Articles | Volume 9, issue 4
Atmos. Meas. Tech., 9, 1587–1599, 2016
https://doi.org/10.5194/amt-9-1587-2016
Atmos. Meas. Tech., 9, 1587–1599, 2016
https://doi.org/10.5194/amt-9-1587-2016

Research article 11 Apr 2016

Research article | 11 Apr 2016

MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP

Benjamin Marchant1,2, Steven Platnick1, Kerry Meyer1,2, G. Thomas Arnold1,3, and Jérôme Riedi4 Benjamin Marchant et al.
  • 1NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 2USRA Universities Space Research Association, Columbia, Maryland, USA
  • 3SSAI, Inc., 10210 Greenbelt Road, Lanham, MD 20706, USA
  • 4LOA (Laboratoire d'Optique Atmospherique), Université Lille 1, France

Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

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Short summary
The current paper presents the new MODIS Collection 6 (C6) cloud thermodynamic phase classification algorithm. To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.