Toward the Next Generation of Microwave Sounders: Benefits of a Low-Earth Orbit Hyperspectral Microwave Instrument in All-Weather Conditions Using AI

This study presents scientific results that serve as arguments for advocating the development of a hyperspectral microwave sensor (HyMS). Through simulation experiments, the results of this study demonstrate the major benefits of HyMS sensor observations in low-Earth orbit (LEO), including; 1) increased information content over the microwave region, 2) improved temperature and moisture sounding in all-weather conditions, resulting from higher signal-to-noise ratios, finer vertical resolution, and a reduced dependence on background information due to the increased spectral resolution around oxygen and water vapor absorption features between 23 and 183 GHz, 3) improved profiling of hydrometeors, and 4) improved resilience to radio frequency interference, demonstrated at 23 GHz, associated with the redundant information provided by the HyMS. The deployment of HyMS instruments in LEO orbit is expected to provide an improved knowledge of the state of the atmosphere, particularly if deployed in the form of a constellation, due to the enhanced temporal, spatial, and spectral resolution capabilities that those sensors can provide with respect to present meteorological microwave sounders. This work takes advantage of artificial intelligence (AI), particularly its capability to rapidly and simultaneously process hundreds of channels and retrieve large sets of geophysical parameters, to assess the impact of HyMS in geophysical space. The results presented in this manuscript are expected to contribute to the design of the next generation of microwave sounders, but also to consider the usage of AI to fully exploit the information content provided by these sensors, particularly if deployed in the form of a constellation of satellites.