Horrendous Haboob in the Heart and Heat of History’s Homeland

We mentioned India earlier this year due to a hellish heatwave. It’s only fair that we talk about one of the other cradles of civilization (human history) and another horrible weather-related h-word.

People have been living along the Nile River in northeastern Africa and on the Arabian Peninsula for thousands of years (dating back to the Paleolithic Era). And, every once in a while, a story comes along that makes you wonder why. I’m not talking about the never-ending human conflict that has plagued the region. I’m talking about the hostile climate. (Of course, it wasn’t always hostile. There have been periods of abundant moisture. Read this. Or this.)

If you’ve watched Raiders of the Lost Ark, you are no-doubt familiar with the ancient city of Tanis, and the story about it that was the basis of the whole plot of the movie. If you haven’t seen the movie: 1) shame on you; and, 2) watch this clip.

“The city of Tanis was consumed by the desert in a sandstorm that lasted a whole year.”

I hate to be the bearer of bad news but, that part of the story is false. No year-long sandstorm hit Tanis. And, despite rumors that the actual Ark is buried in Tanis, it has never been found. (Because it’s stored in a giant government warehouse! Duh!) Plus, Indiana Jones is a fictional character in a movie. But, the movie is not entirely false. According to this article, a major archaeological find did take place at Tanis right before World War II (led by a French archaeologist, no less), and very few people know about it because of the war. Plus, there really was an Egyptian Pharaoh named Shoshenq/Shishak.

Even if Tanis was not buried by a year-long sandstorm, that doesn’t mean nasty sandstorms don’t exist. In fact, most of the Middle East is still dealing with a massive sandstorm that lasted a whole week last week. This storm put Beijing’s air pollution to shame. In fact, the dust reached the highest concentrations ever recorded in Jerusalem since Israel became it’s own country in 1948. It was responsible for several fatalities. Here are some pictures. Here’s a video from Saudi Arabia. Here’s what it looked like in Jordan and Lebanon. And, of course, what follows is what the storm looked like in VIIRS imagery.

Since this dust storm lasted a whole week, we got plenty of VIIRS imagery of the event. It started on the afternoon of 6 September 2015, and here’s the first VIIRS True Color image of it:

VIIRS True Color image of channels M-3, M-4 and M-5 (10:06 UTC 6 September 2015)

VIIRS True Color image of channels M-3, M-4 and M-5 (10:06 UTC 6 September 2015)

Can you see it? (Click on the image to see the full resolution version.) A trained eye can spot it from this image alone. An untrained eye might have difficulty distinguishing it from the rest of the desert and sand. Look for the tan blob over Syria that is obscuring the view of the Euphrates river.

If you can see that, you can track it over the rest of the week:

Animation of VIIRS True Color images (6-12 September 2015)

Animation of VIIRS True Color images (6-12 September 2015)

This animation was reduced to 33% of it’s original size to limit the bandwidth needed to display it. It contains the afternoon overpasses (1 image per day) because you need sunlight to see things in true color. And, while it suffers from the fact that animated GIFs only allow 256 colors (instead of the 16,777,216 colors possible in the original images), you should be able to see the dust “explode” over Israel, Lebanon and Jordan over the next two days. It eventually advects over northwestern Saudi Arabia, Egypt and Cyprus during the rest of the week.

The last time we looked at a major dust storm, the dust was easy to see. It was blown out over the ocean, which is a nice, dark background to provide the contrast needed to see the dust. Here, the dust is nearly the same color as the background – because it is made out of what’s in the background. Is there a better way to detect dust in situations like this?

EUMETSAT developed an RGB composite explicitly for this purpose, and they call it the “Dust RGB.” And we’ve talked about it before. And, here’s what that looks like:

Animation of EUMETSAT Dust RGB images from VIIRS (6-12 September 2015)

Animation of EUMETSAT Dust RGB images from VIIRS (6-12 September 2015)

Since this RGB composite uses only infrared (IR) channels, it works at night (although not as well) so you can get twice as many images over this time period. It also makes dust appear hot pink. The background appears more blue in the daytime images, so the dust does stand out. But, the background becomes more pink/purple at night, so the signal is harder to see at those times. Still, you can see the dust spread from Syria to Egypt over the course of the week.

