The east coast of Australia is on fire!

There’s an ongoing serious situation in Australia: the bush in New South Wales and Queensland is on fire.

Here’s a look at what the Advanced Himawari Imager (AHI) on Himawari-8 saw on 8 November 2019: click here.

What you see in that loop is the “Natural Fire Color RGB” (known to American forecasters as the “Day Land Cloud Fire RGB”) on the left (link to PDF description here), and the “Fire Temperature RGB” on the right (link to PDF description here). These are precisely the products we debuted on this blog seven years ago when we first looked at fires in Australia. Except, now there is a difference: the “Natural Fire Color RGB” is now made with the 3.7 µm band as the red component (replacing the 2.25 µm band I used originally), since the 3.7 µm channel is even better at detecting fires. This also means that we can produce the VIIRS version using “I-band” resolution (375 m). AHI, used in the loop I linked to above, has 2 km resolution* for the mid- and shortwave infrared (IR) bands.

Along the coast, near the northern edge of the images is Brisbane, the third largest city in Australia. Near the southern edge of those images is Sydney, the largest city in Australia. As you can see from Himawari-8, much of the area between the two is on fire. And, this is not the “Outback” where very few people live. This region contains some of the highest population density in Australia, and it’s also prime habitat for koalas, which don’t live anywhere outside of eastern Australia (except in zoos).

It’s no secret that resolution plays in big role in fire detection from satellites. We’ve covered this many times before. But, to hammer the point home (bit of American slang), here’s the resolution difference between VIIRS and AHI in full view from 3:50 UTC on 7 November 2019:

Himawari-8 AHI Day Land Cloud Fire RGB composite of bands 2, 4, and 7 (03:50 UTC, 7 November 2019)

Himawari-8 AHI Day Land Cloud Fire RGB composite of bands 2, 4, and 7 (03:50 UTC, 7 November 2019)

S-NPP VIIRS Day Land Cloud Fire RGB composite of bands I-1, I-2 and I-4 (03:49 UTC, 7 November 2019)

S-NPP VIIRS Day Land Cloud Fire RGB composite of bands I-1, I-2 and I-4 (03:49 UTC, 7 November 2019)

As always, click on each image to bring up the full resolution version. If you just look at the elephant-thumbnail-sized images above without clicking on them, you might get the impression that fires are easier to spot with AHI than with VIIRS. That’s because AHI makes it appear that the entire 2km-wide pixel* is full of fire, when a fire typically only fills a very small percentage of the total area of the pixel. With 375 m resolution**, VIIRS more accurately pinpoints the locations of fire activity. Although, it should be noted that even this is still a larger scale than most fire fronts. To be really accurate, you need something with the resolution of Landsat’s OLI, or a similar radiometer attached to an aircraft – except these high-resolution instruments don’t provide full global coverage multiple times daily like VIIRS, or hemispheric coverage every 10 minutes like AHI. (*On AHI [and ABI and AMI] pixels may be approximated as square-shaped solid angles that are projected onto the curved surface of the Earth from a point roughly 36,000 km above the Equator. 2 km is the width of an IR pixel at the sub-satellite point [on the Equator], where the resolutions are the highest. **VIIRS pixel resolutions vary across the swath by a factor of 2 between nadir and edge of scan, as we shall see. 375 m is the nadir value.)

For completeness, we can do the same comparison with the Fire Temperature RGB:

Himawari-8 AHI Fire Temperature RGB composite of bands 5, 6 and 7 (03:50 UTC, 7 November 2019)

Himawari-8 AHI Fire Temperature RGB composite of bands 5, 6 and 7 (03:50 UTC, 7 November 2019)

S-NPP VIIRS Fire Temperature RGB composite of bands M-10, M-11 and M-12 (03:46 UTC, 7 November 2019)

S-NPP VIIRS Fire Temperature RGB composite of bands M-10, M-11 and M-12 (03:46 UTC, 7 November 2019)

This time, we’re comparing 2 km resolution (AHI) against 750 m resolution (VIIRS), so the differences aren’t as stark. But, this is a good opportunity to remind everyone that the Fire Temperature RGB provides information on fire intensity, while the Natural Fire Color (Day Land Cloud Fire) RGB provides information on fire detections (plus smoke and burn scars), and should be used more as a “fire mask”.

