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.

Sea-effect Snow

Take a look at this image:

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

Is this picture from A) the Keweenaw Peninsula of Michigan in 1978? B) Orchard Park, New York in November 2014 (aka “Snowvember”)? or C) İnebolu, Turkey from just last week?

If you pay attention to details, you will have noticed that I credited İskender Şengör with the picture and properly surmised that the answer is C. If you don’t pay attention to details, get off my blog! The details are where all the interesting stuff happens! You’d never be able to identify small fires or calculate the speed of an aurora  or explain the unknown without paying attention to details.

If you follow the weather (or social media), you probably know about lake-effect snow. (Who can forget Snowvember?) But, have you heard of sea-effect snow?

Areas downwind of the Great Lakes get a lot more snow than areas upwind of the Lakes. I was going to explain why in great detail, but this guy saved me a lot of time and effort. (I have since been notified that much of the material in that last link was lifted from a VISIT Training Session put together by our very own Dan B. You can watch and listen to that training session here.) The physical processes that cause lake-effect snow are not limited to the Great Lakes, however. Anywhere you have a large body of relatively warm water (meaning it doesn’t freeze over) with episodes of very cold winds in the winter you get lake-effect or sea-effect snow.

When you think of the great snowbelts of the world, you probably don’t think of Turkey – but you should! Arctic air outbreaks associated with strong northerly winds blowing across the Black Sea can generate snow at the same rate as Snowvember or Snowpocalypse or Snowmageddon or any other silly name that the media can come up with that has “snow” in it (Snowbruary, Snowtergate aka Frozen-Watergate, Snowlloween, Martin Luther Snow Day, Snowco de Mayo, Snowth of July… Just remember, I coined all of these phrases if you hear them later). Plus, the Pontic Mountains provide a greater upslope enhancement than the Tug Hill Plateau in Upstate New York.

One such Arctic outbreak occurred from 7-9 January 2015, resulting in the picture above. Parts of Turkey received 2 meters (!) of snow (78 inches to Americans) in a 2-3 day period, as if you couldn’t tell from that picture or this one.

From satellites, sea-effect snow looks just like lake-effect snow. (Duh! It’s the same physical process!) Here’s a VIIRS “True Color” image of the lake-effect snow event that took place last week on the Great Lakes:

VIIRS "True Color" RGB composite, taken 19:24 UTC 7 January 2015

VIIRS “True Color” RGB composite, taken 19:24 UTC 7 January 2015.

Wait – that’s no good! We need to be able to distinguish the snow from the clouds. Let’s try that again with the “Natural Color” RGB composite:

VIIRS "Natural Color" RGB composite, taken 19:24 UTC 7 January 2015

VIIRS “Natural Color” RGB composite, taken 19:24 UTC 7 January 2015.

That’s better. Notice how the clouds are formed right over the lakes and how the clouds organize themselves into bands called “cloud streets“. The same features are visible in the sea-effect snow event over Turkey (from one day later):

VIIRS "Natural Color" RGB composite, taken 10:36 UTC 8 January 2015

VIIRS “Natural Color” RGB composite, taken 10:36 UTC 8 January 2015.

Look at how much of Turkey is covered by snow! (Most of that snow cover is from the low pressure system that passed over Turkey a couple days before the sea-effect snow machine kicked in.) And – *cough* attention to details *cough* – you can even see snow over Greece and more sea-effect snow on Crete. There’s also snow down in Syria, Lebanon and Israel (Israel is off the bottom of the image), which is bad news for Syrian refugees.The heavy snow has shut down thousands of roads, closed schools and businesses, and was even the source of a political scandal.

But, on the plus side, the Arctic outbreak in the Middle East brings a unique opportunity to see palm trees covered in snow. And, how often do you get to see the deserts of Saudi Arabia covered in snow? (EUMETSAT has provided more satellite images of this event at their Image Library.)

