Improving simulations of Zeeman absorption spectrum for hyperspectral microwave sounding applications

Accurate simulation of microwave oxygen absorption is critical for upper atmospheric remote sensing, yet traditional models suffer from biases due to simplified Zeeman splitting calculations. This study presents the channel parameters of a hyperspectral microwave sounder for near space temperature profiling, built upon the updated microwave Line-by-Line (LBL) model with Larsson et al. (2019) Zeeman coefficients. The Hyperspectral Microwave Atmospheric Sounder (HMAS) is designed as a 60–63 GHz linearly polarized instrument comprising 150 channels, optimized to 39 composite channels for noise reduction. The HMAS channels are validated by comparing weighting functions and simulated brightness temperatures with Special Sensor Microwave Imager/Sounder (SSMIS) upper atmospheric sounding (UAS) channels. The global distribution of brightness temperature differences between HMAS composite channels and SSMIS channels on representative dates shows that the differences are generally within ±1.3 K, confirming the physical consistency of the HMAS channel design. Temperature profile retrieval experiments are conducted using an improved back propagation (BP) neural network with dual residual blocks and squeeze-and-excitation (SE) attention mechanism based on simulated brightness temperatures from both HMAS and SSMIS corresponding channels. The retrieval results show that the HMAS achieves a root mean square error (RMSE) of 7.652 ± 0.389 K, a mean absolute error (MAE) of 4.911 ± 0.282 K, and a coefficient of determination ( R ² ) of 0.915 ± 0.010, while the SSMIS channels 19–24 yield a RMSE of 7.858 ± 0.314 K, a MAE of 5.107 ± 0.208 K, and an R ² of 0.910 ± 0.010. The HMAS shows potential as a payload for future near space exploration missions.