Notice:
This site has successfully transitioned the image data source from GOES-16 to
GOES-19. There are some remaining anomalies in the production of mesoscale
geocolor images which are being investigated. Everything else should be operating
as expected. Please contact:
NESDIS.STAR.webmaster@noaa.gov if you have any questions.
18 Nov 2025 - 02:06 EST
18 Nov 2025 - 07:06 UTC
GOES-West Mesoscale view - Tropospheric Dust Content at 39°N - 119°W - Lyon County, NV
Half hour loop - 30 images - 1 minute update
To enlarge, pause animation & click the image. Hover over popups to zoom. Use slider to navigate.
While GOES animation code will not run on older Internet Explorer browsers,
they work in the newest versions of Microsoft Edge. If you are using
Internet Explorer, please try a different browser: Chrome, Firefox, Safari, or
MS Edge are all supported.
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0633 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0634 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0635 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0636 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0637 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0638 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0639 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0640 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0641 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0642 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0643 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0644 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0645 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0646 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0647 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0648 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0649 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0650 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0651 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0652 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0653 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0654 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0655 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0656 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0657 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0658 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0659 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0700 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0701 UTC
Tropospheric Dust Content - RGB for identifying tropospheric dust - 18 Nov 2025 - 0702 UTC
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.