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.

Sehr Schweres Unwetter in NRW

Not having full command of the German language, “sehr schweres Unwetter” seems like an understatement. It translates as “very bad thunderstorm,” which in this case is like calling the Titanic a “very big boat”. Of course, if you live in the Great Plains, you probably refer to a supercell thunderstorm as “a little bit of rain and wind” but the storms that hit Nordrhein-Westfalen (NRW) on 9-10 June 2014 rival anything the toughest Oklahoman has experienced (minus the tornadoes). Also, keep in mind that Germany and the Low Countries have nowhere near the wide-open spaces the U.S. Great Plains are known for. Take 5 times the population of Oklahoma and cram them into a land area the size of Maryland. (Or, if you’re from Maryland, multiply your state’s population by three to approximate the population density of the area we’re talking about. Then ponder how anyone in that part of Germany is able to spend less than 18 hours per day stuck in traffic like you would be if you were suddenly surrounded by three times as many people.)

Let me set the scene for you. (If you’ve ever lived in the Midwest, you know the drill.) The air is hot and unbelievably humid. The sky is overcast. There is no wind to speak of, but there is a certain “electricity” in the air that tells you that a violent end to the heatwave is coming. Off in the distance, clouds lower and darken. A gentle rumbling of thunder slowly builds as the storm approaches. Lightning appears and becomes ever more frequent. Right before the storm hits, the winds pick up out of nowhere and… Wait! I don’t need to describe it. I can show it to you:

EDIT: I did need to describe it, because the videos are no longer available. If you weren’t able to see the videos before they were removed, they showed scary looking clouds and nearly constant lightning approaching Bochum. In fact, there were an estimated 113,000 lightning strikes across Germany from the storm.

Germany is, apparently, a land of iPhones and GoPros and all sorts of video recording equipment, and there is no shortage of video of the storm. There are videos of the storm approaching from different perspectives (here, here and here), the strong winds and heavy rains that are more reminiscent of a tropical storm (here, here and here), footage of the lightning in slow-motion and, because this is the Internet, a 30 min. montage of storm footage set to salsa music (although one commenter says the first footage is from a storm in 2010).

The aftermath is pretty impressive also – trees and large branches down everywhere blocking roads, crushing cars and stopping the never-late German train system. In fact, 6 people were killed – mostly by falling trees. Winds were observed in the 140-150 km h-1 range (approximately 85-90 miles per hour), which puts it just below a Category 2 hurricane according to the Saffir-Simpson scale. There were even reports of baseball sized hail, something that’s not unusual in Oklahoma, but is very rare in Europe. (Here is some pretty big hail in the town of Zülpich from earlier in the day.)

Now that you’ve used up the last 90 minutes looking at YouTube videos, let’s get down to business. What do satellites tell us about this storm?

EUMETSAT put together this animation of images from the geostationary satellite Meteosat-10:

Watch that video again, preferably in fullscreen mode. First, the white boxes highlight the supercell thunderstorms over Europe between 01:00 UTC 9 June 2014 and 08:15 UTC 10 June 2014. Right before sunset on 9 June, you can see a storm moving north out of France into Belgium that seems to explode as it heads towards the Netherlands and western Germany. This is our “schweres Unwetter”. The second thing to notice is where that storm is at 02:00 UTC on the 10th. That was the time that VIIRS passed overhead.

So, without any more bloviating, here’s the high-resolution infrared (I-5) image from VIIRS:

VIIRS I-5 image from 02:07 UTC 10 June 2014

VIIRS I-5 image of severe thunderstorms over Europe from 02:07 UTC 10 June 2014

The storm that caused all the damage over Nordrhein-Westfalen has weakened and is now over northeastern Germany on its way to Poland. But, a second impressive supercell complex is pounding Belgium and the Netherlands, and taking aim at western Germany once again.

The coldest pixels are 196.5 K (-76.7 °C or -106 °F) in the storm over Benelux and 198.7 K (-74.5 °C or -102.1 °F) in the storm over northeast Germany. Another impressive thing about these storms is their size relative to the size of these countries. That Benelux storm looks like it’s at least five times the size of Luxembourg and as big as Belgium! (And I’m not counting the area of the anvil, which is even larger. I’m only counting the area containing overshooting tops.)

Since it’s nighttime, what did the Day/Night Band see? Well, the answer depends on how you display the data. You see, we’re approaching the Summer Solstice in the Northern Hemisphere, where the days are long and twilight encroaches the nighttime overpasses at these latitudes. If you try to scale the radiances from lowest = black to highest = white, you get something like this:

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014. Radiance values are displayed and scaled according to text above.

That’s not very helpful because the radiance values vary by 6 orders of magnitude across the scene and we only have 256 colors to work with to relay that information. But, we can take advantage of the fact that the Day/Night Band radiance values are, to the first order, a function of the solar and lunar zenith angles, and use this as the basis for a “dynamic scaling” that compares the observed radiance with an expected maximum and minimum radiance value that is a function of those angles. (In case you’re interested, the dynamic scaling algorithm used here is based around the error function.) This allows you to produce something like this:

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014

VIIRS Day/Night Band image, taken 02:07 UTC 10 June 2014. This image uses dynamic scaling as described in the text.

Here, we’ve lost some quantitative information (colors no longer represent specific radiance values) but we’ve gained valuable qualitative information.  Now we can see where the storms are! Notice the shadows in the overshooting tops of our Benelux storm – right where the coldest pixels are in the infrared image. We can see some of the city lights, but not others, because the twilight encroaching from the northeast is brighter than the cities in that part of the image. (It is easy to pick out London and Paris, though.) If you read the previous post, you might be wondering why there are no mesospheric waves with these storms. That’s because there is too much twilight (and moonlight) to see the airglow. (There’s also the possibility that the stratosphere and mesosphere weren’t conducive for vertically propagating waves, but you wouldn’t be able to tell that under these lighting conditions.)

Some people like to combine the infrared with the Day/Night Band into a single image. This is done by changing the opacity of one of the images and overlaying it on the other. Here’s an example of what that looks like using the dynamically scaled Day/Night Band image:

VIIRS combined IR/DNB image from 02:07 UTC 10 June 2014

VIIRS combined IR/DNB image from 02:07 UTC 10 June 2014

The light/shadow effect of the visible information adds a sort-of 3-D effect to the infrared images and, since this is the Day/Night Band, it can show where the storms are in relation to the urban areas. Here, it seems to work better for the Benelux storm than it does for the other one. (Of course, it would be better without the twilight. And, it works best with a full moon, which occurred three days later.)

Of course, if you have access to the Near Constant Contrast imagery, you don’t have to worry about scaling. The imagery is useful as-is:

VIIRS NCC image, taken at 02:07 UTC 10 June 2014

VIIRS NCC image, taken at 02:07 UTC 10 June 2014

And the combined IR/NCC image looks like this:

Combined IR/NCC image from 02:07 UTC 10 June 2014

Combined IR/NCC image from 02:07 UTC 10 June 2014

In case you’re interested, there are additional videos, animations and images of these storms from the Meteosat High Resolution Visible (HRV) channel at the EUMETSAT Image Library.


Severe Weather in the Mesosphere

So far (*knock on wood*), it’s been a pretty quiet year for severe weather. If you only count tornadoes, there have been 81 tornado reports from 1 January to 4 April this year. (11 of those have come just this week.) This is a lot fewer than the previous three year average of 192 tornadoes by the end of March. For that, you can thank the dreaded, terrifying “Polar Vortex” you’ve heard so much about over the winter. Tornadoes don’t like to come out when it’s cold everywhere. (Although, there was a notable exception on 31 March 2014, when a tornado hit a farm in Minnesota when the area was under a blizzard warning.)

