The Sirocco and the Giant Bowl of Dust

As mentioned before on this blog, there are typhoons, hurricanes, and cyclones, and they’re all basically the same thing. They’re just given a different name depending on where they occur in the world. Similarly, there are many different names for winds (not counting the classification of wind speeds developed by a guy named Beaufort). There’s the Chinook, the Santa Ana, the bora, the föhn (or foehn), the mistral, the zonda, the zephyr and the brickfielder. (A more complete list is here.) Some of these winds are different names for the same phenomenon occurring in different parts of the world, like the föhn, the chinook, the zonda and the Santa Ana. Others are definitely different phenomena, with different characteristics (compare the mistral with the brickfielder), but they all have the same basic cause: the atmosphere is constantly trying to equalize its pressure.

The Mediterranean is home to wide variety of named winds, one of which is the sirocco (or scirocco). (Europe is home to wide variety of languages, so this wind is also known as “ghibli,” “jugo” [pronounced “you-go”], “la calima” and “xlokk” [your guess is as good as mine].) Sirocco is the name given to the strong, southerly or southeasterly wind originating over northern Africa that typically brings hot, dry air and, if it’s strong enough, Saharan dust to Europe. Of course, after picking up moisture from the Mediterranean, the wind becomes humid, making life unpleasant for people along the north shore. Hot, humid and full of dust. Perhaps it’s no surprise that the sirocco is believed to be a cause of insomnia and headaches.

Now, I don’t know how hot it was, but an intense low pressure system passed through the Mediterranean around Leap Day and, out ahead of it, strong, southerly winds carried quite a bit of dust from northern Africa into Italy.  Here’s what it looked like in Algeria. And here’s what it looked like in Salento. See if you can see that dust in these True Color VIIRS images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:09 UTC 28 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:09 UTC 28 February 2016).

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (11:48 UTC 29 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (11:48 UTC 29 February 2016)

No problem, right? With True Color imagery, the dust is usually easy to identify and distinguish from clouds and the ocean because it looks like dust. It’s the same color as the sky over Salento, Italy in that video I linked to. The top image shows multiple source regions of dust (mostly Libya, with a little coming from Tunisia) being blown out over the sea. The second image shows one concentrated plume being pulled into the clouds over the Adriatic Sea, headed for Albania and Greece.

By the way, this storm system brought up to 2 meters (6.5 feet) of snow to northern Italy, and even brought measurable snow to Algeria! Africa and Europe made a trade: you take some of my dust, and I’ll take some of your snow.

But, this wasn’t the worst dust event to hit Europe recently. Here’s what the VIIRS True Color showed over Spain and Portugal on 21 February 2016:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:40 UTC 21 February 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (12:40 UTC 21 February 2016).

And VIIRS wasn’t the only one to see this dust. Here’s a picture taken by Tim Peake, an astronaut on the International Space Station. Again, it’s easy to pick out the dust because it almost completely obscures the view of the background surface. But, what if the background surface is dust colored?

We switch now to the other side of the world and the Takla Makan desert in China, where the dust has been blowing for the better part of a week:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:11 UTC 4 March 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:11 UTC 4 March 2016).

Can you tell what is dust and what is the desert floor? Can you see the Indian Super Smog on the south side of the Himalayas? Here is the same scene on a clear (no dust) day:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:49 UTC 2 March 2016)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:49 UTC 2 March 2016).

There is a subtle difference there, but you need good eyesight to see it. It might be easier to see if you loop the images:

Animation of VIIRS True Color images (1-7 March 2016)

Animation of VIIRS True Color images of the Takla Makan desert (1-7 March 2016).

You’ll have to click on the image to see it animate.

Did you notice the dark brown areas surrounding the Takla Makan? Those are areas that have green vegetation during the summer. Notice how they become completely obscured by the dust as the animation progresses. That’s one one way to tell that there’s dust there. But, as we have seen before, there are other ways to see the dust.

There’s EUMETSAT’s Dust RGB composite applied to VIIRS:

Animation of VIIRS EUMETSAT Dust RGB images (1-7 March 2016)

Animation of VIIRS EUMETSAT Dust RGB images of the Takla Makan desert (1-7 March 2016).

That’s another animation, by the way, so you’ll have to click on it to see it animate. The same is true for the Dynamic Enhanced Background Reduction Algorithm (DEBRA), which we also talked about before:

Animation of VIIRS DEBRA Dust Product images (1-7 March 2016)

Animation of VIIRS DEBRA Dust Product images of the Takla Makan desert (1-7 March 2016)

But, there’s one more dust detection technique we have not discussed before: the “blue light absorption” technique:

Animation of VIIRS Blue Light Dust images (1-7 March 2016)

Animation of VIIRS Blue Light Dust images of the Takla Makan desert (1-7 March 2016).

