GNSS meteorology in Egypt: Modeling weighted mean temperature from radiosonde data

Elhaty, N. M.; Abdelfatah, Mohamed Amin; Mousa, Ashraf; El-Fiky, Gamal

doi:10.1016/j.aej.2019.04.001

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…In Egyptian region, Elhaty et al 33 utilized 3600 profiles from four radiosonde stations in Egypt from 2015 to 2016 to establish a new T m model for Egypt. This regional model was evaluated against other six models, namely Bevis, Schueler, Yao, Liou, Suresh Raju and Wayan.…”

Section: Introductionmentioning

confidence: 99%

A new Egyptian Grid Weighted Mean Temperature (EGWMT) model using hourly ERA5 reanalysis data in GNSS PWV retrieval

Sleem,

Abdelfatah,

Mousa

et al. 2024

Sci Rep

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Precise modeling of weighted mean temperature (Tm) is essential for Global Navigation Satellite System (GNSS) meteorology. In retrieving precipitable water vapor (PWV) from GNSS, Tm is a crucial parameter for the conversion of zenith wet delay (ZWD) into PWV. In this study, an improved Tm model, named EGWMT, was developed to accurately estimate Tm at any site in Egypt. This new model was established using hourly ERA5 reanalysis data from European Centre for Medium-Range Weather Forecasts (ECMWF) covering the period from 2008 to 2019 with a spatial resolution of 0.25° × 0.25°. The performance of the proposed model was evaluated using two types of data sources, including hourly ERA5 reanalysis data from 2019 to 2022 and radiosonde profiles over a six-year period from 2017 to 2022. The accuracy of the EGWMT model was compared to that of four other models: Bevis, Elhaty, ANN and GGTm-Ts using two statistical quantities, including mean absolute bias (MAB) and root mean square error (RMSE). The results demonstrated that the EGWMT model outperformed the Bevis, Elhaty, ANN and GGTm-Ts models with RMSE improvements of 32.5%, 30.8%, 39% and 48.2%, respectively in the ERA5 data comparison. In comparison with radiosonde data, the EGWMT model achieved RMSE improvements of 22.5%, 34%, 38% and 19.5% against Bevis, Elhaty, ANN and GGTm-Ts models, respectively. In order to determine the significance of differences in means and variances, statistical tests, including t-test and F-test, were conducted. The results confirmed that there were significant differences between the EGWMT model and the four other models.

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Section: Introductionmentioning

confidence: 99%

A new Egyptian Grid Weighted Mean Temperature (EGWMT) model using hourly ERA5 reanalysis data in GNSS PWV retrieval

Sleem,

Abdelfatah,

Mousa

et al. 2024

Sci Rep

View full text Add to dashboard Cite

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“…Singh, et al [46] have found that the site specific T m model is better than the developed regional T m model and global model at New Delhi and Patiala. Elhaty, et al [47] use radiosonde profiles from four stations situated in Egypt during 2015-2016 and Bevis linear regression method to develop a new T m model. Several RTMs using one factor (T s ) have been established in China [45,[48][49][50].…”

Section: Introductionmentioning

confidence: 99%

The New Improved ZHD and Weighted Mean Temperature Models Based on GNSS and Radiosonde Data Using GPT3 and Fourier Function

Gao

et al. 2022

Atmosphere

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Compared to the zenith hydrostatic delay (ZHD) obtained from the Saastamonien model based on in-situ measured meteorological (IMM) data and radiosonde-derived weighted mean temperature (), the ZHD and deviations of the GPT3 model have shown obvious periodic trends. This article analyzed the seasonal variations of GPT3-ZHD and GPT3- during the 2016–2020 period in the Yangtze River Delta region, and the new improved ZHD and models were established by the multi-order Fourier function. The precision of the improved-ZHD model was verified using IMM-ZHD products from 7 GNSS stations during the 2016–2020 period. Furthermore, the precisions of improved and precipitable water vapor (PWV) were verified by radiosonde-derived and PWV in the 2016–2019 period. Compared with the IMM-ZHD and GNSS-PWV products, the mean Bias and RMS of GPT3-ZHD are −0.5 mm and 2.1 mm, while those of GPT3-PWV are 2.7 mm and 11.1 mm. Compared to the radiosonde-derived , the mean Bias and RMS of GPT3- are −0.8 K and 3.2 K. The mean Bias and RMS of the improved-ZHD model from 2019 to 2020 are −0.1 mm and 0.5 mm, respectively, decreasing by 0.4 mm and 1.6 mm compared to the GPT3-ZHD, while those of the improved- are −0.6 K and 2.7 K, respectively, decreasing by 0.2 K and 0.5 K compared to GPT3-. The mean Bias and RMS of PWV calculated by GNSS-ZTD, improved-ZHD, and improved- are 0.5 mm and 0.6 mm, respectively, compared to the GNSS-PWV, decreasing by 2.2 mm and 10.5 mm compared to the GPT3-PWV. It indicates that the improved ZHD and models can be used to obtain the high-precision PWV. It can be applied effectively in the retrieval of high-precision PWV in real-time in the Yangtze River Delta region.

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Performance assessment of weighted mean temperature models derived from AIRS and ERA5 reanalysis for calculating GPS precipitable water vapor in the thailand region

2022

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GNSS meteorology in Egypt: Modeling weighted mean temperature from radiosonde data

Cited by 7 publications

References 16 publications

A new Egyptian Grid Weighted Mean Temperature (EGWMT) model using hourly ERA5 reanalysis data in GNSS PWV retrieval

A new Egyptian Grid Weighted Mean Temperature (EGWMT) model using hourly ERA5 reanalysis data in GNSS PWV retrieval

The New Improved ZHD and Weighted Mean Temperature Models Based on GNSS and Radiosonde Data Using GPT3 and Fourier Function

Performance assessment of weighted mean temperature models derived from AIRS and ERA5 reanalysis for calculating GPS precipitable water vapor in the thailand region

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