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By NASA
NASA Goddard MODIS Rapid Response Team During the morning of March 20, 2015, a total solar eclipse was visible from parts of Europe, and a partial solar eclipse from northern Africa and northern Asia. NASA’s Terra satellite passed over the Arctic Ocean on March 20 at 10:45 UTC (6:45 a.m. EDT) and captured the eclipse’s shadow over the clouds in the Arctic Ocean.
Terra launched 25 years ago on Dec. 18, 1999. Approximately the size of a small school bus, the Terra satellite carries five instruments that take coincident measurements of the Earth system: Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth’s Radiant Energy System (CERES), Multi-angle Imaging Spectroradiometer (MISR), Measurements of Pollution in the Troposphere (MOPITT), and Moderate Resolution Imaging Spectroradiometer (MODIS).
On Nov. 28, 2024, one of Terra’s power-transmitting shunt units failed. A response team reviewed Terra’s status and discussed potential impacts and options. Consequently, the team placed ASTER into Safe Mode. As a result, ASTER data are not currently being collected. All other instruments continue uninterrupted.
Image Credit: NASA Goddard MODIS Rapid Response Team
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By NASA
NASA’s Dawn spacecraft captured this image of Vesta as it left the giant asteroid’s orbit in 2012. The framing camera was looking down at the north pole, which is in the middle of the image.NASA/JPL-Caltech/UCLA/MPS/DLR/IDA Known as flow formations, these channels could be etched on bodies that would seem inhospitable to liquid because they are exposed to the extreme vacuum conditions of space.
Pocked with craters, the surfaces of many celestial bodies in our solar system provide clear evidence of a 4.6-billion-year battering by meteoroids and other space debris. But on some worlds, including the giant asteroid Vesta that NASA’s Dawn mission explored, the surfaces also contain deep channels, or gullies, whose origins are not fully understood.
A prime hypothesis holds that they formed from dry debris flows driven by geophysical processes, such as meteoroid impacts, and changes in temperature due to Sun exposure. A recent NASA-funded study, however, provides some evidence that impacts on Vesta may have triggered a less-obvious geologic process: sudden and brief flows of water that carved gullies and deposited fans of sediment. By using lab equipment to mimic conditions on Vesta, the study, which appeared in Planetary Science Journal, detailed for the first time what the liquid could be made of and how long it would flow before freezing.
Although the existence of frozen brine deposits on Vesta is unconfirmed, scientists have previously hypothesized that meteoroid impacts could have exposed and melted ice that lay under the surface of worlds like Vesta. In that scenario, flows resulting from this process could have etched gullies and other surface features that resemble those on Earth.
To explore potential explanations for deep channels, or gullies, seen on Vesta, scientists used JPL’s Dirty Under-vacuum Simulation Testbed for Icy Environments, or DUSTIE, to simulate conditions on the giant asteroid that would occur after meteoroids strike the surface.NASA/JPL-Caltech But how could airless worlds — celestial bodies without atmospheres and exposed to the intense vacuum of space — host liquids on the surface long enough for them to flow? Such a process would run contrary to the understanding that liquids quickly destabilize in a vacuum, changing to a gas when the pressure drops.
“Not only do impacts trigger a flow of liquid on the surface, the liquids are active long enough to create specific surface features,” said project leader and planetary scientist Jennifer Scully of NASA’s Jet Propulsion Laboratory in Southern California, where the experiments were conducted. “But for how long? Most liquids become unstable quickly on these airless bodies, where the vacuum of space is unyielding.”
The critical component turns out to be sodium chloride — table salt. The experiments found that in conditions like those on Vesta, pure water froze almost instantly, while briny liquids stayed fluid for at least an hour. “That’s long enough to form the flow-associated features identified on Vesta, which were estimated to require up to a half-hour,” said lead author Michael J. Poston of the Southwest Research Institute in San Antonio.
Launched in 2007, the Dawn spacecraft traveled to the main asteroid belt between Mars and Jupiter to orbit Vesta for 14 months and Ceres for almost four years. Before ending in 2018, the mission uncovered evidence that Ceres had been home to a subsurface reservoir of brine and may still be transferring brines from its interior to the surface. The recent research offers insights into processes on Ceres but focuses on Vesta, where ice and salts may produce briny liquid when heated by an impact, scientists said.
Re-creating Vesta
To re-create Vesta-like conditions that would occur after a meteoroid impact, the scientists relied on a test chamber at JPL called the Dirty Under-vacuum Simulation Testbed for Icy Environments, or DUSTIE. By rapidly reducing the air pressure surrounding samples of liquid, they mimicked the environment around fluid that comes to the surface. Exposed to vacuum conditions, pure water froze instantly. But salty fluids hung around longer, continuing to flow before freezing.
The brines they experimented with were a little over an inch (a few centimeters) deep; scientists concluded the flows on Vesta that are yards to tens of yards deep would take even longer to refreeze.
The researchers were also able to re-create the “lids” of frozen material thought to form on brines. Essentially a frozen top layer, the lids stabilize the liquid beneath them, protecting it from being exposed to the vacuum of space — or, in this case the vacuum of the DUSTIE chamber — and helping the liquid flow longer before freezing again.
