Article-Journal

On the phenomena-oriented validation of spatial neural-network based surface wind downscaling over the Arctic seas
Neural-network based downscaling offers a computationally efficient alternative to high-resolution dynamical modeling, yet its …
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Neural network atmospheric bias correction on heterogeneous data with fine-scale dynamics preservation
High-resolution regional numerical weather prediction (NWP) models are essential tools for capturing atmospheric dynamics, including …
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Assessment of Atmospheric Dynamics Based on Neural-Network Downscaling of Near-Surface Wind Speed Fields over the Barents and Kara Seas
This study examines the use of a deep learning approach for spatial downscaling (increasing spatial resolution) of near-surface wind …
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ВOCCТАНОВЛЕНИЕ ПРИПОВЕРХНОСТНОЙ ВЛАЖНОСТИ АТМОСФЕРЫ НАД ОКЕАНОМ ПО ДАННЫМ СОПУТСТВУЮЩИХ МЕТЕОРОЛОГИЧЕСКИХ ИЗМЕРЕНИЙ С ПРИМЕНЕНИЕМ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ
Air humidity in the near-surface atmospheric layer over the ocean is a key parameter influencing the transfer of moisture and heat …
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Improving data-driven estimation of significant wave height through preliminary training on synthetic X-band radar sea clutter imagery
X-band marine radar captures the signal reflected from the sea surface. Theoretical studies indicate that the initial unfiltered signal …
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Improved sea surface salinity data for the Arctic Ocean derived from SMAP satellite data using machine learning approaches
Salinity is among the key climate characteristics of the World Ocean. During the last 15 years, sea surface salinity (SSS) is measured …
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