Chinese Super-Smog

No, not a Super-Smörg, super smog. Smog that is so thick, you can taste it. The smog in many parts of eastern China has been so bad this winter, it is literally “off-the-charts“. Based on our Environmental Protection Agency‘s not-very-intuitive Air Quality Index (see pages 13-16, in particular) any value above 300 is hazardous to everyone’s health. The scale doesn’t even go above 500 because the expectation is that the air could never get that polluted. Applying this scale to the air in Beijing, the local U.S. Embassy reported an Air Quality Index value of 755 on 13 January 2013. Visibility has been reduced to 100 m at times. This video (from 31 January 2013) gives a vivid description of the problems of the smog:

If that wasn’t bad enough, here’s video from NBC News where Brian Williams reveals a factory was on fire for three hours before anyone noticed because the smog was so thick!

Did you happen to notice in the beginning of the NBC video that the “air pollution is so bad that the thick smog can now be seen from space”? Of course, the satellite image shown in that clip came from MODIS. (It must have friends in high places. That, or people get the MODIS images out on their blogs less than two weeks after the event occurred, unlike this blog.) Needless to say, VIIRS has seen the smog, too, and it is terrible.

For comparison purposes, here’s what a clean air day looks like over eastern China:

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 05:21 UTC 28 September 2012

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 05:21 UTC 28 September 2012

This is a “true color” composite taken 05:21 UTC 28 September 2012. (As always, click on the image, then on the “2040×1552” link below the banner to see the full resolution image.) There appears to be some air pollution in that image (look near 33° N latitude between 112° and 116° E longitude), but it’s not that noticeable.

Here’s what it looks like when Beijing is reporting record levels of air pollution (04:56 UTC 14 January 2013):

VIIRS true color RGB composite of channels M-03, M-04 and M-05, taken 04:56 UTC 14 January 2013

VIIRS true color RGB composite of channels M-03, M-04 and M-05, taken 04:56 UTC 14 January 2013

You may have heard of a “brown cloud of pollution“. Here the clouds actually appear brown thanks to all that pollution. Notice the area around Shijiazhuang – the most polluted city in China – and how brown those clouds are in comparison to the clouds on the left and right edges of the image. Then look south from Shijiazhuang to where everything south and west of the cloud bank has a dull gray color. That is all smog! It’s enough to make anyone with a respiratory condition want to cough up a lung just from seeing this.

Now, this is a complicated scene with clouds, snow, ice and smog. So, to clear things up (in a manner of speaking), here is the same image with everything labelled:

VIIRS true color RGB composite of channels M-03, M-04, and M-05, taken 04:56 UTC 14 January 2013

VIIRS true color RGB composite of channels M-03, M-04, and M-05, taken 04:56 UTC 14 January 2013

The gray smog can be seen around Beijing as well, but it pales in comparison to the rest of eastern China. Think about that! Replay the videos above and consider that might not have even been the worst smog in China at the time!

Too bad there are a lot of clouds over the area. What does it look like on a “clearer” day? (“Clearer”, of course, refers to the amount of clouds, not air pollution.) It looks worse! The image below was taken at 04:32 UTC on 26 January 2013:

VIIRS true color RGB composite of VIIRS channels M-03, M-04, and M-05, taken 04:32 UTC 26 January 2013

VIIRS true color RGB composite of VIIRS channels M-03, M-04, and M-05, taken 04:32 UTC 26 January 2013

The area covered by smog rivals the area of South Korea, which is visible on the right side of the image. (One of the reports I linked to above put the figure at 1/7th of the land area of China covered by smog around this time, which is actually a lot bigger than South Korea!) I’m just counting the smog in the image that is thick enough to completely obscure the surface. There is likely smog that isn’t as obvious (and isn’t labelled) in that image. The snow between Shijiazhuang, Tianjin and Beijing is covered by smog that isn’t quite thick enough to totally obscure it. And the large area of snow south of Tianjin is likely covered with smog. (It sure is a lot dirtier in appearance than the snow near the top of the image.)

