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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (8 October 2022) | Viewed by 27854

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Special Issue Editors

Dr. Michael E. Gorbunov

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Guest Editor

A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia
Interests: radio occultations; wave optics; mathematical method of wave field analysis; time-frequency analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Vladimir Gubenko

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Guest Editor

Kotel'nikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, Fryazino Branch, Fryazino, Russia
Interests: radio waves; studies of internal gravity waves and sporadic E-layers; radio occulations
Special Issues, Collections and Topics in MDPI journals

Dr. Congliang Liu

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Guest Editor

National Space Science Center, Chinese Academy of Sciences, Beijing, China
Interests: atmospheric remote sensing; GNSS radio occultation; LEO-LEO occultation methods (microwave); GNSS remote sensing data applications
Special Issues, Collections and Topics in MDPI journals

Mr. Vinicius Ludwig Barbosa

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Guest Editor

Department of Mathematics and Natural Sciences, Blekinge Tekniska Högskola, Karlskrona, Sweden
Interests: antennas and propagation; microwave engineering; ionosphere; MATLAB; remote sensing

Ms. Xu Xu

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Guest Editor

School of Atmosphere Sciences, Nanjing University of Information Science & Technology, Nanjing, China
Interests: climate change; atmosphere remote sensing; Radio Occultation

Prof. Dr. Xiaolei Zou

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Guest Editor

School of Atmosphere Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: satellite data applications in weather and climate studies; atmosphere data assimilation; numerical weather prediction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The application of radio occultations (RO) for numerical weather prediction, ionosphere, and space weather has been growing in recent decades. This is explained by the fact that RO observations, which are unique in some respects, allow for achieving a high accuracy and vertical resolution in sounding the Earth’s atmosphere and ionosphere. In this Special Issue, we aim to collect papers discussing different aspects of handling RO observations, ranging from the study of the Earth’s atmospheric phenomena, extreme events, methods of RO data inversion and assimilation into numerical weather prediction models, climatology, planetary boundary layer studies, altimetry, polarimetric RO, studies of internal gravity waves and Rossby waves, statistical studies and validation of data from the newest missions, ionospheric tomography, studies of sporadic E-layers, space weather, RO simulation techniques, and ionospheric correction and bias correction methods. Contributions highlighting the aforementioned and further aspects and benefits related to RO observation usage and introducing new approaches in this area are welcomed.

Dr. Michael E. Gorbunov
Dr. Vladimir Gubenko
Dr. Congliang Liu
Mr. Vinicius Ludwig Barbosa
Ms. Xu Xu
Dr. Xiaolei Zou
Guest Editors

Note: We are pleased to announce a joint Special Issue "Advances in GNSS Radio Occultation Technique and Applications" in Atmosphere. Suggested emphasis and guidelines for the two Special Issues can be found below.

Remote Sensing - Advances on GNSS Radio Occultation Techniques and Understanding
• Radio occultation theory
• Retrieval and processing techniques
• Polarimetric radio occultation
• Accuracy and precision of radio occultation data
• Derivation of temperature and water vapor from radio occultation

Atmosphere - Advances in GNSS Radio Occultation Applications
• Weather and NWP
• Climate Monitoring and Science
• Space weather and Ionospheric Science
• Original and review papers welcome

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. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

radio occultation
numerical weather prediction
ionosphere
space weather
remote sensing

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Published Papers (12 papers)

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Editorial

Jump to: Research, Other

4 pages, 181 KiB

Open AccessEditorial

Editorial for the Special Issue: “Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather”

by Michael Gorbunov

Remote Sens. 2023, 15(8), 2107; https://doi.org/10.3390/rs15082107 - 17 Apr 2023

Cited by 1 | Viewed by 1082

Abstract

Sounding of the Earth’s ionosphere is an important application of the RO technique [...] Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

Research

Jump to: Editorial, Other

18 pages, 15782 KiB

Open AccessArticle

Fractional Fourier Transform and Distributions in the Ray Space: Application for the Analysis of Radio Occultation Data

by Michael Gorbunov and Oksana Dolovova

Remote Sens. 2022, 14(22), 5802; https://doi.org/10.3390/rs14225802 - 17 Nov 2022

