Assessing the Quality of GNSS Radio Occultation Observations in Tropical Cyclones and Implications for Future Observations

Long-range tropical cyclone intensity forecasts remain one of the biggest challenges in numerical weather prediction models. In-situ observations of TC thermodynamics are generally limited to dropsondes and aircraft data, and vertical profiling of TC thermodynamics from conventional passive microwave and infrared sensors has historically been limited due to coarse vertical resolution and signal degradation from clouds and precipitation. High vertical resolution Global Navigation Satellite System (GNSS) radio occultation (RO) soundings are insensitive to clouds and precipitation and provide a unique opportunity to study TC thermodynamic vertical structure. However, the quality of the RO observations in the TC environment has not been thoroughly evaluated.In this study, GNSS RO profiles from COSMIC-1 (2006-2019) and COSMIC-2 (2019-2021) are analyzed in conjunction with colocated dropsondes in the TC environment. COSMIC-1 and COSMIC-2 demonstrate remarkable consistency in RO refractivity and bending angle quality exhibiting less than ±0.25% in difference, throughout the lowest 15 km of the atmosphere. Overall median refractivity difference between GNSS RO profiles and colocated dropsondes are within  0.5% at altitudes of 8 km or higher, confirming the high quality of GNSS RO measurements of the TC upper-troposphere with minimal bias. Below 8 km, refractivity differences generally range between -3% and -1% depending on altitude as well as subset criteria and sampling characteristics. Refractivity bias is mostly unaffected by colocation criteria but accounting for RO ray path orientation relative to the TC significantly reduces biases. Any additional RO biases appear to be generally related to local moisture content, rather than temperature variations. The effects of critical refraction and horizontal inhomogeneities appear to contribute no more than 1% and 0.5% refractivity bias to RO observations of TCs, respectively, but require further study. Thorough understanding of GNSS RO observation quality in the TC environment will allow for the regular use of GNSS RO in TCs to fill in observational gaps and ultimately improve TC simulation and prediction through better model physics, parameterizations, and data assimilation.