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.)

Germany’s Magic Sparkle

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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:

Hell Froze Over (and the Great Lakes, too)

This has been some kind of winter. The media has focused a lot of attention on the super-scary “Polar Vortex” even though it isn’t that scary or that rare. (I wonder if Hollywood will make it the subject of the next big horror movie in time for Halloween.) Many parts of Alaska have been warmer than Georgia, with Lake Clark National Park tying the all-time Alaskan record high temperature for January (62 °F) on 27 January 2014. (Atlanta’s high on that date was only 58 °F.) Sacramento, California broke their all-time January record high temperature, reaching 79 °F three days earlier. In fact, many parts of California had record warmth in January, while everyone on the East Coast was much colder than average. Reading this article made me think of an old joke about statisticians: a statistician is someone who would say: if your feet are stuck in a freezer and your head is stuck in the oven, you are, on average, quite comfortable.

One consequence of the cold air in the eastern United States is that Hell froze over. No, not the Gates of Hell in Turkmenistan. This time I’m talking about Hell, Michigan. Hell is a nice, little town whose residents never get tired of people telling that joke.

It has been so cold in the region around Hell that the Great Lakes are approaching a record for highest percentage of surface area covered by ice. This article mentions some of the benefits of having ice-covered Lakes, including: less lake-effect snow, more sunshine and less evaporation from the Lakes, which would keep lake levels from dropping. Although, that is at the cost of getting ships stuck in the ice, and reducing the temperature-moderating effects of the Lakes, which allows for colder temperatures on their leeward side.

This article (and many other articles I found) uses MODIS “True Color” images to highlight the extent of the ice. Why don’t they show any VIIRS images? Well, I’m here to rectify that.

First off, I can copy all those MODIS images and show the “True Color” RGB composite from VIIRS:

VIIRS "True Color" RGB composite of channels M-3, M-4 and M-5, taken 17:27 UTC 11 February 2014

VIIRS "True Color" RGB composite of channels M-3, M-4 and M-5, taken 17:27 UTC 11 February 2014

While it was a rare, sunny winter day for most of the Great Lakes region on 11 February 2014, it’s hard to tell that from the True Color imagery. I mean, look at this True Color MODIS image shown on NPR’s website. Can you tell what is ice and what is clouds?

There are ways of distinguishing ice from clouds, which I have talked about before but, it doesn’t hurt to look at these methods again and see how well they do here. First, let’s look at my modification of the EUMETSAT “Snow” RGB composite:

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 17:27 UTC 11 February 2014

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 17:27 UTC 11 February 2014

This “Snow” RGB composite differs by using reflectances at 2.25 µm in the place of the 3.9 µm channel that EUMETSAT uses. (Their satellite doesn’t have a 2.25 µm channel.) It’s easy to see where the clouds are now. Of course, now the snow and ice appear hot pink, which you may not find aesthetically pleasing. And it certainly isn’t reminiscent of snow and ice.

If you don’t like the “Snow” RGB, you may like the “Natural Color” RGB composite:

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 17:27 UTC 11 February 2014

VIIRS "Natural Color" RGB composite of channels I-01, I-02 and I-03, taken 17:27 UTC 11 February 2014

This has the benefit of making snow appear a cool cyan color, and has the added benefit that you can use the high-resolution imagery bands (I-01, I-02 and I-03) to create it. There is twice the resolution in this image than in the Snow and True Color RGB images. Here’s another benefit you may not have noticed right away: the clouds, while still white, appear to be slightly more transparent in the Natural Color RGB. This makes it a bit easier to see the edge of the ice on the east side of Lake Michigan and the center of Lake Huron, for example.

If you’re curious as to how much ice is covering the lakes, here are the numbers put out by the Great Lakes Environmental Research Laboratory (which is about a 25 minute drive from Hell) from an article dated 13 February 2014:

Lake Erie: 96%; Lake Huron: 95%; Lake Michigan: 80%; Lake Ontario: 32% and Lake Superior: 95%. This gives an overall average of 88%, up from 80% the week before. The record is 95% set in 1979, although it should be said satellite measurements of ice on the Great Lakes only date back to 1973.

