Using Radio Occultation to Detect Clouds in the Middle and Upper Troposphere

Abstract

Radio occultation (RO) measurements have little direct sensitivity to clouds, but recent studies have shown that they may have an indirect sensitivity to thin, high clouds that are difficult to detect using conventional passive space-based cloud sensors. We implement two RO-based cloud detection (ROCD) algorithms for atmospheric layers in the middle and upper troposphere. The first algorithm is based on the methodology of a previous study, which explored signatures caused by upper tropospheric clouds in RO profiles according to retrieved relative humidity, temperature lapse rate, and gradients in log-refractivity (ROCD-P), and the second is based on inferred relative humidity alone (ROCD-M). In both, atmospheric layers are independently predicted as cloudy or clear based on observational data, including high performance RO retrievals. In a demonstration, we use data from 10 days spanning seven months in 2020 of FORMOSAT-7/COSMIC-2. We use the forecasts of NOAA GFS to aid in the retrieval of relative humidity. The prediction is validated with a cloud truth dataset created from the imagery of the GOES-16 Advanced Baseline Imager (ABI) satellite and the GFS three-dimensional analysis of cloud state conditions. Given these two algorithms for the presence or absence of clouds, confusion matrices and receiver operating characteristic (ROC) curves are used to analyze how well these algorithms perform. The ROCD-M algorithm has a balanced accuracy, which defines the quality of the classification test that considers both the sensitivity and specificity, greater than 70% for all altitudes between 6 and 10.25 km.

Efficient collocation of global navigation satellite system radio occultation soundings with passive nadir microwave soundings

“…Measurements made using radio occultation (RO) of the Earth's atmosphere from the transmitters of the global navigation satellite system (GNSS) are now routine and important contributors to numerical weather prediction and atmospheric reanalysis (Cardinali and Healy, 2014;Banos et al, 2019, and references therein). GNSS RO data fill in large holes in global coverage left by the international network of radiosondes, anchor atmospheric analyses by virtue of their near-absolute accuracy (Gelaro et al, 2017;Hersbach et al, 2020), and provide cloud-free information on atmospheric water vapor in the middle to lower troposphere (Kursinski and Gebhardt, 2014;Mascio et al, 2021). GNSS RO measurements are typically inverted to yield profiles of the index of refraction, a quantity with contributions from atmospheric density, temperature, and water vapor (Kursinski et al, 2000).…”

Efficient Collocation of GNSS Radio Occultation Soundings with Passive Nadir Microwave Soundings

“…Measurements made using radio occultation (RO) by the Earth's atmosphere of the transmitters of the Global Navigation Satellite Systems (GNSS) are now routine and important contributors to numerical weather prediction and atmospheric reanalysis (Cardinali and Healy, 2014;Banos et al, 2019, and references therein). GNSS RO data fills in large holes in global coverage left by the international network of radiosondes, anchors atmospheric analyses by virtue of its near-absolute accuracy (Gelaro et al, 2017;Hersbach et al, 2020), and provides cloud-free information on atmospheric water vapor in the middle to lower troposphere (Kursinski and Gebhardt, 2014;Mascio et al, 2021). GNSS RO measurements are typically inverted to yield profiles of the index of refraction, a quantity with contributions from atmospheric density, temperature and water vapor (Kursinski et al, 2000).…”