Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.1
2.9
Journals
Atmosphere
Special Issues
GNSS Observations in Meteorology and Climate Applications
share announcement

GNSS Observations in Meteorology and Climate Applications

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 (8 April 2022) | Viewed by 11995

Special Issue Editors

Dr. Katarzyna Stępniak

E-Mail Website
Guest Editor
Department of Geodesy, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1, 10-719 Olsztyn, Poland
Interests: global navigation satellite system (GNSS); application of precise GNSS measurements in climate studies; GNSS meteorology; remote sensing
Dr. Maxim Golubkov

E-Mail Website
Guest Editor
Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia
Interests: low ionosphere; GNSS; remote sensing; atomic and molecular physics; Rydberg states

Special Issue Information

Dear Colleagues,

Accurate meteorology and climatology are crucial in the era of climate change and violent weather phenomena. Today, extreme weather events, such as storms, floods, landslides, heat waves, and droughts, are the main concerns of society. Water vapor is a key variable in the hydrological cycle and plays a special role in many atmospheric processes controlling the weather and climate. The global navigation satellite system (GNSS) is one of the few tools that can be used as an atmospheric water vapor sensor and, simultaneously, provide continuous, unbiased, precise, and robust atmosphere condition information.

This Special Issue aims to support collaboration between the geodetic, weather, and climate community and to promote the use of geodetic observations in climate and meteorological applications. This Special Issue is open to all publications on GNSS climate and meteorology. Topics of interest include but are not limited to:

  • Recent advances in precise GNSS data processing and post-processing;
  • Improvement of GNSS methodology to retrieve high-quality atmospheric water vapor;
  • Conversion of GNSS tropospheric estimates to water vapor;
  • Assessment of long-term GNSS datasets for use in climate studies;
  • Real-time determination of tropospheric zenith total delay and integrated water vapor for now-casting and severe weather monitoring,
  • Use of local and dense GNSS networks in the weather forecasting;
  • Validation and improving numerical weather prediction by applying GNSS observations.

Dr. Katarzyna Stępniak
Dr. Maxim Golubkov
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
  • Meteorology
  • Climate
  • Water vapor
  • Tropospheric delay

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 5735 KiB  
Article
Effect of Multiple GNSS Integration on the Number and Spatiotemporal Coverage of Radio Occultation Events
by Congliang Liu, Yueqiang Sun, Weihua Bai, Qifei Du, Wei Li, Xi Wang and Peixian Li
Atmosphere 2022, 13(5), 654; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13050654 - 20 Apr 2022
Cited by 1 | Viewed by 1607
Abstract
The development of global navigation satellite systems (GNSSs) and multi-system compatible radio occultation (RO) techniques provides favorable conditions and opportunities for increasing the number of occultation events and improving their spatiotemporal coverage. The performance of the multiple GNSS RO event number, spatiotemporal coverage, [...] Read more.
The development of global navigation satellite systems (GNSSs) and multi-system compatible radio occultation (RO) techniques provides favorable conditions and opportunities for increasing the number of occultation events and improving their spatiotemporal coverage. The performance of the multiple GNSS RO event number, spatiotemporal coverage, and uniformity need assessments by robust and functional approaches. Firstly, a simulation system of RO events, which took the orbit perturbations into account, was established, and the concepts of global coverage fraction and uniformity of RO events were defined. Secondly, numerical experiments were designed to analyze the GNSS RO performances of a single-receiving satellite and satellite constellations under the condition of using current multiple GNSSs as transmitting satellite systems, in which the Earth was divided into 400 × 400 km2 grids. Finally, the number, timeliness, global coverage fraction, and uniformity of GNSS RO events for a single-receiving satellite and receiving satellite constellations were numerically calculated and analyzed. The results showed that ➀ multiple GNSS integration improved the number of GNSS RO events and their global coverage for a single polar-orbit satellite significantly, e.g., the 24 h multiple GNSS RO event number was about 7.8 times that of the single GNSS system, BeiDou navigation satellite system-3, while the corresponding 24 h global coverage fraction increased nearly 3 times. ➁ In the multiple GNSS integration scenario, the constellation composed of 12 polar-orbit low-Earth-orbit satellites achieved 100% RO event global coverage fraction within 24 h, of which the RO detection capability was comparable to the 100 Spire weather satellites and global positioning system (GPS) RO system. ➂ More GNSS RO events of the polar-orbit constellations were distributed in the middle- and high-latitude zones. Therefore, multiple GNSS integration could increase the RO event number and global coverage significantly to benefit the global climate monitoring and global numerical weather prediction, and the polar-orbit constellations were more favorable to atmospheric detection in middle- and high-latitude regions. Full article
(This article belongs to the Special Issue GNSS Observations in Meteorology and Climate Applications)
►▼ Show Figures

