Ice, Ice, Baby

A winter storm moved through the Northeast U.S. over the weekend of 19-20 January 2019. This Nor’easter was a tricky one to forecast. Temperatures near the coast were expected to be near (or above) freezing. Temperatures inland were expected to be much colder. Liquid-equivalent precipitation, at least according to the GFS, was predicted to be in the 1-3 inch (25-75 mm) range the day before. This could easily convert to 1-2 feet (30-60 cm) of snow. The question on everyone’s mind: who gets the rain, who gets the snow, and who gets the “wintry mix”? The fates of ~40 million people hang in the balance. This is one of the situations that meteorologists live for!

The difference between 71°F and 74°F is virtually meaningless. The difference between 31°F and 34°F (with heavy precipitation, at least) is the difference between closing schools or staying open. It’s the difference between bringing out the plows or keeping them in the garage; paying overtime for power crews to keep the electricity flowing or just another work day; shutting down public transportation or life as usual.

Of course, the obvious follow-up question is: what is the “wintry mix” going to be? Rain mixed with snow? Sleet? Freezing rain? It doesn’t take much to change from one to the other, but there can be a big difference on the resulting impacts based on what ultimately falls from the sky.

So, what happened? Here’s an article that does a good job of explaining it. And, here are PDF files of the storm reports from National Weather Service Forecast Offices in Albany, Boston (actually in Norton, MA) and New York City (actually in Upton, NY). The synopsis: some places received ~1.5 inches (~38 mm) of rain, some places received ~11 inches (~30 cm) of snow and some places were coated in up to 0.6 inches (15 mm) of ice.

Of particular relevance here are the locations that received the ice. If you took the locations listed in the storm reports that had more than 0.1 inches (2.5 mm) of ice (at least the ones in Connecticut) and plotted them on a map, they match up quite well with this map of power outages that came from the article I linked to:

Map of power outages in Connecticut as a result of an ice storm (19-20 January 2019)

Map of power outages in Connecticut as a result of an ice storm (19-20 January 2019). Image courtesy Eversource/NBC Connecticut.

Now, compare that map with this VIIRS image from 22 January 2019 (after the clouds cleared out):

VIIRS channel I-3 image from NOAA-20, 17:09 UTC 22 January 2019

VIIRS channel I-3 image from NOAA-20, 17:09 UTC 22 January 2019

As always, you can click on the image to bring up the full resolution version. This is the high-resolution imagery band, I-3, centered at 1.6 µm from NOAA-20. Notice that very dark band stretching from northern New Jersey into northern Rhode Island? That’s where the greatest accumulation of ice was. Notice how well it matches up with the known power outages across Connecticut!

The ice-covered region appears dark at 1.6 µm because ice is very absorbing at this wavelength and, hence, it’s not very reflective. And, since it is cold, it doesn’t emit radiation at this wavelength either (at least, not in any significant amount). This is especially true for pure ice, as was observed here (particularly the second image), since there aren’t any impurities in the ice to reflect radiation back to the satellite. The absorbing nature of snow and ice compared with the reflective nature of liquid clouds is what earned this channel the nickname “Snow/Ice Band” (PDF).

At shorter wavelengths (less than ~ 1 µm), ice and snow are reflective. (Note how a coating of ice makes everything sparkle in the sunlight.) This makes it nearly impossible to tell where the ice accumulation was in True Color images:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 from NOAA-20, 17:09 UTC 22 January 2019

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 from NOAA-20, 17:09 UTC 22 January 2019

The Natural Color RGB (which the National Weather Service forecasters know as the Day Land Cloud RGB (PDF file)) includes the 1.6 µm band, which is what makes it useful for discriminating clouds from snow and ice. And, as expected, the region of ice accumulation does show up (although it is tempered by the highly reflective nature of snow and ice in the visible and “veggie” bands that make up the other components of the RGB):

VIIRS Natural Color RGB composite of channels, I-1, I-2 and I-3 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS Natural Color RGB composite of channels, I-1, I-2 and I-3 from NOAA-20 (17:09 UTC, 22 January 2019)

Another RGB composite popular with forecasters is the Day Snow/Fog RGB (PDF file), where blue is related to the brightness temperature difference between 10.7 µm and 3.9 µm, green is the 1.6 µm reflectance, and red is the reflectance at 0.86 µm (the “veggie” band). This shows the region of ice even more clearly than the Natural Color RGB:

VIIRS Day Snow/Fog RGB composite of channels (I-5 - I-4), I-3 and I-2 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS Day Snow/Fog RGB composite of channels (I-5 minus I-4), I-3 and I-2 from NOAA-20 (17:09 UTC, 22 January 2019)