The Blue Light Dust detection algorithm keys in on the fact that many different kinds of dust absorb blue wavelengths of light more than the longer visible wavelengths. It uses this information to create an RGB composite where dust appears pastel pink, clouds and snow appear blueish and bare ground appears green. Of course, other features can absorb blue light as well, like the lakes near the northeast corner of the animation that show up as pastel pink. But, depending on your visual preferences and ability to distinguish color, the Blue Light Dust product gives another alternative to the hot pink of the EUMETSAT Dust RGB, the yellow of DEBRA, and the slightly paler tan of the True Color RGB.

One question you might ask is, “How come DEBRA shows a more vivid signal than the other methods?” In the True Color RGB, dust is slightly more pale than the background sand, because it’s made up of (generally) smaller sand particles (which are more easily lofted by the wind) that scatter light more effectively, making it appear lighter in color. In the EUMETSAT Dust RGB, dust appears hot pink because the “split window difference” (12 µm – 10.7 µm) is positive, while the difference in brightness temperatures between 10.7 µm and 8.5 µm is near zero and the background land surface is warm. In DEBRA, the intensity of the yellow is related to the confidence that dust is present in the scene based on a series of spectral tests. DEBRA is confident of the presence of dust even when the signals may be difficult to pick out in the other products, either because it’s a superior product, or because its confidence is misguided. (Hopefully, it’s the former and not the latter.)

By the way, the Takla Makan got its name from the native Uyghurs that live there. Takla Makan means “you can get in, but you can’t get out.” It has also been called the “Sea of Death.” I prefer to call it “China’s Big Bowl of Dust.” It’s a large area of sand dunes (bigger than New Mexico, but smaller than Montana) surrounded on most of its circumference by mountains between 5000 and 7000 m (~15,000-21,000+ feet!). The average annual rainfall is less than 1.5 inches (38 mm). That means when the wind blows it easily picks up the dusty surface, but that dust can’t go anywhere because it’s blocked by mountains (unless it blows to the northeast). The dust is trapped in its bowl.

The Takla Makan is also important historically, because travelers on the original Silk Road had to get around it. Notice on this map, there were two routes: one that skirted the northern edge of the Takla Makan and one that went around the southern edge. This part of Asia was the original meeting point between East and West.

CIRA produces all four imagery products over the Takla Makan desert in near-real time, which you can find here. And, in case you’re curious, you can check out how well DEBRA and the EUMETSAT Dust products compare for the dust-laden siroccos over southern Europe and northern Africa by clicking here and here (for the first event over Spain and Portugal) or here and here (for the second one over Italy and the Adriatic Sea).

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!)

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.

Goose Lake is Gone (Again)

We’ve covered mysteries before on this website. Well, here’s one from 150 years ago:

The emigrants, coming west on the Applegate Trail to Oregon in the 1870s, were puzzled. The trail was, of course, a seemingly unending set of wagon-wheel ruts stretching from the jumping-off points in the Midwest over deserts and mountains and all sorts of obstacles that seemed insurmountable, but weren’t.

But this one seemed impossible. Had the wagons before them really plunged directly into the enormous lake that lay before them? The ruts led directly into the water, and there was no sign of them having come out again.

It was miles across – the other side lay almost invisible on the horizon, much too far to float a caulked wagon. And yes, it was deep – far too deep to ford.

There was nothing for it but a trip around the lake, since the western sky lay on the other side. And so, around they went – making a detour of something like 100 miles.

On the other side, they found the wagon ruts again. They emerged from the water and headed on westward toward the Cascades. Once arrived at the West Coast, none of the previous emigrants knew anything about any lake there.

Was it aliens who came down to Earth to put a lake where there was none before? Did the earlier emigrants have covered wagon submarine technology (and very short term memories)? Maybe it was a very localized, very short-term Ice Age – a glacier snuck down from the Cascades and into the valley in the middle of the night and then melted without anyone noticing. What about that?

SPOILER ALERT: None of those theories is true. Anyone who would come up with these ridiculous ideas should be ashamed of themselves. Oh, wait – I came up with them. Hmmm. What I meant to say is: those are all good theories that are worthy of scientific exploration. Unfortunately, VIIRS wasn’t around in the 1870s. Plus, this mystery has already been solved. As our source explains:

It remained a mystery until, several years later, a drought struck and the lake dried up again.

What we’re talking about is Goose Lake, which is at times the largest lake that’s at least partially in Oregon. (In terms of surface area, not volume.) It’s right on the border between Oregon and California. When Goose Lake is at its fullest, it has a surface area of 147 square miles (380 km2), but it’s only 26 ft (8 m) deep. Maybe, if the emigrants weren’t so cowardly, they could have walked across it (although they might have gotten stuck in the mud). It would have saved 100 miles of extra walking (although they might have gotten stuck in the mud).

As you are probably well aware, California and Oregon are under a long-lasting, extreme drought. So, if you live near Goose Lake, it’s probably no surprise that the lake has dried up again. And, since this is 2015, VIIRS can tell us something about it this time.

Have you ever played one of those “spot the differences” games? (Don’t play them at work, or you’ll never get anything done.) Well, here’s a “spot the differences” game you can play at work – at least if your work involves detecting evidence of drought.

