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.

UHF/VHF

Take a second to think about what would happen if Florida was hit by four hurricanes in one month.

Would the news media get talking heads from both sides to argue whether or not global warming is real by yelling at each other until they have to cut to a commercial? Would Jim Cantore lose his mind and say “I don’t need to keep standing out here in this stuff- I quit!”? Would we all lose our minds? Would our economy collapse? (1: yes. 2: every man has his breaking point. 3: maybe not “all”. 4: everybody panic! AHHH!)

It doesn’t have to just be Florida. It could be four tropical cyclones making landfall anywhere in the CONUS (and, maybe, Hawaii) in a 1-month period. The impact would be massive. But, what about Alaska?

Of course, Alaska doesn’t get “tropical cyclones” – it’s too far from the tropics. But, Alaska does get monster storms that are just as strong that may be the remnants of tropical cyclones that undergo “extratropical transition“. Or, they may be mid-latitude cyclones or “Polar lows” that undergo rapid cyclogenesis. When they are as strong as a hurricane, forecasters call them “hurricance force” (HF) lows. And guess what? Alaska has been hit by four HF lows in a 1-month period (12 December 2015 – 6 January 2016).

With very-many HF lows, some of which were ultra-strong, we might call them VHF or UHF lows. (Although, we must be careful not to confuse them with the old VHF and UHF TV channels, or the Weird Al movie.) In that case, let’s just refer to them as HF, shall we?

The first of these HF storms was a doozy – tying the record for lowest pressure ever in the North Pacific along with the remnants of Typhoon Nuri. Peak winds with system reached 122 mph (106 kt; 196 k hr-1; 54 m s-1) in Adak, which is equivalent to a Category 2 hurricane!

Since Alaska is far enough north, polar orbiting satellites like Suomi-NPP provide more than 2 overpasses per day. Here’s an animation from the VIIRS Day/Night Band, one of the instruments on Suomi-NPP:

Animation of VIIRS Day/Night Band images of the Aleutian Islands (12-14 December 2015)

Animation of VIIRS Day/Night Band images of the Aleutian Islands (12-14 December 2015).

It’s almost like a geostationary satellite! (Not quite, as I’ll show later.) This is the view you get with just 4 images per day. (The further north you go, the more passes you get. The Interior of Alaska gets 6-8 passes, while the North Pole itself gets all 15.) Seeing the system wrap up into a symmetric circulation would be a thing of beauty, if it weren’t so destructive. Keep in mind that places like Adak are remote enough as it is. When a storm like this comes along, they are completely isolated from the rest of Alaska!

Here’s the same animation for the high-resolution longwave infrared (IR) band (I-5, 11.5 µm):

Animation of VIIRS I-5 images of the Aleutian Islands (12-14 December 2015)

Animation of VIIRS I-5 images of the Aleutian Islands (12-14 December 2015).

I’ve mentioned Himawari before on this blog. Well, Himawari’s field of view includes the Aleutian Islands. Would you like to see how this storm evolved with 10 minute temporal resolution? Of course you would.

Here is CIRA’s Himawari Geocolor product for this storm:

Here is a loop of the full disk RGB Airmass product applied to Himawari. Look for the storm moving northeast from Japan and then rapidly wrapping up near the edge of the Earth. This is an example of something you can’t do with VIIRS, because VIIRS does not have any detectors sensitive to the 6-7 µm water vapor absorption band, which is one of the components of the RGB Airmass product. The RGB Airmass and Geocolor products are very popular with forecasters, but they’re too complicated to go into here. You can read up on the RGB Airmass product here, or visit my collegue D. Bikos’ blog to find out more about this storm and these products.

You might be asking how we know what the central pressure was in this storm. After all, there aren’t many weather observation sites in this part of the world. The truth is that it was estimated (in the same way the remnants of Typhoon Nuri were estimated) using the methodology outlined in this paper. I’d recommend reading that paper, since it’s how places like the Ocean Prediction Center at the National Weather Service estimate mid-latitude storm intensity when there are no surface observations. I’ll be using their terminology for the rest of this discussion.

Less than 1 week after the first HF storm hit the Aleutians, a second one hit. Unfortunately, this storm underwent rapid intensification in the ~12 hour period where there were no VIIRS passes. Here’s what Storm #2 looked like in the longwave IR according to Himawari. And here’s what it looked like at full maturity according to VIIRS:

VIIRS DNB image (23:17 UTC 18 December 2015)

VIIRS DNB image (23:17 UTC 18 December 2015).

VIIRS I-5 image (23:17 UTC 18 December 2015)

VIIRS I-5 image (23:17 UTC 18 December 2015).

Notice that this storm is much more elongated than the first one. Winds with this one were only in the 60-80 mph range, making it a weak Category 1 HF low.

