Radio Occultation Research Articles

A novel neural network model of Earth’s topside ionosphere

The Earth’s ionosphere affects the propagation of signals from the Global Navigation Satellite Systems (GNSS). Due to the non-uniform coverage of available observations and complicated dynamics of the region, developing accurate models of the ionosphere has been a long-standing challenge. Here, we present a Neural network-based model of Electron density in the Topside ionosphere (NET), which is constructed using 19 years of GNSS radio occultation data. The NET model is tested against in situ measurements from several missions and shows excellent agreement with the observations, outperforming the state-of-the-art International Reference Ionosphere (IRI) model by up to an order of magnitude, especially at 100-200 km above the F2-layer peak. This study provides a paradigm shift in ionospheric research, by demonstrating that ionospheric densities can be reconstructed with very high fidelity. The NET model depicts the effects of numerous physical processes governing the topside dynamics and can have wide applications in ionospheric research.

Estimation of Moist Atmospheric Profiles from Refraction and Attenuation Measurements by Using Centimeter and Millimeter Wave Links between LEO Satellites

Microwave occultation using centimeter and millimeter wave links between low Earth orbit (LEO) satellites provide a potential way to estimate the moist atmospheric profiles based on refraction and attenuation measurements, which is called the LEO-LEO microwave occultation (LMO) technique. It has not yet been implemented in orbit. In this paper, we analyzed the attenuation properties at different heights of centimeter and millimeter waves based on simulations. The observing capabilities with different frequency combinations at the X, K, and M bands were analyzed. The results show that LMO may improve the retrieval accuracy of bending angles above 35 km. By using several appropriate frequencies at the X+K+M band, water vapor profiles from the near-surface to the lower stratosphere (~24 km) can be obtained. When the M-band frequencies were added, the temperature retrieval accuracy does not change obviously, but the accuracy of water vapor retrieval can significantly improve above 15 km, especially at about 17–24 km, and the RMS errors decrease from over 20% to less 10%. For promoting the LMO mission in the real world, a frequency combination at the X+K band is proposed, which can provide the potential to observe the temperature profiles at about 2.5–50 km and water vapor profiles at about 2.5–15 km accurately under clear and cloudy conditions. This study demonstrates that LMO can greatly extend the capabilities of the radio occultation technique and improve our ability to measure the moist atmospheric profiles globally.

Extreme Heights of 15 January 2022 Tonga Volcanic Plume and Its Initial Evolution Inferred from COSMIC-2 RO Measurements

The Hunga Tonga–Hunga Ha’apai underwater volcano (20.57° S, 175.38° W) violently erupted on 15 January 2022. The volcanic cloud’s top height and initial evolution are delineated by using the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)-2 radio occultation (RO) measurements. The bending angle (BA) anomaly over the Tonga volcanic plume (within 200 km of the eruption center) at 5:17 UTC on 15 January showed a prominent peak at higher stratospheric heights. The top of the BA anomaly revealed that negative to positive change occurred at ~38 km, indicating the first height where the RO line-of-sight encountered the volcanic plume. The BA anomaly further revealed an increase of ~50% at ~36.1 km, and confirmed that the volcanic plume reached above ~36 km. Furthermore, the evolution of BA perturbations within 24 h after the initial explosion is also discussed herein. From collocated RO profiles with the volcanic plume, we can find a clear descent of the peak altitude of the BA perturbation from ~36.1 km to ~29 km within 24 h after the initial eruption. The results from this study will provide some insights into advancing our understanding of volcanic cloud dynamics and their implementation in volcanic plume modeling.