Take another look at that image over the Black Sea. See how the biggest snow band extends south (and curving to the southeast) from the southern tip of the Crimean Peninsula? That is an example of how topography impacts these snow events. Due to differences in friction, surface winds are slightly more backed over land than over water, therefore areas of enhanced surface convergence exist downwind of peninsulas. The snow bands are more intense in these regions of enhanced convergence. There are also bigger than normal snow bands downwind of the easternmost and westernmost tips of Crimea, and extending south from every major point along the west coast of the Black Sea. This is not a coincidence. Land-sea (or land-lake) interactions explain this. Go back and listen to the VISIT training session for more information.

Sea-effect snow affects other parts of the globe as well. It’s why the western half of Honshu (the big island of Japan) and Hokkaido are called “Snow Country“. Japan was also hit with a major sea-effect snowstorm last week and, of course, VIIRS caught it:

VIIRS "Natural Color" RGB composite, taken 03:48 UTC 8 January 2015

VIIRS “Natural Color” RGB composite, taken 03:48 UTC 8 January 2015.

See the clear skies over Korea and the cloud streets that formed over the Sea of Japan? Classic sea-effect clouds. You can even see snow all along the west coast of Honshu in between the breaks in the clouds. Topographic impacts are once again visible. Notice the intense snow band extending southeast from the southern tip of Hokkaido/northern tip of Honshu similar to the super-strength snow band off of Crimea. And there’s another one downwind of the straits between Kyushu and Shikoku. Another detail in this image you should have noticed is the impact that Jeju Island has on the winds and clouds. Those are classic von Kármán vortices which we have discussed before.

Fortunately, 8 January 2015 was near a full moon, so the Day/Night Band was able to capture a great image of these von Kármán vortices:

VIIRS Day/Night Band image, taken 18:09 UTC 7 January 2015

VIIRS Day/Night Band image, taken 18:09 UTC 7 January 2015.

So, to the people of the Great Lakes: Remember you’re not alone. There are people in Turkey and Japan who know what you go through every winter.

 

UPDATE #1: While I was aware (and now you are aware) that sea-effect snow can impact Cape Cod, it was brought to my attention that there is a sea-effect snow event going on there today (13 January 2015). Here’s what VIIRS saw:

VIIRS "Natural Color" RGB composite, taken 17:29 UTC 13 January 2015

VIIRS “Natural Color” RGB composite, taken 17:29 UTC 13 January 2015.

According to sources at the National Weather Service, some places have received 2-3 cm (~ 1 inch) of snow in a four-hour period. It’s not the same as shoveling off your roof in snow up to your neck, but it’s something!

Bárðarbunga, the Toxic Tourist Trap

Quick: what was the name of that Icelandic volcano that caused such a stir a few years ago? Oh, that’s right. You don’t remember. No one remembers. (Unless you live outside the U.S. in a place where you might have actually heard someone say the name correctly.) To Americans, it will forever be known as “That Icelandic Volcano” or “The Volcano That Nobody Can Pronounce” – even though it is possible to pronounce the name. Say it with me: Eye-a-Fiat-la-yo-could (Eyjafjallajökull).

Well, back at the end of August 2014 another volcano erupted in Iceland, and there is no excuse for not being able to pronounce this name correctly: Bárðarbunga. (OK, you have one excuse: use of the letter ð is uncommon outside of Iceland. In linguistics, ð is a “voiced dental fricative” which, in English, is a voiced “th”. “The” has a voiced “th”. “Theme” has an un-voiced “th” or, rather,  “voiceless dental non-sibilant fricative“.) Look, you don’t want to offend any Icelanders, so say it right:

“Bowr-thar-Bunga.” See, it’s easy to say. (You may see people who are afraid of the letter ð refer to the recent eruption as Holuhraun [pronounced “Ho-lu-roin”], because Bárðarbunga is part of the Holuhraun lava field. So be aware of that.)

I know what you’re going to ask: “What is so special about this volcano? I haven’t heard anything about it up to this point, so why should I care?” You haven’t heard anything about it because you don’t live in Iceland or in Europe, which is downwind of Iceland. And, why should you care? Let me count the ways in the rest of this blog post.

