Under normal conditions, water quality tests find, at most, a few hundred K. brevis cells per liter of water—not enough to cause problems. But in August 2018, in the midst of one of the most severe red tide outbreaks to hit Florida’s Gulf Coast in a decade, water samples regularly contained more than one million K. brevis cells per liter.
That was enough to stain large swaths of coastal waters shades of green and brownish-red and leave beaches littered with rotting fish carcasses. Roughly 100 manatees, more than 200 sea turtles, and at least 12 dolphins have been killled by red tides, according to preliminary estimates. For much of August, the toxic bloom stretched about 130 miles (200 kilometers) along Florida’s Gulf coast, from roughly Tampa to Fort Myers. Though the bloom has been active since October 2017, it intensified rapidly in July 2018. The damage grew so severe and widespread that Florida’s governor declared a state of emergency in mid-August.
One of the best ways to test for the presence of K. brevis is to analyze water samples collected from boats or beaches. State environmental agencies do this on a regular basis, but understanding the full extent and evolution of fast-changing blooms, or predicting where they will move with ground sampling alone is a challenge.
Sampling red tide in 2018 (left). An aerial view of red tide in 2005 (right). Photo credits: Florida Fish and Wildlife Conservation Commission.
A screenshot from the University of South Florida’s Near Real-Time Integrated Red tide Information System (IRIS). The image shows various types of data captured by MODIS sensor on Terra on August 19, 2018. Solar-stimulated fluorescence data (NFLH) is particularly useful for locating algal blooms. Image Credit: USF/IRIS
Despite the utility of satellite observations, there are some significant challenges to interpreting satellite data of algal blooms in shallow, coastal waters, explained oceanographer Chuanmin Hu of the University of South Florida. Chief among them: it can be quite difficult to distinguish between algal blooms, suspended sediment, and colored dissolved organic matter (CDOM) that flows into coastal areas.
The Karenia brevis bloom expanded and intensified in late-July. This fluorescence data comes from the OCLI sensor on Sentinel 3. Image courtesy of Rick Stumpf, NOAA.
To get around this problem and make satellites better at pinpointing algal blooms, Hu and colleagues at the University of South Florida have developed a red tide monitoring system that makes use of MODIS observations of fluorescence, which algal bloom emit in response to exposure to sunlight. “If we have fluorescence data to go along with a natural-color image from MODIS, we can say with a high degree of confidence where the algal blooms are and where the sensor is just detecting sediment or CDOM,” he said. When fluorescence data is available, the Florida Fish and Wildlife Commission pushes it out to the public as part of its red tide status updates (see the August 21 update below).
Likewise, NOAA has combined a fluorescence method with a long-standing technique that identifies recent increases in chlorophyll concentration, the combination improves the identification of likely K. brevis blooms — information that then gets incorporated in NOAA’s HAB Forecast System, noted Richard Stumpf, an oceanographer with NOAA.
K. brevis cell abundance shown on an ocean color satellite image from the IRIS system. Warmer colors indicate higher levels of chlorophyll a, an indicator of algae. Cloudy areas are gray. Circles indicate locations where officials tested water samples on the ground. Image Credit: FFW/USF/IRIS.
However, that still leaves some big problems—only about ten percent of MODIS passes collect usable fluorescence data. The rest of the time images are marred by either sunglint or clouds. And the algorithm that scientists use to detect algal blooms with MODIS does not work well within one kilometer of the coast—the part that is of the greatest interest to beachgoers and boaters.
After recording, HABscope uploads videos to a cloud-based server for automatic analysis by computer software. The software rapidly counts the number of K. brevis cells in a water sample by using technology similar to that found in facial recognition apps. But rather than focusing on facial features, the software looks for a particular pattern in the movement of K. brevis cells.
K. brevis are vigorous swimmers, often using a pair of long, whip-like flagella to migrate vertically about 10 to 20 meters (33 to 66 feet) each day. They chart a zig-zagging, corkscrew-shaped path that allows the software to easily pick them out amidst the cast of other phytoplankton found in Gulf of Mexico water samples.
The data about K. brevis abundance at various locations along the coast is then fed into a respiratory distress forecasting tool managed by NOAA. “Respiratory distress forecasts can now be produced 1 to 2 times per day for specific beaches along the Florida Gulf Coast,” said Stumpf. “Previous to this project, these forecasts were issued at most twice a week, and only as general statements about risk within a county. The combination of earth observations with rapid field monitoring will increase the accuracy and usefulness of the forecasts.”
