Don’t Eat Orange Snow

Roughly one month ago, social media (and, later, more conventional media) outlets were inundated with numerous reports of orange snow in eastern Europe and western Asia – reports like this one, this one and this one. Of course, it wouldn’t really be a hit with the media unless someone could claim it was “apocalyptic”. And of course, the apocalypse didn’t happen. It was simply Saharan dust picked up by high winds from an intense mid-latitude cyclone and deposited far away. We’ve seen this before with VIIRS.

These reports focused on Sochi, Russia, home of the 2014 Winter Olympics. Unfortunately, every time I looked for it in VIIRS imagery, it was cloudy in Sochi. But, the plume of Saharan dust that caused this event was clearly visible over the Mediterranean:

NOAA-20 VIIRS true color composite of channels M-3, M-4 and M-5 (10:03 UTC 25 March 2018)

NOAA-20 VIIRS true color composite of channels M-3, M-4 and M-5 (10:03 UTC 25 March 2018)

This image came from our new NOAA-20 VIIRS, which, at this point, is not operational and undergoing additional testing. If you look closer, you might also notice smoke or smog over Poland in the image above (upper left corner). If you really zoom in (click on the image to get to the full resolution version), you may notice a brownish tint to the snow along the north shore of the Black Sea – where the BBC report I linked to listed additional sightings of orange snow. But, the dust-covered snow shows up more clearly in this “before and after” image courtesy of S-NPP VIIRS and the @NOAASatellites twitter account:

"Before" and "After" S-NPP VIIRS true color images from 22 March 2018 (left) and 25 March 2018 (right) showing dust on snow in eastern Europe.

“Before” and “After” S-NPP VIIRS true color images from 22 March 2018 (left) and 25 March 2018 (right).

(As an aside: differences in technique used to produce these true color images are likely larger than the differences between S-NPP VIIRS and NOAA-20 VIIRS, so don’t read too much into the fact that the dust-on-snow appears more clearly in the @NOAASatellites image than in my own.)

But, dust-on-snow is not limited to areas within a few thousand kilometers of the Sahara Desert. (It is limited to areas within 40,000 km of the Sahara [in the horizontal dimension, at least], since that is roughly the circumference of the Earth – and assuming you ignore dust storms on Mars.) Dust on snow can happen anywhere you have snow within striking distance of a source of dust. Another example was captured by a new Landsat-like micro-satellite, Venµs, and its non-microsat predecessor, Sentinel-2B, Landsat’s European cousin. A more dramatic example happened last week right here in Colorado. Here is a VIIRS true color image of Colorado from S-NPP VIIRS, taken on 14 April 2018:

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (19:45 UTC 14 April 2018)

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (19:45 UTC 14 April 2018)

Here are similar images from NOAA-20 and S-NPP from 18 April 2018:

NOAA-20 VIIRS true color composite of channels M-3, M-4 and M-5 (19:20 UTC 18 April 2018)

NOAA-20 VIIRS true color composite of channels M-3, M-4 and M-5 (19:20 UTC 18 April 2018)

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (20:11 UTC 18 April 2018)

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (20:11 UTC 18 April 2018)

The trick is to compare these two images with the image from 14 April. The other trick is to know where you’re supposed to be looking. (Hint: we’re looking at the Sangre de Cristo mountains in southern Colorado.) Here’s a “before” and “after” image overlay trick I’ve used before. (You may have to refresh the page before it will work.) Both of these images are the S-NPP VIIRS ones, for simplicity:

If you slide the bar left to right, you should notice the snow is more brown in the mountains just right of center in the 18 April image. There are other areas where the snow melted between the two images, plus a couple of small clouds that add to the differences. Of course, this is only 750 m resolution. We get a better view with the 375m-resolution visible channel, I-1:

We lose the color information, of course, since we are looking at a single channel, but it is obvious the snow became less reflective in the 18 April image. And, we can prove that this was a result of dust. Here are the visible, true color, Dust RGB, “Blue Light Dust” and DEBRA Dust images from S-NPP on 17 April 2018, courtesy Steve M.:

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (20:26 UTC 17 April 2018)

S-NPP VIIRS true color composite of channels M-3, M-4 and M-5 (20:26 UTC 17 April 2018)

