Tropical Storm Rina

Ever since Hurricane Ophelia, it has been rather quiet in the Atlantic Ocean in regards to tropical cyclone activity, but now we have Tropical Storm Rina in the midst. As of early morning, 7 November 2017, Rina is positioned in the central Atlantic Ocean and is projected to move north, then northeast, and is not expected to hit land. Rina’s magnitude will stay as a tropical storm, not becoming a hurricane during the remainder of its life cycle. The latest updates on Rina can be seen via the National Hurricane Center link, shown here.

Below is a Day/Night Band (DNB) image of Tropical Storm Rina located in the middle of the Atlantic Ocean taken at 0421Z, 7 November 2017. For readers that are not familiar, the DNB satellite product utilizes a sun/moon reflectance model that illuminates atmospheric features, senses emitted and reflected light sources and assists with cloud monitoring during the nighttime. In the image, notice the well-defined circulation of Rina, located just west of the convective clouds and bands. The identification of the circulations are crucial in tropical cyclone forecasting, specifically, in finding the strongest/intense part (s) of the cyclones, which can dramatically affect coastal areas with torrential rainfall, flooding, high winds and storm surge. Additionally, in the top-right corner of the image, the moon percent visibility and the moon elevation angle values are provided. The values imply that the the moon is above the horizon and provided adequate moonlight when the image was taken via satellite.

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Early Morning Fog in Colorado

Early this morning, 3 November 2017, the Colorado Front Range was inundated with fog and low stratus clouds. Fog persisted for several hours this morning. Below is an animation of the fog along the Front Range of Colorado via the ‘RAP Real-Time’ surface observations website, between 08-15Z. As a quick reminder, foggy areas are identified via pink, parallel, horizontal lines, sandwiched in-between the air temperature (red) and corresponding dew-point (green) values.

In complement to the surface observations, static satellite observations can be used to identify the fog/low stratus clouds via the Day/Night Band (DNB) product and the 10.7um -3.7um brightness temperature difference product. Static satellite observations were taken during the early morning hours, 3 November 2017, @ 0903Z (0303Z local time).

Day/Night Band (DNB) (0.7um)

The DNB provides the illumination of atmospheric features, senses emitted and reflected light sources and assists with cloud monitoring during the nighttime. The DNB image below, taken during the full moon stage of the lunar cycle, shows features over the state of Colorado. Dendritic snow patterns via reflected moonlight are seen in Central Colorado highlighting the location of the Rocky Mountains, with clouds to the east and west. Emitted city lights are also seen under the cloud cover, seen via bright clusters along the Front Range.

M15 (10.7um) – M12 (3.74um) brightness temperature difference 

In complement to the DNB, one can utilize the brightness temperature difference between the VIIRS M15-M12, which can assist in identifying which clouds are liquid water clouds, (in this case, fog/low stratus clouds seen as positive, blue values) in comparison to ice clouds (seen as negative, black values). The range of temperature values are displayed from -10 to +10 degrees Kelvin. The validation of the liquid water clouds along the Front Range, complements the surface observations that observed fog/low stratus clouds at this particular point in time (~9Z).

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GOES-16 perspective of Leeside cold front and associated gravity waves – 30 October 2017

The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing.  Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.

On 30 October 2017 GOES-16 observed a leeside cold front with associated gravity waves in the vicinity of eastern New Mexico and the Texas panhandle moving southward.  GOES-16 water vapor bands along with 3.9 micron band are shown here:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/30oct17/wv&loop_speed_ms=60

The 3.9 micron band highlights the colder temperatures behind the cold front, while the 3 water vapor bands highlight the gravity waves associated with the leeside cold front.  For further reading on leeside cold fronts and associated gravity waves you may read the following articles:

https://doi.org/10.1175/1520-0469(1999)056<2986:DTGWCB>2.0.CO;2

https://doi.org/10.1175/1520-0493(2001)129<2633:OONFPA>2.0.CO;2

How about a comparison between numerical simulation and GOES-16 observations?

The 4-km NSSL WRF-ARW model output from the 00Z 30 October run is shown below:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/30oct17/compare&loop_speed_ms=200

Top left) WRF synthetic 6.2 micron imagery

Top right) GOES-16 6.2 micron imagery (time matched with WRF)

Bottom left) WRF synthetic 6.95 micron imagery

Bottom right) GOES-16 6.95 micron imagery (time matched with WRF)

How well did the model capture the gravity waves associated with the leeside cold front?

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Early season lake-effect showers on 25 October 2017

The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing.  Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.

Cold advection over the relatively warm waters of the Great Lakes resulted in bands of showers across the Great Lakes as seen in the GOES-16 Daytime cloud phase distinction RGB:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/25oct17/rgb_daycloud&loop_speed_ms=60

This RGB product makes use of the 1.6 micron band which will highlight glaciation, as well as the 10.3 micron band which highlights cloud top temperature.  Note how well it depicts the lake-effect band over Lake Erie since it can discriminate between glaciated clouds versus non-glaciated clouds, as well as the cloud top temperature differences from the 10.3 micron band contribution.  In this case, temperatures are too warm for snow therefore the precipitation was in the form of rain.  Note the appearance of the band from the Buffalo WSR-88D:

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