There’s another resolution difference that is easy to see from these fires, and it can be quite significant. I first noticed it when looking at this animation I made of the VIIRS Fire Temperature RGB from 1-11 November 2019:

Animated GIF of VIIRS Fire Temperature RGB images (1-11 November 2019)

Animated GIF of VIIRS Fire Temperature RGB images (1-11 November 2019)

You have to click on the animation to get it to play.

Did you notice the same thing I did? You probably noticed the explosive growth of the fires from 7-9 November, but that’s not what I’m talking about. (Hint: Pay close attention to the nighttime images.) At night, without any sunlight present, you lose information on clouds and the background land surface, and only the fires are visible (unless they are obscured by clouds). That’s where today’s feature of interest resides. I’ll zoom in on some of the fires from 5 November 2019 to make it easier to see:

Animated GIF of VIIRS Fire Temperature RGB images (5 November 2019)

Animated GIF of VIIRS Fire Temperature RGB images (5 November 2019)

The image from 14:01 UTC comes from S-NPP, while the image from 14:52 comes from NOAA-20. Is NOAA-20 better than S-NPP at detecting the fires? Well, the reverse happened two nights later:

Animated GIF of VIIRS Fire Temperature RGB images (7 November 2019)

Animated GIF of VIIRS Fire Temperature RGB images (7 November 2019)

This time, the fires appear hotter (brighter) in the 15:03 UTC image, which came from S-NPP. The 14:12 UTC image came from NOAA-20. Here’s a sequence of three images from 10 November where the NOAA-20 image is sandwiched by two S-NPP images:

Animated GIF of VIIRS Fire Temperature RGB images (10 November 2019)

Animated GIF of VIIRS Fire Temperature RGB images (10 November 2019)

So, why do the fires appear brighter in some images and not others? It’s possible that the fires are becoming more active in the middle image (due to an increase in winds, for example), but it’s more likely that you are seeing the direct result of resolution differences between the various overpasses. “But, I thought both VIIRS instruments had the same resolution,” you might say as though it were a question. And that statement would suggest that you forgot about the “bowtie-effect”. (Not the effect that has anything to do with diamonds, but the effect I wrote a whole chapter about here [PDF].) If you read the **above you would already know that the resolution of VIIRS degrades by a factor of two between nadir and the edge of scan. And, if you didn’t already know, NOAA-20 and S-NPP are positioned in space a half-orbit apart. This means that, in the time it takes between a NOAA-20 overpass and a S-NPP overpass, the Earth has rotated by half the width of the swath (approximately). So, when one VIIRS instrument views something at nadir, it will be close to the edge of scan on the other satellite (and have more coarse resolution as a result).

So, in the last animation, the first image (14:05 UTC) is S-NPP viewing the fires from the east near the edge of scan, the middle image (14:56 UTC) is NOAA-20 viewing the fires near nadir, and the third image is S-NPP viewing the fires from the west – even closer to the edge of scan. (Plus, the terrain is sloping away from S-NPP in the last image as well.)

Those factors contribute to the changing appearance of the fires. They also highlight the value of having two VIIRS instruments in space: if one satellite doesn’t get a good look at a fire, the other one likely will.

By the way, these fires have been producing a lot of smoke. Here is a loop of VIIRS True Color images from 6-11 November:

 

And the view from the ground is even more apocalyptic:

Polar Opposites

As we all know, the furthest south you can travel is to the South Pole – the Geographic South Pole, not the Magnetic South Pole or the Geomagnetic South Pole. When you get there, try to face east if you can. (This is easier to do at the “Ceremonial South Pole” than it is at the actual South Pole.)

