Abstract
The Global Navigation Satellite System (GNSS) is commonly recognized by its all-weather capability. However, observations depend on atmospheric conditions which requires the induced tropospheric delay to be estimated as an unknown parameter. In the following study, we investigate the impact of intense weather events on GNSS estimates. GNSS slant total delays (STD) in Precise Point Positioning technique (PPP) strategy were calculated for stations in southwest Poland in a 56 days period covering several heavy precipitation cases. The corresponding delays retrieved from Weather Research and Forecasting (WRF) model by a ray-tracing technique considered only gaseous parts of the atmosphere. The discrepancies are correlated with rain rates and cloud type products from remote sensing platforms. Positive correlation is found as well as GNSS estimates tend to be systematically larger than modeled delays. Mean differences mapped to the zenith direction are showed to vary between 10 mm and 30 mm. The magnitude of discrepancies follows the intensity of phenomena, especially for severe weather events. Results suggest that effects induced by commonly neglected liquid and solid water terms in the troposphere modeling should be considered in precise GNSS applications for the atmosphere monitoring. The state-of-art functional model applied in GNSS processing strategies shows certain deficits. Estimated tropospheric delays with gradients and post-fit residuals could be replaced by a loosely constrained solution without loss of quality.
Highlights
Weather monitoring and nowcasting is currently based on two major data sources: rapid update weather forecast [1,2] and weather radars [3,4], providing information about current weather and short term forecasts
The analysis of hydrometeors impact on discrepancies in tropospheric delays from Global Navigation Satellite System (GNSS) and ray-tracing is summarized in Table 4 by correlation coefficients with respect to Cloud Type (CT) and Multisensor Precipitation Estimate (MPE) products
The troposphere-induced delays are highly dependent on atmospheric conditions and their magnitudes can be used to express intensity of weather phenomena
Summary
Weather monitoring and nowcasting is currently based on two major data sources: rapid update weather forecast [1,2] and weather radars [3,4], providing information about current weather and short term forecasts. We model ray-traced STDs using Weather Research and Forecasting (WRF) model assuming that the signal propagates in the atmosphere that is a pure gas It theoretically depends only on pressure, temperature and water vapor pressure, but it reflects the model accuracy. These residuals should surpass the uncertainty level of estimated tropospheric delays Both GNSS and ray-traced delays need to be provided with superior accuracy in order to properly distinguish troposphere-induced effects from other systematic effects. The paper provides a detailed analysis of data uncertainties and a comprehensive error propagation for tropospheric estimates to reveal effects of atmospheric liquid and solid water absorbed in GNSS signal.
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