If you don’t believe my labels, the “pseudo-true color” or “natural color” RGB composite clearly identifies the low clouds (which usually appear a dirty, off-white color even without smog), ice clouds (pale cyan) and snow (vivid cyan):

VIIRS false color RGB composite of channels M-05, M-07 and M-10 (a.k.a. "natural color"), taken 04:32 UTC 26 January 2013

VIIRS false color RGB composite of channels M-05, M-07 and M-10 (a.k.a. "natural color"), taken 04:32 UTC 26 January 2013

Notice the smog in this image. It is an unholy grayish-greenish color with a value near 70-105-93 in R-G-B color space. The “natural color” composite is made from channels M-05 (0.67 µm, blue), M-07 (0.87 µm, green) and M-10 (1.61 µm, red), which are longer wavelengths than their “true color” counterparts. Longer wavelengths mean reduced scattering by atmospheric aerosols, so the higher green value may be due to the strong surface vegetation signal in M-07 being able to penetrate through the smog. (Either that or the smog is composed of some chemical compound that has a higher reflectivity value in M-07 than in the other two channels.)

I’ve looked at the EUMETSAT Dust, Daytime Microphysics and Nighttime Microphysics/Fog RGBs, which you might think would show super-thick smog and they don’t. At least, it’s not obvious.

The EUMESAT Dust RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The EUMESAT Dust RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The Dust RGB above uses M-14 (8.55 µm), M-15 (10.7 µm) and M-16 (12.0 µm) and requires there to be a large temperature contrast between the dust (cool) and the background surface (hot). Smog almost always occurs when there is a temperature inversion (the air at the ground is colder than the air above) so the necessary temperature contrast won’t exist.

The Daytime Microphysics RGB shows the smoggy areas are a slightly different color than other cloud-free surfaces, but that color can be confused with other non-smoggy surfaces. The clouds really stand out, though:

The EUMETSAT Daytime Microphysics RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The EUMETSAT Daytime Microphysics RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

Perhaps, with a different scaling, the smog might stand out more.

The Nighttime Microphysics RGB from the night before (18:50 UTC 25 January 2013) is interesting. Notice the cloud identified by the letter “B” and the non-cloud next to it, “A”:

The EUMETSAT Nighttime Microphysics/Fog RGB applied to VIIRS, valid 18:50 UTC 25 January 2013

The EUMETSAT Nighttime Microphysics/Fog RGB applied to VIIRS, valid 18:50 UTC 25 January 2013

Now compare this with the Day/Night Band image from the same time:

VIIRS Day/Night Band image of eastern China, taken 18:50 UTC 25 January 2013

VIIRS Day/Night Band image of eastern China, taken 18:50 UTC 25 January 2013

This was a day before full moon. Thanks to the moon, clouds, snow and smog are visible in addition to the city lights. Points “A” and “B” have nearly identical brightness in the Day/Night Band, but only “B” shows up as a cloud in the Nighttime Microphysics RGB. These lighter areas around “A” and “B” are partially obscuring city lights, indicating “B” is a cloud, while “A” is smog. (If either was snow, you’d be able to see the city lights more clearly. See the lighter area northwest of Beijing, which is snow.)

Nothing sees super-smog like the true color composite, but the Day/Night Band will see it as long as there is enough moonlight. Smog as optically thick as a cloud… *hacking cough* … Yuck!

End of Autumn in the Alps

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

And the higher resolution VIIRS image:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Outback on Fire

I’m not talking about a Subaru. I’m talking about the vast expanse of sparsely-populated Australia. We’ve already seen fires in the United States, Russia and the Canary Islands. Well, they have been happening down under, too. (Is there any part of this planet not currently experiencing a drought?)

Despite the risk of getting fire fatigue (“Another post about fires?” *yawn*), we’re going to look at these fires for two reasons. First, it gives me a chance to show off the “fire tornado” video clip that has been making the rounds on the Internet:

Second, VIIRS saw the fire that produced the “fire tornado” (and a whole bunch of other fires) and it gives me a chance to show off the newly christened “Fire Temperature RGB”.

