Wild Week of Wildfires, Part III

The last two posts covered flooding. Now, a month later, we are back to covering last year’s most common topic: wildfires. This time, we’ll make a game out of it. Keep in mind that, for many operational fire weather forecasters, this isn’t a game – it is information that could prove useful in saving lives or homes from destruction. If you have read the earlier posts on fire detection and haven’t forgotten what you’ve been told (here’s a good one to go back and read), this should be easy for you.

The following images are the unmapped data from three consecutive VIIRS granules over the Southwest U.S., starting at 20:36 UTC 11 June 2013. The “raw” data has been processed to produce the “True Color”, “Natural Fire Color” and “Fire Temperature” RGB composites. Plus, the brightness temperature data from channel M-13 (4.0 µm) has a color table applied to it to aid in fire detection. Satellite channels near 4 µm are the “industry standard”, so to speak, for detecting fires as they are highly sensitive to sub-pixel heat sources like fires. The “Natural Fire Color” and “Fire Temperature” composites are RGB composites developed just for VIIRS that both had their debut on this very blog.

The question is: how many fires can you see? Remember, you have to allocate resources (firefighters, helicopters, planes, etc.) based on your assessment. The media is hounding you for all the latest statistics on each blaze and they can’t wait until the 5:00 briefing. They need the scoop now to get higher ratings. Plus, the crew is loading fire retardant on the plane as you read this. Where should the pilot fly to? Everyone is counting on you! (Of course, you would never have just satellite data by itself in a real-life scenario – but, do you want to play this game, or just think of flaws?)

I’ll give you a hint: You won’t see any fires unless you view each image at full resolution. Click on the image, then on the “3200×2304” link below the banner to see the full resolution version. (You could even open each full resolution image in a new tab, and click between the tabs for easy comparison, assuming you’re not using some archaic version of Internet Explorer or another old browser that doesn’t allow tabs. When you would click on the “3200×2304” link, instead right-click and select “Open in New Tab”. Another option would be to save the images and open them in an image viewing software program that will allow you to zoom in more than 100% but, that is starting to sound like a lot of work and I’m not sure I want to play this game anymore. It’s too complicated. By the way, if that’s the way you feel, don’t become the manager of a fire incident team.)

I’ll give you another hint: Many of the hot spots that indicate fires are only 1-2 pixels in size. Be prepared to look for needles in the haystack, and make sure you have your reading glasses on, if you need them.

VIIRS "True Color" composite of channels M-03, M-04 and M-05, taken at 20:36 UTC 11 June 2013

VIIRS "True Color" composite of channels M-03, M-04 and M-05, taken at 20:36 UTC 11 June 2013

VIIRS "Natural Fire Color" composite of channels M-05, M-07 and M-11, taken 20:36 UTC 11 June 2013

VIIRS "Natural Fire Color" composite of channels M-05, M-07 and M-11, taken 20:36 UTC 11 June 2013

VIIRS "Fire Temperature" composite of channels M-10, M-11 and M-12, taken 20:36 UTC 11 June 2013

VIIRS "Fire Temperature" composite of channels M-10, M-11 and M-12, taken 20:36 UTC 11 June 2013

VIIRS channel M-13 image, taken 20:36 UTC 11 June 2013

VIIRS channel M-13 image, taken 20:36 UTC 11 June 2013

So, did you see them all? You should have identified 12 fires. Did you find less than 12? Some of them are hard (or impossible) to see in some of the images. Did you find more than 12? The color scale used on the M-13 image led to false alarms, so you can be forgiven if that’s what caused you count too many.

This example shows some of the complicating factors when trying to identify fires from satellites. It also shows why fire managers never rely on satellite data alone. Now, having said that, VIIRS can and does provide useful information on fires.

First, here’s the answer (link goes to PDF) from the National Interagency Fire Center. They identified 15 active “large incident” fires on 12 June 2013. (They update their maps once per day, so all the fires that started on 11 June make it on the 12 June map.) But, there are differences between their map and what VIIRS saw.

