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20222026
most citedStatistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification

1 citations · 1 across the 3 of their papers we have counts for

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physics.ao-ph2026

Emergent conservation in atmospheric chemical mechanisms

Beatriz Lucia G. Rodriguez, Patrick Obin Sturm, Daniel Getter +1

Conservation laws are time-invariant properties that constrain many physical systems. For systems of chemical reactions, conservation of mass constrains how atoms flow between chem…

physics.ao-ph2022★ 1 cited

Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification

Daniel Getter, Julie Bessac, Johann Rudi +1

Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over re…