JPSS (SNPP and NOAA-20)

The Great Flood of 2015

Posted on January 5, 2016 by Curtis Seaman

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 23^rd and 18 on the 27^th);

– 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 27^th;

– 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 29^th 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).

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).

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:

[beforeafter][/beforeafter]

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:

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). 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.)

Posted in Uncategorized | Tagged Arkansas, false color, flood, I-1, I-2, I-3, Illinois, Indiana, Missouri, Natural Color, resolution, RGB composite, Tennessee | Comments Off

Indian Super-Smog

Posted on December 8, 2015 by Curtis Seaman

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).

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).

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).

November 11^th 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).

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!)

Posted in Uncategorized | Tagged Himawari, India, M-3, M-4, M-5, RGB composite, smog, true color | 1 Comment

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

Posted on October 28, 2015 by Curtis Seaman

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 – 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)

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)

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

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)

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

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)

And, once again, zoomed in:

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).

Posted in Uncategorized | Tagged AHI, Australia, clouds, day/night band, gravity waves, Himawari, Morning Glory, roll cloud | Comments Off

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

Posted on September 15, 2015 by Curtis Seaman

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)

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)

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)

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)

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)

Next, the EUMETSAT Dust RGB:

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)

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)

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

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

Posted in Uncategorized | Tagged Cyprus, day/night band, DEBRA, dust, Egypt, EUMETSAT Dust, false color, Jordan, Lebanon, M-14, M-15, M-16, M-3, M-4, M-5, Middle East, RGB composite, Saudi Arabia, Sudan, Syria, true color | Comments Off

Goose Lake is Gone (Again)

Posted on July 24, 2015 by Curtis Seaman

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)

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)

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.

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 (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

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.)

Posted in Uncategorized | Tagged California, drought, false color, I-1, I-2, I-3, Natural Color, Nevada, Oregon, resolution, RGB composite | Comments Off

The Great Indian Heat Wave of 2015

Posted on June 1, 2015 by Curtis Seaman

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 31^st. 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. 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.

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.

[beforeafter][/beforeafter]
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.

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.

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

Posted in Uncategorized | Tagged dust, India, IR window, RGB composite, saturation, smog, true color | Comments Off

The Aurora Seen Around The World

Posted on April 22, 2015 by Curtis Seaman

Think back to St. Patrick’s Day. Do you remember what you were doing? Hopefully you were wearing something green. And, hopefully, you didn’t leave anything green in the gutter behind the bar (e.g. undigested lunch or beverages or a mixture of the two). If you did, we don’t want to hear about it. It’s unpleasant enough that you had to read that and have that image in your mind. Apologies if you are eating.

If your mind was lucid enough that night, or the following night, did you remember to look up to the northern sky? Or, right above you, if you live far enough north? (Swap “north” for “south” if you live in the Southern Hemisphere. Everything is backwards there.) Was it a clear night?

If you answered “no” to the first two questions and “yes” to the third question, you missed out on an opportunity to see something green in the sky – one of the great atmospheric wonders of the world: the aurora. If you answered “yes” then “no”, tough luck. The lower atmosphere does not always cooperate with the upper atmosphere. If you answered “yes” on everything and still didn’t see the aurora, then you need to move closer to your nearest magnetic pole. Or, away from light pollution. (Although, truth be told, it is possible to live too far north or south to see the aurora. But, not many people live there. Those who do rarely have to worry about light pollution.)

If you forgot to look up at the night sky on 17-18 March 2015, you have no excuse. The media was hyping the heck out of it. That link is just one example of media predictions of the aurora being visible as far south as Dallas and Atlanta. While I couldn’t find any photographic evidence that that actually happened, there were people as far south as Ohio, Pennsylvania and New Jersey that saw the aurora. In the other hemisphere – the backwards, upside-down one – the aurora was seen as far north as Australia and New Zealand, which is a relatively rare occurrence for them. And there are no shortage of pictures and videos if you want proof: pictures, more pictures, even more pictures, video and pictures, video, and a couple more short videos here, here and here.

Now, we already know that VIIRS can see the aurora. We’ve covered both the aurora borealis and aurora australis before. This time, we’ll take a look at both at the same time – not literally, of course! – since the Day/Night Band viewed the aurora (borealis and australis) on every orbit for an entire 24 hour period, during which time it covered every part of the Earth. So, follow along as VIIRS circled the globe in every sense of the word during this event.

First, we start with the aurora australis over the South Pacific, south of Pitcairn Island, at 10:15 UTC on 17 March 2015. We then proceed westward, ending over the South Pacific, south of Easter Island at 08:16 UTC on 18 March 2015. Click on each image in the gallery to see the medium resolution version. Above each of those images is a link containing the dimensions of the high resolution version. Click on that to see the full resolution.