Figure 1

13 pages, 25669 KiB  
Article
Temporal Analysis of GNSS-Based Precipitable Water Vapor during Rainy Days over the Philippines from 2015 to 2017
by Agana Louisse S. Domingo and Ernest P. Macalalad
Atmosphere 2022, 13(3), 430; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13030430 - 07 Mar 2022
Cited by 2 | Viewed by 3021
Abstract
Precipitable water vapor (PWV) is a parameter used to estimate water vapor content in the atmosphere. In this study, estimates of PWV from PIMO, PLEG and PPPC global navigation satellite system (GNSS) stations are evaluated regarding the PWV obtained from its collocated radiosonde [...] Read more.
Precipitable water vapor (PWV) is a parameter used to estimate water vapor content in the atmosphere. In this study, estimates of PWV from PIMO, PLEG and PPPC global navigation satellite system (GNSS) stations are evaluated regarding the PWV obtained from its collocated radiosonde (RS) stations. GNSS PWV were highly correlated with RS PWV (R ~ 0.97). Mean bias error (MBE) between −0.18 mm and −13.39 mm, and root mean square error (RMSE) between 1.86 mm and 2.29 mm showed a good agreement between GNSS PWV and RS PWV. The variations of PWV are presented. Daily variations of PWV conformed to the daily data of rainfall which agrees to the climate types of Quezon City (Type I), Legaspi (Type II), and Puerto Princesa (Type III) based on the Coronas climate classification. Moreover, PWV monthly variation at all sites is high from May to October (~62 mm) and low from November to April (~57 mm). The relationship between PWV and rainfall at all stations showed positive correlation coefficients between +0.49 to +0.83. Meanwhile, it is observed that when PWV is high (low), its variability is low (high). This study shows the potential of GNSS to study water vapor and its contribution to weather analysis. Full article
(This article belongs to the Special Issue GNSS Observations in Meteorology and Climate Applications)
►▼ Show Figures

Figure 1

19 pages, 5407 KiB  
Article
Forecasting GNSS Zenith Troposphere Delay by Improving GPT3 Model with Machine Learning in Antarctica
by Song Li, Tianhe Xu, Yan Xu, Nan Jiang and Luísa Bastos
Atmosphere 2022, 13(1), 78; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13010078 - 03 Jan 2022
Cited by 11 | Viewed by 2275
Abstract
Antarctica has a significant impact on global climate change. However, to draw climate change scenarios, there is a need for meteorological data, such as water vapor content, which is scarce in Antarctica. Global navigation satellite system (GNSS) networks can play a major role [...] Read more.
Antarctica has a significant impact on global climate change. However, to draw climate change scenarios, there is a need for meteorological data, such as water vapor content, which is scarce in Antarctica. Global navigation satellite system (GNSS) networks can play a major role in overcoming this problem as the tropospheric delay that can be derived from GNSS measurements is an important data source for monitoring the variation of water vapor content. This work intends to be a contribution for improving the estimation of the zenith tropospheric delay (ZTD) obtained with the latest global pressure–temperature (GPT3) model for Antarctica through the use of long short-term-memory (LSTM) and radial basis function (RBF) neural networks for modifying GPT3_ZTD. The forecasting ZTD model is established based on the GNSS_ZTD observations at 71 GNSS stations from 1 January 2018 to 23 October 2021. According to the autocorrelation of the bias series between GNSS_ZTD and GPT3_ZTD, we predict the LSTM_ZTD for each GNSS station for period from October 2020 to October 2021 using the LSTM day by day. Based on the bias between LSTM_ZTD and GPT3_ZTD of the training stations, the RBF is adopted to estimate the LSTM_RBF_ZTD of the verified station, where the LSTM_ZTD represents the temporal forecasting ZTD at a single station, and the LSTM_RBF_ZTD represents the predicted ZTD obtained from space. Both the daily and yearly RMSE are calculated against the reference (GNSS_ZTD), and the improvement of predicted ZTD is compared with GPT3_ZTD. The results show that the single-station LSTM_ZTD series has a good agreement with the GNSS_ZTD, and most daily RMSE values are within 20 mm. The yearly RMSE of the 65 stations ranges from 6.4 mm to 32.8 mm, with an average of 10.9 mm. The overall accuracy of the LSTM_RBF_ZTD is significantly better than that of the GPT3_ZTD, with the daily RMSE of LSTM_RBF_ZTD significantly less than 30 mm, and the yearly RMSE ranging from 5.6 mm to 50.1 mm for the 65 stations. The average yearly RMSE is 15.7 mm, which is 10.2 mm less than that of the GPT3_ZTD. The LSTM_RBF_ZTD of 62 stations is more accurate than GPT3_ZTD, with the maximum improvement reaching 76.3%. The accuracy of LSTM_RBF_ZTD is slightly inferior to GPT3_ZTD at three stations located in East Antarctica with few GNSS stations. The average improvement across the 65 stations is 39.6%. Full article
(This article belongs to the Special Issue GNSS Observations in Meteorology and Climate Applications)
►▼ Show Figures

