The Radio Occultation Processing Package, ROPP

Culverwell, I. D.; Lewis, Huw; Offiler, D.; Marquardt, Christian; Burrows, C. P.

doi:10.5194/amt-8-1887-2015

Cited by 35 publications

(31 citation statements)

References 27 publications

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“…Based on the measurements of pseudo-range and carrier phase as well as the attitude information of the GNOS POD antenna, the GNSS clock offsets, GNSS precise orbit information, and the Earth orientation parameters, the LEO POD can be conducted by integrating the equations of celestial motion. Currently, in FY-3C GNOS data processing, the Bernese software (V5.0) (Dach et al, 2007) and the Position And Navigation Data Analyst (PANDA) software (Zhao et al, 2017) have been used and evaluated, and both of them can deliver highly accurate POD results.…”

Section: Fy-3c Gnos Level 1 Data Processingmentioning

confidence: 99%

The FengYun-3C radio occultation sounder GNOS: a review of the mission and its early results and science applications

et al. 2018

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Abstract. The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads on board the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. FY-3C GNOS, on board the FY-3 series C satellite launched in September 2013, was designed to acquire setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou Navigation Satellite System (BDS) and the US Global Positioning System (GPS). So far, the GNOS measurements and atmospheric and ionospheric data products have been validated and evaluated and then been used for atmosphere- and ionosphere-related scientific applications. This paper reviews the FY-3C GNOS instrument, RO data processing, data quality evaluation, and preliminary research applications according to the state-of-the-art status of the FY-3C GNOS mission and related publications. The reviewed data validation and application results demonstrate that the FY-3C GNOS mission can provide accurate and precise atmospheric and ionospheric GNSS (i.e., GPS and BDS) RO profiles for numerical weather prediction (NWP), global climate monitoring (GCM), and space weather research (SWR). The performance of the FY-3C GNOS product quality evaluation and scientific applications establishes confidence that the GNOS data from the series of FY-3 satellites will provide important contributions to NWP, GCM, and SWR scientific communities.

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Section: Fy-3c Gnos Level 1 Data Processingmentioning

confidence: 99%

The FengYun-3C radio occultation sounder GNOS: a review of the mission and its early results and science applications

et al. 2018

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“…Contrarily, if there are more measurements than the unknown profile elements, equation should be considered for atmospheric profile retrieval. Equation can be solved using the Levenberg‐Marquardt formula with fast convergence (Culverwell et al, ; Rodgers, ). However, both 14 channels for retrieving temperature profile and 8 channels for inversion of water vapor profile are much smaller than the number of the atmospheric profile layers, so the iteration equation is used to solve the minimization of J ( X ) in this study.…”

Section: Dvar Retrieval Algorithmmentioning

confidence: 99%

Retrieval of Atmospheric Profiles in the New York State Mesonet Using One‐Dimensional Variational Algorithm

Yang

Min

2018

JGR Atmospheres

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A one‐dimensional variational (1DVAR) algorithm was developed, which combines measurements taken by the ground‐based microwave radiometer profiler (MWRP) with the Rapid Refresh (RAP) model to retrieve a more accurate temperature and humidity profiles under clear sky. The passive and active microwave‐vector radiative transfer model was used to simulate brightness temperatures and calculate weighting functions for 22 channels of the MWRP. As MWRP measurements are mainly weighted in the lower atmosphere, a measurement adjustment is performed to reduce the contribution from above 10 km. The results of the 1DVAR algorithm have been compared with the MWRP built‐in neural network (NN) retrievals and radiosonde observations, which show that the 1DVAR method outperforms the NN retrieval both in temperature and water vapor. Our statistical study further shows that the water vapor profiles from RAP are biased higher than the radiosonde observations, while the 1DVAR‐retrieved humidity values show significant improvements throughout the entire 10‐km range. The improvements in temperature profiles occur mainly within the lowest 4‐km atmosphere, while upper level retrievals are mostly influenced by initial values. This is consistent with the characteristics of the Jacobian matrix and the background error covariance matrix. The outcomes of 44 clear‐sky cases show that the maximum mean retrieval error of the 1DVAR algorithm is less than 0.2 K for temperature below 4 km and less than 0.15 g/m3 in water vapor density. These results are shown to be significantly better than the NN retrieval (3.0 K and 1.25 g/m3) and also superior to the RAP reanalysis (0.3 K and 0.5 g/m3).

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“…The IGS ultra rapid orbit products, with an approximate accuracy of 10 cm in orbit, are chosen for near-real-time operational use. The low Earth orbit (LEO) precise orbit determination (POD) can be estimated by integrating the equations of celestial motion (Beutler, 2005) using Bernese software Version 5.0 (Dach et al, 2007). The single difference technique is applied to obtain the excess phase as a function of time in an Earth-centred inertial reference frame.…”

Section: Introductionmentioning

confidence: 99%

Processing and quality control of FY-3C GNOS data used in numerical weather prediction applications

Liao¹,

Healy²,

Zhang³

2019

Atmos. Meas. Tech.

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Abstract. The Chinese radio occultation sounder GNOS (Global Navigation Occultation Sounder) is on the FY-3C satellite, which was launched on 23 September 2013. Currently, GNOS data are transmitted via the Global Telecommunications System (GTS), providing 450–500 profiles per day for numerical weather prediction applications. This paper describes the processing of the GNOS profiles with large biases related to L2 signal degradation. A new extrapolation procedure in bending angle space corrects the L2 bending angles using a thin ionosphere model and the fitting relationship between L1 and L2. We apply the approach to improve the L2 extrapolation of GNOS. The new method can effectively eliminate about 90 % of large departures. In addition to the procedure for the L2 degradation, this paper also describes our quality control (QC) for FY-3C GNOS. A noise estimate for the new L2 extrapolation can be used as a QC parameter to evaluate the performance of the extrapolation. A statistical comparison between GNOS bending angles and short-range ECMWF (European Centre for Medium-Range Weather Forecasts) forecast bending angles demonstrates that GNOS performs almost as well as the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding (GRAS), especially in the core region from around 10 to 35 km. The GNOS data with the new L2 extrapolation are suitable for assimilation into numerical weather prediction systems.

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The Radio Occultation Processing Package, ROPP

Cited by 35 publications

References 27 publications

The FengYun-3C radio occultation sounder GNOS: a review of the mission and its early results and science applications

The FengYun-3C radio occultation sounder GNOS: a review of the mission and its early results and science applications

Retrieval of Atmospheric Profiles in the New York State Mesonet Using One‐Dimensional Variational Algorithm

Processing and quality control of FY-3C GNOS data used in numerical weather prediction applications

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