My colleagues at CIRA have developed another way to identify dust: DEBRA. DEBRA is an acronym for Dynamic Enhanced Background Reduction Algorithm. As the name implies, DEBRA works by subtracting off the expected background signal, thereby reducing the background and enhancing the signal of the dust. So, instead of trying to see brown dust over a brown background (i.e. True Color RGB) or trying to see hot pink dust over a pinkish/purplish background (i.e. EUMETSAT Dust RGB) you get this:

Animation of VIIRS "DEBRA Dust" images (6-11 September 2015)

Animation of VIIRS “DEBRA Dust” images (6-11 September 2015)

DEBRA displays dust as yellow over a grayscale background. The intensity of the yellow is related to the confidence that a given pixel contains dust. It could display dust as any color of the rainbow, but yellow was chosen specifically because there are fewer people that are colorblind toward yellow than any other type of colorblindness. That makes the dust very easy to see for nearly everyone. (Sorry, tritanopes and achromats.) One of the biggest complaints about RGB composites is that the 7-12% of the population that has some form of colorblindness have difficulty trying to see what the images are designed to show. (Since I’m so fond of RGB composites, I better check my white male trichromat privilege. Especially since, according to that last link, white males are disproportionately colorblind.) The point is: we now have a dust detection algorithm that works well with (most) colorblind people, and it makes dust easier to see even for people that aren’t colorblind. DEBRA also works at night, but I’ve only shown daytime images here to save on filesize.

The last two frames of the DEBRA animation show something interesting: an even more massive dust storm in northern Sudan and southern Egypt! Fortunately, fewer people live there, but anyone who was there at the time must have a story to tell about the experience. Here are closer up views of that Sudanese sandstorm (or should I say “haboob” since this is the very definition of the word?). First the True Color:

VIIRS True Color image (10:32 UTC 10 September 2015)

VIIRS True Color image (10:32 UTC 10 September 2015)

Next, the EUMETSAT Dust RGB:

VIIRS EUMETSAT Dust RGB image (10:32 UTC 10 September 2015)

VIIRS EUMETSAT Dust RGB image (10:32 UTC 10 September 2015)

And, finally DEBRA:

MSG-3 DEBRA Dust image (10:30 UTC 10 September 2015)

MSG-3 DEBRA Dust image (10:30 UTC 10 September 2015)

If you’re wondering why the DEBRA image doesn’t seem to line up with the other two, it’s because I cheated. The DEBRA image came from the third Meteosat Second Generation satellite (MSG-3), which is a geostationary satellite. The majority of the haboob was outside our normal VIIRS processing domain for DEBRA, so I grabbed the closest available MSG-3 image. It has much lower spatial resolution, but similar channels, so DEBRA works just as well. And, you don’t necessarily need high spatial resolution to see a dust storm that is ~ 1000 km across. What MSG-3 lacks in spatial resolution, it makes up for in temporal resolution. Instead of two images per day, you get 1 image every 15 minutes. Here is a long loop of MSG-3 images over the course of the whole week, where you can see both sandstorms: (WARNING: this loop may take a long time to load because it contains ~600 large images). Keep your eye on Syria early on, then on Egypt and Sudan. Both haboobs appear to be caused by the outflow of convective storms. Also, how many other dust storms are visible over the Sahara during the week? For comparison purposes, here’s a similar loop of EUMETSAT Dust images. (MSG-3 does not have True Color capability.)

These sandstorms have certainly made their impact: they’ve broken poor air quality records, killed people, made life worse for refugees, closed ports and airports, and even affected the Syrian civil war.  Plus, the storms coincided with a heatwave. Having +100 °F (~40 °C) temperatures, high humidity and not being able to breathe because of the dust sounds awful. Correction: it is awful. And, life goes on in the Middle East.