Improving the Wet Refractivity Estimation Using the Extremely Learning Machine (ELM) Technique

Constructing accurate models that provide information about water vapor content in the troposphere improves the reliability of numerical weather forecasts and the position accuracy of low-cost Global Navigation Satellite System (GNSS) receivers. However, developing models with high spatial-temporal resolution demands compact observational datasets in the regions of interest. Empirical models, such as the Global Pressure and Temperature 3 (GPT3w), have been constructed based on the monthly averaged outputs of numerical weather models. These models are based on the assimilation of existing measurements to provide estimations of atmospheric parameters. Therefore, their accuracy may be reduced over regions with a low resolution of radiosonde or continuous GNSS stations. By emerging and increasing the Low-Earth-Orbiting (LEO) satellites that measure atmospheric parameter profiles using the Radio Occultation (RO) technique, new opportunities have appeared to acquire high-resolution atmospheric observations at different altitudes. This study aims to apply these RO observations to improve the accuracy of the GPT3w model over Iran, which is sparse in terms of long-term GNSS and radiosonde measurements. The temperature, pressure, and water vapor pressure parameters from the GPT3w model have been used as the input layers of the Extremely Learning Machine (ELM) technique. The wet refractivity indices from the RO technique are considered target parameters in the output layer to train the ELM. The RO observations of 2007–2020 are applied for training, and those of 2020–2022 for evaluating the performance of the developed ELM. Our numerical results indicate that the developed ELM decreases the Root-Mean-Square Error (RMSE) values of the wet refractivity indices by about 17 percent, compared to the original GPT3w RMSE values. Additionally, the wet refractivity indices from ELM have revealed correlation coefficients of about 0.64, which is about 1.9 times those related to the original GPT3w model. The performance of ELM has also been examined by comparison with the data of six located radiosonde stations covering the year 2020. This comparison shows an improvement of about 14 percent in the average RMSE values of the estimated wet refractivity indices.

Statistical validation of ionospheric electron density profiles retrievals from GOES geosynchronous satellites

In this paper, we discuss a novel retrieval of ionospheric electron density profiles using the Radio Occultation (RO) technique applied to measurements captured by the Global Positioning System (GPS) receivers onboard two Geostationary Operational Environmental Satellites (GOES). The GOES satellites operate at ~35,800 km altitude and are primarily weather satellites that operationally contribute continuous remote-sensing data for real-time weather forecasting, as well as near-Earth environment monitoring and Sun observations. The GPS receivers onboard GOES-16 and GOES-17 satellites can track GPS signals propagated through the Earth’s atmosphere, and although the receivers are primarily designed for navigation and station-keeping maneuvers, these GPS measurements that traverse the Earth’s atmosphere can be used to retrieve the ionospheric electron density profiles. This process poses a range of technical challenges. GOES RO links are different from the traditional low Earth orbit (LEO) RO geometry since the receiver is located in an orbit that is higher in altitude than the GPS constellation of transmitters. Additionally, the GPS receivers onboard GOES satellites provide only single-frequency GPS L1 observations and have clocks much less stable than those typically used for RO measurements. The geographical distribution of the retrieved GEO-based RO profiles was found to be uniquely constrained and repeatable based on the relative geostationary fixed positions in the Earth-Centered Earth Fixed reference frame with respect to the GPS constellation orbiting at lower altitude, and significantly different from the coverage patterns of LEO-based RO missions. We demonstrate the successful application of the proposed RO profiling technique with a statistically significant set of GPS observations from GOES-16 and GOES-17 satellites over several years of data collection. This enabled us to retrieve more than 10,000 ionospheric electron density profiles with a maximum altitude of up to 1000–2000 km, much higher than any existing LEO-based RO mission. We demonstrate good performance of GEO-based RO measurements for properly specifying the vertical distribution of ionospheric plasma density by comparing the profiles dataset from the GOES RO experiment with independent reference observations – ground-based ionosondes and LEO-based RO missions, as well as model simulation results provided by the empirical International Reference Ionosphere model. Over multiple years of observations, statistical analysis of discrepancies between the ionospheric F2 layer peak parameters (peak density and height) derived from geosynchronous GOES observations and reference measurements was conducted. This analysis reveals a very good agreement between GOES RO electron density profiles and independent types of measurements in both the F2 peak and the profile shape.

