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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.
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THE RESEARCH AND EDUCATION COLLABORATIVE OCCULTATION NETWORK: A SYSTEM FOR COORDINATED TNO OCCULTATION OBSERVATIONS
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Abstract We propose to design and build an algorithm that will use a convolutional neural network (CNN) and observations from the Unistellar Network to reliably detect asteroid occultations. The Unistellar Network is made of more than 10,000 digital telescopes owned by citizen scientists, and is regularly used to record asteroid occultations. In order to process the increasing amount of observational produced by this network, we need a quick and reliable way to analyze occultations. In an effort to solve this problem, we trained a CNN with artificial images of stars with 20 different types of photometric signals. Inputs to the network consist of two stacks of snippet images of stars, one around the star that is supposed to be occulted and a reference star used for comparison. We need the reference star to distinguish between a true occultation and artifacts introduced by a poor atmospheric condition. Our Occultation Detection Neural Network can analyze three sequences of stars per second with 91% precision and 87% recall. The algorithm is sufficiently fast and robust so we can envision incorporating it on board the eVscopes to deliver real-time results. We conclude that citizen science represents an important opportunity for the future studies and discoveries in the occultations, and that application of artificial intelligence will permit us to to take better advantage of the ever-growing quantity of data to categorize asteroids.more » « less
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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 per day 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 (C2), Spire, and Yunyao. The penetration rates (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° S–45° N). Larger uncertainties occur in the tropics compared to higher latitudes below 20 km. Relatively small variations in longitude exist. The assimilation of ROMEX data caused small degradations in biases in several NWP models. We investigate biases in the observations by comparing them to each other and to models. C2 bending angles appear to be biased by about +0.1–0.15 % compared to Spire and other ROMEX data. These apparent biases, some 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 (radius of a sphere that best fits the Earth’s surface curvature at a given location and orientation of the RO occultation plane and is used in the RO BA retrievals).more » « less
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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.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3847/0004-6256/151/3/73
