Globally, about 1 billion people live near glaciers and depend on glacial water. As temperatures continue to climb due to global warming, glaciers can become unstable and hazardous to nearby communities. These communities risk exposure to a series of linked processes, like ice collapse, flooding, and landslides, which could have life-threatening consequences. Scientists call these events catastrophic glacier hazard chains, or CGHC. So, a team of scientists in China sought to understand the driving forces behind these dangerous phenomena. 

The team focused on a CGHC event that occurred in 2018 at the Sedongpu Glacier, located in the Eastern Himalayas. During this event, the glacier obstructed the flow of 30 million square meters (more than 300 million square feet) of the Yarlung Tsanpo River, one of the main rivers within the region. 

To reconstruct the event, the team observed satellite images of the Sedongpu glacier over time, using a process called remote sensing. They used the images to calculate ice volumes, glacier velocities, and glacier movement between 1961 and 2018, to determine the glacier’s long-term physical properties and how they changed over time. They found that from 1968 to 2013, the Sedongpu Glacier shrank, or retreated, by over 6 football fields. It also lost ice and water volume and increased its velocity.

The scientists also measured earthquake waves on the Earth’s surface, or seismicity, to characterize any downslope rock or debris movements caused by the glacial retreat. They measured seismicity across 11 different seismic stations within 580 kilometers (about 350 miles) of the glacier. Then, they used this data to identify 2 distinct phases of the CGHC event on Sedongpu Glacier: the ice-rock avalanche and the debris flow.

When the ice-rock avalanche occurred, the team detected noticeable increases in seismicity, suggesting it lasted over 30 seconds. During those 30 seconds, over 8 million cubic meters (more than 280 million cubic feet) of ice fell onto the main glacier. The team recorded even more increases in seismicity during the debris flow, which lasted nearly 5 minutes. The debris from the avalanche hit the main valley glacier at nearly 300 kilometers (200 miles) per hour.

The researchers combined these data to describe how the 2018 CGHC event unfolded. First, the backward movement and shrinkage of the glacier produced an unstable sheet of ice hanging over a cliff face. The steep slope and large cracks in the ice caused an ice-rock avalanche. Debris from the avalanche then accumulated on the main glacier, causing it to move faster. As the main valley glacier moved downslope, it picked up even more debris from the bottom and sides of the glacial valley. The melting ice also increased the glacier’s velocity, and its movement eventually transitioned into a debris flow, which obstructed the Yarlung Tsangpo River. 

In total, the CGHC event in the Sedongpu Glacier travelled over 10 kilometers (6 miles) and moved down in elevation for over 3 kilometers (about 2 miles) at a velocity of about 100 kilometers (about 70 miles) per hour. The glacier accumulated enough debris and ice to fill thousands of Olympic-sized swimming pools. Imagine what this could do to a nearby village!

It’s difficult for scientists to estimate when CGHC events will occur, but this team proposed several factors that could help predict them. These factors included the size of the ice-rock avalanche and the glacier velocity, as well as the occurrence of earthquakes, temperature changes, and the melting of the glacier’s underside. They stated that these factors can combine to create a domino effect that drives the CGHC process. They recommended consistent glacial monitoring as temperatures continue to climb, in the Himalayas and globally. 

The team concluded that understanding CGHC events can help scientists mitigate glacial hazards and keep people safe, especially in mountainous areas such as the Eastern Himalayas. They stated that their findings illustrate the dangerous processes behind glacial melting, but further research is needed to accurately assess those processes and ensure nearby communities remain safe.

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In the Bolivian Altiplano, fewer Aymara farmers are relying on local weather knowledge to schedule farming tasks, like choosing the best dates to plant crops and predicting a frost or drought. At the same time, there is growing doubt about whether these traditional indicators remain relevant today in the context of rapid social, economic, and climatic changes. 

Farmers are struggling because the National Weather Service of Bolivia (SEHNAMI) fails to provide useful weather forecasts due to the geographical complexity of the Andes and a scarcity of weather stations. In addition, many farmers can’t access this information because SEHNAMI lacks local outreach programs to deliver reports directly to them. In a region with a weak technical forecasting system, local knowledge is a vital resource, but its use is declining.