Cited by 3 | Viewed by 1572

Abstract

The concept of the phase space plays a key role in the analysis of oscillating signals. For a 1-D signal, the coordinates of the 2-D phase space are the observation time and the instant frequency. For measurements of propagating wave fields, the time and instant frequency are linked to the spatial location and wave normal, defining a ray. In this case, the phase space is also termed the ray space. Distributions in the ray space find important applications in the analysis of radio occultation (RO) data because they allow the separation of interfering rays in multipath zones. Examples of such distributions are the spectrogram, Wigner distribution function (WDF), and Kirkwood distribution function (KDF). In this study, we analyze the application of the fractional Fourier transform (FrFT) to the construction of distributions in the ray space. The FrFT implements the phase space rotation. We consider the KDF averaged over the rotation group and demonstrate that it equals the WDF convolved with a smoothing kernel. We give examples of processing simple test signals, for which we evaluate the FrFT, KDF, WDF, and smoothed WDF (SWDF). We analyze the advantages of the SWDF and show examples of its application to the analysis of real RO observations. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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32 pages, 13511 KiB

Open AccessArticle

Atmospheric GNSS RO 1D-Var in Use at UCAR: Description and Validation

by Tae-Kwon Wee, Richard A. Anthes, Douglas C. Hunt, William S. Schreiner and Ying-Hwa Kuo

Remote Sens. 2022, 14(21), 5614; https://doi.org/10.3390/rs14215614 - 7 Nov 2022

Cited by 11 | Viewed by 2311

Abstract

This paper describes, along with some validation results, the one-dimensional variational method (1D-Var) that is in use at the University Corporation for Atmospheric Research (UCAR) to retrieve atmospheric profiles of temperature, pressure, and humidity from the observation of the Global Navigation Satellite System (GNSS) radio occultation (RO). The retrieved profiles are physically consistent among the variables and statistically optimal as regards to a priori error statistics. Tests with idealized data demonstrate that the 1D-Var is highly effective in spreading the observational information and confirm that the method works as designed and expected, provided that correct input data are given. Tests for real-world data sets show that the retrieved profiles agree remarkably well with global weather analyses and collocated high vertical resolution radiosonde observations, and that the 1D-Var can produce value-added retrievals with respect to a priori profiles. We also find that the retrieved profiles are of exceptional long-term stability, suggesting that the 1D-Var can provide an excellent climate data record. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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21 pages, 9885 KiB

Open AccessArticle

Using GNSS Radio Occultation Data to Monitor Tropical Atmospheric Anomalies during the January–February 2009 Sudden Stratospheric Warming Event

by Ying Li, Yunbin Yuan and Min Song

Remote Sens. 2022, 14(13), 3234; https://doi.org/10.3390/rs14133234 - 5 Jul 2022

Cited by 1 | Viewed by 2193

Abstract

We used Global Navigation Satellite System (GNSS) radio occultation (RO) temperature, density, and bending angle profiles to monitor tropical atmospheric anomalies during the January–February 2009 sudden stratospheric warming (SSW) event on a daily basis. We constructed RO anomaly profiles (tropical mean (30°S–30°N)) and gridded mean anomalies, as well as tropopause height and temperature anomalies. Based on the anomalies, we investigated the response time and region of the tropical atmosphere to SSW. It was found that the GNSS RO data were robust in monitoring tropical atmospheric anomalies during SSW. The tropical stratosphere revealed cooling simultaneously with polar stratospheric warming, although the magnitudes of the maximum tropical mean anomalies were 6–7 times smaller than the polar mean. Altitude variations showed that tropical stratospheric anomalies were largest within 35–40 km, which were 5 km higher than those in the polar region. On the onset day of 23 January, temperature anomalies over 0–30°N were mostly more than −5 K, which were larger than those of −2 K detected over the 0–30°S band, and the largest anomalies were detected over northern Africa with values more than −10 K. RO density and bending angle anomalies responded to SSW in a similar way as temperature but were 20 km higher. Following cooling, the tropical upper stratosphere and lower mesosphere revealed visible warming, with anomalies more than 10 K in the sector of 15°S–15°N. Tropopause anomalies revealed the largest variations over 20°N–30°N, further confirming that the extratropical region of the northern hemisphere is a key region for the dynamical coupling between the polar and tropical regions. Tropopause height anomalies had clear increase trends from 16 January to 8 February, with anomalies of the 20°N–30°N band that were −2 km on Jan 16 and increased to −0.5 km on Feb 6 with a variation of 1.5 km, while variations in other bands were within 0.5 km. Tropopause temperature anomalies had clear decrease trends over the same period, with anomalies at 20°N–30°N of 4 K on 16 January and decreasing to about −1 K on 8 February, while anomalies in other bands showed variations within 3 K. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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18 pages, 6645 KiB