You probably have heard of Kīlauea (and have no trouble pronouncing that name) and the lava flow that inched its way towards the town of Pahoa. Kīlauea has been continuously erupting since 1983. Bárðarbunga erupted on 29 August 2014 and has been spewing lava ever since, which at this point, is over 100 days of non-stop erupting. It’s Iceland’s version of Kīlauea. (Hopefully, it won’t continue to erupt for another 30 years.)

Just like Kīlauea, Bárðarbunga is attracting tourists from all over the world. It seems every wannabe photographer and videographer has gone (or wants to go) to Iceland to try to come up with the next viral video showing the breathtaking lava flows. Seriously, do a search for Bardarbunga or Holuhraun on YouTube or vimeo and see how many results show up. Here’s a pretty typical example (filmed by someone from Iceland):

Want to join in the fun? Just grab your camera, head to Iceland, hire an airplane or helicopter pilot, and find the most dramatic music you can think of to go along with your footage. Watch out, though – the airspace around the volcano can be rather crowded. As this video shows, it can be hard to film the volcano without other aircraft getting in the way.

If photography is more your thing, here are the latest images of the eruption on Twitter. (Look for the pictures of Beyonce and Jay-Z. If Twitter is correct, they flew over the volcano for his birthday. Viewing the eruption has gone mainstream! You’re too late, hipsters! Good luck getting to the next volcanic eruption before it becomes cool.)

Back to the matter at hand: why you should care about Bárðarbunga. After its first 100 days of erupting, it has created a field of new lava (76 km2) that is larger than the island of Manhattan (59 km2). The volcano has been creating a toxic plume of SO2 for the last 100 days that is making it difficult to breathe. (Here are some of the known health effects of breathing SO2.) SO2 can ultimately be converted into sulfuric acid (acid rain), depending on the chemistry in the air around the volcano. And while it may not be producing as much ash as Eyjafjallajökull did, VIIRS imagery shows it is producing ash, which is a threat to aircraft.

If you follow this blog, you know the best RGB composite for detecting ash is the True Color composite. This is because the visible wavelength channels that make the composite are sensitive to the scattering of light by small particles, like dust, smoke and ash. Iceland is a pretty cloudy place, so it’s not always easy to spot the ash plume, so here it is at its most visible:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 12:57 UTC 11 September 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 12:57 UTC 11 September 2014. The red arrow points to the location of Bárðarbunga.

Click on the image (or any other image) to see the full resolution version. The red arrow shows the location of Bárðarbunga. In case you’re wondering, the borders drawn inside the island are IDL’s knowledge of the boundaries of lakes and glaciers (jökull in Icelandic). The big one just south of the red arrow is Vatnajökull – the largest glacier in Europe and one of three national parks in Iceland. (If you want to go there, be aware of closures due to volcanic activity.)

See the ash plume extending from the red arrow to the east-northeast out over the Atlantic Ocean? Now, try to find the ash plume in this animation of True Color images from 29 August to 14 October 2014:

Animation of VIIRS True Color images of Iceland 29 August - 14 October 2014

Animation of VIIRS True Color images of Iceland 29 August – 14 October 2014

As with most of my animations, I have selectively removed images where it was too cloudy to see anything. Sometimes, the steam from the volcano mixes with the ash to make its own clouds, much like a pyrocumulus. Watch for the ash to get blown to the northwest and then southwest in early October. In case you can’t see it, here’s a static example:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 12:15 UTC 10 October 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 12:15 UTC 10 October 2014. The red arrow shows the location of Reykjavik.

This time, the red arrow shows Reykjavik, the nation’s capitol and likely only city in Iceland you’ve heard of. The ash plume is pretty much right over Reykjavik!

Over the course of the first 100 days, no place in Iceland has been kept safe from the ash plume. But, that’s not the only threat from Bárðarbunga: I also mentioned SO2. If you recall from our look at Copahue (Co-pa-hway – say it right!) the EUMETSAT Dust algorithm is sensitive to SO2. So, can we detect the toxic sulfur dioxide plume from Bárðarbunga? Of course! But, it does depend on cloudiness and just how much (and how high) SO2 is being pumped into the atmosphere.

