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Measurements of atmospheric HDO/H2O in southern California from CLARS-FTS
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  • Zhao-Cheng Zeng,
  • Olivia Addington,
  • Thomas J Pongetti,
  • Robert L Herman,
  • Keeyoon Sung,
  • Sally Newman,
  • Andreas Schneider,
  • Tobias Borsdorff,
  • Yuk L. Yung,
  • Stanley Sander
Zhao-Cheng Zeng
University of California, Los Angeles

Corresponding Author:[email protected]

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Olivia Addington
California Institute of Technology
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Thomas J Pongetti
NASA-JPL
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Robert L Herman
Jet Propulsion Laboratory
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Keeyoon Sung
Jet Propulsion Lab (NASA)
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Sally Newman
California Institute of Technology
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Andreas Schneider
Earth science group, SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
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Tobias Borsdorff
SRON Netherlands Institute of Space Research
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Yuk L. Yung
California Institute of Technology
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Stanley Sander
Jet Propulsion Laboratory
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Abstract

Atmospheric isotopologues of water vapor (e.g., HDO) are important tracers for understanding Earth’s hydrological cycles. Most remote sensing measurements of these isotopologues, however, are column averaged values and sparse in space and time. Measurements targeting the planetary boundary layer (PBL) are much rarer. In this study, we retrieved HDO and H from CLARS-FTS observations (2011-2019). The isotopological abundance δD, which represents the relative difference of the HDO/H2O ratio to a standard abundance ratio, is also calculated. The averaged δD retrievals are (−156.1±60.0)‰ with an uncertainty of (6.1±10.2)‰ for LA Basin Survey m and (−344.7±95.0)‰ with an uncertainty of (42.4±31.6)‰ for Spectralon Viewing Observation mode. In LA, the δD shows a seasonal cycle that is primarily driven by the change of atmospheric humidity. The temporal variabilities in δD data between CLARS-FTS and a collocated Total Carbon Column Observing Network (TCCON) observatory are highly correlated. The difference between CLARS and TCCON δD retrievals can primarily be attributed to the difference in their observation geometries. We conclude that the HDO and δD measurements from CLARS-FTS provide high spatial and temporal resolution datasets for further study of hydrological processes in the LA megacity.