Copertina

Using machine learning to downscale coarse-resolution environmental variables for understanding the spatial frequency of convective storms

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yu, Hungjui, Hoef, Lander Ver, Rasmussen, Kristen L., Ebert-Uphoff, Imme
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Atmospheric and Oceanic Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

How to use score-based diffusion in earth system science: A satellite nowcasting example
di: Chase, Randy J., et al.
Pubblicazione: (2025)

A Primer on Topological Data Analysis to Support Image Analysis Tasks in Environmental Science
di: Hoef, Lander Ver, et al.
Pubblicazione: (2022)

Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery
di: Lagerquist, Ryan, et al.
Pubblicazione: (2024)

An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
di: Ward-Leikis, Bryn, et al.
Pubblicazione: (2025)

Evaluation of Tropical Cyclone Track and Intensity Forecasts from Artificial Intelligence Weather Prediction (AIWP) Models
di: DeMaria, Mark, et al.
Pubblicazione: (2024)

HiRO-ACE: Fast and skillful AI emulation and downscaling trained on a 3 km global storm-resolving model
di: Perkins, W. Andre, et al.
Pubblicazione: (2025)

A multi-frequency spaceborne radar perspective of deep convection
di: Chase, Randy J., et al.
Pubblicazione: (2024)

Evaluating local climate in global storm-resolving models with the Köppen-Geiger classification
di: van Heerwaarden, Chiel C., et al.
Pubblicazione: (2026)

A global unstructured, coupled, high-resolution hindcast of waves and storm surge
di: Mentaschi, Lorenzo, et al.
Pubblicazione: (2023)

Emerging AI-based weather prediction models as downscaling tools
di: Koldunov, Nikolay, et al.
Pubblicazione: (2024)

A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics
di: Sorensen, Benedikt Barthel, et al.
Pubblicazione: (2024)

On the Extrapolation of Generative Adversarial Networks for downscaling precipitation extremes in warmer climates
di: Rampal, Neelesh, et al.
Pubblicazione: (2024)

Knowledge-guided machine learning for disentangling Pacific sea surface temperature variability across timescales
di: Hall, Kyle J. C., et al.
Pubblicazione: (2025)

Revealing recurrent regimes of mid-latitude atmospheric variability using novel machine learning method
di: Mukhin, Dmitry, et al.
Pubblicazione: (2024)

Precipitation diffusion downscaling and application to out-of-distribution simulations with and without stratospheric aerosol injection
di: Dong, Cameron, et al.
Pubblicazione: (2026)

Assessing the potential of state-of-the-art machine learning and physics-informed machine learning in predicting sea surface temperature
di: Sunil, Akshay, et al.
Pubblicazione: (2024)

Condensation mass sink and intensification of tropical storms
di: Makarieva, Anastassia M., et al.
Pubblicazione: (2024)

Dynamical-generative downscaling of climate model ensembles
di: Lopez-Gomez, Ignacio, et al.
Pubblicazione: (2024)

Rapid topographic scatter of near-inertial waves generated by storms
di: Barnes, Ashley J., et al.
Pubblicazione: (2023)

Prediction of storm surge on evolving landscapes under climate change
di: Johnson, David R, et al.
Pubblicazione: (2023)

Do AI models predict storm impacts as accurately as physics-based models? A case study of the February 2020 storm series over the North Atlantic
di: Afargan-Gerstman, Hilla, et al.
Pubblicazione: (2025)

Network science disentangles internal climate variability in global spatial dependence structures
di: Ray, Arnob, et al.
Pubblicazione: (2025)

An update to ECMWF's machine-learned weather forecast model AIFS
di: Moldovan, Gabriel, et al.
Pubblicazione: (2025)

Role of the ocean for fast atmospheric evolution revealed by machine learning
di: Antonio, Bobby, et al.
Pubblicazione: (2026)

Flo: A data-driven limited-area storm surge model
di: Kristensen, Nils Melsom, et al.
Pubblicazione: (2026)

Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate
di: Lin, Jerry, et al.
Pubblicazione: (2024)

Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies
di: Kutsuna, Takuro, et al.
Pubblicazione: (2026)

Seasonal forecasting using the GenCast probabilistic machine learning model
di: Antonio, Bobby, et al.
Pubblicazione: (2025)

Projecting U.S. coastal storm surge risks and impacts with deep learning
di: Rice, Julian R., et al.
Pubblicazione: (2025)

Rainfall forecasts in daily use over East Africa improved by machine learning
di: Cooper, Fenwick C., et al.
Pubblicazione: (2025)

Hybrid weather prediction using spectral nudging toward machine-learning forecasts
di: Polichtchouk, I., et al.
Pubblicazione: (2026)

Blending machine learning and physics-based approaches for weather and climate: a typology
di: Shipway, Benjamin J, et al.
Pubblicazione: (2026)

Improving forecasts of precipitation extremes over Northern and Central Italy using machine learning
di: Grazzini, Federico, et al.
Pubblicazione: (2024)

NORA-Surge: A storm surge hindcast for the Norwegian Sea, the North Sea and the Barents Sea
di: Kristensen, Nils Melsom, et al.
Pubblicazione: (2023)

Sources of low-frequency $δ^{18}$O variability in coastal ice cores from Dronning Maud Land
di: Vannitsem, Stéphane, et al.
Pubblicazione: (2024)

Probabilistic storyline attribution using machine learning
di: Loer, Frieder, et al.
Pubblicazione: (2026)

The role of elevated terrain and the Gulf of Mexico in the production of severe local storm environments over North America
di: Li, Funing, et al.
Pubblicazione: (2020)

Atmospheric stability sets maximum moist heat and convection in the midlatitudes
di: Li, Funing, et al.
Pubblicazione: (2025)

Dependence of convective precipitation extremes on near-surface relative humidity
di: van der Drift, Robert J., et al.
Pubblicazione: (2024)

Skilful global seasonal predictions from a machine learning weather model trained on reanalysis data
di: Kent, Chris, et al.
Pubblicazione: (2025)