An Empirical Model of the Sporadic E Layer Intensity Based on COSMIC Radio Occultation Observations

AbstractIonospheric sporadic E layers are common phenomena occurring in the ionospheric E region altitude (∼90–120 km) with much higher electron density. The lack of a large amount of sporadic E layer intensity observation on a global scale restrains the construction of global modeling of sporadic E layer intensity. Recent studies reveal that radio occultation observation can be used for sporadic E layer intensity inversion. In this paper, a low‐mid latitude empirical model of sporadic E layer critical frequency is constructed based on Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation data during 2007–2012. Model results show good accordance with ionosonde observations over 16 stations in different latitudes. In general, the model has a good performance in simulating the climate variation features of sporadic E layer intensity with averaged deviation 0.23 MHz which indicates a slight overestimation. Besides, spatial and temporal variations simulated by the model are also analyzed and show good agreement with known sporadic E layer features. However, the empirical may be only suitable for climate research at present and potential methods to improve the model will be investigated in the latter research.

A Low‐Latitude Three‐Dimensional Ionospheric Electron Density Model Based on Radio Occultation Data Using Artificial Neural Networks With Prior Knowledge

AbstractThe accurate estimation of electron density in the ionosphere is crucial for various applications including remote sensing systems, communication, satellite positioning, and navigation. Previous ionospheric models using artificial neural networks (ANN) are only data‐driven, whose effects are entirely affected by observational data. In this paper, we utilize the results of International Reference Ionosphere (IRI)‐2016 as prior knowledge to develop a low‐latitude (30°N–30°S) three‐dimensional ionospheric electron density model using ANN, namely ANN‐IRI, based on COSMIC radio occultation ionospheric profiles during 2006–2020. The prior knowledge helps ANN‐IRI get a better prediction effect and obtain convergence more quickly. The COSMIC data sets above the altitude 150 km are divided into three sets, a training set (2006–2014 and 2018–2020), a validation set (2016), and a test set (2015 and 2017). For the test set, ANN‐IRI shows a good performance for predicting the electron density, better than ANN (without prior knowledge) and IRI‐2016. And ANN‐IRI behaves better during quiet than disturbed times as well as during low solar activity than high solar activity years. In addition, we corrected effectively the error of ANN‐IRI in the lower ionosphere source from COSMIC data based on IRI‐2016 and spline interpolation. Compared with completely independent data sets from incoherent scatter radars (ISRs) and ROCSAT‐1 in situ observations, the electron density predicted by corrected ANN‐IRI exhibits good similarity. Generally, ANN‐IRI behaves better than ANN and IRI‐2016 for predicting electron density. Our work demonstrates a new possibility of applying deep learning methods with prior knowledge to a broader field of geosciences, particularly for problems of prediction.

Ionospheric Tomography: A Compressed Sensing Technique Based on Dictionary Learning

GNSS (Global Navigation Satellite System) observation insufficiency limits the development of the voxel-based computerized ionospheric tomography (CIT) technique. Electron densities of voxels without observation cannot be accurately estimated by the commonly used algebraic reconstruction techniques. In this study, we proposed a compressed sensing technique (CST) based on dictionary learning for ionospheric tomography. Specifically, the K-SVD (singular value decomposition) algorithm was used for dictionary learning based on training sets that are derived from the NeQuick model, hereafter referred to as the CST_NeQuick algorithm. K-SVD uses the orthogonal matching pursuit (OMP) for sparse coding and the SVD approach for dictionary updating. Both simulations and real experiments demonstrated the feasibility and superiority of the CST algorithm when compared to the widely used multiplicative algebraic reconstruction technique (MART). It was found that the CST_NeQuick algorithm’s tomographic performances were mostly superior to those of the MART algorithm in comparison with the independent slant total electron content (STEC) references. Another CST-based tomographic experiment was performed by using the MART-based solutions for dictionary learning, hereafter referred to as the CST_MART algorithm. It showed that the CST_MART algorithm can reduce the average root mean square (RMS) of the CIT-derived STEC by 37.3 % and 20.2 %, respectively, when compared to the MART and CST_NeQuick algorithms. Besides, the CST_MART algorithm’s electron density profiles also showed more agreement with the electron density profiles that were derived from radio occultation data.