: VIIRS DNB image of the aurora australis, 10:15 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 11:58 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 13:35 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 15:14 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 16:55 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 18:39 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 20:20 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 22:02 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 23:46 UTC 17 March 2015.

: VIIRS DNB image of the aurora australis, 01:27 UTC 18 March 2015.

: VIIRS DNB image of the aurora australis, 03:10 UTC 18 March 2015.

: VIIRS DNB image of the aurora australis, 04:52 UTC 18 March 2015.

: VIIRS DNB image of the aurora australis, 06:32 UTC 18 March 2015.

: VIIRS DNB image of the aurora australis, 08:16 UTC 18 March 2015.

Notice how much variability there is in the spatial extent and shape of the aurora from one orbit to the next. Everything is represented, from diffuse splotches to well-defined ribbons (which are technical terms, of course, wink, wink). You can see just how close the aurora was to being directly over Australia and New Zealand. And, if you looked at the high resolution versions of all the images (which are very large), you might have seen this:

VIIRS DNB image of the aurora australis, 18:39 UTC 17 March 2015.

Just below center, the aurora is illuminating gravity waves forced by Heard Island. The aurora is also directly overhead of it’s “twin”, “Desolation Island” (aka Îles Kerguelen, upper-right corner right at the edge of the swath), although it looks too cloudy for the scientists and penguins living there to see it. (How many more Remote Islands can I mention that I’ve featured before?)

Now, I’m a sucker for animations, so I thought I’d combine all of these images into one and here it is (you can click on it to see the full-resolution version):

Animation of VIIRS DNB images of the aurora australis, 17-18 March 2015.

Here, it is easier to notice that the aurora is much further north (away from the South Pole) near Australia and New Zealand and further south (closer to the pole) near South America. This is proof that the geomagnetic pole does not coincide with the geographic pole. This also puts the southern tips of Chile and Argentina at a disadvantage when it comes to seeing the aurora, compared to Australia and New Zealand.

Now, repeat everything for the aurora borealis – beginning over central Canada (07:57 UTC 17 March 2015) and ending there ~24 hours later (07:40 UTC 18 March 2015):

: VIIRS DNB image of the aurora borealis, 07:57 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 09:37 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 11:19 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 12:59 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 14:40 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 16:21 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 18:02 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 19:45 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 21:26 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 23:08 UTC 17 March 2015.

: VIIRS DNB image of the aurora borealis, 00:52 UTC 18 March 2015.

: VIIRS DNB image of the aurora borealis, 02:33 UTC 18 March 2015.

: VIIRS DNB image of the aurora borealis, 04:11 UTC 18 March 2015.

: VIIRS DNB image of the aurora borealis, 05:56 UTC 18 March 2015.

: VIIRS DNB image of the aurora borealis, 07:40 UTC 18 March 2015.

Basically, if you were anywhere in Siberia where there were no clouds, you could have seen the aurora. (For those who are not impressed, Siberia is a big area.) Did you see the aurora directly over North Dakota? (I showed a video of that above.) Did you notice it was mostly south of Anchorage, Alaska? (Typically, it’s over Fairbanks.) It was pretty close to Moscow and Scotland, also. But, what about the sightings in Ohio, New Jersey, and Germany? It doesn’t look like the aurora was close to those places…

For one, the aurora doesn’t have to be overhead to see it. Depending on the circumstances (e.g. auroral activity, atmospheric visibility, light pollution, etc.), you can be 5 degrees or more of latitude away and it will be visible. Second, these are single snapshots of an aurora that is constantly moving. (We already know the aurora can move pretty fast.) It may have been closer to these places when VIIRS wasn’t there to see it.

Lastly, here’s an animation of the above images, moving in the proper clockwise direction, unlike in that backwards, upside-down hemisphere:

Animation of VIIRS DNB images of the aurora borealis, 17-18 March 2015.

If you want to know more about what causes the aurora, watch this video. If you want to know why auroras appear in different colors, read this. If you want to know why aboriginal Australians viewed the aurora as an omen of fire, blood, death and punishment, and why various Native American tribes viewed the aurora as dancing spirits that were happy, well, you have a lot more reading to do: link, link and link.

