Simulated impact multipath (SIM) occurs when forward operators propagate Global Navigation Satellite System (GNSS) radio occultation (RO) signals through strongly nonspherical atmospheric structures, producing multivalued bending angles that cannot be assimilated directly. In this study, the relationships between SIM and planetary boundary layer (PBL) structures were quantified using COSMIC-2 RO observations and ERA5 reanalysis during two periods (January and July 2022). The results show that SIM affects ~36% of RO profiles, with more than 70% of cases occurring within 0.5 km above the diagnosed PBL top. By defining the simulated impact multipath height (SIMH) as the first detection level of SIM, we found that discarding data below the SIMH reduces bending angle biases by more than half and substantially decreases their scatter. These results provide direct physical evidence linking SIM to strong vertical gradients near PBL structures and establish a quantitative basis for simple, effective quality control, thereby improving weather prediction, particularly in the data-sparse tropical lower troposphere.

The water vapor transport characteristics over the Tibetan Plateau associated with TC Amphan (2020) based on radio occultation observation

Abstract. Polarimetric radio occultation (PRO) extends the capability of standard radio occultation (RO) by providing not only the conventional thermodynamic profiles but also information on clouds and precipitation. The differential phase (ΔΦ) is the cumulative phase shift between horizontal and vertical polarizations observed from PRO caused by aspherical hydrometeors along the propagation path, typically measured in millimeters. In early 2025, Yunyao Aerospace Technology Co., Ltd. successfully launched the first Chinese low Earth orbit satellite equipped with a PRO payload, generating over 500 measurements per day. Based on this mission, we established an end-to-end PRO data processing chain incorporating on-orbit calibration and tailored for operational applications. We analysed approximately 53 000 events collected between March and June 2025, in conjunction with the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM) precipitation product (IMERG). The results show that ΔΦ remains close to zero under non-precipitating conditions but exhibits distinct peaks at 3–5 km altitude when traversing precipitation layers, with amplitudes strongly correlated with path-averaged rainfall rates. Thresholds of 1, 2, and 5 mm h−1 are proposed as indicators of precipitation sensitivity, detection confidence, and heavy-rain events, respectively, and a ΔΦ-to-rainfall intensity mapping table is derived to quantify this relationship. Yunyao PRO data preserve the thermodynamic retrieval quality of conventional RO while enabling effective precipitation detection, thereby providing important data support for the theoretical, technical and data research on the transition of meteorological observations from “temperature, humidity and pressure” observations to new types of observations such as precipitation.

Abstract A Coronal Mass Ejection (CME) was detected crossing the radio signals transmitted by the Mars Express (MEX) and Tianwen-1 (TIW) spacecraft at a solar elongation of 4.4 o . The impact of the CME was clearly identifiable in the spacecraft signal SNR, Doppler noise and phase residuals observed at the University of Tasmania’s Very Long Baseline Interferometry (VLBI) antenna in Ceduna, South Australia. The residual phases observed from the spacecraft were highly correlated with each other during the transit of the CME across the radio ray-path despite the spacecraft signals having substantially different Doppler trends. We analyse the auto- and cross-correlations between the spacecraft phase residuals, finding time-lags ranging between 3.18-14.43 seconds depending on whether the imprinted fluctuations were stronger on the uplink or the downlink radio ray-paths. We also examine the temporal evolution of the phase fluctuations to probe the finer structure of the CME and demonstrate that there was a clear difference in the turbulence regime of the CME leading edge and the background solar wind conditions several hours prior to the CME radio occultation. Finally, autocorrelation of the MEX two-way radio Doppler noise data from Ceduna and closed-loop Doppler data from ESA’s New Norcia ground station antenna were used to constrain the location of the CME impact along the radio ray-path to a region 0.2 AU from the Sun, at a heliospheric longitude consistent with CME origin at the Sun. The results presented demonstrate the potential of the multi-spacecraft-in-beam technique for studying CME structures in great detail, and providing measurements that complement the capabilities of future solar monitoring instruments.

Abstract Cold plasma distribution in the ionosphere‐plasmasphere system governs wave‐particle interactions, plasma energization and loss, and radio wave propagation. A longstanding observational gap at altitudes 800–8,000 km has largely prevented studying the coupled dynamics of the two regions. Here, we show that observations by JAXA's Arase mission can bridge this gap. Electron densities inferred from the upper hybrid resonance frequencies measured by Arase are highly consistent with radio occultation profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission, with a median difference of 5%. Using the combined COSMIC‐Arase data set, we provide a convenient way to reconcile the two regions in empirical models based on the analytical Chapman function inversion for scale height. Our results enable studying fundamental questions about the ionosphere‐plasmasphere coupling, their transition, and life cycle of cold plasma in near‐Earth space.