First, the Mail Trail fire (#5 in the PDF) is outside the domain of these three VIIRS granules, so you couldn’t have found that in these images. Fires #3, 4 and 7 (Healy, Porcupine and Ferguson) are obscured by clouds, and/or were mostly contained, transitioning from active to inactive. The Tres Lagunas Fire (#13) started back in May and is undergoing mop up activities. The hot spots from that fire (if there are any left) aren’t visible in the images, but the burn scar is. That leaves the Stockade (#1), Crowley Creek (#2), Hathaway (#6), Fourmile (#8), Silver (#9), Thompson Ridge (#10), Jaroso (#11), Big Meadows (#12), Royal Gorge (#14), and Black Forest (#15) – 10 fires which are all visible in the VIIRS images. Plus, VIIRS saw two more fires that are not included on that list: one in southern California (near the Salton Sea) that I couldn’t find any information on, plus a pellet plant fire in Show Low, Arizona. (Small fires in towns are usually outside the scope of the National Interagency Fire Center, so they don’t bother to list those.)

I would argue that the “Fire Temperature” composite worked the best at identifying each of these fires, but all 4 images have their uses. Here’s the Fire Temperature RGB image with the visible fires identified:

VIIRS "Fire Temperature" composite of channels M-10, M-11 and M-12, taken 20:36 UTC 11 June 2013

VIIRS "Fire Temperature" composite of channels M-10, M-11 and M-12, taken 20:36 UTC 11 June 2013

Answer honestly. Which fires did you see, and which fires did you miss?

The Fire Temperature RGB takes advantage of the VIIRS channels in the portion of the electromagnetic spectrum ranging from the near-infrared (NIR) to the shortwave infrared (SWIR). The blue component is M-10 (1.61 µm), the green component is M-11 (2.25 µm) and the red component is M-12 (3.7 µm). As wavelength increases over this range, the contribution of the Earth’s emission sources increases and the contribution from the sun decreases. As a result, only the hottest hot spots show up in M-10, as they have to be seen over the large signal of radiation from the sun reflecting off the Earth’s surface. In M-12 (as in M-13), hot spots from fires produce more radiation at that wavelength than the amount of reflected solar radiation. M-11 is somewhere in the middle. That means relatively cool (e.g. smoldering) or small fires only show up in M-12, which makes those pixels appear red. Pixels containing fires hot enough or large enough to show up in M-11 will take on an orange to yellow color. Pixels containing fires hot enough or large enough to show up in all three channels will appear white.

You have to be careful, though, as some pixels in the Fire Temperature RGB appear red, even though there aren’t any fires in them. A few of these pixels show up red in the M-13 image, and are labelled as “not a fire/false alarm”:

VIIRS M-13 image, taken 20:36 UTC 11 June 2013

VIIRS M-13 image, taken 20:36 UTC 11 June 2013

According to the color table used, any pixel with a brightness temperature above 340 K (67 °C) will be colored, with colors ranging from red to orange to pale yellow as temperature increases. Now, look at that area in the True Color image (or on Google Maps):

VIIRS "True Color" composite of channels M-03, M-04 and M-05, taken 20:36 UTC 11 June 2013

VIIRS "True Color" composite of channels M-03, M-04 and M-05, taken 20:36 UTC 11 June 2013

That area is very dark – almost black – volcanic rock with very little vegetation that has been baking in the sun all day. It has managed to acquire a brightness temperature that is higher than some of the active fire pixels. The Crowley Creek fire doesn’t show up as red in the M-13 image (the Stockade fire is the one with the yellow and orange pixels) and the Fourmile fire is barely visible. (It has two pixels warmer than 340 K, even though 10 pixels appear red in the Fire Temperature RGB). The color scale in the M-13 image could be applied to a different temperature range, but you’ll always have that trade-off: have the colors start at too high a temperature, and you’ll miss some fires; have the colors start at too low a temperature, and you’ll increase the false alarms.