The furthest south you can get by boat is an island off the coast* of Antarctica, called Ross Island. (*The term “coast” is used loosely here, since Ross Island is usually connected to Antarctica by the Ross Ice Shelf.) At the southern tip of Ross Island is the largest “city” in Antarctica: McMurdo Station. McMurdo is the port-of-entry for most visitors to Antarctica. It is also home to a ground station that receives data from NOAA-20 (and many other satellites). So, if you love the lower latency that comes with NOAA-20 VIIRS data, you have McMurdo Station to thank. (S-NPP data is only downlinked at Svalbard – once per orbit – while NOAA-20 is downlinked at both Svalbard and McMurdo.) This is the location of today’s resolved mystery.

The mystery began with the development of a new website for viewing global VIIRS imagery: Polar SLIDER*. (*Shameless self-promotion: I helped develop that website.) If you click on that link, choose “Southern Hemisphere” from the Sector menu to view Antarctica. With every product, you can zoom in anywhere on the globe* to view the full resolution data. (*Claim is void near the Equator.) Under the Product menu, you can choose between all 22 VIIRS channels (16 M-bands, 5 I-bands, and the Day/Night Band), or from a list of imagery products and cloud products. (And we are always working to add new products.) Since it’s perpetual night down there right now, you’ll notice that the visible and near-IR bands don’t give you much information – except the Day/Night Band, of course, which can provide images like this:

NOAA-20 VIIRS DNB image (14:25 UTC, 14 August 2019)

NOAA-20 VIIRS DNB image (14:25 UTC, 14 August 2019)

Ross Island is in the center of that image. That bright light at the southern tip of Ross Island is McMurdo Station. The second bright light south of that is the “airport“. Here’s an annotated image with the map plotted on it:

NOAA-20 VIIRS DNB image of Ross Island and surroundings (14:25 UTC, 14 August 2019)

NOAA-20 VIIRS DNB image of Ross Island and surroundings (14:25 UTC, 14 August 2019)

As always, click on an image to see it in full resolution. Now that we have our bearings, let’s look at the high resolution mid-wave IR band (I-4/3.74 µm):

NOAA-20 VIIRS channel I-4 (14:25 UTC, 14 August 2019)

NOAA-20 VIIRS channel I-4 (14:25 UTC, 14 August 2019)

See that white dot in the middle of Ross Island? What is that? (Hint: it’s not part of the map.)

To make some sense of this, look at the color table plotted on the bottom of the image. White pixels on this scale (not counting the map) are +100°C (+373 K). In contrast, the dark turquoise color surrounding it is in the -25°C to -30°C range (243-248 K). What could be over 100°C in Antarctica in the winter? Did something catch on fire?

It turns out, it is a semi-permanent feature according to this animation collected from Polar SLIDER. (You have to click on the animation to see it play.)

Animation of VIIRS channel I-4 images (13 August 2019)

Animation of VIIRS channel I-4 images (13 August 2019)

Looking at Day/Night Band images over the same time period, it also shows up as a bright spot:

Animation of VIIRS DNB images (13 August 2019)

Animation of VIIRS DNB images (13 August 2019)

Maybe it’s a nuclear reactor that powers all of McMurdo Station? (Nope. There was a nuclear power plant, but that was de-commissioned in 1972.) Maybe the fact that this bright (in the DNB), hot spot (mid-IR) is on top of a mountain has something to do with it? (Bingo!)

Ross Island is made up of volcanoes, the most prominent of which are Mt. Erebus and Mt. Terror (named for the ships on the original expedition that discovered them). Mt. Terror (the one on the right) is inactive. Mt. Erebus, on the other (left) hand, is the southernmost active volcano in the world. And, what’s relevant here is the fact that it is home to one of only five known lava lakes in the world. So, molten-hot liquid rock exists in an ice-covered environment where temperatures regularly dip down to -50°C or -60°C. And, it’s right next to the largest settlement in Antarctica. Sleep tight. (Since we’re less than a week away from the first sunrise of the spring, get your sleep while you can down there!)

