V20 Dust To Dust Pdf Download [EXCLUSIVE]
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v20 dust to dust pdf download
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Example of feature imprinting upon GOES-16 ABI GeoColor V2.0 imagery from 2156 UTC 10 Apr 2019. A lofted dust signal, based on the spectral difference between the 10 and 12 μm, is normalized and used to modulate the RGB color components of the GeoColor image in a nonuniform way, imparting a yellow tonality to regions of high dust confidence (see text for details).
To frame this discussion, Fig. 4 shows how the dayside and nightside components of GeoColor V2.0 combine to form the final blended imagery product. The quality of the dayside imagery is improved over GeoColor V1.0 (Fig. 3), due to the ABI processing described in section 5a(1). In contrast to GeoColor V1.0 there is asymmetry in terms of the layer depths of the vertical stacks, with the dayside being a single layer of information [Synthetic Hybrid Atmospherically Corrected (SHAC) true color]. Inserting a layer on the dayside (e.g., a lofted dust enhancement) in between the high clouds and the surface for example, would require definition of an independent upper layer (such as Fig. 3a).
The DEBRA technique (Miller et al. 2017), mentioned in section 5a(2), has been applied to isolating lofted mineral dust features in satellite imagery atop complex surface backgrounds. The technique leverages conventional infrared spectral differences for dust detection, coupled with a priori information on how those same signals are expected to appear in land surface background under dust-free conditions (via cloud-cleared background information or via a surface spectral emissivity database), as a way of reducing dust false alarms caused primarily by deserts).
In a similar way, the DEBRA dust product is communicated as value-added imagery by imprinting the dust confidence factor upon conventional grayscale visible and infrared imagery, enabling coloration of targeted areas of the image that provide significant isolation of the dust features. This concept of feature imprinting offers yet another method of introducing quantitative information to satellite imagery in a way that preserves the meteorological context while highlighting features of interest to the human analyst. 350c69d7ab