of IWV during the precipitation event, demonstrating its potential for high-resolution water vapor monitoring. These findings highlight the effectiveness of low-cost GNSS networks in providing valuable insights into atmospheric water vapor dynamics, contributing to improved weather forecasting and hydrological modeling.
水汽在天气变化中起着至关重要的作用,因此监测大气水汽含量对于可靠的天气预报至关重要。本研究探讨了利用低成本全球导航卫星系统(GNSS)网络监测强降水事件期间水汽输送的可行性。在GNSS数据处理中获取天顶湿延迟(ZWD)产品,然后将其转换为积分水汽(IWV)。此外,本研究还调查了各种因素的影响,包括近实时产品、加权平均温度([公式:见原文])估计模型以及转换因子对[公式:见原文]变化的敏感性。结果表明:(1)相位中心变化(PCV)校正对于准确估计ZWD至关重要,而低成本天线通常无法进行这种校正,缺少这些校正可能导致ZWD低估数毫米。(2)近实时GNSS产品显示出与最终产品相当的精度,能够及时监测IWV。(3)低成本站点估计的ZWD与大地测量级站点估计的ZWD高度一致,证明了其可靠性。(4)GPT3、GTrop和GGNTm模型能够有效地将ZWD转换为IWV,尽管[公式:见原文]估计精度略有差异,但差异可忽略不计。(5)该网络有效地捕捉了降水事件期间IWV的时空演变,证明了其在高分辨率水汽监测方面的潜力。这些发现突出了低成本GNSS网络在提供有关大气水汽动力学的有价值见解方面的有效性,有助于改进天气预报和水文建模。