Radio Occultation Research Articles

Sporadic E Layer Intensification in the Winter of 2009 Examined by FORMOSAT‐3/COSMIC RO Data and GAIA Model

AbstractThis study examines the role of winds in wintertime sporadic E layer intensification (WEsLI) in 2009 from a global viewpoint. Previous studies showed that sporadic E layer (EsL) intensity had increased for 20–30 days in some winters, although intense EsLs do not form generally in winter. A recent study found that vertical ion convergence (VIC) driven by intensified migrating semidiurnal (SW2) tides caused WEsLI at middle latitudes in 2009. However, no studies have investigated the global distributions and generation mechanisms of WEsLI in 2009. Herein, we employed FORMOSAT‐3/COSMIC radio occultations to investigate the global distributions of WEsLI in 2009. Distributions of VIC driven by winds obtained from the Ground‐to‐topside model of Atmosphere and Ionosphere for Aeronomy were compared with global WEsLI distributions to elucidate the role of winds in WEsLI. We found that WEsLI in 2009 occurred at geomagnetic low/middle latitudes except between W and E. WEsLI was observed below 120 km altitudes, especially at 12–17 local times. WEsLI was attributable to VIC driven by SW2 tides, migrating diurnal tides, and eastward propagating diurnal tides with wavenumber 3. Tidal amplifications were possibly related to mesospheric/stratospheric atmospheric variations such as sudden stratospheric warming, zonal mean zonal winds, and quasi‐biennial oscillations. WEsLI in 2009 is further evidence of the coupling between EsLs and mesospheric/stratospheric atmospheric variations through tidal modifications.

Assessment of FY-3E GNOS II Radio Occultation Data Using an Improved Three-Cornered Hat Method

The spatial–temporal sampling errors arising from the differences in geographical locations and measurement times between co-located Global Navigation Satellite System (GNSS) radio occultation (RO) and radiosonde (RS) data represent systematic errors in the three-cornered hat (3CH) method. In this study, we propose a novel spatial–temporal sampling correction method to mitigate the sampling errors associated with both RO–RS and RS–model pairs. We analyze the 3CH processing chain with this new correction method in comparison to traditional approaches, utilizing Fengyun-3E (FY-3E) GNSS Occultation Sounder II (GNOS II) RO data, atmospheric models, and RS datasets from the Hailar and Xisha stations. Overall, the results demonstrate that the improved 3CH method performs better in terms of spatial–temporal sampling errors and the variances of atmospheric parameters, including refractivity, temperature, and specific humidity. Subsequently, we assess the error variances of the FY-3E GNOS II RO, RS and model atmospheric parameters in China, in particular the northern China and southern China regions, based on large ensemble datasets using the improved 3CH data processing chain. The results indicate that the FY-3E GNOS II BeiDou navigation satellite system (BDS) RO and Global Positioning System (GPS) RO show good consistency, with the average error variances of refractivity, temperature, and specific humidity being less than 1.12%2, 0.13%2, and 700%2, respectively. A comparison of the datasets from northern and southern China reveals that the error variances for refractivity are smaller in northern China, while temperature and specific humidity exhibit smaller error variances in southern China, which is attributable to the differing climatic conditions.

Speed and accuracy investigations of neural network algorithms for ionospheric modelling at an equatorial region

