A series of strong upper jets and related large scale subsidence helped to bring gusty winds to northeast Colorado for an extended period from 5-7 January 2020. Winds across the eastern plains generally gusted as high as 30-50 mph, while winds in the foothills and mountains peaked above 60 mph, with some reports of winds in excess of 80 mph.
During the afternoon of the 6th, gusty winds across the plains in the presence of dry, dormant fields resulted in widespread blowing dust. Recall the 10.3 – 12.3 um “split window difference” is able to highlight lofted dust quite well given the absorption of radiation at 10.3 um by silicate particles present in the dust. When lofted dust is present in the low levels, therefore, the 10.3 um band will sense slightly higher in the atmosphere, or cooler temperatures, compared to the 12.3 um band, resulting in a slightly negative SWD. For this event, the lofted dust is readily apparent in the SWD across NE Colorado as darker shades of gray (Fig 1). I prefer a linear gray scale color table when using the SWD, whether it be for detecting lofted dust or moisture gradients. For this case, the range of the gray scale was adjusted to -2 to 5 to better highlight the lofted dust. It is recommended and simple to adjust the range on the fly to make the feature of interest stand out. However, a default value from around -3 to 10 will at least prove useful for initial detection.
The SWD is combined with the 10.3 um IR-Window channel and 11.2 µm – 8.4 µm Split Cloud Phase Difference (SCPD) to give us the Dust RGB, which can also be used for cloud classification. Similar to the SWD, the SCPD will highlight low-level lofted dust (small positive values). For this case, the dust is highlighted in the default RGB, as pink (Fig 2).
A slight modification to the RGB increases contrast and allows for easier identification of the dust plume. Instead of pink, the dust now appears as a dark blue above a brighter cyan/blue background (Fig 3). Low clouds appear as bright green, very cold surface as slightly darker green, and warmer surface as brighter cyan. High clouds are red.
The difference in RGB recipe is shown in Figure 4.
There is a GOES-R derived product for dust detection. In this case, it appears to capture the most opaque region of the dust plume (Fig 5).
That night, strong winds continued across the front range, extending into the adjacent plains. Surface observations are unable to capture the spatial intricacies of the gap winds as they seep into the lower elevations and I-25 corridor. Overnight GOES IR imagery showed the extent of the gusty winds via the presence of the warm anomalies due to the strong sinking/warming flow from west to east off of the high terrain (Fig 6).
In this example the warmer brightness temperatures are represented by darker shades of gray, while the cooler temperatures are lighter shades of gray. Gusty westerly winds per the surface obs match up with the warmer brightness temperatures per the satellite IR. The eastern slopes/downsloping region of the foothills appears warmer, while areas further west in the mountains are colder. Near the I-25 corridor, including the Denver area, localized areas of warming/gusty winds are diagnosed extending from west to east out of the mountain gaps. For example, early in the loop, Denver obs within a warmer plume indicate temperatures in the low 40s with winds gusting near 40 mph. Nearby areas with cooler IR brightness temperatures have surface obs in the low 20s and light winds. A broader area of gusty westerly downsloping winds and resulting warmer temperatures is measured over southern Wyoming advancing southeast into far northern Colorado, while much colder temperatures and lighter winds under the inversion are present over much of the rest of eastern Colorado.
An IR animation with RAP model temperature analysis highlights the broader surface temperature pattern, but fails to capture the smaller scale warmer gap flow regions (Fig 7).
The hourly Land Surface Temperature (LST) derived product form GOES-16 captures the smaller-scale warm features (lighter blue) quite well as they emanate from the foothills (Fig 8).
This more detailed (spatially/temporally) information available from GOES could aid mountain area forecasters in making their short-term forecast updates for wind and temperature during overnight wind events.
Bill Line, NESDIS/CIRA