Drought in the Land of the Long, White Cloud

Posted on March 22, 2013 by Curtis_Seaman

Science fiction fanatics know it as “Middle-earth“. Abel Tasman, the Dutch explorer who became the first European to sail there, called it “Staten Landt“, which was later changed to Nieuw Zeeland, Nova Zeelandia, and, finally, New Zealand. The native Maori people call it “Aotearoa“, which loosely translates to “the land of the long, white cloud”.

A group of volcanic islands southeast of Australia, New Zealand is known for the Southern Alps, the locations where they filmed the Lord of the Rings trilogy and rugby, although I’m sure there’s more to the country than that. Residents of New Zealand refer to themselves as “kiwis”, although it is not clear if they prefer to be thought of as birds or fruit.

Being an island nation in the mid-latitudes with 17 peaks above 10,000 ft (3,000 m), you might expect there would be no shortage of moisture and uplift to form clouds and precipitation. There are sea breezes, mountain/valley circulations, orographic uplift of prevailing winds, periodic mid-latitude cyclones and the occasional tropical storm to get things started. But, that’s not the case this year.

The North Island is currently experiencing its worst drought in over 30 years. Many places have experienced less than half of normal precipitation this summer, according to NIWA (their version of NOAA). These are places that normally receive 40-80 inches of precipitation per year. (Remember, summer just ended down there and that 500 mm is roughly 20 inches.)

Wellington, the nation’s capital, has begun rationing water for the first time in recorded history (which covers about 170 years). The chair of the Wellington region’s committee in charge of the water supply was quoted as saying, “People should shower with a friend, if that’s an option . . . or put a brick in the toilet. If you know anyone who’s particularly adept at rain dances, then encourage them to get out there and do what they do.”

One of the previous links mentioned that the drought is so bad, it can be seen from space. They didn’t provide evidence to back up that claim, so I guess I have to do it. Here’s what VIIRS saw on 28 January 2013 (before the North Island went 4-6 weeks without any significant precipitation):

"True Color" RGB composite of VIIRS channels M-03, M-04 and M-05, taken 01:49 UTC 28 January 2013

And here is what VIIRS saw on 21 March 2013 (after 4-6 weeks without significant precipitation):

"True Color" RGB composite of VIIRS channels M-03, M-04, and M-05, taken 02:15 UTC 21 March 2012

The two images above are “true color” composites. If you look closely at the two images, you might notice significantly less green vegetation in the 21 March 2013 image, particularly in box that covers 39° to 40° S latitude and 174° to 176° E longitude. (Remember, you can see the full-resolution image by clicking on it, and then on the “1434×2120” link below the banner.)

Not convincing? Maybe it shows up a bit better in the “natural color” composite, which has a strong vegetation signal. Here are those images:

False color composite of VIIRS channels M-05, M-07 and M-10, taken 01:49 UTC 28 January 2013

False color composite of VIIRS channels M-05, M-07 and M-10, taken 02:15 UTC 21 March 2012

And just to be clear, here are the images zoomed in on the west side of the North Island, where the drought has hit the hardest:

Drought impact on vegetation in the North Island of New Zealand between 28 January and 21 March 2013

Drought impact on vegetation in the North Island of New Zealand between 28 January (left) and 21 March 2013 (right)

In the image on the left, from 28 January, light green areas represent grassland/pasture (backed up by this land use map) and dark green areas represent forests. In the image on the right, from 21 March, the grassy areas have turned brown while the forests have remained green. Six weeks with almost no rain will do that to grass.

While the “true color” and “natural color” RGB composites are only qualitative (and require viewers to be able to distinguish sometimes subtle changes in the amount of green in the images), there are ways to quantify the “greenness” of vegetation from satellite. The most widely used method is the Normalized Difference Vegetation Index (NDVI for short). The NDVI has been calculated for more than 40 years with Landsat and AVHRR. We can do the same calculation with VIIRS. That’s what is shown below.

VIIRS NDVI images of New Zealand from 28 January and 21 March 2013

VIIRS NDVI images of New Zealand from 28 January (left) and 21 March 2013 (right)

On this color scale, red and yellow colors indicate high values of NDVI (or very green vegetation). Green and blue colors indicate low values of NDVI (sparse, dead or brown vegetation). Notice how most of the North Island has gone from yellow or red in January (on the left) to blue or green in March (on the right). NDVI values have decreased by 20-30% over this period.

I guess if there is one benefit of the drought, it’s that it has been clear enough over New Zealand for satellites to see it. In fact, January and February have broken records for the amount of sunshine in many parts of the country. The land of the long, white cloud hasn’t been living up to its name.

Chinese Super-Smog

Posted on February 15, 2013 by Curtis_Seaman

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

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

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

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

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

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 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

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

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

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

Posted on December 17, 2012 by Curtis_Seaman

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. 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. 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. 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

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. 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

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

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. 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. 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 Case of the 100-year-old Ash Cloud

Posted on November 29, 2012 by Curtis_Seaman

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

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

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 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

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

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

“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

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.