Open AccessArticle

COSMIC-2 RO Profile Ending at PBL Top with Strong Vertical Gradient of Refractivity

by Xu Xu and Xiaolei Zou

Remote Sens. 2022, 14(9), 2189; https://doi.org/10.3390/rs14092189 - 3 May 2022

Cited by 2 | Viewed by 2047

Abstract

The Formosa Satellite-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (Satellite-7/COSMIC-2), which was successfully launched on 25 June 2019, provides dense radio occultation (RO) observations over the tropics and subtropics. This study examines the RO-observed lowest altitude and its possible relationship to refractivity gradients and planetary boundary layer (PBL) heights. COSMIC-2 RO data over the Southeast Pacific region (SEP) and the South-Central Pacific (SCP) from August 2020 are employed to determine their RO-observed lowest altitudes, and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data are used to obtain the gradients of refractivity. Results show that there are no ray perigees below the PBL top when the vertical gradient of

N - N (r)

is strong (<−65 N-unit km⁻¹), where

N (r)

represents the vertical profile of the spherically symmetric refractivity. Significantly strong local vertical gradients due to atmospheric ducting occur more frequently over the SEP than the SCP areas. For some cases, a strong local horizontal gradient of refractivity in the tangent direction of a ray near its perigee point can also limit the RO profile from going further below even when the vertical gradient of

N - N (r)

is relatively weak. Fortunately, only about 0.6% COSMIC-2 RO profiles are unaffected by the above factors but cannot observe below 2-km altitude. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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26 pages, 6668 KiB

Open AccessArticle

Evaluation of Forward Models for GNSS Radio Occultation Data Processing and Assimilation

by Nan Deng, Weihua Bai, Yueqiang Sun, Qifei Du, Junming Xia, Xianyi Wang, Congliang Liu, Yuerong Cai, Xiangguang Meng, Cong Yin, Feixiong Huang, Peng Hu, Guangyuan Tan and Xiaoxu Liu

Remote Sens. 2022, 14(5), 1081; https://doi.org/10.3390/rs14051081 - 23 Feb 2022

Cited by 3 | Viewed by 2356

Abstract

In radio occultation (RO) data processing and data assimilation, the forward model (FM) is used to calculate bending angle (BA) from refractivity (N). The accuracy and precision of forward modeled BA are affected by refractivity profiles and FM methods, including Abel integral algorithms (direct, exp, exp_T, linear) and methods of interpolating refractivity during integral (log-cubic spline and log-linear). Experiment 1 compares these forward model methods by comparing the difference and relative difference (RD) of the experimental value (forward modeled ECMWF analysis) and the true value (BA of FY3D RO data). Results suggested that the exp with log-cubic spline (log-cubic) interpolation is the most accurate FM because it has better integral accuracy (less than 2%) to inputs, especially when the input is lower than an order of magnitude of 1 × 10⁻² (that is, above 60 km). By contrast, the direct induced a 10% error, and the improvement of exp T to exp is limited. Experiment 2 simulated the exact errors of an FM (exp) based on inputs on different vertical resolutions. The inputs are refractivity profiles on model levels of three widely used analyses, including ECMWF 4Dvar analysis, final operational global analysis data (FNL), and ERA5. Results demonstrated that based on exp and log-cubic interpolation, BA on model level of ECMWF 4Dvar has the highest accuracy, whose RD is 0.5% between 0–35 km, 4% between 35–58 km, and 1.8% between 58–80 km. By contrast, the other two analyses have low accuracy. This paper paves the way to better understanding the FM, and simulation errors on model levels of three analyses can be a helpful FM error reference. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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14 pages, 8489 KiB

Open AccessArticle

Noise Floor and Signal-to-Noise Ratio of Radio Occultation Observations: A Cross-Mission Statistical Comparison

by Michael Gorbunov, Vladimir Irisov and Christian Rocken

Remote Sens. 2022, 14(3), 691; https://doi.org/10.3390/rs14030691 - 1 Feb 2022

Cited by 5 | Viewed by 2157

Abstract

Multiple radio occultation (RO) missions are currently providing observations that are assimilated by the world’s leading numerical weather prediction centers. These RO missions use the same signals originating from the Global Navigation Satellite Systems (GNSS), but they have different satellite designs and sizes with different antennas and receivers. This results in different noise levels for different missions. Although the amplitude data are characterized by the Signal-to-Noise Ratio (SNR), the noise, to which they are normalized, is not the real Noise Floor (NF) of the RO observations. We study the statistical distributions of the SNR and NF for RO missions including COSMIC, COSMIC2, METOP-A, METOP-B, METOP-C, and Spire. We demonstrate that different missions have different NF values and different NF and SNR distributions, sometimes multimodal. We propose to use the most probable NF value as an SNR normalization constant in order to compare the SNR values from different RO missions. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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25 pages, 5049 KiB