Neural networks are very efficient tools for modeling, including ionospheric modeling. The training algorithm is important for achieving the optimum performance of the trained network. This research is therefore meant to evaluate and compare the performances of ten neural network training algorithms based on their prediction accuracies, and the duration/times taken by each of the algorithms to establish the optimum result. The neural networks were trained using electron density measurements by Radio Occultation (RO) technique from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites. Data for the period 2006 through 2021 was used. The networks were trained using about 2.9 million data points collected from the Kano region, Nigeria (5-degree rectangular region around geographic: 12.00° N, 8.59° E) after performing data quality control. The training algorithms considered in the work include: Bayesian Regularization (BR); Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFG); Conjugate Gradient with Powell/Beale (CGB); Fletcher-Reeves Conjugate Gradient (CGF); Gradient descent with momentum and adaptive learning rate (GDX); Levenberg Marquardt (LM); One Step Secant (OSS); Polak-Ribiére Conjugate Gradient (CGP); Resilient Backpropagation (RP); and Scaled Conjugate Gradient (SCG). The results showed that the BR and the LM algorithms gave the best performances in minimizing the errors of prediction (the mean RMSEs are respectively 112 and 114 ×103 electrons/cm3), but the RP algorithm, which came third in terms of accuracy, was significantly faster than both the LM and BR algorithms. The worst-performing algorithm in terms of accuracy was the GDX algorithm, although it was the fastest algorithm. The BFG algorithm was the worst-performing algorithm in terms of a combination of speed and accuracy. The developed neural network model was validated using ionosonde electron density measurements obtained from Ilorin, Nigeria (geographic: 8.5° N, 4.5° E; geomagnetic: 1.8° S). A comparison of the neural network, the NeQuick, and the IRI model predictions relative to the ionosonde measurements indicate that the neural network model was the best-performing model; the NN model predictions minimized the mean absolute errors (MAEs) in ∼44% of 399 ionosonde profiles investigated, the IRI model did so in ∼32%, and the NeQuick did so in ∼24%. The MAEs of the NeQuick however exhibited the best (least) variance. In overall, the NN model gave the least (best) mean of the MAEs (∼73 × 103 cm−3), compared to ∼82 × 103 cm−3 given by both the NeQuick and the IRI models, further supporting the idea that neural networks are excellent for present-day ionospheric modeling.

Planetary Wave Signature in Low Latitude Sporadic E Layer Obtained From Multi‐Mission Radio Occultation Observations

AbstractThe Sporadic E layer or Es is an ionospheric phenomenon characterized by enhancements in electron density within 90–120 km above the Earth's surface. Based on the wind shear theory, the formation of Es layers is associated with vertical shears in the horizontal wind, in the presence of the Earth's magnetic field. This study explores the role of planetary waves on inducing these vertical shears and subsequently shaping Es layers. Our investigations benefit from a large amount of data facilitated by the FORMOSAT‐7/COSMIC2 and Spire missions, which offer extensive global coverage. A wave analysis is applied to the Es intensity as represented by the S4 index derived from radio occultation measurements, in search of potential planetary wave signatures. Additionally, measurements from Aura/MLS are used to analyze corresponding spectra for the geopotential height, enabling a comparative examination of planetary wave signatures in the Es layer and geopotential height variations. The findings reveal westward and eastward wave components with specific wavenumbers and periods, suggesting the involvement of westward propagating quasi 6‐day, quasi 4‐day planetary waves, and eastward propagating Kelvin waves with a period of around 3 days in Es layer formation at low latitudes.

Ensemble Based Estimation of Wet Refractivity Indices Using a Functional Model Approach

AbstractThe estimation of the wet refractivity indices is crucial for applications like weather predictions or improving the accuracy of real‐time positioning techniques. Traditionally, solving the inverse tomography problem to estimate these atmospheric parameters has been challenging due to its ill‐posed nature and high computational demands, necessitating additional constraints. To overcome these challenges, the data assimilation method is proposed here to integrate Global Navigation Satellite System (GNSS) observations into a background model. In this study, the Ensemble Kalman Filter (EnKF) was served as the assimilation core to reduce the computational load and to enable the epoch‐wise estimation of wet refractivity indices. The Global Pressure and Temperature 3 (GPT3w) model was utilized as the background, and wet refractivity indices at each epoch were transformed into B‐spline coefficients, representing state vector parameters. Subsequently, GNSS derived zenith wet delay (ZWD) values were integrated into the model using the EnKF method. The study's region encompassed the western parts of Europe and incorporated approximately 893 GNSS stations. Evaluation spanned from 1 January 2017 to 31 December 2017. The estimated wet refractivity indices from the proposed method were compared with observations from 16 existing radiosonde stations, radio occultation data, and ZWD values from the 47 selected GNSS test stations. Additionally, calculated ZWD values, resulting from the integration of wet refractivity indices, were compared to the ZWD values from 47 test stations in the study region. The numerical results demonstrated that the proposed method achieved a root mean square error value of approximately 2.6 ppm, which was nearly 49% and 18% lower than that of the considered empirical and numerical atmospheric models, respectively.