Scientists in the past focused on preserving local weather knowledge or discussing how it might help communities adapt to climate change. However, very few researchers have scientifically validated local weather indicators, since doing so requires many years of historical meteorological data to establish statistical “skill” in local forecasting. 

Faced with this gap, researchers in the US and Bolivia recently set out to validate indigenous indicators in 2 Bolivian municipalities: Umala in the Central Altiplano and Ancoraimes in the Northern Altiplano. To do this, they paired each traditional weather sign with a measurable variable, like temperature, that could approximate it. This approach allowed them to directly compare traditional observations with scientific data.

The researchers wanted to determine whether traditional weather knowledge is still accurate and relevant under current conditions, since validating these methods would strengthen local knowledge and benefit the schools and policies that promote it. To test this, the researchers worked with 6 Aymara communities. First, they conducted workshops with local leaders and experts to compile a set of weather-forecast indicators. Then, they surveyed 95 farmers to rank the reliability of these indicators. 

Through discussions with these communities, the team identified 13 weather indicators in the Central region and 20 in the Northern region. These indicators included specific plants, animals, and physical factors like constellations or winds that the farmers used to decide when and where to plant crops, and to predict weather conditions for the next season. The researchers focused on 2 key indicators that the farmers ranked as most reliable: the presence or absence of moisture under rocks on the Fiesta de San Juan on June 24th, and the flowering patterns of specific plants, called Thola and Sank’ayu. The farmers used the San Juan indicator to predict whether the upcoming year would be rainy or dry, and the plants to determine the most favorable dates for planting to avoid agricultural risks like frosts.

Finally, the researchers compared forecasts based on these 2 signs with over 30 years of meteorological data from nearby weather stations. In both cases, they used the minimum daily temperature as the measurable way to represent these local signs scientifically. Their results showed that the minimum daily temperature on the Fiesta de San Juan could explain more than half (55.5%) of the changes in rainfall during the growing season. They also confirmed that severe frosts that “burned” Thola and Sank’ayuthe flowers were followed by periods without rain, validating the farmers’ strategy of delayed planting.

The researchers concluded that local weather indicators used by Aymara farmers are most reliable for seasonal planning, especially in predicting the start of the rainy season. They stated that this result helps legitimize traditional knowledge and empower the community. For example, these communities now hold regular meetings to discuss forecasts and share this information with their neighbors via WhatsApp groups. 

However, the team acknowledged that local knowledge was limited to short-term forecasting, as it only provided warnings a few hours in advance. Farmers need alerts several days in advance to effectively reduce their vulnerability to events such as frosts or hail. For this reason, the researchers suggested that the next step will be to co-produce forecasts by combining meteorological science with traditional knowledge.

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Nearly 170 billion tons of ice melt off the Greenland Ice Sheet every year, but scientists don’t fully understand the process by which this melting occurs. Researchers in the past suggested that liquid water forms at the glacier’s surface, where warm air and sunlight melt the ice. This meltwater travels down through cracks in the glacier and along the bedrock beneath it and flows out to sea. 

However, some scientists view this model as too simple because it assumes water only flows downward and ignores how temperature affects water movement. They argue that an oversimplified melting model is unreliable for predicting how future ice sheets will behave.

One group of researchers tested this by investigating how water movement across Greenland is controlled by lakes beneath the ice sheet, called subglacial lakes. They monitored a newly discovered subglacial lake using high-resolution satellite images taken from 2012 to 2019 and 3D surface maps generated from the images. They focused on ice sheet changes from July 22 to August 1, 2014, during a suspected subglacial lake drainage event. A drainage event is like a water balloon that’s too full, bursting from excess pressure. 

They examined images of the Greenland ice sheet taken from Landsat-8, 3D surface maps from the Polar Geospatial Center, and data from ICESat and ICESat-2 taken in the summer of 2014. Based on these data, the researchers identified a 2-square-kilometer (0.8-square-mile) region of ice rising 10 to 15 meters (about 30 to 50 feet), forming a dome on the ice sheet’s surface. They suggested that this dome formed when a large, meltwater-fed lake developed on the bedrock beneath the ice sheet, pushing the ice upward. 

