The Mystery Channel

I wrote the first post on this blog more than 5.5 years ago. Since then, I have covered a multitude of instances where VIIRS imagery has helped us learn about the world we live on. But, during that time there has been one channel on VIIRS that has never been mentioned. Not once. And, what may be even more surprising is that this channel is not featured on any of the next generation geostationary satellites. It’s not on the GOES-R Program’s ABI, not on Himawari’s AHI, not on the upcoming Meteosat Third Generation FCI. Those with photographic memories will know exactly which channel I’m talking about. The rest of you will just have to guess, or go back through the archives and use the process of elimination to figure it out.

So, is this channel useless? Why is it on VIIRS, but not ABI? Which one is it? The suspense is killing me! I can’t answer that second question, but I can definitely answer the third and give some insights to #1. (The short answer to #1 is “No” – otherwise we wouldn’t be here.) But, to do this, we have to remember why Lake Mille Lacs disappeared earlier this year. It might also be good to remember our earlier posts on Greenland, because that is the location of our most recent mystery.

We begin with the view of Greenland from GOES-16 back at the end of July 2017:

This video covers the period of time from 0700 UTC 27 July to 2345 UTC 28 July. If you follow this blog, you already know that this the “Natural Color” RGB composite, which in GOES-16 ABI terms is made of bands 2 (0.64 µm), 3 (0.86 µm) and 5 (1.61 µm). Notice the whitish coloration over the central portion of Greenland. This is the feature of interest.

We know from experience (and earlier blog posts) that snow and ice are not very reflective at 1.6 µm, which is why it takes on that cyan appearance in Natural Color imagery. Whitish colors are indicative of liquid clouds. But, the feature of interest doesn’t appear to move over this two day period. (If you look closely, it does appear to shrink a little, though.) It’s hard to believe a cloud could be that stationary over a two day period.

Let’s isolate the 1.6 µm band by itself to see if we can tell what’s going on:

Shortly after the first sunrise, you can see a patch of liquid clouds over the ice that quickly dissipate, leaving our feature of interest exposed. Clouds appear again near the first sunset, and late in the second day (28 July). The feature of interest isn’t as bright as those clouds, but is brighter than the rest of the ice and snow on Greenland.

At shorter wavelengths, nearly all of Greenland is bright, so our feature of interest isn’t as noticeable. Here’s the 0.86 µm band from ABI:


 
But, it shows up at the two longer shortwave IR bands. Here’s the 2.25 µm band:


 
The same is true for 3.9 µm, but I won’t waste time showing it.

So, what is going on? What is our feature of interest?

Well, the problem is, Greenland is way off on the limb from the perspective of GOES-16’s current location. Perhaps we need a better view from something that passes directly overhead of Greenland. Hmmm. What could that be?

This is a VIIRS blog after all, so I think you know the answer to my rhetorical question. Let’s start with our good old friend, Natural Color, which we should all be familiar with:

S-NPP VIIRS Natural Color RGB composite of bands M-5, M-7 and M-10 (14:40 UTC 27 July 2017)

S-NPP VIIRS Natural Color RGB composite of bands M-5, M-7 and M-10 (14:40 UTC 27 July 2017)

You can tell by the shadows cast where the clouds are, even if they are a similar color to the background of snow and ice on Greenland. But, the feature of interest isn’t very obvious. There appears to be an area of lighter cyan over the central portions of the ice sheet, but it definitely doesn’t look like a cloud. Let’s break it up into single channels, like we did with ABI, starting with M-7 (0.86 µm):

S-NPP VIIRS channel M-7 (14:40 UTC 27 July 2017)

S-NPP VIIRS channel M-7 (14:40 UTC 27 July 2017)

Again, it’s all bright. How about M-10 (1.61 µm)?

S-NPP VIIRS channel M-10 (14:40 UTC 27 July 2017)

S-NPP VIIRS channel M-10 (14:40 UTC 27 July 2017)

Now, Greenland appears all dark. For completeness, let’s look at M-11 (2.25 µm):

S-NPP VIIRS channel M-11 (14:40 UTC 27 July 2017)

S-NPP VIIRS channel M-11 (14:40 UTC 27 July 2017)

It’s subtle, but you can see a hint of brightening over the south-central portion of the ice sheet. (In case you’re wondering why it looks so much darker in VIIRS than ABI, it’s because our visible and near-IR GOES-16 imagery uses “square root scaling” by default. In image processing terms, it’s the same as a gamma correction of 2. The VIIRS images don’t have that.) Now, for the ace up my sleeve – the one channel that has never appeared before on this blog:

S-NPP VIIRS channel M-8 (14:40 UTC 27 July 2017)

S-NPP VIIRS channel M-8 (14:40 UTC 27 July 2017)

This is M-8, centered at 1.24 µm. Its primary use is listed in the JPSS Program literature as “cloud particle size.” Based on reading the documentation for the cloud products, it appears M-8 is used operationally only as a backup for M-5 (0.67 µm) in the cloud optical thickness and effective particle size retrievals under certain conditions, or when M-5 fails to converge on solution. One of those conditions is the retrieval of cloud properties over snow and ice. As we shall see, however, M-8 is very good at determining the properties of the snow and ice itself.

