Optimizing Boundary Conditions in GNSS Tomography: A Continuous 7‐Month Case Study in the Amazon

Abstract

Different estimates of the regional water vapor scale height, taken from ERA5 reanalysis, in situ observations and the direct optimization of retrieved water vapor profiles in GNSS tomography, are found to have major impact in the performance of tomographic inversions, with the better results displaying mean errors comparable to radiosondes. The analysis uses 7 months of GNSS (Global Navigation Satellite Systems) observations in the Amazon Dense GNSS Network near Manaus, Brazil, in 2011–2012, to compute a time series of water vapor profiles, with a tomographic technique capable of producing quasi‐instantaneous inversions with minimal external data or constraints. Results compare very well with 12‐hourly in situ radiosondes, especially in the lower troposphere above 2 km, and its daily‐to‐seasonal variability compares well with WRF (Weather Research and Forecasting) convective‐permitting simulations driven by ERA5 boundary conditions, suggesting that GNSS tomography may be an important source of atmospheric water vapor data for different applications.