First, let’s look at the boring (yet still valuable) way of detecting fires: identifying hot spots in a 3.9 µm image. Here’s what VIIRS channel M-13 (4.0 µm) saw over Australia on 19 September 2012:

VIIRS channel M-13 image of central Australia, taken 04:34 UTC 19 September 2012

VIIRS channel M-13 image of central Australia, taken 04:34 UTC 19 September 2012

Pixels hotter than 350 K show up as black in this image. Given this information, how many fires can you see? (Hint: click on the image, then on the “3200×1536” link below the banner to see the image at full resolution. And, no, wise guy – you don’t count all the black pixels outside the boundaries of the data.)

Here’s the “pseudo-true color” RGB composite (this time made of M-05 [0.67 µm, blue], M-07 [0.87 µm, green], and M-10 [1.61 µm, red]):

False-color RGB composite of VIIRS channels M-05, M-07 and M-10, taken 04:34 UTC 19 September 2012

False-color RGB composite of VIIRS channels M-05, M-07 and M-10, taken 04:34 UTC 19 September 2012

With this RGB composite, really hot fires show up as bright red pixels. More hot spots are visible in the M-13 image than the “pseudo-true color” image because M-13 is much more sensitive to the heat from fires than M-05, M-07 and M-10 are. M-10 only picks up the signal from the hottest (or biggest) fires. M-05 and M-07 don’t pick up the heat signal at all, because the radiation from the sun, reflected off the Earth’s surface, drowns it out (which is precisely why the hot spots look red). M-13 is also better at detecting fires because it works at night, unlike these three channels.

You can make the hot spots from the smaller/less hot (lower brightness temperature) fires more visible by replacing M-10 with M-11 (2.25 µm) as the red channel in the RGB composite. M-11 is more sensitive to hot spots than M-10. If you do that, you get this image:

False-color RGB composite of VIIRS channels M-05, M-07 and M-11, taken 04:34 UTC 19 September 2012

False-color RGB composite of VIIRS channels M-05, M-07 and M-11, taken 04:34 UTC 19 September 2012

Since the previous RGB composite is often referred to as “natural color”, maybe this one should be called the “natural fire color” RGB composite. Now, most of the hot spots (not just the hottest ones) show up as red.

It should be noted that the fire complex in the grid box bounded by the 24 °S and 26 °S latitude and 128 °E and 132 °E longitude lines is where the video of the fire tornado came from. That fire is currently burning close to Uluru (a.k.a. Ayers Rock), the site where the creator beings live, according to local legend. According to an Uluru-Kata Tjuta National Park newsletter from back in July, prescribed burns were taking place in and around the park, although it’s not clear if the fires seen by VIIRS now (in September) are part of the prescribed burns.

EUMETSAT recently held a workshop on RGB satellite products, where a new RGB composite was proposed for VIIRS: the “Fire Temperature RGB”, made from M-10 (1.61 µm, blue), M-11 (2.25 µm, green) and M-12 (3.70 µm, red). Here’s what that looks like:

False-color RGB composite of VIIRS channels M-10, M-11 and M-12, taken 04:34 UTC 19 September 2012

False-color RGB composite of VIIRS channels M-10, M-11 and M-12, taken 04:34 UTC 19 September 2012

In this composite, hot spots from fires show up as yellow, orange, bright red or white, depending on how hot they are. Liquid clouds show up as light blue. Ice clouds, which are missing from this scene, typically show up as dark green. The background surface shows up as a shade of purple. Burn scars, which show up as dark brown in the “natural color” and “natural fire color” composites, show up as more of a maroon color in the “fire temperature” composite. Coincidently, maroon is the “official color” of Queensland, although it looks like most of the maroon burn scars show up in the Northern Territory.