The True Color image should have helped you identify 5 of the fires. The smoke plumes that show up are a dead giveaway. I’m talking about the Big Meadows, Royal Gorge, Jaroso, Thompson Ridge and Silver fires, of course. There may be smoke with the Hathaway fire, but it would be mixed in with the cirrus clouds and hard to see. Not all fires produce a lot of smoke, though. Having information on the ones that do aids in issuing air quality alerts, among other benefits.

Lastly, the Natural Fire Color image highlights most (but not all) of the fires. Look for the red pixels:

VIIRS "Natural Fire Color" composite of channels M-05, M-07 and M-11, taken 20:36 UTC 11 June 2013

VIIRS "Natural Fire Color" composite of channels M-05, M-07 and M-11, taken 20:36 UTC 11 June 2013

The Natural Fire Color doesn’t show active hot spots at Crowley Creek, and the Hathaway and Fourmile fires are difficult to see, because they aren’t quite hot enough. (Generally speaking, any fire that shows up red in the Fire Temperature RGB is too cold to show up as red in the Natural Fire Color.) But, this composite has the advantage of showing burn scars in addition to the active fires. Burn scars appear dark brown. The Fourmile and Crowley Creek burn scars are visible. Plus, burn scars from last year’s fires still show up: The Whitewater-Baldy, High Park and Waldo Canyon scars are identified. The Tres Lagunas was mentioned above, and it’s burn scar is visible. If you look closely, I’m sure you could find more burn scars from last year’s long fire season.

Here are all four images, zoomed in on each fire at 800%, combined into an animation to highlight how each fire appears in each image:

Animation of M-13, True Color, Natural Fire Color and Fire Temperature imagery zoomed in each fire (20:36 UTC 11 June 2013)

Animation of M-13, True Color, Natural Fire Color and Fire Temperature imagery zoomed in each fire (20:36 UTC 11 June 2013)

For some reason, you have to click to the full resolution version of the image before the animation will display.

Hopefully, this exercise is useful in demonstrating the complications that arise when trying to detect fires from satellites in space, as well as the strengths and weaknesses of some of the various methods VIIRS has at it’s disposal to aid the fire weather community.

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!

The Case of the 100-year-old Ash Cloud

Lost in all the commotion caused by Hurricane Sandy, a curious event occurred on the other side of the country on 30 October 2012. A cloud of ash obscured the skies of Kodiak Island, Alaska, diverting flights in the region and forcing the people of Kodiak to stay inside or wear masks. Alaska has quite a few volcanoes, so this may not be a big thing to them except, this was no ordinary volcanic eruption: it was the leftovers of a volcanic eruption from 100 years ago!

The volcano that came to be known as Novarupta erupted on 6 June 1912. It was one of the largest volcanic eruptions of recorded history. It was 10 times more powerful than Mt. St. Helens with 100 times more ash. The explosion was heard more than 1100 km (700 miles) away in Juneau. The force of the eruption caused nearby Mt. Katmai to collapse on itself (10 km away). It formed the Valley of Ten Thousand Smokes and, most importantly for us, covered the surrounding land with 150 m (500 ft) of ash.

This pile of ash – still there today – can be lifted by a stiff breeze (or, more appropriately, “strong breeze” or higher on the Beaufort wind scale), and blown pretty high off the ground (4000 ft according to the news report). This isn’t the first time this has happened. MODIS observed the same thing back in 2003.

So, what did VIIRS see? Here’s the “true color” image, the RGB composite of channels M-03 (0.488 µm, blue), M-04 (0.555 µm, green) and M-05 (0.672 µm, red):

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 22:23 UTC 30 October 2012

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 22:23 UTC 30 October 2012

Be sure (as with all the images) to click on the image, then on the link below the banner to see it at full resolution. (The link contains the dimensions of the full size image.)