The research team that developed the HABscope app included oceanographers, ecologists, computer application developers, and public health experts. Photo Credit: Mote Marine Laboratory.
A posthumous plea from Sellers arrived in July 2018 in the form of an article in PNAS. The topic was one that he cared deeply about: building a better space-based system for observing and understanding the carbon cycle and its climate feedbacks.
As NASA’s Patrick Lynch reported, Sellers wrote the paper along with colleagues at NASA’s Jet Propulsion Laboratory and the University of Oklahoma. Work on the paper began in 2015, and Sellers continued working with his collaborators up until about six weeks before he died. They carried on the research and writing of the paper until its publication in July 2018.
The carbon cycle refers to the constant flow of carbon between rocks, water, the atmosphere, plants, soil, and fossil fuels. Climate change feedbacks—natural effects that may amplify or diminish the human emissions of greenhouse gases—are one of the most poorly understood aspects of climate science.
Here is how Sellers and colleagues characterized the current state of the carbon cycle in the PNAS article:
“It is quite remarkable and telling that human activity has significantly altered carbon cycling at the planetary scale. The atmospheric concentrations of carbon dioxide (CO2) and methane (CH4) have dramatically exceeded their envelope of the last several million years.”
They also explain in detail how we have altered the carbon cycle:
“The perturbation by humans occurs first and foremost through the transfer of carbon from geological reservoirs (fossil fuels) into the active land–atmosphere–ocean system and, secondarily, through the transfer of biotic carbon from forests, soils, and other terrestrial storage pools (e.g., industrial timber) into the atmosphere.”
Scientists understand the broad outlines of how this works relatively well. What worried Sellers was the potential curve balls the climate might throw at us with unanticipated feedbacks. They addressed some of the the challenges in understanding how climate change might affect concentrations of carbon dioxide and methane through feedbacks.
For carbon dioxide:
“While experimental studies consistently show increases in plant growth rates under elevated CO2 (termed carbon dioxide fertilization), the extrapolation of even the largest-scale experiments to ecosystem carbon storage is problematic, and some ecologists have argued that the physiological response could be eliminated entirely by restrictions due to limitation by nutrients or micronutrients. However, there is recent evidence from the atmosphere that suggests increasing CO2 enhances terrestrial carbon storage, leading to the continued increase in land uptake paralleling CO2 concentrations.”
As we detailed in a separate story, the situation is even more complicated for methane. Sellers and his colleagues explained some of the challenges in understanding the feedbacks that affect that potent greenhouse gas this way:
“Atmospheric methane is currently at three times its preindustrial levels, which is clearly driven by anthropogenic emissions, but equally clearly, some of the change is because of carbon-cycle–climate feedbacks. Atmospheric CH4 rose by about 1 percent per year in the 1970s and 1980s, plateaued in the 1990s, and resumed a steady rise after 2006. Why did the plateau occur? These trends in atmospheric methane concentration are not understood. They may be due to changes in climate: increases in temperature, shifts in the precipitation patterns, changes to wetlands, or proliferation in the carbon availability to methane-producing bacteria.”
The consequences of the gaps in understanding could be significant.
“Terrestrial tropical ecosystem feedbacks from the El Nino drove an ∼2-PgC increase in global CO2 emissions in 2015. If emissions excursions such as this become more frequent or persistent in the future, agreed-upon mitigation commitments could become ineffective in meeting climate stabilization targets. Earth system models disagree wildly about the magnitude and frequency of carbon–climate feedback events, and data to this point have been astonishingly ineffective at reducing this uncertainty.”
NASA’s current missions and partnership missions in orbit. Credit: NASA
Sellers and his colleagues do offer a solution. It has much to do with satellites.
“Space-based observations provide the global coverage, spatial and temporal sampling, and suite of carbon cycle observations required to resolve net carbon fluxes into their component fluxes (photosynthesis, respiration, and biomass burning). These space-based data substantially reduce ambiguity about what is happening in the present and enable us to falsify models more effectively than previous datasets could, leading to more informed projections.”
NASA’s Worldview app lets you explore Earth as it looks right now or as it looked almost 20 years ago. See a view you like? Take a snapshot and share your map with a friend or colleague. Want to track the spread of a wildfire? You can even create an animated GIF to see change over time.
Through an easy-to-use map interface, you can watch tropical storms developing over the Pacific Ocean; track the movement of icebergs after they calve from glaciers and ice shelves; and see wildfires spread and grow as they burn vegetation in their path. Pan and zoom to your region of the world to see not only what it looks like today, but to investigate changes over time. Worldview’s nighttime lights layers provide a truly unique perspective of our planet.
What else can you do with Worldview? Add imagery by discipline, natural hazard, or key word to learn more about what’s happening on this dynamic planet. View Earth’s frozen regions with the Arctic and Antarctic views. Take a look at current natural events like tropical storms, volcanic eruptions, wildfires, and icebergs at the touch of a button using the “events” tab.
In July 2016, the lower portion of a valley glacier in the Aru Range of Tibet detached and barreled into a nearby valley, killing nine people and hundreds of animals. The huge avalanche, one of the largest scientists had ever seen, sent a tongue of debris spreading across 9 square kilometers (3 square miles). With debris reaching speeds of 140 kilometers (90 miles) per hour, the avalanche was remarkably fast for its size.
(NASA Earth Observatory image by Joshua Stevens, using modified Copernicus Sentinel 2 data processed by the European Space Agency. Image collected on July 21, 2016.)
Researchers were initially baffled about how it had happened. The glacier was on a nearly flat slope that was too shallow to cause avalanches, especially fast-moving ones. What’s more, the collapse happened at an elevation where permafrost was widespread; it should have securely anchored the glacier to the surface.
Two months later, it happened again — this time to a glacier just a few kilometers away. One gigantic avalanche was unusual; two in a row was unprecedented. The second collapse raised even more questions. Had an earthquake played a role in triggering them? Did climate change play a role? Should we expect more of these mega-avalanches?
(NASA Earth Observatory image by Joshua Stevens and Jesse Allen, using ASTER data from NASA/GSFC/METI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team. Image collected on October 4, 2016.)
Now scientists have answers about how these unusual avalanches happened. There were four factors that came together and triggered the collapses, an international team of researchers reported in Nature Geoscience. The scientists analyzed many types of satellite, meteorological, and seismic data to reach their conclusions. They also sent teams of researchers to investigate the avalanches in the field.
First, increasing snowfall since the mid-1990s caused snow to pile up and start working its way toward the front edge of the glaciers (a process known as surging). Second, a great deal of rain fell in the summer of 2016. As a result, water worked its way through crevasses on the surface and lubricated the undersides of the glaciers. Third, water pooled up underneath the glaciers, even as the edges remained frozen to the ground. Fourth, the glaciers sat on a fine-grained layer of siltstone and clay that became extremely slippery.
Notice the large amounts of silt and clay in the path of the first avalanche. (Photo taken on July 15, 2017, by Adrien Gilbert/University of Oslo)
Earth Observatory checked in with Andreas Kääb (University of Oslo), lead author of the study, to find out more about how the avalanche happened and what it means.
These glaciers were not on a steep slope, but the avalanche moved quite quickly. How did that happen? Strong resistance by the frozen margins and tongues of the glaciers allowed the pressure to build instead of enabling them to adjust. The glaciers were loading up more and more pressure until the frozen margins suddenly failed. Local people reported a load bang. Once the margins failed, there was nothing at the glacier bed to hold it back, just water-soaked clay.
Your study notes that there was “undestroyed grassy vegetation on the lee side of the hills, suggesting that the fast-moving mass had partially jumped over it.” Are you saying the avalanche was airborne? If so, is that unusual? Yes, for a small part of the avalanche path. We see this for other large-volume, high-speed avalanches, and it really illustrates the massive amount of energy released. You need quite high speeds in order for debris to jump. For us, the phenomenon is important as validation for the speeds obtained from the seismic signals the avalanches triggered and the avalanche modeling that we did.
Would you say these collapses were a product of climate change? Climate change was necessary, but other factors that had nothing to do with climate were also critical. The increasing mass of the glaciers since the 1990s and the heavy rains and meltwater in 2016 are connected to climate change. The type of bedrock and the way the edges were frozen to the ground had nothing to do with climate change.