Posted in Uncategorized | Tagged Alaska, aurora, Australia, Canada, day/night band, Finland, Germany, Greenland, Heard Island, Iles Kurguelen, New Zealand, North Dakota, Norway, remote island, Russia, Scotland, Siberia, Sweden | 4 Comments

Germany’s Magic Sparkle

Posted on March 16, 2015 by Curtis Seaman

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Posted in Uncategorized | Tagged Czech Republic, Europe, false color, Fire Temperature RGB, Germany, I-1, I-2, I-3, I-4, I-5, M-1, M-10, M-11, M-12, M-3, M-4, M-5, M-7, Natural Color, resolution, RGB composite, solar panel, true color | Comments Off

Remote Islands IV: Where’s Waldo (Pitcairn)? Edition

Posted on February 10, 2015 by Curtis Seaman

Take a look at this VIIRS “Natural Color” image and see if you can find Pitcairn Island. It’s in there somewhere:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3, taken 22:25 UTC 10 April 2014

You’re definitely going to want to click through to the full resolution version. (Click on the image, then click again.) You won’t be able to see it otherwise. Take your time. Note: this is actually pretty similar to searching for fires.

Did you see it?

If you answered “no”: Good! That’s just what the early settlers of Pitcairn Island wanted: an island that no one could find! If you answered “yes”: I think you’re mistaken. You probably saw Henderson Island, which is bigger and easier to see.

Pitcairn is only 3.6 km across. That’s just 7 pixels in this composite of high-resolution (375 m at nadir; I-band) channels. It’s total land area is 4.6 km². Henderson Island is 37.3 km². There’s even a third island visible in this picture, but you need the eyes of an eagle to see it – Oeno at 0.65 km². Look again and see if you see any green pixels.

If you give up, here’s the answer:

VIIRS Natural Color RGB composite of channels I-1, I-2 and I-3, taken at 22:25 UTC 10 April 2014. The visible islands are labelled.

Now, you may have just clicked to the full-resolution version and are now wondering if I’m right about Oeno Island. Is there really anything there? Yes. Just look at that part of the image zoomed in by 800%:

VIIRS Natural Color image (10 April 2014) zoomed in on Oeno Island

See those three green pixels (not counting the latitude line drawn on there) that are surrounded by lighter blue pixels? That’s Oeno. It is one of the smallest islands you can say that VIIRS “saw”. Here’s what it looks like from a really high-resolution satellite. The light blue pixels surrounding it are the surrounding reef and lagoon of the atoll.

So, why all the interest in a couple of tiny islands in a remote part of the Pacific Ocean? First of all, there are winter storms battering both coasts of the United States, so it’s nice to enjoy a little bit of escapism. Now you can fantasize about being on a tropical island instead of facing the reality of shoveling another 2 feet of snow. Second, it’s fun to look for little islands that can’t be seen with current geostationary satellites (although it will be interesting to see if the high-resolution [0.5 km] visible channel on Himawari will be able to see it; it might be too far east, though). Plus, it’s been over two years since I last looked at remote islands – there may a whole new generation of viewers interested in this stuff who never knew this was part of the blog. Third, I don’t have to write as much and you don’t have to read as much as I fill my blog post quota for the month.

However, to barely keep things on the topic of atmospheric science and satellite meteorology, I will note that, in the images above, you can see a string of clouds streaming to the northwest from both Pitcairn and Henderson Islands. This is the visible manifestation of fluid dynamics which we have discussed before.

If you’ve heard of Pitcairn Island prior to this, it’s probably because you heard of the Mutiny on the Bounty. A group of mutineers who didn’t want to be hanged for their crime settled on Pitcairn Island and burned their ships so they could never leave and, hopefully, never be found. That is the very definition of “getting away from it all”. (Pitcairn is also known to stamp collectors who seek the very rare stamps from the far corners of the world. Selling stamps to tourists is actually a significant part of their economy.)

Today, the island is home to ~50 people – all but two of which are direct descendents of the mutineers. Oeno and Henderson Islands are uninhabited. Henderson Island is a UNESCO World Heritage Site that has been largely untouched by mankind. Oeno Island is a favorite “get-away” spot for Pitcairn Islanders for whom an island of 50 people is just too crowded!

If you want to know more about Pitcairn or you have an hour of free time to use up, check out this documentary on the island, its history, and the people who make it their mission to visit one of the world’s most remote islands:

Posted in Uncategorized | Tagged false color, I-1, I-2, I-3, Natural Color, Pacific, Pitcairn, remote island, resolution, RGB composite | Comments Off

Sea-effect Snow

Posted on January 13, 2015 by Curtis Seaman

Take a look at this image:

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Posted in Uncategorized | Tagged Black Sea, Canada, day/night band, false color, ice and snow, Japan, Korea, M-10, M-3, M-4, M-5, M-7, michigan, Middle East, Natural Color, New York, RGB composite, true color, Turkey, vortex street | 1 Comment