Results 111 to 120 of about 3,014 (298)
Polar‐low track prediction using machine‐learning methods
Quarterly Journal of the Royal Meteorological Society, EarlyView.Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang +4 more
wiley +1 more source
Modeling snow mechanics with microtomographic images
, 2014 Caractériser les propriétés mécaniques de la neige est un défi majeur pour la prévision et la prédétermination du risque d’avalanche. Du fait du grand nombre de types de neige et de la difficulté à effectuer des mesures sur ce matériau très fragile, la ...
Hagenmuller, Pascal
core
Quarterly Journal of the Royal Meteorological Society, EarlyView.This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff +1 more
wiley +1 more source
Adhesion of Wet Snow to Different Cable Surfaces
Cohesion of snow and its adhesion to cable surfaces are the decisive factors for wet-snow shedding from power-line cables. Knowing the adhesive strength of snow is essential to predict when snow will shed and what consequences it will have on the ...
Hefny, Reham +3 more
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An opportunity index to anticipate when subseasonal predictions are useful
Quarterly Journal of the Royal Meteorological Society, EarlyView.Simultaneously active subseasonal windows of forecast opportunity can be combined into a single opportunity index, which can be used operationally to anticipate enhanced or reduced subseasonal prediction skill. For predictions of temperature anomalies in Switzerland during summer—a region and season with particularly low predictability—skill can nearly
Dominik Büeler +4 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 +7 more
wiley +1 more source
Tensile strength and fracture mechanics of cohesive dry snow related to slab avalanches
, 2011 Fracture mechanics has been applied for over 30 years to explain the release of slab avalanches, but most studies have focused on the initial shear fracture which governs the loss of slab stability rather than the ultimate tensile fracture which releases
Borstad, Christopher P.
core
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 +3 more
wiley +1 more source
Modeling Wet-Snow Shedding from Current-Carrying Conductors
The initiation of wet-snow shedding from currentcarrying conductors was studied experimentally and theoretically. A suspended cable with cylindrical snow accretion was considered, and some of the snow properties at the end of sleeve were measured and ...
Kollar, László E. +3 more
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Forecast‐Error Diagnostics in Neural Weather Models
Quarterly Journal of the Royal Meteorological Society, EarlyView.Deep learning weather prediction models enable efficient forecast‐error diagnostics through auto‐differentiation and low computational cost. We apply grid‐point relaxation and gradient‐based error sensitivity to identify key forecast‐error sources. Results show that medium‐range forecasts in the midlatitudes benefit most from relaxing the stratosphere ...
Uroš Perkan +2 more
wiley +1 more source