M-8 shows quite clearly the bright central portion of Greenland (our feature of interest) surrounded by dark at the edges of the ice sheet (even without any gamma correction). Snow-free areas appear brighter than the edge of the ice sheet because, much like M-7/0.86 µm, vegetation is also highly reflective at 1.24 µm.

This example shows what we’ve long known. Snow and ice are highly reflective in the visible (and very near IR) portions of the electromagnetic spectrum. In the short- and mid-wave IR, snow and ice are absorbing and cold. This means they don’t emit or reflect much radiation at these wavelengths. That’s why they appear dark at 1.61 and 2.25 µm. M-8 straddles the boundary of these regions as exemplified by this graph:

Reflectance spectra of snow

Reflectance spectra of snow. The highlighted portion shows the bandwidth of VIIRS channel M-8.

The information in this graph comes from the ASTER Spectral Library created by NASA. Note that the reflectance of snow in M-8 is highly variable and a function of the snow grain size. This may explain why the central portion of Greenland’s ice sheet appears so bright, while the edges are so dark in M-8. Another explanation is that, much like in Minnesota, snow melt causes a drop in reflectance. Slush just isn’t as reflective as fresh snow, and M-8 is highly sensitive to this.

The last week in July was a very warm one for Greenland. The capitol, Nuuk, recorded highs in the 60s (°F), or upper-teens (°C), peaking at 71°F (22°C) on 29 July 2017. Normal for that time of year is 52°F (11°C).

Since Greenland is pretty far north, we can take advantage of the multiple VIIRS overpasses per day and really capture this snowmelt:

Animation of daytime VIIRS M-8 images (27-29 July 2017)

Animation of daytime VIIRS M-8 images (27-29 July 2017)

This animation, which you may have to click on to get it to play, covers the three day period 27-29 July 2017. Here’s it is obvious what impact the heat wave is having on Greenland’s ice and snow. Our “feature of interest” really shrinks over this period of time.

In early August, the snow and ice start to recover and become more reflective again. Here’s an extended animation that includes the relatively clear days of 17 July, 20 July and the entire period from 30 July to 3 August 2017:

Animation of VIIRS M-8 (17 July - 3 August 2017)*

Animation of VIIRS M-8 (17 July – 3 August 2017)*

Our “feature of interest” is unmelted snow/ice on Greenland’s ice sheet.

Now, this is the VIIRS Imagery Team Blog. We can do a better job of highlighting this snowmelt by combining it with other channels in an RGB composite. One way is to replace M-7 with M-8 in the Natural Color RGB:

Animation of VIIRS Natural Color imagery composites of channels, M-5, M-8 and M-10 (17 July - 3 August 2017)*

Animation of VIIRS Natural Color imagery composites of channels, M-5, M-8 and M-10 (17 July – 3 August 2017)*

Fresh, fine snow has the cyan color we’re all familiar with, but now coarse snow and melting snow are a deeper, more vivid blue color.

Another option takes a page out of the EUMETSAT Snow playbook. Here’s one with M-8 as the blue component, M-7 as the green component and M-5 as the red component:

Animation of VIIRS RGB composite using channels, M-8, M-7 and M-5 (17 July - 3 August 2017)*

Animation of VIIRS RGB composite using channels, M-8, M-7 and M-5 (17 July – 3 August 2017)*

Now the fresh, fine snow is pale yellow, while the coarse snow and snowmelt are a darker yellow-orange. The question is: which one do you like better?

So, I have now talked about every band on VIIRS. And, I learned that the last time I looked at melting on Greenland, I should have been looking at M-8 from the very beginning.

There’s Something in the Water

In the fast paced world of weather, Hurricane Irma is old news. There’s already a Wikipedia page on it. But, people that were in Irma’s path are still cleaning up (at least at the time I’m writing this). In case you’ve already forgotten, or were living in a Faraday cage underground, here’s a quick recap. Among the factoids: Irma was the strongest hurricane ever recorded in the Atlantic basin and it was a Category 5 (the highest the scale goes) for the longest period of time of any Atlantic hurricane. The island of Barbuda took a direct hit from Irma and is now desolate and decimated. Jacksonville, which did not take a direct hit, received record flooding due to winds blowing the St. Johns River inland, while heavy rains inland were trying to flow out to sea. And, the hearing impaired mocked Manatee County, Florida for using a sign language interpreter that didn’t know sign language. Just in the U.S. alone, 26 people died.

Satellite imagers with higher resolution than VIIRS captured the damage. First, Landsat (~30 m spatial resolution) showed how vegetation was stripped from the soil in Antigua, Barbuda and the Virgin Islands. And, Worldview-4 (~30 cm resolution!) captured images of damaged structures in the Florida Keys and other islands in the Caribbean for Digital Globe (not a paid advertisement or endorsement). Our newest satellite, GOES-16, monitored Irma all the way from birth to death. (Shout out to my collegues at CIRA who provided the imagery used in that article!) And, of course, the VIIRS Day/Night Band showed the extent of power outages in Florida, which I won’t talk about further because I’ve already been beaten to it.

But, VIIRS works during the day, too. And it captured an aspect of Irma’s impact not mentioned above. We’ll start by taking a look at a VIIRS True Color image from 31 August 2017:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (1840 UTC 31 August 2017)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (1840 UTC 31 August 2017)

Remember, you can click on an image to bring up the full resolution version. Let’s compare this “before” image with one taken after Irma hit:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (1813 UTC 12 September 2017)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (1813 UTC 12 September 2017)

Notice anything different between the two images?

Apart from all the clouds (which are always different between two images), it shouldn’t take long to notice a change in the water surrounding Florida and, to a lesser extent, the Bahamas. You see, hurricanes bring with them heavy rains, high winds and waves and storm surge. The winds and waves churn up sediment at the bottom of the ocean – like this guy, only more, at least in shallow areas like the Florida Keys and the Bahamas. The storm surge causes beach erosion and flooding along the coasts while the heavy rains cause inland flooding (of both the “flash” and “river” variety). And, when was the last time you saw crystal clear floodwater? Floodwater is filled with dirt from the soils it eroded. Plus, there’s often garbage, raw sewage and toxic chemicals that may make it as hazardous as the hurricane itself. And, let’s not mention floating fire ant colonies because no one want to think about those – except I just did.

If you look closely, you may even see this sediment and pollution beginning to be entrained in currents in the Gulf of Mexico as well as on the Atlantic side of Florida. And, remember that the Atlantic side of Florida is home to the Gulf Stream (the current, not the aircraft).

Of course, we don’t have to just compare two days. We can monitor this sediment and pollution for as long as it’s there. Here’s a video showing both the before image (31 August 2017) and 6 days after (12-17 September 2017):


 
You can view it in full screen by clicking on the icon in the lower right corner of the video. After watching it several times, you should see two things: sediment around the Florida Keys does get pulled into the Gulf Stream, with visible eddies where the polluted water meets the clean water; and the polluted water generally gets darker with time. The latter is due to the fact that more of the dirt and sand and garbage settle out with time, slowly restoring the ocean to its pre-Irma appearance.

You might also notice the ocean around the Bahamas is always lighter in color. This is true even in the “before” image. This is because the water is very shallow in the Bahama Banks, and you can see all the way to the bottom. But, offshore on the west side of the largest island (Andros) the water becomes nearly white after Irma’s passage:

Comparison of VIIRS True Color images before and after Hurricane Irma (2017)

Comparison of VIIRS True Color images before and after Hurricane Irma (2017)

Go back to the video and see that it barely darkens over time. It is possible that, just like flood-induced erosion changes the landscape on the ground, the storm-induced waves and surge may have altered the underwater topography (“bathymetry”) of the Grand Bahama Bank and made the water even shallower. We’ll just have to wait and see how dark it gets.

Postscript: our VIIRS-like geostationary imager, the Advanced Baseline Imager (ABI) on GOES-16 also saw this sediment in the waters off the coast of Florida: click here. Remember, ABI doesn’t have a green wavelength visible band, but that’s no problem for CIRA’s Synthetic True Color imagery! [/end shameless plug]

Steve and the Color Purple

It’s not often that a new discovery takes place that baffles the minds of lifelong scientists. This is a story about one that seems to have gone viral over the last few days. The abbreviated version (summarized from this article, this article, and this article, and many others like it) is as follows:

A group of dedicated aurora photographers noted a particular type of aurora that was different from what we normally think of. Instead of a rapidly changing curtain of light glowing green or red, it is a single arc of light, “purple” in color, with less apparent motion than a normal aurora. It doesn’t appear to move with the Earth’s magnetic field. The picture that accompanies every article about it is this one:

Photograph credited to Dave Markel Photography

Photograph credited to Dave Markel Photography

The early guess was that it’s an example of a “proton arc” – a type of aurora caused by high energy protons rather than electrons. (Do a Google Image Search for “proton arc” and you’ll see many other examples.) However, the plot thickened when an expert on the aurora, Prof. Eric Donovan at the University of Calgary, debunked that guess based on the fact that proton arcs are not visible to the human eye. This was backed up by a graduate student at the University of Alaska-Fairbanks. Not knowing what else to call it, the dedicated aurora photographers named it Steve. No joke. (It comes from the animated movie, Over the Hedge.) The name has caught on, and now the internet is full of photographic examples of “Steve”. Here’s a time lapse video.

The Aurorasaurus Project has compiled a list of things we know about Steve. Our expert aurora professor matched up a known time and location of a Steve photograph with an overpass of the European Space Agency’s Swarm satellites and found this out:

“As the satellite flew straight though Steve, data from the electric field instrument showed very clear changes. The temperature 300 kilometres (185 miles) above Earth’s surface jumped by 3,000°C (5,400 degrees Fahrenheit) and the data revealed a 25 kilometre (15.5 mile) wide ribbon of gas flowing westwards at about 6 km/s (3.7 miles per second) compared to a speed of about 10 m/s (32.8 feet per second) either side of the ribbon.”

So, while we don’t exactly know what causes “Steve”, we do know that it is relatively common. (Do that Google Image Search for “proton arc” again for proof.) And we know it’s not a proton arc. Of course, the question that is relevant to us on this blog is: Can the VIIRS Day/Night Band see Steve?

There was a significant geomagnetic storm 22-23 April 2017 that may provide the answer. One of the Alberta Aurora Chasers (our dedicated group of aurora photographers) took this picture and, in the comments, noted the location (Lake Minnewanka, Alberta) and approximate time (“maybe 12:30” AM on the 22nd). Compare that with the nearest Day/Night Band image:

VIIRS Day/Night Band image (08:12 UTC 22 April 2017)

VIIRS Day/Night Band image (08:12 UTC 22 April 2017)

I put a gold star on there to indicate the location of Lake Minnewanka. Don’t see it? Here’s a close-up:

VIIRS Day/Night Band image above zoomed-in on Lake Minnewanka.

VIIRS Day/Night Band image above zoomed-in on Lake Minnewanka. The gold star indicates the location of the lake.

Unfortunately, Lake Minnewanka is outside the VIIRS swath. But, Aurorasaurus says Steve is often hundreds or thousands of miles long, and oriented east-west, so it should extend into the VIIRS swath. Now, this VIIRS image was taken at about 2:15 AM local time, almost two hours after the photograph was taken. Aurorasaurus also says Steve is visible on the order of minutes, “up to 20 minutes or more”. So, maybe Steve disappeared in the time between the two images. I certainly don’t see any straight or smooth arc of light near the star that resembles Steve. Although, just north of Calgary (the closest city within the VIIRS swath to Lake Minnewanka) there is faint evidence of aurora light, and it is on the equator-ward side of the aurora, which is consistent with previous observations.

The streaks of light visible near Calgary (and general streakiness across the whole aurora) are due to the way the VIIRS instrument scans the scene and the high-temporal variability of the aurora, which we’ve discussed before. But, as I mentioned, these streaks don’t extend for hundreds or thousands of miles.

Maybe, VIIRS had better luck on the next overpass (~3:55 AM local time):

VIIRS Day/Night Band image (09:53 UTC 22 April 2017)

VIIRS Day/Night Band image (09:53 UTC 22 April 2017)

Again, nothing jumps out to say, “Aha! That’s Steve!” So, was Steve there and VIIRS failed to see it? Or, was Steve not there at the time of the VIIRS overpass? The answer to that depends in part on the definition of “purple”.

Is Steve really “purple” as people describe? Or, is it violet? Wikipedia actually has a good section on this (at least, until someone edits it). There’s also the page discussing the “Line of Purples“. The problem stems from the fact that violet is a color similar to purple, but is physically very different. Violet is the name given to a specific wavelength range of light, specifically the visible portion of the spectrum less than 450 nm. Purple is a combination of blue and red wavelengths – blue being wavelengths between ~450 nm and ~495 nm and red being anything visible above ~620 nm. Violet and purple look similar to us because the cone cells in our eyes have a similar response to both colors. However, in the RGB color space of the computer you’re viewing this on, and in the color cameras used to take pictures of Steve, violet is impossible to duplicate. This is because violet is not a combination of red, green and blue – it’s its own wavelength. The red, green and blue light emitting diodes (or phosphors on a plasma screen) don’t emit violet wavelengths. Your camera stores the information it collects in RGB color space, too, and has to approximate violet the same way your computer does – by making it a bluer shade of purple. Depending on the camera, the detectors used may not even be sensitive to violet light.

So, what does this mean for VIIRS? The Day/Night Band is not sensitive to radiation at wavelengths shorter than ~500 nm, which includes blue and violet. But, it is sensitive to red and beyond – up to ~900 nm. So, if Steve really is purple, the Day/Night Band will only be sensitive to the red component of it. (It would be more faint, but VIIRS would likely be sensitive to it, given that it is sensitive to airglow, which is much more faint than the aurora.) If Steve is really violet, than the Day/Night Band won’t see it at all.

So, can the Day/Night Band detect Steve? I can’t answer that based on this information. We will have to wait for another dedicated aurora photographer to take a picture of Steve at a time and place when VIIRS is directly overhead. Feel cheated by that? Just enjoy the images of the aurora above. And, here are a few more from this event:

VIIRS Day/Night Band image (11:34 UTC 22 April 2017)

VIIRS Day/Night Band image (11:34 UTC 22 April 2017)

VIIRS Day/Night Band image (07:53 UTC 23 April 2017)

VIIRS Day/Night Band image (07:53 UTC 23 April 2017)

VIIRS Day/Night Band image (09:34 UTC 23 April 2017)

VIIRS Day/Night Band image (09:34 UTC 23 April 2017)

Don’t forget to click on them to see the full resolution!

UPDATE (13 October 2017): Over the years, I have looked at a number of Day/Night Band images of the aurora. During that time, I’ve noticed some “auroras” that appear to be very “Steve”-like. One example is shown in the image below from 17 January 2015.

VIIRS Day/Night Band image (13:09 UTC 17 January 2015)

VIIRS Day/Night Band image (13:09 UTC 17 January 2015)

The question is: is this an example of Steve? Or, just a less active aurora?

Of course, being over a remote part of northern Alaska, it’s unlikely anyone got a photograph to prove it was Steve. We’ll still have to wait for the perfect alignment of Steve, Steve-hunters and VIIRS to know if the Day/Night Band can (or cannot) detect them.

On the Disappearance of Lake Mille Lacs

Two weeks ago, one of Minnesota’s 10,000 lakes disappeared, leaving them with only 9,999. And, it wasn’t a small one, either. It was the state’s second largest inland lake. But, this is not like Goose Lake, which actually did dry up. The lake in question simply became temporarily invisible. So, no need to panic, fishing and boating enthusiasts. But, as you’ll see, the term “invisible” can be just as ambiguous as the term “lake”.

Let’s start with the fact that Minnesota doesn’t have 10,000 lakes. Their slogan is a lie! Depending on how you define a lake, Minnesota has 21,871, or 15,291, or 11,842. But, Wisconsin might have more (or less) and likes to argue with Minnesota about that fact. Michigan might have way more (62,798) or way less (6,537). And, they all pale in comparison to the number of lakes in Alaska. Here is an article that explains the situation nicely.

With that out of the way, today’s story comes from “current GOES” and what one colleague noticed during a cursory examination of GOES Imager images. Here’s the GOES-13 visible image from 19:30 UTC 27 January 2017:

GOES-13 visible image, taken 19:30 UTC 27 January 2017

GOES-13 visible image, taken 19:30 UTC 27 January 2017

Compare that with the visible image from 19:15 UTC 2 February 2017:

GOES-13 visible image, taken 19:15 UTC 2 February 2017

GOES-13 visible image, taken 19:15 UTC 2 February 2017

Notice anything different between the two images over Minnesota? No? Then let’s flip back-and-forth between the two, with a giant, red arrow pointing to the area in question:

Animation of the above images

Animation of the above images. The red arrow points to Lake Mille Lacs.

The red arrow is pointing to the location of Lake Mille Lacs. You might know it as Mille Lacs Lake. (Either way, it’s name is redundant; “Mille Lacs” is French for “Thousand Lakes,” making it Thousand Lakes Lake.) As the above images show, on 27 January 2017 Lake Mille Lacs was not visible in the GOES image. On 2 February 2017, it was. They both look like clear days, so what happened? Why did Lake Mille Lacs disappear?

As I said before, the lake didn’t dry up. It simply became temporarily invisible. But, this requires a discussion about what it means to be “visible”. Lake Mille Lacs shows up in the image from 2 February 2017 because it appears brighter than the surrounding land. That’s because the lake is covered with snow. Aren’t the surrounding land areas also covered with snow? Yes. However, the surrounding lands also have trees which obscure the snow and shade the background surface, which is why forested areas appear darker even when there is snow.

That leads to this question: why does the lake appear darker on 27 January? Because it rained the week before. Want proof? Look at the almanac for Brainerd (NW of Lake Mille Lacs) for the period of 18-22 January 2017. Every day made it above freezing along with several days of rain. Much of the snow melted (including the snow on the lake). Want more proof? Here’s a video taken on the lake from 20 January 2017. See how Minnesotans drive around on frozen lakes – even in the rain? And, see how wet and slushy the surface of the ice is? This makes it appear darker than when there is fresh snow on top. If you’ve ever seen a pile of slush, you know it’s not bright white, but a dull gray color. The less reflective slush on the lake reduced the apparent brightness down to the level of the surrounding woodlands. That’s why the lake appeared to disappear.

Now, this is “current GOES” imagery. We can do better with VIIRS, since we have more channels to play with. And, as we all know, GOES-R successfully launched back in November 2016 and is now in orbit as GOES-16. This satellite has the first Advanced Baseline Imager (ABI) in space. The ABI has many of the same channels as VIIRS, so the following discussion applies to both instruments. “New” GOES will have up to 500 m resolution in the visible, which is much closer to VIIRS (375 m) than “current” GOES (1 km). That’s another thing to think about when we talk about what is visible and what isn’t.

Here are the VIIRS high-resolution visible (I-1) images that correspond to the GOES images above:

VIIRS high-resolution visible (I-1) image, taken 19:35 UTC 27 January 2017

VIIRS high-resolution visible (I-1) image, taken 19:35 UTC 27 January 2017

VIIRS high-resolution visible (I-1) image, taken 19:22 UTC 2 February 2017

VIIRS high-resolution visible (I-1) image, taken 19:22 UTC 2 February 2017

Although, we should probably focus on Minnesota. Here are the cropped images side-by-side:

Comparison between VIIRS high-resolution visible (I-1) images

Comparison between VIIRS high-resolution visible (I-1) images

Remember: you can click on any image to bring up the full resolution version.

Although Lake Mille Lacs is just barely visible in the image from 27 January, it’s much easier to see on 2 February. So, we get the same story from VIIRS that we got with GOES, which is good. That means we don’t have a major fault of a multi-million dollar satellite. It’s a “fault” of the radiative properties of slush, combined with the low resolution of the GOES images above.

Keep your eyes also on the largest inland lake in Minnesota: Red Lake. The Siamese twins of Upper and Lower Red Lake didn’t get as much rain as Lake Mille Lacs and its snow never fully melted, so its appearance doesn’t change much between the two images.

The GOES Imager also has a longwave infrared (IR) channel, and a mid-wave IR channel similar to VIIRS. Since the goal of this is not to compare GOES to VIIRS, but to show how these lakes appear at different wavelengths, we’ll stick to the VIIRS images. Here are the high-resolution VIIRS longwave IR images from the same times:

Comparison of VIIRS high-resolution longwave IR (I-5) images

Comparison of VIIRS high-resolution longwave IR (I-5) images

In both images, the lakes are nearly invisible! This is because the longwave IR is primarily sensitive to temperature changes, and the slush is nearly the same temperature as the background land surface. With no temperature contrast to key on, the lake looks just like the surrounding land. Although, if you zoom in and squint, you might say that Lake Mille Lacs is actually more visible in the image from 27 January. 27 January was a warmer day (click back on that Brainerd almanac), and the surrounding land warmed up more than the slushy ice on the lake. 2 February was much colder on the lake and the land. But, let this be a lesson that, just because the lake doesn’t show up, it doesn’t mean the lake doesn’t exist!

Something interesting happens when you look at the mid-wave IR. All the lakes are visible, and take on a similar brightness, no matter how slushy they are:

Comparison of VIIRS high-resolution mid-wave IR (I-4) images

Comparison of VIIRS high-resolution mid-wave IR (I-4) images

In this wavelength range, both reflection of solar energy and thermal emission are important. Snow, ice and slush are not reflective and they are cold, making the lakes appear darker than the surrounding land. The fact that the land surrounding Lake Mille Lacs and Red Lake is darker on 2 February than it is on 27 January is further proof that it was a colder day with more snow on the ground.

Here’s where we get to the advantage of VIIRS (and, soon, GOES-16): it has more channels in the shortwave and near-IR. The 1.6 µm “snow and ice” band has a lot of uses, and I expect it will be a popular channel on the ABI. Here’s what the high-resolution channel looks like from VIIRS:

Comparison of VIIRS high-resolution near-IR (I-3) images

Comparison of VIIRS high-resolution near-IR (I-3) images

Compare these with the visible images above. Now, the reverse is true: Lake Mille Lacs is easier to see in the first image than the second! You can’t call it invisible at all on 27 January! The presence of liquid water makes the slush very absorbing – more than even ice and snow – so it appears nearly black. In fact, it’s hard to tell the difference between the slushy ice-covered Lake Mille Lacs, and the open waters of Lake Superior, which has no ice or slush on it. On 2 February, we see the fresh layer of snow on Lake Mille Lacs has increased the lake’s reflectivity, but it’s still slightly darker than the surrounding snow covered land. This is for two reasons: snow and ice are absorbing at 1.6 µm and the surrounding woodlands are more reflective.

Here’s a better comparison between the “visible” and the “snow and ice” bands:

Comparison of VIIRS I-1 and I-3 images (animation)

Comparison of VIIRS I-1 and I-3 images (animation)

You’ll have to click on the image to see it animate between the two.

Here’s an animation showing all five high-resolution bands on VIIRS for the two days:

Comparison of VIIRS high-resolution imagery channels (animation)

Comparison of VIIRS high-resolution imagery channels (animation)

Again, you have to click on it to see it animate.

Now, we can combine channels into RGB composites that highlight the snow and ice. We’ve discussed several RGB composites for snow detection before. And, we have been looking at the Natural Color RGB for a long time. This composite combines the high-resolution bands I-1 (0.64 µm), I-2 (0.86 µm) and I-3 (1.6 µm) as the blue, green and red components of the image, respectively. Here’s what it looks like for these two days:

Comparison of VIIRS Natural Color RGB composites

Comparison of VIIRS Natural Color RGB composites using high-resolution imagery bands

Lake Mille Lacs is visible on both days – first because it’s darker than the surroundings, then because it’s brighter. This composite demonstrates how vegetation can obscure the surface snow – it appears more brown in deciduous forests (and bare fields with no snow) and green in coniferous areas. But, the important point is that the wetter the snow and slush, the darker it appears. The fresher the snow, the brighter cyan color it has.

This is exaggerated in the “Snow RGB” that combines moderate resolution bands M-11 (2.25 µm), M-10 (1.6 µm) and M-7 (0.86 µm):

Comparison of VIIRS "Snow RGB" composites of channels M-11, M-10 and M-7

Comparison of VIIRS “Snow RGB” composites of channels M-11, M-10 and M-7

M-11 (2.25 µm) is sold as a “cloud particle size” band, but it also helps with snow and ice detection (and fires). The presence of water in melting snow enhances the darkening at 2.25 µm. In this RGB, that means melting snow appears more red, while fresh snow appears more pink. The slush on Lake Mille Lacs appears very dark – almost as dark as Lake Superior – so a Minnesotan might be forgiven if they see the image from 27 January and decide not to drive out on the lake to go ice fishing because they think the ice isn’t there.

Of course, VIIRS also gives us the True Color RGB – the most intuitive RGB composite – that combines the blue-, green- and red-wavelength visible bands: M-3 (0.48 µm), M-4 (0.55 µm) and M-5 (0.67 µm). If you’re curious, here’s what that looks like:

Comparison of VIIRS True Color RGB composite images

Comparison of VIIRS True Color RGB composite images

The slush on Lake Mille Lacs looks just like dirty slush and the fresh snow looks just like snow. (As it should!)

So, the second biggest lake in Minnesota never disappeared – it just changed its surface properties. And, it will always be “visible” to VIIRS in one channel or another – unless it’s cloudy (or it completely dries up).

December Fluff

By now, you probably know the drill: a little bit of discussion about a particular subject, throw in a few pop culture references, maybe a video or two, then get to the good stuff – high quality VIIRS imagery. Then, maybe add some follow-up discussion to emphasize how VIIRS can be used to detect, monitor, or improve our understanding of the subject in question. Not today.

You see, VIIRS is constantly taking high quality images of the Earth (except during orbital maneuvers or rare glitches). There isn’t enough time in a day to show them all, or go into a detailed discussion as to their relevance. And, nobody likes to read that much anyway. So, as we busily prepare for the upcoming holidays, we’re going to skip the in-depth discussion and get right to the good stuff.

Here then is a sample of interesting images taken by VIIRS over the years that weren’t featured on their own dedicated blog posts. Keep in mind that they represent the variety of topics that VIIRS can shed some light on. Many of these images represent topics that have already been discussed in great detail in previous posts on this blog. Others haven’t. It is important to keep in mind… See, I’m starting to write too much, which I said I wasn’t going to do. I’ll shut up now.

Without further ado, here’s a VIIRS Natural Color image showing a lake-effect snow event that produced a significant amount of the fluffy, white stuff back in November 2014:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (18:20 UTC 18 November 2014)

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (18:20 UTC 18 November 2014)

As always, click on the image to bring up the full resolution version. Did you notice all the cloud streets? How about the fact that the most vigorous cloud streets have a cyan color, indicating that they are topped with ice crystals? The whitish clouds are topped with liquid water and… Oops. I’m starting to discuss things in too much detail, which I wasn’t going to do today. Let’s move on.

Here’s another Natural Color RGB image using the high-resolution imagery bands showing a variety of cloud streets and wave clouds over the North Island of New Zealand:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (02:55 UTC 3 September 2016)

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (02:55 UTC 3 September 2016)

Here’s a Natural Color RGB image showing a total solar eclipse over Scandinavia in 2015:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (10:06 UTC 20 March 2015)

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (10:06 UTC 20 March 2015)

Here’s a VIIRS True Color image and split-window difference (M-15 – M-16) image showing volcanic ash from the eruption of the volcano Sangeang Api in Indonesia in May 2014:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:20 UTC 31 May 2014)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:20 UTC 31 May 2014)

VIIRS split-window difference (M-15 - M-16) image (06:20 UTC 31 May 2014)

VIIRS split-window difference (M-15 – M-16) image (06:20 UTC 31 May 2014)

Here’s a VIIRS True Color image showing algae and blowing dust over the northern end of the Caspian Sea (plus an almost-bone-dry Aral Sea):

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (09:00 UTC 18 May 2014)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (09:00 UTC 18 May 2014)

Here is a high-resolution infrared (I-5) image showing a very strong temperature gradient in the Pacific Ocean, off the coast of Hokkaido (Japan):

VIIRS I-5 (11.45 um) image (03:45 UTC 12 December 2016)

VIIRS I-5 (11.45 um) image (03:45 UTC 12 December 2016)

The green-to-red transition just southeast of Hokkaido represents a sea surface temperature change of about 10 K (18 °F) over a distance of 3-5 pixels (1-2 km). This is in a location that the high-resolution Natural Color RGB shows to be ice- and cloud-free:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (03:45 UTC 12 December 2016)

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (03:45 UTC 12 December 2016)

Here’s a high-resolution infrared (I-5) image showing hurricanes Madeline and Lester headed toward Hawaii from earlier this year:

VIIRS I-5 (11.45 um) image (22:55 UTC 30 August 2016)

VIIRS I-5 (11.45 um) image (22:55 UTC 30 August 2016)

Here are the Fire Temperature RGB (daytime) and Day/Night Band (nighttime) images of a massive collection of wildfires over central Siberia in September 2016:

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 (05:20 UTC 18 September 2016)

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 (05:20 UTC 18 September 2016)

VIIRS Day/Night Band image (19:11 UTC 18 September 2016)

VIIRS Day/Night Band image (19:11 UTC 18 September 2016)

Here is a 5-orbit composite of VIIRS Day/Night Band images showing the aurora borealis over Canada (August 2016):

Day/Night Band image composite of 5 consecutive VIIRS orbits (30 August 2016)

Day/Night Band image composite of 5 consecutive VIIRS orbits (30 August 2016)

Here is a view of central Europe at night from the Day/Night Band:

VIIRS Day/Night Band image (01:20 UTC 21 September 2016)

VIIRS Day/Night Band image (01:20 UTC 21 September 2016)

And, finally, for no reason at all, here’s is a picture of Spain wearing a Santa hat (or sleeping cap) made out of clouds:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (13:05 UTC 18 March 2014)

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 (13:05 UTC 18 March 2014)

There you have it. A baker’s ten examples showing a small sample of what VIIRS can do. No doubt it will be taking more interesting images over the next two weeks, since it doesn’t stop working over the holidays – even if you and I do.