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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 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 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. 

Abstract We report a new ionosphere phenomenon: Equatorial ionization anomaly (EIA) discontinuity (EIAD), based on OI 135.6 nm radiance observations from the Global Observations of Limb and Disk (GOLD), ground‐based total electron content maps and in‐situ ion density data from Constellation Observing System for Meteorology, Ionosphere, and Climate‐2. The EIAD occurs when the OI radiance of the EIA crest has a local minimum, at a fixed UT, with the radiance in the local longitude region being weaker than that on the east and west sides. In the GOLD field‐of‐view, EIAD follows the seasonal variations of EIA. EIAD appears more often over the Atlantic Ocean and Africa than over South America. It occurs more in the southern crest during the December solstice, and more in the northern crest during both equinoxes. EIAD can occur under both quiet and disturbed times. 

Abstract Slant absolute total electron content (TEC) is observed by the Formosa Satellite‐7/Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (FORMOSAT‐7/COSMIC‐2, F7/C2) Tri‐GNSS Radio Occultation System (TGRS) instrument. We present details of the data processing algorithms, validation, and error assessment for the F7/C2 global positioning system (GPS) absolute TEC observations. The data processing includes estimation and application of solar panel dependent pseudorange multipath maps, phase to pseudorange leveling, and estimation of separate L1C‐L2C and L1C‐L2P receiver differential code biases. We additionally perform a validation of the F7/C2 GPS absolute TEC observations through comparison with colocated, independent, TEC observations from the Swarm‐B satellite. Based on this comparison, we conclude that the accuracy of the F7/C2 GPS absolute TEC observations is less than 3.0 TEC units. Results are also presented that illustrate the suitability of the F7/C2 GPS absolute TEC observations for studying the climatology and variability of the topside ionosphere and plasmasphere (i.e., altitudes above the F7/C2 orbit of550 km). These results demonstrate that F7/C2 provides high quality GPS absolute TEC observations that can be used for ionosphere‐thermosphere data assimilation as well as scientific studies of the topside ionosphere and plasmasphere. 

Using the high-rate phase and amplitude scintillation data from FORMOSA7/COSMIC two mission and back-propagation method, we geolocate plasma irregularities that cause scintillations. The results of geolocation are compared with the NASA GOLD UV image data of plasma bubbles. The root mean square of the zonal difference between estimated locations of plasma irregularities and plasma bubbles are about 1.5° and for single intersection cases 0.5° in the magnetic longitude. The geolocation data provide more accurate scintillation location around the globe compared to assigning to the tangent point and is valuable space weather product, which will be routinely available for public use. 

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