A Machine Learning Approach for Air-Quality Forecast by Integrating GNSS Radio Occultation Observation and Weather Modeling

Air-quality monitoring and forecasting are crucial for atmosphere pollution control and management. We propose an innovative data-driven framework for air quality index (AQI) prediction by integrating GNSS radio occultation (GNSS-RO) observation and weather modeling. Empowered by the state-of-the-art machine learning approach, our method can effectively predict regional AQI with a comparable accuracy much more quickly than the traditional numerical modeling and simulation approach. In a real case study using a representative region of China, our data-driven approach achieves a 2000 times speedup; meanwhile, the prediction error measured by rRMSE is only 2.4%. We investigate further the effects of different models, hyperparameters, and meteorological factors on the performance of our AQI prediction framework, and reveal that wind field and atmospheric boundary-layer height are important influencing factors of AQI. This paper showcases a direct application of GNSS-RO observation in assisting in forecasting regional AQI. From a machine learning point of view, it provides a new way to leverage the unique merits of GNSS atmospheric remote sensing technology with the help of the more traditional weather forecasting modeling approach.

Ganymede's Ionosphere Observed by a Dual‐Frequency Radio Occultation With Juno

AbstractIn June 2021, the Juno spacecraft executed a close flyby of Ganymede. During the encounter, Juno passed behind Ganymede for 15 min as observed from Earth, providing the geometry to conduct a radio occultation experiment to probe Ganymede's tenuous ionosphere. X‐band and Ka‐band radio links were transmitted from Juno to antennas at the Deep Space Network. Electrons encountered along the radio propagation path advance the signal's phase and a linear combination the two frequencies allows for a direct measurement of the electron content along the propagation path. On occultation ingress, an ionosphere peak of 2,000 ± 500 (1‐σ) cm−3 near the surface was observed. On occultation egress, no statistically significant ionosphere was detected. Ingress observation viewed where Ganymede's intrinsic magnetic field lines are open whereas egress observation viewed where the field lines are closed, implying electron impact ionization plays a key role in the generation of the ionosphere.

Equatorial waves resolved by balloon-borne Global Navigation Satellite System radio occultation in the Strateole-2 campaign

Abstract. Current climate models have difficulty representing realistic wave–mean flow interactions, partly because the contribution from waves with fine vertical scales is poorly known. There are few direct observations of these waves, and most models have difficulty resolving them. This observational challenge cannot be addressed by satellite or sparse ground-based methods. The Strateole-2 long-duration stratospheric superpressure balloons that float with the horizontal wind on constant-density surfaces provide a unique platform for wave observations across a broad range of spatial and temporal scales. For the first time, balloon-borne Global Navigation Satellite System (GNSS) radio occultation (RO) is used to provide high-vertical-resolution equatorial wave observations. By tracking navigation signal refractive delays from GPS satellites near the horizon, 40–50 temperature profiles were retrieved daily, from balloon flight altitude (∼20 km) down to 6–8 km altitude, forming an orthogonal pattern of observations over a broad area (±400–500 km) surrounding the flight track. The refractivity profiles show an excellent agreement of better than 0.2 % with co-located radiosonde, spaceborne COSMIC-2 RO, and reanalysis products. The 200–500 m vertical resolution and the spatial and temporal continuity of sampling make it possible to extract properties of Kelvin waves and gravity waves with vertical wavelengths as short as 2–3 km. The results illustrate the difference in the Kelvin wave period (20 vs. 16 d) in the Lagrangian versus ground-fixed reference and as much as a 20 % difference in amplitude compared to COSMIC-2, both of which impact estimates of momentum flux. A small dataset from the extra Galileo, GLONASS, and BeiDou constellations demonstrates the feasibility of nearly doubling the sampling density in planned follow-on campaigns when data with full equatorial coverage will contribute to a better estimate of wave forcing on the quasi-biennial oscillation (QBO) and improved QBO representation in models.