S-NPP VIIRS Dust RGB image (20:26 UTC 17 April 2018)

S-NPP VIIRS Dust RGB image (20:26 UTC 17 April 2018)

S-NPP VIIRS Blue Light Dust image (20:26 UTC 17 April 2018)

S-NPP VIIRS Blue Light Dust image (20:26 UTC 17 April 2018)

S-NPP VIIRS DEBRA Dust image (20:26 UTC 17 April 2018)

S-NPP VIIRS DEBRA Dust image (20:26 UTC 17 April 2018)

If you are unfamiliar with them, we’ve looked at the Dust RGB, Blue Light Dust and DEBRA before, here and here. As seen in the above images, this was not a difficult to detect dust case. Even Landsat-8 captured this event, which is surprising given the narrow swath and 16-day orbit repeat cycle. (Sure, it’s higher resolution than VIIRS, but will it be overhead when you need it?)

So now we get to why dust-on-snow is important. There is a growing body of research (e.g. this paper) that shows dust-on-snow has a big impact on water resources in places like the Rocky Mountains. You see, dirty snow is less reflective than clean snow. That means it absorbs more solar radiation. This, in turn, means it heats up and melts faster, leading to earlier spring run-off. The end result is less water later in the season, which opens the door to wildfires and more severe droughts. This article that, coincidentally, was published as I was writing this, sums things up nicely. It is so important, the Center for Snow and Avalanche Studies has formed CODOS: the Colorado Dust on Snow Program, whose purpose is to monitor dust on snow and provide weekly updates.

As for why you shouldn’t eat orange snow, that should be obvious. You shouldn’t eat any snow that isn’t pure white (and even that might be risky). But, feel free to eat colorful ice, as long as you know where it came from.

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.

The Sirocco and the Giant Bowl of Dust

As mentioned before on this blog, there are typhoons, hurricanes, and cyclones, and they’re all basically the same thing. They’re just given a different name depending on where they occur in the world. Similarly, there are many different names for winds (not counting the classification of wind speeds developed by a guy named Beaufort). There’s the Chinook, the Santa Ana, the bora, the föhn (or foehn), the mistral, the zonda, the zephyr and the brickfielder. (A more complete list is here.) Some of these winds are different names for the same phenomenon occurring in different parts of the world, like the föhn, the chinook, the zonda and the Santa Ana. Others are definitely different phenomena, with different characteristics (compare the mistral with the brickfielder), but they all have the same basic cause: the atmosphere is constantly trying to equalize its pressure.

The Mediterranean is home to wide variety of named winds, one of which is the sirocco (or scirocco). (Europe is home to wide variety of languages, so this wind is also known as “ghibli,” “jugo” [pronounced “you-go”], “la calima” and “xlokk” [your guess is as good as mine].) Sirocco is the name given to the strong, southerly or southeasterly wind originating over northern Africa that typically brings hot, dry air and, if it’s strong enough, Saharan dust to Europe. Of course, after picking up moisture from the Mediterranean, the wind becomes humid, making life unpleasant for people along the north shore. Hot, humid and full of dust. Perhaps it’s no surprise that the sirocco is believed to be a cause of insomnia and headaches.

Now, I don’t know how hot it was, but an intense low pressure system passed through the Mediterranean around Leap Day and, out ahead of it, strong, southerly winds carried quite a bit of dust from northern Africa into Italy.  Here’s what it looked like in Algeria. And here’s what it looked like in Salento. See if you can see that dust in these True Color VIIRS images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:09 UTC 28 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:09 UTC 28 February 2016).

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (11:48 UTC 29 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (11:48 UTC 29 February 2016)

No problem, right? With True Color imagery, the dust is usually easy to identify and distinguish from clouds and the ocean because it looks like dust. It’s the same color as the sky over Salento, Italy in that video I linked to. The top image shows multiple source regions of dust (mostly Libya, with a little coming from Tunisia) being blown out over the sea. The second image shows one concentrated plume being pulled into the clouds over the Adriatic Sea, headed for Albania and Greece.

By the way, this storm system brought up to 2 meters (6.5 feet) of snow to northern Italy, and even brought measurable snow to Algeria! Africa and Europe made a trade: you take some of my dust, and I’ll take some of your snow.

