Wheeler Lake is a reservoir along the Tennessee River in northern Alabama. The Aqua MODIS Sea Surface Temperature product (above) showed that water temperatures along the axis of the lake were as warm as the lower 50s F (cyan color enhancement) on 07 February 2016.

Following the passage of a strong cold front on 08 February, the northwesterly flow of air with surface temperatures in the 30s F on 09 February allowed for a narrow “lake effect” (or in this case, river effect) snow band to form over Wheeler Lake, which created accumulating snowfall to the southeast (downwind) of the lake. This lake effect snow band could be seen in a RealEarth composite of Suomi NPP VIIRS / Aqua MODIS true-color Red/Green/Blue (RGB) images and radar reflectivity (below). The lake effect plume began to shift northward during the afternoon hours, as surface winds briefly backed to a more westerly direction.

On 10 February, the northwesterly flow of cold air was less pronounced, but was still enough to allow for a narrow lake effect plume to be seen early in the day on 1-minute interval GOES-14 Super Rapid Scan Operations for GOES-R (SRSO-R) images (below; also available as a large 89 Mbyte animated GIF). As the clouds cleared during the afternoon hours, small patches of white snow cover could be seen just southeast of Wheeler Lake.

In a comparison of Terra MODIS true-color and false-color RGB images (below), the presence of snow cover (cyan in the false-color image) could be seen between the lines of cumulus clouds.

Data from NOHRSC (below) showed that as much as 3.0 inches of total snowfall was measured downwind of Wheeler Lake (in the higher elevation of the Union Hill area) during the 09-11 February period, and the snow depth on the morning of 10 February was 2.5 inches at that location (enough to be seen on the GOES-14 visible images above).

Additional information and images of this event can be found here.

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1-minute interval GOES-14 Super Rapid Scan Operations for GOES-R (SRSO-R) Visible (0.63 µm) images (above; also available as a large 71 Mbyte animated GIF) revealed the formation of clusters of aircraft “hole punch clouds” over central North and South Carolina on the morning of 09 February 2016. These types of cloud features form when aircraft fly through a layer of clouds composed of supercooled water droplets; cooling from wake turbulence (reference) and/or the particles from the jet engine exhaust which may act as ice condensation nuclei cause the small water droplets to turn into larger ice crystals (which then often fall from the cloud layer, creating “fall streak holes“). Similar features have been discussed in previous blog posts.

A comparison of GOES-14 Visible (0.63 µm, 1-km resolution) and Shortwave Infrared (3.9 µm, 4-km resolution) images (below; also available as a large 71 Mbyte animated GIF) offered evidence that the cloud material within each “hole punch” was composed of ice crystals, which exhibited colder (lighter gray) IR brightness temperatures than the surrounding supercooled water droplet clouds. It is likely that many of the hole punch features were caused by aircraft ascending from or descending to the Charlotte Douglas International Airport in North Carolina (KCLT).

In a comparison 1-km resolution POES AVHRR Visible (0.86 µm) and Infrared (12.0 µm) images (below), the cloud-top IR brightness temperatures in the vicinity of the hole punch features were only as cold as -20 to -24º C (cyan to blue color enhancement), which again is supportive of the cloud layer being composed of supercooled water droplets.

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One-minute interval Super Rapid Scan Operations for GOES-R (SRSO-R) Visible (0.63 µm) and Water Vapor (6.5 µm) images (above) showed the development and rapid intensification (surface analyses) of a mid-latitude cyclone just off the East Coast of the US on 07 February 2016. The storm produced moderate to heavy rainfall across eastern North Carolina, along with some light to moderate snow and sleet at a few locations.

A closer view of the GOES-14 Visible (0.63 µm) images (below; also available as a large 85 Mbyte animated GIF) revealed the rapid motion of low-altitude clouds when gaps in the high-altitude clouds were present. Very strong winds were caused by the strong pressure gradient, with gusts as high as 72 mph, and a large Royal Caribbean cruise ship experienced some damage due to the winds (media report 1 | media report 2). The corresponding GOES-14 Water Vapor (6.5 µm) images, which also extend further in time after dark, are available here.

A comparison of 1-km resolution POES AVHRR Visible (0.86 µm) and Infrared (12.0 µm) images at 2202 UTC (below) displayed greater detail of the classic “cusp” signature of high clouds, indicative of an intensifying surface cyclone (VISIT lesson). At the time, wind gusts to 60 knots were seen at one the buoys off the coast of North Carolina.

At 0137 UTC, a closed-off low level circulation center could be seen on a POES AVHRR Infrared (12.0 µm) image (below).

Additional information on this storm can be found on the Satellite Liaison Blog.

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There are two animations a the top of this blog post, one with a 1-minute timestep, above, and one with a 15-minute timestep, below. The strong winter storm that hit Colorado on Monday 1 February (Blog Post) was accompanied by multiple cloud layers and snow during the day on Monday was not steady. Was it related to the holes that are present in the clouds? How easy is it to track the different clouds to predict the arrival, overhead, of a gap in the high clouds? Especially for the low clouds in eastern Colorado in this example, cloud hole tracking can be done with more confidence with 1-minute imagery. Decision Support related to short time-scale variability in snow accumulations can be done with more confidence with the 1-minute imagery.

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On 7 February 2016, GOES-14 in SRSO-R monitored the development of a very strong storm over the Atlantic Ocean (blog post) east of the United States. Consider the animations below, starting with the standard GOES-East time steps (nominally every 15 minutes with some gaps). If you are monitoring the storm development, or the motion of the individual convective clouds, the 15-minute temporal gaps are insufficient for confident detection of cloud motions. When, for example, does the surface circulation first appear? Do the cloud towers that appear in the 15-minute animation persist over the course of 15 minutes, or do they decay and reappear? In the succeeding animations below, at 5- and 1-minute intervals, increasing amounts of detail are present because the better temporal resolution is convincingly following features. Additionally, the precise timing of events is better captured.

The differences between 1-, 5- and 15-minute time steps are visualized in the rocking animation below. The right-most panel has a 15-minute timestep always, the middle panel starts with a 15-minute time step before switching to 5-minute, and the left-most panel shows 15-minute, 5-minute and 1-minute time steps. Note how the convective towers appear and disappear on timescales that make resolution in the 5-minute time step difficult and in the 15-minute timestep impossible. The region below is excised from the animations above, and is over the ocean south of the developing low pressure system.

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