Affiliation:
1. Space Environment and Radio Engineering (SERENE) University of Birmingham Birmingham UK
2. European Centre for Medium‐Range Weather Forecasts Reading UK
3. Met Office Exeter UK
Abstract
AbstractCulverwell et al. (2023, https://doi.org/10.1029/2023SW003572) described a new one‐dimensional variational (1D‐Var) retrieval approach for ionospheric GNSS radio occultation (GNSS‐RO) measurements. The approach maps a one‐dimensional ionospheric electron density profile, modeled with multiple “Vary‐Chap” layers, to bending angle space. This paper improves the computational performance of the 1D‐Var retrieval using an improved background model and validates the approach by comparing with the COSMIC‐2 profile retrievals, based on an Abel Transform inversion, and co‐located (within 200 km) ionosonde observations using all suitable data from 2020. A three or four layer Vary‐Chap in the 1D‐Var retrieval shows improved performance compared to COSMIC‐2 retrievals in terms of percentage error for the F2 peak parameters (NmF2 and hmF2). Furthermore, skill in retrieval (compared to COSMIC‐2 profiles) throughout the bottomside (∼90–300 km) has been demonstrated. With a single Vary‐Chap layer the performance is similar, but this improves by approximately 40% when using four‐layers.
Publisher
American Geophysical Union (AGU)