Saved in:
| Main Authors: | Xu, Rui, Yao, Dawen, Pian, Yuzhuang, Cao, Ruhui, Fu, Yixin, Yang, Xinru, Gan, Ting, Liu, Yonghong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.12367 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
by: Liu, Shigan, et al.
Published: (2025)
by: Liu, Shigan, et al.
Published: (2025)
Compound heat wave and PM2.5 pollution episodes in U.S. cities
by: Henry, Sarah, et al.
Published: (2023)
by: Henry, Sarah, et al.
Published: (2023)
Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
by: Chen, Yuan, et al.
Published: (2026)
by: Chen, Yuan, et al.
Published: (2026)
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)
Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery
by: Lagerquist, Ryan, et al.
Published: (2024)
by: Lagerquist, Ryan, et al.
Published: (2024)
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)
Spatio-temporal Joint Analysis of PM2.5 and Ozone in California with INLA
by: Pan, Jianan, et al.
Published: (2024)
by: Pan, Jianan, et al.
Published: (2024)
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)
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)
OTProf: estimating high-resolution profiles of optical turbulence ($C_n^2$) from reanalysis using deep learning
by: Pierzyna, Maximilian, et al.
Published: (2026)
by: Pierzyna, Maximilian, et al.
Published: (2026)
Seasonal forecasting using the GenCast probabilistic machine learning model
by: Antonio, Bobby, et al.
Published: (2025)
by: Antonio, Bobby, et al.
Published: (2025)
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)
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)
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)
Aragats high altitude research station 80 years of continuous cosmic ray monitoring
by: Asaturyan, Z., et al.
Published: (2024)
by: Asaturyan, Z., et al.
Published: (2024)
Probabilistic storyline attribution using machine learning
by: Loer, Frieder, et al.
Published: (2026)
by: Loer, Frieder, et al.
Published: (2026)
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)
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)
Revealing recurrent regimes of mid-latitude atmospheric variability using novel machine learning method
by: Mukhin, Dmitry, et al.
Published: (2024)
by: Mukhin, Dmitry, 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)
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)
Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet)
by: Cai, Shengjuan, et al.
Published: (2024)
by: Cai, Shengjuan, et al.
Published: (2024)
Track-Dependent Links between Tropical Cyclones and Extratropical Predictability in Physical and AI Models
by: Zhang, Gan
Published: (2026)
by: Zhang, Gan
Published: (2026)
Amplified Summer Wind Stilling and Land Warming Compound Energy Risks in Northern Midlatitudes
by: Zhang, Gan
Published: (2024)
by: Zhang, Gan
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)
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)
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)
Multi-scale assessment of high-resolution reanalysis precipitation fields over Italy
by: Cavalleri, Francesco, et al.
Published: (2024)
by: Cavalleri, Francesco, et al.
Published: (2024)
A global unstructured, coupled, high-resolution hindcast of waves and storm surge
by: Mentaschi, Lorenzo, et al.
Published: (2023)
by: Mentaschi, Lorenzo, et al.
Published: (2023)
Interpolation of mountain weather forecasts by machine learning
by: Iwase, Kazuma, et al.
Published: (2023)
by: Iwase, Kazuma, et al.
Published: (2023)
A high-resolution prediction dataset for solar energy across China (2015-2060)
by: Zhu, Daoming, et al.
Published: (2025)
by: Zhu, Daoming, et al.
Published: (2025)
Enhanced predictions of the Madden-Julian oscillation using the FuXi-S2S machine learning model: Insights into physical mechanisms
by: Cao, Can, et al.
Published: (2025)
by: Cao, Can, et al.
Published: (2025)
Identifying high resolution benchmark data needs and Novel data-driven methodologies for Climate Downscaling
by: Curran, Declan, et al.
Published: (2024)
by: Curran, Declan, et al.
Published: (2024)
Hybrid machine learning data assimilation for marine biogeochemistry
by: Higgs, Ieuan, et al.
Published: (2025)
by: Higgs, Ieuan, et al.
Published: (2025)
A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics
by: Sorensen, Benedikt Barthel, et al.
Published: (2024)
by: Sorensen, Benedikt Barthel, et al.
Published: (2024)
Modeling Indoor PM$_{2.5}$ Exposure During Retrofits: Plastic Film Barriers and a Quadratic Baseline Approach
by: Sipakov, Rostyslav, et al.
Published: (2025)
by: Sipakov, Rostyslav, et al.
Published: (2025)
Simulating the Air Quality Impact of Prescribed Fires Using Graph Neural Network-Based PM$_{2.5}$ Forecasts
by: Liao, Kyleen, et al.
Published: (2023)
by: Liao, Kyleen, et al.
Published: (2023)
Confronting Contemporary Seasonality Changes in East Asian Tropical Cyclone Landfalls with a Multi-Century Historical Baseline
by: Zhang, Gan, et al.
Published: (2025)
by: Zhang, Gan, et al.
Published: (2025)
How different are deterministic physics suites when coupled to fixed model dynamics and why?
by: Groot, Edward, et al.
Published: (2026)
by: Groot, Edward, et al.
Published: (2026)
Similar Items
-
A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
by: Liu, Shigan, et al.
Published: (2025) -
Compound heat wave and PM2.5 pollution episodes in U.S. cities
by: Henry, Sarah, et al.
Published: (2023) -
Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
by: Chen, Yuan, et al.
Published: (2026) -
Using machine learning to downscale coarse-resolution environmental variables for understanding the spatial frequency of convective storms
by: Yu, Hungjui, et al.
Published: (2025) -
Center-fixing of tropical cyclones using uncertainty-aware deep learning applied to high-temporal-resolution geostationary satellite imagery
by: Lagerquist, Ryan, et al.
Published: (2024)