Seasonal Variation of the Martian Dayside Ionosphere

AbstractThe Martian ionosphere has many similarities and differences compared to Earth, attracting significant attention. This paper utilizes radio occultation data from the Mars Global Surveyor (MGS), Mars Atmosphere and Volatile Evolution Mission (MAVEN), and ESA Mars Express mission (MEX), associated with the measurements from Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) aboard MEX, to investigate the seasonal variation of the Martian dayside ionosphere. Data preprocessing is performed first to isolate the influence of solar zenith angle and solar radiation, the seasonal variation of the Martian dayside ionosphere explored in this study. The results suggest that the peak electron density reaches its minimum and maximum at LS = 70.2° and LS = 250.2°, respectively, with an amplitude of 16.5% concerning the average (LS is referred to as the solar longitude of Mars). The peak altitude experiences its minimum at LS = 78.4° and maximum at LS = 258.4°, and its relative amplitude is 12.1%. The outcomes suggest that the seasonal variations in the Martian ionosphere are primarily attributed to the Mars‐Sun distance change, which is different from the situation on Earth. This study will benefit both Martian ionosphere modeling and Earth’s ionosphere understanding in the future.

Performance assessment of multi-source GNSS radio occultation from COSMIC-2, MetOp-B/C, FY-3D/E, Spire and PlanetiQ over China

Global Navigation Satellite System (GNSS) radio occultation (RO) is one of the most crucial observations in atmospheric and climate science. GNSS RO globally produces accurate and long-term stable vertical profiles for essential climate variables with high vertical resolution in all weather conditions. RO measurements offer global coverage but may be limited for specific regions. Currently, various RO satellite constellation programs have been developed by nations and companies, and the growing quantity of RO observations can contribute not only globally but also has the potential to benefit specific regions, such as China. To investigate the potential of RO observation in China, the performance of five operational RO measurements from COSMIC-2, MetOp-B/C, FY-3D/E, Spire and PlanetiQ on data coverage capabilities and quality are assessed by comparing with ERA5 and radiosonde over China. The results of data coverage showed that all RO missions can acquire extensive coverage over China with effective low-altitude penetration capability, whereas MetOp-B/C exhibits some gaps in local time coverage. The results of data quality confirmed that commercial Spire and PlanetiQ are comparable to those of national-led COSMIC-2, MetOp-B/C and FY3D/E, even though Spire exhibited a lower signal-to-noise ratio (SNR). The mean bending angle and refractivity relative differences of all RO measurements are within ±0.53/1.30 % and ± 0.54/0.28 % (with respect to ERA5/radiosonde) in the altitude range of 5 to 35 km, respectively, and the corresponding relative standard deviations (SD) are less than 2.20/6.99 % and 1.35/1.56 %, respectively. Mean temperature and specific humidity differences of all RO measurements are within ±0.18/0.22 K and ± 0.08/0.22 g/kg, respectively, from the near-surface to 12 km, with SD of less than 1.26/1.67 K and 0.84/0.91 g/kg. Among the five RO missions, FY-3D/E exhibits larger errors in refractivity, temperature and specific humidity. The RO profiles derived from GPS, GLONASS, BeiDou and Galileo show comparable quality at the altitudes below 35 km. These results can help users further understand the capabilities and performance of these RO observations and indicate the application potential of numerous RO profiles from multi-source RO measurements, which is anticipated to enhance numerical weather predictions for China.

A Software Tool for the True Height Analysis of Ionograms Using the Iterative Gradient Correction (IGC) Method