This phenomenon is similar to how on Earth lava flows farther in lava tubes than when exposed to cool surface temperatures. It also matches up with modeling research conducted around potential mud volcanoes on Mars and volcanoes that may have spewed icy material from volcanoes on Jupiter’s moon Europa.
“Our results contribute to a growing body of work that uses lab experiments to understand how long liquids last on a variety of worlds,” Scully said.
Find more information about NASA’s Dawn mission here:
https://science.nasa.gov/mission/dawn/
News Media Contacts
Gretchen McCartney
Jet Propulsion Laboratory, Pasadena, Calif.
818-287-4115
gretchen.p.mccartney@jpl.nasa.gov
Karen Fox / Molly Wasser
NASA Headquarters, Washington
202-358-1600
karen.c.fox@nasa.gov / molly.l.wasser@nasa.gov
2024-178
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Last Updated Dec 20, 2024 Related Terms
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By NASA
Download PDF: Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Energy modulators (EM), also known as energy absorbers, are safety-critical components that are used to control shocks and impulses in a load path. EMs are textile devices typically manufactured out of nylon, Kevlar® and other materials, and control loads by breaking rows of stitches that bind a strong base webbing together as shown in Figure 1. A familiar EM application is a fall-protection harness used by workers to prevent injury from shock loads when the harness arrests a fall. EMs are also widely used in parachute systems to control shock loads experienced during the various stages of parachute system deployment.
Random forest is an innovative algorithm for data classification used in statistics and machine learning. It is an easy to use and highly flexible ensemble learning method. The random forest algorithm is capable of modeling both categorical and continuous data and can handle large datasets, making it applicable in many situations. It also makes it easy to evaluate the relative importance of variables and maintains accuracy even when a dataset has missing values.
Random forests model the relationship between a response variable and a set of predictor or independent variables by creating a collection of decision trees. Each decision tree is built from a random sample of the data. The individual trees are then combined through methods such as averaging or voting to determine the final prediction (Figure 2). A decision tree is a non-parametric supervised learning algorithm that partitions the data using a series of branching binary decisions. Decision trees inherently identify key features of the data and provide a ranking of the contribution of each feature based on when it becomes relevant. This capability can be used to determine the relative importance of the input variables (Figure 3). Decision trees are useful for exploring relationships but can have poor accuracy unless they are combined into random forests or other tree-based models.
The performance of a random forest can be evaluated using out-of-bag error and cross-validation techniques. Random forests often use random sampling with replacement from the original dataset to create each decision tree. This is also known as bootstrap sampling and forms a bootstrap forest. The data included in the bootstrap sample are referred to as in-the-bag, while the data not selected are out-of-bag. Since the out-of-bag data were not used to generate the decision tree, they can be used as an internal measure of the accuracy of the model. Cross-validation can be used to assess how well the results of a random forest model will generalize to an independent dataset. In this approach, the data are split into a training dataset used to generate the decision trees and build the model and a validation dataset used to evaluate the model’s performance. Evaluating the model on the independent validation dataset provides an estimate of how accurately the model will perform in practice and helps avoid problems such as overfitting or sampling bias. A good model performs well on
both the training data and the validation data.
The complex nature of the EM system made it difficult for the team to identify how various parameters influenced EM behavior. A bootstrap forest analysis was applied to the test dataset and was able to identify five key variables associated with higher probability of damage and/or anomalous behavior. The identified key variables provided a basis for further testing and redesign of the EM system. These results also provided essential insight to the investigation and aided in development of flight rationale for future use cases.
For information, contact Dr. Sara R. Wilson. sara.r.wilson@nasa.gov
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By NASA
Dr. Jeannette Wing and Dr. Christa Peters-Lidard sign a collaborative Space Act Agreement at NASA’s Goddard Space Flight Center on Monday, Dec. 16, 2024. NASA/Travis Wohlrab NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and Columbia University in New York, New York, enacted a collaborative Space Act Agreement to advance research and education opportunities during a signing ceremony Monday, Dec. 16, at Goddard.
Presiding over the ceremony were Dr. Christa Peters-Lidard, director of Goddard’s Sciences and Exploration directorate, and Dr Jeannette Wing, executive vice president for research and professor of computer science at Columbia University.
Columbia University has been a trusted partner for many years and has a long history of interactions with Goddard Space Flight Center. Notably, the Goddard Institute for Space Studies (GISS) is located at Columbia University serving as a laboratory in Goddard’s Earth Sciences Division and is affiliated with the Columbia Climate School and School of Engineering and Applied Science.
The agreement expands NASA’s CU partnership to Goddard’s Greenbelt campus and will be centered around collaborative research, education, technology development, workforce development, science and engineering exchanges, applied science, commercial as well as nonprofit research along with technology infusion.
Areas of mutual interest include but are not limited to: artificial intelligence, foundation models, machine learning, and data science; climate sustainability, justice, adaptation, and resilience; materials and sensors; quantum sensing and computing; Earth science, planetary science, heliophysics, physics and astrophysics.
