Results 81 to 90 of about 471 (203)

Uncertainty‐Aware Machine Learning for Onset of Deep Convection: Under what Conditions Are Trigger Predictions More Reliable?

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract Machine Learning (ML) models have emerged as a powerful tool for predicting deep convection triggering, yet the atmospheric conditions that systematically challenge these models in detecting deep convection remain poorly understood. To diagnose such ambiguous regimes, we trained a Controlled Abstention Neural Network (CAN) that separates high‐
Ashish Bhattarai, Youtong Zheng
wiley   +1 more source

Equivalent Subsurface Thermal Characteristics for Heterogeneous Surfaces

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract Land‐surface and atmospheric models often represent subgrid‐scale variability using a single set of effective properties. Estimating these equivalent properties is critical for predicting land‐atmosphere exchanges accurately, but challenging when materials with distinct radiative and thermal characteristics coexist, particularly in urban ...
Erfan Hosseini, Elie Bou‐Zeid
wiley   +1 more source

Scaling and Uncertainty in Soil Moisture Modelling: A Probabilistic Deep Learning Perspective

Hydrological Processes, Volume 40, Issue 8, August 2026.
A probabilistic Gaussian Mixture Long Short‐Term Memory framework is used to investigate soil moisture dynamics across the continental United States using meteorological forcings and physiographic attributes. Predictions are evaluated at unseen International Soil Moisture Network sites to ensure realistic regional transfer.
Balazs Bischof, Erwin Zehe, Ralf Loritz
wiley   +1 more source

Assessing Taiwan's Future Climate: High Resolution Projections and Regional Impacts From Statistical Downscaling of CMIP6 Data

International Journal of Climatology, Volume 46, Issue 10, August 2026.
The Taiwan Empirical‐Statistical Downscaling (TaiESD) dataset utilises quantile mapping (QM) for temperature and quantile delta mapping (QDM) for precipitation bias correction. It was developed to provide high‐resolution climate change information for Taiwan.
Cheng‐Ta Chen, Yu‐Shiang Tung, Chun‐Yu Wang, Shiou‐Li Lin   +3 more
wiley   +1 more source

Aligning Real‐Time Recurrence Computational Fluid Dynamics Simulations with Plant Data for the Ruhrstahl–Heraeus Degassing Process of Steel

steel research international, Volume 97, Issue 8, Page 4207-4222, August 2026.
Uncertainties exist in computational fluid dynamics (CFD) modeling of complex metallurgical processes, even when partly validated by laboratory experiments. rCFD enables computationally efficient prediction of long‐term RH degassing and can be adapted to vary flow conditions.
Xiaomeng Zhang, Maria Thumfart, Roman Rössler, Stefan Pirker   +3 more
wiley   +1 more source

Wind Turbine Control for Spatially Varying Turbulence

Wind Energy, Volume 29, Issue 8, August 2026.
ABSTRACT This study investigates the influence of inflow turbulence generation simulation methods and blade pitch control strategies on the performance and blade structure loading of a large offshore wind turbine. Two inflow representations were considered: synthetic Kaimal turbulence generated in accordance with IEC design standards and large‐eddy ...
Hannah Mullings, Mina Ghobrial, Wenjun Ye, Yi Zhang, David Apsley, Peter Stansby   +5 more
wiley   +1 more source

Gradient‐Free Online Learning of Subgrid‐Scale Dynamics With Neural Emulators

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.
Abstract In this paper, we propose a generic algorithm to train machine learning‐based subgrid parametrizations online, that is, with a posteriori loss functions, but for non‐differentiable numerical solvers. The proposed approach leverages a neural emulator to approximate the reduced state‐space solver, which is then used to allow gradient propagation
H. Frezat, R. Fablet, G. Balarac, J. Le Sommer   +3 more
wiley   +1 more source

Assessing Cloud and Precipitation Properties on Temporal Scales Using LASSO Simulations Over the ARM Eastern North Atlantic (ENA) Site

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract The representation of low clouds and precipitation remains a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub‐grid variability and scale‐dependent sampling. This study evaluates the performance of preliminary simulations from the Large‐Eddy Simulation (LES) Atmospheric ...
Jiakun Liang, Daniel T. McCoy, William I. Gustafson Jr., Scott E. Giangrande, Satoshi Endo, John Rausch, Jennifer D. Small Griswold   +6 more
wiley   +1 more source

The Ceiling Height of Wildland Fire Plumes in Quasi‐Steady Stratified and Sheared Boundary Layers

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract Radar observations from a prescribed fire experiment reveal a large‐scale, billow‐like vorticity structure associated with the plume head near the onset of plume bending. This bending limits the vertical extent of the plume and defines the characteristic plume ceiling height.
Jie Sun, Kevin Speer, Bryan Quaife, Ming Cai, David Schvartzman   +4 more
wiley   +1 more source

Formulation and Implementation of a Dynamic Roughness Length for Improved Surface Wind Speeds in WRF

Earth and Space Science, Volume 13, Issue 8, August 2026.
Abstract Accurate near‐surface winds from the Weather Research and Forecasting (WRF) model are essential for wind‐energy applications, yet persistent biases remain that depend on terrain, season, and land cover. This study develops and evaluates an observation‐informed, time‐varying aerodynamic roughness length for WRF. The roughness length is inferred
S. Srivastava, K. R. Schell
wiley   +1 more source