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GNSS Meteorology: Algorithm, Modelling, Assessment and Application
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GNSS Meteorology: Algorithm, Modelling, Assessment and Application

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (3 October 2024) | Viewed by 5240

Special Issue Editors

Dr. Fei Yang

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Guest Editor
College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Interests: GNSS meteorology; water vapor tomography; atmospheric modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Ming Shangguan

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Guest Editor
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: GNSS meteorology; atmosphere remote sensing; weather monitoring
Dr. Liangke Huang

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Guest Editor
College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, 541004, China
Interests: GNSS precise positioning; GNSS atmospheric sounding; tropospheric modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Di Zhang

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Guest Editor
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079，China
Interests: GNSS tropospheric delay; mapping function; atmospheric asymmetry; gradient

Special Issue Information

Dear Colleagues,

GNSS meteorology refers to the use of the effect of the atmosphere on the propagation of GNSS radio signals to derive information on the state of the neutral atmosphere. With the continuous observations from GNSS receivers from both satellite platforms and ground permanent stations, it has become an excellent tool for studying the earth atmosphere, snow depth, soil moisture, and terrestrial water storage variations with the advantages of continuous operation, a low cost, all-weather conditions, high accuracy, and high temporal resolution. For instance, not only can the two-dimensional content of the precipitable water vapor (PWV) be retrieved by GNSS, the three-dimensional distribution of water vapor density can be reconstructed by the water vapor tomography. It has a wide range of applications, such as meteorology, climatology, nowcasting, 4D monitoring of weather events and hydrological phenomena.

In this Special Issue, we are looking for articles that discuss the recent trends, current progress and future directions for GNSS meteorology, and articles that describe the algorithm, model and applications related to GNSS meteorology. We welcome original research on topics including, but not limited to:

  • Water vapor retrievals based on multi-GNSS;
  • Derivation of GNSS atmospheric parameters;
  • PWV/IWV time series analysis and prediction;
  • Modeling for the atmospheric parameters;
  • Water vapor tomography;
  • Numerical nowcasting based on GNSS observations;
  • GNSS data assimilation and application;
  • Climate change;
  • GNSS radio occultation;
  • Monitoring of the rainfall/drought/particle using GNSS PWV/ZWD/ZTD;
  • Comprehensive utilization of multi-source atmospheric data;
  • Parameter inversion using GNSS-IR.

Dr. Fei Yang
Dr. Ming Shangguan
Dr. Liangke Huang
Dr. Di Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GNSS
  • atmosphere
  • troposphere
  • precipitable water vapor
  • weighted mean temperature
  • GNSS reflectometry
  • GNSS RO
  • ray tracing
  • data assimilation
  • tomography
  • numerical modelling
  • weather forecast
  • numerical forecast
  • climate change

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Published Papers (5 papers)