Can we expect to see more big glacial collapses as the world gets warmer? It’s not clear. Climate change could increase or, maybe even more likely, decrease the probability of such massive collapses. Most glaciers on Earth are actually losing mass (not gaining, like the two glaciers in Tibet were). Also, if permafrost becomes less widespread over time and glacier margins melt, it is less likely that pressure will build up in that way that it did in this case.
I know you used several types of satellite data as part of this analysis. Can you mention a few that yielded particularly useful information? We used a lot of different sources of data: Sentinel 1 and 2, TerraSAR-X/TanDEM-X, Planet Labs, and DigitalGlobe WorldView. Landsat 8 was absolutely critical because it gave the first and critical indication of the soft-bed characteristics. The entire Landsat series was instrumental for checking the glacier history since the 1980s. We also used declassified Corona data back to the 1960s.
Are these sorts of avalanches likely to happen in other parts of the world? Honestly, I have no clue at the moment, but we would be much less surprised next time. We know now that this type of collapse can happen under special circumstances. (It happened once before in the Caucasus at Kolka Glacier.) One thing that should be investigated is whether there are other glaciers—especially polythermal ones—with these very fine-grained materials underneath them.
Three dimensional CNES Pléiades image of the avalanches. Processed by Etienne Berthier. Via Twitter.
Atmospheric rivers stretched from Asia to North America in October 2017. Learn more.
If you live on the West Coast of North America, you have probably heard meteorologists talk about “atmospheric rivers” — the narrow, low-level plumes of moisture that often accompany extratropical storms and transport large volumes of water vapor across long distances. When atmospheric rivers encounter land, they can drop tremendous amounts of rain and snow. That can be good for replenishing reservoirs and for quenching droughts, but these remarkable meteorological features can also trigger destructive floods, landslides, and wind storms.
During the past decade, atmospheric rivers have fueled a flood of another type: scientific research papers. Prior to 2004, fewer than 10 studies mentioned atmospheric rivers in any given year; in 2015, about 200 studies were published on the matter. The availability of increasingly sophisticated satellite and aircraft data has fueled the trend, according to a recent article in the Bulletin of the American Meteorological Society. Here’s a sampling of what scientists have learned about these rivers in the sky.
They Can Bring Rains, Winds, And Lots of Damage
In a study led by Duane Waliser of NASA’s Jet Propulsion Laboratory and published in Nature Geoscience, researchers showed that atmospheric rivers are among the most damaging storm types in the middle latitudes. Of the wettest and windiest storms (those ranked in the top 2 percent), atmospheric rivers were associated with nearly half of them. Waliser and colleagues found that atmospheric rivers were associated with a doubling of wind speed compared to all storm conditions.
They Shift With The Seasons
During the winter, atmospheric rivers in the Pacific generally shift northward and westward, Bryan Mundhenk of Colorado State University and colleagues concluded in a study. They also found that the El Niño/Southern Oscillation (ENSO) cycle can affect the frequency of atmospheric river events and shift where they occur. The research was based on data processed by MERRA, a NASA reanalysis of meteorological data from satellites.
They Aren’t Just a West Coast Thing
Atmospheric rivers are a global phenomenon and responsible for about 22 percent of all water runoff. One recent study from a University of Georgia team underscored that the U.S. Southeast sees a steady stream of atmospheric rivers. “They are more common than we thought in the Southeast, and it is important to properly understand their contributions to rainfall given our dependence on agriculture and the hazards excessive rainfall can pose,” said Marshall Shepherd of the University of Georgia. Other studies note that atmospheric rivers have contributed to anomalous snow accumulation in East Antarctica and extreme rainfall in the Bay of Bengal.
Climate Change Could Alter Them
A recent study led by Christine Shields of the National Center for Atmospheric Research suggests that climate change could push atmospheric rivers in the Pacific toward the equator and bring more intense rains to southern California. The modeling calls for smaller increases in rain rates in the Pacific Northwest. Another ensemble of models shows a 35 percent increase in the number of days with landfalling atmospheric rivers in western North America.
Satellites Are Key to Studying Their Precipitation
While there are few ground-based weather stations in the open ocean to tally how much rain falls, satellites such as those included in the Global Precipitation Measurement (GPM) mission can estimate precipitation rates from above. “Satellites have proven valuable over both the ocean and land, though uncertainties are often larger over land because of complicating factors like the terrain and the presence of snow on the surface,” said Ali Behrangi, the author of a study that assessed the skill of different satellite-derived measurements of precipitation rates.