Breaking things up into the individual components, we can see how the ice transitions from being reflective in the visible and near-infrared (near-IR) to absorbing in the shortwave-IR:

VIIRS high-resolution visible channel, I-1, from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution visible channel, I-1 (0.64 µm), from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution "veggie" channel, I-2, from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS high-resolution “veggie” channel, I-2 (0.86 µm), from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-8 from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-8 (1.24 µm) from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-11  from NOAA-20 (17:09 UTC, 22 January 2019)

VIIRS channel M-11 (2.25 µm) from NOAA-20 (17:09 UTC, 22 January 2019)

Of course, the 1.6 µm image was already shown, so I didn’t bother to repeat it. If you squint, you can even see a hint of the ice signature at 1.38 µm, the “Cirrus Band“, where most of the surface signal is blocked by water vapor absorption in the atmosphere:

VIIRS "cirrus" channel, M-9, from NOAA-20 (17:09 UTC 22 January 2019)

VIIRS “cirrus” channel, M-9 (1.38 µm), from NOAA-20 (17:09 UTC 22 January 2019)

If the ice had accumulated in southern New Jersey or Pennsylvania, though, it would not have shown up in this channel, since the air was too moist at this time to see all the way down to the surface. But, you can compare this image with the previous images to see why they call it the “cirrus band”, since the cirrus does show up much more clearly here.

So, mark this down as another use for VIIRS: detecting areas impacted by ice storms. And remember, even though ice storms may have a certain beauty, they are also dangerous. And, not just for the obvious reasons. This storm in particular came complete with ice missiles. So, for the love of everyone else on the road, scrape your car clean of ice before risking your life out there!

Sea-effect Snow

Take a look at this image:

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

Photo credit: İskender Şengör via Severe Weather Europe on Facebook

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

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

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

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

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

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

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

VIIRS "True Color" RGB composite, taken 19:24 UTC 7 January 2015

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

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

VIIRS "Natural Color" RGB composite, taken 19:24 UTC 7 January 2015

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

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

VIIRS "Natural Color" RGB composite, taken 10:36 UTC 8 January 2015

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

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

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

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

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

VIIRS "Natural Color" RGB composite, taken 03:48 UTC 8 January 2015

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

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

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

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

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

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

 

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

VIIRS "Natural Color" RGB composite, taken 17:29 UTC 13 January 2015

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

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

Beginning of Autumn in the Great Lakes

Have you noticed it? The seasons are changing (for the mid- and high latitudes, at least). Days are getting shorter (or longer if you live in the upside-down hemisphere). This time of year, if you live in Alaska or Scandinavia or similar high latitude locations, you lose about 5-10 minutes of available daylight each day. (That’s between a half and one hour per week!) You may have noticed by the fact that your neighbor no longer mows the lawn at 11:00 PM because it’s still bright outside and hey, why not? I wasn’t going to sleep anyway.

Closer to home – in the mid-latitudes – loss of daylight is more like 1-3 minutes per day, which isn’t as noticeable. But, one day, you watch the sun set and look at the clock and realize that it’s only 6:30 PM and you think, didn’t it used to be light out later than this?

That’s not the only way to tell the seasons are changing. For one, there’s the arrival of snow. (Although parts of Montana, Wyoming and South Dakota received snow earlier this year while it was still technically summer.)  And, for two, there’s what VIIRS observed on 27 September 2014:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:57 UTC 27 September 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:57 UTC 27 September 2014

In case it’s not obvious, here’s what VIIRS saw earlier in the month (8 September 2014):

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:13 UTC 8 September 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:13 UTC 8 September 2014

Notice anything different between the two images? (Remember to click on the images, then on the “1735 x 1611” links below the banner to see the images in full resolution.)

That’s right – the loss of daylight leads to one of the benefits of autumn: fall foliage. VIIRS True Color imagery shows, quite clearly, that the leaves of New England and eastern Canada have changed color. Forests that were green in early September have turned orange, red and brown by the end of the month.

Another thing you may have noticed comparing those two images: the change from green to beige in the area around Montreal, Quebec. This is another sign of autumn: the fall harvest. This is a productive agricultural region in eastern Canada, and what you are seeing is the green vegetation (crops) being harvested, leaving behind bare dirt.

True Color imagery is useful for observing the changing foliage and the harvest because it is designed to reproduce what we humans observe on the ground. The red, green and blue components of the RGB composite are channels in the red (M-5, 0.67 µm), green (M-4, 0.55 µm) and blue (M-3, 0.48 µm) portions of the electromagnetic spectrum. When leaves change from green to red, the True Color RGB detects that.