Tropical Cyclone Idai: Before, During and After

As of the time of this writing, there is currently a humanitarian crisis in Mozambique caused by what was Tropical Cyclone Idai. Here’s the situation as of 25 March 2019.

Wikipedia actually has a pretty detailed history of Idai. Long story short, one of the worst (“worst” meaning large negative impact on humans) tropical cyclones in recorded history for the Southern Hemisphere formed just off the coast of Mozambique on 4 March 2019. It quickly headed inland as a tropical storm, where it dropped heavy rains on northern Mozambique and Malawi. Then, it turned back into the Mozambique Channel, headed for Madagascar, stopped, turned around, rapidly intensified, and then hit Mozambique a second time as a Category 2 cyclone. After making it on land a second time, it stalled out and dissipated, dropping more heavy rain in the process on central Mozambique and eastern Zimbabwe. Here is a long loop from Meteosat-8 showing much of the life cycle of Cyclone Idai as it appeared in the longwave infrared (IR).

Here’s a visible (True Color) loop from VIIRS that covers most of the month of March:

Animation of VIIRS True Color images from both S-NPP and NOAA-20 (1-25 March 2019)

Animation of VIIRS True Color images from both S-NPP and NOAA-20 (1-25 March 2019)

This loop has been reduced in resolution to half of its original size to save on file size. Even with only 2-3 images per day (since we combined both S-NPP and NOAA-20 images), you can still clearly see the cyclone over Mozambique early in the loop head out to sea and then turn around and hit Mozambique again, where it dumped heavy rain for several days.

But, I want to draw your attention to several of the images in that loop: the beginning, the middle, and the end. On 1 March 2019, NOAA-20 got a pretty clear view of central Mozambique:

NOAA-20 VIIRS True Color composite image (11:32 UTC, 1 March 2019)

NOAA-20 VIIRS True Color composite image (11:32 UTC, 1 March 2019)

We’ll call this the “Before” image – and this one is full resolution (750 m). (NOTE: You have to click on it show it at full resolution.) We can also look at the Natural Color RGB (also known as the Day Land Cloud RGB and about a dozen other names), which we can make with the high resolution imagery bands I-1, I-2 and I-3:

NOAA-20 VIIRS Natural Color RGB composite image (11:32 UTC, 1 March 2019)

NOAA-20 VIIRS Natural Color RGB composite image (11:32 UTC, 1 March 2019)

This is also at full resolution (375 m). (Again, only if you click on it.)

The worst of the flooding occurred with Idai’s second landfall on 14 March 2019, and both VIIRS got great views of Idai prior to landfall:

NOAA-20 Natural Color RGB composite image (10:47 UTC, 14 March 2019)

NOAA-20 Natural Color RGB composite image (10:47 UTC, 14 March 2019)

S-NPP Natural Color RGB composite image (11:38 UTC, 14 March 2019)

S-NPP Natural Color RGB composite image (11:38 UTC, 14 March 2019)

These images were taken ~50 min. apart. And, if you couldn’t already tell, they’re the high resolution Natural Color images. This is for two reasons: 1) who doesn’t want to see tropical cyclones at the highest resolution possible? and 2) the Natural Color RGB brings out details in the cloud structure you can’t see in True Color. As we’ve discussed before, Natural Color highlights ice clouds in a cyan color, while liquid clouds are nearly white. But, if you look closely in the above images, you will see lighter and darker cyan regions in the clouds above (or at the top of) the eyewall. This is due to differences in particle size. Larger ice particles appear more cyan, while smaller ice particles appear more white. (Of course, there is also some shadowing going on, which accounts for the darkest regions.)