Open AccessArticle

Impacts of Orbital and Constellation Parameters on the Number and Spatiotemporal Coverage of LEO-LEO Occultation Events

by Congliang Liu, Gottfried Kirchengast, Yueqiang Sun, Veronika Proschek, Xin Wang, Longfei Tian, Qifei Du, Weihua Bai, Chunjun Wu, Peng Hu and Guangyuan Tan

Remote Sens. 2021, 13(23), 4849; https://doi.org/10.3390/rs13234849 - 29 Nov 2021

Cited by 7 | Viewed by 2628

Abstract

The development of small-satellite technologies allows the low Earth orbit intersatellite link (LEO-LEO) occultation method to observe the Earth’s atmosphere with global coverage and acceptable costs using electromagnetic signals, in which the L/X/K/M band and short-wave infrared band signals have been well demonstrated to be suitable. We hence need to investigate the impacts of orbital and constellation parameters on the number and spatiotemporal distribution of LEO-LEO occultation events for best-possible LEO-LEO occultation mission design and optimization at the targeted mission size. In this study, firstly, an occultation events location simulation model accounting for the right ascension of the ascending node (RAAN) precession was set up and the concept of a time-dependent global coverage fraction of occultation events was defined. Secondly, numerical experiments were designed to investigate the orbital parameters’ impacts and to assess the performance of LEO-LEO occultation constellations, in which the Earth is divided into 5° × 5° latitude and longitude cells. Finally, the number, timeliness, and global coverage fraction of occultation events for two-orbit and multi-orbit LEO-LEO constellations were calculated and analyzed. The results show that: ① the orbit inclination and RAAN are the main impacting parameters followed by orbital height, while the RAAN precession is a relevant modulation factor; ② co-planar counter-rotating receiving and transmitting satellite orbits are confirmed to be ideal for a two-satellite LEO-LEO constellation; ③ polar and near-polar orbit constellations most readily achieve global coverage of occultation events; near-equator orbit constellations with supplementary receiving and transmitting satellite orbit planes also readily form the occultation event geometry, though the occultation events are mainly distributed over low and low-to-middle latitude zones; and ④ a well-designed larger LEO-LEO occultation constellation, composed of 36–72 satellites, can meet the basic requirements of global numerical weather prediction for occultation numbers and timeliness, yielding 23,000–38,000 occultation events per day and achieving 100% global coverage in 12–18 h. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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21 pages, 10458 KiB

Open AccessArticle

A High Latitude Model for the E Layer Dominated Ionosphere

by Sumon Kamal, Norbert Jakowski, Mohammed Mainul Hoque and Jens Wickert

Remote Sens. 2021, 13(18), 3769; https://doi.org/10.3390/rs13183769 - 20 Sep 2021

Cited by 2 | Viewed by 2240

Abstract

Under certain conditions, the ionization of the E layer can dominate over that of the F2 layer. This phenomenon is called the E layer dominated ionosphere (ELDI) and occurs mainly in the auroral regions. In the present work, we model the variation of the ELDI for the Northern and Southern Hemispheres. Our proposed Neustrelitz ELDI Event Model (NEEM) is an empirical, climatological model that describes ELDI characteristics by means of four submodels for selected model observables, considering the dependencies on appropriate model drivers. The observables include the occurrence probability of ELDI events and typical E layer parameters that are important to describe the propagation medium for High Frequency (HF) radio waves. The model drivers are the geomagnetic latitude, local time, day of year, solar activity and the convection electric field. During our investigation, we found clear trends for the model observables depending on the drivers, which can be well represented by parametric functions. In this regard, the submodel NEEM-N characterizes the peak electron density

N m E

of the E layer, while the submodels NEEM-H and NEEM-W describe the corresponding peak height

h m E

and the vertical width

w v E

of the E layer electron density profile, respectively. Furthermore, the submodel NEEM-P specifies the ELDI occurrence probability