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Last Updated Dec 18, 2024 EditorKaty MersmannContactJeremy Eggers Related Terms
Goddard Institute for Space Studies Goddard Space Flight Center View the full article
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By NASA
5 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Data from the SWOT satellite was used to calculate average water levels for lakes and reservoirs in the Ohio River Basin from July 2023 to November 2024. Yellow indicates values greater than 1,600 feet (500 meters) above sea level; dark purple represents water levels less than 330 feet (100 meters). Data from the U.S.-European Surface Water and Ocean Topography mission gives researchers a detailed look at lakes and reservoirs in a U.S. watershed.
The Ohio River Basin stretches from Pennsylvania to Illinois and contains a system of reservoirs, lakes, and rivers that drains an area almost as large as France. Researchers with the SWOT (Surface Water and Ocean Topography) mission, a collaboration between NASA and the French space agency CNES (Centre National d’Études Spatiales), now have a new tool for measuring water levels not only in this area, which is home to more than 25 million people, but in other watersheds around the world as well.
Since early 2023, SWOT has been measuring the height of nearly all water on Earth’s surface — including oceans, lakes, reservoirs, and rivers — covering nearly the entire globe at least once every 21 days. The SWOT satellite also measures the horizontal extent of water in freshwater bodies. Earlier this year, the mission started making validated data publicly available.
“Having these two perspectives — water extent and levels — at the same time, along with detailed, frequent coverage over large areas, is unprecedented,” said Jida Wang, a hydrologist at the University of Illinois Urbana-Champaign and a member of the SWOT science team. “This is a groundbreaking, exciting aspect of SWOT.”
Researchers can use the mission’s data on water level and extent to calculate how the amount of water stored in a lake or reservoir changes over time. This, in turn, can give hydrologists a more precise picture of river discharge — how much water moves through a particular stretch of river.
The visualization above uses SWOT data from July 2023 to November 2024 to show the average water level above sea level in lakes and reservoirs in the Ohio River Basin, which drains into the Mississippi River. Yellow indicates values greater than 1,600 feet (500 meters), and dark purple represents water levels less than 330 feet (100 meters). Comparing how such levels change can help hydrologists measure water availability over time in a local area or across a watershed.
Complementing a Patchwork of Data
Historically, estimating freshwater availability for communities within a river basin has been challenging. Researchers gather information from gauges installed at certain lakes and reservoirs, from airborne surveys, and from other satellites that look at either water level or extent. But for ground-based and airborne instruments, the coverage can be limited in space and time. Hydrologists can piece together some of what they need from different satellites, but the data may or may not have been taken at the same time, or the researchers might still need to augment the information with measurements from ground-based sensors.
Even then, calculating freshwater availability can be complicated. Much of the work relies on computer models. “Traditional water models often don’t work very well in highly regulated basins like the Ohio because they have trouble representing the unpredictable behavior of dam operations,” said George Allen, a freshwater researcher at Virginia Tech in Blacksburg and a member of the SWOT science team.
Many river basins in the United States include dams and reservoirs managed by a patchwork of entities. While the people who manage a reservoir may know how their section of water behaves, planning for water availability down the entire length of a river can be a challenge. Since SWOT looks at both rivers and lakes, its data can help provide a more unified view.
“The data lets water managers really know what other people in these freshwater systems are doing,” said SWOT science team member Colin Gleason, a hydrologist at the University of Massachusetts Amherst.
While SWOT researchers are excited about the possibilities that the data is opening up, there is still much to be done. The satellite’s high-resolution view of water levels and extent means there is a vast ocean of data that researchers must wade through, and it will take some time to process and analyze the measurements.
More About SWOT
The SWOT satellite was jointly developed by NASA and CNES, with contributions from the Canadian Space Agency (CSA) and the UK Space Agency. NASA’s Jet Propulsion Laboratory, managed for the agency by Caltech in Pasadena, California, leads the U.S. component of the project. For the flight system payload, NASA provided the Ka-band radar interferometer (KaRIn) instrument, a GPS science receiver, a laser retroreflector, a two-beam microwave radiometer, and NASA instrument operations. The Doppler Orbitography and Radioposition Integrated by Satellite system, the dual frequency Poseidon altimeter (developed by Thales Alenia Space), the KaRIn radio-frequency subsystem (together with Thales Alenia Space and with support from the UK Space Agency), the satellite platform, and ground operations were provided by CNES. The KaRIn high-power transmitter assembly was provided by CSA.
To learn more about SWOT, visit:
https://swot.jpl.nasa.gov
News Media Contacts
Jane J. Lee / Andrew Wang
Jet Propulsion Laboratory, Pasadena, Calif.
818-354-0307 / 626-379-6874
jane.j.lee@jpl.nasa.gov / andrew.wang@jpl.nasa.gov
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Last Updated Dec 17, 2024 Related Terms
SWOT (Surface Water and Ocean Topography) Jet Propulsion Laboratory Water on Earth Explore More
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