The three-dimensional plasma structures and flows of the Earth’s upper atmosphere due to the Moon’s gravitational force

The semidiurnal (12.42 h) and semimonthly (14.76 days) lunar tides have been well-known by fishermen for several centuries. The gravitational force of the relative positions between the Sun, the Moon, and the Earth results in two symmetrical tidal bulges (double bulges) appearing at equatorial latitudes directly under and opposite the Moon. We utilize ionospheric GNSS (Global Navigation Satellite System) radio occultation soundings to show the global three-dimensional structures and dynamics of the double bulges of ionospheric lunar tides for the first time. The double-bulge amplitude of ionospheric F2-peak height hmF2, lagging the sublunar or antipodal point by about 2–3 h, is about 3–5 km at the equator and 1.5–2.0 km at ± 35° magnetic latitude. The electron density further depicts global three-dimensional plasma flows in the ionosphere.

Tropical Cyclone Planetary Boundary Layer Heights Derived from GPS Radio Occultation over the Western Pacific Ocean

According to GPS radio occultation data from previous studies, the height of the planetary boundary layer (PBLH) is defined as the altitude at which the vertical gradient of refractivity N is at its local minimum, called the gradient approach. As with its density, the atmosphere’s refractivity falls broadly exponentially with height. The spherically symmetric refractivity Nss(r) was established to account for the standard deviation of atmospheric refractivity with altitude. Ni is the residual from the fundamental vertical variations of refractivity, defined as Ni(r) = N(r) − Nss(r). In this study, the vertical gradient of N is replaced by the vertical gradient of Ni to optimize the gradient approach, called the local gradient approach. Using the US radiosonde and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultations (ROs) data from 2007–2011, these two PBLH-determining approaches are evaluated. The PBLHs estimated by the gradient approach and the local gradient approach have RMSE values of 0.73 km and 0.65 km, respectively. The PBLH obtained by the local gradient approach is closer to the radiosonde-derived value. In this paper, the COSMIC-2 ROs data and the western Pacific typhoon best track data are collocated in time and space during 2020–2021, and the axisymmetric composite structural characteristics of the tropical cyclone (TC) PBLs are analyzed. The lowest vertical gradients of N and Ni of TCs correspond closely with the average PBLHs. We find that the mean PBLHs of tropical depressions (TD), tropical storms (TS), and typhoons (TY) all have their local maxima at a radial distance of 125 km with heights of 1.03 km, 1.12 km, and 1.36 km, respectively. After 375 km, 575 km, and 935 km of TD, TS, and TY radial distances, the mean PBLHs become stable and cease to vary. The mean PBLH undulations increase significantly with the increase in tropical cyclone intensity. Niwet is the residual from the fundamental vertical variations of wet refractivity, defined as Niwet(r) = Nwet(r) − Nsswet(r). Local minima of Niwet and Ni vertical gradients of TD, TS, and TY have comparable distributions and are concentrated between 0.5 km and 1 km.

Deriving Ionospheric Sporadic E Intensity From FORMOSAT‐3/COSMIC and FY‐3C Radio Occultation Measurements