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Research

21 pages, 17022 KiB  
Article
Evaluation and Analysis of Next-Generation FY-4A LPW Products over Various Climatic Regions in China
by Wenyuan Zhang, Xinyu Xiao, Jinsong Peng, Shubi Zhang, Endrit Shehaj and Gregor Moeller
Atmosphere 2024, 15(12), 1545; https://doi.org/10.3390/atmos15121545 - 23 Dec 2024
Abstract
Atmospheric water vapor, a significant constituent of the atmosphere, affects the energy balance between Earth’s atmosphere and space, and its changes play a crucial role in the greenhouse effect. Layer precipitable water (LPW), which represents the column-integral water vapor within a vertical range, [...] Read more.
Atmospheric water vapor, a significant constituent of the atmosphere, affects the energy balance between Earth’s atmosphere and space, and its changes play a crucial role in the greenhouse effect. Layer precipitable water (LPW), which represents the column-integral water vapor within a vertical range, is increasingly recognized as a key indicator of atmospheric water vapor distributions and variations. Due to its capability for layer-wise monitoring, LPW products have the potential to offer valuable insights into the characteristics and evolution of climatic regions through refined atmospheric spatiotemporal information. However, the observational quality and spatiotemporal variations of LPW products across different climate zones, e.g., the diverse climatic regions in China, have not been systematically assessed. In this paper, we aim to evaluate and analyze the climatic and seasonal variations of FY-4A LPW products across five climatic regions in China, contributing to a deeper understanding of water vapor variability and providing valuable data for climate change research. A surface pressure calibration algorithm for ERA5 data is developed to calculate accurate ERA5 LPW products. The results show that all four FY-4A LPWs are consistent with ERA5 LPWs, with an overall root mean square error (RMSE) of 2.58, 0.90, 1.30, and 1.01 mm, respectively. Furthermore, FY-4A LPWs are underestimated in the temperate monsoon area and overestimated in the subtropical and tropical monsoon regions, while FY-4A observations agree well with ERA5 reanalysis in temperate continental and plateau mountain zones. These analyses highlight the remarkable climate dependency of FY-4A LPWs and their potential for climate-related studies. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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13 pages, 4298 KiB  
Article
Towards Real-Time Integrated Water Vapor Estimates with Triple-Frequency Galileo Observations and CNES Products
by Mohamed Abdelazeem
Atmosphere 2024, 15(11), 1320; https://doi.org/10.3390/atmos15111320 - 2 Nov 2024
Viewed by 600
Abstract
Integrated water vapor (IWV) is a crucial parameter for tropospheric sounding and weather prediction applications. IWV is essentially calculated using observations from global navigation satellite systems (GNSS). Presently, the Galileo satellite system is further developed, including more visible satellites that transmit multi-frequency signals. [...] Read more.
Integrated water vapor (IWV) is a crucial parameter for tropospheric sounding and weather prediction applications. IWV is essentially calculated using observations from global navigation satellite systems (GNSS). Presently, the Galileo satellite system is further developed, including more visible satellites that transmit multi-frequency signals. This study aims to evaluate the accuracy of real-time IWV estimated from a triple-frequency Galileo-only precise point positioning (PPP) processing model utilizing E1, E5a, E5b, and E5 observations, which is not addressed by the previous studies. For this purpose, Galileo datasets from 10 global reference stations spanning various 4-week periods in the winter, spring, summer, and fall seasons are acquired. To process the acquired datasets, dual- and triple-frequency ionosphere-free PPP solutions are used, including E1E5a PPP, E1E5aE5b PPP, and E1E5E5b PPP solutions. The publicly available real-time products from the Centre National d’Etudes Spatiales (CNES) are utilized. The real-time IWV values are computed and then validated with the European Centre for Medium-Range Weather Forecasting (ECMWF) reanalysis products (ERA5) counterparts. The findings demonstrate that the root mean square error (RMSE) of the estimated IWV is less than 3.15 kg/m2 with respect to the ECMWF ERA5 counterparts. Furthermore, the E1E5aE5b PPP and E1E5E5b PPP models enhance the IWV’s accuracy by about 11% and 16%, respectively, compared with the E1E5a PPP model. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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12 pages, 7758 KiB  
Article
Evaluation of the Zenith Tropospheric Delay (ZTD) Derived from VMF3_FC and VMF3_OP Products Based on the CMONOC Data
by Haoran Zhang, Liang Chen, Fei Yang, Jingge Ma, Junya Zhang, Wenyu Sun and Shiqi Xu
Atmosphere 2024, 15(7), 766; https://doi.org/10.3390/atmos15070766 - 27 Jun 2024
Viewed by 907
Abstract
Prior tropospheric information, especially zenith tropospheric delay (ZTD), is particularly important in GNSS data processing. The two types of ZTD models, those that require and do not require meteorological parameters, are the most commonly used models, whether the non-difference or double-difference mode is [...] Read more.