AbstractDeriving the precise true height electron density profile from the measured ionosonde virtual heights is quite a challenging problem. Recently, Ankita and Tulasi Ram (2023, https://doi.org/10.1029/2023RS007808) presented a new method, Iterative Gradient Correction (IGC) method, for true height analysis that uses HF radio wave propagation path computations to reconstruct the true height profile. Through iterative corrections on electron density gradients between successive points, the IGC method minimizes errors below a specified tolerance at each point and reconstructs a complete electron density profile. The derived profiles from the IGC method are found to be accurate when compared with Incoherent Scatter Radar and Global Navigation Satellite System—Radio Occultation observations. To facilitate true height analysis by IGC method for a wider user community, a MATLAB‐based software has been developed and is outlined in this report. The software can be installed on any Windows platform and is designed with a user‐friendly interface for easy and efficient application by the users. It can analyze multiple scaled ionograms in a single run and outputs the real height profiles in ASCII format. Further, the software also captures important ionospheric parameters such as the base altitudes and peak frequencies of E‐ and F‐layers (e.g., hE, hF, foE, and foF2) etc., from the computed true height profiles and tabulates in a separate output file for the ready use. The software also provides the option for extrapolation of true height profile into top‐side ionosphere up to a user‐specified height and reconstructs the complete vertical electron density profile.

Assessment of Commercial GNSS Radio Occultation Performance from PlanetiQ Mission

Global Navigation Satellite System (GNSS) radio occultation (RO) provides valuable 3-D atmospheric profiles with all-weather, all the time and high accuracy. However, GNSS RO mission data are still limited for global coverage. Currently, more commercial GNSS radio occultation missions are being launched, e.g., PlanetiQ. In this study, we examine the commercial GNSS RO PlanetiQ mission performance in comparison to KOMPSAT-5 and PAZ, including the coverage, SNR, and penetration depth. Additionally, the quality of PlanetiQ RO refractivity profiles is assessed by comparing with the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) data in October 2023. Our results ensure that the capability of PlanetiQ to track signals from any GNSS satellite is larger than the ability of KOMPSAT-5 and PAZ. The mean L1 SNR for PlanetiQ is significantly larger than that of KOMPSAT-5 and PAZ. Thus, PlanetiQ performs better in sounding the deeper troposphere. Furthermore, PlanetiQ’s average penetration height ranges from 0.16 to 0.49 km in all latitudinal bands over water. Generally, the refractivity profiles from all three missions exhibit a small bias when compared to ERA5-derived refractivity and typically remain below 1% above 800 hPa.

First Detections of Ionospheric Plasma Density Irregularities from GOES Geostationary GPS Observations during Geomagnetic Storms

In this study, we present the first results of detecting ionospheric irregularities using non-typical GPS observations recorded onboard the Geostationary Operational Environmental Satellites (GOES) mission operating at ~35,800 km altitude. Sitting above the GPS constellation, GOES can track GPS signals only from GPS transmitters on the opposite side of the Earth in a rather unique geometry. Although GPS receivers onboard GOES are primarily designed for navigation and were not configured for ionospheric soundings, these GPS measurements along links that traverse the Earth’s ionosphere can be used to retrieve information about ionospheric electron density. Using the radio occultation (RO) technique applied to GPS measurements from the GOES–16, we analyzed variations in the ionospheric total electron content (TEC) on the links between the GPS transmitter and geostationary GOES GPS receiver. For case-studies of major geomagnetic storms that occurred in September 2017 and August 2018, we detected and analyzed the signatures of storm-induced ionospheric irregularities in novel and promising geostationary GOES GPS observations. We demonstrated that the presence of ionospheric irregularities near the GOES GPS RO sounding field of view during geomagnetic disturbances was confirmed by ground-based GNSS observations. The use of RO observations from geostationary orbit provides new opportunities for monitoring ionospheric irregularities and ionospheric density.

East–West Difference in the Ionospheric Response During the Recovery Phase of May 2024 Super Geomagnetic Storm Over the East Asian