Another thing to note is the first image comes from NOAA-20, which was to the east of Idai. This provides a great view of the sloped structure of the west side of the eyewall. (And, not much information on the east side of the eyewall.) The second image comes from Suomi-NPP, which was to the west of Idai, looking at the east side of the eyewall. The two satellites in tandem provide an almost 3D view of the clouds in the eyewall (separated by 50 minutes, of course).

Also, see that peninsula that is just to the west of the eyewall in the last two images? (Hint: you won’t see it unless you bring up the full resolution versions.) That’s where the city of Beira is (or was). Beira was home to half a million people, and was one of the major ports in Mozambique. It took a direct hit from the eyewall of Idai, which destroyed approximately 90% of the buildings there. Beira was also ground zero for the resulting flooding, and the pictures coming out are not pretty.

This is a good segue to talk about the images from the end of the loop. NOAA-20 captured a relatively cloud-free view of Mozambique on 25 March 2019:

NOAA-20 VIIRS True Color composite image (10:42 UTC, 25 March 2019)

NOAA-20 VIIRS True Color composite image (10:42 UTC, 25 March 2019)

NOAA-20 VIIRS Natural Color RGB composite image (10:47 UTC, 25 March 2019)

NOAA-20 VIIRS Natural Color RGB composite image (10:47 UTC, 25 March 2019)

These images were collected 10 days after landfall, and the flooding is still evident. Don’t believe me? Compare these “After” images with the “Before” images shown earlier (zoomed in on Beira):

Animation comparing NOAA-20 True Color RGB composite images from 1 March 2019 and 25 March 2019

Animation comparing NOAA-20 True Color RGB composite images from 1 March 2019 and 25 March 2019

Notice the fertile, green agricultural land surrounding Beira in the “before” image that is covered by brown floodwater in the “after” image. Just like what we saw in the pictures from Beira.

But, there’s a lot flooding that is not so easy to see in the True Color that shows up better in the Natural Color RGB:

Animation comparing NOAA-20 Natural Color RGB images from 1 March 2019 and 25 March 2019

Animation comparing NOAA-20 Natural Color RGB images from 1 March 2019 and 25 March 2019

Since this VIIRS Natural Color imagery has twice the resolution of True Color, this animation is too large for WordPress to play it automatically. You have to click on it to see the animation play.

We’ve talked before about differences between True Color and Natural Color when it comes to flooding, and this example shows it quite well. You see, True Color can miss flooding, because water is pretty transparent at visible wavelengths. If the water is clear, you can see through it and, from the perspective of VIIRS, you see the ground underneath the water (as long as the water is relatively shallow). If the water is muddy, like most of this flooding, it’s easier to see (since radiation reflects off the particles in the water), but it can look the same as the mud (or bare ground) that isn’t covered by water.

Natural Color uses longer wavelengths, where water is much more absorbing, so water appears nearly black. That’s why it is typically easier to see flooding against a background of non-flooded land in Natural Color than True Color. But, the flooding around Beira is so muddy, the high reflectivity in the visible channel (which is the blue component of the RGB) starts to win out, and the floodwater appears more blue than black.

We can prove it by looking at the individual bands that make up these RGB composites. Remember to click to play the animations for the I-bands:

Comparison of NOAA-20 channel I-1 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel I-1 (0.64 µm) images from 1 March and 25 March 2019

Comparison of NOAA-20 channel I-2 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel I-2 (0.87 µm) images from 1 March and 25 March 2019

Comparison of NOAA-20 channel I-3 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel I-3 (1.61 µm) images from 1 March and 25 March 2019

Note that the flooded areas look brighter in I-1 (thanks to the dirty water) and look darker in I-2 and I-3 (because they are less sensitive to the dirt in the water and more sensitive to the water itself).

