Results 161 to 170 of about 4,257,836 (266)

Multilayer Carbon-Structured BaTiO₃@C Nanocomposites with Wide Microwave Absorption Bandwidth and Excellent Corrosion Resistance. [PDF]

Materials (Basel)
Guo S, Sun Y, Li S, Jiang X, Sun D.
europepmc   +1 more source

Mesoscale Modeling of Titan’s Shangri‐La Region: The Impact of Surface Properties on Winds

Journal of Geophysical Research: Planets, Volume 131, Issue 10, October 2026.
Abstract The knowledge of Titan’s near‐surface atmosphere is sparse. The Huygens descent probe measured winds, and the multiple dune field observations and possible dust storms suggest active near‐surface dynamics. The Dragonfly rotorcraft lander will fly close to the surface in the Shangri‐La region, near the Huygens landing site, where complex dune ...
Maxence Lefèvre, Léa E. Bonnefoy, Aymeric Spiga, Bruno de Batz de Trenquelléon, Sébastien Lebonnois, Alexander G. Hayes   +5 more
wiley   +1 more source

CROF-Net: A Robust Algorithm for Simulation-Measurement Cross-Domain Few-Shot HRRP Target Recognition. [PDF]

Sensors (Basel)
Xu X, Zhu M, Yu K, Liu K.
europepmc   +1 more source

A Regional Intercomparison of Ice Sheet Mass Balance Estimates of the Northwest Greenland Ice Sheet

Journal of Geophysical Research: Earth Surface, Volume 131, Issue 10, October 2026.
Abstract Changes in ice sheet mass manifest as changes in ice flow, ice thickness, and gravitational attraction. These parameters can be measured from space and used to track Greenland's contribution to sea level rise independently from each other. While an excellent level of agreement between these satellite techniques has been demonstrated at the ice
Inès N. Otosaka, Andrew Shepherd, Andreas Groh, Thorben Döhne, Xavier Fettweis, Brice Noël   +5 more
wiley   +1 more source

Entrained debris records regrowth of the Greenland Ice Sheet after the last interglacial. [PDF]

Nat Geosci
Holschuh N, Christianson K, Dienstfrey W, Hills B, Hoffman AO, Paden J, Winter K, Zuraw R.   +7 more
europepmc   +1 more source

In the Age of AI—Are National Models and Data Sets Still Important for Stream Flow Prediction?

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Accurate streamflow prediction is critical for effective water resource management, and recent advances in deep learning and multi‐basin data sets have significantly improved model skill. Global deep‐learning models, trained on thousands of catchments have demonstrated strong generalization across diverse climates and continents.
Brett Snider, Ehsan Roshani
wiley   +1 more source

Time‐Varying Operation Policies With GRU‐Based Parameterization for Adaptive Multi‐Objective Reservoir Operation Under Climate Change

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Designing reservoir operation policies that can adapt to non‐stationary hydroclimatic conditions is a major challenge for water resources management under climate change. This study develops an adaptive dynamic operation policy (ADOP), in which Gaussian radial basis functions (RBFs) are coupled with a gated recurrent unit (GRU)‐based ...
Yiming Wei, Renchao Wang, Lu Zhuo, Zengchuan Dong   +3 more
wiley   +1 more source

Impact of Two Radio Occultation Constellations on Numerical Weather Prediction: Polar‐Orbits Only and Mixed Polar‐Equatorial Orbits

Earth and Space Science, Volume 13, Issue 10, October 2026.
Abstract This study explores the relative impact of two orbital configurations for Global Navigation Satellite System radio occultation (RO) observations in numerical weather prediction using observing system simulation experiments (OSSE). Three experiments are carried out: a Control experiment with no RO observations and two experiments with 14,000 RO
Nikki C. Privé, Christopher Barsoum, Douglas Hunt, Michael J. Murphy, Richard Anthes, William Gullotta, Natalie Laudier   +6 more
wiley   +1 more source

Oil spill segmentation of noisy SAR images using domain adaptation based UNet. [PDF]

Sci Rep
Zaheeruddin S, Suganthi K.
europepmc   +1 more source

Machine Learning Predictions of PM2.5 and Their Applications to Exposure and Health Assessment in the CONUS

GeoHealth, Volume 10, Issue 10, October 2026.
Abstract Atmospheric fine particulate matter (PM2.5) is one of the most important risk factors for various respiratory and cardiovascular diseases. We develop a two‐phase data‐driven framework that uses geostationary Aerosol Optical Depth (AOD) retrievals to predict hourly PM2.5 at 0.01° × 0.01° resolution and support exposure assessment across ...
K. Fan, A. Bloom, Z. Qu
wiley   +1 more source