I just said that there have been 11 tornado reports this week. Eight of those came in the past 24 hours. At the southern end of the line that brought the tornadoes to Illinois, Missouri and Texas, the severe weather included golf ball-size hail and this:


That report came from the National Weather Service in Corpus Christi, TX and it was caused by non-tornadic straight-line winds in Orange Grove. Winds capable of ripping a shed out of the ground, combined with golf ball-sized hail – that’s one recipe for broken windows. And it’s not a pleasant way to be awakened at 4:30 in the morning.

A couple of hours earlier, VIIRS caught this severe storm as it was rapidly growing. Here’s what the storm looked like in the high-resolution infrared channel (I-5, 11.45 µm):

VIIRS high-resolution IR image (channel I-5), taken at 08:13 UTC 4 April 2013.

VIIRS high-resolution IR image (channel I-5), taken at 08:13 UTC 4 April 2013.

Make sure you click on the image, then on the “2999×2985” link below the banner to see the full resolution image, which, for some reason, is the only version where the colors display correctly.

The storm that hit Orange Grove is the southern-most storm, with what looks like a letter “C” imprinted on the top. (That kind of feature typically looks more like a “V” and makes this an “Enhanced-V” storm, which you can learn more about here. Enhanced-V storms are noted for their tendency to produce severe weather.) For those of you keeping score at home, the coldest pixel in this storm is 184.7 K (-88.5 °C).

Compare the image above with the Day/Night Band image below (from the same time):

VIIRS Day/Night Band image, taken at 18:13 UTC 4 April 2014

VIIRS Day/Night Band image, taken at 08:13 UTC 4 April 2014

There are a few interesting features in this image. For one, there’s a lot of lightning over Louisiana, Arkansas and Mississippi. (Look for the rectangular streaks.) There’s even some lighting visible where our “Enhanced-V” is. Two, it takes a lot of cloudiness to actually obscure city lights: only the thickest storm clouds appear to be capable of blocking out light from the surface. Three: there are a lot of boats out in the Gulf of Mexico at 3 o’clock in the morning (and a few oil rigs as well). And four: notice what appear to be concentric rings circling the location where our severe storm is with its enhanced-V.

In this image, there is no moonlight (we’re before first quarter, so the moon isn’t up when VIIRS passes over at night). The light we’re seeing in those ripples is caused by “airglow”, which we’ve seen before. And the ripples themselves may be similar to what is called a “mesospheric bore.” If you don’t want to get too technical, a mesospheric bore is when this happens in the mesosphere. They are related to – but not exactly analogous to – undular bores, which you can read more about here.

Unlike the situation described for the undular bore in that last link, the waves here are caused by our severe storm. To put it simply, we have convection that has formed in unstable air in the troposphere. This convection rises until it hits the tropopause, above which the air is stable. This puts a halt to the rising motion of the convection but, some of the air has enough momentum to make it in to the stratosphere. This is called the “overshooting top“, and is where our -88°C pixels are located. (Look for the pinkish pixels in the middle of the “C” in the full-resolution infrared image.) The force of this overshooting top creates waves in the stable layer of air above (the stratosphere) that propagate all the way up into the mesosphere. The mesosphere is where airglow takes place, and these waves impact the optical path length through the layer where light is emitted. This of course, impacts the amount of light we see. The end result: a group of concentric rings of airglow light surrounding our storm.

You could make the argument that the waves we see in the Day/Night Band image are not an example of a bore. Bores tend to be more linear and propagate in one direction. These waves are circular and appear to propagate in all directions out from a central point. It may be better to describe them as “internal buoyancy waves“, which are similar to what happens when you drop a pebble into a pond. Only, in this case the pebble is a parcel of air traveling upwards, and the surface of the water is a stable layer of air. Compare the pebble drop scenario with this video of a bore traveling upstream in a river to see the difference.

