Post Atmospheric River Events in California, 011317

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.

states2

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.

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Atmospheric River event of 7-9 January 2017

A significant atmospheric river affected the west coast on 7-9 January, 2017.  The GOES water vapor imagery shows the development of clouds associated with an approaching trough off the west coast, these clouds advected into the west coast:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/8jan17_wv&loop_speed_ms=80

and resulted in significant precipitation across California:

ahps_precip

 

at times, we can infer moisture from the water vapor imagery.  In this case we can infer abundant moisture where the clouds develop and advect onshore, however the water vapor channel is not the best way to assess moisture.  Instead, making use of a satellite derived moisture product (i.e., precipitable water) is a much better approach.  The CIRA layered precipitable water (PW) product:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/8jan17_lpw

Provides not only a plan view of the moisture, but also a 3-dimensional perspective since it observes moisture at different layers in the vertical.  The lowest layer (upper left) is the PW (units are inches) in the surface to 850 mb layer, the upper right is the PW in the 850-700 mb layer, the lower left is the PW in the 700-500 mb layer, and the lower right is the PW in the 500-300 mb layer.  Typically the greatest magnitude of moisture is found in the lowest layer, however what the mid/upper level layers provide can be very important for significant precipitation events.  Usually, significant precipitation events are characterized by relatively high precipitation efficiency, which tends to exist in an environment that is saturated through a deep layer.  Therefore, if the PW is relatively high in the lower, mid and upper levels, the precipitation efficiency is near 100%.  As you may suspect, the PW values in all 3 layers for this case are quite high.  Keep in mind, this product utilizes data from polar orbiting microwave instruments which means they can see through (most) cloud cover, unlike the GOES Imager or Sounder instruments.

The Orographic Rain Index (ORI) is a product developed by CIRA made specifically for these type of Atmospheric River (AR) events.  The product is based on research by Alan White and others from NOAA/PSD that investigated water vapor transport into terrain for AR events.  ORI produces an index related to this water vapor transport using satellite derived TPW combined with GFS winds and high resolution terrain data.  The idea is to highlight regions of terrain induced short-term flooding potential.   For this particular case, the ORI product:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/8jan17_ori

shows higher values oriented along various ridgelines in central California that would be most susceptible to flooding for this storm.  A more detailed description of ORI can be found at http://rammb.cira.colostate.edu/research/goes-r/proving_ground/cira_product_list/orographic_rain_index.asp

Real-time data is available at:

http://rammb.cira.colostate.edu/ramsdis/online/goes-r_proving_ground.asp#Orographic_Rain_Index_(ORI)

Atmospheric Rivers typically have relatively strong winds in the low to mid layer to help advect moisture rapidly.  The winds in this layer were particularly strong for this event, with wind gusts as high as 173 mph observed:

squaw_summit_obs

Link to post from Twitter

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