On the GOES-R side of the house the plan currently consists of four main products: the Flight Icing Threat (FIT), simulated ABI imagery from both the WRF and NAM Nest, and further demonstration of the Fog and Low Stratus (FLS).
The FIT consists of three main components including a single-layer threat index, and multi-layer threat index, and a display which keys in on supercooled large droplets (SLD). The single-layer index utilizes a number cloud properties to identify icing conditions likely at the cloud tops where the satellite signal is not blocked by thick ice clouds. The multi-layer also uses these properties, but in addition it utilizes cloud optical properties to identify icing beyond thin ice clouds, or cirrus. Lastly, the SLD component uses a similar process to the GOES-R Cloud Phase product, but keys only in on potential areas of supercooled cloud droplets. These areas are then further distinguished based on the surface conditions (snow/ice or no snow/ice) and size, with larger SLDs corresponding to a higher likelihood of icing.
Each component is available for GE and GW, and also in a merged display. Check out the loop below for a sneak peek: the GE single layer, the merged single-layer, the merged multi-layer, and the merged SLD. The final image is the GOES-R Cloud Top Height (meters), used to determine the height of the given FIT value. Bases are typically determined via freezing level.
Our simulated imagery is the same as that demonstrated within the 2012 Summer Experiment, with synthetic imagery generated not only from the WRF, but recently the NAM Nest as well. Data from the two models will provide a comparison of model performance as well as allow more familiarization with future GOES-R bands.
Thanks to all who have been involved in the preparations for the experiment! To keep up to date on the latest GOES-R activities during the experiment, please stay tuned to the blog. Content will likely consist of screen captures from various cases throughout each day as well as forecaster feedback and comments.
See you next week!

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