Saved in:
| Main Authors: | Mukhin, Dmitry, Hannachi, Abdel, Braun, Tobias, Marwan, Norbert |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.10073 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Metastability, atmospheric midlatitude circulation regimes and large-scale teleconnection: a data-driven approach
by: Mukhin, Dmitry, et al.
Published: (2024)
by: Mukhin, Dmitry, et al.
Published: (2024)
Visualizing driving forces of spatially extended systems using the recurrence plot framework
by: Riedl, Maik, et al.
Published: (2024)
by: Riedl, Maik, et al.
Published: (2024)
Fast response of deep ocean circulation to mid-latitude winds in the Atlantic
by: Frajka-Williams, E., et al.
Published: (2025)
by: Frajka-Williams, E., et al.
Published: (2025)
Role of the ocean for fast atmospheric evolution revealed by machine learning
by: Antonio, Bobby, et al.
Published: (2026)
by: Antonio, Bobby, et al.
Published: (2026)
Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city
by: Meyer, David, et al.
Published: (2023)
by: Meyer, David, et al.
Published: (2023)
An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
by: Ward-Leikis, Bryn, et al.
Published: (2025)
by: Ward-Leikis, Bryn, et al.
Published: (2025)
Knowledge-guided machine learning for disentangling Pacific sea surface temperature variability across timescales
by: Hall, Kyle J. C., et al.
Published: (2025)
by: Hall, Kyle J. C., et al.
Published: (2025)
Quantifying intra-regime weather variability for energy applications
by: Gerighausen, Judith, et al.
Published: (2024)
by: Gerighausen, Judith, et al.
Published: (2024)
Using machine learning to downscale coarse-resolution environmental variables for understanding the spatial frequency of convective storms
by: Yu, Hungjui, et al.
Published: (2025)
by: Yu, Hungjui, et al.
Published: (2025)
Seasonal forecasting using the GenCast probabilistic machine learning model
by: Antonio, Bobby, et al.
Published: (2025)
by: Antonio, Bobby, et al.
Published: (2025)
Probabilistic storyline attribution using machine learning
by: Loer, Frieder, et al.
Published: (2026)
by: Loer, Frieder, et al.
Published: (2026)
Rainfall forecasts in daily use over East Africa improved by machine learning
by: Cooper, Fenwick C., et al.
Published: (2025)
by: Cooper, Fenwick C., et al.
Published: (2025)
Hybrid weather prediction using spectral nudging toward machine-learning forecasts
by: Polichtchouk, I., et al.
Published: (2026)
by: Polichtchouk, I., et al.
Published: (2026)
Assessing the potential of state-of-the-art machine learning and physics-informed machine learning in predicting sea surface temperature
by: Sunil, Akshay, et al.
Published: (2024)
by: Sunil, Akshay, et al.
Published: (2024)
Future changes in land and atmospheric variables: An analysis of their couplings in the Iberian Peninsula
by: Ojeda, Matilde García-Valdecasas, et al.
Published: (2024)
by: Ojeda, Matilde García-Valdecasas, et al.
Published: (2024)
Improving forecasts of precipitation extremes over Northern and Central Italy using machine learning
by: Grazzini, Federico, et al.
Published: (2024)
by: Grazzini, Federico, et al.
Published: (2024)
ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses
by: Watt-Meyer, Oliver, et al.
Published: (2024)
by: Watt-Meyer, Oliver, et al.
Published: (2024)
Probabilistic modelling of atmosphere-surface coupling with a copula Bayesian network
by: Mack, Laura, et al.
Published: (2025)
by: Mack, Laura, et al.
Published: (2025)
Mid-latitude interactions expand the Hadley circulation
by: Moon, W., et al.
Published: (2024)
by: Moon, W., et al.
Published: (2024)
Uncoupled high-latitude wave models in COAMPS
by: Rogers, W. E., et al.
Published: (2025)
by: Rogers, W. E., et al.
Published: (2025)
A general framework for the asymptotic analysis of moist atmospheric flows
by: Bäumer, Daniel, et al.
Published: (2025)
by: Bäumer, Daniel, et al.
Published: (2025)
An update to ECMWF's machine-learned weather forecast model AIFS
by: Moldovan, Gabriel, et al.
Published: (2025)
by: Moldovan, Gabriel, et al.
