In addition to its use in detecting wind fields over water (link 1, link 2), SAR data can also be used to detect ice. An example is shown above: similar domains on 20 and 24 January 2022 (from this website; this image on 20 January 2022 and this on one 24 January 2022) are toggled. There is a general increase in Lake Michigan shore ice off shore of southwestern Lower Michigan. Ice concentrations have also increased in western Lake Erie, Lake St Clair, Saginaw Bay in Lake Huron, and along the southwestern shore of Lake Huron. Strong winds were occurring over Lake Huron on the 20th as denoted by the yellow enhancement over the Lake.

SAR data are best used by viewing them each day. The imagery below shows views on different days in December 2021 and January 2022 over Lakes Erie (below) and Michigan (bottom). Note how ice cover can diminish (for example, over Saginaw Bay between 16 and 20 January) in response (typically) to strong winds that can move ice to the middle of the lake where it will melt.

A similar occurrence is shown in Lake Michigan (bottom): there is a filament of near-shore ice on 21 January that had detached from the shoreline under strong southwesterly flow. On 1200 UTC on 22 January, when strong southwesterlies continued, the ice is gone. It’s also not present on 1208 UTC on 23 January, when winds shift back to northerly. Detachment of ice from the shore can be a hazard to fishermen! The Lake Michigan cases also include very strong southwesterly winds (denoted by the yellow enhancements).

Note that ice in a cloud can also cause strong returns that can be misinterpreted as strong winds. Ice will strongly reflect the microwave signals from the RCM (RADARSat Constellation Mission) satellites. That’s the case in this image over Lake Ontario, and this summertime convection view of Lake Superior. Use caution when you see very strong winds; ask: could this be ice in the cloud, or in the lake?

GOES-16 Visible imagery, below, from 21 January 2022 (more imagery from this date is available here), shows challenges in monitoring ice in single-banded imagery. The detached shoreline ice noted in the SAR imagery becomes more faint with time, suggesting melting. The ice over southern Lake Michigan is apparent. Clouds over western Lake Erie make it very hard to interpret ice coverage there.

Very cold air is forecast to overspread the Great Lakes this week. Check to see if ice coverage increases at this link!

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GOES-16 “Red” Visible (0.64 µm) images [click to play animated GIF | MP4]

1-minute Mesoscale Domain Sector GOES-16 (GOES-East) “Red” Visible (0.64 µm) images (above) displayed mesovortices over southern Lake Michigan on 21 January 2022. The formation of these mesovortex features was aided by a mid-lake convergence of surface winds, which was suggested by RAP40 surface wind fields and shown n more detail by Metop-C ASCAT winds from this site (below).

Metop-C ASCAT surface scatterometer winds [click to enlarge]

Farther to the north, in spite of a cold night across northeast Wisconsin and Upper Michigan — with morning low temperatures of -30ºF at Laona, Wisconsin and -39ºF at Amasa, Michigan — GOES-16 Visible images (below) showed that southerly winds helped to open an ice lead near the center of Green Bay, with a slow northward drift of pack ice in the northern half of the bay. A lone ice floe was also seen moving northward near the western edge of the clouds in Lake Michigan.

 GOES-16 “Red” Visible (0.64 µm) images [click to play animated GIF |MP4]

A toggle between NOAA-20 VIIRS True Color and False Color RGB images (below) revealed a more detailed view of the ice structure — and also showed the narrow southwest-to-northeast oriented damage path that remained from a June 2007 EF-3 tornado that went through a portion of Menominee, Langlade and Oconto counties. The higher spatial resolution of the VIIRS imagery helped to highlight the aforementioned isolated ice floe in Lake Michigan (which appeared as cyan in the False Color RGB image).

NOAA-20 VIIRS True Color and False Color RGB images [click to enlarge]

To the east, mesovortices were also observed in Lake Huron – long with ice floes drifting away from the coast of Lower Michigan (below).

GOES-16 “Red” Visible (0.64 µm) images [click to play animated GIF | MP4]

A was the case in Lake Michigan, these Lake Huron mesovortices were forming along an axis of surface wind convergence, seen in Metop-B ASCAT data (below).

Metop-B ASCAT surface scatterometer winds [click to enlarge]

A larger-scale toggle between NOAA-20 VIIRS True Color and False Color RGB images — created using data received from the SSEC/CIMSS Direct Broadcast ground station — provided a view of the entire Great Lakes region (below). 

NOAA-20 VIIRS True Color RGB and False Color RGB images (credit: Margaret Mooney, CIMSS) [click to play animation]

===== 23 January Update =====

GOES-16 “Red” Visible (0.64 µm) images [click to play animated GIF | MP4]

On 23 January, GOES-16 Visible images (above) showed that northwesterly winds were causing a few ice floes to drift eastward out of Green Bay and into Lake Michigan.

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MIMIC Total Precipitable Water fields for the 24 hours ending 1700 UTC on 21 January, above, show abundant moisture flowing into southern Alaska. Hourly GOES-17 infrared imagery (Band 13 clean window infrared imagery at 10.3 µm), below, shows a large cyclonic circulation to the south and west of Alaska that is helping to draw moisture towards the state. Level 2 Total Precipitable Water (TPW) is overlain on the imagery and two things stand out: because it is a clear-sky only product, and because the north Pacific Ocean is very cloudy on the 21st, there is little TPW information. Also, GOES-R Total Precipitable Water is not completely Full Disk; TPW is computed to a Local Zenith Angle of 67^o (ATBD) and you can see the cut-off for the product in northwestern Canada. Those two things argue for the utility of microwave detection of moisture over Alaska, as shown above.

Much of Alaska Southeast from Yakutat to Wrangell is under a Flood Watch. (Image, taken from this site)

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The Community Satellite Processing Package (CSPP) Algorithm Integration Team (AIT) has released a new version of processing software that creates (using updated Enterprise algorithms) Level 2 GOES-R products from radiance products. It also includes processing to provide Quick Look imagery for those products; that is, if you have the processed Level 2 product files, you can display them. One example is shown above, Cloud Top Phase from 1401 UTC on 20 January 2022.

The processing package is available here (a quick easy registration may be required): Look for “AIT Framework V2.0beta4 Software for Linux” and download the gzipped tar file. Note also that documentation is also available (link). Per that documentation, I downloaded the software into a directory that I changed directories to, and I put that directory at the front of my unix PATH, i.e., export PATH=”$PWD:$PATH”. Then I used the aitf-ql (“ql” for quick-look) command:

aitf-ql /path/to/directory/holding/L2products/ACTPC/*s20220201401*.nc --image_size 2560.0 1920. -o /home/scottl/

I have specified both the image size, and the output directory. If you have access to L2 imagery (in NOAA CLASS, for example), this is an easy way to view the imagery. Note that this software will also create QuickLooks from ABI radiance files, as the GOES-17 example below shows. You can create imagery for computed brightness temperature (Bands 7-16) or reflectance (Bands 1-6).

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