Abstract. The tropical width is changing, with a poleward expansion being linked to anthropogenic climate change. This in turn has great implications on the temperature and precipitation patterns in the subtropical regions. Previous studies have found varying widening trends, most of which have been derived using reanalysis and climate model data. These trend discrepancies underline the need for studies using alternative datasets. Here, we explore the potential of GNSS radio occultation (RO) data for analyzing the tropical width as an independent observational source of information with key characteristics: high accuracy, global availability, and long-term consistency. We evaluate the skill of RO temperature and newly established RO wind records to accurately capture tropical width features, using tropopause break and jet stream metrics. The results are compared to three state-of-the-art reanalysis datasets (i.e., ERA5, MERRA-2, and JRA-3Q). Zonal-mean patterns and the regional structure of tropical width features are investigated to test the utility of RO in respect to its spatial robustness. Furthermore, we provide a perspective on the necessary record length for reliable trend estimation of the tropical width. Comparisons of RO to reanalyses show overall high agreement of the zonal-mean values. As for the zonally resolved metrics, results from reanalyses and RO align well with exceptions over the northern hemisphere. While the RO record length is still a bit too short for detecting tropical width trends, the results are encouraging and confirm that RO is a valuable alternative observation-based dataset, with increasing relevance towards the future.

Abstract Global Navigation Satellite Systems (GNSS) radio occultation (RO) is a satellite remote sensing technique that uses GNSS measurements collected on low-Earth orbiting (LEO) satellites to profile the Earth's neutral atmosphere and ionosphere with high vertical resolution and global coverage. A theoretical study has shown that high-rate estimation of GNSS satellite clock offsets is critical to the retrieval of bending angles in GNSS RO processing, particularly for GLONASS. Inspired by this study, we have generated high-rate GNSS satellite clock products at 2-second intervals using the GINAN GNSS software, based on globally-distributed ground GNSS stations. Then we perform RO bending angle retrievals for the COSMIC-2 mission using one week of our clock products. The fundamental noise of GLONASS RO has dropped by 34% when using 2-second clock products compared to 30-second clock products. Furthermore, the uncertainty of the bending angle estimation in GPS+GLONASS RO has reached < 1×10^(-6) radian, an ultra-precise level that allows the RO technique to monitor weather and space weather with a higher sensitivity.

Abstract Global Navigation Satellite System radio occultation (GNSS-RO) data have become an essential part of observational assimilation in numerical weather prediction (NWP) models due to their high accuracy and precision, insensitivity to clouds and precipitation, high vertical resolution, and a considerable increase in sampling density in recent years. Their impact has been demonstrated in many global models, as well as in several regional models. In this study, we show the impact of assimilating GNSS-RO bending angle (BA) observations on 10 tropical cyclone (TC) forecasts from the 2022 Atlantic hurricane season using the Hurricane Analysis and Forecast System (HAFS) model. Our evaluation shows that track forecasts are improved considerably (∼15%–20%) after assimilating RO BAs, mainly through global model forecasts as initial and boundary conditions for HAFS, and these improvements are especially evident at longer forecast lead times. A case study of Hurricane Ian, a category 5 hurricane, which made landfall along the western Florida coast, showed greatly improved landfall prediction 3–5 days before landfall after assimilating RO BAs due to improved forecasts of the synoptic-scale steering flow over the region. Further study after adding many additional commercial RO profiles for assimilation through the Radio Occultation Modeling Experiment (ROMEX) showed 25%–30% improvements to TC intensity forecasts at longer lead times, albeit utilizing fewer TCs in the sample. For example, Hurricane Ian showed HAFS accurately forecasting maximum wind speeds, including its rapid intensification, 2–4 days in advance due to the improved representation of midlevel moisture in the vicinity of Ian. These results emphasize the benefits that RO can provide to both TC track and intensity forecasts. Significance Statement The purpose of this study is to understand how utilizing larger numbers (relative to what is operationally available) of radio occultation (RO) satellite observations in a hurricane model can impact tropical cyclone forecasts. It is important to determine the value of these additional data for possible commercial RO data purchases as well as developing future RO satellite missions. Our results show improvements to both track and intensity forecasts for tropical cyclones after using these additional data in the model.

