Global Navigation Satellite System (GNSS) observations of troposphere steam vapor support weather forecasting and tracking harsh weather phenomena in many national and international weather services.
Global navigation satellite systems are ubiquitous in modern technology and data-driven societies, supporting more applications beyond positioning, navigation and timing (PNT) activities.
The role of GNS in weather forecasting
GNSS signals experience a variety of atmospheric effects, as they travel from mostly Earth Central Orbit (MEO) satellite transmitters to receivers either at low Earth Orbit (LEO) satellites or on terrestrial tracking stations. Troposphere signal delay is one of the most important contributors to GNSS positioning errors, and has a significant impact on accuracy after dealing with orbital and satellite and receiver clock uncertainties.
When the GNSS signal passes through the troposphere, which is at least 15km in the atmosphere, it encounters various levels of water vapor, temperature, and pressures that slowly bend the path. This effect is usually broken down into two components. It is a relatively stable hydrostatic pressure delay associated with atmospheric pressure, and a highly variable wetting delay driven by water vapor.
Advanced GNSS processing strategies rely on mapping functions to project these delays experienced in the prospects between receivers and satellites onto Zenith’s delays, while stochastic models estimate wet delay variations and horizontal gradients. By separating these terms and carefully adjusting random walks or similar constraints, GNSS analysis can capture both progressive and rapid changes in atmospheric water vapor.
Water vapor estimates from GNSS play an important role in modern weather forecasting, as atmospheric steam is the dominant natural greenhouse gas, but are also a determinant of weather, particularly precipitation. GNSS-derived atmospheric products such as total zenith delay and precipitation-enabled water vapor estimation can help identify the time and location of precipitation when assimilated into a numerical weather forecast (NWP) model. This allows meteorologists to predict storms, tropical cyclone behavior, or heavy rain, and ultimately improve harsh weather warnings. Because water vapor plays a direct role in the precipitation process, timely GNSS-derived atmospheric products often lead to more accurate rainfall prediction, local wind prediction, and storm timing. Furthermore, the densely distributed GNSS network allows for tomography-like methods and the generation of three-dimensional reconstructions of the steam field. These are particularly interesting for studying some of the physical processes of storms.
Applications in climate research and long-term monitoring
Beyond operational weather, global navigation satellite systems play an increasingly important role in climate research. Long-term records of troposphere delays capture gradual changes in moisture distribution and provide a high-resolution dataset that informs studies of extreme precipitation, cloud cover, temperature, and changes in moisture feedback. These records are especially valuable as they provide continuous 24-hour observations and complement other observation systems such as Radiosondo and satellite remote sensing. Recognizing the need for such long-term tracking, the Intergovernmental Panel on Climate Change (IPCC) emphasizes the importance of consistent observations of atmospheric steam to understand climate change and change.
The era of multiple GNSS constellations
By employing observations from multiple GNS constellations of GPS, Glonass, Galileo, Beidou, QZSS and IRNSS, analysts achieve better spatial coverage and more frequent sampling, improving atmospheric estimate resolution. These insights can help identify local phenomena such as convective cells and sea breeze fronts that may be overlooked by traditional weather observations. Furthermore, in regions with a sparse network of weather stations, the global navigation satellite system adds important low-cost supplements to enhance understanding of short-lived weather extremes and long-term climate change.
Navigate complexity
Despite these advances, the dynamic nature of water transport and the rapid onset of convective events remain complicated. Stochastic constraints such as random walk noise models for wet delays are not always consistent with actual atmospheric variability, and can lead to over-putting during sudden surges of moisture or in more stable conditions. Ongoing research examines adaptive constraints that shift according to near-realistic time weather indicators, thus capturing sharp gradients more faithfully.
Overall, troposphere delay remains crucial to GNSS accuracy and serves as a gateway to wider atmospheric applications. Continuing improvements in modeling these delays, adoption of multiple-connection data, and adaptation to near-real-time forecasts have driven significant advances in research focusing on weather and climate. High frequency products benefit users who need fast and accurate locations, such as aviation, disaster response, and data assimilation of numerical weather models, while long-term records track how water vapor patterns evolve over seasons, years and decades. As the methods continue to improve troposphere variability parameterization, GNSS is poised to enhance both real-time navigation and long-term monitoring of the global changing climate.
GNSS Meteorology by GGE
GGE boasts established capabilities in the processing of GNSS observations for operability assimilation into NWP models, special studies of harsh weather phenomena, and for searching for atmospheric water vapor for long-term monitoring.
Nearly real-time (NRT) applications, namely operational assimilation and processing takes place within minutes to hours of data capture, with a particular emphasis on timeline and reliability. GNSS data can be collected from a regional, global station network in minutes and then processed, providing a solution updated every 30 or 60 minutes with a delay estimate of 5-15 minutes.
In rapid-moving scenarios such as navigation of ground and aerial vehicles, even storm tracking allows GNSS-derived atmospheric products to be updated in real time, i.e., from seconds to minutes, frequently, even in storm tracking. Such frequent updates are currently commonly used to keep the weather down, but are essential as the water vapor distribution, temperature profiles, and local weather patterns can shift dramatically, especially during the development of convective storms.
Long-term monitoring applications are the most concerning strategies and error mitigation modeling, as they allow coordinate reference frames, consistency and uniformity of GNSS satellite and bias products, and the climate record from which these changes are derived, to be unreliable. Careful homogenization of these records, like most other climatological data, is required to prevent misinterpretation.
GGE provides:
Data handling solutions for GNSS data processing expertise and high level expertise in Meteorological Research & Prediction Models (WRF) and WRF Data Assimilation (WRFDA) geodetic and geospatial technology and related data analysis, and applications for its applications
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