In fact, if you look closer at the Day/Night Band image, in the lower-right corner (over the Gulf of Mexico) there is another group of more linear waves and ripples in the airglow that may actually be from a bore. It’s hard to say for sure, though, without additional information such as temperature, local air density, pressure and wind speeds way up in that part of the mesosphere.

By the way, you can see mesospheric bores and other waves in the airglow if you have sensitive-enough camera, like the one that took this image:

Photograph of a mesospheric bore. Image courtesy T. Ashcraft and W. Lyons (WeatherVideoHD.TV)

Photograph of a mesospheric bore. Image courtesy T. Ashcraft and W. Lyons (WeatherVideoHD.TV)

And, if you’re interested, the Arecibo Observatory has a radar and optical equipment set up to look at these upper-atmosphere waves (scroll down to Panel 2 on this page). The effect of these waves on atmospheric energy transport is a hot topic of research.

Golf ball-sized hail at the Earth’s surface is related to energy transport 100 km up in the atmosphere!


NOTE: This post has been updated since it was first written to clarify that the circular waves are likely not evidence of a bore, as was originally implied. They are more likely internal buoyancy waves, which are also known as gravity waves. For more information, consult your local library.

Rare Super Typhoon in the Pacific Ocean

If you pay attention to tropical cyclones, that headline may be confusing. Unlike the Super Cyclone in the Indian Ocean we just looked at, Super Typhoons are not rare in the Pacific Ocean. There have been 5 of them this year. What is rare is a typhoon that is estimated to be one of the strongest storms ever recorded in human history. I am, of course, speaking about Typhoon Haiyan, which the Philippines will forever remember as Yolanda.

Animation of visible images from MTSAT of Super Typhoon Haiyan from 7 November 2013

Animation of visible images from MTSAT of Super Typhoon Haiyan (Yolanda) from 7 November 2013. Courtesy Dan Lindsey (NOAA).

If you don’t pay that much attention to tropical cyclones, you should be asking, “How do we know it is one of the most intense tropical cyclones ever in recorded human history?” You may also be asking, “Why does it have two names?” And, “What is the difference between a typhoon and a hurricane and a tropical cyclone?”

I’ll answer those in reverse order. Typhoons, hurricanes and tropical cyclones are different names given to the same physical phenomenon. If it occurs in the Atlantic Ocean or the Pacific Ocean north of the Equator and east of the International Date Line, it is called a “hurricane”, a name that was derived from Huracan, the Mayan god of wind and storms. If it occurs in the Pacific Ocean north of the Equator and west of the International Date Line, it is called a “typhoon”, which may come from the Chinese “daaih-fùng” (big wind), Greek “typhōn” (wind storm) or Persian “ṭūfān” (a hurricane-like storm). Anywhere else and it is a “cyclone” – a term for rotating winds, which ultimately comes from the Greek “kyklos” (circle).

Why does it have two names (Haiyan and Yolanda)? Different parts of the world use different naming conventions. When it comes to typhoons, the United States uses the naming convention of the Japan Meteorological Agency and the World Meteorological Organization. The Philippines come up with their own name list. That’s why we know it as Haiyan, while Filipinos know it as Yolanda.

Now, was this really the most intense tropical cyclone in all of recorded human history? That question is more difficult to answer. It depends on how you define “intensity”. Is it the lowest atmospheric pressure at the Earth’s surface? Is it the highest 1-minute, 5-minute or 10-minute average wind speed at the Earth’s surface? Is it based on structural damage? Deaths?

The last two, damage and deaths, are better measures of the storm’s impact, rather than its physical strength. So, we’re going to focus on how one would measure the physical strength of the storm.

Barometers, used to measure pressure, have been around for about 400 yearsAnemometers, which measure wind speed, have been around in their modern form for about 160 years. (It is also possible to estimate wind speeds from Doppler radar, technology that has been around since World War II, although these estimates are not as accurate as anemometers.) The primary issue is getting these instruments inside a super typhoon (and not having them be destroyed in the process).

