Evaluation of GNSS Radio Occultation Profiles in the Vicinity of Atmospheric Rivers

Abstract

Increasing the density of Global Navigation Satellite System radio occultation (RO) with commercial Smallsats and the next generation COSMIC-2 constellation is expected to improve analyses of the state of atmosphere, which is essential for numerical weather prediction. High vertical resolution RO profiles could be useful to observe atmospheric rivers (ARs) over the ocean, which transport water vapor in shallow, elongated corridors that frequently impact the west coasts of continents. The multi-year AR Reconnaissance campaign has extensively sampled ARs over the northeastern Pacific with dropsondes, providing an invaluable dataset to evaluate the reliability of RO retrievals. These dropsondes, and a reanalysis product that assimilates them, are compared to three RO datasets: (1) established operational missions, (2) COSMIC-2, and (3) the commercial Spire constellation. Each RO dataset has biases relative to reanalyses of less than 0.5% N in the upper troposphere and negative biases in the lower troposphere. Direct colocations with dropsondes indicate that vertical refractivity gradients present within ARs may be contributing to negative biases at higher altitudes inside than outside ARs, where the greatest variability and vertical gradients are at the well-defined boundary layer top. Observations from Spire are overly smooth, affecting the ability to resolve the low-level structure of an AR. Surprisingly, the depth of penetration into the lower troposphere is greater inside an AR than outside for all datasets. The results indicate that the observation errors used for assimilation of RO within ARs should consider the height dependent biases that are associated with the structure of the atmosphere.

Using the Commercial GNSS RO Spire Data in the Neutral Atmosphere for Climate and Weather Prediction Studies

“…The objective of this study is to precisely characterize the quality of the Spire CubeSats data in the neutral atmosphere in terms of their (i) precision, (ii) stability, and (iii) retrieval accuracy and uncertainty [2]. Many studies [34][35][36][37][38][39][40][41][42] have reported on the quality of Spireretrieved data products using collocated in situ radiosondes, satellite observations, or reanalysis data interpolated onto RO locations. For example, Ref.…”