Here’s what Goose Lake looked like three years ago, according to VIIRS Natural Color imagery:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (20:40 UTC 15 July 2012)

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (20:40 UTC 15 July 2012)

Note that it’s not as dark in color as the other lakes because it is so shallow. Now, here’s the same scene just last week:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (21:40 UTC 16 July 2015)

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3 (21:40 UTC 16 July 2015)

Notice anything different? Now, for this spot-the-differences game, we’re going to ignore clouds, because they are always going to be different between the two images, difficult to count, and irrelevant to this discussion. (Except that clouds can obscure the view of a lake and can cast shadows that look like lakes.)

Since I labelled Goose Lake on those images, you have no excuse for not spotting that difference. Besides, if you can’t see that 147 square miles of lake surface are missing from the second image, you have no hope to see any of the other differences.

I counted at least 20 lakes or reservoirs that are present in the 2012 image that have dried up and vanished in the 2015 image. Plus, there are about as many lakes or reservoirs that have noticeably shrunk since 2012. Can you spot them all? Can you see more than I did?

After you’ve declared yourself done, compare your results with mine:

Comparison of the above VIIRS Natural Color images of Goose Lake.

Comparison of the above VIIRS Natural Color images of Goose Lake.

As always, click on it to see the full resolution image. I’ve marked with red arrows those lakes that are visible in the 2012 image that are not visible in the 2015 image. Yellow arrows indicate the lake has lost surface area (but not totally vanished) between 2012 and 2015. And, there are a few spots that look like surface water visible in the 2015 image that are not present in 2012 – I’ve marked those with green arrows. There are a couple of lakes visible in the 2012 image that are covered by clouds in the 2015 image. Those are left unmarked. I’ve also labelled a burn scar left over from a pretty big wildfire in south-central Oregon visible in 2012 that has since disappeared. That’s the main non-lake, non-cloud related difference between the two images.

Most notably, Upper Alkali Lake (southeast of Goose Lake) dried up, which you should have noticed without me pointing it out. Drews Reservoir on the northwest side of Goose Lake in Oregon appears to have dried up, as does New Year Lake right across the border from Upper Alkali Lake in Nevada. Thompson Reservoir (the northernmost red arrow) looks bone dry and Gerber Reservoir (west of Drews Reservoir) has very little water left. The eastern half of Clear Lake Reservoir is now empty and the western half is significantly reduced in size. Three big reservoirs (lakes) on the southern edge of the image have also lost quite a bit of water (Trinity Lake, Shasta Lake and Eagle Lake).

Even if you don’t care that a bunch of salty, alkaline lakes in rural Jefferson (as they might prefer you to call it) have dried up, you should care about the reservoirs. And not just for the boating and other water recreation activities, which are now hazardous. When towns run out of water, prime agricultural land lays fallow, and Tom Selleck gets in trouble with the law, you know things are serious.

The reservoirs closer to central California are down quite a bit as well, and these impact a lot of people. Use your honed-in spot-the-difference skills in these VIIRS I-2 (0.865 µm) images from the same dates and times as the above images:

VIIRS I-2 image (20:40 UTC 15 July 2012)

VIIRS I-2 image (20:40 UTC 15 July 2012)

VIIRS I-2 image (21:40 UTC 16 July 2015)

VIIRS I-2 image (21:40 UTC 16 July 2015)

I-2 is one of the components of the Natural Color imagery (the green component). What makes it good for this purpose is that land and, particularly, vegetation are highly reflective at this wavelength, so they appear bright. Water is absorbing, so it appears black (or nearly so if the water’s dirty or shallow). It also has 375 m resolution at nadir. If you click to the full resolution versions of the above images, you can see that most of the reservoirs have lost quite a bit of surface area between 2012 and 2015.

If you’re too lazy, or have poor eyesight, click on this image below to better compare the two images:

Comparison of VIIRS I-2 images from the same dates and times as above

Comparison of VIIRS I-2 images from the same dates and times as above

One more point that needs to be made: 375 m resolution at nadir is good for weather satellites like VIIRS, but the fact that you can see the loss of water in these images is testimony to how bad this drought is!

As you may or may not know, the resolution of VIIRS in these images degrades from 375 m at nadir to 750 m at the edge of the swath. As a reasonable approximation, that’s means each pixel is a quarter mile to a half mile wide. That means each pixel of missing water represents between 40 and 160 acres. We’ll say 100 acres, given that these images were taken roughly halfway between nadir and edge of scan. If the water was only 1 foot deep in these pixels, that would be a loss of 100 acre-feet. That’s 32.5 million gallons of water. (By the way, the average household uses between 0.5 and 1 acre-foot per year in water.)

Multiply the number of pixels that have lost water by 100 to get the area in acres. Multiply that by the average depth of the water lost to get the volume in acre-feet. And then multiply that by 325,852 gallons per acre-foot and that’s a lot of gallons of missing water!

(In case you’re interested, this PDF document says the average depth of Goose Lake is 8 ft. At 147 sq. mi. of surface area, that’s 245 billion gallons of water gone, give or take.)