They also saw that on July 22, 2014, the dome began to collapse. Over the next 10 days, it dropped by 85 meters (about 280 feet), forming a basin. Using the dome’s dimensions, the researchers estimated that 90 million cubic meters, or about 3 billion cubic feet, of water drained from the lake at an average rate of 100 cubic meters, or about 3500 cubic feet, per second over the 10 days. This is roughly equivalent to 36,000 Olympic swimming pools draining at a rate of 1 pool every 25 seconds! 

The researchers also found that during the collapse, 40-meter-high (130-foot) ice blocks were uprooted about 1 kilometer (0.6 mile) downstream from the basin, followed by 6 square kilometers (about 2 square miles) of smooth ice. The researchers hypothesized that these features formed when water burst through the ice, flowed along its surface, and then reentered the ice sheet.

Next, they used data from Landsat 5, Landsat 9, the National Snow and Ice Data Center, and the U.S. Geological Survey to demonstrate that the drainage event also affected the surrounding environment. When the water reentered the ice sheet, it flowed beneath the Harding Glacier downstream. This influx of fast-moving water reduced pressure at the glacier’s base, slowing its movement. Simultaneously, the increased drainage beneath the Harding Glacier caused 500 to 600 meters (about 1,600 to 2,000 feet) of ice to break off its end. 

In response to these changes, the researchers hypothesized that subglacial waters rose to the surface rather than sinking to the bedrock because the ice sheet was frozen to it. To test this, they simulated temperatures at the base of the ice sheet using computer-generated thermal models. They input a range of likely bedrock temperatures and ice thicknesses to simulate possible conditions under the ice sheet. They found that all the simulations predicted the glacier’s base would remain below -5°C (23°F). At such low temperatures, the ice would be frozen to the bedrock before subglacial water could drain out. Since water couldn’t flow under the glacier, it was forced to travel upward. 

The researchers used these findings to develop a new conceptual model of how glacial meltwater moves. First, surface ice melts and flows into a subglacial lake. As meltwater accumulates, pressure builds at the base of the ice sheet, forming a dome on the surface. A drainage event causes the dome to collapse. As water moves downward through the glacier, it is blocked from reaching the base because the ice is frozen to the bedrock. The water then moves upward, bursts through the surface, travels across it, and eventually reenters the glacier before draining to the ocean.

The team concluded that water movement above, through, and below glaciers is interconnected. Destructive upward flow of meltwater, followed by downward flow beneath glaciers, can weaken ice sheet structure and alter downstream glacier dynamics. Their work highlights the need for more scientists to consider the processes driving glacial ice loss.

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Many volcano scientists spend their time monitoring volcanoes to predict if, or when, they’ll next erupt. The challenge for these scientists is to forecast the exact probability of an eruption and the moment it will occur. 

To address this problem, a team of researchers developed an early-detection system to determine when to issue alerts about volcanic eruptions. Their motivation was that previous alert systems weren’t accurate enough because they couldn’t detect underground volcanic processes that occur right before an eruption. 

From 2014 to 2023, the researchers conducted a series of tests to accurately detect temporary, low-frequency vibrations using an instrument called a seismometer. The researchers focused on these transient signals because they come from earthquakes and other ground phenomena, which scientists often rely on to predict volcanic eruptions. These phenomena include ground tilting caused by fracturing from the movement of magma and volcanic gases. The scientists named these signals the “Jerk” signals because they occur due to sudden movements. 

The team set up their experiment at Piton de la Fournaise, a volcano at La Réunion Island off the east coast of Madagascar. They discovered the Jerk signals by detecting and analyzing mysterious short-term signals from existing and experimental seismic data. During real-time experiments, they detected signals 8 kilometers (about 5 miles) from the volcano at the Rivière de l’Est seismic station. These signals resulted from changes in ground elevation as magma moved, and they preceded eruptions by minutes and sometimes hours. 

The researchers measured the Jerk signals in units of newton-meters per second, which conveys how fast physical changes occurred in or around the volcano. In addition to real-time experiments, the team checked the Jerk signals’ accuracy by analyzing the station’s past data to determine when these signals would have occurred before an eruption.