The ash cloud (blowing right over the center of Kodiak Island) is not as obvious in this image as it was in the MODIS image in the link above, although it is visible. To be fair, the plume was much more optically thick in 2003, and there were fewer clouds and less snow to confuse it with.

Here is the false color (“pseudo-true color” or “natural color”) image, the RGB composite of channels M-05 (0.672 µm, blue), M-07 (0.865 µm, green) and M-10 (1.61 µm, red):

VIIRS false color RGB composite of channels M05, M-07 and M-10, taken 22:23 UTC 30 October 2012

VIIRS false color RGB composite of channels M05, M-07 and M-10, taken 22:23 UTC 30 October 2012

Hmmm. Once again, the ash plume is visible but not particularly noticeable. Is there a way to highlight the ash plume to make it easier to see?

EUMETSAT (the European Organisation for the Exploitation of Meteorological Satellites) has defined an RGB composite for detecting dust. Their product, which was developed primarily to detect dust storms over the Saharan desert, uses channels that are present (or similar to ones that are present) on VIIRS. This means we can apply the dust product for VIIRS as the difference between M-16 and M-15 (red), the difference between M-15 and M-14 (green) and M-15 by itself (blue), all in units of brightness temperature. If you do that, and use the same color scaling they use, you get this image:

The EUMETSAT Dust RGB composite applied to VIIRS for 22:23 UTC 30 October 2012

The EUMETSAT Dust RGB composite applied to VIIRS for 22:23 UTC 30 October 2012

The arrow points to the source region of the ash plume. In this RGB composite, dust shows up as hot pink (magenta), but it’s barely visible here. The reason is that this dust product is primarily useful where there is a large temperature contrast between the dust plume and the background surface, which we don’t have here.

A more common way to detect volcanic ash is to use the “split-window difference”. The “split-window difference” is the difference in brightness temperature between a 10.7-11.0 µm channel and a 12.0 µm channel. This difference is useful because volcanic ash has a difference of opposite sign to most everything else. Here’s what the split window difference (M-15 – M-16) looks like for this case:

VIIRS "Split-window difference" image from 22:23 UTC 30 October 2012

VIIRS "Split-window difference" image from 22:23 UTC 30 October 2012

This image has been scaled so that the colors range from -1 K (black) to +7 K (white). The ash plume stands out a bit more here by being much darker than the background. The only problem is, it isn’t perfect. Large amounts of water vapor, optically thick clouds, desert surfaces and boundary layer temperature inversions can all produce a negative difference (just like volcanic ash does).

These problems can be overcome to a certain extent by combining the “split-window difference” with a Principal Component Image (PCI) analysis technique. (This technique is too complicated to describe here but, if you have access to AMS journals, check out these journal papers.) Now, the ash plume is the only thing that’s black:

VIIRS PCI analysis image from 22:23 UTC 30 October 2012

VIIRS PCI split window analysis image from 22:23 UTC 30 October 2012. Image courtesy Don Hillger. Upside-down text courtesy McIDAS-X.

Notice the smaller plume identified by the orange arrow. This plume is not easy to identify in any of the previous images. The PCI technique works well. But, we’re not going to stop there.

Remember the dust plumes off the Cape Verde islands? They produced a strong signal in the difference between M-12 (3.7 µm) and M-15 (10.7 µm) due to solar reflection. Does a 100-year-old ash plume produce a similarly strong signal? See for yourself:

VIIRS channel difference image between M-12 and M-15 from 22:23 UTC 30 October 2012

VIIRS channel difference image between M-12 and M-15 from 22:23 UTC 30 October 2012

It does produce a signal, but it’s not as bright as the surrounding clouds. The color scale here ranges from -2 K (black) to +90 K (white).

