Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency

Greg M Mcfarquhar (1) , Darrel Baumgardner (2) , Aaron Bansemer (3) , Steven J Abel , Jonathan Crosier (4) , Jeff French (5) , Phil Rosenberg (6) , Alexei Korolev (7) , Alfons Schwarzoenboeck (8) , Delphine Leroy (8) , Junshik Um (1) , Wei Wu (1, 3) , Andrew J Heymsfield (3) , Cynthia Twohy , Andrew Detwiler , Paul Field (9) , Andrea Neumann (10) , Richard Cotton (11) , Duncan Axisa (3) , Jiayin Dong (1)

1 UIUC - University of Illinois at Urbana-Champaign [Urbana]
2 Centro de Ciencias de la Atmosfera [Mexico]
3 NCAR - National Center for Atmospheric Research [Boulder]
4 NCAS - National Centre for Atmospheric Science [Manchester]
5 UW - University of Wyoming
6 SEE - School of Earth and Environment [Leeds]
7 ECCC - Environment and Climate Change Canada
8 LaMP - Laboratoire de Météorologie Physique
9 University of Leeds
10 UND - University of North Dakota [Grand Forks]
11 United Kingdom Met Office [Exeter]

In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

Domaines: Océan, Atmosphère; Météorologie

Greg M Mcfarquhar, Darrel Baumgardner, Aaron Bansemer, Steven J Abel, Jonathan Crosier, et al.. Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency. Meteorological Monographs- American Meteorological Society, 2017, 58, pp.11.1-11.33. ⟨10.1175/amsmonographs-d-16-0007.1⟩. ⟨hal-01980968⟩