% E L D I

. The dataset underlying our studies contains more than two million vertical electron density profiles covering a period of almost 13 years. These profiles were derived from ionospheric GPS radio occultation observations on board the six COSMIC/FORMOSAT-3 satellites (Constellation Observing System for Meteorology, Ionosphere and Climate/Formosa Satellite Mission 3). We divided the dataset into a modeling dataset for determining the model coefficients and a test dataset for subsequent model validation. The normalized root mean square deviation (NRMS) between the original and the predicted model observables yields similar values across both datasets and both hemispheres. For NEEM-N, we obtain an NRMS varying between 36.1% and 47.1% and for NEEM-H, between 6.1% and 6.3%. In the case of NEEM-W, the NRMS varies between 38.5% and 41.1%, while it varies between 56.5% and 60.3% for NEEM-P. In summary, the proposed NEEM utilizes primary relationships with geophysical and solar wind observables, which are useful for describing ELDI occurrences and the associated changes of the E layer properties. In this manner, the NEEM paves the way for future prediction of the ELDI and of its characteristics in technical applications, especially from the fields of telecommunications and navigation. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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20 pages, 8783 KiB

Open AccessArticle

Evaluation of Operational Monsoon Moisture Surveillance and Severe Weather Prediction Utilizing COSMIC-2/FORMOSAT-7 Radio Occultation Observations

by Yu-Chun Chen, Chih-Chien Tsai, Yi-chao Wu, An-Hsiang Wang, Chieh-Ju Wang, Hsin-Hung Lin, Dan-Rong Chen and Yi-Chiang Yu

Remote Sens. 2021, 13(15), 2979; https://doi.org/10.3390/rs13152979 - 28 Jul 2021

Cited by 5 | Viewed by 2306

Abstract

Operational monsoon moisture surveillance and severe weather prediction is essential for timely water resource management and disaster risk reduction. For these purposes, this study suggests a moisture indicator using the COSMIC-2/FORMOSAT-7 radio occultation (RO) observations and evaluates numerical model experiments with RO data assimilation. The RO data quality is validated by a comparison between sampled RO profiles and nearby radiosonde profiles around Taiwan prior to the experiments. The suggested moisture indicator accurately monitors daily moisture variations in the South China Sea and the Bay of Bengal throughout the 2020 monsoon rainy season. For the numerical model experiments, the statistics of 152 moisture and rainfall forecasts for the 2020 Meiyu season in Taiwan show a neutral to slightly positive impact brought by RO data assimilation. A forecast sample with the most significant improvement reveals that both thermodynamic and dynamic fields are appropriately adjusted by model integration posterior to data assimilation. The statistics of 17 track forecasts for typhoon Hagupit (2020) also show the positive effect of RO data assimilation. A forecast sample reveals that the member with RO data assimilation simulates better typhoon structure and intensity than the member without, and the effect can be larger and faster via multi-cycle RO data assimilation. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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25 pages, 10020 KiB

Open AccessArticle

Supervised Detection of Ionospheric Scintillation in Low-Latitude Radio Occultation Measurements

by Vinícius Ludwig-Barbosa, Thomas Sievert, Anders Carlström, Mats I. Pettersson, Viet T. Vu and Joel Rasch

Remote Sens. 2021, 13(9), 1690; https://doi.org/10.3390/rs13091690 - 27 Apr 2021

Cited by 9 | Viewed by 2508

Abstract

Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high-quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatology studies for more than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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15 pages, 1082 KiB

Open AccessTechnical Note

A Comparison of Sporadic-E Occurrence Rates Using GPS Radio Occultation and Ionosonde Measurements

by Rodney A. Carmona, Omar A. Nava, Eugene V. Dao and Daniel J. Emmons

Remote Sens. 2022, 14(3), 581; https://doi.org/10.3390/rs14030581 - 26 Jan 2022

Cited by 13 | Viewed by 2092

Abstract

Sporadic-E (

E_{s}

) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques [...] Read more.

Sporadic-E (

E_{s}

E_{s}

formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate

E_{s}

occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site and then combined to determine the most accurate GPS-RO technique for two thresholds on sporadic-E intensity: no lower limit and fbEs

\geq 3

MHz. Overall, the Yu

S_{4}

method shows the closest agreement with ionosonde measurements for total

E_{s}

occurrence rates without a lower limit on intensity, while the phase-based Chu technique shows the closest agreement for fbEs

\geq 3

MHz. This analysis demonstrates that the variation in GPS-RO derived sporadic-E occurrence rates is due to varying thresholds on the sporadic-E intensities in terms of fbEs. Full article

(This article belongs to the Special Issue Radio Occultations for Numerical Weather Prediction, Ionosphere, and Space Weather)

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