Prior tropospheric information, especially zenith tropospheric delay (ZTD), is particularly important in GNSS data processing. The two types of ZTD models, those that require and do not require meteorological parameters, are the most commonly used models, whether the non-difference or double-difference mode is applied. To improve the accuracy of prior tropospheric information, the Vienna Mapping Functions (VMFs) data server provides a gridded set of global tropospheric products based on the ray-tracing technique using Numerical Weather Models (NWMs). Note that two types of gridded tropospheric products are provided: the VMF3_OP for the post-processing applications and the VMF3_FC for real-time applications. To explore the accuracy and adaptability of these two grid products, a comprehensive analysis and discussion were conducted in this study using the ZTD data from 255 stations of the Crustal Movement Observation Network of China (CMONOC) as references. The numerical results indicate that both VMF3_FC and VMF3_OP exhibit high accuracy, with RMSE/Bias values of 17.53/2.25 mm and 14.62/2.67 mm, respectively. Both products displayed a temporal trend, with larger RMSE values occurring in summer and smaller values in winter, along with a spatial trend of higher values in the southeast of China and lower values in the northwest of China. Additionally, VMF3_OP demonstrated superior performance to VMF3_FC, with smaller RMSE values for each month and each hour. For the RMSE difference between these two products, 108 stations had a difference of more than 3 mm, and the number of stations with a difference exceeding 1 mm reached 217. Moreover, the difference was more significant in the southeast than in the northwest. This study contributes to the understanding of the differences between the two precision products, aiding in the selection of suitable ZTD products based on specific requirements. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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17 pages, 2343 KiB  
Article
A Refined Atmospheric Weighted Average Temperature Model Considering Multiple Factors in the Qinghai–Tibet Plateau Region
by Kunjun Tian, Si Xiong, Zhengtao Wang, Bingbing Zhang, Baomin Han and Bing Guo
Atmosphere 2023, 14(12), 1760; https://doi.org/10.3390/atmos14121760 - 29 Nov 2023
Viewed by 1181
Abstract
The Qinghai–Tibet Plateau region has significant altitude fluctuations and complex climate changes. However, the current global weighted average temperature (Tm) model does not fully consider the impact of meteorological and elevation factors on it, resulting in existing models being unable to accurately predict [...] Read more.
The Qinghai–Tibet Plateau region has significant altitude fluctuations and complex climate changes. However, the current global weighted average temperature (Tm) model does not fully consider the impact of meteorological and elevation factors on it, resulting in existing models being unable to accurately predict the Tm in the region. Therefore, this study constructed a weighted average temperature refinement model (XTm) related to surface temperature, water vapor pressure, geopotential height, annual variation, and semi-annual variation based on measured data from 13 radiosonde stations in the Qinghai–Tibet Plateau region from 2008 to 2017. Using the Tm calculated via the numerical integration method of radiosonde observations in the Qinghai–Tibet Plateau region from 2018 to 2019 as a reference value, the quality of the XTm model was tested and compared with the Bevis model and GPT2w (global pressure and temperature 2 wet) model. The results show that for 13 modeling stations, the bias and root-mean-square (RMS) values of the XTm model were −0.02 K and 2.83 K, respectively; compared with the Bevis, GPT2-1, and GPT2w-5 models, the quality of XTm was increased by 47%, 38%, and 47%, respectively. For the four non-modeling stations, the average bias and RMS values of the XTm model were 0.58 K and 2.78 K, respectively; compared with the other three Tm models, the RMS values and the mean bias were both minimal. In addition, the XTm model was also used to calculate the global navigation satellite system (GNSS) precipitable water vapor (PWV), and its average values for the theoretical RMSPWV and RMSPWV/PWV generated by water vapor calculation were 0.11 mm and 1.03%, respectively. Therefore, in the Qinghai–Tibet Plateau region, the XTm model could predict more accurate Tm values, which, in turn, is important for water vapor monitoring. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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14 pages, 3292 KiB  
Article
Verification and Accuracy Analysis of Single-Frequency Occultation Processing Based on the BeiDou Navigation System
by Ruimin Li, Qifei Du, Ming Yang, Haoran Tian, Yueqiang Sun, Xiangguang Meng, Weihua Bai, Xianyi Wang, Guangyuan Tan and Peng Hu
Atmosphere 2023, 14(4), 742; https://doi.org/10.3390/atmos14040742 - 19 Apr 2023
Cited by 2 | Viewed by 1473
Abstract
GNSS single-frequency occultation processing technology has the advantage of simple instrumentation, but it is not clear about the accuracy of the Beidou-based single-frequency occultation processing. This paper verifies the single-frequency occultation processing algorithm of the BeiDou navigation system (BDS) and analyzes its accuracy [...] Read more.
GNSS single-frequency occultation processing technology has the advantage of simple instrumentation, but it is not clear about the accuracy of the Beidou-based single-frequency occultation processing. This paper verifies the single-frequency occultation processing algorithm of the BeiDou navigation system (BDS) and analyzes its accuracy based on occultation observation data from the FY3E satellite. The research aimed to verify the single-frequency ionospheric relative total electron content (relTEC), analyze the accuracy of the reconstructed second frequency B3∗’s excess phase Doppler, and analyze the accuracy of the refractive index products. Results: (1) As for relTEC and excess phase Doppler, the correlation coefficient between single-frequency occultation processing and dual-frequency occultation processing is greater than 0.95. (2) The relative average deviations of the excess phase Doppler of B3∗ are mostly less than 0.2%, and the relative standard deviations are mostly around 0.5%. (3) The bias index and root mean square index of single/dual-frequency inversion have good consistency compared with ERA5 data. All the results show that the single- and dual-frequency inversion refractive index products have comparable accuracies, and the accuracy of the standard deviation of single-frequency inversion refractive index products over 25 km being slightly lower than that of dual-frequency inversion refractive index products. Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
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