AbstractThe total electron content (TEC) profiles from the FORMOsa SATellite mission‐3/Constellation Observing System for the Meteorology, Ionosphere, and Climate (COSMIC) and the Fengyun‐3C (FY‐3C) radio occultation (RO) missions during 2006 and 2019 are used to establish the models for deriving the ionospheric sporadic E (Es) critical frequency (foEs). Smax is derived as the maximum vertical gradient of TEC disturbance, which is extracted from a RO TEC profile using the singular spectrum analysis method. Three candidate conversion models are obtained by fitting Smax with foEs observed by collocated ionosondes, and the one with the best performance, the COSMIC&FY‐3C (CF) model, is applied for deriving foEs (foEsCF) from the TEC data of the two missions jointly. For comparison, the C model, which is of similar form as the CF model while being established without using the FY‐3C data, is applied for deriving foEs (foEsC) from the COSMIC TEC data only. The validations over four independent ionosonde stations demonstrate that mean improvements of 0.11 MHz (32%) in the absolute bias and 0.24 MHz (17%) in the root mean square error are obtained by foEsCF compared with foEsC. The spatiotemporal distributions of Es intensity during 2015 and 2019, presented respectively by foEsCF and foEsC, are further compared. The CF model provides more abundant and more detailed information about Es intensity distribution, which is most distinct at high latitudes where the contribution of FY‐3C RO TEC data is significant. Our results reveal that with the aging of the COSMIC satellites, FY‐3C TEC data is a valuable supplementary RO data source for Es‐related studies.

Global Sporadic‐E Occurrence Rate Climatology Using GPS Radio Occultation and Ionosonde Data

AbstractAn updated global climatology of blanketing sporadic E (Es) is developed from a combined data set of Global Positioning System (GPS) radio occultation (RO) and ground‐based ionosonde soundings over the period of September 2006–January 2019. A total of 46 sites and 3.2 million total soundings from the Global Ionosphere Radio Observatory network in combination with 3.0 million occultations from the Constellation Observing System for Meteorology, Ionosphere, and Climate constellation are used to calculate global occurrence rates (ORs) for two blanketing frequency thresholds: all blanketing sporadic‐E with no limit on intensity (all‐Es) and moderate‐Eswith fbEs ≥ 3 MHz. Following the GPS‐RO to ionosonde comparison by Carmona et al. (2022),https://doi.org/10.3390/rs14030581the all‐Esrates are calculated using ionosonde data and an amplitude‐based S4threshold for the GPS‐RO data while the moderate‐Esrates use a primarily phase‐based technique. Occurrence rates are separated by intensity, season, month, and solar local time for quiet geomagnetic conditions. Overall, the general geomagnetic trends agree with previous Esclimatologies and the ORs peak near 50% for all‐Esand 25% for moderate‐Esmeasured in the mid‐latitudes during local summer in the late afternoon. Low ORs are observed near the South Atlantic Anomaly and North America, and a general asymmetry is observed between hemispheres with higher ORs in the Northern Hemisphere. High‐latitude and late morning blanketing Esare found to be stronger but less frequent with rates nearly equal to the moderate‐Esmid‐latitude maximums.

Atypically Intense and Delayed Response of the Martian Ionosphere to the Regional Dust Storm of 2016: A Study Using MAVEN Observations and Models

AbstractDuring Mars dust storms, atmospheric heating and expansion moves the ionospheric peak upward. Typically, peak altitude increases by no more than 10 km, and this increase occurs simultaneously with the expansion of the dust storm. However, Felici et al. (2020), https://doi.org/10.1029/2019JA027083, using the Mars Atmosphere Volatile EvolutioN (MAVEN) Radio Occultation Science Experiment (ROSE), reported an unusually large increase of ∼20 km at southern latitudes in early October 2016 during a modest dust storm. Here, we investigate why the ionospheric peak altitude increased so much in these observations. We extend the time series of ionospheric peak altitude values beyond the limited extent of the ROSE observations by applying a one‐dimensional photochemical model, in which neutral atmospheric conditions are based on in situ MAVEN Neutral Gas Ion Mass Spectrometer observations at similar latitudes and solar zenith angles to those observed by ROSE. We find that the ionospheric peak altitude was highest throughout October 2016 yet both the local and global atmospheric dust loading were greatest 1 month earlier. We hypothesize that (a) a portion of the unusually large 20 km enhancement in peak altitude and (b) the unusual delay between the greatest dust loading and the highest peak altitude were both associated with the occurrence of perihelion, which maximizes solar heating of the atmosphere, in late October 2016.

