Open AccessEstimating the vertical variation of cloud droplet effective radius using multispectral near‐infrared satellite measurements
Author(s) -
Chang FuLung,
Li Zhanqing
Publication year - 2002
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2001jd000766
Subject(s) - effective radius , multispectral image , remote sensing , satellite , marine stratocumulus , cloud top , environmental science , cloud computing , meteorology , geology , computer science , physics , aerosol , quantum mechanics , astronomy , galaxy , operating system
This paper presents a satellite‐based retrieval method for inferring the vertical variation of cloud droplet effective radius (DER) by utilizing multispectral near‐infrared (NIR) measurements at 1.25, 1.65, 2.15, and 3.75 μm, available from the Moderate Resolution Imaging Spectrometer (MODIS) satellite observations. The method is based on the principle that these multispectral NIR measurements convey DER information from different heights within a cloud, which is sufficient to allow for the retrieval of a linear DER vertical profile. The method is applicable to low‐level, nonprecipitating, stratiform clouds as their DER often increases monotonically from cloud bottom to cloud top. As such, an optimum linear DER profile can be derived by comparing multispectral NIR measurements to corresponding model values generated for a large set of linear DER profiles. The retrieval method was evaluated and compared to the conventional 3.7‐μm retrieval method by applying both methods to some marine stratocumulus clouds with in situ observations of microphysical profiles. Capable of capturing the DER variation trend, the retrieved linear DER profiles showed large improvement over the conventional 3.75‐μm retrievals. Mean differences between the linear DER retrievals and observed profiles were generally small for both cloud top and bottom (<1.0 μm), whereas the conventional retrievals are prone to systematic overestimation near cloud bottom. The sensitivities of the linear DER retrieval to various parameters, as well as the error analyses, were also investigated extensively.