UHF/VHF

Take a second to think about what would happen if Florida was hit by four hurricanes in one month.

Would the news media get talking heads from both sides to argue whether or not global warming is real by yelling at each other until they have to cut to a commercial? Would Jim Cantore lose his mind and say “I don’t need to keep standing out here in this stuff- I quit!”? Would we all lose our minds? Would our economy collapse? (1: yes. 2: every man has his breaking point. 3: maybe not “all”. 4: everybody panic! AHHH!)

It doesn’t have to just be Florida. It could be four tropical cyclones making landfall anywhere in the CONUS (and, maybe, Hawaii) in a 1-month period. The impact would be massive. But, what about Alaska?

Of course, Alaska doesn’t get “tropical cyclones” – it’s too far from the tropics. But, Alaska does get monster storms that are just as strong that may be the remnants of tropical cyclones that undergo “extratropical transition“. Or, they may be mid-latitude cyclones or “Polar lows” that undergo rapid cyclogenesis. When they are as strong as a hurricane, forecasters call them “hurricance force” (HF) lows. And guess what? Alaska has been hit by four HF lows in a 1-month period (12 December 2015 – 6 January 2016).

With very-many HF lows, some of which were ultra-strong, we might call them VHF or UHF lows. (Although, we must be careful not to confuse them with the old VHF and UHF TV channels, or the Weird Al movie.) In that case, let’s just refer to them as HF, shall we?

The first of these HF storms was a doozy – tying the record for lowest pressure ever in the North Pacific along with the remnants of Typhoon Nuri. Peak winds with system reached 122 mph (106 kt; 196 k hr-1; 54 m s-1) in Adak, which is equivalent to a Category 2 hurricane!

Since Alaska is far enough north, polar orbiting satellites like Suomi-NPP provide more than 2 overpasses per day. Here’s an animation from the VIIRS Day/Night Band, one of the instruments on Suomi-NPP:

Animation of VIIRS Day/Night Band images of the Aleutian Islands (12-14 December 2015)

Animation of VIIRS Day/Night Band images of the Aleutian Islands (12-14 December 2015).

It’s almost like a geostationary satellite! (Not quite, as I’ll show later.) This is the view you get with just 4 images per day. (The further north you go, the more passes you get. The Interior of Alaska gets 6-8 passes, while the North Pole itself gets all 15.) Seeing the system wrap up into a symmetric circulation would be a thing of beauty, if it weren’t so destructive. Keep in mind that places like Adak are remote enough as it is. When a storm like this comes along, they are completely isolated from the rest of Alaska!

Here’s the same animation for the high-resolution longwave infrared (IR) band (I-5, 11.5 µm):

Animation of VIIRS I-5 images of the Aleutian Islands (12-14 December 2015)

Animation of VIIRS I-5 images of the Aleutian Islands (12-14 December 2015).

I’ve mentioned Himawari before on this blog. Well, Himawari’s field of view includes the Aleutian Islands. Would you like to see how this storm evolved with 10 minute temporal resolution? Of course you would.

Here is CIRA’s Himawari Geocolor product for this storm:

Here is a loop of the full disk RGB Airmass product applied to Himawari. Look for the storm moving northeast from Japan and then rapidly wrapping up near the edge of the Earth. This is an example of something you can’t do with VIIRS, because VIIRS does not have any detectors sensitive to the 6-7 µm water vapor absorption band, which is one of the components of the RGB Airmass product. The RGB Airmass and Geocolor products are very popular with forecasters, but they’re too complicated to go into here. You can read up on the RGB Airmass product here, or visit my collegue D. Bikos’ blog to find out more about this storm and these products.

You might be asking how we know what the central pressure was in this storm. After all, there aren’t many weather observation sites in this part of the world. The truth is that it was estimated (in the same way the remnants of Typhoon Nuri were estimated) using the methodology outlined in this paper. I’d recommend reading that paper, since it’s how places like the Ocean Prediction Center at the National Weather Service estimate mid-latitude storm intensity when there are no surface observations. I’ll be using their terminology for the rest of this discussion.

Less than 1 week after the first HF storm hit the Aleutians, a second one hit. Unfortunately, this storm underwent rapid intensification in the ~12 hour period where there were no VIIRS passes. Here’s what Storm #2 looked like in the longwave IR according to Himawari. And here’s what it looked like at full maturity according to VIIRS:

VIIRS DNB image (23:17 UTC 18 December 2015)

VIIRS DNB image (23:17 UTC 18 December 2015).

VIIRS I-5 image (23:17 UTC 18 December 2015)

VIIRS I-5 image (23:17 UTC 18 December 2015).

Notice that this storm is much more elongated than the first one. Winds with this one were only in the 60-80 mph range, making it a weak Category 1 HF low.

Storm #3 hit southwest Alaska just before New Year’s, right at the same time the Midwest was flooding. This one brought 90 mph winds, making it a strong Category 1 HF low. This one is bit difficult to identify in the Day/Night Band. I mean, how many different swirls can you see in this image?

VIIRS DNB image (13:00 UTC 30 December 2015)

VIIRS DNB image (13:00 UTC 30 December 2015).

(NOTE: This was the only storm of the 4 to happen when there was moonlight available to the DNB, which is why the clouds appear so bright. The rest of the storms were illuminated by the sun during the short days and by airglow during the long nights.) The one to focus on is the one of the three big swirls closest to the center of the image (just above and right of center). It shows up a little better in the IR:

VIIRS I-5 image (13:00 UTC 30 December 2015)

VIIRS I-5 image (13:00 UTC 30 December 2015).

The colder (brighter/colored) cloud tops are the clue that this is the strongest storm, since all three have similar brightness (reflectivity) in the Day/Night Band. If you look close, you’ll also notice that this storm was peaking in intensity (reaching mature stage) right as it was making landfall along the southwest coast of Alaska.

Storm #4 hit the Aleutians on 6-7 January 2016 (one week later), and was another symmetric/circular circulation. This storm brought winds of 94 mph (2 mph short of Category 2!) The Ocean Prediction Center made this animation of its development as seen by the Himawari RGB Airmass product. Or, if you prefer the Geocolor view, here’s Storm #4 reaching mature stage. But, this is a VIIRS blog. So, what did VIIRS see? The same storm at higher spatial resolution and lower temporal resolution:

Animation of VIIRS DNB images of the Aleutian Islands (6-7 January 2016)

Animation of VIIRS DNB images of the Aleutian Islands (6-7 January 2016).

Animation of VIIRS I-5 images of the Aleutian Islands (6-7 January 2016)

Animation of VIIRS I-5 images of the Aleutian Islands (6-7 January 2016).

This storm elongated as it filled in and then retrograded to the west over Siberia. There aren’t many hurricanes that do that after heading northeast!

So, there you have it: 4 HF lows hitting Alaska in less than 1 month, with no reports of fatalities (that I could find) and only some structural damage. Think that would happen in Florida?

The Great Flood of 2015

As we begin 2016, struggling to get back into the swing of things at work and vowing not to overeat or over-drink ever again, it’s appropriate to bid farewell to 2015 – not just for all the weird weather events that we covered on this blog over the year, but also for the weird, wacky weather that ruined many people’s holidays. I’m not sure of the exact number, but this article mentions 43 weather-related fatalities in the U.S. in the second half of December. Let’s see, between 23-30 December 2015, there were:

–    77 tornadoes (including 38 on the 23rd and 18 on the 27th);

–    Parts of New Mexico and west Texas got over 2 ft (60 cm) of snow from a blizzard that created drifts upwards of 10 ft (3 m) on the 27th;

–    Record warmth was observed in the Northeast before and during Christmas and the site of Snowvember went until 18 December before the first measurable snow of the season;

–    Chicago received almost 2″ of sleet (48 mm) on the 29th when any accumulation of sleet is quite rare;

–    And – what will be our focus here – St. Louis received over 3-months-worth of precipitation in three days (26-28 December), from a storm that flooded a large area of Missouri, Illinois and Arkansas. In fact, the St. Louis area had the wettest December on record, right after having the 7th wettest November on record, which put it over the top for wettest calendar year on record. Current estimates place 31 fatalities at the hands of this flooding, which caused the Mississippi River to reach its highest crest since the Great Flood of 1993.

What kind of satellite imager would VIIRS be if it couldn’t detect massive flooding on the largest river in North America? (Hint: not a very useful one. Or, a less useful one, if you’re not into hyperbole.) Hey, if it works in Paraguay, it works here – or it isn’t science!

I shouldn’t have to prove that the Natural Color RGB is useful for detecting flooding (since I have done it many, many, many, many, many, many times before), so we can go right to the imagery. Here’s what the Midwest looked like on 13 November 2015 – before the flooding began:

VIIRS Natural Color RGB composite of channels I-1, I-2, and I-3 (19:02 UTC 13 November 2015)

VIIRS Natural Color RGB composite of channels I-1, I-2, and I-3 (19:02 UTC 13 November 2015).

And, here’s what the same area looked like on New Year’s Day:

VIIRS Natural Color RGB composite of channels I-1, I-2, and I-3 (18:45 UTC 1 January 2016)

VIIRS Natural Color RGB composite of channels I-1, I-2, and I-3 (18:45 UTC 1 January 2016).

Notice anything different? This is actually the reverse of the last time we played “Spot the Differences” – we’re looking for where water is now that wasn’t there before, instead of searching for bare ground that used to have water on it.

Of course, the first thing to notice is the large area of snow covering Iowa, Nebraska and northwest Missouri that wasn’t there back in November. Next, we have more clouds over the southern and northern parts of the scene. Those are the easy differences to spot. Now look for the Missouri River in eastern Missouri, the Arkansas River in Arkansas, the Illinois River in Illinois, the Indiana River in Indiana… Wait! There is no Indiana River. I fooled you! (Although, there are rivers in Indiana that are flooded.)

The most significant areas of flooding are in northeast Arkansas and the “Bootheel” of Missouri (which I think looks more like a toe or a claw than a heel), and the Mississippi River along the border of Tennessee shows signs of significant flooding as well. (If only it were the Tennessee River!) Here’s a before and after comparison, zoomed in on that part of the region:

13 November 20151 January 2016

You may have to refresh the page to get this to work right.

There’s a lot more water in the image from 1 January 2016 than there was back in November 2015! Since we are looking at the high-resolution Imagery bands, our quick-and-dirty estimate of water volumes still applies like it did for California’s drought: multiply the number of water-filled pixels by the depth (in feet) of the flooding, and by 100 acres to get the floodwater volume in acre-feet. Then multiply that by 325,852 gallons per acre-foot to get the volume in gallons. Even though this estimate is not exact, you can see how the gallons of floodwater add up. And, if you live in California, you can dream of seeing that much water! If you live in Missouri and can think of an economical way to transport this water to California, you’d be rich.

Now, see how many other areas of flooding you can find when you compare the two images in animation form:

Animation of VIIRS Natural Color RGB images from 13 November 2015 and 1 January 2016

Click to view an animation of VIIRS Natural Color RGB images from 13 November 2015 and 1 January 2016.

You will have to click on the image to see the animation. You can click on the image again to see it in full resolution (with most web browsers).

One thing you might notice is that some of the floodwaters appear more blue than black. Take a look at the Arkansas River in particular. As we discussed with the Rio Paraná and Rio Paraguay, this is due to the increased sediment that increases the albedo of the water at visible wavelengths. In other places the floodwaters are shallow enough that VIIRS can see the ground underneath – again making the water appear more blue in this RGB composite.

Wouldn’t it be nice to identify areas of flooding without having to play a “Spot the Differences” game? Maybe something that would automatically detect flooded areas? Well, you’re in luck:

VIIRS-based Flood Map (18:48 UTC 1 January 2016)

VIIRS-based Flood Map (18:48 UTC 1 January 2016). Image courtesy S. Li (GMU).

This image is an example of the VIIRS-based flood detection product being developed by the JPSS Program’s River Ice and Flooding Initiative. This initiative is a collaboration between university-based researchers and NOAA forecasters who use products like these to help save lives. Thanks to S. Li for developing the product for and providing the image!

If you want to know what the flooding looks like from the ground, here is a nice video. Or, you can look at some pictures here.

As a final note, the American Meteorological Society is holding its Annual Meeting in New Orleans next week. This event will be held at the Convention Center – right on the bank of the Mississippi River – right at the time the river is forecast to crest from these floodwaters. The world’s largest gathering of weather enthusiasts might be directly impacted by this flood. Let’s hope no one has to swim their way to any poster sessions or keynote speeches! (I don’t think local residents want to deal with any flooding, either.)

Indian Super-Smog

We’ve poked a lot of fun at China and their serious smog problem. (Just this week, Beijing schools had their very first “smog day.” It’s just like a “snow day”, except you can’t go outside and write your name in it.) But, as it turns out, China is not the only country to produce super-thick smog. India does it, too. And, from the point of view of human health, India’s smog may actually be worse!

The World Health Organization just released a list of the Top 20 smoggiest cities, and 13 of them are in India (plus 1 in Bangladesh and 3 in Pakistan). Not a single Chinese city was anywhere in the Top 20! I’d consider taking back some of things I’ve said about China, except that 1) I never lied (although I did quote Brian Williams), and 2) the Chinese government is now instituting “smog days” because the smog is so bad. What I will do is stop comparing every type of air pollution to Chinese smog. From now on (at least until they start making some positive changes), India is the paragon of poor air quality on this blog.

Since VIIRS has no trouble seeing Chinese smog, it should have no problem seeing Indian smog. And it doesn’t:

VIIRS True Color RGB composite of channels M-4, M-4 and M-5 (07:14 UTC 18 November 2015)

VIIRS True Color RGB composite of channels M-4, M-4 and M-5 (07:14 UTC 18 November 2015).

You guessed it: all that gray area is optically thick smog! Let’s not forget, too, that India is the seventh largest country in world (2.4% of the Earth’s total surface area!), which is quite a large area to be covered by smog.

In the True Color image above from 18 November 2015, you can see that the people of Tibet are grateful for the Himalayas, which are an effective barrier to the smog. They may not get much air up there on the highest plateau in the world, but what little there is is much cleaner than what’s down below!

If your respiratory system is sensitive to this kind of thing, you might not want to read any further. Consider this your trigger warning. For those few brave enough to continue – prepare yourself, because it gets worse!

Here’s another VIIRS True Color image from 14 November 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:50 UTC 14 November 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:50 UTC 14 November 2015).

Now it’s even harder to see the background surface along the base of the Himalayas. And, it’s easy to compare India’s pollution with Burma’s – I mean Myanmar’s – clean air.

VIIRS passed over the center of India on 11 November 2015 and saw that almost the entire country was covered by smog, with the thickest smog near Delhi:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:46 UTC 11 November 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:46 UTC 11 November 2015).

November 11th was the night of Diwali, the Hindu, Sikh and Jain “Festival of Lights” celebrating the “triumph of goodness over evil and knowledge over ignorance.” If you clicked that link and thought, “that doesn’t look so bad,” then note that the first few pictures were taken in England. In India, it was much smokier. I guess lighting all those fireworks in India comes with this “pro”: they can light the way through the thick smog; and this “con”: they give off smoke that adds to the thick smog. And, while the smog didn’t stop people from celebrating Diwali, it did affect people’s plans. It also caused a huge increase in the market for air purifiers.

The super-smog was not confined to November or Diwali. It’s still going on! Here’s a VIIRS image from 5 December 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:56 UTC 5 December 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:56 UTC 5 December 2015).

I assure you that India and Bangladesh are under there somewhere beneath all that gray muck!

As I mentioned in the previous post, we now have access to data from the new Japanese satellite, Himawari, which can be thought of as a geostationary version of VIIRS. Himawari-8 hangs out over the Equator at a longitude of 140 °E and it takes images of the full disk every 10 minutes. From its perspective, India is right on the edge of the Earth (which, in satellite meteorology is called “the limb”). This means Himawari’s line-of-sight to India has an extra long path through the atmosphere, and that makes the smog look even worse. Here’s a True Color/Geocolor loop of Himawari images of India’s “Worse-than-China” Super-Smog. You can find this and other amazing loops on our new “Himawari Loop of the Day” webpage. We also produce a lot of other Himawari imagery products, which we post here.

Shameless plugs aside, don’t forget: India’s smog is actually worse than China’s. And, unless you live in India, you probably didn’t think that was possible! (If you do live in India, get them to clean up the air!)

(What’s the Story) Middle-of-the-Night Glory?

A Morning Glory is a lot of things: a flower, a town in Kentucky, a popular choice for song and album titles, and – what is most relevant for us – it’s a rare atmospheric phenomenon that is both beautiful and potentially deadly.

For glider pilots, it’s the atmospheric equivalent to catching a 40-wave off the North Shore of Oahu. Like surfing the North Shore, the thrill is in catching a powerful wave and going for a ride, which only happens if you position yourself in the right spot. And, just like surfing a monster wave, one misstep can result in being crushed downward into a pile of jagged rocks and swept out to sea. The difference is, a North Shore wave is 10-12 m high and only travels a 100 m or so until it hits land and stops. A Morning Glory wave is 500-1000 m high and can travel hundreds of kilometers over a period of several hours. Here’s a picture of one:

MorningGloryCloudBurketownFromPlane

“MorningGloryCloudBurketownFromPlane” by Mick Petroff – Mick Petroff. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:MorningGloryCloudBurketownFromPlane.jpg#/media/File:MorningGloryCloudBurketownFromPlane.jpg

Simply put, a Morning Glory is a solitary wave, or “soliton“. We talked about mesospheric bores before, which are another kind of soliton. In this case, however, the soliton propagates through (or along the top of) the atmosphere’s boundary layer. Sometimes, it produces a cloud or series of clouds that came to be known as a “Morning Glory” because these clouds commonly occur near sunrise in the one place on Earth where this event isn’t rare.

Enough talk. The Day/Night Band (DNB) on VIIRS just saw a one. Let’s see if you can see it:

VIIRS DNB image of Australia (15:24 UTC 26 October 2015)

VIIRS DNB image of Australia (15:24 UTC 26 October 2015)

This really is like “Where’s Waldo?” because the image covers a much larger area than the Morning Glory. Even I didn’t see it at first. But, zoom in to the corner of the image over the Gulf of Carpentaria. (You can click on any of these images to see the full resolution version.) Now do you see it?

VIIRS DNB image of the Gulf of Carpentaria (15:24 UTC 26 October 2015)

VIIRS DNB image of the Gulf of Carpentaria (15:24 UTC 26 October 2015)

Once more on the zoom, and it’s obvious:

Same as above, but zoomed in on the Morning Glory.

Same as above, but zoomed in on the Morning Glory.

But, this happened at ~1:30 AM local time – depending on where in that image you are looking – so maybe it’s a Middle-of-the-Night Glory instead of a Morning Glory. (Fun fact: Northern Territory and South Australia are on a half-hour time zone, GMT+9:30. Queensland and the rest of eastern Australia are at GMT+10:00. But, the southern states have Daylight Saving Time while the north and west do not. That means almost every state has it’s own time zone.)

The Gulf of Carpentaria is where Morning Glory clouds are most likely to form. And, this is the peak season for them. (The season runs from late August to mid-November.) What is rare is seeing them so clearly at night.

Since this image was taken one night before a full moon, there was plenty of moonlight available to the DNB to see the “roll clouds” that are indicative of the Morning Glory. You can even see ripples that extend beyond the endpoints of the clouds, which might be some kind of aerosol plume affected by the waves.

There is another way to see this Morning Glory, and it’s what we call the “low cloud/fog product”. The low cloud/fog product is simply the difference in brightness temperature between the longwave infrared (IR) (10.7 µm) and the mid-wave IR (3.9 µm). For low clouds, this difference is positive at night and negative during the day. Here is an example of the low cloud/fog product applied to a new geostationary satellite, Himawari-8:

Animation of AHI Low Cloud/Fog product images (10:00 - 22:50 UTC 26 October 2015)

Animation of AHI Low Cloud/Fog product images (10:00 – 22:50 UTC 26 October 2015)

The Advanced Himawari Imager (AHI) on Himawari-8 is similar to VIIRS, except it has water vapor channels in the IR and it doesn’t have the Day/Night Band. It also stays in the same place relative to the Earth and takes images of the “full disk” every 10 minutes. That’s what allows you to see – in impressive detail – the evolution of this Morning Glory. The low, liquid clouds switch from white to black after sunrise because, as I said, the signal switches from positive (white) to negative (black) at sunrise. Ice clouds (e.g. cirrus) always look black in this product.

Here’s a zoomed in version of the above animation:

As above, except zoomed in to highlight the Morning Glory

As above, except zoomed in to highlight the Morning Glory

Of course, once the sun rises, the standard visible imagery from AHI captures the tail end of the Morning Glory:

Animation of AHI Band 3 images (20:00 - 23:30 UTC 26 October 2015)

Animation of AHI Band 3 images (20:00 – 23:30 UTC 26 October 2015)

And, once again, zoomed in:

As above, except zoomed in to highlight the Morning Glory

As above, except zoomed in to highlight the Morning Glory

At this point, it really is a Morning Glory, since it appeared at sunrise. Of course, at night, only the VIIRS Day/Night Band under full moonlight can show it in “all of its glory”. (Pun definitely intended.)

Pilots take note: the waves can still exist even when the clouds evaporate, and they are a source of severe turbulence.

If you want to know more about the phenomenon, watch this video with a lot of information or this video with a lot of pretty pictures. And, while a lot of people believe the cause of the Morning Glory is still a mystery, one scientist in Germany thinks the cause is now known. You can read all about his and other’s research into the science behind these solitary waves at this webpage.

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.