Using the Angular Dependence of the Polarization Ratio to Analyze Aircraft Passive Microwave Measurements over Land
Richard de Jeu (Transmissivity B.V.)
Susan Steele-Dunne (TU Delft - Geoscience and Remote Sensing)
Timothy Lang (NASA Marshall Space Flight Center)
Corey G. Amiot (University of Alabama in Huntsville)
Marian Klein (Boulder Environmental Sciences and Technology, LLC)
Madison Eble (Boulder Environmental Sciences and Technology, LLC)
Diego G. Miralles (Universiteit Gent)
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Abstract
The derivation of geophysical parameters from passive microwave observations over land has always been challenging. Soil conditions, land cover, and the atmosphere affect the measurements to varying degrees, and it is difficult to isolate these individual contributions. In this study, we assess whether multiangle observations provide additional information that can strengthen existing retrieval algorithms. Between October and November 2024, a series of airborne flights carrying the advanced microwave precipitation radiometer (AMPR) were conducted over the United States. Three land-based flights with multiangle observations from 0° to 45° and dual-polarized measurements at 10.7, 19.35, and 37.1 GHz were analyzed. The data showed a strong linear relationship between the microwave polarization ratio and the incidence angles within the 25°–45° range (e.g., R
2 > 0.9 for 71.2% of all flight scans analyzed at 10.7 GHz). The linear model for the polarization ratio showed a similar performance in terms of root-mean-square error (RMSE) to simulations based on a τ–ω radiative transfer model and commonly used assumptions. The observed linearity was further evaluated with satellite observations from the AMSR2. This evaluation confirmed the observed linearity across all three frequencies. The slope of the relationship between the polarization ratio and the incidence angle was calculated for each multiangle flight scan, which was sensitive to both soil moisture (SM) and vegetation. This new parameter, which was derived from multiple observations, appeared to be consistent in time and space, revealing similar patterns along flight lines acquired at different times. The slope was used as input in regression models (RMs) to derive SM. A model solely based on 10.7-GHz data revealed a strong correlation (R
2 = 0.81) with Level-3 SM from the SM active passive (SMAP) mission, demonstrating the potential of multiangle retrievals with established SM products.
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