Abstract NOAA began operational assimilation of radio occultation (RO) observations from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-1) mission over 15 years ago. Since then, other operational and research missions have been incorporated into the operational suite. To increase the volume of RO profiles and their geographical coverage beyond what COSMIC-2 provides, which is mostly limited to the tropical and subtropical regions, NOAA engaged in procurement activities with commercial companies capable of delivering RO data for operational use. Tests were conducted in this study to quantify the value of commercial RO data for numerical weather prediction (NWP) applications and their relative value compared to a U.S. Government RO data source (viz., COSMIC-2). When commercial RO soundings are added to a baseline that already assimilates COSMIC-2 bending angle observations, it is found that commercial RO soundings bring benefits to global weather forecast skill, mostly by reducing the temperature and wind root-mean-squared error globally. As expected, the benefits are larger in the extratropics. Statistics between COSMIC-2 and commercial RO data show similar values, indicating that higher signal-to-noise values are not necessary to improve weather forecasting—at least with current modeling capabilities. The quality of commercial RO is sufficient for current global NWP applications. Finally, and supporting earlier studies with simulated data, results show that global RO data distribution is needed to improve NWP skill globally. Significance Statement The results of this paper are significant because they inform on the value of radio occultation observations from different sources for global numerical weather prediction applications, thus helping decision-makers plan for future commercial data buys.

Abstract Ionospheric data assimilation is the art of combining imperfect data with incomplete models to estimate the state of the ionosphere. The three most common data types are ionosonde measurements, Ground‐to‐GNSS (Global Navigation Satellite System), TEC (Total Electron Content) measurements, and RO (Radio Occultation) TEC measurements. Despite the ubiquitous use of these measurement types, scant research exists on the relative merits of each measurement type. This study evaluates the impact of assimilating all possible combinations of these three measurement types. To do this, we simulate representative data for all three measurement types using an electron density truth model, and then ingest all possible combinations of data in separate assimilation runs. Since we assimilate ground TEC in an absolute and relative sense, this yields 11 combinations. The performance of each assimilation run is assessed by how well each analysis replicates the truth model's vertical TEC (vTEC), critical plasma frequency of the F2 layer (foF2), the height at which it occurs (hmF2) and HF propagation metrics. When considering vTEC, fof2, and hmF2, we find that absolute ground TEC data is the most useful for specifying vTEC and that Radio Occultation data is the most useful when specifying foF2 and hmF2. Somewhat surprisingly, we find that adding absolute ground TEC can worsen predictions of foF2 and hmF2. Our analysis of HF propagation shows that ionosonde and RO data are quite valuable, and that ingesting ground TEC in a relative sense is better than absolute, regardless of what additional data (RO, Ionosonde) is present.

Abstract This study investigates the ionospheric response to the May 2024 geomagnetic storm using electron density and scintillation data from space‐based Global Navigation Satellite System (GNSS) radio occultation (RO) satellites and ground‐based GNSS receivers. Electron density profiles retrieved from commercial RO observations revealed a distinct depletion in the F‐region and an enhancement in the E‐region at high latitudes during the storm, particularly during the recovery phase. These findings were supported and corroborated by observations from collocated digital ionosondes and incoherent scatter radar. A collocation analysis between scintillation indices retrieved from RO data and ground‐based ionospheric scintillation monitoring receivers demonstrated temporal and spatial agreement between the two data sets during the storm. RO‐derived scintillation indices exhibited clear altitude dependence, with strong scintillation in both the F‐ and E‐regions during the initial and main phases of the storm, and increased E‐region scintillation accompanied by suppressed F‐region scintillation during the recovery phase. The variations were consistent with background electron density conditions at different altitudes.

Radio occultation for tropical cyclone monitoring and prediction

Abstract. The Radio Occultation Modeling EXperiment (ROMEX) is an international collaboration to test the impact of varying numbers of radio occultation (RO) profiles in operational numerical weather prediction (NWP) models. An average of 35 000 RO profiles d−1 for September–November 2022 from 13 different missions are being used in experiments at major NWP centers. This paper evaluates properties of ROMEX data, with emphasis on the three largest datasets: COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere and Climate-2 or C2), Spire, and Yunyao. The penetration depths (percent of profiles reaching different levels above the surface) of most of the ROMEX datasets are similar, with more than 80 % of all occultations reaching 2 km or lower and more than 50 % reaching 1 km or lower. The relative uncertainties of the C2, Spire, and Yunyao bending angles and refractivities are estimated using the three-cornered hat method. They are similar on the average in the region of overlap (45–45° N). Larger uncertainties occur in the tropics compared to higher latitudes below 20 km. Relatively small variations in longitude exist. We investigate biases in the observations by comparing them to each other and to models. C2 bending angles appear to be biased by about 0.15 % compared to Spire and other ROMEX data between 10 and 30 km altitude. These biases, most of which are representativeness or sampling differences, are caused by the different orbits of C2 and other ROMEX missions around the non-spherical Earth and the associated varying radii of curvature.