M-06 (0.746 µm) is highly sensitive to anything that reflects solar radiation in the atmosphere or on the surface, which we learned from Hurricane Isaac. Here’s what the M-06 image looks like:

VIIRS channel M-06 image, taken 22:23 UTC 30 October 2012

VIIRS channel M-06 image, taken 22:23 UTC 30 October 2012

“Big deal,” you say. “None of those are better than the PCI analysis.” That may be true, but watch what happens when we combine M-06, the M-12 – M-15 image and the split-window difference image in a single RGB composite:

VIIRS RGB composite of M06 (blue), M12 - M15 (green) and M15 - M16 (red), taken 22:23 UTC 30 October 2012

VIIRS RGB composite of M06 (blue), M12 - M15 (green) and M15 - M16 (red), taken 22:23 UTC 30 October 2012

In this composite, blue values represent the M-06 reflectance scaled from 0 to 1.6, green values represent the brightness temperature difference between M-12 and M-15 scaled from -2 K to +90 K, and red values represent the brightness temperature difference between M-15 and M-16 scaled from -1 K to +7 K.

From a theoretical perspective, this RGB composite does exactly what you want: make the thing you’re trying to detect the only thing that is a certain color. For example, the ash plumes are the only things in this image that are green. From a practical perspective, however, this RGB composite doesn’t work so well. It only works because the ash plume is over water (otherwise M-06 wouldn’t be very useful). It only works during the day, where M-06 is available and the difference between M-12 and M-15 is significant (no solar component to M-12 at night).

Plus, the rainbow of colors is difficult to make sense of: green ash; clouds ranging from light blue to purple to orange (a function of optical thickness, particle size, and phase); bright purple snow; dark purple vegetation; maroon water. It’s not exactly pleasing to the eye. In contrast, the PCI analysis technique that uses the split-window difference works day and night, over ocean and over land. And it isn’t confusing to look at. Maybe we should have stopped when we got to the PCI technique. But then, we wouldn’t have learned anything new.

VIIRS Captures a Glimpse of Hell

VIIRS has seen Hell and, luckily, it did not get scared. No, I’m not talking about Hell, Michigan, which is actually a nice place (and not as scary as their website would indicate). I’m talking about the Gates of Hell (or Door to Hell, depending on who you talk to) in Turkmenistan. You can see a single video of it here and, if that isn’t enough to get a sense of it, someone compiled a list of 296 videos of the Gates of Hell near Derweze/Darvaza, Turkmenistan.

Turkmenistan doesn’t have much – 80% of it is the Karakum Desert – but it does have a lot of oil and natural gas deposits. Back in 1971, the Soviet Union wanted to take advantage of these deposits, so they began drilling a gas well near the town of Derweze. Unfortunately, the drilling opened up a sinkhole that ate the drilling rig and caused the natural gas to leak out in large quantities. Oh, no! What to do now? Light it on fire!

The team of geologists thought that the best way to prevent the town from being suffocated by the toxic fumes was to ignite the gas, let it burn itself out in a few days, and return to see what the damage was. Guess what? That fire is still burning today – 41 years later!

This constantly burning crater is only 230 ft (70 m) across. So it may come as a surprise (to some people, at least) that VIIRS has no trouble seeing it. The highest-resolution channels on VIIRS have a spatial resolution of ~375 m at nadir. The fiery pit is so visible, the Day/Night Band (DNB), with ~740 m resolution, makes the Gates of Hell look like the biggest town in central Turkmenistan:

VIIRS Day/Night Band image of Turkmenistan, taken 22:26 UTC 13 September 2012

VIIRS Day/Night Band image of Turkmenistan, taken 22:26 UTC 13 September 2012

The red arrow points out the light source that is the Gates of Hell. One other thing to note from this image is all the lights in the Caspian Sea. Those are oil rigs, with the largest light source (the one closest to the center of the Caspian Sea) being the floating/sinking city of Neft Daşları (a.k.a Oily Rocks), which sounds like a pretty interesting/sad/weird place to work.