UPDATE #1 (17 September 2015): Here’s a nice, zoomed-in, animated GIF of the Syrian haboob as seen by the DEBRA dust algorithm, made from MSG-3 images:

Click to view 59 MB Animated GIF

UPDATE #2 (17 September 2015): Steve M. also tipped me off to another – even more impressive – haboob that impacted Iraq at the beginning of the month (31 August – 2 September 2015). Here’s an animation of the DEBRA view of it:

Click to view 28 MB Animated GIF

This dust storm was even seen at night by the Day/Night Band, thanks to the available moonlight:

VIIRS Day/Night Band image of Iraq (22:43 UTC 31 August 2015)

VIIRS Day/Night Band image of Iraq (22:43 UTC 31 August 2015)

Look at that cute little swirl. Well, it would be cute if it weren’t so hazardous.

UPDATE #3 (4 October 2021): Here is a link to more information about color blindness, provided by an avid viewer: Everything you need to know about Color Blindness

The Great Indian Heat Wave of 2015

Have you ever slept in a really hot room?

Of course, if you clicked on that link, keep in mind two things: perjury is a crime, and extreme heat is no joke. It is number one on the list of causes of weather-related fatalities. It may not capture the attention of the media like tornadoes, typhoons and tiger sharks but, exposure to extreme heat and extreme cold are routinely found to be the top two killers worldwide. (Well, that depends on the source of your information and how deaths are or are not attributed to weather. Some say extreme droughts and floods kill more.)

And of course, video footage of tornadoes and typhoons is more dramatic than frying an egg on the sidewalk or watching someone sweat inside a car. But, a recent heat wave in India is actually grabbing some attention from the media. Is it because there have been more than 2,200 documented fatalities? Or, the fact that it has been hot enough to make the roads melt?

Take a look at this hi/lo temperature calendar produced by the Weather Underground for Delhi, India during May 2015. If you’re paying attention, you’ll notice that only 4 days during the month had high temperatures less than 100 °F (38 °C). What is more concerning is that 18 out of the 31 days had low temperatures in the 80s. Look at May 18, 25 and 31: the lowest temperature recorded on each of those days was 87 °F (31 °C)! And take a look at the 10-day period in Hyderabad, India (May 20-29): highs near 110 °F everyday, with lows in the mid- to upper-80s.

And, for those of you in Phoenix or Death Valley, it is not a dry heat. According to this website, the automated weather station in Tirumala, Andhra Pradesh state recorded a temperature of 50 °C (122 °F) on May 31st. The day before, the high was 49 °C (120 °F), with a dew point of 24 °C (75 °F), which yields a heat index (or “feels like”) temperature of 59 °C (139 °F)!

Whether you side with Newman or Kramer on wanting to kill yourself after sleeping in a really hot room, with temperatures like this, it might not be your choice. If your body can’t cool down, you’ll be in trouble – especially if you don’t have air conditioning, like a lot of people in India.

You’ve probably guessed by now that VIIRS is capable of telling us something about this heatwave. And, you’re right! (Otherwise I wouldn’t be writing this.)

You should all know by now that the amount of radiation in the longwave infrared (IR) “window” (10-11 µm) is a function of the temperature of the object you’re looking at. We often refer to an object’s “brightness temperature,” which is the temperature that a black body would have if it emitted the same amount of radiation. With that in mind, here is the VIIRS longwave IR (M-15) image from 18 May 2015:

VIIRS IR (M-15) image from 08:06 UTC 18 May 2015.

VIIRS IR (M-15) image from 08:06 UTC 18 May 2015. Colors correspond to brightness temperatures according to the scale at lower right.

The first thing to notice is: there aren’t many clouds out there to block out the sun. The second thing to notice is: that big, black area in west-central India is where the color-enhancement of the image has lead to “saturation”. The IR color table I like to use saturates at brightness temperatures of 330 K (57 °C), which isn’t usually a problem because most places around the globe don’t get that hot. Some pixels in this image reached 332 K (59 °C/139 °F)! (The detectors of M-15 don’t saturate unless the brightness temperature is higher than 380 K, so this is not a problem with VIIRS.)

To prove there weren’t many clouds, here’s the True Color RGB (M-3/M-4/M-5):

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 08:06 UTC 18 May 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 08:06 UTC 18 May 2015.

There is some smog and dust, though, if you look close but, it’s not quite the same thing. And wait! The observed temperatures were only 40-45 °C, not 59 °C! What gives?

Aha! You are now aware of the difference between “air temperature” and “skin temperature”. The satellite observes “skin temperature” – the temperature of the surface of the objects it’s looking at*.  Thermometers measure the temperature of the air 2 m above the ground (assuming they follow the WMO standards [PDF]). As anyone who has ever tried to fry an egg on the sidewalk knows, the egg would never get cooked if you suspended it in the air 2 m above the ground. The ground heats up a lot more than the air does in this situation. One of the reasons is that the atmosphere doesn’t absorb radiation in this wavelength range*- and, if it did, it wouldn’t be an “atmospheric window”.

(* Not exactly. The atmosphere does have some effects in this wavelength range that have to be removed to get a true skin temperature. These effects increase with wavelength in the 11-12 µm range, which is why you may hear it called a “dirty window”.)

Another thing you should already know (even without cracking a few eggs) is that it’s much more comfortable to walk barefoot on grass in a park, than it is to walk barefoot in the parking lot (especially if it’s hot enough to make the asphalt melt). VIIRS can also tell you this.

Below, we’ve zoomed in on the area around Bombay (Mumbai) and the Gulf of Cambay. This is an image overlay that you might have to refresh your browser to see. Bombay is on the coast near the bottom of the images. As you drag the line back and forth, notice the areas with vegetation in the True Color image have a lower brightness temperature than the areas with bare ground.


Vegetation has the ability to keep itself cool (in a process similar to sweating), unlike the bare dirt. Of course, there may be some terrain effects and marine effects along the coastline that are keeping those areas cooler. Although, the terrain west of the Gulf is the hottest part of the scene (notice it has very little green vegetation). And, if you think the marine-influenced boundary layer moderates the temperatures, which it does, it greatly adds to the humidity. Bombay’s highs during the month of May were only in the 90s F (33-35 °C), but dew points were also 80-86 °F (27-30 °C). This gives a heat index of anywhere between 110-130 °F (45-54 °C). And, of course, with all that humidity, it never cooled off at night.

I mentioned smog and dust earlier. Well, the haze, smog and dust were even worse over northwestern India on 20 May 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 07:28 UTC 20 May 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 07:28 UTC 20 May 2015.

If you click on the image to see it in full resolution, you can see that the smog is trapped by the Himalayas. That means the people of Tibet are not only at more comfortable temperatures, they can also breathe fresh air.

In case you’re wondering, the dust does show up in the IR as well:

VIIRS IR (M-15) image, taken 07:28 UTC 20 May 2015

VIIRS IR (M-15) image, taken 07:28 UTC 20 May 2015.

Haze, smog, dust, unbearable heat and humidity: it’s no wonder why the people of India pray for the monsoon.

Germany’s Magic Sparkle

You may or may not have heard that a small town in Italy received 100 inches (250 cm; 2.5 m; 8⅓ feet; 8 x 10-17 parsecs) of snow in 18 hours just last week (5 March 2015). That’s a lot of snow! It’s more than what fell on İnebolu, Turkey back in the beginning of January. But, something else happened that week that is much more interesting.

All you skiers are asking, “What could be more interesting than 100 inches of fresh powder?” And all you weather-weenies are asking, “What could be more interesting than being buried under a monster snowstorm? I mean, that makes Buffalo look like the Atacama Desert!” The answer: well, you’ll have to read the rest of this post. Besides, VIIRS is incapable of measuring snow depth. (Visible and infrared wavelengths just don’t give you that kind of information.) So, looking at VIIRS imagery of that event isn’t that informative.

This is (or was, until I looked into it in more detail) another mystery. Not a spooky, middle-of-the-night mystery, but one out in broad daylight. (We can thus automatically rule out vampires.)

