Results 171 to 180 of about 408,400 (310)

Retrieval of Snow Depth in Arctic Multi-year Ice Based on SMRT Model

Haiyang Kaifa yu guanli
The L-band microwave radiative transfer model can simulate the physical propagation process of microwave radiation signals in the Arctic ice and snow, and serves as an effective tool to invert the snow thickness of the Arctic ice.
FAN Yanfei, LI Lele, PANG Chunyu, SHI Lijian   +3 more
doaj  

A multimodel intercomparison study of variable‐resolution global models with grid refinement over the Arctic and Antarctic

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We document the protocol and first results from the first ever coordinated multimodel variable‐resolution experiment set with refinement over the polar regions. We find that the refinement generally yields model‐dependent effects. The most consistent improvement is an amelioration of the upper‐level cold bias in the polar regions that translates into ...
Lise Seland Graff, Dörthe Handorf, Raphael Köhler, Xavier Levine, René R. Wijngaard, Gareth J. Marshall, Alexey Yu. Karpechko, Ryan S. Williams, Priscilla A. Mooney   +8 more
wiley   +1 more source

Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis, A. Carrassi, J. Brajard, L. Bertino, M. Broccoli, D. Iovino, T.S. Finn, M. Bocquet   +7 more
wiley   +1 more source

Impact of data assimilation on Arctic sea‐ice thickness variability and its coupling with atmospheric forcing

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie, Yue Ying, Richard Davy, Laurent Bertino   +3 more
wiley   +1 more source

Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry. [PDF]

Sensors (Basel), 2019
Wei H, He X, Feng Y, Jin S, Shen F.
europepmc   +1 more source

Observations and numerical simulations of a valley‐exit wind in the Alpine Bolzano basin

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The evolution and spreading of the nocturnal valley‐exit wind flowing from the Isarco Valley into the Bolzano basin, in the Italian Alps, are found to be influenced by the basin temperature stratification. Measurements and high‐resolution simulations show that a cold‐air pool favors an upward trajectory of the flow at the exit of the valley.
Federica Gucci, Andrea Zonato, Marco Falocchi, Dino Zardi, Lorenzo Giovannini   +4 more
wiley   +1 more source

Snow depth variability in the Northern Hemisphere mountains observed from space. [PDF]

Nat Commun, 2019
Lievens H, Demuzere M, Marshall HP, Reichle RH, Brucker L, Brangers I, de Rosnay P, Dumont M, Girotto M, Immerzeel WW, Jonas T, Kim EJ, Koch I, Marty C, Saloranta T, Schöber J, De Lannoy GJM.   +16 more
europepmc   +1 more source

Validation of MODIS snow cover images over Austria

, 2006
International audienceThis study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product over the territory of Austria. The aims are (a) to analyse the spatial and temporal variability of the MODIS snow product classes, (b)
Blöschl, G., Parajka, J.
core   +2 more sources

Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions

Journal of Field Robotics, EarlyView.
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos, Steven Kay, Julia Wajoras, Robert Field, Evridiki V. Ntagiou, Fakher Mohammad, Yang Gao   +6 more
wiley   +1 more source

Improving the accuracy of gridded snow depth estimation through multi-source data and a machine learning fusion model. [PDF]

Sci Rep
Qiao D, Chen X, Zhou J, Liang S, Liu G.
europepmc   +1 more source