To avoid false alarms during their experiments, the researchers needed to distinguish between the signal amplitudes of ocean tides and the transient Jerk signals. So, they used computational software to predict the signals from ocean tides. This was necessary because the instruments that record ground phenomena are also sensitive to tidal movements.  

The Jerk system sent its first automatic alarm in June 2014, 1 hour before the first volcanic tremor, signalling that magma was at the Earth’s surface. The team recorded the last signal in their study on July 2, 2023, 40 minutes before the eruption, at a slow 1.5 newton-meters per second. From 2014 to 2023, other Jerk detections occurred between a few minutes and up to 8 hours before an eruption.

To further assess the strength of the Jerk signals, the team examined previous eruption records at Piton de la Fournaise. They found that for the 24 eruptions between 1998 and 2010, a Jerk alarm would have gone off 83% of the time. Of the 48 eruptions that occurred between 1998 and 2023, including the eruptions during their real-time tests, about 42 Jerk alarms would have occurred. However, they found that the Jerk signals were more accurate during their real-time analysis than they would have been for the eruptions 20 years earlier. 

Although the researchers successfully detected pre-eruption signals, they noted that the Jerk alarms occasionally arrived too late due to the data processing time, which takes at least 10 to 15 minutes. They reported 2 late alarms: one on June 11, 2019, and the other on February 10, 2020. Therefore, after 10 years of tracking the Jerk signals, the team evaluated their success rates at 22 successful alarms out of 24 eruptions, for a 92% positive rate. 

Before using the Jerk signals, many volcanologists struggled to predict the exact moment a volcano erupts. The team concluded that, in addition to the usual methods for detecting pre-eruption earthquakes, observatory scientists could now use Jerk signals to confidently notify authorities in advance of volcanic eruptions, so they can alert people living near volcanoes worldwide. 

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Around 66 million years ago, an asteroid wiped out 75% of the species on Earth. This event caused the extinction of all dinosaurs except birds, referred to as non-avian dinosaurs. However, an open question in paleontology is whether the dinosaurs were already declining before the asteroid hit. Many scientists think that around 5 to 10 million years before the extinction event, dinosaurs became less biologically diverse across America, making them more prone to extinction. 

To investigate this hypothesis, scientists recently revisited fossils in a rock layer from the end of the dinosaur era that previous researchers had incorrectly dated. The bulk of the fossils from this period had previously been collected from a different section of rocks called the Hell Creek Formation in Montana. These researchers studied a rock layer in New Mexico that is exposed to the surface, known as the Naashoibito Member. It’s approximately 30 meters (about 100 feet) thick and formed from ancient river sediments. 

To determine when the Naashoibito Member formed, the scientists measured the decay of radioactive elements within its mineral grains over time, a technique called radiometric dating. The scientist reasoned that these mineral grains must have crystallized before being transported and incorporated into the Naashoibito Member, so their youngest ages should provide a maximum depositional age. 

They determined the ages of 1,046 crystals of the mineral feldspar from 2 dinosaur-bearing rock layers in the Naashoibito Member. Based on these ages, the researchers found that a sandstone within 5 meters (about 16 feet) of the lowest boundary of the Naashoibito Member must be younger than 66.9 million years old. They found that the other layer, which is around 3.5 meters (11 feet) from the base of the lowest boundary, must be younger than 66.4 million years old. These age ranges indicated that the sandstone contains dinosaur fossils formed 400,000 years before their extinction.

Next, the researchers measured the direction of magnetic minerals inside the rocks, using a practice called magnetostratigraphy. The direction of these minerals indicates where Earth’s magnetic field was pointing at that time. Scientists have shown that the Earth’s magnetic field has flipped multiple times over Earth’s history, so they can use these magnetic signals to create a timescale for when the sediments formed. 

The researchers wanted to determine whether the magnetic minerals were lined up in a direction like today, called normal polarity, or the opposite, called reverse polarity. The researchers found one rock layer with normal polarity at the base of the Naashoibito Member, and one with reverse polarity in the upper part of the Naashoibito Member. These magnetic field directions lined up with 2 known polarity intervals over a timeline that matched the feldspar dates. Together, these data demonstrated that the Naashoibito Member formed at the end of the dinosaur era, around the same time as the Hell Creek Formation.

