GNSS-RO Deep Refraction Signals from Moist Marine Atmospheric Boundary Layer (MABL)
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2022-06-11
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Citation of Original Publication
Wu, Dong L., Jie Gong, and Manisha Ganeshan. 2022. "GNSS-RO Deep Refraction Signals from Moist Marine Atmospheric Boundary Layer (MABL)" Atmosphere 13, no. 6: 953. https://doi.org/10.3390/atmos13060953
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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract
The marine atmospheric boundary layer (MABL) has a profound impact on sensible heat and moisture exchanges between the surface and the free troposphere. The goal of this study is to develop an alternative technique for retrieving MABL-specific humidity (q) using GNSS-RO data in deep-refracted signals. The GNSS-RO signal amplitude (i.e., signal-to-noise ratio or SNR) at the deep straight-line height (HSL) was been found to be strongly impacted by water vapor within the MABL. This study presents a statistical analysis to empirically relate the normalized SNR (SRO) at deep HSL to the MABL q at 950 hPa (~400 m). When compared to the ERA5 reanalysis data, a good linear q–SRO relationship is found with the deep HSL SRO data, but careful treatments of receiver noise, SNR normalization, and receiver orbital altitude are required. We attribute the good q–SRO correlation to the strong refraction from a uniform, horizontally stratiform and dynamically quiet MABL water vapor layer. Ducting and diffraction/interference by this layer help to enhance the SRO amplitude at deep HSL. Potential MABL water vapor retrieval can be further developed to take advantage of a higher number of SRO measurements in the MABL compared to the Level-2 products. A better sampled diurnal variation of the MABL q is demonstrated with the SRO data over the Southeast Pacific (SEP) and the Northeast Pacific (NEP) regions, which appear to be consistent with the low cloud amount variations reported in previous studies.