AbstractIn this study, we offer an extensive examination of the F‐region ionospheric disturbances during the May 2024 superstorm, focusing primarily on the middle‐low latitude regions of East Asia. Our analysis is grounded in a wealth of data sources including Total Electron Content (TEC), ionospheric parameters NmF2 and hmF2, Electron Density Profile (EDP) retrieved from Radio Occultation (RO) data, and ∑[O]/[N2] from the Global Ultraviolet Imager (GUVI), among others, complemented by model simulations. The observed negative ionospheric storm effect, characterized by a significant and long‐lasting reduction in electron density across the entire China, commenced immediately following the sudden storm commencement (SSC) on 10 May and continued through the main and early recovery phase of the storm on 11 May. On 11–12 May, positive ionospheric storm impacts were initially observed in a restricted geographical area from the post‐midnight to sunrise, first manifesting over the eastern regions of China and then shifting to the central regions. Subsequently, a pronounced negative storm effect persisted throughout the later stages of recovery phase. In contrast, the western regions of China experienced a positive storm effect on 12 May followed by a comparatively mild negative storm phase. This persistent extensive zonal gradient in electron density across the East Asian region resembles the scenarios depicted in prior superstorms attributed to the thermospheric circulation patterns. The disparity in the ionospheric response from east to west in this area is probably a common feature during superstorms, potentially resulting from an arch‐shaped structure of elevated ∑[O]/[N2].

Development of the Ionospheric E‐Region Prompt Radio Occultation Based Electron Density (E‐PROBED) Model

AbstractThis work reports the development of the first version of the E‐region Prompt Radio Occultation Based Electron Density (E‐PROBED) Model. This is an empirical model of E‐region electron density (Ne) between 90 and 120 km developed using radio occultation measurements from the COSMIC‐1 mission. This first version captures more than 80% of the observed variability in monthly‐mean latitude‐local time‐altitude E‐region Ne profiles but it does not account for longitudinal variability at constant local‐time. This work also reports a validation of E‐PROBED simulations through comparisons with ionosondes and incoherent scatter radar (ISR) E‐region Ne profiles. E‐PROBED generally agrees with these ground‐based observations during day‐time. During night‐time, there is a large disparity between E‐PROBED and ISR values. Finally, this work compares E‐PROBED with E‐region Ne simulated by the International Reference Ionosphere (IRI) and the Specified Dynamics—Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD‐WACCM‐X). One of the main differences amongst these models is on the simulation of variabilities that cannot be attributed to photoionization. IRI barely simulates any variability not driven by photoionization. Both E‐PROBED and SD‐WACCM‐X simulates variability not driven by photoionization. Another main difference is in the absolute magnitude of night‐time E‐region Ne values. Both IRI and SD‐WACCM‐X are substantially lower than E‐PROBED. This work first concludes that E‐PROBED can conveniently provide E‐region Ne latitude—local time variabilities and structures that COSMIC‐1 observes. This work also concludes that E‐region Ne have significant non‐photoionization driven variabilities.

Differences among the total electron content derived by radio occultation, global ionospheric maps and satellite altimetry

In recent years, significant progress has been in ionospheric modeling research through data ingestion and data assimilation from a variety of sources, including ground-based global navigation satellite systems, space-based radio occultation and satellite altimetry (SA). Given the diverse observing geometries, vertical data coverages and intermission biases among different measurements, it is imperative to evaluate their absolute accuracies and estimate systematic biases to determine reasonable weights and error covariances when constructing ionospheric models. This study specifically investigates the disparities among the vertical total electron content (VTEC) derived from SA data of the Jason and Sentinel missions, the integrated VTEC from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and global ionospheric maps (GIMs). To mitigate the systematic bias resulting from differences in satellite altitudes, the vertical ranges of various VTECs are mapped to a standardized height. The results indicate that the intermission bias of SA-derived VTEC remains relatively stable, with Jason-1 serving as a benchmark for mapping other datasets. The mean bias between COSMIC and SA-derived VTEC is minimal, suggesting good agreement between these two space-based techniques. However, COSMIC and GIM VTEC exhibit remarkable seasonal discrepancies, influenced by the solar activity variations. Moreover, GIMs demonstrate noticeable hemispheric asymmetry and a degradation in accuracy ranging from 0.7 to 1.7 TECU in the ocean-dominant Southern Hemisphere. While space-based observations effectively illustrate phenomena such as the Weddell Sea anomaly and longitudinal ionospheric characteristics, GIMs tend to exhibit a more pronounced mid-latitude electron density enhancement structure.