Why does Lake Ontario have such a low percentage? That last article states, “Lake Ontario has a smaller surface area compared to its depth, so it loses heat more slowly. It’s like putting coffee in a tall, narrow mug instead of a short, wide one. The taller cup keeps the coffee warmer.”  Doesn’t heat escape from the sides of a mug as well as the top? And isn’t Lake Superior deeper than Lake Ontario? Another theory is that “Lake Ontario’s depth and the churning caused by Niagara Falls means that it needs long stretches of exceptionally cold weather to freeze.”  Does Niagara Falls really have that much of an impact on the whole lake?

So, what is the correct explanation? I’m sorry, VIIRS can’t answer that. It can only answer “How Much?” It can’t answer “Why?”

 

BONUS UPDATE (17 February 2014):

It has come to my attention that the very next orbit provided better images of the Great Lakes, since they were no longer right at the edge of the swath. Here, then, are the True Color, Snow and Natural Color RGB composite images from 19:07 UTC, 11 February 2014:

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 19:07 UTC 11 February 2014

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 19:07 UTC 11 February 2014

 

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 19:07 UTC 11 February 2014

VIIRS "Snow" RGB composite of channels M-11, M-10 and M-7, taken 19:07 UTC 11 February 2014

 

VIIRS "Natural Color" composite of channels I-01, I-02, and I-03, taken 19:07 UTC 11 February 2014

VIIRS "Natural Color" composite of channels I-01, I-02, and I-03, taken 19:07 UTC 11 February 2014

 

UPDATE #2 (18 March 2014): The Great Lakes ice cover peaked at 92.2% on 6 March 2014, just short of the all-time record in the satellite era. March 6th also happened to be a clear day over the Great Lakes, and VIIRS captured these images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 18:35 UTC 6 March 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 18:35 UTC 6 March 2014

 

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 18:35 UTC 6 March 2014

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 18:35 UTC 6 March 2014

Record Russian Rain Runoff Responsible for Rapid River Rise

Sorry, I couldn’t help myself with that title.  Last time we looked at flooding in Russia, it was in the western parts – generally near Moscow and primarily along the Oka River – and caused by rapid melting of record spring snowfall. This time, flooding is occurring in Russia’s Far East, primarily along the Amur River, caused by heavy rainfall related to monsoon wind patterns in the region – record levels of flooding not seen before in the 160 years Russians have settled in the area.

Unfortunately, this natural disaster is affecting more than just Russia. In China, many people are dead or missing as the result of flooding. (The figure of “hundreds dead or missing” includes flooding caused by typhoons Utor and Trami in southeastern China, flash flooding in western China, and the subject of today’s post: river flooding in northeastern China and far east Russia.) The Chinese provinces of Liaoning, Jilin and Heilongjiang have been hit particularly hard with persistent, heavy rains since late July, as have areas just across the border in Amur Oblast, Khabarovsk Krai and the Jewish Autonomous Oblast in Russia.

A few more facts: Heilongjiang is the Chinese name for the Amur River. It translates to English as “Black Dragon”. The Mongols called it Kharamuren (“Black Water”), which, I assume, the early Russian settlers shortened to Amur. It is the longest undammed river in the Eastern Hemisphere and the home to the endangered Amur leopard and Amur tiger. Since 1850, the Amur River has been the longest piece of the border between China and Russia. Now, in 2013, the Amur River has reached the highest levels ever recorded.

Backing up a bit, here’s what the area looked like according to “Natural Color” or “pseudo-true color” VIIRS imagery back in the middle of July:

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 03:27 UTC 14 July 2013

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 03:27 UTC 14 July 2013

As always, click on the image, then on the “2368×1536” link below the banner to see the full resolution version. Here’s what the same area looked like about a month later:

VIIRS false color RGB composite of channels I-01, I-02 and I-03, taken 03:14 UTC 21 August 2013

VIIRS false color RGB composite of channels I-01, I-02 and I-03, taken 03:14 UTC 21 August 2013

Notice anything different? The Amur River has overflowed its floodplain and is over 10 km (6 miles) wide in some places. Just downriver (northeast) from Khabarovsk, the flooded area is up to 30 km (18 miles) wide!