Greenland Eddies and Swirls

Posted on October 22, 2012 by Curtis_Seaman

Last time we visited Greenland, it was because VIIRS saw evidence of the rapid ice melt event in July 2012. We return to Greenland because of this visible image VIIRS captured on 18 October 2012:

VIIRS channel I-01 image taken 12:43 UTC 18 October 2012

This image was taken by the high-resolution visible channel, I-01 (0.64 µm), and was cropped down to reduce the file size. Greenland is in the upper-left corner of the image. The northwest corner of Iceland is visible in the lower-left corner of the image.

So, what’s with all the swirls off the coast of Greenland? Are they clouds swirled around by winds? Or some kind of sea serpent – perhaps a leviathan or a kraken? (Based on the descriptions, they would be big enough for VIIRS to see them.)

Sadly, for all you science fiction and fantasy fanatics, those swirls are just icebergs breaking up as they enter warmer water, the chunks of ice caught up in eddies in the East Greenland Current. This is easier to see when you look at the “true color” image below:

VIIRS "true color" RGB composite of channels M-3, M-4 and M-5, taken 12:43 UTC 18 October 2012

Make sure to click on the image, then on the “3200×1536” link below the banner to see the image at full resolution. Since the true color RGB composite is made from moderate resolution channels M-03 (0.488 µm, blue), M-04 (0.555 µm, green) and M-05 (0.672 µm, red), we can include more of the swath before we get into file size issues. That allows us to see the extent of the ice break-up along the Greenland coast.

There is a lot to notice in the true color image. The large icebergs at the top of the image breakup into smaller and smaller icebergs as they float down the east coast of Greenland, until they finally melt. These visible “swirls” (or “eddies” in oceanography terms) extend from 75 °N latitude down to 68 °N latitude where the ice disappears (melts).

The upper-right corner with missing data is on the night side of the “terminator” (the line separating night from day), where we lose the amount of visible radiation needed for these channels to detect stuff. (The Day/Night Band would still collect data, however, as it is much more sensitive to the low levels of visible radiation observed at night.) See how the ice and the high clouds appear to get a bit more pink as you move from west (left) to east (right)? It’s the same reason cirrus clouds often look pink at sunset. The sun is setting on the North Atlantic and more of the blue radiation from the sun is scattered by the atmosphere than red radiation. The red radiation that’s left is then reflected off the clouds (and ice and snow) toward the satellite.

Just to prove that the swirls are indeed ice and not clouds, here’s the “pseudo-true color” (a.k.a. “natural color”) RGB composite made from channels M-05 (0.672 µm, blue), M-07 (0.865 µm, green) and M-10 (1.61 µm, red):

VIIRS natural color image of channels M-05, M-07 and M-10, taken 12:43 UTC 18 October 2012

The deep blue color of the swirls in this RGB composite is indicative of ice, not clouds. These channels are not impacted by atmospheric scattering at any sun angle, though, so there is no change in the color of the clouds as you approach the terminator.

You may have also noticed the cloud streets downwind of the icebergs off the coast of Greenland. These clouds are formed in the same way as lake-effect clouds are in the Great Lakes. Cold, arctic air flowing south over the icebergs meets the relatively warm water of the open ocean. The moisture evaporating from the warmer waters condenses in the cold air and forms clouds.

How much warmer is that water? Here’s the high-resolution infrared (IR) image (I-05, 11.45 µm):

VIIRS channel I-05 image, taken 12:43 UTC 18 October 2012

At ~375 m resolution at nadir, this is the highest resolution available in the IR on a non-classified satellite today. Look at all the structure in the cloud-free areas of the ocean! Lots of little eddies show up in the IR that are invisible in the visible and near-IR channels shown previously. The only eddies visible in the true color and natural color images are the ones that had ice floating in them. Here we see they extend much further south than the ice.

The ice-free water that is not obscured by clouds is 10-15 K warmer than where the icebergs are found. The eddies are caused by the clash between the southward flowing, cold Eastern Greenland Current and the northbound, warm North Atlantic Drift (the tail end of the Gulf Stream), which are important in the global transport of energy. They are not ship-sinking whirlpools caused by any krakens in the area – at least VIIRS didn’t observe any.

UPDATE (February 2013): Below is another image of the eddies and swirls off the eastern coast of Greenland. This “natural color” image was taken 13:34 UTC 15 February 2013:

VIIRS false color RGB composite of channels M-05, M-07 and M-10, taken 13:34 UTC 15 February 2013. Image courtesy Don Hillger.

Since it is winter, the ice extends further south along the coast before it melts. Once again, there is a lot of structure visible in the edge of the ice, where the East Greenland Current and North Atlantic Drift interact. Another thing to notice is the shadows. At the top of the image just right of center is Scoresby Sound, which is completely frozen over. Given that the sun is pretty low in the sky over Greenland in the winter (if it rises at all, since most of Greenland is north of the Arctic Circle), the mountains south of the Sound cast some pretty long shadows on the ice. It’s possible to use the length of the shadows with the solar zenith angle to estimate the height of those mountains (although there are more accurate ways to determine a mountain’s elevation from satellite). VIIRS provides impressive detail, even from the moderate resolution bands.

JPSS (SNPP and NOAA-20)

VIIRS Imagery and Visualization Team Blog

Tag Archives: M-10

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Chinese Super-Smog

End of Autumn in the Alps

The Case of the 100-year-old Ash Cloud

Greenland Eddies and Swirls