Storm #3 hit southwest Alaska just before New Year’s, right at the same time the Midwest was flooding. This one brought 90 mph winds, making it a strong Category 1 HF low. This one is bit difficult to identify in the Day/Night Band. I mean, how many different swirls can you see in this image?

VIIRS DNB image (13:00 UTC 30 December 2015)

VIIRS DNB image (13:00 UTC 30 December 2015).

(NOTE: This was the only storm of the 4 to happen when there was moonlight available to the DNB, which is why the clouds appear so bright. The rest of the storms were illuminated by the sun during the short days and by airglow during the long nights.) The one to focus on is the one of the three big swirls closest to the center of the image (just above and right of center). It shows up a little better in the IR:

VIIRS I-5 image (13:00 UTC 30 December 2015)

VIIRS I-5 image (13:00 UTC 30 December 2015).

The colder (brighter/colored) cloud tops are the clue that this is the strongest storm, since all three have similar brightness (reflectivity) in the Day/Night Band. If you look close, you’ll also notice that this storm was peaking in intensity (reaching mature stage) right as it was making landfall along the southwest coast of Alaska.

Storm #4 hit the Aleutians on 6-7 January 2016 (one week later), and was another symmetric/circular circulation. This storm brought winds of 94 mph (2 mph short of Category 2!) The Ocean Prediction Center made this animation of its development as seen by the Himawari RGB Airmass product. Or, if you prefer the Geocolor view, here’s Storm #4 reaching mature stage. But, this is a VIIRS blog. So, what did VIIRS see? The same storm at higher spatial resolution and lower temporal resolution:

Animation of VIIRS DNB images of the Aleutian Islands (6-7 January 2016)

Animation of VIIRS DNB images of the Aleutian Islands (6-7 January 2016).

Animation of VIIRS I-5 images of the Aleutian Islands (6-7 January 2016)

Animation of VIIRS I-5 images of the Aleutian Islands (6-7 January 2016).

This storm elongated as it filled in and then retrograded to the west over Siberia. There aren’t many hurricanes that do that after heading northeast!

So, there you have it: 4 HF lows hitting Alaska in less than 1 month, with no reports of fatalities (that I could find) and only some structural damage. Think that would happen in Florida?

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.

Sehr Schweres Unwetter in NRW

Not having full command of the German language, “sehr schweres Unwetter” seems like an understatement. It translates as “very bad thunderstorm,” which in this case is like calling the Titanic a “very big boat”. Of course, if you live in the Great Plains, you probably refer to a supercell thunderstorm as “a little bit of rain and wind” but the storms that hit Nordrhein-Westfalen (NRW) on 9-10 June 2014 rival anything the toughest Oklahoman has experienced (minus the tornadoes). Also, keep in mind that Germany and the Low Countries have nowhere near the wide-open spaces the U.S. Great Plains are known for. Take 5 times the population of Oklahoma and cram them into a land area the size of Maryland. (Or, if you’re from Maryland, multiply your state’s population by three to approximate the population density of the area we’re talking about. Then ponder how anyone in that part of Germany is able to spend less than 18 hours per day stuck in traffic like you would be if you were suddenly surrounded by three times as many people.)

Let me set the scene for you. (If you’ve ever lived in the Midwest, you know the drill.) The air is hot and unbelievably humid. The sky is overcast. There is no wind to speak of, but there is a certain “electricity” in the air that tells you that a violent end to the heatwave is coming. Off in the distance, clouds lower and darken. A gentle rumbling of thunder slowly builds as the storm approaches. Lightning appears and becomes ever more frequent. Right before the storm hits, the winds pick up out of nowhere and… Wait! I don’t need to describe it. I can show it to you:

http://www.youtube.com/watch?v=TFbsubhW5s0

http://www.youtube.com/watch?v=9sLfWkqoIq8

EDIT: I did need to describe it, because the videos are no longer available. If you weren’t able to see the videos before they were removed, they showed scary looking clouds and nearly constant lightning approaching Bochum. In fact, there were an estimated 113,000 lightning strikes across Germany from the storm.

Germany is, apparently, a land of iPhones and GoPros and all sorts of video recording equipment, and there is no shortage of video of the storm. There are videos of the storm approaching from different perspectives (here, here and here), the strong winds and heavy rains that are more reminiscent of a tropical storm (here, here and here), footage of the lightning in slow-motion and, because this is the Internet, a 30 min. montage of storm footage set to salsa music (although one commenter says the first footage is from a storm in 2010).