Published: (2025)
Advancing global sea ice prediction capabilities using a fully-coupled climate model with integrated machine learning
by: Gregory, William, et al.
Published: (2025)
by: Gregory, William, et al.
Published: (2025)
Revealing the drivers of turbulence anisotropy over flat and complex terrain: an interpretable machine learning approach
by: Mosso, Samuele, et al.
Published: (2025)
by: Mosso, Samuele, et al.
Published: (2025)
Concept drift of simple forecast models as a diagnostic of low-frequency, regime-dependent atmospheric reorganisation
by: Zhou, Haokun
Published: (2025)
by: Zhou, Haokun
Published: (2025)
Blending machine learning and physics-based approaches for weather and climate: a typology
by: Shipway, Benjamin J, et al.
Published: (2026)
by: Shipway, Benjamin J, et al.
Published: (2026)
Generative machine learning methods for multivariate ensemble post-processing
by: Chen, Jieyu, et al.
Published: (2022)
by: Chen, Jieyu, et al.
Published: (2022)
Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate
by: Lin, Jerry, et al.
Published: (2024)
by: Lin, Jerry, et al.
Published: (2024)
Skilful global seasonal predictions from a machine learning weather model trained on reanalysis data
by: Kent, Chris, et al.
Published: (2025)
by: Kent, Chris, et al.
Published: (2025)
Identifying atmospheric fronts based on diabatic processes using the dynamic state index (DSI)
by: Mack, Laura, et al.
Published: (2022)
by: Mack, Laura, et al.
Published: (2022)
Quantifying the radiative response to surface temperature variability: A critical comparison of current methods
by: Fredericks, Leif, et al.
Published: (2025)
by: Fredericks, Leif, et al.
Published: (2025)
ACE2-SOM: Coupling an ML atmospheric emulator to a slab ocean and learning the sensitivity of climate to changed CO$_2$
by: Clark, Spencer K., et al.
Published: (2024)
by: Clark, Spencer K., et al.
Published: (2024)
Uncertainty-permitting machine learning reveals sources of dynamic sea level predictability across daily-to-seasonal timescales
by: Brettin, Andrew, et al.
Published: (2025)
by: Brettin, Andrew, et al.
Published: (2025)
Improvements to the post-processing of weather forecasts using machine learning and feature selection
by: Iwase, Kazuma, et al.
Published: (2026)
by: Iwase, Kazuma, et al.
Published: (2026)
Sea wave data reconstruction using micro-seismic measurements and machine learning methods
by: Iafolla, Lorenzo, et al.
Published: (2024)
by: Iafolla, Lorenzo, et al.
Published: (2024)
Evapotranspiration trends over the last 300 years reconstructed from historical weather station observations via machine learning
by: Shi, Haiyang
Published: (2024)
by: Shi, Haiyang
Published: (2024)
Emergent conservation in atmospheric chemical mechanisms
by: Rodriguez, Beatriz Lucia G., et al.
Published: (2026)
by: Rodriguez, Beatriz Lucia G., et al.
Published: (2026)
Interpolation of mountain weather forecasts by machine learning
by: Iwase, Kazuma, et al.
Published: (2023)
by: Iwase, Kazuma, et al.
Published: (2023)
Estimation of AMOC transition probabilities using a machine learning based rare-event algorithm
by: Jacques-Dumas, Valérian, et al.
Published: (2024)
by: Jacques-Dumas, Valérian, et al.
Published: (2024)
Multivariate post-processing of probabilistic sub-seasonal weather regime forecasts
by: Mockert, Fabian, et al.
Published: (2024)
by: Mockert, Fabian, et al.
Published: (2024)
Similar Items
-
Metastability, atmospheric midlatitude circulation regimes and large-scale teleconnection: a data-driven approach
by: Mukhin, Dmitry, et al.
Published: (2024) -
Visualizing driving forces of spatially extended systems using the recurrence plot framework
by: Riedl, Maik, et al.
Published: (2024) -
Fast response of deep ocean circulation to mid-latitude winds in the Atlantic
by: Frajka-Williams, E., et al.
Published: (2025) -
Role of the ocean for fast atmospheric evolution revealed by machine learning
by: Antonio, Bobby, et al.
Published: (2026) -
Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city
by: Meyer, David, et al.
Published: (2023)