Evaluation of Spaceborne Microwave Hyperspectral Technology for Atmospheric Boundary Layer Temperature and Humidity Profiling

This paper conducts an in-depth analysis of spaceborne hyperspectral microwave radiometers for remotely sensing atmospheric boundary layers’ temperature and humidity profiles. Utilizing 137 vertical-level atmospheric profile data from the European Centre for Medium-Range Weather Forecasts (ECMWF), the study employs the Atmospheric Radiative Transfer Simulator (ARTS) to construct a forward model of an Earth-based spaceborne microwave radiometer, enabling the computation of the Jacobian matrix. This research thoroughly evaluates the posterior probability of retrieval errors and vertical resolution by analyzing both the background error covariance matrix and the measurement error covariance matrix alongside the Jacobian matrix. Findings reveal that a spectral resolution of 10 MHz significantly enhances the accuracy of posterior retrieval errors and improves vertical resolution, in contrast to the 1000 MHz resolution, which shows lesser efficacy. While hyperspectral microwave radiometers offer clear benefits for detailed atmospheric profiling, the increase in spectral resolution does not uniformly translate to performance enhancements due to the accompanying rise in system noise. These results underscore the importance of conducting meticulous assessments to determine the most effective spectral resolution for radiometers, considering the intricate balance between information gain and noise.