Beyond Geostrophic and Gradient Wind: Enhancing Radio Occultation Wind Field Estimation

The Global Navigation Satellite System radio occultation (GNSS-RO) technique has been demonstrated to significantly enhance our understanding of the free atmosphere, with particular emphasis on the Upper Troposphere and Lower Stratosphere. We present improved estimations of global three-dimensional wind fields derived from low-pass filtered monthly mean geopotential height data. Geostrophic, gradient, and equatorial balance winds were estimated to provide foundational wind estimates, consistent with methodologies employed in previous studies. To advance beyond the traditional reliance on geostrophic and gradient wind, higher-order terms in the horizontal momentum equations, specifically advection and curvature, were considered. Newly derived wind fields were systematically evaluated against original winds from the European Center for Medium-Range Weather Forecast (ECMWF) Reanalysis 5 (ERA5), using a best-estimate algorithm. Building upon this methodology, the application of the best-estimate algorithm revealed that geostrophic winds incorporating advection were most applicable in the troposphere, while gradient winds with advection showed superior estimates in the stratosphere. Thus, the tropopause acts as a physical boundary delineating the domains of applicability for geostrophic and gradient-based wind approximations. Compared to their fundamental formulations, advection significantly improved both geostrophic and gradient wind estimates relative to the original ERA5 winds. In tropical regions, equatorial balance winds considering curvature provided the most accurate estimates across the entire vertical extent. Our findings emphasize the significant potential of GNSS-RO geopotential height data to move beyond the limitations of traditional geostrophic and gradient wind approximations. The results pave the way for creating a comprehensive global three-dimensional wind field climatology by leveraging the unique advantages of GNSS-RO, such as long-term consistency, high vertical resolution, and global coverage. This dataset will be a valuable resource for the scientific community, supporting climate monitoring and enhancing the understanding of atmospheric dynamics, particularly in the stratosphere, where data assimilation in reanalyses remains limited.