But, this wasn’t the worst dust event to hit Europe recently. Here’s what the VIIRS True Color showed over Spain and Portugal on 21 February 2016:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:40 UTC 21 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:40 UTC 21 February 2016).

And VIIRS wasn’t the only one to see this dust. Here’s a picture taken by Tim Peake, an astronaut on the International Space Station. Again, it’s easy to pick out the dust because it almost completely obscures the view of the background surface. But, what if the background surface is dust colored?

We switch now to the other side of the world and the Takla Makan desert in China, where the dust has been blowing for the better part of a week:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:11 UTC 4 March 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:11 UTC 4 March 2016).

Can you tell what is dust and what is the desert floor? Can you see the Indian Super Smog on the south side of the Himalayas? Here is the same scene on a clear (no dust) day:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:49 UTC 2 March 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:49 UTC 2 March 2016).

There is a subtle difference there, but you need good eyesight to see it. It might be easier to see if you loop the images:

Animation of VIIRS True Color images (1-7 March 2016)

Animation of VIIRS True Color images of the Takla Makan desert (1-7 March 2016).

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

Did you notice the dark brown areas surrounding the Takla Makan? Those are areas that have green vegetation during the summer. Notice how they become completely obscured by the dust as the animation progresses. That’s one one way to tell that there’s dust there. But, as we have seen before, there are other ways to see the dust.

There’s EUMETSAT’s Dust RGB composite applied to VIIRS:

Animation of VIIRS EUMETSAT Dust RGB images (1-7 March 2016)

Animation of VIIRS EUMETSAT Dust RGB images of the Takla Makan desert (1-7 March 2016).

That’s another animation, by the way, so you’ll have to click on it to see it animate. The same is true for the Dynamic Enhanced Background Reduction Algorithm (DEBRA), which we also talked about before:

Animation of VIIRS DEBRA Dust Product images (1-7 March 2016)

Animation of VIIRS DEBRA Dust Product images of the Takla Makan desert (1-7 March 2016)

But, there’s one more dust detection technique we have not discussed before: the “blue light absorption” technique:

Animation of VIIRS Blue Light Dust images (1-7 March 2016)

Animation of VIIRS Blue Light Dust images of the Takla Makan desert (1-7 March 2016).

The Blue Light Dust detection algorithm keys in on the fact that many different kinds of dust absorb blue wavelengths of light more than the longer visible wavelengths. It uses this information to create an RGB composite where dust appears pastel pink, clouds and snow appear blueish and bare ground appears green. Of course, other features can absorb blue light as well, like the lakes near the northeast corner of the animation that show up as pastel pink. But, depending on your visual preferences and ability to distinguish color, the Blue Light Dust product gives another alternative to the hot pink of the EUMETSAT Dust RGB, the yellow of DEBRA, and the slightly paler tan of the True Color RGB.

One question you might ask is, “How come DEBRA shows a more vivid signal than the other methods?” In the True Color RGB, dust is slightly more pale than the background sand, because it’s made up of (generally) smaller sand particles (which are more easily lofted by the wind) that scatter light more effectively, making it appear lighter in color. In the EUMETSAT Dust RGB, dust appears hot pink because the “split window difference” (12 µm – 10.7 µm) is positive, while the difference in brightness temperatures between 10.7 µm and 8.5 µm is near zero and the background land surface is warm. In DEBRA, the intensity of the yellow is related to the confidence that dust is present in the scene based on a series of spectral tests. DEBRA is confident of the presence of dust even when the signals may be difficult to pick out in the other products, either because it’s a superior product, or because its confidence is misguided. (Hopefully, it’s the former and not the latter.)

By the way, the Takla Makan got its name from the native Uyghurs that live there. Takla Makan means “you can get in, but you can’t get out.” It has also been called the “Sea of Death.” I prefer to call it “China’s Big Bowl of Dust.” It’s a large area of sand dunes (bigger than New Mexico, but smaller than Montana) surrounded on most of its circumference by mountains between 5000 and 7000 m (~15,000-21,000+ feet!). The average annual rainfall is less than 1.5 inches (38 mm). That means when the wind blows it easily picks up the dusty surface, but that dust can’t go anywhere because it’s blocked by mountains (unless it blows to the northeast). The dust is trapped in its bowl.