The aftermath is pretty impressive also – trees and large branches down everywhere blocking roads, crushing cars and stopping the never-late German train system. In fact, 6 people were killed – mostly by falling trees. Winds were observed in the 140-150 km h-1 range (approximately 85-90 miles per hour), which puts it just below a Category 2 hurricane according to the Saffir-Simpson scale. There were even reports of baseball sized hail, something that’s not unusual in Oklahoma, but is very rare in Europe. (Here is some pretty big hail in the town of Zülpich from earlier in the day.)

Now that you’ve used up the last 90 minutes looking at YouTube videos, let’s get down to business. What do satellites tell us about this storm?

EUMETSAT put together this animation of images from the geostationary satellite Meteosat-10:

Watch that video again, preferably in fullscreen mode. First, the white boxes highlight the supercell thunderstorms over Europe between 01:00 UTC 9 June 2014 and 08:15 UTC 10 June 2014. Right before sunset on 9 June, you can see a storm moving north out of France into Belgium that seems to explode as it heads towards the Netherlands and western Germany. This is our “schweres Unwetter”. The second thing to notice is where that storm is at 02:00 UTC on the 10th. That was the time that VIIRS passed overhead.

So, without any more bloviating, here’s the high-resolution infrared (I-5) image from VIIRS:

VIIRS I-5 image from 02:07 UTC 10 June 2014

VIIRS I-5 image of severe thunderstorms over Europe from 02:07 UTC 10 June 2014

The storm that caused all the damage over Nordrhein-Westfalen has weakened and is now over northeastern Germany on its way to Poland. But, a second impressive supercell complex is pounding Belgium and the Netherlands, and taking aim at western Germany once again.

The coldest pixels are 196.5 K (-76.7 °C or -106 °F) in the storm over Benelux and 198.7 K (-74.5 °C or -102.1 °F) in the storm over northeast Germany. Another impressive thing about these storms is their size relative to the size of these countries. That Benelux storm looks like it’s at least five times the size of Luxembourg and as big as Belgium! (And I’m not counting the area of the anvil, which is even larger. I’m only counting the area containing overshooting tops.)

Since it’s nighttime, what did the Day/Night Band see? Well, the answer depends on how you display the data. You see, we’re approaching the Summer Solstice in the Northern Hemisphere, where the days are long and twilight encroaches the nighttime overpasses at these latitudes. If you try to scale the radiances from lowest = black to highest = white, you get something like this:

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014. Radiance values are displayed and scaled according to text above.

That’s not very helpful because the radiance values vary by 6 orders of magnitude across the scene and we only have 256 colors to work with to relay that information. But, we can take advantage of the fact that the Day/Night Band radiance values are, to the first order, a function of the solar and lunar zenith angles, and use this as the basis for a “dynamic scaling” that compares the observed radiance with an expected maximum and minimum radiance value that is a function of those angles. (In case you’re interested, the dynamic scaling algorithm used here is based around the error function.) This allows you to produce something like this:

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014. This image uses dynamic scaling as described in the text.

Here, we’ve lost some quantitative information (colors no longer represent specific radiance values) but we’ve gained valuable qualitative information.  Now we can see where the storms are! Notice the shadows in the overshooting tops of our Benelux storm – right where the coldest pixels are in the infrared image. We can see some of the city lights, but not others, because the twilight encroaching from the northeast is brighter than the cities in that part of the image. (It is easy to pick out London and Paris, though.) If you read the previous post, you might be wondering why there are no mesospheric waves with these storms. That’s because there is too much twilight (and moonlight) to see the airglow. (There’s also the possibility that the stratosphere and mesosphere weren’t conducive for vertically propagating waves, but you wouldn’t be able to tell that under these lighting conditions.)

Some people like to combine the infrared with the Day/Night Band into a single image. This is done by changing the opacity of one of the images and overlaying it on the other. Here’s an example of what that looks like using the dynamically scaled Day/Night Band image:

VIIRS combined IR/DNB image from 02:07 UTC 10 June 2014

VIIRS combined IR/DNB image from 02:07 UTC 10 June 2014

The light/shadow effect of the visible information adds a sort-of 3-D effect to the infrared images and, since this is the Day/Night Band, it can show where the storms are in relation to the urban areas. Here, it seems to work better for the Benelux storm than it does for the other one. (Of course, it would be better without the twilight. And, it works best with a full moon, which occurred three days later.)

Of course, if you have access to the Near Constant Contrast imagery, you don’t have to worry about scaling. The imagery is useful as-is:

VIIRS NCC image, taken at 02:07 UTC 10 June 2014

VIIRS NCC image, taken at 02:07 UTC 10 June 2014

And the combined IR/NCC image looks like this:

Combined IR/NCC image from 02:07 UTC 10 June 2014

Combined IR/NCC image from 02:07 UTC 10 June 2014

In case you’re interested, there are additional videos, animations and images of these storms from the Meteosat High Resolution Visible (HRV) channel at the EUMETSAT Image Library.