Figure 1

18 pages, 5915 KiB  
Article
Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
by Xiang Dong, Fang Sun, Qinglin Zhu, Leke Lin, Zhenwei Zhao and Chen Zhou
Atmosphere 2021, 12(11), 1468; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12111468 - 06 Nov 2021
Cited by 3 | Viewed by 2049
Abstract
Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of [...] Read more.
Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively. Full article
(This article belongs to the Special Issue GNSS Observations in Meteorology and Climate Applications)
►▼ Show Figures

Figure 1

16 pages, 4233 KiB  
Article
Disturbances of the Thermosphere and the Ionosphere during a Meteorological Storm
by Olga P. Borchevkina, Yuliya A. Kurdyaeva, Yurii A. Dyakov, Ivan V. Karpov, Gennady V. Golubkov, Pao K. Wang and Maxim G. Golubkov
Atmosphere 2021, 12(11), 1384; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12111384 - 22 Oct 2021
Cited by 14 | Viewed by 1844
Abstract
Determination of the physical mechanisms of energy transfer of tropospheric disturbances to the ionosphere is one of the fundamental problems of atmospheric physics. This article presents the results of observations carried out using two-wavelength lidar sensing at tropospheric altitudes and satellite GPS measurements [...] Read more.
Determination of the physical mechanisms of energy transfer of tropospheric disturbances to the ionosphere is one of the fundamental problems of atmospheric physics. This article presents the results of observations carried out using two-wavelength lidar sensing at tropospheric altitudes and satellite GPS measurements during a meteorological storm in Kaliningrad (Russia, 54.7° N, 20.5° E) on 1 April 2016. During lidar sensing, it was found that the amplitudes of variations in atmospheric parameters with periods of acoustic (AWs) and internal gravity (IGWs) waves significantly increased. As a result of numerical modeling using the AtmoSym software package, it was shown that there is a noticeable increase in the period of temperature disturbances from 6–12 min to 10–17 min at altitudes from 150 km up to 230 km during the vertical propagation of acoustic waves and internal gravity waves from the troposphere. Nonlinear and dissipative processes in this layer lead to the formation of sources of secondary waves in the thermosphere with periods longer than those of primary ones. In this case, the unsteady nature of the wave source and the short duration of its operation does not lead to significant heating of the thermosphere. Simultaneous satellite observations demonstrate the response of the ionosphere (total electron content (TEC) disturbance) to tropospheric disturbances. Analysis of the time series of the amplitudes of the reflected lidar signal and TEC made it possible to determine that the response time of the ionosphere to tropospheric disturbances is 30–40 min. Full article
(This article belongs to the Special Issue GNSS Observations in Meteorology and Climate Applications)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop