October 2016 Puzzler

October 24th, 2016 by Pola Lem

october_puzzler_2016

Every month on Earth Matters, we offer a puzzling satellite image. The October 2016 puzzler is above. Your challenge is to use the comments section to tell us what part of the world we are looking at, when the image was acquired, what the image shows, and why the scene is interesting.

How to answer. Your answer can be a few words or several paragraphs. (Try to keep it shorter than 200 words). You might simply tell us what part of the world an image shows. Or you can dig deeper and explain what satellite and instrument produced the image, what spectral bands were used to create it, or what is compelling about some obscure speck in the far corner of an image. If you think something is interesting or noteworthy, tell us about it.

The prize. We can’t offer prize money or a trip to Mars, but we can promise you credit and glory. Well, maybe just credit. Roughly one week after a puzzler image appears on this blog, we will post an annotated and captioned version as our Image of the Day. In the credits (and also on this blog), we will acknowledge the person who was first to correctly ID the image. We may also recognize certain readers who offer the most interesting tidbits of information about the geological, meteorological, or human processes that have played a role in molding the landscape. Please include your preferred name or alias with your comment. If you work for or attend an institution that you want us to recognize, please mention that as well.

Recent winners. If you’ve won the puzzler in the last few months or work in geospatial imaging, please sit on your hands for at least a day to give others a chance to play.

Releasing Comments. Savvy readers have solved some of our puzzlers after only a few minutes or hours. To give more people a chance to play, we may wait between 24-48 hours before posting the answers we receive in the comment thread.

Good luck!

Editor’s Note: Congratulations to Peter Gunnarsson, and James Varghese for being some of the first readers to solve the puzzler on Facebook. Congratulations to Vera Maria for being the first to weigh in with the answer on Earth Matters. See a labeled version of the October puzzler here.

September 2016 was Warmest on Record by Narrow Margin

October 18th, 2016 by Michael Cabbage & Leslie McCarthy

September 2016 was the warmest September in 136 years of modern record-keeping, according to a monthly analysis of global temperatures by scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York.

tempanoms_gis_september2016

NASA Earth Observatory chart by Joshua Stevens, based on data from the NASA Goddard Institute for Space Studies.

September 2016’s temperature was a razor-thin 0.004 degrees Celsius warmer than the previous warmest September in 2014. The margin is so narrow those two months are in a statistical tie. Last month was 0.91 degrees Celsius warmer than the mean September temperature from 1951-1980.

The record-warm September means 11 of the past 12 consecutive months dating back to October 2015 have set new monthly high-temperature records. Updates to the input data have meant that June 2016, previously reported to have been the warmest June on record, is, in GISS’s updated analysis, the third warmest June behind 2015 and 1998 after receiving additional temperature readings from Antarctica. The late reports lowered the June 2016 anomaly by 0.05 degrees Celsius to 0.75.

“Monthly rankings are sensitive to updates in the record, and our latest update to mid-winter readings from the South Pole has changed the ranking for June,” said GISS director Gavin Schmidt. “We continue to stress that while monthly rankings are newsworthy, they are not nearly as important as long-term trends.”

The monthly analysis by the GISS team is assembled from publicly available data acquired by about 6,300 meteorological stations around the world, ship- and buoy-based instruments measuring sea surface temperature, and Antarctic research stations. The modern global temperature record begins around 1880 because previous observations didn’t cover enough of the planet. Monthly analyses are updated when additional data become available, and the results are subject to change.

Related Links
+ For more information on NASA GISS’s monthly temperature analysis, visit: data.giss.nasa.gov/gistemp.

+ For more information about how the GISS analysis compares to other global analysis of global temperatures, visit:
http://earthobservatory.nasa.gov/blogs/earthmatters/2015/01/21/why-so-many-global-temperature-records/

+ To learn more about climate change and global warming, visit:
http://earthobservatory.nasa.gov/Features/GlobalWarming/

Hurricane Roundup: Matthew from Above

October 14th, 2016 by Pola Lem

screenshot-2016-10-14-17-33-32

After Hurricane Matthew ripped through Haiti, it blew through the Southeast. From above, NASA satellites, aircraft, and astronauts kept watch on the storm. The Earth Observatory published several images of the destructive storm (thumbnails above). The below includes a sampling of other notable images and maps related to the storm.