Abstract. The tropopause is a key indicator of atmospheric climate change, influenced by both the troposphere and stratosphere. Here we present a global view of tropopause changes, using high-resolution GNSS radio occultation data from 2002 to 2024. We identify significant trends in lapse rate tropopause (LRT) temperature and height with seasonal and regional detail. The tropical LRT has warmed, with particularly strong warming (>1 K per decade) over the South Pacific during austral spring and summer, while height changes remain largely insignificant. Outside the tropics, LRT temperature changes are confined to southern high latitudes in winter, showing cooling of up to 1 K per decade. Notably, LRT height has increased significantly across most extratropical regions, with localized trends exceeding 200 m per decade over Asia and the Middle East during Northern Hemisphere winter. An exception is the LRT height decreases over the South Pacific, coinciding with a LRT warming in that region. These results highlight the interrelated effects of tropospheric and stratospheric changes and demonstrate the value of precise tropopause monitoring for detecting ongoing changes in the global climate system.

Abstract. Atmospheric rivers (ARs) are long filaments that transport large amounts of water vapor from the Tropics to mid- and high latitudes. They are directly related to heavy precipitation and extreme weather leading to flooding and mud slides. Accurate identification of AR structures over the ocean is important to improve the forecast of their landfall location and timing. Global Navigation Satellite Systems (GNSS) radio occultation (RO) is a space-based technique that can measure meteorological variables with high vertical resolution. While RO can observe structures like ARs in individual RO profiles, RO observations have non-uniform and sparse spatial and temporal sampling, so it is not yet possible to fully characterize AR morphology using RO alone. In this work, we use previous research in which we applied machine learning (ML) to enhance the spatial and temporal resolution of RO observations. Here, we train neural networks (NNs) to map RO observations and help resolve ARs. Analyses using existing RO data, such as from the COSMIC-2 mission, showed that the sampling density is insufficient to resolve and geo-locate ARs. Adding observations from the other available missions (for example METOP) improved matters, but was still insufficient to reliably reconstruct AR structure. We undertake a study to determine how many LEO RO satellites would be needed to quantify the structure, location, and timing of ARs. We simulate RO observations as would be obtained with Walker constellations of 12, 24, 36, 48 and 60 LEO RO satellites. First, we investigate possible constellations for proper AR monitoring. We aim for constellations that lead to hourly RO counts that change as little as possible during the AR (up to several days). This allows us to resolve ARs with similar accuracy during the scenario. We conclude that 3 or 6 orbital planes and inclinations between 85 and 90° perform best. Second, we make use of 12 h forecasts of the European Centre for Medium-range Weather Forecasts (ECMWF) system to interpolate the forecasts to the simulated RO constellation sampling coordinates. Third, we use the ECMWF-based RO observations to train ML models and map them to the ECMWF grid. We compare ML-mapped RO sampled grids to ECMWF products in a closed-loop validation. Initially, we map RO refractivity at 2 km geopotential height, where small-scale structures related to water vapor are visible. We find that at least 36 RO satellites are needed to characterize the morphology of ARs in the Pacific basin with useful precision and accuracy (from the ML produced maps). Then, we use a framework with two consecutive NNs to map column-integrated water vapor (IWV) from profiles of RO. The first NN maps the refractivity into IWV, and the second NN maps the IWV spatially. In this case, we find that a constellation of 48 satellites is needed to continuously map IWV fields accurately and thus reconstruct the morphology of ARs with useful precision and accuracy. Finally, when using RO, we find that mapping refractivity into IWV is less accurate over land than over oceans. To further improve the AR mapping over land, we made use of IWV from ground-based (GB) GNSS. The significantly higher spatial and temporal resolutions of GB data compared to RO lead to much improved IWV fields and thus AR path and shape over land.

Abstract The upper layers of Jupiter's atmosphere, offering critical insights into the planet's deeper structure, are accessible through radio occultation experiments. Since July 2023, NASA's Juno extended mission has provided the first high‐resolution radio occultation measurements since the Voyager era, probing the thermal structure and composition down to approximately 0.5 bar. We use these measurements to study Jupiter's latitudinally dependent vertical thermal structure. We observe cooler stratospheric and warmer tropospheric temperatures at the equatorial region compared to mid‐ and high‐latitudes, and temporal variations in the North Equatorial Belt's thermal structure on a time scale of a few months. These observations align with archival mid‐infrared data from Cassini's CIRS and current ground‐based Texas Echelon Cross Echelle Spectrograph observations, as well as previous studies based on Voyager radio occultations and the Galileo probe, offering an enhanced view of Jupiter's lower stratosphere and upper troposphere thermal structure.