If you read my post on Copahue, you should have no trouble picking out the sulfur dioxide plume in this image of Bárðarbunga:

EUMETSAT Dust RGB composite applied to VIIRS, 12:57 UTC 11 September 2014

EUMETSAT Dust RGB composite applied to VIIRS, 12:57 UTC 11 September 2014

This image is from the same time as the first True Color image above, when the plume was very easy to see. Also note the large quantity of contrails (aka “chemtrails” to the easily misled). Those are the linear black streaks west of Iceland. If you’re confident in your ability to see the sulfur dioxide, see how often you can pick it out in this animation:

Animation of EUMETSAT Dust RGB images from VIIRS (29 August - 10 October 2014)

Animation of EUMETSAT Dust RGB images from VIIRS (29 August – 10 October 2014)

Some detail is lost because an RGB composite may contain as many as 16 million colors, while the .gif image standard only allows 256. But, you can still see the pastel-colored SO2 plume, which almost looks greenish under certain conditions due to interactions with clouds. Also note the volcano itself appears cyan – the hottest part of the image has a cool color! Unusual in a composite that makes almost everything appear red or pink.

If you want to see the volcano look more like a hot spot, here are animations of the shortwave IR (M-13, 4.0 µm) and the Fire Temperature RGB composite (which I promote whenever I can). I should preface these animations by saying I have not removed excessively cloudy images but, at least 80% of the days have two VIIRS afternoon overpasses and, to reduce filesizes, I have kept only one image per day:

Animation of VIIRS M-13 images of Iceland (29 August - 15 October 2014)

Animation of VIIRS M-13 images of Iceland (29 August – 15 October 2014)

The Fire Temperature RGB is made up of M-10 (1.6 µm; blue), M-11 (2.25 µm; green) and M-12 (3.7 µm; red):

Animation of VIIRS Fire Temperature RGB images of Iceland (29 August - 15 October 2014)

Animation of VIIRS Fire Temperature RGB images of Iceland (29 August – 15 October 2014)

No surprise, molten rock is quite hot! That area of lava has saturated my color table for M-13 and it saturated the Fire Temperature RGB. As I’ve said before, only the hottest fires show up white in the Fire Temperature RGB and lava is among the hottest things you’ll see with VIIRS. Sometimes, you can see the heat from the volcano through clouds (and certainly through the ash plume)! It’s also neat to watch the river of lava extend out to the northeast and then cool.

To quantify it a bit more, the first day VIIRS was able to see the hot spot of Bárðarbunga (31 August 2014), the M-13 brightness temperature was the highest I’ve seen yet: 631.99 K. The other midwave-IR channels (M-12 and I-4; 3.7 and 3.74 µm, respectively) saturate at 368 K. The Little Bear Fire (2012) peaked at 588 K and that fire was hot enough to show up in M-10 (1.6 µm) during the day, so it’s no wonder that we’ve saturated the Fire Temperature RGB.

There’s one more interesting way to look at Bárðarbunga using a new RGB composite. When I was first tipped to this event, I saw this image from NASA, which you can read more about here. That image was taken by the Operational Land Imager (OLI) from Landsat-8 and is a combination of “green, near-infrared and shortwave infrared” channels. Applying this to VIIRS, that combination becomes M-4 (0.55 µm), M-7 (0.87 µm) and M-11 (2.25 µm), which is similar to the Natural Color composite (M-5, 0.64 µm; M-7, 0.87 µm; M-10, 1.61 µm) except for a few notable differences. M-4 is more sensitive to smoke and ash and vegetation than M-5. And M-11 is more sensitive to fires and other hotspots than M-10.

The differences are subtle, but you can see them in this direct comparison:

Comparison between VIIRS "Natural Color" and "False Color with Shortwave IR" RGB composites (12:38 UTC 14 October 2014)

Comparison between VIIRS “Natural Color” and “False Color with Shortwave IR” RGB composites (12:38 UTC 14 October 2014)

NASA calls this RGB composite “False Color with Shortwave Infrared,” although I’m sure there has to be a better name. Any suggestions?