Soil Moisture
Matthew drenched the Carolinas, breaking records for single day rainfall in six places, The Washington Post reported. The Southeast received a total of 13.6 trillion gallons of water—that’s three-fourths the volume of the Chesapeake Bay. Hard-hit areas of North Carolina received 15 inches (38 centimeters) of rain.

That downpour saturated the area, causing values for soil moisture to increase substantially. The North American Land Data Assimilation System (NLDAS) mapped these values for October 1, 2016.

Even before the storm arrived, the ground in many areas was saturated. Eastern North Carolina and northeastern South Carolina have localized areas over the 98th percentile. That means that on October 1, the soil was wetter than it was on that date in 98 percent of previous years. The already-wet soils and heavy precipitation from Matthew led to significant flooding in these areas.

carolinas_01oct2016_nldas-sm-perc

Image: NASA

Temperature and Precipitation
The Jet Propulsion Laboratory (JPL) HAMSR instrument flew above Hurricane Matthew on October 7, 2016, aboard a NASA Global Hawk aircraft. The image below shows atmospheric temperatures overlaid atop ground-based radar and satellite visible images, according to a JPL release. Reds tones show a lack of clouds, whereas blue tones show ice and heavy precipitation. At the top left is an image taken from the Global Hawk.

hamsr_resized

Image: JPL/NASA


Clouds Swirling from Above
Expedition 49 astronaut Kate Rubins took the photograph below from the International Space Station at 21:05 Universal Time, on October 4, 2016, as the hurricane approached the Florida coast. Hurricane clouds fill the shot, which includes the station’s solar arrays.

iss049e028833

Photo: NASA/Kate Rubins

Louisiana

Heavy rains fell on Louisiana in August 2016, causing record-high crests for a number of rivers in the area. Map by Joshua Stevens/NASA Earth Observatory.

In the United States, we say “it’s raining cats and dogs” when we get a heavy downpour. In South Africa, it rains “women with clubs.” In Slovakia, a good soak means “tractors are falling.”

World languages brim with rainy day idioms. But when it comes to describing copious amounts of wet stuff, meteorologists do not encourage wordplay. Researchers are particularly adamant about one expression that does not work: the “rain bomb.”

The summer of 2016 brought extreme rain to multiple parts of the U.S., taking lives and causing billions  in property damage. In July, thunderstorms dumped more than six inches of rain on Elicott City, Maryland in roughly two hours, causing flash floods that upended cars and lives. In May, nearly eight inches of rain fell in two days, among a series of heavy rains to inundate Texas. Most recently in Louisiana, more than 30 inches of rain fell in three days, stranding 20,000 people and killing nine.

The Louisiana storm didn’t meet the criteria of a tropical depression as defined by the National Hurricane Center: a tropical cyclone in which the maximum sustained surface wind speed is 38 miles per hour (62 kilometers per hour) or less. In another instance of precise wording, 2012’s Hurricane Sandy technically ceased to be a “hurricane” a few hours before it made landfall, turning into a “post-tropical cyclone.”

For some in the media, “tropical depression” lacks pizzazz and conviction. It lacks the visceral pelting of tractors falling out of the sky or of women with clubs beating down on the Earth. Some news organizations referred to the Louisiana event as a rain bomb. So what should we call severe rain?

NASA scientists George Huffman and Owen Kelley parsed some of the commonly-used rain terminology.  

For one, there’s the “rain shaft.” A rain shaft is a centralized column of precipitationnot necessarily heavy rain. “The rain shaft […] is any rain event, no matter how modest or foreboding, that can be seen stretching from the cloud to the ground,” wrote Huffman, a research meteorologist at NASA’s Goddard Space Flight Center.

Then, there are “microbursts.” These are severe wind events caused by a “small column of exceptionally intense and localized sinking air that results in a violent outrush of air at the ground,” according to AccuWeather. Microbursts are smaller than 2.5 miles (4 kilometers) in size.

Be careful of mixing rain shafts with microbursts, Huffman cautioned.

“Just as you don’t have a microburst with every rain shaft, you don’t necessarily have an identifiable rain shaft with every microburst,” wrote Huffman in an email. “The really interesting dynamics of microbursts are a bit rare, and frequently not present in flooding rains.”

There’s also a size distinction between the different systems, NASA scientists said. A rain shaft comes out of an individual convective cell, making it roughly five to ten kilometers across. (By contrast, tropical depressions measure roughly 100 to 500 kilometers across.)

But in some cases, like Louisiana’s, the term “tropical depression” works, said Owen Kelley. “You don’t need to appeal to rain shafts, microbursts, or rain bombs to explain this system,” Kelley wrote in an email. The storm in Louisiana was “just a plain-old tropical depression that got stuck in one place for several days in a row and therefore dumped a lot of rain in one place.” That weather system did display some of the common signs of a tropical system. For instance, Huffman notes that it had low pressure at low and middle altitudes, and high pressure at the top, “implying some degree of warm core.” (Mid-latitude systems have a cold core, with the most negative pressure deviation at the system’s top.)

Researchers agree, though, about one term, “rain bomb,” which appeared in a couple of articles this summer in reference to extreme rainfall events. Don’t use it, scientists said. While it makes for a catchy headline, “rain bomb” is not an established meteorological term.  

For extreme rain, Kelley suggested yet another phrase: “vigorous convective cells.” These severe rainstorms can take on various forms: super-cells, squall lines, isolated cells.

Microbursts, rain shafts, vigorous convective cells. At the end, isn’t it all just wet stuff coming out of the sky? Yes and no, scientists say. Terms used to describe extreme rain should be used with an eye on precision. As extreme rains (and extreme weather, in general) become more frequent, so will the terms we use to describe them.

Julia: A Drenching, Perplexing Tropical Storm

September 28th, 2016 by Kathryn Hansen

julia_tmo_2016258

Tropical Storm Julia made headlines in September 2016, but not in the usual way. It wasn’t a particularly strong or destructive storm, although it brought heavy rainfall to coastal areas of the eastern United States from Florida to Virginia. The unusual aspect was where it formed: Julia became a tropical storm while over land, not over the ocean.

The image above, acquired at 11:55 a.m. Eastern Daylight Time (15:55 Universal Time) on September 14, 2016, with the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite, shows Julia over the southeastern United States. At the time, the storm was moving toward the east and had maximum sustained winds of about 55 kilometers (35 miles) per hour.

A NASA-funded study in 2013 by meteorologists Theresa Andersen and Marshall Shepherd described a new category of storm—one that draws energy from water on land. The research showed that some storms can derive energy from the evaporation of abundant soil moisture. Since publishing the research, Shepherd and colleagues have received frequent inquiries as to whether a particular storm was influenced by this “brown ocean” effect. In the case of Julia, the answer is not clear.

“I personally find it overly speculative to make that linkage right now,” Shepherd said. “Frankly, the Baton Rouge floods may have more of a link to the brown ocean than this event, which experienced quite a bit of moisture advection from the ocean.”

The uncertainty in Julia’s case comes from its position. Although the storm developed its center while over land, it was still too close to the ocean for scientists to distinguish an influence from land-based water. Read Shepherd’s full explanation here.

September Puzzler

September 20th, 2016 by Adam Voiland

september_puzzler_2016
Every month on Earth Matters, we offer a puzzling satellite image. The September 2016 puzzler is above. Your challenge is to use the comments section to tell us what part of the world we are looking at, when the image was acquired, what the image shows, and why the scene is interesting.

How to answer. Your answer can be a few words or several paragraphs. (Try to keep it shorter than 200 words). You might simply tell us what part of the world an image shows. Or you can dig deeper and explain what satellite and instrument produced the image, what spectral bands were used to create it, or what is compelling about some obscure speck in the far corner of an image. If you think something is interesting or noteworthy, tell us about it.

The prize. We can’t offer prize money or a trip to Mars, but, we can promise you credit and glory. Well, maybe just credit. Roughly one week after a puzzler image appears on this blog, we will post an annotated and captioned version as our Image of the Day. In the credits (and also on this blog), we will acknowledge the person who was first to correctly ID the image. We may also recognize certain readers who offer the most interesting tidbits of information about the geological, meteorological, or human processes that have played a role in molding the landscape. Please include your preferred name or alias with your comment. If you work for or attend an institution that you want us to recognize, please mention that as well.