The Takla Makan is also important historically, because travelers on the original Silk Road had to get around it. Notice on this map, there were two routes: one that skirted the northern edge of the Takla Makan and one that went around the southern edge. This part of Asia was the original meeting point between East and West.

CIRA produces all four imagery products over the Takla Makan desert in near-real time, which you can find here. And, in case you’re curious, you can check out how well DEBRA and the EUMETSAT Dust products compare for the dust-laden siroccos over southern Europe and northern Africa by clicking here and here (for the first event over Spain and Portugal) or here and here (for the second one over Italy and the Adriatic Sea).

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.

End of Autumn in the Alps

Much of the United States has had a below-average amount of snow this fall (and below-average precipitation for the whole year). Look at how little snow cover there was in the month of November. Parts of Europe, however, have seen snow. It’s nice to know that it’s falling somewhere. But, can you tell where?

Here is a visible image (0.6 µm) from Meteosat-9, taken 12 December 2012 (at 12:00 UTC):

Meteosat-9 visible image of central Europe, taken 12:00 UTC 12 December 2012

Meteosat-9 visible image of central Europe, taken 12:00 UTC 12 December 2012. Image courtesy EUMETSAT.

And here’s the infrared image (10.8 µm) from the same time:

Meteosat-9 IR-window image of central Europe, taken 12:00 UTC 12 December 2012

Meteosat-9 IR-window image of central Europe, taken 12:00 UTC 12 December 2012. Image courtesy EUMETSAT.

These are images provided by EUMETSAT. Can you tell where the snow is? Or what is snow and what is cloud?

Here’s a much higher resolution image from VIIRS (zoomed in the Alps), taken only 3 minutes later:

VIIRS visible image of central Europe, taken 12:03 UTC 12 December 2012

VIIRS visible image (channel I-01) of central Europe, taken 12:03 UTC 12 December 2012

Now is it easy to differentiate clouds from snow? Just changing the resolution doesn’t help that much.

This has long been a problem for satellites operating in visible to infrared wavelengths. Visible-wavelength channels detect clouds based on the fact that they are highly reflective (just like snow). Infrared (IR) channels are sensitive to the temperature of the objects they’re looking at, and detect clouds because they are usually cold (just like snow). So, it can be difficult to distinguish between the two. If you had a time lapse loop of images, you’d most likely see the clouds move, while the snow stays put (or disappears because it is melting). But, what if you only had one image? What if the clouds were anchored to the terrain and didn’t move? How would you detect snow in these cases?

EUMETSAT has developed several RGB composites to help identify snow. The Daytime Microphysics RGB (link goes to PowerPoint file) looks like this:

Meteosat-9 "Daytime Microphysics" RGB composite of central Europe, taken 12:00 UTC 12 December 2012

Meteosat-9 "Daytime Microphysics" RGB composite of central Europe, taken 12:00 UTC 12 December 2012. Image courtesy EUMETSAT.

Snow is hot pink (magenta), which shows up pretty well. Clouds are a multitude of colors based on type, particle size, optical thickness, and phase. That whole PowerPoint file linked above is designed to help you understand all the different colors.

The Daytime Microphysics RGB uses a reflectivity calculation for the 3.9 µm channel (the green channel of the RGB). Without bothering to do that calculation, I’ve replaced the reflectivity at 3.9 µm with the reflectivity at 2.25 µm (M-11) when applying this RGB product to VIIRS, and produced a similar result:

VIIRS "Daytime Microphysics" RGB composite of the Alps, taken 12:03 UTC 12 December 2012

VIIRS "Daytime Microphysics" RGB composite of the Alps, taken 12:03 UTC 12 December 2012

Except for the wavelength difference of the green channel (and minor differences between the VIIRS channels and Meteosat channels), everything else is kept the same as the official product definition. Once again, the snow is pink, in sharp contrast to the clouds and the snow-free surfaces. We won’t bother to show the Nighttime Microphysics/Fog RGB (link goes to PowerPoint file) since this is a daytime scene.