In case you think the lights are coming from the town of Derweze and not the actual Gates of Hell, here’s a zoomed in image from the DNB along with the M-12 (3.7 µm) brightness temperatures:

VIIRS Day/Night Band image of the Derweze "Gates of Hell", Turkmenistan, taken 22:26 UTC 13 September 2012

VIIRS Day/Night Band image of the Derweze "Gates of Hell", Turkmenistan, taken 22:26 UTC 13 September 2012

VIIRS channel I-04 image of the Derweze "Gates of Hell", Turkmenistan, taken 22:26 UTC 13 September 2012

VIIRS channel M-12 image of the Derweze "Gates of Hell", Turkmenistan, taken 22:26 UTC 13 September 2012. The color scale ranges from 210 K (white) to 300 K (black).

The Gates of Hell is the only light source that also shows up as a 345 K hot spot in channel M-12. Since this is a nighttime image, the signal in M-12 comes only from emission from the Earth (and clouds, etc.) without any contribution from solar reflection (as there would be during the day). What you see in the M-12 image is the temperature of the objects in the scene, just like a typical infrared (IR) satellite image, except with higher sensitivity to sub-pixel heat sources. The clouds show up as cold (bright, in this color table) above the warmer (darker) land surface. Sarygamysh Lake (and a few other smaller lakes) show up as really warm (dark) because the desert floor at night cools off much more than the water does.

The moon here was only ~10% full, so there wasn’t enough light reflecting off the few clouds in the scene for the DNB to detect them. In fact, with so little moonlight, everything is dark in the DNB. Everything, that is, except for the towns, villages and flaming craters of burning methane.

A Wild Week of Wildfires

The last few weeks have been filled with lightning-ignited wildfires across the United States. The County Line Fire, along the Florida-Georgia border was caused by lightning on 5 April 2012 and burned ~35,000 acres. The Whitewater-Baldy Complex (began 16 May 2012) – the largest wildfire in New Mexico history – started as two different fires (both caused by lightning) that merged together. It’s over 280,000 acres (that’s not a typo) and continues to burn (as of 13 June 2012). The Duck Lake Fire (began 24 May 2012) burned 21,000 acres of Michigan’s Upper Peninsula and was caused by lightning. The Little Bear Fire (began 4 June 2012), also in New Mexico, was caused by lightning and has burned ~37,000 acres.  Much closer to home, the High Park Fire (began 9 June 2012) is already the largest wildfire in Larimer County history and the third largest fire in Colorado history. It has burned ~46,000 acres and I bet you can guess what caused it.

It’s not clear who is to blame here – there is a long list of suspects – but I bet it was Thor. Even though the U.S. is generally the domain of the Thunderbird, Thor has a mountain-crushing hammer called Mjöllnir, which makes him as good a suspect as any. He may have been in cahoots with Indra or Marduk who are the bringers of rain, and have been holding back on us. Look at how dry it has been across the majority of the country.

With all of these fires, it’s hard to know where to begin. We’re going to ignore the County Line Fire as it was put out over a month ago. We’re also going to ignore the Whitewater-Baldy Complex, as it is so big, it can be seen by GOES. (Kidding! We kid because we love.) Plus, it’s been done before. The VIIRS view of the High Park Fire has also been looked at by CIMSS, with an interesting comparison between VIIRS and MODIS.