Next, the researchers wanted to test whether non-avian dinosaurs maintained their diversity across different regions of Western North America during this time period. They compared fossil patterns from locations across North America using statistical grouping methods that determine how similar or different their environments were. They found that temperature, rather than geographical location alone, was the best predictor of diversity at the extinction event. 

The team concluded that a diverse population of Naashoibito dinosaurs lived at around the same time as the Hell Creek dinosaurs. Earlier scientists surmised that dinosaurs were already on the decline because they studied the colder northern regions, where diversity was lower. However, these results suggest that warmer conditions in the south still supported diverse dinosaur populations. Together, this evidence suggests that dinosaurs were still diverse and thriving 66 million years ago, and that their extinction was indeed a result of the asteroid impact.

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In 2011, miles of rock shifted deep underwater in the Japan Trench, causing an earthquake that deformed the seafloor and caused a devastating tsunami. Off the Eastern Coast of the Tōhoku region in Japan, a huge piece of the Earth’s crust carrying the Pacific Ocean, known as a tectonic plate, is forcing itself beneath Japan and into the Earth’s interior. Researchers think rock from this plate pushed against rock far beneath Japan, building pressure until it became too great. The lower plate slipped, spreading energy from the slip site and causing the earthquake. 

Plate slip can cause 2 types of outcomes. The first occurs kilometers deep in the Earth’s crust, causing earthquakes too small to trigger tsunamis. The second type causes extreme slip events that begin deep in the crust, like the 2011 event that extended into the Japan Trench and warped the seafloor. The moving seafloor displaces seawater, causing a tsunami. These events are referred to as slip-to-the-trench style earthquakes.

Researchers think this phenomenon is not unique to 2011, as Japan has a long history of tsunami-causing earthquakes. Charlotte Pizer and colleagues investigated sediment from the Japan Trench to unearth the geologic history of slip-to-the-trench style earthquakes.

In between earthquakes, Japanese islands continuously shed sediment that fills the trench, forming horizontal layers. Slip-to-the-trench earthquakes bend and fold these layers. The team hypothesized that if they found these folds in the Japan Trench and dated them, they could catalogue the record of slip-to-the-trench style earthquakes in the area.

Earthquakes like these occur repeatedly, meaning that younger ones can erase folds caused by older ones. To account for this overprinting, the researchers chose a study site within the Japan Trench about 100 kilometers (60 miles) north of where the most severe earthquakes occur. This site is only mildly deformed by slip-to-the-trench earthquakes since it’s so far from their source, making it easier for the team to identify individual events. 

Pizer and her group pieced together data collected from this site by previous researchers to reconstruct Japan’s earthquake history. They compiled 3 main types of data. Two of these were images of sediment layers in the trench constructed from reflections of vibrations sent into the ground, called seismic profiles. 

The first seismic profile captured the full trench, over 1 kilometer deep (about 0.6 miles), at 5-meter (16-feet) resolution. Using this method, any layers smaller than 5 meters thick won’t appear in the image. The second seismic profile captured only the top 40 meters (130 feet) of sediment, but could detect layers as thin as 10 centimeters (4 inches). 

The final type of data they used came from a 36-meter (120-foot) long cylinder of sediment extracted from the bottom of the trench, called a sediment core. Researchers in the past tied layers within this sediment core to historic earthquake events. They showed that it recorded 2 specific earthquakes in the area, the Kyotoku earthquake of 1454 CE, and the Jogan earthquake of 869 CE, both of which likely caused tsunamis. 

Pizer’s team could observe the depth of the Kyotoku and Jogan earthquake layers taken from the sediment core in their high-resolution seismic profile of the trench. In these high-resolution data, they noticed that deformation occurred in the sediment up to the layer marking the Jogan earthquake, but not above it, meaning deformation of the trench happened during this 869 CE event. 

