Results 141 to 150 of about 14,366 (306)
Inertial oscillation of a vertical rotating draft with application to a supercell storm [PDF]
An analytic model (vertical rotating draft) which includes the gross features of a supercell storm on an f-plane, undergoes an inertial oscillation that appears to have been overlooked in previous analytic and numerical models.
Costen, Robert C., Stock, Larry V.
core +1 more source
Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model
AGU Advances, Volume 7, Issue 2, April 2026.Abstract Machine learning (ML)‐based models have demonstrated high skill and computational efficiency, often outperforming conventional physics‐based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic‐scale atmospheric dynamics, their performance across timescales and under out‐of ...
Ziming Chen +11 more
wiley +1 more source
Active microwave sensing of the atmosphere, chapter 4 [PDF]
The use of active microwave systems to study atmospheric phenomena is studied. Atmospheric pollution, weather prediction, climate and weather modification, weather danger and disaster warning, and atmospheric processes and interactions are ...
core +1 more source
Estimating Mediterranean Cyclone Activity via Explainable Machine Learning
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract Intense cyclones in the Mediterranean drive most of the region's rainfall and wind‐wave extremes, exerting a significant socio‐economic impact. Currently there are no established analytical tools for estimating Mediterranean cyclone activity from climatological fields.
Guido Ascenso +5 more
wiley +1 more source
Steamship Portland: X-Storms [PDF]
In this lesson students will discover what causes extreme storms such as the Portland Gale of 1898 and the Halloween Nor'easter of 1991. They will identify and explain three factors that contributed to extreme storm conditions in the northwest Atlantic ...
Mel Goodwin
core
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract In this study, we developed a TabNet‐based machine learning model to predict tropical cyclone (TC) rapid intensification (RI) in the Western North Pacific. The most significant challenge in predicting RI is the severe class imbalance between rapid and non‐rapid intensification cases, typically 4.2:1 ratio based on 1977–2021 records.
Sanghyeok An +5 more
wiley +1 more source
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract Data‐driven emulation of storm surges has emerged as a valuable tool for supporting regional coastal risk assessment. Surrogate models for such applications are developed using data sets of surge predictions for synthetic storms across a large number of locations, corresponding to the nodes of the utilized numerical model used. Recent work has
P. Toofani Movaghar +3 more
wiley +1 more source
Climate Change Impacts on Hydrology in the Upper James Watershed, Virginia
JAWRA Journal of the American Water Resources Association, Volume 62, Issue 2, April 2026.ABSTRACT Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center–Hydrologic Modeling System (HEC‐HMS) is applied to evaluate climate change impacts ...
Imiya Mudiyanselage Chathuranika +1 more
wiley +1 more source
ANTICYCLONIC EDDIES IN THE ALASKA GYRE (AND CAPE HORN CURRENT?)
Gayana, 2004 Sea surface height (SSH) fields, constructed from multiple altimeters, have revealed the annual generation of anticyclonic eddies around the Alaska Gyre.
P. Ted Strub
doaj