Results 71 to 80 of about 17,653,942 (158)

One to Three‐Day Lead Streamflow Forecast Using Multi‐Head Attention With Long Short‐Term Memory in Reservoir Regulated Catchment

Water Resources Research, Volume 62, Issue 8, August 2026.
Abstract Accurate, timely, and actionable flood forecasting has potential for reducing flood risk but remains challenging due to uncertainties in meteorological forecasts, poor hydrological observations, and increasing forecast errors with lead time. While Long Short‐Term Memory (LSTM) models have surpassed conventional hydrological forecasting models,
Hiren Solanki, A. S. Aravinthakshan, Sayuj Gupta, Vimal Mishra   +3 more
wiley   +1 more source

Statistical Model of Subsurface Scattering Bias in ICESat‐2's ATL06 Product

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract ICESat‐2 uses visible laser pulses and photon‐counting detectors to range the Earth's surface, providing precision altimetry for measuring ice sheet elevation change. However, since water ice is transparent to visible light, the photon returns recorded by ICESat‐2's ATLAS instrument may originate from subsurface scattering inside the snow or ...
Thilini Bamunu Arachchige, Kelly E. Gleason, Jonathan C. Ryan, Markus Allgaier   +3 more
wiley   +1 more source

Mission design concepts for repeat groundtrack orbits and application to the ICESat mission [PDF]

, 2008
textThe primary objective of the NASA sponsored ICESat mission is to study the short and long term changes in the ice mass in the Greenland and Antarctica regions.
Pie, Nadege
core  

Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements: Uncertainty Analyses

Frontiers in Remote Sensing, 2022
The application of diffusion theory and Monte Carlo lidar radiative transfer simulations presented in Part I of this series of study suggests that snow depth can be derived from the first-, second- and third-order moments of the lidar backscattering ...
Xiaomei Lu, Yongxiang Hu, Xubin Zeng, Snorre A. Stamnes, Thomas A. Neuman, Nathan T. Kurtz, Yuekui Yang, Peng-Wang Zhai, Meng Gao, Meng Gao, Wenbo Sun, Kuanman Xu, Zhaoyan Liu, Ali H. Omar, Rosemary R. Baize, Laura J. Rogers, Brandon O. Mitchell, Knut Stamnes, Yuping Huang, Nan Chen, Carl Weimer, Jennifer Lee, Zachary Fair   +22 more
doaj   +1 more source

Robust Regional Contrast but Penetration‐Sensitive Snow Thickness Over Sea Ice From Multi‐Winter Antarctic CRYO2ICE Observations

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract Snow on Antarctic sea ice modulates albedo, thermodynamic growth, and snow–ice formation, yet remains a leading uncertainty in altimetry‐derived sea‐ice thickness. Here we use the post‐2022 CRYO2ICE configuration to derive along‐track winter snow thickness from ICESat‐2 laser and CryoSat‐2 Ku‐band radar freeboards over the Weddell and Ross ...
Xinlong Liu, Alexander D. Fraser, Rachel L. Tilling, Petra Heil, Stuart P. Corney   +4 more
wiley   +1 more source

A Scalable, Cloud‐Based Workflow for Spectrally‐Attributed ICESat‐2 Bathymetry With Application to Benthic Habitat Mapping Using Deep Learning

Earth and Space Science
Since the 2018 launch of NASA's ICESat‐2 satellite, numerous studies have documented the bathymetric measurement capabilities of the space‐based laser altimeter.
Forrest Corcoran, Christopher E. Parrish, Lori A. Magruder, J. P. Swinski   +3 more
doaj   +1 more source

Enhanced Retrieval of Spring Snow Depth Over Pan‐Arctic Sea Ice From AMSR2 Observations for 2013–2023 Using Multi‐Model Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Snow on sea ice modulates the Earth's radiation budget and sea ice mass balance, yet satellite retrievals of Arctic snow depth remain subject to substantial algorithmic uncertainty. We develop a multi‐model machine learning (ML) framework for retrieving spring snow depth over Arctic sea ice from Advanced Microwave Scanning Radiometer 2 (AMSR2).
Yi Zhou, Chentong Zhang, Alek Petty, Xianwei Wang, Ruibo Lei, Wenxuan Liu, Yu Zhang   +6 more
wiley   +1 more source

Diagnosing Cryospheric Runoff Dynamics: A Distributed Differentiable Hydrological Model With Global Transfer Learning

Water Resources Research, Volume 62, Issue 8, August 2026.
Abstract Accurate hydrological prediction in alpine regions remains challenging due to complex cryospheric processes and limited observational records. Traditional hydrological models are often subject to structural uncertainty, whereas purely data‐driven deep learning (DL) models may lack physical interpretability under non‐stationary climate ...
Jun Mei, Bin Yong, Gerald Corzo, Yang Hong, Ruochen Sun, Xin Tao, Jiahu Wang, Qingyun Duan   +7 more
wiley   +1 more source

Discrepancy in Satellite Altimetry Products Hinders Robust Retrieval of GIA Signals From Bedrock GNSS Data in Greenland

Geophysical Research Letters, Volume 53, Issue 14, 28 July 2026.
Abstract Isolating glacial isostatic adjustment (GIA) signals from Global Navigation Satellite System (GNSS) observations of vertical land motion (VLM) in Greenland requires removal of elastic solid Earth response to contemporary ice mass change. This elastic correction depends on ice‐surface elevation changes derived from satellite altimetry and firn ...
Holly Kyeore Han, Surendra Adhikari, Lambert Caron, Hui Gao, Parviz Ajourlou, Shfaqat Khan, Beata M. Csatho   +6 more
wiley   +1 more source

ICESat‐2 Pointing Calibration and Geolocation Performance

Earth and Space Science, 2021
ICESat‐2 science requirements are dependent on the accurate real‐time pointing control (i.e., geolocation control) and postprocessed geolocation knowledge of the laser altimeter surface returns. Prelaunch pointing alignment errors and postlaunch pointing
S. B. Luthcke, T. C. Thomas, T. A. Pennington, T. W. Rebold, J. B. Nicholas, D. D. Rowlands, A. S. Gardner, S. Bae   +7 more
doaj   +1 more source