Most of my images and loops have come from the first 45 days after eruption. This was a very active period for the volcano, and is where most of the previously mentioned videos came from. (And trust me, you and your browser couldn’t handle the massive animations that would have resulted from using all 100+ days of images.) To prove Bárðarbunga has gone on beyond that, here’s one of the new RGB composites from 17 November 2014:

VIIRS false color RGB composite of channels M-4, M-7 and M-11, taken 13:42 UTC 17 November 2014

VIIRS false color RGB composite of channels M-4, M-7 and M-11, taken 13:42 UTC 17 November 2014

This image really makes Iceland look like a land of fire and ice, which is exactly what it is!

When China Looks Like Canada

OK, so there probably aren’t any “Canadatowns” in China like there are Chinatowns in Canada. (Now you’re probably wondering what a Canadatown in China would look like. Maybe stores and restaurants selling poutine and maple syrup? Hockey rinks and curling sheets everywhere? A Tim Hortons on every street corner?) But this isn’t about that!

Last time I made the comparison between Canada and China, it was because there were numerous fires, particularly in the Northwest Territories, that produced so much smoke that it choked the air, making it difficult to breathe. This smoke was visible all the way down to the Lower 48 United States. These huge smoke plumes looked a lot like Chinese super-smog. Today, we’re talking not about the smoke and smog… well, actually, smoke and smog will be mentioned… hmm. Uh, what I mean is we’re focusing on the zillions of fires that VIIRS saw over Manchuria – just like the zillions of fires in the Northwest Territories. Well, OK, not “just like” – those fires were caused by Mother Nature. These fires appear to be intentionally set by human beings and are much smaller.

A CIRA colleague was checking out a real-time loop of MTSAT 3.75 µm imagery over northeastern China and reported seeing bright spots (which are typically hot spots from fires) throughout the area for most of the last month. So what is going on there?

MTSAT has ~4 km spatial resolution, so it’s not the best for fire detection. (At the time of this writing, CIRA has access to MTSAT-2, aka Himawari-7, which has 4 km spatial resolution in the infrared channels. The Advanced Himawari Imager {AHI} was successfully launched on Himawari-8 on 7 October 2014 and, when the operational imagery becomes available, it will have 2 km resolution in this channel [and it will have many of the channels that VIIRS has]. CIRA has plans to acquire this data when it becomes available. Until then, you’ll have to deal with coarse spatial resolution.) To really see what is going on, you need the spatial resolution of VIIRS.

Of course, spatial resolution is not the only thing you need. Check out the VIIRS M-13 (4.0 µm)  image below from 04:48 UTC 18 November 2014. How many hot spots can you see?

VIIRS M-13 image of northeastern China, taken 04:48 UTC 18 November 2014

VIIRS M-13 image of northeastern China, taken 04:48 UTC 18 November 2014.

This image uses a color table specifically designed to highlight hot spots from fires. Any pixel above 317 K (44 °C or 111 °F) is colored. (As always, click on the image to see it in full resolution.) There aren’t that many colored pixels, even though we’re using a relatively low temperature threshold for fire detection. There are, however, a lot of nearly black pixels, which means they are warmer than the background, but not warm enough to be highlighted. (In case you’re not sure, I’m talking about the area between 45° and 48°N, 123° and 128°E.) If we used this temperature threshold in a summer scene, there would be a lot false alarm fire detections.

A situation like this is when the Fire Temperature RGB composite comes in handy. It can detect the small (or low temperature) fires with no problem, particularly since the background isn’t very warm. Try to count up all the red pixels in this image from the same time:

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12, taken 04:48 UTC 18 November 2014

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12, taken 04:48 UTC 18 November 2014.