Pay attention to Khabarovsk. Back in 1897, the Amur River crested there with a stage of 6.42 m (about 21 feet in American units), which was the previous high water mark. On 22 August 2013, the river stage reached 7.05 m (23 feet) and was expected to keep rising to 7.8 m (25.6 feet) by the end of August. The map below (in Russian) shows the local river levels on 22 August 2013. It came from this website.

Amur River levels at various locations in Khabarovsk Krai, Russia on 22 August 2013.

Amur River levels at various locations in Khabarovsk Krai, Russia on 22 August 2013.

Note that Khabarovsk in Cyrillic is Хабаровск (the black dot in the lower left), and Amur is Амур. The blue numbers represent the river stage in cm. Red numbers indicate the change in water level (in cm) over the last 24 hours. The colored dots indicate how high the river level is above flood stage according to the color scale (also in cm). The river at Khabarovsk is more than 4 meters (13 feet) above flood stage.

Not impressed by comparing a “before” and “after” image? Here’s an animation over that time period (14 July to 21 August 2013), with images from really cloudy days removed:

Animation of VIIRS false-color composites of channels I-01, I-02 and I-03

Animation of VIIRS false-color composites of channels I-01, I-02 and I-03. Click on the image, then on the "1184x768" link below the banner to view the animation.

You have to click through to the full resolution version before the loop will play. In order to not make the world’s largest animated GIF, the I-band images in the loop have been reduced in resolution by a factor of 2, making them the same resolution as if I had used M-5, M-7 and M-10 to make this “Natural Color” composite.

The Day/Night Band is not known for its ability to detect flooding at night, but it also saw how large the Amur River has become:

VIIRS Day/Night Band image, taken 17:27 UTC 20 August 2013

This image was taken on 20 August 2013, which just so happens to be the night of a full moon. The swollen rivers are clearly visible thanks to the moonlight (and general lack of clouds).

Khabarovsk is a city of over 500,000 people and would require a major evacuation effort if the river reached the expected 7.8 m level. Over 20,000 people have already been evacuated in Russia alone (and over a million people in China) according to this report. Oh, and at least two bears.

This heavy rain and flooding makes it all the more surprising that, a little further north and west in Russia, there have been numerous, massive wildfires. Check out this “True Color” image from VIIRS, taken on 16 August 2013:

VIIRS"True Color" composite of channels M-3, M-4 and M-5, taken 03:12 UTC 16 August 2013.

VIIRS"True Color" composite of channels M-3, M-4 and M-5, taken 03:12 UTC 16 August 2013.

See the supersized swirling Siberian smoke spreading… OK, I’ll quit with the alliteration. Here’s the smoke plume on the very next overpass (about 90 minutes later) seen on a larger scale:

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 04:52 UTC 16 August 2013.

VIIRS "True Color" composite of channels M-3, M-4 and M-5, taken 04:52 UTC 16 August 2013.

A strong ridge of high pressure with its clockwise flow is trapping the smoke over the region. In this image you can see quite a few of the smoke sources where the fires are still actively burning. Look in the latitude/longitude box bounded by 98 °E to 105 °E and 59 °N to 61 °N. By the way, that’s Lake Baikal on the bottom of the image, just left of center.

A quick back-of-the-envelope calculation indicates that the area covered by smoke is roughly 500,000 km2. (Of course it is complicated by the fact that the smoke is mixing in with the clouds, so it is hard to define a true boundary for the smoke on the north and west sides.) That puts it in the size range of Turkmenistan, Spain and Thailand. If that’s not a good reference for you, how’s this? The smoke covers an area larger than California and smaller than Texas.

These fires have burned for more than a month. This article from NASA includes a MODIS image from 25 July 2013 containing massive smoke plumes and shows that areas of central Russia (particularly north of the Arctic Circle) have had a record heatwave this summer. And here are a few more images of the smoke from MODIS over the past few weeks.

Heatwaves and fires and floods? Russia is all over the map. Literally. I mean, look at a map of Asia – Russia is all over that place. It even spreads into Europe!