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Ice Cloud Optical Thickness, Effective Radius, And Ice Water Path Inferred From Fused MISR and MODIS Measurements Based on a Pixel‐Level Optimal Ice Particle Roughness Model
Author(s) -
Wang Yi,
Yang Ping,
Hioki Souichiro,
King Michael D.,
Baum Bryan A.,
Di Girolamo Larry,
Fu Dongwei
Publication year - 2019
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2019jd030457
Subject(s) - effective radius , moderate resolution imaging spectroradiometer , environmental science , spectroradiometer , liquid water path , ice cloud , pixel , remote sensing , radius , surface roughness , range (aeronautics) , atmospheric sciences , meteorology , materials science , physics , optics , geology , aerosol , satellite , astrophysics , computer science , reflectivity , astronomy , composite material , radiative transfer , computer security , galaxy
The Multi‐angle Imaging SpectroRadiometer (MISR) provides measurements over a wider scattering‐angle range for a given location than a cross‐track scanning sensor such as the MODerate resolution Imaging Spectroradiometer (MODIS). Based on a full year (2013) of fused MISR‐MODIS datasets, we develop a variable surface roughness model for ice particles with the goal of identifying the optimal degree of roughness in the ice model for a given pixel containing single‐layer ice clouds. For the MISR‐MODIS observations over oceans, severe roughness values are often selected for a pixel when optical thickness (τ) and particle effective radius ( R eff ) are large in conjunction with larger cloud heterogeneity index ( H σ ) or a warmer cloud top temperature. Furthermore, τ, R eff , and ice water path are retrieved with the optimal model and compared to operational MODIS Collection 6 (MC6) products that assume a constant roughness. In general, the retrievals based on the present optimal model lead to greater consistency with MISR measurements, and result in larger median τ by 10.1% and smaller median R eff by 6.5% but almost identical ice water path in comparison with the MC6 counterparts. The higher average τ value is caused by a slightly larger number of large τ cases, but the smaller average R eff value is due to the shifting of the retrieved R eff value toward smaller values by approximately 2–4 μm in comparison to the MC6 distribution over all seasons. Both τ retrievals have similar regional and monthly variations, but a larger annual cycle of R eff is associated with the optimal model.