It started with a comparison between “True Color” and “Natural Color” images over Germany from 9 March 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 11:54 UTC 9 March 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 11:54 UTC 9 March 2015.

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 11:54 UTC 9 March 2015

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 11:54 UTC 9 March 2015.

The point was to show, once again, how the Natural Color RGB composite can be used to differentiate snow from low clouds. That’s when I noticed it. Bright pixels (some white, some orange, some yellow, some peach-colored) in the Natural Color image, mostly over Bavaria. (Remember, you can click on the images, then click again, to see them in full resolution.) Thinking they might be fires, I plotted up our very own Fire Temperature RGB:

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 from 11:54 UTC 9 March 2015

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12 from 11:54 UTC 9 March 2015.

I’ve gone ahead and drawn a white box around the area of interest. Let’s zoom in on that area for these (and future) images.

VIIRS True Color RGB (11:54 UTC 9 March 2015)

VIIRS True Color RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

VIIRS Natural Color RGB (11:54 UTC 9 March 2015)

VIIRS Natural Color RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

VIIRS Fire Temperature RGB (11:54 UTC 9 March 2015)

VIIRS Fire Temperature RGB (11:54 UTC 9 March 2015). Zoomed in and cropped to highlight the area of interest.

Now, these spots really show up. But, they’re not fires! Fires show up red, orange, yellow or white in the Fire Temperature composite (which is one of the benefits of it). They don’t appear pink or pastel blue. What the heck is going on?

Now, wait! Go back to the True Color image and look at it at full resolution. There are white spots right where the pastel pixels show up in the Fire Temperature image. (I didn’t notice initially, because white spots could be cloud, or snow, or sunglint.) This is another piece of evidence that suggests we’re not looking at fires.

For a fire to show up in True Color images, it would have to be about as hot as the surface of the sun and cover a significant portion of a 750-m pixel. Terrestrial fires don’t typically get that big or hot on the scale needed for VIIRS to see them at visible wavelengths. Now, fires don’t have to be that hot to show up in Natural Color images, but even then they appear red. Not white or peach-colored. If a fire was big enough and hot enough to show up in a True Color image, it would certainly show up in the high-resolution infrared (IR) channel (I-05, 11.45 µm), but it doesn’t:

VIIRS high-resolution IR (I-05) image (11:54 UTC 9 March 2015)

VIIRS high-resolution IR (I-05) image (11:54 UTC 9 March 2015).

You might be fooled, however, if you looked at the mid-wave IR (I-04, 3.7 µm) where these do look like hot spots:

VIIRS high-resolution midwave-IR (I-04) image (11:54 UTC 9 March 2015)

VIIRS high-resolution midwave-IR (I-04) image (11:54 UTC 9 March 2015).

What’s more amazing is I was able to see these bright spots all the way down to channel M-1 (0.412 µm), the shortest wavelength channel on VIIRS:

VIIRS "deep blue" visible (M-1) image (11:54 UTC 9 March 2015)

VIIRS “deep blue” visible (M-1) image (11:54 UTC 9 March 2015).

So, what do we know? Bright spots appear in all the bands where solar reflection contributes to the total radiance (except M-6 and M-9). I checked. (They don’t show up in M-6 [0.75 µm], because that channel is designed to saturate under any solar reflection so everything over land looks bright. They don’t show up in M-9 [1.38 µm] because solar radiation in that band is absorbed by water vapor and never makes it to the surface.) Hot spots do not coincide with these bright spots in the longer wavelength IR channels (above 4 µm).

What reflects a lot of radiation in the visible and near-IR but does not emit a lot in the longwave IR? Solar panels. That’s the answer to the mystery. VIIRS was able to see solar radiation reflecting off of a whole bunch of solar panels. That is the source of Germany’s “magic sparkle”.

Don’t believe me? First off, Germany is a world leader when it comes to producing electricity from solar panels. Solar farms (or “solar parks” auf Deutsch) are common – particularly in Bavaria, which produces the most solar power per capita of any German state.

