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!

Hell Froze Over (and the Great Lakes, too)

This has been some kind of winter. The media has focused a lot of attention on the super-scary “Polar Vortex” even though it isn’t that scary or that rare. (I wonder if Hollywood will make it the subject of the next big horror movie in time for Halloween.) Many parts of Alaska have been warmer than Georgia, with Lake Clark National Park tying the all-time Alaskan record high temperature for January (62 °F) on 27 January 2014. (Atlanta’s high on that date was only 58 °F.) Sacramento, California broke their all-time January record high temperature, reaching 79 °F three days earlier. In fact, many parts of California had record warmth in January, while everyone on the East Coast was much colder than average. Reading this article made me think of an old joke about statisticians: a statistician is someone who would say: if your feet are stuck in a freezer and your head is stuck in the oven, you are, on average, quite comfortable.

One consequence of the cold air in the eastern United States is that Hell froze over. No, not the Gates of Hell in Turkmenistan. This time I’m talking about Hell, Michigan. Hell is a nice, little town whose residents never get tired of people telling that joke.

It has been so cold in the region around Hell that the Great Lakes are approaching a record for highest percentage of surface area covered by ice. This article mentions some of the benefits of having ice-covered Lakes, including: less lake-effect snow, more sunshine and less evaporation from the Lakes, which would keep lake levels from dropping. Although, that is at the cost of getting ships stuck in the ice, and reducing the temperature-moderating effects of the Lakes, which allows for colder temperatures on their leeward side.

This article (and many other articles I found) uses MODIS “True Color” images to highlight the extent of the ice. Why don’t they show any VIIRS images? Well, I’m here to rectify that.

First off, I can copy all those MODIS images and show the “True Color” RGB composite from VIIRS:

VIIRS "True Color" RGB composite of channels M-3, M-4 and M-5, taken 17:27 UTC 11 February 2014

VIIRS "True Color" RGB composite of channels M-3, M-4 and M-5, taken 17:27 UTC 11 February 2014

While it was a rare, sunny winter day for most of the Great Lakes region on 11 February 2014, it’s hard to tell that from the True Color imagery. I mean, look at this True Color MODIS image shown on NPR’s website. Can you tell what is ice and what is clouds?

There are ways of distinguishing ice from clouds, which I have talked about before but, it doesn’t hurt to look at these methods again and see how well they do here. First, let’s look at my modification of the EUMETSAT “Snow” RGB composite:

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 17:27 UTC 11 February 2014

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 17:27 UTC 11 February 2014

This “Snow” RGB composite differs by using reflectances at 2.25 µm in the place of the 3.9 µm channel that EUMETSAT uses. (Their satellite doesn’t have a 2.25 µm channel.) It’s easy to see where the clouds are now. Of course, now the snow and ice appear hot pink, which you may not find aesthetically pleasing. And it certainly isn’t reminiscent of snow and ice.

If you don’t like the “Snow” RGB, you may like the “Natural Color” RGB composite:

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 17:27 UTC 11 February 2014

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 17:27 UTC 11 February 2014

This has the benefit of making snow appear a cool cyan color, and has the added benefit that you can use the high-resolution imagery bands (I-01, I-02 and I-03) to create it. There is twice the resolution in this image than in the Snow and True Color RGB images. Here’s another benefit you may not have noticed right away: the clouds, while still white, appear to be slightly more transparent in the Natural Color RGB. This makes it a bit easier to see the edge of the ice on the east side of Lake Michigan and the center of Lake Huron, for example.

If you’re curious as to how much ice is covering the lakes, here are the numbers put out by the Great Lakes Environmental Research Laboratory (which is about a 25 minute drive from Hell) from an article dated 13 February 2014:

Lake Erie: 96%; Lake Huron: 95%; Lake Michigan: 80%; Lake Ontario: 32% and Lake Superior: 95%. This gives an overall average of 88%, up from 80% the week before. The record is 95% set in 1979, although it should be said satellite measurements of ice on the Great Lakes only date back to 1973.

Why does Lake Ontario have such a low percentage? That last article states, “Lake Ontario has a smaller surface area compared to its depth, so it loses heat more slowly. It’s like putting coffee in a tall, narrow mug instead of a short, wide one. The taller cup keeps the coffee warmer.”  Doesn’t heat escape from the sides of a mug as well as the top? And isn’t Lake Superior deeper than Lake Ontario? Another theory is that “Lake Ontario’s depth and the churning caused by Niagara Falls means that it needs long stretches of exceptionally cold weather to freeze.”  Does Niagara Falls really have that much of an impact on the whole lake?

So, what is the correct explanation? I’m sorry, VIIRS can’t answer that. It can only answer “How Much?” It can’t answer “Why?”

 

BONUS UPDATE (17 February 2014):

It has come to my attention that the very next orbit provided better images of the Great Lakes, since they were no longer right at the edge of the swath. Here, then, are the True Color, Snow and Natural Color RGB composite images from 19:07 UTC, 11 February 2014:

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 19:07 UTC 11 February 2014

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 19:07 UTC 11 February 2014

 

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 19:07 UTC 11 February 2014

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 19:07 UTC 11 February 2014

 

VIIRS "Natural Color" composite of channels I-01, I-02, and I-03, taken 19:07 UTC 11 February 2014

VIIRS "Natural Color" composite of channels I-01, I-02, and I-03, taken 19:07 UTC 11 February 2014

 

UPDATE #2 (18 March 2014): The Great Lakes ice cover peaked at 92.2% on 6 March 2014, just short of the all-time record in the satellite era. March 6th also happened to be a clear day over the Great Lakes, and VIIRS captured these images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 18:35 UTC 6 March 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 18:35 UTC 6 March 2014

 

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 18:35 UTC 6 March 2014

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 18:35 UTC 6 March 2014