Impact of Atmospheric River Reconnaissance Dropsonde Data on the Assimilation of Satellite Radiance Data in GFS

Abstract Satellites provide the largest dataset for monitoring the earth system and constraining analyses in numerical weather prediction models. A significant challenge for utilizing satellite radiances is the accurate estimation of their biases. High-accuracy nonradiance data are commonly employed to anchor radiance bias corrections. However, aside from the impacts of radio occultation data in the stratosphere, the influence of other types of “anchor” observation data on radiance assimilation remains unclear. This study provides an assessment of impacts of dropsonde data collected during the Atmospheric River (AR) Reconnaissance program, which samples ARs over the northeast Pacific, on the radiance assimilation using the Global Forecast System (GFS) and Global Data Assimilation System at the National Centers for Environmental Prediction. The assimilation of this dropsonde dataset has proven crucial for providing enhanced anchoring for bias corrections and improving the model background, leading to an increase of ∼5%–10% in the number of assimilated microwave radiance in the lower troposphere/midtroposphere over the northeast Pacific and North America. The impact on tropospheric infrared radiance is not only small but also beneficial. Impacts of dropsondes on the use of stratospheric channels are minimal due to the absence of dropsonde observations at certain altitudes, such as aircraft flight levels (e.g., 150 hPa). Results in this study underscore the usefulness of dropsondes, along with other conventional data, in optimizing the assimilation of satellite radiance. This study reinforces the importance of a diverse observing network for accurate weather forecasting and highlights the specific benefits derived from integrating dropsonde data into radiance assimilation processes. Significance Statement This study aims to evaluate the impact of aircraft reconnaissance dropsondes on the assimilation of satellite radiance data, utilizing observations from the 2020 Atmospheric River Reconnaissance program. The key findings reveal a substantial enhancement in the model first guess and improved estimates of radiance biases. Notably, there is a significant 5%–10% increase in microwave radiance observations over the northeastern Pacific and North America, with positive yet modest effects observed in tropospheric infrared radiance. These findings underscore the crucial role of atmospheric river reconnaissance dropsondes as anchor data, enhancing the assimilation of radiance observations. In essence, the inclusion of these dropsondes in routine networks is particularly valuable for optimizing data assimilation in regions with sparse observational data.

The Initial Assessment of Ionospheric Radio Occultation Data of MSS‐1 Satellite and Its Applications in Scintillation Exploration

The Initial Assessment of Ionospheric Radio Occultation Data of MSS‐1 Satellite and Its Applications in Scintillation Exploration

First Results of Airborne GNSS Radio Occultation Sounding From Airbus Commercial Aircraft

AbstractThe lack of high vertical resolution atmospheric thermodynamic structure observations inside or near major weather events impedes our understanding of physical processes and their predictability in numerical weather prediction (NWP) models. Airborne Global Navigation Satellite System (GNSS) radio occultation (airborne radio occultation [ARO]) has proven to be a viable remote sensing option to offer dense soundings near flight tracks. The global fleet of commercial aircraft already equipped with GNSS receivers could be leveraged to produce an unprecedented number of ARO soundings along global flight paths. Eleven cases of atmospheric bending angle and refractivity profiles were successfully retrieved and compared with the colocated European Center for Medium‐Range Weather Forecasting global reanalysis data. Good quality measurements are obtained with median refractivity differences less than 1% in the middle and upper troposphere, between 5.5 and 11.5 km. Given the use of aircraft data (e.g., Aircraft Meteorological DAta Relay) for data assimilation, incorporating ARO profiles would be a valuable addition, further enhancing the accuracy of aviation and weather forecasts.

Characterization of the M1 and M2 layers in the undisturbed Martian ionosphere at a variety of solar conditions with MAVEN ROSE

We utilize data from the MAVEN Radio Occultation Science Experiment (Withers et al., 2020) - with unprecedented coverage in solar zenith angle - to isolate the effects that local time and season induce on the photochemical ionosphere of Mars around solar minimum, leading to solar maximum. 185 out of the 1228 electron density profiles of the Martian undisturbed ionosphere collected by MAVEN ROSE between July 2016 and December 2022 show a distinct M1 layer below the M2 layer. We define undisturbed here as conditions when there are no solar events or dust storms to influence the ionosphere. This allowed us to study the behavior of both the M2 and M1 peak densities and altitudes as a function of solar zenith angle, and, for the first time, to be able to separate these trends by dusk and dawn local time, as well as by southern spring and summer versus southern fall and winter. We find that the M1 layer at small SZA can occur at altitudes lower than 100 km; that the peak altitudes and densities of both the M2 and M1 layers at dawn change more with season than they do at dusk; and that the M2 peak density decreases at a faster rate than the M1 with SZA.

