As we all know there were two atmospheric river events that occurred in California in the past week and a half. Both atmospheric river events dumped large amounts of precipitation and snow to the state of California. There was a plethora of reports indicating mudslides, flooding and several feet of snow (10+ feet of snow) in the Sierra Nevada Mountains which also includes Lake Tahoe.
After these events concluded, approximately 12 January 2017, I was curious to see what the Near-Constant Contrast (NCC) satellite imagery features were picked up during the night-time hours. For readers that are not familiar with NCC, it is a derived product of the Day/Night Band (DNB), which utilizes a sun/moon reflectance model that illuminates atmospheric features, emitted lights and assists with cloud monitoring during the night-time hours.
The below AWIPS-II screenshot, shows the NCC satellite imagery hovered over the North-Central portion of California at 0910Z (0110 local time) on 13 January 2017. In the bottom-left corner is the moon percent visibility and the corresponding moon elevation angle above the horizon (expressed in degrees). Due to the fact that this observation was taken near the full moon stage of the lunar cycle, the atmospheric features can be easily detected. In the satellite image one can see clouds seen off the coast of California, the emitted city lights of San Francisco and Sacramento. Additional features that can be seen are the low clouds and fog that are located in the north-western part of the state, the snow over the Sierra Nevada mountains, and some high-level clouds hovering over the city of Reno, Nevada.
The high level clouds are not as discernible over the mountains, since both the clouds and snow in the mountains both reflect the color white. By inference, one can differentiate between the two by the texture difference between the clouds (broad, uniform, white swaths) and snow (white dendritic formations, over the mountains). The Cooperative Institute for Research in the Atmosphere (CIRA), has been working on products that could help discriminate between snow and mid-to-upper level clouds, which hopefully one day will be implemented into AWIPS-II.