Recently added

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

Molina, Maria J.; O’Brien, Travis A.; Anderson, Gemma; Ashfaq, Moetasim; Bennett, Katrina E.; Collins, William D.; Dagon, Katherine; Restrepo, Juan M.; Ullrich, Paul A. (American Meteorological Society, 2023)

A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions

Chen, Jiaxin; Ashton, Ian G. C.; Steele, Edward C. C.; Pillai, Ajit C. (American Meteorological Society, 2023)

Physics-Constrained Deep Learning Postprocessing of Temperature and Humidity

Zanetta, Francesco; Nerini, Daniele; Beucler, Tom; Liniger, Mark A. (American Meteorological Society, 2023)

Emulating the Adaptation of Wind Fields to Complex Terrain with Deep Learning

Le Toumelin, Louis; Gouttevin, Isabelle; Helbig, Nora; Galiez, Clovis; Roux, Mathis; Karbou, Fatima (American Meteorological Society, 2023)

Equity, Inclusion, and Justice: An Opportunity for Action for AMS Publications Stakeholders

Unknown author (American Meteorological Society, 2023)

Skillful U.S. Soy Yield Forecasts at Presowing Lead Times

Vijverberg, Sem; Hamed, Raed; Coumou, Dim (American Meteorological Society, 2023)

Short-Term (7 Day) Beaufort Sea Ice Extent Forecasting with Deep Learning

Keller, Mary Ruth; Piatko, Christine; Clemens-Sewall, Mary Versa; Eager, Rebecca; Foster, Kevin; Gifford, Christopher; Rollend, Derek; Sleeman, Jennifer (American Meteorological Society, 2023)

Cross-Validation Strategy Impacts the Performance and Interpretation of Machine Learning Models

Sweet, Lily-belle; Müller, Christoph; Anand, Mohit; Zscheischler, Jakob (American Meteorological Society, 2023)

Can Machine Learning Models Be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Time Scales?

Kiefer, Selina M.; Lerch, Sebastian; Ludwig, Patrick; Pinto, Joaquim G. (American Meteorological Society, 2023)

Masthead

Unknown author (American Meteorological Society, 2023)

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator

Reinhardt, Maria; Schoger, Sybille Y.; Kurzrock, Frederik; Potthast, Roland (American Meteorological Society, 2023)

Statistical Modeling of Monthly and Seasonal Michigan Snowfall Based on Machine Learning: A Multiscale Approach

Meng, Lei; Zhu, Laiyin (American Meteorological Society, 2023)

The Development and Initial Capabilities of ThunderCast, a Deep Learning Model for Thunderstorm Nowcasting in the United States

Ortland, Stephanie M.; Pavolonis, Michael J.; Cintineo, John L. (American Meteorological Society, 2023)

Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands

Cambier van Nooten, Charlotte; Schreurs, Koert; Wijnands, Jasper S.; Leijnse, Hidde; Schmeits, Maurice; Whan, Kirien; Shapovalova, Yuliya (American Meteorological Society, 2023)

Bias Correcting Climate Model Simulations Using Unpaired Image-to-Image Translation Networks

Fulton, D. James; Clarke, Ben J.; Hegerl, Gabriele C. (American Meteorological Society, 2023)

Understanding Spatial Context in Convolutional Neural Networks Using Explainable Methods: Application to Interpretable GREMLIN

Hilburn, Kyle A. (American Meteorological Society, 2023)

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales

Annau, Nicolaas J.; Cannon, Alex J.; Monahan, Adam H. (American Meteorological Society, 2023)

Environment-Aware Digital Twins: Incorporating Weather and Climate Information to Support Risk-Based Decision-Making

Dale, Kirstine I.; Pope, Edward C. D.; Hopkinson, Aaron R.; McCaie, Theo; Lowe, Jason A. (American Meteorological Society, 2023)

Perspectives on Artificial Intelligence for Predictions in Ecohydrology

Massoud, Elias C.; Hoffman, Forrest; Shi, Zheng; Tang, Jinyun; Alhajjar, Elie; Barnes, Mallory; Braghiere, Renato K.; Cardon, Zoe; Collier, Nathan; Crompton, Octavia; Dennedy-Frank, P. James; Gautam, Sagar; Gonzalez-Meler, Miquel A.; Green, Julia K.; Kove (American Meteorological Society, 2023)

