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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 5 | Copyright
Atmos. Meas. Tech., 8, 2037-2049, 2015
https://doi.org/10.5194/amt-8-2037-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 09 May 2015

Research article | 09 May 2015

Airborne in situ vertical profiling of HDO / H216O in the subtropical troposphere during the MUSICA remote sensing validation campaign

C. Dyroff1, S. Sanati1, E. Christner1, A. Zahn1, M. Balzer2, H. Bouquet2, J. B. McManus3, Y. González-Ramos4, and M. Schneider1 C. Dyroff et al.
  • 1Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe, Germany
  • 2Karlsruhe Institute of Technology (KIT), Institute for Data Processing and Electronics (IPE), Karlsruhe, Germany
  • 3Aerodyne Research Inc., 45 Manning Road, Billerica, MA 01821, USA
  • 4Agencia Estatal de Meteorologa (AEMET), Santa Cruz de Tenerife, Spain

Abstract. Vertical profiles of water vapor (H2O) and its isotope ratio D / H expressed as δD(H2O) were measured in situ by the ISOWAT II diode-laser spectrometer during the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) airborne campaign. We present recent modifications of the instrument design. The instrument calibration on the ground as well as in flight is described. Based on the calibration measurements, the humidity-dependent uncertainty of our airborne data is determined. For the majority of the airborne data we achieved an accuracy (uncertainty of the mean) of Δ(δD) ≈10‰. Vertical profiles between 150 and ~7000 m were obtained during 7 days in July and August 2013 over the subtropical North Atlantic Ocean near Tenerife. The flights were coordinated with ground-based (Network for the Detection of Atmospheric Composition Change, NDACC) and space-based (Infrared Atmospheric Sounding Interferometer, IASI) FTIR remote sensing measurements of δD(H2O) as a means to validate the remote sensing humidity and δD(H2O) data products. The results of the validation are presented in detail in a separate paper (Schneider et al., 2014). The profiles were obtained with a high vertical resolution of around 3 m. By analyzing humidity and δD(H2O) correlations we were able to identify different layers of air masses with specific isotopic signatures. The results are discussed.

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