Abstract
The simplest way of building a look-up table (LUT) for the retrieval of cloud microphysical properties is to use a standard atmospheric profile and vertically uniform cloud microphysics. Such an assumption has been demonstrated to be incoherent with in-cloud observations. This paper aims to show the effect of some atmospheric conditions associated with fog as well as its macro-and microstructure on brightness temperature (BT) for the MSG/ SEVIRI satellite using libRadtran. The sensitivity tests were performed by gradually changing some features from the initial data, such as cloud cover, total water vapor column, thermal inversion intensity, fog depth, fog microstructure, and others. The results revealed that some variables can cause significant variations on BT and, consequently, discrepancies in the retrieval of fog microphysical properties. Also, a variation as high as 0.5°C was found on BT just by switching uniform to the non-uniform profile of fog microphysics depending on the channel, the droplet size, and optical thickness.
Highlights
This paper aims to show the effect of some atmospheric conditions associated with fog as well as its macro-and microstructure on brightness temperature (BT) for the MSG/ SEVIRI satellite using libRadtran
A variation as high as 0.5 ̊C was found on BT just by switching uniform to the non-uniform profile of fog microphysics depending on the channel, the droplet size, and optical thickness
Daytime fog detection and microphysical recovery consist of combining visible and near-infrared channels so that visible channels are more sensitive to fog optical thickness and near-infrared channels are more sensitive to fog droplet size as in [4] [5] [6]
Summary
[10] used a radiative transfer model to identify the ideal channel combinations for the retrieval of low cloud microphysical properties in the infrared spectral range and they found that MSG infrared channels were more sensitive to particle size than to optical thickness. Such a result showed that the retrieval of cloud microphysical properties at night can be a task somewhat difficult. The difficulty is associated with the understanding of the roles of each variable in the microphysical retrieval That they vary as the temperature of the surface and the azimuth angle can generate convolutions in the microphysical reference and this can make microphysical recovery difficult since convolutions can generate ambiguous results. This means that for the same brightness temperature, it is possible to obtain two distinct results of droplet size and liquid water content
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