A new study provides the first global accounting of fluctuations in lake and reservoir water levels. The research shows 57 percent of the variability occurs in dammed reservoirs and other bodies of water managed by people, highlighting the dominant role humans now play in Earth s water cycle.
E-Mail
The planet Mars has no global magnetic field, although scientists believe it did have one at some point in the past. Previous studies suggest that when Mars global magnetic field was present, it was approximately the same strength as Earth s current field. Surprisingly, instruments from past Mars missions, both orbiters and landers, have spotted patches on the planet s surface that are strongly magnetized a property that could not have been produced by a magnetic field similar to Earth s, assuming the rocks on both planets are similar.
Ahmed AlHantoobi, an intern working with Northern Arizona University planetary scientists, assistant professor Christopher Edwards and postdoctoral scholar Jennifer Buz in NAU s Department of Astronomy and Planetary Science, led a study looking for answers to explain these magnetic anomalies. The team explored the relationships between the strength of the magnetic field on the surface and the composition of the crust in the Terra Sirenum-T
Credit: National Park Service
To investigate humans impact on freshwater resources, scientists have now conducted the first global accounting of fluctuating water levels in Earth s lakes and reservoirs - including ones previously too small to measure from space.
The research, published March 3 in the journal
Nature, relied on NASA s Ice, Cloud and land Elevation Satellite 2 (ICESat-2), launched in September 2018.
ICESat-2 sends 10,000 laser light pulses every second down to Earth. When reflected back to the satellite, those pulses deliver high-precision surface height measurements every 28 inches (70 centimeters) along the satellite s orbit. With these trillions of data points, scientists can distinguish more features of Earth s surface, like small lakes and ponds, and track them over time.
E-Mail
IMAGE: The goal of OC-SMART is to improve the quality of global ocean color products retrieved from satellite sensors, especially under complex environmental conditions. The top image shows OC-SMART s performance in. view more
Credit: Stevens Institute of Technology
Researchers at Stevens Institute of Technology have developed a new machine learning-powered platform, known as OC-SMART, that can process ocean color in satellite images 10 times faster than the world s leading platform. The work, which will be adopted by NASA, is one of the first machine learning-based platforms in ocean color analysis that can process both coastal and open ocean regions globally to reveal data on sea health and the impact of climate change.