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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 StatementThe 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 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 Plasma irregularities in the ionosphere induce scintillation of radio signals. Radio occultation (RO) observations of the Global Navigation Satellite Systems (GNSS) signals from low Earth orbit (LEO) allow monitoring of the ionospheric scintillation. Under certain conditions, it is possible to localize (geolocate) plasma irregularities along the line‐of‐sight between the GNSS and LEO satellites. While several techniques have been considered for the localization, in this study we use the back propagation (BP) of complex RO signals (phase and amplitude) measured at a high rate (HR), 50–100 Hz. Our method is based on a numerical solution of the wave equation, originally proposed for geolocation in 2002, with some modifications. We consider theoretical aspects of the BP technique, including assumptions, approximations and limitations, and perform numerical modeling of radio wave propagation. We investigate geolocation by BP for two regions with aligned and mis‐aligned irregularities and explain multi‐valued geolocations. We focus on the equatorial F region, consistent with the COSMIC‐2 observation sampling and use the IGRF‐13 model of the Earth's magnetic field to define the orientation of plasma irregularities. We use our method for processing of COSMIC‐2 HR scintillation data collected from the precise orbit determination antennas for 2 years: 2021 and 2023 (years with low and high solar activity). The results, represented by gridded monthly maps of geolocations, show clear seasonal and interannual variations. Additionally, we present comparison of the geolocations obtained independently from L1 and L2 signals for a 2‐month period. 

Abstract The space weather event on 10–11 May 2024 was a high‐impact geomagnetic storm, resulting in a SYM‐H index decrease to −518 nT, the lowest level registered in several decades. We investigated the response of the Earth's ionosphere during the main phase of this storm using a comprehensive data set of ionospheric observations (in situ plasma density and/or Total Electron Content (TEC)) from twenty Low‐Earth‐Orbit satellites such as COSMIC‐2, Swarm, GRACE‐FO, Spire, DMSP, and Jason‐3, orbiting at altitudes between 320 and 1,330 km. We found that ionospheric response followed a classical development pattern with the largest positive effects occurred at low and middle latitudes in daytime and evening sectors, associated with significant intensification of the Equatorial Ionization Anomaly (EIA) by the super fountain effect. The greatest effects occurred in the Pacific and American longitudinal sectors, which were in daylight, between 19 and 24 UT on 10 May 2024. This time overlaps with a period of steady southward IMF Bz and favorable conditions for long‐lasting penetration electric fields. The EIA crest‐to‐crest separation expanded to 40–60° in latitude with the largest poleward excursion of the crest to ∼27° magnetic latitude. The extreme EIA expansion with crest separation up to 60° in latitude along with a giant plasma bite‐out near the magnetic equator were observed in the dusk/evening sector over South America. The ground‐based TEC showed an enhancement up to ∼200 TECU, while satellites detected an increase in topside TEC up to ∼100–155 TECU, indicating key contribution of the topside ionosphere into the ground‐based TEC. 

Abstract On 5 March 2023, Professor Lev Gutman would have been 100 years old. This article describes Professor Gutman’s legacy in the field of dynamic mesoscale meteorology and numerical weather prediction. Gutman developed his career as a mathematician and meteorologist in the Soviet Union, where he built a school of specialists in mesoscale meteorology from the 1950s through the 1970s. He primarily worked on analytical methods to solve complex nonlinear problems, such as the structure of sea breezes, mountain–valley circulations, and thermal convection over heated terrain. Gutman pioneered the development of theories of cumulus clouds, tornadoes, and other atmospheric phenomena. In the 1960s, he carried out numerous research investigations on these topics with his doctoral students and collaborators at the High-Altitude Geophysical Institute in Nalchik in the northern Caucasus and later at the Siberian Scientific Center near Novosibirsk. Gutman compiled the results from these studies into a monograph titled “Introduction to the Nonlinear Theory of Mesoscale Meteorological Processes,” which was published in Russian in 1969 and later translated into English, Chinese, and Japanese. This monograph became a major textbook for specialists in mesoscale meteorology, remaining relevant to this day. After Professor Gutman immigrated to Israel in 1978, his collaborations expanded to include Israeli and western scientists from Europe and the United States. Gutman did not receive the recognition he deserved due to the political realities of the time. His book and his seminal analytical solutions should still be useful for early career scientists in mesoscale meteorology and atmospheric dynamics. 

Abstract Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇_HN|). In this paper we show how the uncertainties of two RO datasets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇_HN| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇_HN| below 8 km. Significance StatementThese results contribute to the understanding of the sources of uncertainties in radio occultation observations. They could be used to improve the effectiveness of these observations in their assimilation into numerical weather prediction and reanalysis models by improving the estimation of their observational errors. 

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 three-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 three months of RO observations during the first ROMEX period (ROMEX-1, September-November 2022) will be a rich data set 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 Applications 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. 

Abstract Between 2014 and 2018, the National Oceanic and Atmospheric Administration conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan for the next generation of operational environmental satellites. The study generated some important questions that could be addressed by observing system simulation experiments (OSSEs). This paper describes a series of OSSEs in which benefits to numerical weather prediction from existing observing systems are combined with enhancements from potential future capabilities. Assessments include the relative value of the quantity of different types of thermodynamic soundings for global numerical weather applications. We compare the relative impact of several sounding configuration scenarios for infrared (IR), microwave (MW), and radio occultation (RO) observing capabilities. The main results are 1) increasing the revisit rate for satellite radiance soundings produces the largest benefits but at a significant cost by requiring an increase in the number of polar-orbiting satellites from 2 to 12; 2) a large positive impact is found when the number of RO soundings per day is increased well beyond current values and other observations are held at current levels of performance; 3) RO can be used as a mitigation strategy for lower MW/IR sounding revisit rates, particularly in the tropics; and 4) smaller benefits result from increasing the horizontal resolution along the track of the satellites of MW/IR satellite radiances. Furthermore, disaggregating IR and MW instruments into six evenly distributed sun-synchronous orbits is slightly more beneficial than when the same instruments are combined and collocated on three separate orbits. 

Abstract Superrefraction at the top of the atmospheric boundary layer introduces problems for assimilation of radio occultation data in weather models. A method of detection of superrefraction by spectral analysis of deep radio occultation signals introduced earlier has been tested using 2 years of COSMIC-2/FORMOSAT-7 radio occultation data. Our analysis shows a significant dependence of the probability of detection of superrefraction on the signal-to-noise ratio, which results in a certain sampling nonuniformity. Despite this nonuniformity, the results are consistent with the known global distribution of superrefraction (mainly over the subtropical oceans) and show some additional features and seasonal variations. Comparisons to the European Centre for Medium-Range Weather Forecasts analyses and limited set of radiosondes show reasonable agreement. Being an independent measurement, detection of superrefraction from deep radio occultation signals is complementary to its prediction by atmospheric models and thus should be useful for assimilation of radio occultation data in the atmospheric boundary layer.