It is possible to attach an anemometer and a barometer to an airplane, then fly the plane into the storm to measure the wind and pressure (which is done for almost every hurricane on a path to hit the United States), but not every country is wealthy enough to afford their own research aircraft. Plus, it’s tough to find anyone crazy enough to fly into a storm as strong as Haiyan. Here is a story of why “hurricane hunting” isn’t always a good idea.

Weather satellites, which have been around for 50 years, can view these storms from afar (with no risk of being damaged by them) and are the primary way to determine wind speeds and pressures (particularly when the storm is out over the ocean, where there aren’t many barometers and anemometers). The method to determine the strength of a storm from satellite is called the “Dvorak Technique”, developed by Vernon Dvorak in the 1970s, and discussed in detail here. Basically, the algorithm takes the current appearance of the storm in visible and infrared wavelengths (how symmetric it is about the eye, what is the brightness temperature in the warmest pixel in the eye, what is the brightness temperature of the coldest ring of clouds around the eye, and so on), along with the recent history of the storm’s appearance and relates that to a storm’s central pressure and maximum sustained wind speed based on an empirical relationship. For those storms that have been viewed by both satellite and aircraft, the Dvorak Technique has been shown to be pretty accurate: over 50% of storms have wind speed errors less than 5 knots, and overall root-mean-square errors of 11 knots.

The image loop from MTSAT above, and the VIIRS images below of Haiyan (Yolanda) highlight the relevant points the Dvorak Technique keys on when determining its intensity: a well defined eye with warm infrared brightness temperatures (up to +23 °C), a ring of cold clouds surrounding the eye (the purple color corresponds to temperatures less than -80 °C), and it’s hard to find a storm more symmetric than this one.

VIIRS infrared (I-5) image of Typhoon Haiyan (Yolanda), taken 16:39 UTC 6 November 2013

VIIRS infrared (I-5) image of Typhoon Haiyan (Yolanda), taken 16:39 UTC 6 November 2013. Image courtesy Dan Lindsey (NOAA). Brightness temperatures are given in K.

VIIRS infrared (I-5) image of Super Typhoon Haiyan (Yolanda) taken 16:16 UTC 7 November 2013

VIIRS infrared (I-5) image of Super Typhoon Haiyan (Yolanda) taken 16:16 UTC 7 November 2013. Image courtesy Dan Lindsey (NOAA). Brightness temperatures are given in degrees Celsius (on the same scale as the previous image).

As a quick aside about the power of VIIRS, Haiyan was right at the edge of the scan when the image above was taken. Look at the impressive detail even at the edge of scan! See if you can beat that, MODIS!

Using Dvorak’s method, Haiyan (Yolanda) achieved the maximum possible value on the “T-number” scale: 8.0. That puts the maximum sustained winds above 170 knots (315 km h-1 or 195 mph!) and the sea-level pressure below 900 mb (hPa), according to the scale. You can’t get any stronger than that because the data used to develop the empirical relationship doesn’t contain any storms stronger than that. We’ve reached signal saturation on the Dvorak “T-number” scale. (And the Saffir-Simpson scale, and the Beaufort scale.) All we can say is Haiyan right up there with the strongest tropical cyclones ever observed. We can also say that Haiyan was the only storm to make landfall as an 8.0 on the “T-number” scale. But, beyond that, we would need actual in situ observations to know just how strong Haiyan (Yolanda) really was.

As expected, one of the strongest typhoons ever to make landfall caused some power outages. The Day/Night Band on VIIRS captures it well:

VIIRS Day/Night Band image of the central Philippines, taken 16:50 UTC 31 October 2013VIIRS Day/Night Band image of the central Philippines, taken 17:02 UTC 10 November 2013

Did you notice the vertical bar in the above image that you can click on? Slide it left to right to see the differences in the amount of city lights (and nocturnal fishing activities) before and after Haiyan (Yolanda) made landfall. Tacloban was, of course, one of the hardest hit heavily populated areas. As you can see from radar, it took a direct hit from the eyewall.

