Skip to Navigation Skip to content

Regional and Mesoscale Meteorology Branch

Search the RAMMB website

GOES Blowing Dust

Product Information:


Expand All | Collapse All

The Cooperative Institute for Research in the Atmosphere (CIRA) in Fort Collins, Colorado, together with the NOAA/NESDIS RAMM Branch is developing and distributing the Blowing-Dust Product.

The Blowing-Dust product is created at CIRA, and will be sent to NWS Central Region Headquarters, and then distributed to the WFOs as a product on their AWIPS.

The size of one east or west Blowing-Dust product image is 20 MB, with updates available every 30 minutes.

Product Description:


Expand All | Collapse All

The Blowing-Dust satellite imagery product, developed at the CIRA, is demonstrated on the RAMSDIS Online web page for GOES-West only, because the “split-window” bands are currently available on that operational GOES satellite only. The product displays standard GOES Imager data in a unique way using simple image differencing and color enhancement. Inputs are the 10.7 um (more-transparent longwave) and 12.0 um (less-transparent longwave) infrared window bands from the GOES Imager.

The Blowing-Dust product demonstrates a unique kind of imagery that is still available on older GOES Imager instruments and all GOES Sounder instruments (although at lower 10 km spatial resolution). The “split-window” bands will reappear in the GOES-R era. GOES-R will feature the Advanced Baseline Imager (ABI) sensor which will be able to produce both a higher spatial resolution (2 km) and higher temporal resolution (5 min) version of the Blowing-Dust product.

Here, is a brief description of how the Blowing-Dust product is created from GOES Imager data:

The Blowing-Dust product can be computed from the two longwave infrared window bands available on older operational geostationary satellites, up through GOES-11. (On newer GOES, the less-transparent longwave band was replaced by a 13.3 µm band used to better detect the levels of clouds.)

Simple image differencing is used to compute the longwave infrared window band difference in temperature units. Since the brightness temperatures in two longwave window bands (10.7 minus 12.0 µm) are only slightly different, that temperature difference has an average near zero and a range from at most about -10°C to +10°C, and much less for most image features. That difference is then stretched to fill the full range of available image counts (0-255) and is color-enhanced to emphasize the negative temperature differences (as yellow and red) that are indicative of blowing dust (with the more intense dust as red).

The basis for the Blowing-Dust product, but without the cloud mask, can be seen in Figure 2, (where the enhancement colors are similar but slightly shifted in the Blowing-Dust product to eliminate red colors for the smallest positive temperature differences.) The product is then improved by applying a cloud mask that eliminates the larger positive temperature differences (shown in blue in Figure 2).

bddg2

Figure 2. Example of the Blowing-Dust image product over the western United States, without the cloud mask applied to produce the white areas in Figure 1. The product depicts negative temperature differences in red and positive temperature differences in yellow and blue. Visible imagery is used to detect and mask out clouds, eliminating much of the blue area associated with clouds when the Blowing-Dust product in Figure 1 is created. The color table is also shifted slightly in Figure 1, to eliminate all red values that represent the smallest positive temperature differences in this image.

The Blowing-Dust product is generated similarly day or night, since the longwave window bands are not affected directly by reflected solar radiation.

Product Examples and Interpretation


The Blowing-Dust product is even better when viewed as an image loop. Real-time examples are available on the RAMSDIS Online web page for GOES-West only, but the product only infrequently shows blowing dust, usually during the winter/spring months when strong winds stir up the lowest levels of the atmosphere and particles are available to become dust. The best examples of blowing dust occur in the western or central U.S., typically over dry terrain, during strong wind events.

In Figure 1 the surface winds at the time of the image are plotted on top of the Blowing-Dust product. The plotted winds help verify that the yellow and red portion of the image are indeed blowing dust, whipped up at the leading edge of a low pressure system centered slightly to the north and west of the (yellow and red) dust signature.

The negative temperature differences that appear yellow and red (and are indicative of blowing dust) are caused by opaque matter carried aloft by winds. That matter, which partially blocks the view of the surface, under normal conditions has a brightness temperature below that of the underlying surface. These lower temperatures are picked up preferentially by the less transparent of the two longwave window bands, and are emphasized as the negative temperature difference that is seen in the Blowing-Dust product.

Advantages and Limitations


The Blowing-Dust product provides a simple yet visually powerful display of areas of airborne dust whipped up by high winds. The color enhancement shows blowing dust as yellow and red, with red as thicker dust. The (red) signature of blowing dust is rather obvious for larger areas of blowing dust, but less obvious for tiny patches of dust, that may only occupy a few GOES pixels, as sometimes seen downwind of the Sierra Nevada mountains.

The main disadvantage of the product is that large portions of the southwestern U.S. have surface emissivity characteristics that give rise to negative temperature differences. These weak-but-false (yellow) dust signatures may appear during later portions of the day. While the Blowing-Dust product is not affected directly by reflected solar radiation, the solar heating during the day can result in a weak-but-false dust signal. A solution to this problem is to in observe the Blowing-Dust product over time, with a new image every 30 minutes, and to not rely on a single image for any blowing-dust signatures.

Interactions with NWS users via the Proving Ground will assist algorithm developers in improving this product, such as the desired enhancements, product scaling, etc., to best tailor this unique application to the end-user needs. The development of future, improved products will also benefit from user feedback.