To easily compare the different views of the fires (and make it obvious to everyone what the fires look like), here’s an animation, zoomed in on the lower left corner of each of the images above:

Animated loop of images of the fires in Australia as seen by VIIRS, 04:34 UTC 19 September 2012

Animated loop of images of the fires in Australia as seen by VIIRS, 04:34 UTC 19 September 2012

The yellow highlighted areas are where the active fires are.

Now that you’ve seen several different ways of displaying fire hot spots with VIIRS, which one do you like best?

Fires in Paradise

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Fires near the “Coldest City on Earth”

Raise your hand if you’ve only ever heard of Yakutsk because of the board game “Risk”. (If you raised your hand, you might want to look around and make sure that no-one saw you raise your hand for no reason.)  Yakutsk is actually the capital city of the Sakha Republic (a.k.a. Yakutia), which, according to Wikipedia, is the largest sub-national governing body in the world (only slightly smaller than India in terms of land area). Over 260,000 people live in Yakutsk, which has been called the “Coldest City on Earth” (with 950,000 total in Yakutia) even though, according to this article, it doesn’t sound very pleasant in the winter (or summer, for that matter). In January, the average temperature is -42 °C (-45 °F), and it isn’t very far from Oymyakon, where the lowest temperature ever recorded in a permanently inhabited location was observed (-71.2 °C or -96.2 °F). In the summer, it can make it up to +35 °C (95 °F) and legends tell of reindeer dying from choking on all the insects that cloud the air.

This summer, large areas of Siberia (including Yakutia) have been on fire. Some pictures from MODIS have already been circulating around the internet (e.g. here and here). And someone beat me to posting VIIRS images already. To make it easier to judge the size of the fires that are visible in the VIIRS Day/Night Band (DNB) image in the last link, here is a close-up with latitude and longitude lines added:

VIIRS DNB image of fires in Siberia, taken 16:25 UTC 4 August 2012

VIIRS DNB image of fires in Siberia, taken 16:25 UTC 4 August 2012

At this latitude, longitude lines are ~55 km apart. The latitude lines are ~111 km apart. So, you can see that these fires cover quite a large area. Unfortunately, you can’t see Yakutsk, which is underneath the clouds (and possibly smoke) at about 62° N, 130° E.

For comparison, here is the M-13 (4.05 µm) image from the same time. The primary purpose of M-13 is to detect wildfires. Notice how all of the hot spots (black spots) line up with all of the light sources that the DNB saw:

VIIRS channel M-13 brightness temperature image taken 16:25 UTC 4 August 2012

VIIRS channel M-13 brightness temperature image taken 16:25 UTC 4 August 2012

The visible image from earlier that day showed just how much smoke was produced by all of these fires:

Visible image of fires in Siberia from VIIRS channel M-5, taken 02:38 UTC 4 August 2012

Visible image of fires in Siberia from VIIRS channel M-5, taken 02:38 UTC 4 August 2012

Except for a few clouds near the edges of the scene, that is pretty much all smoke.

A few days later, the burn areas were easily visible with many fires still active, although not producing nearly as much smoke. RGB composites can really highlight what is going on with these fires, so let’s look at a few.

You should already be familiar with the “true color” image (M-3, 0.488 µm [blue], M-4, 0.555 µm [green] and M-5, 0.672 µm [red]):

True color image from VIIRS channels M3, M4 and M5 of fires in Siberia, taken 03:22 UTC 7 August 2012

True color image from VIIRS channels M3, M4 and M5 of fires in Siberia, taken 03:22 UTC 7 August 2012

And the “pseudo-true color” image made by combining the first three I-bands (I-01, 0.64 µm [blue], I-02, 0.865 µm [green] and I-03, 1.61 µm [red]):

False color (or "pseudo-true color") image of fires in Siberia from VIIRS channels I-01, I-02 and I03, taken 03:22 UTC 7 August 2012

False color (or "pseudo-true color") image of fires in Siberia from VIIRS channels I-01, I-02 and I03, taken 03:22 UTC 7 August 2012

The “pseudo-true color” image may be referred to as “natural color” depending on who you talk to. It should be noted that these last two images were kept at the native resolution of VIIRS with no re-mapping or re-sizing the image. There is only cropping to keep the file sizes manageable.

