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” by Mick Petroff – Mick Petroff. Licensed under CC BY-SA 3.0 via Commons –

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.

UPDATE (12/16/2016): We’ve seen more examples of Morning Glory waves and clouds with Himawari-8. The formation of two Morning Glory waves may be seen on our Himawari Loop-of-the-Day webpage here and here. Plus, there is an extended loop covering a two day period shown in this very large animated GIF (83 MB).

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.)

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.