Recent winners. If you’ve won the puzzler in the last few months or work in geospatial imaging, please sit on your hands for at least a day to give others a chance to play.

Releasing Comments. Savvy readers have solved some of our puzzlers after only a few minutes or hours. To give more people a chance to play, we may wait between 24-48 hours before posting the answers we receive in the comment thread.

Good luck!

Editor’s Note: Congratulations to Cait Stuart, Tyler Keaton, and Rosemary Butt for being some of the first readers to solve the puzzler on Facebook. Congratulations to Adam Liefloff for being the first to weigh in with the answer on Earth Matters. See a labeled version of the September puzzler here.

 

 

While I was interviewing University of North Carolina climate scientist Wei Mei about his new research that shows a significant increase in the intensity of land-falling typhoons in the western Pacific, the strongest storm of the 2016 season (Super Typhoon Meranti) was on the verge of slamming into China after grazing Taiwan.

“Meranti fits the trend,” said Wei. “In 2016 so far, there have been six typhoons in the northwestern Pacific. Three have already made it to category 4 or 5. In the late 1970s, only about one-quarter of typhoons reached that strength. Now about half do.”

meranti_tmo_2016258

NASA Earth Observatory MODIS image of Super Typhoon Meranti.

Some meteorologists have mused that with sustained winds of 165 knots (190 miles per hour), Meranti would have been the equivalent of a Category 6 storm—if the Saffir-Simpson scale actually went that high. (It maxes out at 5). Even though Meranti only grazed southern Taiwan, it still knocked out power to 500,000 households and produced giant waves along the coast.

The focus of Mei’s research, however, is not Meranti or the 2016 typhoon season. Working with colleague Shang-Ping Xie of Scripps Institution of Oceanography, Mei has been digging through records that detail every typhoon in the northwestern Pacific since 1977 and looking for changes in the intensity of storms. What they found was a strong increase in typhoon intensity. Overall, landfalling storms strengthened by about 15 percent over the past four decades, with the proportion of typhoons reaching categories 4 and 5 more than doubling. Mei and Xie showed that storms that passed over waters relatively near to land and moved toward land (red and green dots in the chart below) have strengthened the most. Those that stayed out over the open ocean (black and blue dots) did not strengthen by a significant amount.

screen-shot-2016-09-15-at-1-08-06-pm

Figure from Mei and Xie, 2016.

“Elevated rates of warming in coastal seas (in comparison to the open ocean) are the reason for the intensification of land-falling typhoons,” said Mei. Between 1977 and 2013, many coastal areas in Asia have warmed by upwards of 0.20 degrees Celsius (0.36 degrees Fahrenheit) per decade along the coasts—more than twice as much as open ocean areas.  In the chart below, notice all the deep reds (more warming) near the coasts; farther out to sea tends to be yellow and orange (less warming).

screen-shot-2016-09-15-at-5-05-11-pm

Figure from Mei and Xie, 2016.

“We are not arguing that the warming of the coastal seas is due to greenhouse gas-driven climate change; that would require attribution studies that we have not conducted yet,” he said. “But we feel confident that land-falling storms are getting stronger because of rising sea surface temperatures, particularly in a band off the coast of East and Southeast Asia.” A related 2015 study led by Mei argued that sea surface temperatures are a more important factor in controlling long-term variations in typhoon intensity than other factors, such as vertical wind shear.

In this study, Mei and Xie did not look at the frequency of storm development. Some storm researchers have argued that a warming world may make hurricanes and typhoons stronger but less frequent.

For more details about Mei and Xie’s latest study, read more from Scripps Institution of Oceanography, The Verge, and Nature Geoscience.

himawari_09214_stormearthmeranti

Himawari-8 image of Super Typhoon Meranti and night lights (in orange) of Asia via Colorado State University and Mashable.

 

Visualizing the Warmest August in 136 Years

September 12th, 2016 by Leslie McCarthy & Michael Cabbage

August 2016 was the warmest August in 136 years of modern record-keeping, according to a monthly analysis of global temperatures by scientists at NASA’s Goddard Institute for Space Studies (GISS).