The Absorption Coefficient of Decimeter Radio Waves (~19 cm) in the Earth’s Ionosphere Based on the Inverse Problem Solution in Radio Occultation Satellite Studies during the June 2015 Magnetic Storm

The Absorption Coefficient of Decimeter Radio Waves (~19 cm) in the Earth’s Ionosphere Based on the Inverse Problem Solution in Radio Occultation Satellite Studies during the June 2015 Magnetic Storm

Evaluation for effects of variable Martian upper atmosphere on ionospheric peak electron density based on the MGS RO observation

The Martian ionospheric peak is dominated by photochemical processes at dayside. Its primary variations can be well described by the Chapman theory; nevertheless, deviation still exists between observation and the theory. Some factors may be responsible for that deviation, in which the variable upper atmosphere is an important one. Ionospheric radio occultation (RO) measurement can be used to investigate the effect of the upper atmosphere on the Martian ionosphere, since concurrent variations of the ionospheric peak and the neutral scale height (Hn) can be estimated from RO electron density profiles. In this study, Hn was estimated from the Mars Global Surveyor (MGS) RO observation to quantitatively evaluate the effect of the upper atmosphere on the variability of the peak electron density of the M2 layer (NmM2). That effect manifests in the abilities of solar zenith angle functions for describing NmM2 variability and in the NmM2 deviation from the Chapman theory. Compared with the Chapman function, the simple cosine function is sufficiently accurate for describing dayside NmM2 variation owing to the cold Martian upper atmosphere that consists of heavier molecules, which weakens the spherical effect of planetary atmosphere. Hn variations, especially the longitudinal variation associated with non-migrating tides, are important factors responsible for the NmM2 deviation from the Chapman theory. Statistically, they can cause ∼1.4% average deviation for the condition of the MGS RO measurement. An effective modification method based on available Hn was correspondingly suggested to promote the accuracy of NmM2 estimation based on the Chapman theory. It is notable that Hn variations do not show evident contribution to NmM2 deviation from the Chapman theory in the southern hemisphere, where the stronger crustal magnetic fields likely have dominant contribution to the NmM2 deviation as compared with Hn variations.

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

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.

An Investigation of the Lower Stratospheric Gravity Wave Activity in Tibetan Plateau Based on Multi-GNSS RO Dry Temperature Observations

To understand the activity of gravity waves (GWs) over the Tibetan Plateau (TP) is of great significance for improving global climate models. Considering that the lower stratosphere is the main level of GWs activity, this paper first established a 14-year 2° × 2° longitude–latitude monthly mean GWs model in the lower stratosphere (18~20 km) of the TP by combining post-processed dry temperature profiles provided by the multi-Global Navigation Satellite System (GNSS) radio occultation (RO) missions: The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and the Meteorological Operational (METOP) series polar-orbiting meteorological satellites (METOP-A, METOP-B, and METOP-C) from August 2006 to September 2020. Based on this model, this paper analyzed the characteristics of GWs activity around TP and the effects of topography, background wind, and zonal wind on GWs activity and summarized the general process of topographic wave excitation and upward propagation around TP. The spatial distribution of the lower stratospheric GW Ep is highly correlated with the spatial distribution of background wind and the topography of TP during GWs excitation. The GW Ep is obviously filtered by the zero-speed wind. The change in GW Ep is strongly correlated with the change in topography. These phenomena indicate that the GWs of TP are mainly topographic waves. Moreover, the lower stratospheric GW Ep of TP shows that periodic changes are mainly affected by the periodic background wind, and the GW Ep value is larger in February and smaller in August. The large GW Ep in the lower stratosphere of TP is not only related to the GWs strongly generated by the interaction between the strong background wind and the large elevation or large topographic changes but also related to the strong zonal westerly winds that promote the propagation of GWs upward. Multivariable linear regression models were used to reconstruct the lower stratospheric GW Ep over TP based on the background wind and the zonal wind and a goodness of fit of 81.1% was achieved. It indicates that the GW Ep is dominated by the topographic wave over TP in the lower stratosphere and the background wind has a greater influence on the GWs than the zonal wind.