With winds estimated at 195 mph, Haiyan (Yolanda) was like an EF-4 tornado. A 30-mile wide EF-4 tornado that lasted for several hours.

UPDATE: I have been notified that the above sliding bar trick in the Day/Night Band images above doesn’t work in all browsers (or for all operating systems). If that’s the case for you, click on the image below, then on the “1000×1000” link below the banner to see the high resolution animation.

VIIRS Day/Night Band images highlighting power outages caused by Typhoon Haiyan (Yolanda) 2013

VIIRS Day/Night Band images highlighting power outages caused by Typhoon Haiyan (Yolanda) 2013. Images courtesy Steve Miller (CIRA).

The first two images in the animation show the Day/Night Band images from the nighttime overpasses on 31 October and 9 November 2013. The last two frames (one with the map plotted and one without) highlight the differences in these images by creating an RGB composite of the before and after images. Power outages show up as red in this composite. Areas that have kept their power show up a golden color. Areas with light after the storm, but not before the storm, show up green. In this case, green areas highlight where boats were after the storm, and where clouds scattered the city lights over a larger area than they appeared to be before the storm, when there were no clouds overhead. It’s another way to look at power outages in the Day/Night Band.

Rare Super Cyclone in the Indian Ocean

The Indian Ocean has just had its first Super Cyclone since 2007. The name of it is “Phailin” and I bet you just pronounced it incorrectly (unless you speak Thai). It’s closer to “PIE-leen” than it is to “FAY-lin”. The name was derived from the Thai word for sapphire. (If you go to Google Translate and translate “sapphire” into Thai, you can click on the “audio” icon {that looks like a speaker} in the lower right corner of the text box to hear a robotic voice pronounce it. You can also click on the fourth suggested translation below the text box and try to pronounce that as well.)

If you’re tired of reading about flooding in this blog, you’re probably going to want to avoid reading about Phailin. It already dumped up to 735 mm (28.9 inches) of rain on the Andaman Islands in a 72-hour period. Aside from the heavy rains, Phailin is a text-book example of “rapid intensification”, as official estimates of the storm’s intensity grew from 35 kt (65 km h-1 or 40 mph) when the storm was first named, to 135 kt (250 km h-1 or 155 mph!) just 48 hours later. Here’s a loop of what that rapid intensification looks like from the geostationary satellite, Meteosat-7. (Those are the Andaman Islands where the cyclone first forms.)

VIIRS being on a polar-orbiting satellite, it’s not possible to get an image of the cyclone every 30 minutes like you can with Meteosat-7. VIIRS only views a cyclone like Phailin twice per day. But, VIIRS can do things that Meteosat-7 can’t. The first is produce infrared (IR) imagery at 375 m resolution. (Meteosat-7 has 5 km resolution.) The image below is from the high resolution IR band, taken at 20:04 UTC 10 October 2013:

VIIRS high-resolution IR image of Super Cyclone Phailin, taken 20:04 UTC 10 October 2013

VIIRS high-resolution IR image of Super Cyclone Phailin, taken 20:04 UTC 10 October 2013

Look at the structure of the clouds surrounding the eye. (You’re definitely going to want to see it at full resolution by clicking on the image, then on the “3875×3019” link below the banner.) VIIRS is detecting wave features in the eyewall that other current IR sensors aren’t able to detect because they don’t have the resolution. The coldest cloud tops are found in the rainband to the west of the eyewall (look for that purple color) and are 179 K (-94 °C). That’s pretty cold!

Also notice the brightness temperature gradient on the west side of the eye is a lot sharper than on the east side of the eye. This is because the satellite is west of eye (the nadir line is along the left edge of the plotted data), looking down on the storm at an angle, revealing details about the side of the eyewall on the east side. Look down on the inside of a cardboard tube or a piece of pipe at an angle to replicate the effect. (Actually, the eye wall of a tropical cyclone slopes away from the center, so it’s more like funnel than a tube. If you go looking for a cardboard tube or a piece of pipe to look at, the results will be inaccurate. Grab a funnel instead.)