What we are going to do is show off interesting features of some of these fires that haven’t been shown or discussed before (as far as we know). We begin with “saturation”. Both the High Park Fire and Little Bear Fire saturated the VIIRS 3.7 µm channels (I-04 and M-12):

Channel I-04 image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel I-04 (3.7 µm) image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel M-12 image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel M-12 (3.7 µm) image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel I-04 image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel I-04 (3.7 µm) image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel M-12 image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel M-12 (3.7 µm) image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

The top two images are of the Little Bear Fire, which formed near the border of Lincoln and Otero counties in New Mexico. The bottom two images are of the High Park Fire in Larimer County, Colorado. For each fire, the high resolution 3.7 µm channel (I-04) is compared with the moderate resolution 3.7 µm channel (M-12). The colors range from white (cold) to black (hot). But, wait a minute! If white is cold, why are there white pixels mixed in with the black ones that indicate the hot spots? That’s because these channels are saturating and experiencing “fold-over”. The peak brightness temperatures these channels can measure is ~ 367 – 368 K. Anything warmer than that won’t be detected, so the channel is said to be saturated. When it really gets above that limit you can have “fold-over”, where not only are you not observing the higher, correct temperature, the detectors actually report a lower temperature or radiance. In these fires, the fold-over is resulting in brightness temperatures down to 203 K for M-12 and 208 K for I-04, which is about 90-100 K colder than even the area surrounding the fires!

Luckily, VIIRS has a 4.0 µm channel (M-13) that was designed to not saturate at the temperature of typical wildfires. Compare the hottest pixels in the M-13 images below with the fold-over pixels from M-12 and I-04 above:

Channel M-13 image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel M-13 (4.0 µm) image of the Little Bear Fire from VIIRS taken 20:16 UTC 9 June 2012

Channel M-13 image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel M-13 (4.0 µm) image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

The hottest pixel in M-13 reached a temperature of 588 K for the Little Bear Fire and 570 K for the High Park Fire – over 200 K warmer than the saturation points of M-12 and I-04!

These fires were so hot, they appeared in channels that don’t usually show a fire signal. Limiting our attention to the High Park Fire (which was almost literally in our back yard), here’s the I-05 (11.5 µm) image from 10 June 2012:

Channel I-05 image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel I-05 (11.5 µm) image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

The highest temperature observed in I-05 was 380 K. Longer wavelength channels, such as in I-05 are less sensitive to sub-pixel hot spots than channels in the 3.7 – 4.0 µm range, so fires don’t often show up. For pixels to have a 380 K brightness temperature in I-05, it means that the average temperature over the entire pixel had to be above +100 °C – hot enough to boil water!

Fires don’t often show up at shorter wavelengths, either, because the amount of solar radiation usually dwarfs any signal from the Earth’s surface. But, the High Park Fire did reach saturation at 2.25 µm (M-11):

Channel M-11 image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

Channel M-11 (2.25 µm) image of the High Park Fire from VIIRS taken 19:59 UTC 10 June 2012

The color scale has been reversed so that it is more inline with visible imagery. The white pixels represent saturation in M-11 at a radiance of 38 W m-2 µm-1 sr-1. The reflectance of these pixels saturated at a value of 1.6, which means that the amount of radiation detected in this channel was more than 1.6 times the amount you would expect to see if the surface was a perfect mirror reflecting all the solar radiation back to the satellite. Thus, the fire’s contribution to the total radiance was significant in this channel.

The contribution from the surface (i.e., the fire) was also visible in the 1.6 µm channel (M-10), but it isn’t exciting enough to show. One channel shorter down on VIIRS (M-9, 1.38 µm) and the signal disappears against the high reflectivity of the smoke plume.

It’s impossible to leave out the Day/Night Band, which shows just how large and how close the High Park Fire got to Fort Collins:

Day/Night Band image of the High Park Fire from VIIRS taken 09:58 UTC 11 June 2012

Day/Night Band image of the High Park Fire from VIIRS taken 09:58 UTC 11 June 2012. Image courtesy Dan Lindsey.

The smoke plume, while not exactly visible, is affecting the view of the east side of the fire and Fort Collins, making them appear more blurry than they would if the sky were completely clear. You can also see that, overnight on 11 June 2012, the fire covered an area larger than any of the cities visible in the image (except for Denver, which is mostly cropped off the bottom of the image).

Hopefully, Marduk will start doing his job and bring us some rain and these will be the last fires for a while.