Abstract This paper presents an analysis of Juno's first radio occultation experiments. Relying on two‐way radio links in the X‐ and Ka‐bands, we processed data from NASA's Deep Space Network antennas through a ray‐tracing inversion algorithm. By effectively isolating dispersive effects, we obtained measurements of the neutral atmosphere's characteristics. This enabled the derivation of pressure and temperature profiles from the recorded frequencies. These results complement prior data from Voyager occultations and CIRS observations, providing valuable contributions to our understanding of Jupiter's atmospheric dynamics.

ABSTRACT The Amazon rainforest is a critical component of the global climate system, with its vast vegetation driving the regional water cycle through evapotranspiration. However, deforestation is severely disrupting this balance, and most studies have focused primarily on surface‐level impacts. This study examines how deforestation affects the vertical structure of humidity in Amazonia, using high‐vertical‐resolution specific humidity profiles from GPS radio occultation (GPS‐RO) observations between 2007 and 2023. Gid cells across the region were classified by the percentage of accumulated forest loss (low deforestation, LD < 10%; high deforestation, HD > 50%) using data from the PRODES/INPE system. Results show consistent and significant drying in highly deforested areas, especially in the lower troposphere (below ~3–4 km), with the strongest reductions in specific humidity (up to −7.8 g kg −1 ) found below 1.5 km. This drying intensifies during the dry season (May–September), when forest‐driven evapotranspiration plays its greatest role. Humidity differences persist into the mid‐troposphere, suggesting possible changes in convective development or broader‐scale compensatory subsidence. The robustness of the signal was validated through integrated humidity profiles at different vertical layers, confirming that the observed drying is not a methodological artefact but a direct physical consequence of vegetation loss. These findings highlight the deep coupling between land cover and moisture dynamics in the tropics, with major implications for regional climate modelling and conservation strategies in the Amazon.

Radio occultation (RO) is a technique used for measuring planetary atmosphere properties by orbiting satellites, like temperature, pressure, and water vapor. Typically using Global Navigation Satellite System (GNSS) signals, this technique is often assessed with atmospheric properties measured by radiosonde (RS) stations around the world. The aim of this study is to assess the radio occultation temperature and pressure profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate 2 (COSMIC-2) and Korean Multi-purpose Satellite 5 (KOMPSAT-5) satellites using data from collocated radiosonde stations over the Philippines. Their deviations are analyzed using their mean and standard deviations. COSMIC-2 and KOMPSAT-5 temperature and pressure from the atmPrf product are in good agreement with radiosondes above 5–10 km, where moisture is negligible. COSMIC-2 has good agreement with radiosonde stations in 2020. KOMPSAT-5 has good agreement with radiosonde stations in 2019–2020. For both satellites, the deviations are larger within the lower troposphere, compared to heights above ~5–10 km. For both years, KOMPSAT-5 deviations are higher during the summer season until 10 km. For COSMIC-2, deviations are higher during the summer and autumn seasons. The quality of these results shows COSMIC and KOMPSAT as possible high-quality applications for weather prediction. In addition to providing comparable high-precision data, radio occultation can provide more dense coverage of areas without radiosondes.

Abstract. The international collaborative Radio Occultation Modeling EXperiment (ROMEX) project marks the first time using a large volume of real data to assess the impact of increased Global Navigation Satellite System radio occultation (GNSS-RO) observations beyond current operational levels, moving past previous theoretical simulation-based studies. The ROMEX project enabled the use of approximately 35 000 daily RO profiles – nearly triple the number typically available to operational centers, which is about 8000 to 12 000 per day. This study investigates the impact of increased RO profiles on numerical weather prediction (NWP) with the Joint Effort for Data assimilation Integration (JEDI) and the global forecast system (GFS), as part of the ROMEX effort. A series of experiments were conducted assimilating varying amounts of RO data along with a common set of other key observations. The results confirm that assimilating additional RO data further improves forecasts across all major meteorological fields, including temperature, humidity, geopotential height, and wind speed, for most of vertical levels. These improvements are significantly evident in verification against both critical observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses, with beneficial impacts lasting up to 5 d. Conversely, withholding RO data resulted in forecast degradations. The results also suggest that forecast improvements scale approximately logarithmically with the number of assimilated profiles, and no evidence of saturation was observed. Biases in the forecast of temperature and geopotential height over the lower stratosphere are discussed, and they are consistent with findings from other studies in the ROMEX community.