A31I-3143:
Cloud vertical structure and the impact of MODIS liquid water path retrieval assumptions: Developing a theoretical framework and evaluating retrievals using large-eddy simulations
Wednesday, 17 December 2014
Daniel J Miller, University of MD Baltimore County, Baltimore, MD, United States, Zhibo Zhang, University of Maryland Baltimore County, Baltimore, MD, United States, Steven E Platnick, NASA Goddard Space Flight Center, Greenbelt, MD, United States and Andrew S Ackerman, NASA Goddard Institute for Space Studies, New York, NY, United States
Abstract:
The vertical structure of marine boundary layer (MBL) clouds plays an important role in satellite retrievals of cloud microphysical properties such as droplet size (re) , liquid water path (LWP), and droplet number concentration (CDNC). Passive optical retrievals of LWP such as those performed by MODIS rely on cloud vertical structure assumptions to relate cloud optical thickness (τ) and re retrievals to a corresponding LWP. Typically these passive remote sensing techniques assume that clouds are vertically homogenous [Platnick et al., 2003]. However, it has been suggested that an adiabatic cloud model could potentially introduce more realistic assumptions for some MBL cloud regimes [Wood and Hartmann, 2005; Bennartz, 2007]. In reality, cloud vertical structure is often more complicated than either of these assumptions because structure can be altered by both precipitation and mixing processes. This work examines the impact of varied and realistic cloud vertical structures on retrievals requiring fixed homogeneous or adiabatic structure assumptions. To address this we use the DHARMA cloud large-eddy simulation (LES) model [Ackerman et al. 2004] and a MODIS-like satellite retrieval simulator [Zhang et al. 2012]. The LES and retrieval simulator allow for the direct comparison of retrievals to the in-situ microphysical structure of the LES cloud field. Physical properties from the LES cloud field such as the degree of adiabaticity and droplet growth lapse rate are examined and linked to the impact of retrieval biases. The retrieval comparison led to the development of a predictive theoretical framework for determining which of the LES pixels satisfied either homogeneous or adiabatic vertical structure assumptions. The theoretical model was also utilized to extend a single-layer adiabatic cloud model to an arbitrary two-layer model capable of characterizing the impact of entrainment features on cloud retrievals performed on the LES. Our results overwhelmingly demonstrate that the impact of realistic cloud vertical structure on retrievals is more complicated than either of the vertical structure assumptions currently being implemented by the remote sensing community.
