Test of a non-local excess phase delay operator for GPS radio occultation data assimilation

Shao, Hui; Zou, Xiaolei; Hajj, G. A.

doi:10.1117/1.3094060

Cited by 8 publications

(5 citation statements)

References 20 publications

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“…4. Another paper, (Shao et al 2009), to some extend similar to ours, with large number of observations (1158 RO events) but, simulate the signal in the 2D vertical plane only in the straight lines around the local tangent points, reports that there is up to 5% difference in relative difference between observed and ray-traced signal. These two results show similar performance to our solution (see, e.g., Figure 4).…”

Section: Excess Phase Data Validationsupporting

confidence: 64%

“…The most significant relative differences appear above the 20 km height level. In the paper by Shao et al (2009), the differences between GPS RO data and simulated data reach a standard deviation of 1-3 refraction units at heights below 14 km altitude. That can be considered as a 1-2% difference which is similar to our differences between COSMIC-1-based solutions and observations from atmPhs files at heights below 14 km.…”

Section: Excess Phase Data Validationmentioning

confidence: 94%

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GNSS signal ray-tracing algorithm for the simulation of satellite-to-satellite excess phase in the neutral atmosphere

Cegla,

Rohm,

Moeller

et al. 2024

J Geod

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Traditionally, GNSS space-based and ground-based estimates of tropospheric conditions are performed separately. It leads to limitations in the horizontal (e.g., a single space-based radio occultation profile covers a 300 km slice of the troposphere) and vertical resolution (e.g., ground-based estimates of troposphere conditions have spacing equal to stations’ distribution) of the tropospheric products. The first stage to achieve an integrated model is to create an effective 3D ray-tracing algorithm for the satellite-to-satellite (radio occultation) path reconstruction. We verify the consistency of the simulated data with the RO observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) Data Analysis and Archive Center (CDAAC) in terms of excess phase and bending angle. The results show that our solution provides an effective RO excess phase, with a relative error varying from 35% at the height of 25–30 km (1.0–1.5 m) to 0.5% at heights 5–10 km (0.1–1 m) and 14 to 2% at heights below 5 km (2–14 m). The bending angle retrieval on simulated data attained for high-resolution ray-tracing, bias lower than 2% with respect to the observed bending angle. The optimal solution takes about 1 s for one transmitter–receiver pair with a tangent point below 5 km altitude. The high-resolution processing solution takes 3 times longer.

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Section: Excess Phase Data Validationsupporting

confidence: 64%

Section: Excess Phase Data Validationmentioning

confidence: 94%

GNSS signal ray-tracing algorithm for the simulation of satellite-to-satellite excess phase in the neutral atmosphere

Cegla,

Rohm,

Moeller

et al. 2024

J Geod

View full text Add to dashboard Cite

show abstract

“…As a consequence, the distance of the propagation path changes due to the bending of the signal, which leads to a difference between the phase delay of the actual received signal by the LEO satellite and the phase delay in the case of straight-line propagation. Such delay is defined as Excess Phase Delay, also known as EPD [4]. If the electron content in the signal propagation path is high, the phase velocity of signal propagation will be greater than its propagation velocity in vacuum, resulting in a possible negative EPD value; otherwise, the EPD value will be positive [5].…”

Section: Introductionmentioning

confidence: 99%

A Disturbance Frequency Index in Earthquake Forecast Using Radio Occultation Data

et al. 2023

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Earthquake forecasting is the process of forecasting the time, location, and magnitude of an earthquake, hoping to gain some time to prepare to reduce the disasters caused by earthquakes. In this paper, the possible relationship between the maximum electron density, the corresponding critical frequency, and the occurrence of earthquakes is explored by means of radio occultation data based on mechanism analysis and actual earthquake-nearby data. A new disturbance frequency index is proposed in this paper as a novel method to help forecast earthquakes. Forecasting of the location and timing of earthquakes is based on the connection between proven new frequency distributions and earthquakes. The effectiveness of this index is verified by backtracking observation around the 2022 Ya’an earthquake. Using this index, occultation data can forecast the occurrence of earthquakes five days ahead of detection, which can help break the bottleneck in earthquake forecasting.

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“…Since RO observations are highly accurate, have a high vertical resolution, long‐term stability, and all‐weather capability (Kursinski et al ., 1997), and can be assimilated without bias correction, they are a complement to microwave and infrared measurements. Positive influences of assimilating RO observations on numerical weather prediction have been well studied (Healy, 2008; 2013; Shao et al ., 2009; Cucurull, 2010; Bauer et al ., 2014). In many operational assimilation schemes, observations are weighted proportionally to the inverse of their error variances (Shao and Zou, 2002; Li et al ., 2009), which means that overestimating the observation error will decrease the impact on the result of data assimilation.…”

Section: Introductionmentioning

confidence: 99%

Estimating GPS radio occultation observation error standard deviations over China using the three‐cornered hat method

Zou

2020

Quart J Royal Meteoro Soc

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Observation error variances are required input parameters for assimilating GPS radio occultation (RO) data in numerical weather prediction systems. A three‐cornered hat method is applied to estimate RO observation error standard deviation (SD) of both refractivity and bending angle. RO data from the Global Navigation Satellite System Receiver for Atmospheric Sounding on board the MetOp‐A/B satellites from 1 January 2016 to 31 August 2019, along with radiosonde observations, the European Centre for Medium‐Range Weather Forecasts Interim reanalysis, and the Global Forecast System forecast analysis, are employed in this study. Taking the Guam radiosonde station as an example, we first introduce a detailed procedure of estimating GPS RO fractional error SDs, which shows the significant impacts of outliers on the resulting error SDs, especially in the lower and middle troposphere. Fractional bending angle error SDs near 48 radiosonde stations in China are then estimated for the same time period of more than 3 years. The RO fractional error SDs near the 48 radiosonde stations have a significant latitudinal dependence, larger at lower than higher latitudes. This characteristic feature of the RO bending angle errors agrees with that of the bending angle uncertainty information provided by the Constellation Observing System for Meteorology, Ionosphere, and Climate Data Analysis and Archival Center.

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Test of a non-local excess phase delay operator for GPS radio occultation data assimilation

Cited by 8 publications

References 20 publications

GNSS signal ray-tracing algorithm for the simulation of satellite-to-satellite excess phase in the neutral atmosphere

GNSS signal ray-tracing algorithm for the simulation of satellite-to-satellite excess phase in the neutral atmosphere

A Disturbance Frequency Index in Earthquake Forecast Using Radio Occultation Data

Estimating GPS radio occultation observation error standard deviations over China using the three‐cornered hat method

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