Imagery from GOES-16 ABI greatly enhances our ability to detect and differentiate cloud types. During the day, visible imagery makes this task fairly simple. At night, however, it is difficult to detect low clouds and differentiate cloud types using the raw IR imagery alone. In this post we investigate the varying cloud types/heights over Colorado/New Mexico and the southern High Plains on 12 August 2017 using GOES-16 image combinations.
The 10.3 – 3.9 um difference from GOES satellites has long been used to detect low clouds and fog at night. The higher spatial and temporal resolution from GOES-16 allows us to now detect and track low cloud and fog evolution with more precision. The first animation below is the 10.3 – 3.9 um fog difference over the region during the pre-dawn hours (Figure 1). The blacks and darkest grays represent a positive difference, or water clouds with small droplets. The negative values, or light grays to white, represent ice/high clouds. The fog difference is great for differentiating low-mid/water clouds from upper/ice clouds, but does not allow one to further discern cloud type/height.
With the increase in spectral bands available with GOES-16 (16 vs 5), we now have the ability to create more advanced image combinations, including RGBs. An RGB is created by combining three channels or channel combinations, each of which contribute to the color red, green, or blue. One such RGB known as the advanced nighttime microphysics RGB, is particularly helpful for further differentiating cloud types/heights at night. The ingredients for this RGB are as follows:
- Red: 12.3 – 10.35 um for cloud thickness. Large contributions come from low positive to negative difference values (thick clouds or clear skies and dry atm). Small contributions will come from high positive difference values (thin clouds or clear skies and very moist atmosphere).
- 10.35 – 3.9 um (green) for ice vs water cloud. Large contributions come from high positive difference values (water clouds). Small contributions come from values near 0 (land) and negative values (ice clouds).
- 10.35 um temperature. Large contributions come from warmer temperatures (low clouds or clear skies). Small contributions come from cold temperatures (high clouds).
The nighttime microphysics RGB below is for the same time period and domain.
Figure 2: 12 August 2017 GOES-16 nighttime microphysics RGB. Full resolution
Lets analyze the imagery at 1142 in Figure 3. First let’s start with the water clouds, those that appeared dark (positive difference). The nighttime microphysics , in this case, draws out three fairly distinct colors from these dark areas. The widespread aqua colors across the eastern plains are low clouds, and the most likely areas of fog in the scene. The area has fairly strong green and blue contributions, telling us these are low water clouds. Surface METAR observations within this region did in fact range from fog to ceilings <500 ft. The patch of clouds in south central Colorado has more of a green tint to them due to higher contributions from red and green (a thicker cloud) and lower contributions from blue (slightly cooler cloud). These are still likely low clouds, but less likely to be fog. METAR’s confirm ceilings around 1300 ft. In central Colorado, the light green to tan colors tell us these are actually mid level clouds (water and possibly ice mixed in), as they have an even lower contribution from blue (even cooler clouds) but still have contributions from red and green. METAR’s indicate ceilings of 10,000 ft with these clouds. The nighttime microphysics RGB allowed for these three areas of water clouds to be differentiated, something the fog difference alone could not do.
Analyzing the same figure, we also see that areas of upper clouds, which appear light gray to white in the fog difference (negative values), can be broken into multiple groups. High thick high clouds appear the most red since they have little to no contribution from both blue (cold) and green (ice), but moderate contribution from red (thick). High thin clouds appear a dark blue to almost black given little to no contribution from red (thin) and green (ice), and little contribution from blue (cold cloud but semi-transparent).
The land surface color will vary, and other features such as fire hotspots and snow cover can be diagnosed in the nighttime microphysics RGB.
Quick guides and other training resources for the GOES-16 RGB’s will be available in the coming months.
Figure 4: 1142 UTC 12 August 2017 GOES-16 Nighttime Microphysics RGB and Fog Difference for same time. Full res
-Bill Line, NWS
“The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.”