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill

Hoffman, Lauren; Mazloff, Matthew R.; Gille, Sarah T.; Giglio, Donata; Bitz, Cecilia M.; Heimbach, Patrick; Matsuyoshi, Kayli (American Meteorological Society, 2023)

YaBeSH Engineering and Technology Library

Archive

Artificial Intelligence for the Earth Systems: Recent submissions

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions

Physics-Constrained Deep Learning Postprocessing of Temperature and Humidity

Emulating the Adaptation of Wind Fields to Complex Terrain with Deep Learning

Equity, Inclusion, and Justice: An Opportunity for Action for AMS Publications Stakeholders

Skillful U.S. Soy Yield Forecasts at Presowing Lead Times

Short-Term (7 Day) Beaufort Sea Ice Extent Forecasting with Deep Learning

Cross-Validation Strategy Impacts the Performance and Interpretation of Machine Learning Models

Can Machine Learning Models Be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Time Scales?

Masthead

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator

Statistical Modeling of Monthly and Seasonal Michigan Snowfall Based on Machine Learning: A Multiscale Approach

The Development and Initial Capabilities of ThunderCast, a Deep Learning Model for Thunderstorm Nowcasting in the United States

Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands

Bias Correcting Climate Model Simulations Using Unpaired Image-to-Image Translation Networks

Understanding Spatial Context in Convolutional Neural Networks Using Explainable Methods: Application to Interpretable GREMLIN

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales

Environment-Aware Digital Twins: Incorporating Weather and Climate Information to Support Risk-Based Decision-Making

Perspectives on Artificial Intelligence for Predictions in Ecohydrology

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill

Artificial Intelligence for the Earth Systems: Recent submissions

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena ﻿

A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions ﻿

Physics-Constrained Deep Learning Postprocessing of Temperature and Humidity ﻿

Emulating the Adaptation of Wind Fields to Complex Terrain with Deep Learning ﻿

Equity, Inclusion, and Justice: An Opportunity for Action for AMS Publications Stakeholders ﻿

Skillful U.S. Soy Yield Forecasts at Presowing Lead Times ﻿

Short-Term (7 Day) Beaufort Sea Ice Extent Forecasting with Deep Learning ﻿

Cross-Validation Strategy Impacts the Performance and Interpretation of Machine Learning Models ﻿

Can Machine Learning Models Be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Time Scales? ﻿

Masthead ﻿

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator ﻿

Statistical Modeling of Monthly and Seasonal Michigan Snowfall Based on Machine Learning: A Multiscale Approach ﻿

The Development and Initial Capabilities of ThunderCast, a Deep Learning Model for Thunderstorm Nowcasting in the United States ﻿

Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands ﻿

Bias Correcting Climate Model Simulations Using Unpaired Image-to-Image Translation Networks ﻿

Understanding Spatial Context in Convolutional Neural Networks Using Explainable Methods: Application to Interpretable GREMLIN ﻿

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales ﻿

Environment-Aware Digital Twins: Incorporating Weather and Climate Information to Support Risk-Based Decision-Making ﻿

Perspectives on Artificial Intelligence for Predictions in Ecohydrology ﻿

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill ﻿

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions

Physics-Constrained Deep Learning Postprocessing of Temperature and Humidity

Emulating the Adaptation of Wind Fields to Complex Terrain with Deep Learning

Equity, Inclusion, and Justice: An Opportunity for Action for AMS Publications Stakeholders

Skillful U.S. Soy Yield Forecasts at Presowing Lead Times

Short-Term (7 Day) Beaufort Sea Ice Extent Forecasting with Deep Learning

Cross-Validation Strategy Impacts the Performance and Interpretation of Machine Learning Models

Can Machine Learning Models Be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Time Scales?

Masthead

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator

Statistical Modeling of Monthly and Seasonal Michigan Snowfall Based on Machine Learning: A Multiscale Approach

The Development and Initial Capabilities of ThunderCast, a Deep Learning Model for Thunderstorm Nowcasting in the United States

Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands

Bias Correcting Climate Model Simulations Using Unpaired Image-to-Image Translation Networks

Understanding Spatial Context in Convolutional Neural Networks Using Explainable Methods: Application to Interpretable GREMLIN

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales

Environment-Aware Digital Twins: Incorporating Weather and Climate Information to Support Risk-Based Decision-Making

Perspectives on Artificial Intelligence for Predictions in Ecohydrology

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill