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!)

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!

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).

Germany’s Magic Sparkle

You may or may not have heard that a small town in Italy received 100 inches (250 cm; 2.5 m; 8⅓ feet; 8 x 10-17 parsecs) of snow in 18 hours just last week (5 March 2015). That’s a lot of snow! It’s more than what fell on İnebolu, Turkey back in the beginning of January. But, something else happened that week that is much more interesting.

All you skiers are asking, “What could be more interesting than 100 inches of fresh powder?” And all you weather-weenies are asking, “What could be more interesting than being buried under a monster snowstorm? I mean, that makes Buffalo look like the Atacama Desert!” The answer: well, you’ll have to read the rest of this post. Besides, VIIRS is incapable of measuring snow depth. (Visible and infrared wavelengths just don’t give you that kind of information.) So, looking at VIIRS imagery of that event isn’t that informative.

This is (or was, until I looked into it in more detail) another mystery. Not a spooky, middle-of-the-night mystery, but one out in broad daylight. (We can thus automatically rule out vampires.)

It started with a comparison between “True Color” and “Natural Color” images over Germany from 9 March 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 11:54 UTC 9 March 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 11:54 UTC 9 March 2015.

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 11:54 UTC 9 March 2015

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 11:54 UTC 9 March 2015.

The point was to show, once again, how the Natural Color RGB composite can be used to differentiate snow from low clouds. That’s when I noticed it. Bright pixels (some white, some orange, some yellow, some peach-colored) in the Natural Color image, mostly over Bavaria. (Remember, you can click on the images, then click again, to see them in full resolution.) Thinking they might be fires, I plotted up our very own Fire Temperature RGB:

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 from 11:54 UTC 9 March 2015

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 from 11:54 UTC 9 March 2015.

I’ve gone ahead and drawn a white box around the area of interest. Let’s zoom in on that area for these (and future) images.

VIIRS True Color RGB (11:54 UTC 9 March 2015)

VIIRS True Color RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

VIIRS Natural Color RGB (11:54 UTC 9 March 2015)

VIIRS Natural Color RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

VIIRS Fire Temperature RGB (11:54 UTC 9 March 2015)

VIIRS Fire Temperature RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

Now, these spots really show up. But, they’re not fires! Fires show up red, orange, yellow or white in the Fire Temperature composite (which is one of the benefits of it). They don’t appear pink or pastel blue. What the heck is going on?

Now, wait! Go back to the True Color image and look at it at full resolution. There are white spots right where the pastel pixels show up in the Fire Temperature image. (I didn’t notice initially, because white spots could be cloud, or snow, or sunglint.) This is another piece of evidence that suggests we’re not looking at fires.

For a fire to show up in True Color images, it would have to be about as hot as the surface of the sun and cover a significant portion of a 750-m pixel. Terrestrial fires don’t typically get that big or hot on the scale needed for VIIRS to see them at visible wavelengths. Now, fires don’t have to be that hot to show up in Natural Color images, but even then they appear red. Not white or peach-colored. If a fire was big enough and hot enough to show up in a True Color image, it would certainly show up in the high-resolution infrared (IR) channel (I-05, 11.45 µm), but it doesn’t:

VIIRS high-resolution IR (I-05) image (11:54 UTC 9 March 2015)

VIIRS high-resolution IR (I-05) image (11:54 UTC 9 March 2015).

You might be fooled, however, if you looked at the mid-wave IR (I-04, 3.7 µm) where these do look like hot spots:

VIIRS high-resolution midwave-IR (I-04) image (11:54 UTC 9 March 2015)

VIIRS high-resolution midwave-IR (I-04) image (11:54 UTC 9 March 2015).

What’s more amazing is I was able to see these bright spots all the way down to channel M-1 (0.412 µm), the shortest wavelength channel on VIIRS:

VIIRS "deep blue" visible (M-1) image (11:54 UTC 9 March 2015)

VIIRS “deep blue” visible (M-1) image (11:54 UTC 9 March 2015).

So, what do we know? Bright spots appear in all the bands where solar reflection contributes to the total radiance (except M-6 and M-9). I checked. (They don’t show up in M-6 [0.75 µm], because that channel is designed to saturate under any solar reflection so everything over land looks bright. They don’t show up in M-9 [1.38 µm] because solar radiation in that band is absorbed by water vapor and never makes it to the surface.) Hot spots do not coincide with these bright spots in the longer wavelength IR channels (above 4 µm).

What reflects a lot of radiation in the visible and near-IR but does not emit a lot in the longwave IR? Solar panels. That’s the answer to the mystery. VIIRS was able to see solar radiation reflecting off of a whole bunch of solar panels. That is the source of Germany’s “magic sparkle”.

Don’t believe me? First off, Germany is a world leader when it comes to producing electricity from solar panels. Solar farms (or “solar parks” auf Deutsch) are common – particularly in Bavaria, which produces the most solar power per capita of any German state.

Second: I was able to link specific solar parks with the bright spots in the above images using this website. (Not all of those solar parks show up in VIIRS, though. I’ll get to that.) And these solar parks can get quite big. Let’s take a look at a couple of average-sized solar parks on Google Maps: here and here. The brightest spot in the VIIRS Fire Temperature image (near 49° N, 11° E) matches up with this solar park, which is almost perfectly aligned with the VIIRS scans and perpendicular to the satellite track.

Third: it’s not just solar parks. A lot of people and businesses have solar panels on their roofs. Zoom in on Pfeffenhausen, and try to count the number of solar panels you see on buildings.

One more thing: if you think solar panels don’t reflect a lot of sunlight, you’re wrong. Solar power plants have been known reflect so much light they instantly incinerate birds*. (*This is not exactly true. See the update below.)

Another important detail is that all of the bright spots visible in the VIIRS images are a few degrees (in terms of satellite viewing angle) to the west of nadir. Given where the sun is in the sky this time of year (early March) and this time of day (noon) at this latitude (48° to 50° N), a lot of these solar panels are in the perfect position to reflect sunlight up to the satellite. But, not all of them. Some solar panels track the sun and move throughout the day. Other panels are fixed in place and don’t move. Only the solar panels in the right orientation relative to the satellite and the sun will be visible to VIIRS.

At these latitudes during the day, the sun is always to south and slightly to the west of the satellite. For the most part, solar panels to the east of the satellite will reflect light away from the satellite, which is why you don’t see any of those. If the panel is pointed too close to the horizon, or too close to zenith (or the sun is too high or too low in the sky), the sunlight will be reflected behind or ahead of the satellite and won’t be seen. You could say that this “sparkle” is actually another form of glint, like sun glint or moon glint – only this is “solar panel glint”.

Here’s a Natural Color image from the very next day (10 March 2015), when the satellite was a little bit further east and overhead a little bit earlier in the day:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 from 11:35 UTC 10 March 2015

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 from 11:35 UTC 10 March 2015.

Notice the half-dozen-or-so bright spots over the Czech Republic. These are just west of the satellite track and in the same position relative to satellite and sun. (The bright spot near the borders of Austria and Slovakia matches up with this solar farm.) The bright spots over Germany are gone because they no longer line up with the sun and satellite geometry.

As for the pastel colors in the Natural Color and Fire Temperature RGBs, those are related to the proportional surface area of the solar panels relative to the size of each pixel as well as the background reflectivity of the ground surrounding the solar panels. The bright spots do generally appear more white in the high-resolution version of the Natural Color RGB from 9 March:

VIIRS high-resolution Natural Color (I-01, I-02, I-03) RGB image (11:54 UTC 9 March 2015)

VIIRS high-resolution Natural Color (I-01, I-02, I-03) RGB image (11:54 UTC 9 March 2015).

See, we learned something today. Germany sparkles with green electricity and VIIRS can see it!

UPDATES (17 March 2015): Thanks to feedback from Renate B., who grew up in Bavaria and currently owns solar panels, we have this additional information: there is a push to add solar panels onto church roofs throughout Bavaria, since they tend to be the tallest buildings in town (not shaded by anything) and are typically positioned facing east, so the south-facing roof slopes are ideal for collecting sunlight. The hurdle is that churches are protected historical buildings that people don’t want to be damaged. Also, it’s not a coincidence that many solar parks have their solar panels facing southeast (and align with the VIIRS scan direction). They are more efficient at producing electricity in the morning, when the temperatures are lower, than they are in the afternoon when the panels are warmer. They face southeast to better capture the morning sun.

Also, to clarify (as pointed out by Ed S.): the solar power plant that incinerates birds generates electricity from a different mechanism than the photovoltaic (PV) arrays seen in these images from Germany. PV arrays (aka solar parks) convert direct sunlight to electricity. The “bird incinerator” uses a large array of mirrors to focus sunlight on a tower filled with water. The focused sunlight heats the water until it boils, generating steam that powers a turbine. Solar parks and solar panels on houses and churches do not cause birds to burst into flames.

Fires in Paradise

Sometimes, it seems like the whole world is on fire. Siberia. The western United States (which has been burning for some time). And now, the Canary Islands. The Spanish islands have been under a drought, as has much of Spain. (As an indication of how dry it has been, one fire in mainland Spain was started by someone flicking a cigarette butt out of their car window in a traffic jam – a fire that ultimately led to two deaths.) Back in July, fires got started on Tenerife – a major resort destination – and earlier this month, fires began on La Palma and La Gomera. At least two firefighters have already died battling these fires.

For your reference, here is a VIIRS “true color” image (M-3 [0.488 µm], M-4 [0.555 µm], M-5 [0.672 µm]) of the Canary Islands, with the major islands labelled:

VIIRS true color RGB composite of channels M-3, M-4 and M-5, taken 14:01 UTC 5 August 2012

VIIRS true color RGB composite of channels M-3, M-4 and M-5, taken 14:01 UTC 5 August 2012

If you look closely at this image, from 5 August 2012, you can see smoke plumes coming off of La Palma and La Gomera. You can also see what looks like a von Kármán vortex street downwind of La Palma. That’s the west coast of Africa in the lower-right corner of the image.

As discussed previously, the true color RGB composite is better for viewing the smoke plume, but you can’t actually see the fire directly. So, here’s the M-5 (0.672 µm), M-7 (1.61 µm) and M-11 (2.25 µm) composite from the same time:

VIIRS RGB composite of channels M-5, M-7 and M-11, taken 14:01 UTC 5 August 2012

VIIRS RGB composite of channels M-5, M-7 and M-11, taken 14:01 UTC 5 August 2012

It’s easy to see where the fires are actively burning with this composite. Let’s zoom in to make it even more obvious:

VIIRS false color RGB composite of channels M-5, M-7 and M-11, taken 14:01 UTC 5 August 2012

VIIRS false color RGB composite of channels M-5, M-7 and M-11, taken 14:01 UTC 5 August 2012

All the bright red pixels indicate where the fire is actively burning. You can also see the burn scar on Tenerife (not as easily as in Siberia) where the M-5, M-7, M-11 RGB composite shows the fire was back in July:

VIIRS false color RGB composite of  channels M-5, M-7 and M-11, taken 14:38 UTC 18 July 2012

VIIRS false color RGB composite of channels M-5, M-7 and M-11, taken 14:38 UTC 18 July 2012

La Gomera has been the hardest hit island, where thousands of people had to be evacuated, and approximately 10% of Garajonay National Park has burned. Garajonay National Park is home to one of the last remaining laurisilva forests, which has been around for 11 million years. That lush vegetation burned hot, and channel I-04 (3.7 µm) reached saturation as that area went up in flames:

VIIRS channel I-04 image of fires in the Canary Islands, taken 14:01 UTC 5 August 2012

VIIRS channel I-04 image of fires in the Canary Islands, taken 14:01 UTC 5 August 2012

The two white pixels on La Gomera are where I-04 reached saturation and “fold-over” due to the heat from the fire. M-13 (4.0 µm), which is a dual-gain band designed to not saturate, reached a brightness temperature of 451 K over La Gomera, compared with a saturation brightness temperature of 367 K for channel I-04.

The fires also showed up in the Day/Night Band that night:

VIIRS Day/Night Band image of the Canary Islands, taken 02:25 UTC 6 August 2012

VIIRS Day/Night Band image of the Canary Islands, taken 02:25 UTC 6 August 2012

The red arrows point out the fires on La Palma and La Gomera. The fire on La Gomera covers a significant percentage of the island. The yellow arrow points to Lanzarote, which, for some reason, is not part of IDL’s map. On the night this image was taken, the moon was approximately 84% full, so you can see a number of clouds as well the city lights from the major resort areas of the Canary Islands. The biggest visible city in Africa is El Aaiún, the disputed capital of Western Sahara.

Finally, here’s the “pseudo-true color” composite of VIIRS channels I-01 (0.64 µm), I-02 (0.87 µm) and I-03 (1.61 µm) from 13:42 UTC 6 August 2012. This is a full granule at the native resolution of the Imagery bands with no re-mapping, showing the rich detail of VIIRS high-resolution imagery, including more interesting cloud vortices:

VIIRS false color RGB composite of channels I-01, I-02 and I-03, taken 13:42 UTC 6 August 2012

VIIRS false color RGB composite of channels I-01, I-02 and I-03, taken 13:42 UTC 6 August 2012

Make sure to click on the image, then on the “6400×1536” link to see it in its full glory.