NOAA GOES Image Viewer website
30 Jan 2023 - 15:18 EST
30 Jan 2023 - 20:18 UTC

GOES-West Mesoscale view - Tropospheric Dust Content at 39°N - 119°W - Lyon County, NV

Half hour loop - 30 images - 1 minute update

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Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1948 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1948 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1949 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1949 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1950 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1950 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1951 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1951 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1952 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1952 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1953 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1953 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1954 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1954 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1955 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1955 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1956 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1956 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1957 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1957 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1959 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 1959 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2000 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2000 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2001 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2001 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2002 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2002 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2003 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2003 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2004 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2004 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2005 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2005 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2006 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2006 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2007 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2007 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2008 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2008 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2009 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2009 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2010 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2010 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2011 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2011 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2012 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2012 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2013 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2013 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2014 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2014 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2015 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2015 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2016 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2016 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2017 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2017 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2018 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 30 Jan 2023 - 2018 UTC
legend for Dust RBG

Dust RGB key:

1 - Dust plume, day (bright magenta, pink) Note: Dust at night becomes purple shades below 3 km

2 - Low, water cloud (light purple)

3 - Desert surface, day (light blue)

4 - Mid, thick clouds (tan shades)

5 - Mid, thin cloud (green)

6 - Cold, thick clouds (red)

7 - High, thin ice clouds (black)

8 - Very thin clouds, over warm surface (blue)


Dust RGB Dust can be hard to see in visible and infrared imagery because it is optically thin, or because it appears similar to other cloud types such as cirrus. The RGB product is able to contrast airborne dust from clouds using band differencing and the IR thermal channel. The IR band differencing allows dust storms to be observed during both daytime and at night.

• For more details, see the Dust RGB Quick Guide, (PDF, 978 KB)