That’s a lot of fires! It’s probably because there are so many of them that they were visible in MTSAT. If you look closely at the full resolution image, there are two significant fires in North Korea, plus many more smaller fires/hot spots northwest and north of the Yellow Sea. Go back and compare the Fire Temperature RGB with the M-13 image. Admit it: fires in this scene are easier to see in the RGB composite.

If you don’t believe me, check out the M-13 and Fire Temperature RGB images that have been zoomed in on main concentration of fires. The Fire Temperature RGB has been lightened a little bit and the M-13 image has been darkened a little bit to highlight the hot spots better.

VIIRS M-13 image (as above) but zoomed in and slightly darkened

VIIRS M-13 image (as above) but zoomed in and slightly darkened.

VIIRS Fire Temperature RGB image (as above) but zoomed in and lightened slightly

VIIRS Fire Temperature RGB image (as above) but zoomed in and lightened slightly.

If you want to know why the Fire Temperature RGB composite works, go back and read this and this. Otherwise, stay put. If you’re familiar with the Fire Temperature RGB, because you are a loyal follower of this blog, you may be wondering why the overall image looks so dark.

All the previous cases where I’ve shown this RGB have been in the summer, typically under bright sunlight (since fires don’t tend to occur in winter). Here, it’s almost winter so there is less sunlight and the background surface is colder, which are going to make the image appear darker. Plus, there is some snow in the scene and snow appears black in this RGB composite. It’s not reflective at 1.61 µm (blue component) or 2.25 µm (green component) or at 3.74 µm (red component), plus it’s cold so it doesn’t emit much radiation at any of these wavelengths either.

The Natural Color RGB shows where the snow is. Look for the cyan signature of snow and ice here:

VIIRS Natural Color RGB composite of channels M-5, M-7, and M-10, taken 04:48 UTC 18 November 2014

VIIRS Natural Color RGB composite of channels M-5, M-7, and M-10, taken 04:48 UTC 18 November 2014.

The Natural Color RGB shows that the fires are occurring in an area with a lot of lakes. Also, there isn’t a very strong green signature from vegetation in this area. So what is burning? Your guess is as good as mine. (Unless your guess is a bunch of Chinese children using magnifying glasses to burn ants. That’s not a very good guess – particularly because, as I said, there is less sunlight in the winter and it’s colder so the ants wouldn’t ignite easily. Also, that’s a cruel thing to suggest and my reasoned account of why that wouldn’t work should not be taken as an implicit admission that I ever did such a thing as a kid.)

A quick perusal of Google Maps reveals that it is an area full of agricultural fields. So my guess is that it’s some sort of end-of-year burning of agricultural waste. They are all small or low temperature fires and they’re not anything that made the news (I checked), so it’s doubtful that it’s a zillion uncontrolled fires.

How do we even know they’re fires? Besides the fact that they show up in the Fire Temperature RGB, we can also see the smoke. Check out this True Color RGB image and focus on the area where the majority of the fires are occurring:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken at 04:48 UTC 18 November 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken at 04:48 UTC 18 November 2014.

There are visible smoke plumes right where the greatest concentration of hot spots is located. There is also a long plume of gray along the base of the Changbai Mountains stretching southwest to the shores of the Yellow Sea, but it’s not clear if that is also smoke or simply smog. By the way, if you have respiratory ailments, don’t look at the southwest corner of the image (west of the Yellow Sea) because that’s definitely smog! The northern extent of that large area of smog is the Beijing metropolitan area.

What is most cough- and barf- inducing about that smog near Beijing is that it is thick enough to completely obscure the view of the surface. Last time we looked at that, it was record levels of smog that was receiving international attention. The thick, surface obscuring smog you see here isn’t record breaking or news-worthy – it’s simply a normal late fall day in eastern China!

If you can’t think of anything else to be thankful for on Thursday, you can be thankful that you don’t have to breathe air like that. Unless you live there. But, then, you wouldn’t be celebrating Thanksgiving anyway. And, if you live in Canada, you already had your Thanksgiving. You get to just sit back, relax, and watch Americans trample each other to death for discount electronics. Being able to avoid the Black Friday mob is something to be truly thankful for!