Strong persistent cooling of the stratosphere after the Hunga eruption

The 2022 eruption of the Hunga volcano was a major event that propelled aerosols and water vapor up to an altitude of 53–57 km. It caused an unprecedented stratospheric hydration that is expected to affect composition, thermal structure, circulation and dynamics for years. Using vertically high resolved satellite observations from radio occultation, we focus on the temperature impact in the stratosphere from the eruption in January 2022 until December 2023. Separating the signals of the Hunga eruption from the broader stratospheric variability reveals a strong persistent radiative cooling of up to –4 K in the tropical and subtropical middle stratosphere from early after the eruption until mid-2023, clearly corresponding to the water vapor distribution. Our results provide new insights from observations into both the localized temperature changes and the persistent stratospheric cooling caused by the Hunga eruption and document this exceptional climatic effect not seen for previous volcanic eruptions.

Radio Occultation Modeling Experiment (ROMEX): Determining the Impact of Radio Occultation Observations on Numerical Weather Prediction

Abstract The international radio occultation (RO) community is conducting a collaborative effort to explore the impact of a large number of RO observations on numerical weather prediction (NWP). This effort, the Radio Occultation Modeling Experiment (ROMEX), has been endorsed by the International Radio Occultation Working Group, a scientific working group under the auspices of the Coordination Group for Meteorological Satellites (CGMS). ROMEX seeks to inform strategies for future RO missions and acquisitions. ROMEX is planned to consist of at least one 3-month period during which all available RO data are collected, processed, archived, and made available to the global community free of charge for research and testing. Although the primary purpose is to test the impact of varying numbers of RO observations on NWP, the 3 months of RO observations during the first ROMEX period (ROMEX-1, September–November 2022) will be a rich dataset for research on many atmospheric phenomena. The RO data providers have sent their data to EUMETSAT for processing. The total number of RO profiles averages between 30 000 and 40 000 per day for ROMEX-1. The processed data (phase, bending angle, refractivity, temperature, and water vapor) will be distributed to ROMEX participants by the Radio Occultation Meteorology Satellite Application Facility (ROM SAF). The data will also be processed independently by the UCAR COSMIC Data Analysis and Archive Center (CDAAC) and available via ROM SAF. The data are freely available to all participants who agree to the conditions that the providers be acknowledged, and the data are not used for commercial or operational purposes.

Comparison of tropical cyclone structures over different ocean basins revealed in COSMIC-2 radio occultation observations

Utilizing three-years COSMIC-2 radio occultation (RO) bending angle (BA) observations from 1 October 2019 to 31 December 2022, composite structures of BA anomalies α−α¯env/α¯env in vertical and radial directions are generated for hurricanes, tropical storms and tropical depressions over the ocean basins of North Atlantic, West Pacific, East Pacific, South Pacific, North Indian, and South Indian. The magnitude and altitude of the maximum BA anomaly within hurricanes, tropical storms and tropical depressions are about (6 km, 14%), (5 km, 11%) and (3.5 km, 9%), respectively. The vertical and radial extents of BA anomaly exceeding 6% are (6 km, 450 km) and (7 km, 500 km) over North Atlantic and West Pacific oceans, respectively. The warm core of hurricane over East Pacific ocean displays the widest radial extent (650 km), while that over North India ocean has the deepest vertical extent (8.5 km). As expected, the BA anomalies of tropical storms and tropical depressions are weaker in magnitude and smaller in size than those of hurricanes. An exception is found for the maximum BA anomaly of hurricanes over South Pacific ocean is not located near hurricane centers but at the 175-km radial distance. Accordingly, the mean altitudes of the atmospheric boundary layer estimated from COSMIC-2 BA observations increase from the 175-km radial distances to both sides for hurricanes over South Pacific ocean, while those over the other five ocean basins increase from eye centers outward.