The individual M-bands that comprise the True Color RGB, shown below, have been corrected for Rayleigh scattering and scaled the same as in the True Color images above:

Comparison of NOAA-20 channel M-3 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel M-3 (0.48 µm) images from 1 March and 25 March 2019

Comparison of NOAA-20 channel M-4 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel M-4 (0.55 µm) images from 1 March and 25 March 2019

Comparison of NOAA-20 channel M-5 images from 1 March and 25 March 2019

Comparison of NOAA-20 VIIRS channel M-5 (0.67 µm) images from 1 March and 25 March 2019

It is quite difficult to detect the flooding using the visible channels (M-3, M-4, M-5 and I-1) alone. But, the flooded areas are generally brighter in the “after” images. However, the water is easy to see in the shortwave IR channels (I-2, and I-3 along with M-7 and M-10, which were not shown).

Of course, this was a very long-winded way of looking at the flooding. We could have just used the JPSS Program’s official Flood Product made with VIIRS, created by researchers at George Mason University. Here is a three day composite image (composited to reduce the impact of clouds), covering 19-22 March 2019:

NOAA-20 VIIRS Flood Detection Product using a 3-day cloud-free composite (19-22 March 2019)

NOAA-20 VIIRS Flood Detection Product using a 3-day cloud-free composite (19-22 March 2019). Image courtesy S. Li (GMU).

Red and yellow areas show where flooding is detected. Gray areas are areas that were cloudy all three days. As an interesting side note, this product is validated against the Natural Color RGB. For more on this product, click here. If you want to know how much precipitation actually fell, here is a loop provided by NASA made with observations from GPM (Global Precipitation Measurement Mission):

You get bonus points if you can read the scale below the images. But, even without a magnifying glass, you can probably guess: it’s a lot of rain!

Ice, Ice, Baby

A winter storm moved through the Northeast U.S. over the weekend of 19-20 January 2019. This Nor’easter was a tricky one to forecast. Temperatures near the coast were expected to be near (or above) freezing. Temperatures inland were expected to be much colder. Liquid-equivalent precipitation, at least according to the GFS, was predicted to be in the 1-3 inch (25-75 mm) range the day before. This could easily convert to 1-2 feet (30-60 cm) of snow. The question on everyone’s mind: who gets the rain, who gets the snow, and who gets the “wintry mix”? The fates of ~40 million people hang in the balance. This is one of the situations that meteorologists live for!

The difference between 71°F and 74°F is virtually meaningless. The difference between 31°F and 34°F (with heavy precipitation, at least) is the difference between closing schools or staying open. It’s the difference between bringing out the plows or keeping them in the garage; paying overtime for power crews to keep the electricity flowing or just another work day; shutting down public transportation or life as usual.

Of course, the obvious follow-up question is: what is the “wintry mix” going to be? Rain mixed with snow? Sleet? Freezing rain? It doesn’t take much to change from one to the other, but there can be a big difference on the resulting impacts based on what ultimately falls from the sky.

So, what happened? Here’s an article that does a good job of explaining it. And, here are PDF files of the storm reports from National Weather Service Forecast Offices in Albany, Boston (actually in Norton, MA) and New York City (actually in Upton, NY). The synopsis: some places received ~1.5 inches (~38 mm) of rain, some places received ~11 inches (~30 cm) of snow and some places were coated in up to 0.6 inches (15 mm) of ice.

Of particular relevance here are the locations that received the ice. If you took the locations listed in the storm reports that had more than 0.1 inches (2.5 mm) of ice (at least the ones in Connecticut) and plotted them on a map, they match up quite well with this map of power outages that came from the article I linked to:

Map of power outages in Connecticut as a result of an ice storm (19-20 January 2019)

Map of power outages in Connecticut as a result of an ice storm (19-20 January 2019). Image courtesy Eversource/NBC Connecticut.