Now, you’ve probably known since elementary school (or at least middle school) that leaves change color because of chlorophyll. And, unless you became a botanist, that is probably the limit of your knowledge on the subject. But, there’s a lot of interesting chemistry that goes on inside a leaf (and the whole tree) that determines it’s color.

Of course, leaves are green because they contain chlorophyll. Chlorophyll is necessary for plants to convert sunlight into sugar. Chlorophyll, by necessity due to it’s job, is highly absorbing of visible-wavelength radiation, although it is slightly less absorbing of green wavelengths. Green light is therefore preferentially reflected out of the leaves and into your eye, and the leaves appear green.

When the sunlight goes away and the air becomes cold, deciduous trees go into hibernation. They break down the chlorophyll in their leaves, and send the remaining nutrients down into the trunk and roots. This exposes the carotinoids that were in the leaves and these carotinoids have a yellow or orange color – they preferentially reflect yellow and/or orange wavelengths. Red colors come from a pigment called anthocyanin, which was recently discovered to be a sort of “plant sunscreen”.

Now, utilizing sunscreen when you get all your energy from the sun may sound silly but, recent studies have shown that anthocyanin protects the leaves from sun damage once the chlorophyll is gone so that the tree has time to extract all the nutrients out of the leaves before they fall off. Trees in poor soil conditions are more likely to turn red in the fall as a natural defense mechanism – they need to store all the nutrients they can from their leaves, since they aren’t getting them from the soil.

Oak and other leaves turn brown in the fall because of a buildup of tannin (link to PDF file), which is a waste product. Brown leaves are full of plant poo! Think about that the next time you go on a fall color driving tour.

Now, back to the satellite science before the biologists come after me for grossly oversimplifying leaf chemistry. I’ve often talked about the Natural Color RGB composite as being similar to the True Color RGB in many instances (except for the detection of ice and snow). So, what does that look like here?

Here’s the VIIRS Natural Color RGB from 8 September 2014:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 17:13 UTC 8 September 2014

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 17:13 UTC 8 September 2014

And here’s the same RGB from 27 September 2014:

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 17:57 UTC 27 September 2014

VIIRS Natural Color RGB composite of channels M-5, M-7 and M-10, taken 17:57 UTC 27 September 2014

Why does the vegetation still appear green when the leaves have changed color? Because we’ve made vegetation artificially appear green. The Natural Color RGB uses the red wavelength visible channel (M-5, 0.67 µm) as the blue component. The green component is a near-infrared channel (M-7, 0.87 µm), where plants are their most reflective – leaves and other plant tissues don’t absorb radiation at this wavelength. The red component is a longer wavelength channel (M-10, 1.61 µm) where the water inside the leaves starts to absorb radiation and the reflectance goes down. Cellulose and lignin also weakly absorb at 1.61 µm. The bottom line is, plants are highly reflective at 0.87 µm regardless of how healthy the plant is, or what color the leaves are – so they will always appear green in the Natural Color images.

You might also note the one difference (apart from clouds) that shows up between the two Natural Color images is the lack of green surrounding Montreal in the 27 September image. This is another sign of the fall harvest: the highly reflective plants have been removed and all that’s left is dirt, which is not as reflective. That’s why those areas appear more brown in the later image.

If we look a bit further west in the True Color imagery from 27 September 2014, the fall color really stands out:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:57 UTC 27 September 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 17:57 UTC 27 September 2014

Fall colors are visible from the Adirondacks of Upstate New York and Quebec to the Upper Peninsula of Michigan. The most vivid fall color is in Ontario – both in the area of Sault Ste. Marie and in the area of Algonquin Provincial Park, the oldest provincial park in Canada. Every autumn, the Friends of Algonquin Park post pictures of the fall colors, including this shot from 27 September 2014 showing just what VIIRS was seeing. Amazing colors!

We have sunny days, cool nights and plant survival techniques to thank for that.

 

BONUS:

Here’s a desktop wallpaper that’s zoomed in on the above image and cropped to the most popular screen resolution (1366×768):

VIIRS True Color RGB Composite Desktop Wallpaper (17:57 UTC 27 September 2014)

VIIRS True Color RGB Composite Desktop Wallpaper (17:57 UTC 27 September 2014). This image fits monitors with a 16:9 ratio and is optimized for 1366×768 screen resolutions.

Make sure you click on the image, then on the “1366 x 768” link below the banner to get the full resolution image. Then you can right-click on the image and choose “Set as desktop background” to save it as your new desktop wallpaper.