Second: I was able to link specific solar parks with the bright spots in the above images using this website. (Not all of those solar parks show up in VIIRS, though. I’ll get to that.) And these solar parks can get quite big. Let’s take a look at a couple of average-sized solar parks on Google Maps: here and here. The brightest spot in the VIIRS Fire Temperature image (near 49° N, 11° E) matches up with this solar park, which is almost perfectly aligned with the VIIRS scans and perpendicular to the satellite track.

Third: it’s not just solar parks. A lot of people and businesses have solar panels on their roofs. Zoom in on Pfeffenhausen, and try to count the number of solar panels you see on buildings.

One more thing: if you think solar panels don’t reflect a lot of sunlight, you’re wrong. Solar power plants have been known reflect so much light they instantly incinerate birds*. (*This is not exactly true. See the update below.)

Another important detail is that all of the bright spots visible in the VIIRS images are a few degrees (in terms of satellite viewing angle) to the west of nadir. Given where the sun is in the sky this time of year (early March) and this time of day (noon) at this latitude (48° to 50° N), a lot of these solar panels are in the perfect position to reflect sunlight up to the satellite. But, not all of them. Some solar panels track the sun and move throughout the day. Other panels are fixed in place and don’t move. Only the solar panels in the right orientation relative to the satellite and the sun will be visible to VIIRS.

At these latitudes during the day, the sun is always to south and slightly to the west of the satellite. For the most part, solar panels to the east of the satellite will reflect light away from the satellite, which is why you don’t see any of those. If the panel is pointed too close to the horizon, or too close to zenith (or the sun is too high or too low in the sky), the sunlight will be reflected behind or ahead of the satellite and won’t be seen. You could say that this “sparkle” is actually another form of glint, like sun glint or moon glint – only this is “solar panel glint”.

Here’s a Natural Color image from the very next day (10 March 2015), when the satellite was a little bit further east and overhead a little bit earlier in the day:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 from 11:35 UTC 10 March 2015

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10 from 11:35 UTC 10 March 2015.

Notice the half-dozen-or-so bright spots over the Czech Republic. These are just west of the satellite track and in the same position relative to satellite and sun. (The bright spot near the borders of Austria and Slovakia matches up with this solar farm.) The bright spots over Germany are gone because they no longer line up with the sun and satellite geometry.

As for the pastel colors in the Natural Color and Fire Temperature RGBs, those are related to the proportional surface area of the solar panels relative to the size of each pixel as well as the background reflectivity of the ground surrounding the solar panels. The bright spots do generally appear more white in the high-resolution version of the Natural Color RGB from 9 March:

VIIRS high-resolution Natural Color (I-01, I-02, I-03) RGB image (11:54 UTC 9 March 2015)

VIIRS high-resolution Natural Color (I-01, I-02, I-03) RGB image (11:54 UTC 9 March 2015).

See, we learned something today. Germany sparkles with green electricity and VIIRS can see it!

UPDATES (17 March 2015): Thanks to feedback from Renate B., who grew up in Bavaria and currently owns solar panels, we have this additional information: there is a push to add solar panels onto church roofs throughout Bavaria, since they tend to be the tallest buildings in town (not shaded by anything) and are typically positioned facing east, so the south-facing roof slopes are ideal for collecting sunlight. The hurdle is that churches are protected historical buildings that people don’t want to be damaged. Also, it’s not a coincidence that many solar parks have their solar panels facing southeast (and align with the VIIRS scan direction). They are more efficient at producing electricity in the morning, when the temperatures are lower, than they are in the afternoon when the panels are warmer. They face southeast to better capture the morning sun.

Also, to clarify (as pointed out by Ed S.): the solar power plant that incinerates birds generates electricity from a different mechanism than the photovoltaic (PV) arrays seen in these images from Germany. PV arrays (aka solar parks) convert direct sunlight to electricity. The “bird incinerator” uses a large array of mirrors to focus sunlight on a tower filled with water. The focused sunlight heats the water until it boils, generating steam that powers a turbine. Solar parks and solar panels on houses and churches do not cause birds to burst into flames.

Sea-effect Snow

Take a look at this image:

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

When China Looks Like Canada

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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