Another advantage of VIIRS is the Day/Night Band, a broadband visible channel that is sensitive to the low levels of light that occur at night. There is no geostationary satellite in space with this capability. The image below was taken from the Day/Night Band at the same time as the IR image above:

VIIRS Day/Night Band image of Super Cyclone Phailin, taken 20:04 UTC 10 October 2013

VIIRS Day/Night Band image of Super Cyclone Phailin, taken 20:04 UTC 10 October 2013

The Day/Night Band shows the eye clearly. Plus, being able to see the city lights gives an idea of the amount of people and infrastructure that are in the storm’s path.

Now, hold on a minute. 10 October 2013 was one day before first quarter moon, which means the moon was below the horizon when this image was taken. (Generally speaking, the moon is only up for nighttime VIIRS overpasses that occur from two days after first quarter to two days after last quarter.) If you want get more specific, India is one of the few places with a half-hour offset from most time zones (UTC +5:30), which means this image was taken at a local time of 1:34 AM 11 October 2013. Local moonrise time for the eastern coast of India for that date was 11:33 AM (10 hours later), while the moonset occurred 3.5 hours earlier (10:02 PM). This means you should be asking the obvious question: if there was no moonlight (and obviously no sunlight either, since this a nighttime image), why is VIIRS able to see the cyclone?

Was it the scattering of city lights off the clouds that allows you to see the clouds at night, like in this photo? No, because this cyclone is way out over the ocean, in the middle of the Bay of Bengal. Due to the curvature of the Earth, city lights won’t illuminate any clouds more than a few tens of kilometers away. The center of this storm is about 600 km away from any city lights and is still visible. At the most, only the very edges of the storm near cities would be illuminated if this were the case.

I can see at least two lightning strikes in the image, so is it lightning illuminating the cloud from the inside? No, it’s not that either. See how streaky the lightning appears? The whole storm would look like a series streaks, some brighter than others, depending on how close they were to the tops of the clouds (and how close the lightning was to the position of the VIIRS sensor’s field of view during each scan). The top of the storm is much too uniform in brightness for it to be caused by lightning.

So, if you’re so smart, what is the explanation, Mr. Smartypants? I’m glad you asked. It is a phenomenon called “airglow” (or sometimes “nightglow” when it occurs at night). You can read more about it here and here. The basic idea is that gas molecules in the upper atmosphere interact with ultraviolet (UV) radiation and emit light. Some of these light emissions head down toward the earth’s surface, are reflected back to space by the clouds, and detected by the satellite.

Really? Some tiny amount of gas molecules way up in the atmosphere emit a very faint light due to excitation by UV radiation, and you’re telling me VIIRS can see it? But, it’s nighttime! There’s no UV radiation at night! How do you explain that? The UV radiation breaks up the molecules into individual atoms during the day. At night, the atoms recombine back into molecules. That’s when they emit the light. Look, it’s in a peer-reviewed scientific journal if you don’t believe me. (A shortened press release about it is here.) Thanks to airglow (and the sensitivity of the Day/Night Band), VIIRS can see visible-wavelength images of storms at night even when there is no moon!

Getting back to the Super Cyclone, here’s what Phailin looked like in the high-resolution IR channel the next night (19:45 UTC 11 October 2012), right around the time where it reached its maximum intensity:

VIIRS channel I-05 image of Super Cyclone Phailin, taken 19:45 UTC 11 October 2013

VIIRS channel I-05 image of Super Cyclone Phailin, taken 19:45 UTC 11 October 2013

Here, the cyclone is much closer to nadir (the nadir line passes through the center of the image), so you’re more-or-less looking straight down into the eye on this orbit. The corresponding Day/Night Band image is below:

VIIRS Day/Night Band image of Super Cyclone Phailin, taken 19:45 UTC 11 October 2013

VIIRS Day/Night Band image of Super Cyclone Phailin, taken 19:45 UTC 11 October 2013

Once again, the cyclone is illuminated by airglow. (Some of the outer rainbands are also being lit up by city lights, which are visible through the clouds.) The only question is, what is that bright thing off the coast of Burma (Myanmar) that shows up in both Day/Night Band images? It looks like a huge, floating city. According to Google Maps, there’s nothing there. That is one question I don’t have the answer to (*see Update #2*).