EUMETSAT has also developed a Snow RGB (link goes to PowerPoint file):

Meteosat-9 "Snow" RGB composite of central Europe, taken 12:00 UTC 12 December 2012

Meteosat-9 "Snow" RGB composite of central Europe, taken 12:00 UTC 12 December 2012. Image courtesy EUMETSAT.

This also uses the reflectivity calculated for the 3.9 µm channel. Plus, it uses a gamma correction for the blue and green channels. Is it just me, or does snow show up better in the Daytime Microphysics RGB?

If you switch out the 3.9 µm for the 2.25 µm channel again and skip the gamma correction when creating this RGB composite for VIIRS, the snow stands out a lot more:

VIIRS "Snow" RGB (with modifications as explained in the text), taken 12:03 UTC 12 December 2012

VIIRS "Snow" RGB (with modifications as explained in the text), taken 12:03 UTC 12 December 2012

Now you have snow ranging from pink to red with gray land areas, black water and pale blue to light pink clouds. This combination of channels makes snow identification easier than the official “Snow RGB”, I think.

All of this is well and good but, for my money, nothing beats what EUMETSAT calls the “natural color” RGB. I have referred to it as the “pseudo-true color“. Here’s the low-resolution EUMETSAT image:

Meteosat-9 "Natural Color" RGB of central Europe, taken 12:00 UTC 12 December 2012. Image courtesy EUMETSAT.

And the higher resolution VIIRS image:

VIIRS "Natural Color" RGB of central Europe, taken 12:03 UTC 12 December 2012

VIIRS "Natural Color" RGB composite of channels M-5, M-7 and M-10, taken 12:03 UTC 12 December 2012

The VIIRS image above uses the moderate resolution channels M-5, M-7 and M-10, although this RGB composite can be made with the high-resolution imagery channels I-01, I-02 and I-03, which basically have the same wavelengths and twice the horizontal resolution. Below is the highest resolution offered by VIIRS (cropped down slightly to reduce memory usage when plotting the data):

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 12:03 UTC 12 December 2012

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 12:03 UTC 12 December 2012

Make sure to click on the image and then on the “2594×1955” link below the banner to see the image in full resolution.

This RGB composite is easier on the eyes and easier to understand. Snow has high reflectivity in M-5 (I-01) and M-7 (I-02) but low reflectivity in M-10 (I-03) so, when combined in the RGB image, it shows up as cyan. Liquid clouds have high reflectivity in all three channels so it shows up as white (or dirty, off-white). The only source of contention is that ice clouds, if they’re thick enough, will also show up as cyan.

Except for the cyan snow and ice, the “natural color” RGB is otherwise similar to a “true color” image. Vegetation shows up green, unlike the other RGB composites where it has been gray or purple or a very yellowish green. That makes it more intuitive for the average viewer. You don’t need to read an entire guide book to understand all the colors that you’re seeing.

Compare all of these RGB composites against the single channel images at the top of the page. They all make it easier to distinguish clouds from snow, although some work better than others. Now compare the VIIRS images with the Meteosat images. Which ones look better?

(To be fair, it’s not all Meteosat’s fault. The images provided by EUMETSAT are low-resolution JPG files [which is a lossy-compression format]. The VIIRS images shown here are loss-less PNG files, which are much larger files to have to store and they require more bandwidth to display.)

As a bonus (consider it your Christmas bonus), here are a few more high-resolution “natural color” images of snow and low clouds over the Alps. These are kept at a 4:3 width-to-height ratio and a 16:9 ratio, so they make ideal desktop wallpapers.

VIIRS "natural color" composite of channels I-01, I-02 and I-03, taken 12:29 UTC 14 November 2012

VIIRS "natural color" composite of channels I-01, I-02 and I-03, taken 12:29 UTC 14 November 2012. This is an ideal desktop wallpaper for 4:3 ratio monitors.

That was the 4:3 ratio image. Here’s the 16:9 ratio image:

VIIRS "natural color" composite of channels I-01, I-02 and I-03, taken 12:29 UTC 14 November 2012

VIIRS "natural color" composite of channels I-01, I-02 and I-03, taken 12:29 UTC 14 November 2012. This is an ideal desktop wallpaper for 16:9 ratio monitors.

Enjoy the snow (or be glad you don’t have to drive in it)!