Now, compare that map with this VIIRS image from 22 January 2019 (after the clouds cleared out):

VIIRS channel I-3 image from NOAA-20, 17:09 UTC 22 January 2019

VIIRS channel I-3 image from NOAA-20, 17:09 UTC 22 January 2019

As always, you can click on the image to bring up the full resolution version. This is the high-resolution imagery band, I-3, centered at 1.6 µm from NOAA-20. Notice that very dark band stretching from northern New Jersey into northern Rhode Island? That’s where the greatest accumulation of ice was. Notice how well it matches up with the known power outages across Connecticut!

The ice-covered region appears dark at 1.6 µm because ice is very absorbing at this wavelength and, hence, it’s not very reflective. And, since it is cold, it doesn’t emit radiation at this wavelength either (at least, not in any significant amount). This is especially true for pure ice, as was observed here (particularly the second image), since there aren’t any impurities in the ice to reflect radiation back to the satellite. The absorbing nature of snow and ice compared with the reflective nature of liquid clouds is what earned this channel the nickname “Snow/Ice Band” (PDF).

At shorter wavelengths (less than ~ 1 µm), ice and snow are reflective. (Note how a coating of ice makes everything sparkle in the sunlight.) This makes it nearly impossible to tell where the ice accumulation was in True Color images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 from NOAA-20, 17:09 UTC 22 January 2019

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 from NOAA-20, 17:09 UTC 22 January 2019

The Natural Color RGB (which the National Weather Service forecasters know as the Day Land Cloud RGB (PDF file)) includes the 1.6 µm band, which is what makes it useful for discriminating clouds from snow and ice. And, as expected, the region of ice accumulation does show up (although it is tempered by the highly reflective nature of snow and ice in the visible and “veggie” bands that make up the other components of the RGB):

VIIRS Natural Color RGB composite of channels, I-1, I-2 and I-3 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS Natural Color RGB composite of channels, I-1, I-2 and I-3 from NOAA-20 (17:09 UTC, 22 January 2019)

Another RGB composite popular with forecasters is the Day Snow/Fog RGB (PDF file), where blue is related to the brightness temperature difference between 10.7 µm and 3.9 µm, green is the 1.6 µm reflectance, and red is the reflectance at 0.86 µm (the “veggie” band). This shows the region of ice even more clearly than the Natural Color RGB:

VIIRS Day Snow/Fog RGB composite of channels (I-5 - I-4), I-3 and I-2 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS Day Snow/Fog RGB composite of channels (I-5 minus I-4), I-3 and I-2 from NOAA-20 (17:09 UTC, 22 January 2019)

Breaking things up into the individual components, we can see how the ice transitions from being reflective in the visible and near-infrared (near-IR) to absorbing in the shortwave-IR:

VIIRS high-resolution visible channel, I-1, from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution visible channel, I-1 (0.64 µm), from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution "veggie" channel, I-2, from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution “veggie” channel, I-2 (0.86 µm), from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-8 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-8 (1.24 µm) from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-11  from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-11 (2.25 µm) from NOAA-20 (17:09 UTC, 22 January 2019)

Of course, the 1.6 µm image was already shown, so I didn’t bother to repeat it. If you squint, you can even see a hint of the ice signature at 1.38 µm, the “Cirrus Band“, where most of the surface signal is blocked by water vapor absorption in the atmosphere:

VIIRS "cirrus" channel, M-9, from NOAA-20 (17:09 UTC 22 January 2019)

VIIRS “cirrus” channel, M-9 (1.38 µm), from NOAA-20 (17:09 UTC 22 January 2019)

If the ice had accumulated in southern New Jersey or Pennsylvania, though, it would not have shown up in this channel, since the air was too moist at this time to see all the way down to the surface. But, you can compare this image with the previous images to see why they call it the “cirrus band”, since the cirrus does show up much more clearly here.

So, mark this down as another use for VIIRS: detecting areas impacted by ice storms. And remember, even though ice storms may have a certain beauty, they are also dangerous. And, not just for the obvious reasons. This storm in particular came complete with ice missiles. So, for the love of everyone else on the road, scrape your car clean of ice before risking your life out there!