Any other questions about cyclones in India? Check out this FAQ guide put out by the India Meteorological Department.

With a peak intensity estimate at 140 kts (259 km h-1 or 161 mph), Phailin was one of the strongest cyclones ever in the Indian Ocean. (Only 2007’s Gonu – 145 kt – was stronger. Several other storms have been estimated at 140 kt.) The last time a cyclone of Phailin’s intensity hit India, over 10,000 people died. Credit must be given to the Indian government, who successfully evacuated 900,000 people from the coast (the article refers to 9.1 lakhs; one lakh is 100,000), and so far, only about 25 people have been confirmed dead. In fact, fewer people were killed by this cyclone than were killed by a panicked stampede outside a temple in central India the same weekend.


UPDATE #1 (15 October 2013): The Day/Night Band also captured the power outages caused by Phailin. Here is a side-by-side comparison of Day/Night Band images along the coast of the state of Odisha (also called Orissa), which took a direct hit from the cyclone – a zoomed in and labelled version of the 10 October image above (two days before landfall) against a similar image from 14 October 2013 (two days after landfall):

VIIRS Day/Night Band images from before and after Super Cyclone Phailin made landfall along the east coast of India.

VIIRS Day/Night Band images from before and after Super Cyclone Phailin made landfall along the east coast of India.

Notice the lack of lights in and around the small city of Berhampur. That’s roughly where Phailin made landfall. Also, notice the difference in appearance of the metropolitan area of Calcutta. It almost appears as if the city was cut in two as a result of electricity being out in large parts of the city.


UPDATE #2 (15 October 2013): Thanks to Renate B., we’ve figured out the bright lights over the Bay of Bengal near the coast of Myanmar (Burma) are due to offshore oil and gas operations. Take a look at the map on this website. See the yellow box marked “A1 & A3”? That is a hotly contested area for gas and oil drilling, right where the bright lights are. It is claimed by Burma (Myanmar) and India, China and South Korea are all invested in it. China has built a pipeline out to the site that cuts right through Myanmar (Burma) that some of the locals are not happy about.


UPDATE #3 (16 October 2013): It was pointed out to me that the maximum IR brightness temperature in the eye of the cyclone in the 20:04 UTC 10 October 2013 image was 297.5 K (24.4 °C), which is pretty warm for a hurricane/cyclone/typhoon eye. It is rare for the observed IR brightness temperature inside the eye to exceed 25-26 °C. Of course, the upper limit is the sea surface temperature, which is rarely above 31-33 °C. And the satellite’s spatial resolution affects the observed brightness temperature, along with a number of other factors.

A warm eye is related to a lack of clouds in (or covering up) the eye, the eye being large enough to see all the way to the surface at the viewing angle of satellite, the satellite having high enough spatial resolution to identify pixels that don’t contain cloud, and the underlying sea surface temperature. Powerful, slow moving storms may churn the waters enough to mix cooler water from the thermocline up into the surface layer, reducing the sea surface temperature. Heavy rains and cloud cover from the storm may also lower the sea surface temperature. Phailin was generally over 28-29 °C water, and was apparently moving fast enough (or the warm water was deep enough) to not mix too much cool water from below (a process called upwelling).

It may or may not have any practical implications, but the high resolution IR imagery VIIRS is able to produce may break some records on warmest brightness temperature ever observed in a tropical cyclone eye.