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GNSS-RO Deep Refraction Signals from Moist Marine Atmospheric Boundary Layer (MABL)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 (H(SL)) 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 (S(RO)) at deep HSL to the MABL q at 950 hPa (~400 m). When compared to the ERA5 reanalysis data, a good linear q–S(RO) relationship is found with the deep H(SL) S(RO) data, but careful treatments of receiver noise, SNR normalization, and receiver orbital altitude are required. We attribute the good q–S(RO) 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 S(RO) amplitude at deep H(SL). Potential MABL water vapor retrieval can be further developed to take advantage of a higher number of S(RO) measurements in the MABL compared to the Level-2 products. A better sampled diurnal variation of the MABL q is demonstrated with the S(RO) 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.
Document ID
20220013781
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Dong L. Wu ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Jie Gong ORCID
(Universities Space Research Association Columbia, Maryland, United States)
Manisha Ganeshan
(Universities Space Research Association Columbia, Maryland, United States)
Date Acquired
September 8, 2022
Publication Date
June 11, 2022
Publication Information
Publication: Atmosphere
Publisher: MDPI
Volume: 13
Issue: 6
Issue Publication Date: June 1, 2022
e-ISSN: 2073-4433
URL: https://www.mdpi.com/2073-4433/13/6/953
Subject Category
Geosciences (General)
Funding Number(s)
WBS: 509496.02.08.13.47
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
External Peer Committee
Keywords
diurnal variation
GNSS-RO
atmospheric boundary layer
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