Although the seasonal temperature cycle typically peaks in July, August 2016 wound up tied with July 2016 for the warmest month ever recorded. August 2016’s temperature was 0.16 degrees Celsius warmer than the previous warmest August (2014). The month also was 0.98 degrees Celsius warmer than the mean August temperature from 1951-1980.

tempanoms_gis_august2016

NASA Earth Observatory chart by Joshua Stevens, based on data from the NASA Goddard Institute for Space Studies.

 

“Monthly rankings, which vary by only a few hundredths of a degree, are inherently fragile,” said GISS Director Gavin Schmidt. “We stress that the long-term trends are the most important for understanding the ongoing changes that are affecting our planet.” Those long-term trends are apparent in the plot of temperature anomalies above.

The record warm August continued a streak of 11 consecutive months (dating to October 2015) that have set new monthly temperature records. The analysis by the GISS team is assembled from publicly available data acquired by about 6,300 meteorological stations around the world, ship- and buoy-based instruments measuring sea surface temperature, and Antarctic research stations. The modern global temperature record begins around 1880 because previous observations didn’t cover enough of the planet.

Related Links
+ For more information on NASA GISS’s monthly temperature analysis, visit: data.giss.nasa.gov/gistemp.

+ For more information about how the GISS analysis compares to other global analysis of global temperatures, visit:
http://earthobservatory.nasa.gov/blogs/earthmatters/2015/01/21/why-so-many-global-temperature-records/

+ To learn more about climate change and global warming, visit:
http://earthobservatory.nasa.gov/Features/GlobalWarming/

Related Reading in the News
+ Mashable: Earth sets record for hottest August, extending warm streak another month
http://mashable.com/2016/09/12/earth-warmest-august-hottest-summer/#ivXnyy8yusqu

+ XKCD: A Timeline of Earth’s Average Temperature
http://xkcd.com/1732/

+ Climate Central: August Ties July as Hottest Month Ever on Record
http://www.climatecentral.org/news/august-ties-july-as-hottest-month-on-record-20691

August Puzzler

August 29th, 2016 by Pola Lem

puzzler_201608_revised

Every month on Earth Matters, we offer a puzzling satellite image. The August 2016 puzzler is above. Your challenge is to use the comments section to tell us what part of the world we are looking at, when the image was acquired, what the image shows, and why the scene is interesting.

How to answer. Your answer can be a few words or several paragraphs. (Try to keep it shorter than 200 words). You might simply tell us what part of the world an image shows. Or you can dig deeper and explain what satellite and instrument produced the image, what spectral bands were used to create it, or what is compelling about some obscure speck in the far corner of an image. If you think something is interesting or noteworthy, tell us about it.

The prize. We can’t offer prize money, but, we can promise you credit and glory (well, maybe just credit). Roughly one week after a puzzler image appears on this blog, we will post an annotated and captioned version as our Image of the Day. In a blog post, we’ll acknowledge the person who was first to correctly ID the image. We’ll also recognize people who offer the most interesting tidbits of information about the geological, meteorological, or human processes that have played a role in molding the landscape. Please include your preferred name or alias with your comment. If you work for or attend an institution that you want us to recognize, please mention that as well.

Recent winners. If you’ve won the puzzler in the last few months or work in geospatial imaging, please sit on your hands for at least a day to give others a chance to play.

Releasing Comments. Savvy readers have solved some of our puzzlers after only a few minutes or hours. To give more people a chance to play, we may wait between 24-48 hours before posting the answers we receive in the comment thread.

Good luck!


Editor’s Note: The answer to this puzzler was Clew Bay in Ireland, the Bay of the Partly Drowned Hills. Though we had many readers submit the correct location, a special congratulations to Brendan Conway for being the first to do so on Earth Matters. And congratulations also to Thomas Es Thomas for sharing some interesting details about the image on Facebook.

6 Ways Earth Observations Tackle Real-World Problems

August 29th, 2016 by Kathryn Hansen, Mike Carlowicz, and Pola Lem

This summer, recent college graduates and early career professionals launched 30 small research projects as part of NASA’s DEVELOP program. The aim is to use NASA satellite observations of Earth to address an environmental or public policy issue. The young researchers have just 10 weeks to do it!