The high-resolution data were only able to image sediments from recent earthquakes since 869 CE, but the low-resolution profile, which imaged the full trench, was able to capture the deeper, older record. When they looked deeper into the trench sediment, the researchers noticed that deformation from the 869 CE event had spread from where the tectonic plate is colliding with Japan. They saw at least 6 more similarly deformed layers, implying each was its own slip-to-the-trench event, although the dates of these events are unknown.

Pizer and colleagues concluded that slip-to-the-trench earthquakes are long-standing, common events in the Japan Trench. They hope future scientists will continue to research this site to better assess tsunami risks in Japan.

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The continent of Africa is splitting into 2 tectonic plates in the middle of Ethiopia. In the recent past, geophysicists have improved their understanding of how tectonic plates like these separate. They’ve shown that continents begin to split apart as the crust and upper mantle, known as the lithosphere, crack and shift. Later, magma from deep within the Earth travels upward through these cracks to Earth’s surface, forming volcanoes. Therefore, scientists know that volcanoes form in areas of continental rifting, but not how quickly they form, which complicates efforts to assess volcanic hazards in rift zones.

Researchers led by Kevin Wong sought to answer this question by examining a mineral formed when magma cools, called olivine. They focused on 72 olivine crystals ranging in size from 1 to 4 millimeters (0.04 to 0.16 inches) from rocks collected at the Boku and Ziway volcanic fields in the Main Ethiopian Rift (MER) zone in Africa. They explained that the lithosphere in this area is still about 35 to 40 kilometers (21 to 25 miles) thick. This thick lithosphere suggests that the MER represents an intermediate stage of continental separation and offers a rare opportunity to study how tectonic stretching transitions into magmatic rifting in the process.

Wong and his team analyzed olivine because it’s one of the first minerals to crystallize from magma, and it continues to grow as the magma rises and cools. As magma rises, its composition changes, producing sharp chemical “zones” within the growing crystals, analogous to growth rings in trees. Changing temperatures and magma compositions cause different elements, like magnesium and iron, to diffuse into and out of the crystals at various rates during the magma’s ascent. So scientists can model these chemical zones and their boundaries in olivine crystals to determine how quickly the magma ascended from the upper mantle to erupt in the rift.

Wong and colleagues examined the olivine crystals from the MER volcanic fields using high-magnification imaging and chemical analyses, with an instrument known as an electron microprobe. Within each crystal, the team mapped 10 to 15 points spaced approximately 5 to 15 microns apart (about 10% of the thickness of a human hair) along a transect from the inner core to the outer rim, spanning its growth zones. 

They found 2 different populations of olivine crystals. The first consisted of normal-zoned crystals with magnesium-rich inner cores, and the second consisted of reverse-zoned crystals with lower magnesium cores. They explained that recently-formed magmas in the deep Earth contain higher amounts of the element magnesium relative to iron. The magnesium-rich zone has a sharp boundary with the magnesium-poor zone, but this boundary can get blurred when elements diffuse across it. Diffusion progressively smooths these crystal boundaries over time at known rates, so researchers can use their “blurryness” to extract information on how quickly the crystals equilibrated with the surrounding magma.

The researchers used numerical models to estimate how quickly magnesium and iron would diffuse across these chemical boundaries at different temperatures and surrounding magma chemistries. They compared thousands of simulated diffusion profiles to their measured olivine diffusion profiles. They used this iterative process to estimate that the crystals diffused, on average, for 40 and 17 days in the surrounding magma while ascending from the deep Earth to erupt at Boku and Ziway, respectively. They further tested these estimates using a growth-diffusion model that better represented natural crystal behavior. That model produced ascent times of about 27 days on average and better reproduced the crystal zoning patterns they observed.

Based on these models, the researchers concluded that intermediate-stage rifting events happen on unexpectedly short timescales. Magmas travel up to 40 kilometers (25 miles) from the deep Earth to the surface within, on average, a single calendar month, which is closer to human timescales than geologic timescales. They suggested that this rapid ascent is likely due to highly developed magmatic plumbing systems in the lithosphere that form before much lithospheric thinning. However, they noted that their results still suggest a wider range in ascension timescales than optimal for disaster mitigation and prediction. 

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