As discussed before, the pseudo-true color composite has the advantage of easily distinguishing ice and snow from liquid clouds, and it is really sensitive to vegetation. Plus, scattering by molecules in the atmosphere is greatly reduced, so you don’t have to do any atmospheric correction to produce a nice image. There is also the advantage that it uses I-bands, which have twice the resolution of the M-bands. But, that advantage was almost always neutralized by the fact that the images would have to be compressed to create a reasonable file size so that it would fit on this blog. If you click on the images above, then on the full-resolution link below the banner, you can easily compare the true resolution between the M-band image and the I-band image.

You can see here that the burn scars (all the dark brown areas) show up really well in the pseudo-true color image. (Some of the lighter or reddish brown areas are mountain ranges.) You might also notice that the active fires are still producing smoke, which shows up a lot better in the true color image. Some of the burn scars cover an area close to 60 km across.

As luck would have it (or, more accurately, the planning ahead by the scientists and engineers who designed VIIRS), channels M-5 (0.672 µm), M-7 (0.865 µm) and M-10 (1.61 µm) are very similar to the first three I-bands, so we can easily produce an M-band “pseudo-true color” image:

"Pseudo-true color" composite of VIIRS channels M-5, M-7 and M-10 of fires in Siberia, taken 03:22 UTC 7 August 2012

"Pseudo-true color" composite of VIIRS channels M-5, M-7 and M-10 of fires in Siberia, taken 03:22 UTC 7 August 2012

For reference, the location of Yakutsk has been identified. Also, if you’re curious, the big river that curves from the left-middle of the image to the top-center is the Lena River. It is up to 10 km wide in parts, particularly north of Yakutsk. Its second largest tributary, the Aldan River, is also easily visible as it meanders through a lot of the burn areas.

If you replace M-10 with M-11 (2.25 µm) as the red channel, you get this image:

False color RGB composite of VIIRS channels M-5, M-7 and M-11, taken 03:22 UTC 7 August 2012

False color RGB composite of VIIRS channels M-5, M-7 and M-11, taken 03:22 UTC 7 August 2012

Here, the green is darker due to the lower reflectivity of the surface in M-11 compared with M-10. The advantage of this RGB composite it that, if you zoom in, you can actually see where the fires are still active, as those pixels show up bright red. (If the fire is hot enough, you’ll get red pixels in the “pseudo-true color” composite also, but M-11 is more responsive to heat from fires than M-10, so you can see lower temperature fires this way.) You can also see the faint bluish smoke plumes originating from the areas that are actively burning.

If you go in the other direction and use only the shortest wavelengths, the surface becomes difficult to see, but the smoke stands out more. Here is the RGB composite of M-1 (0.412 µm [blue]), M-2 (0.445 µm [green]) and M-3 (0.488 µm [red]):

False color RGB composite of VIIRS channels M-1, M-2 and M-3, taken 03:22 UTC 7 August 2012

False color RGB composite of VIIRS channels M-1, M-2 and M-3, taken 03:22 UTC 7 August 2012

Here, the wavelengths of these channels range from the violet to the blue portion of the visible spectrum. At these shorter wavelengths, scattering in the atmosphere becomes much more important and the solar radiation has a tough time making it all the way to the surface. All the smoke and haze increases the scattering, so it is difficult to pick out features on the surface. That same scattering, though, really highlights the smoke plumes, which are difficult to see in the other false color composites.  Since the scattering by the stuff in this image doesn’t vary much between these three channels, you get an image without much color to it.

With much of Colorado and, really, much of the western U.S. having burned already this year, it’s easy to know what the people of Siberia are going through. Fortunately, none of the fires have really threatened any towns. And, another plus: I bet those clouds of mosquitoes don’t like the dry weather that has caused all of these fires.