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GOES-R Snow Cover

Frequently Asked Questions about the GOES-R Snow Cover Product

 

1) What is this product?

The GOES-R Snow Cover produces a fractional snow cover for all clear pixels.  The resolution of this product is 2km.  The GOES-R Snow Cover product is only available during the day.  It is accurate to 0.15 (15%) per pixel.  The values vary from 0.0 to 1.0.  The GOES-R Snow Cover product is not produced beyond 62 degrees local zenith angle.1

This product is useful when trying to assess if snow is present on the ground.  It can also be used to distinguish between snow-covered ground or low/high cloud

 

2) How often do I receive this data?

The cadence of the Snow Cover product is 60 minutes regardless of scan mode.  However, there are independent images for Full Disk, CONUS, and Mesoscale scans.

 

3) How do I display this product in AWIPS-II?

To display this product in AWIPS-II, go to the "GOES-R" tab of the CAVE menu, then select "Derived Products."  From there, select the region of interest (GOES-E, GOES-W, or GOES Test and Full Disk, CONUS, and Mesoscale).  Then, select the Snow Cover product.

Alternately, use the AWIPS Product Browser.  Select "Sat", then either "GOES-16" or "GOES-17".  From there, choose "Full Disk", "CONUS", or "Meso", then select "SC."

 

4) How do I interpret the color maps associated with this product?

Color maps have not been established for this product.

 

5) What other imagery/products might I use in conjunction with this product?

This product can be used in conjunction with visible 0.64um satellite imagery (if available) to assist with differentiating between clouds and snow on the ground.  

 

6) How is this product created?

The GOES-R Snow Cover product utilizes GOES-R bands 0.47 um, 0.64 um, 0.86 um, 1.37 um, 1.6 um, 2.2 um, 3.9 um, and 10.33 um.  The algorithm performance is sensitive to imagery artifacts or instrument noise. Since snow is a highly reflective material in the visible portion of the electromagnetic spectrum, the product may be sensitive to detector saturation and damping. Also, since the algorithm relies on spectral mixture analysis, imagery artifacts and instrument noise will negatively impact its performance. 1

 

The ancillary data used to calculate the cloud top height includes1:

- Interpolated spectral libraries calculated ahead of time in five-degree increments of angles of solar zenith, view zenith, and relative azimuth (solar azimuth – view azimuth). These libraries are used to de-mix the spectral signature from a pixel. The various calculated spectra are used alone or in pairs to determine the best fit to the spectral response in the pixel.

 

- Model types are used to direct the algorithm on how to attempt to unmix a pixel’s spectral signature. Currently, there are spectral libraries for many variations of snow, vegetation, rock, and ice. 

 

- Dynamically-updated (by GOESRSCAG) non-snow endmember per pixel. The most prominent non-snow endmember for each pixel is stored in a file, and on subsequent runs, the non-snow endmember which corresponds to this ground covering is used to calculate the snow fraction. This field is recalculated for pixels which are close to solar noon (for best solar illumination). 

 

- Land-Water Mask. GOESRSCAG will skip non-land pixels identified in a common product land-water mask

 

1Cline, Donald, Andrew Rost, Thomas Painter, and Christopher Bovitz. NOAA NESDIS Center for Satellite Applications and Research Algorithm Theoretical Basis Document: Snow Cover v.2.1. 7 September 30, 2010. http://www.goes-r.gov/products/ATBDs/baseline/baseline-snow-cover-v2.0.pdf

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