On Aug. 10, 2016, the “DEVELOPers” gathered at NASA Headquarters in Washington, D.C., to showcase their results. So, how can Earth observations solve real-world problems? Let’s take a look:

1. They help land managers identify the locations of invasive species.

Image credit: NASA/Bill Ingalls

Image credit: NASA/Bill Ingalls

Austin Haney, DEVELOP project co-lead at University of Georgia, has seen first-hand how an invasive species can affect the ecosystem of Lake Thurmond, a large reservoir that straddles Georgia and South Carolina. Birds in the area “behave visibly different,” he said, after they consume a toxic cyanobacteria that lives on Hydrilla verticillata, an invasive aquatic plant. Ingesting the toxin causes a neurodegenerative disease and ultimately death. Scores of birds have been found dead in areas where large amounts of the toxin-supporting Hydrilla grow. To help lake managers better address the situation, Haney and project members developed a tool that uses data from the Landsat 8 satellite to map the distribution of Hydrilla across the lake.

 

2. They help identify wildlife habitat threatened by wildfires.

Image Credit: NASA/Bill Ingalls

Image credit: NASA/Bill Ingalls

Maps that depict habitat and fire risk in eastern Idaho previously stopped short of Craters of the Moon National Monument, where shrubs and grasses transition to a sea of ankle-twisting basalt. But the environment is not as inhospitable as it first appears. Throughout the monument there are more than 500 kipukas — pockets of older lava capable of supporting some vegetation. That means they are also prone to burning. Project lead Courtney Ohr explained how her team used data from the Landsat 8 and Sentinel-2 satellites to simulate the area’s susceptibility to wildfires. Decisionmakers can use this model to monitor the remote wildlife habitat from afar.

 

3. In conjunction with Instagram, they help find seaweed blooms

Image credit: Caribbean Oceans Team

Image credit: Caribbean Oceans Team

Who knew that Instagram could be a tool for science? One DEVELOP team searched for photographs of massive seaweed (sargassum) blooms in the Caribbean, mapped the locations, and then checked what satellites could see. In the process, they tested two techniques for finding algae and floating vegetation in the ocean.

 

4. They help conserve water by reducing urban stormwater runoff.

Image credit: NASA/Bill Ingalls

Image credit: NASA/Bill Ingalls

Atlanta’s sewer system is among the nation’s most expensive, yet the city still struggles with stormwater. It’s an uphill climb as new construction paves over more of the city, removing landscapes that could absorb rain. The University of Georgia DEVELOP team partnered with The Nature Conservancy to address the problem.

Using satellite imagery, the team pinpointed 17 communities ripe for more green infrastructure and reforestation that could capture more of the city’s runoff. The team used two models — Land-Use Conflict Identification Strategy and the Soil and Water Assessment Tool — as well as the Landsat and Terra satellite data. Their analysis provides local groups with a working picture of the city’s water resources.

 

5. They show the spread of the mite eating away Puerto Rico’s palm trees.

Image credit: NASA/Bill Ingalls

Image credit: NASA/Bill Ingalls

The red palm mite has devastated Puerto Rico’s trees in recent years, chewing through coconut palms, bananas, and plantains on the island. The pests have spread and hurt crops across the Caribbean.

A DEVELOP team led by Sara Lubkin analyzed satellite imagery to track the mites’ rapid spread from 2002. The team mapped changes to vegetation (such as yellowing) and differences in canopy structure. They made use of imagery from Landsat, Hyperion, and IKONOS, as well as aerial views. Their work can be used to mitigate current mite infestations and monitor and prevent future ones.

 

6. They evaluate landslide-prone areas in the developing world

Image credit: East Africa Disasters II Team

Image credit: East Africa Disasters II Team

One team of DEVELOPers took on a project to aid people in developing nations. They examined satellite imagery to find past landslides in the African nation of Malawi. Factors such as flooding after long periods of drought have made the country increasingly prone to landslides. Blending maps of the landscape, rainfall data, and population centers, the young researchers assessed the areas most at risk—and most in need of education and support—from landslides.

Want to read more about DEVELOP projects? Want to get involved? Summaries, images, and maps of current and past projects can be viewed HERE. You can also learn how to apply for the DEVELOP program HERE.