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.

A Year in a Week – VIIRS Captures Colorado Flooding

A year’s worth of precipitation fell on parts of Colorado in one week’s time (9 September to 17 September 2013). As Colorado State Climatologist Nolan Doesken said, “Whenever you get your annual precip in a few days time, you’re in trouble.” So it is that this blog returns to flooding once again. Flooding that hit real close to home.

If you have an hour and a half available, you might want to watch this video with preliminary results and discussion about what happened given by scientists from the Colorado State University (CSU) Department of Atmospheric Science and CIRA (including Nolan Doesken and fellow JPSS Imagery Team member Dan Lindsey). If you don’t have an hour and a half, here’s an article with a good background on the events as they happened in Boulder (although if you’re a slow reader, it may not save you much time since it’s pretty comprehensive). A less comprehensive, 4-page summary of the event was put together by the University of Colorado-Boulder, the Colorado Climate Center (at CSU) and NOAA’s Earth System Research Laboratory (ESRL) which may be found here (PDF document).

The Colorado Climate Center and the Department of Atmospheric Science at CSU have put together this website to document the flood event. If you haven’t seen enough pictures of the flooding on the news or elsewhere on the internet, these two pages here and here give a good idea of the damage that resulted. By the end of September, 8 people were confirmed dead in Colorado as a result of the flooding.

Just to make sure that all of you have seen this, here are the precipitation totals (in inches) from various National Weather Service (NWS) Cooperative Observers, trained weather spotters, automated rain guages and CoCoRaHS members for the 7-day period ending on the 16 September 2013, put together by the Denver/Boulder NWS Forecast Office:

Preliminary rainfall totals over Northern Colorado, 9-16 September 2013

Preliminary rainfall totals (in inches) over Northern Colorado, 9-16 September 2013. Image courtesy NWS.

Remember to multiply those numbers by 25.4 if you’re used to using millimeters as the standard measure of rain. Also, keep in mind that this part of the world averages somewhere between 12 and 20 inches of precipitation per year.

From a satellite perspective, there really isn’t much (that isn’t classified) that can beat Digital Globe, a private company that specializes in high-resolution satellite imagery. Here’s what you can see with 0.5 m resolution. (Oh, how meteorologists would love to have data and forecast models on that kind of resolution – even if we’d all be drowning in yottabytes of data!)

In contrast, the high resolution imagery channels on VIIRS have ~350 m resolution, which is not enough to see each individual puddle, but it is enough to capture the flooding that occurred on the South Platte River subsequent to the 5-18 inches of rain that fell along the Front Range mountains.

Here’s what the “Natural Color” RGB composite of channels I-01 (0.64 µm, blue), I-02 (0.87 µm, green) and I-03 (1.61 µm, red) looked like before the flooding occurred:

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:49 UTC 7 September 2013

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:49 UTC 7 September 2013

Click on the image, then on the “1172×866″ link below the banner to see the full resolution version. Note that you can’t actually see the South Platte River before the flooding occurred, but you can see the dark olive color of the river valley (caused by the mixture of trees, other ground vegetation and rich soils along the river) and the swath of light green irrigated farmland on either side of the river.

The week that the flooding occurred, it was very cloudy (duh!), so VIIRS wasn’t able to see much. But, on the 14th (which people around here refer to as “that Saturday” because each day that week brought specific memories to those that lived through it) the clouds briefly broke enough for VIIRS to see that the South Platte River valley had begun to flood:

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:17 UTC 14 September 2013

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:17 UTC 14 September 2013. The yellow arrow indicates the furthest east extent of flooding along the South Platte River.

Look for the dark, bluish-greenish color (scientific term) extending as far east as the yellow arrow. That arrow is pointing to the leading edge of the flood water, which was near the town of Weldona at this time. Places upriver from there all the way to the north side of Denver were experiencing significant (even record breaking) flooding.

Three days later (17 September 2013, about one week after the flooding began) it was a really clear day over Colorado, which made it easy to see that the flooding made it past Fort Morgan and Sterling out to little Sedgwick:

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 20:01 UTC 17 September 2013

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 20:01 UTC 17 September 2013. The yellow arrow indicates the furthest east extent of flooding along the South Platte River at this time.

Two weeks after the flood began, flood waters made the South Platte River visible all the way to (and past) North Platte, Nebraska, another site of record flooding roughly 250 miles away from where the heavy rains occurred!

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:30 UTC 24 September 2013

VIIRS false-color RGB composite of channels I-01, I-02 and I-03, taken 19:30 UTC 24 September 2013. Note that the South Platte River is visible from Denver, CO to North Platte, NE as a result of the flooding.

Here’s a short animation of this sequence of images:

Animation of VIIRS false-color composites of channels I-01, I-02 and I-03 from 7-24 September 2013

Animation of VIIRS false-color composites of channels I-01, I-02 and I-03 from 7-24 September 2013

You have to click on the image, then on the “1172×866″ link to see the images loop.

It should also be said that this event didn’t just affect Colorado. Parts of New Mexico reported over 12 inches of rain and at least 1 death. Cheyenne, Wyoming just recorded the second wettest month on record (dating back to the late 1800s). And, as mentioned above, the flooding made it down the Platte River all the way to central Nebraska. And, as a piece of good news, this flood water is being used to refill the Ogallala Aquifer, which has been low due to long-term, drier-than-normal conditions.

Events like this generally bring more questions than answers: Was it a “100-year flood” or a “1000-year flood”? Could the forecasts have been better? If the forecasts were better, would anyone have believed them? How do you prepare for unprecedented events?