Information Content Analysis of Hyperspectral Microwave Observations in Planetary Boundary Layers

This study investigates the improvement of temperature and water vapor retrievals within the planetary boundary layer (PBL) under both clear-sky and cloudy conditions by using hyperspectral microwave measurements. We conduct an information content analysis to assess the impact of different spectral resolutions and channel selections on retrieval accuracy.

To achieve this, we use a radiative transfer model to simulate brightness temperatures for hyperspectral microwave within the frequency range of 6-250 GHz. These simulations incorporate realistic observation noise from both instruments and radiative transfer processes. By perturbing temperature, water vapor, and cloud profiles and observing the impact on brightness temperatures, we investigate the sensitivity of various microwave regions to these atmospheric parameters. This analysis helps us determine the optimal spectral resolutions and channel selection for maximizing the information content of the measurements. We then used a regression model to predict temperature and water vapor profiles to validate these finding.

Finally, we compare our simulated results with real observations from our flight campaigns to validate our findings and assess the overall performance of the retrieval algorithm.