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Today we’re taking the chance to highlight a few colorized GOES products that are produced by the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University in Fort Collins, Colorado. The three products we’re looking at today are RGB (red-green-blue) combinations for Cloud-Snow Coverage, DEBRA Dust, and GeoColor images. These products have been available since mid 2021, and are distributed through Unidata’s LDM on the NIMAGE feedtype.
NOTE: Unfortunately, CAVE renders RGB products via the hardware on the graphics card, which is not supported on our CAVE distributions for MacOS or Virtual Machine. This is currently only supported on Direct Windows and Direct Linux installations.
These CIRA products are only produced for the East and West CONUS Sectors. All three products can be founded and loaded in CAVE through our Satellite menu:
Satellite > [GOES-East CONUS | GOES-West CONUS] > RGB Composites > Under the CIRA RGBs (derived at CIRA) subheader
The products can be loaded and displayed like any other satellite imagery.
The Day Cloud-Snow product is produced through a combination of six different GOES channels and is used to help distinguish clouds from snow and ice. This is a daytime only product for snow/cloud discrimination, at night only a single channel is used to provide cloud information only. Unlike other RGB snow/ice products, snow is portrayed in a more intuitive color – white. Also, this product discriminates between low and high clouds. To learn more about the color meanings please refer to this Quick Guide. An example from CAVE is shown below:
The DEBRA Dust product uses the Dynamic Enhancement Background Reduction (DEBRA) algorithm to produce images where dust can be quickly and easily identified with its yellow color. The color intensity increase also corresponds to the increased likelihood of dust. More information about this product can be found on the Quick Guide. An example from CAVE is shown below:
The GeoColor product provides an approximation for true color Earth imagery. The striking color and detail is not only eye-catching, but also provides a valuable way to identify many weather conditions and phenomena. At night, a multispectral product is created that differentiates between low liquid water clouds and higher ice clouds with static city lights for geo-referencing. More information about this product is provided on the Quick Guide. An example from CAVE is shown below:
Aside from using CAVE to view and analyze these data products, you can also access the same data through python-awips. We have written an example notebook of how to access and download the images locally. This data can also be used in combination with any other dataset from EDEX, or other outside data as well to produce more accurate and useful figures or analysis.
We hope you enjoyed learning about these useful products produced by CIRA. Please check back in two weeks for our next blog post.
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This blog was posted in reference to v18.2.1-6 of NSF Unidata AWIPS