Recently added

Understanding Cloud Systems’ Structure and Organization Using a Machine’s Self-Learning Approach

Chatterjee, Dwaipayan; Acquistapace, Claudia; Deneke, Hartwig; Crewell, Susanne (American Meteorological Society, 2023)

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Unknown author (American Meteorological Society, 2023)

Exploring Randomly Wired Neural Networks for Climate Model Emulation

Yik, William; Silva, Sam J.; Geiss, Andrew; Watson-Parris, Duncan (American Meteorological Society, 2023)

Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder

Passarella, Linsey S.; Mahajan, Salil (American Meteorological Society, 2023)

A Deep Learning–Based Velocity Dealiasing Algorithm Derived from the WSR-88D Open Radar Product Generator

Veillette, Mark S.; Kurdzo, James M.; Stepanian, Phillip M.; McDonald, Joseph; Samsi, Siddharth; Cho, John Y. N. (American Meteorological Society, 2023)

Photographic Visualization of Weather Forecasts with Generative Adversarial Networks

Sigg, Christian; Cavallaro, Flavia; Günther, Tobias; Oswald, Martin R. (American Meteorological Society, 2023)

A Deep Learning Filter for the Intraseasonal Variability of the Tropics

Stan, Cristiana; Mantripragada, Rama Sesha Sridhar (American Meteorological Society, 2023)

Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks

Sekiyama, Tsuyoshi Thomas; Hayashi, Syugo; Kaneko, Ryo; Fukui, Ken-ichi (American Meteorological Society, 2023)

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network

Scarino, Benjamin; Itterly, Kyle; Bedka, Kristopher; Homeyer, Cameron R.; Allen, John; Bang, Sarah; Cecil, Daniel (American Meteorological Society, 2023)

Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability

Connolly, Charlotte; Barnes, Elizabeth A.; Hassanzadeh, Pedram; Pritchard, Mike (American Meteorological Society, 2023)

Atmospheric Pattern–Based Predictions of S2S Sea Level Anomalies for Two Selected U.S. Locations

Lee, Cameron C.; Sheridan, Scott C.; Dusek, Gregory P.; Pirhalla, Douglas E. (American Meteorological Society, 2023)

Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in Geoscience

Mamalakis, Antonios; Barnes, Elizabeth A.; Ebert-Uphoff, Imme (American Meteorological Society, 2023)

O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments

Leufen, Lukas Hubert; Kleinert, Felix; Schultz, Martin G. (American Meteorological Society, 2023)

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Jackson, Robert C.; Raut, Bhupendra A.; Dematties, Dario; Collis, Scott M.; Ferrier, Nicola; Beckman, Pete; Sankaran, Rajesh; Kim, Yongho; Park, Seongha; Shahkarami, Sean; Newsom, Rob (American Meteorological Society, 2023)

Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach

Yang, Shuxian; Ling, Fenghua; Li, Yue; Luo, Jing-Jia (American Meteorological Society, 2023)

GRRIEn Analysis: A Data Science Cheat Sheet for Earth Scientists Learning from Global Earth Observations

Carter, Elizabeth; Hultquist, Carolynne; Wen, Tao (American Meteorological Society, 2023)

Correcting Subseasonal Forecast Errors with an Explainable ANN to Understand Misrepresented Sources of Predictability of European Summer Temperatures

van Straaten, Chiem; Whan, Kirien; Coumou, Dim; van den Hurk, Bart; Schmeits, Maurice (American Meteorological Society, 2023)

YaBeSH Engineering and Technology Library

Archive

Artificial Intelligence for the Earth Systems: Recent submissions

Understanding Cloud Systems’ Structure and Organization Using a Machine’s Self-Learning Approach

Masthead

Exploring Randomly Wired Neural Networks for Climate Model Emulation

Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder

A Deep Learning–Based Velocity Dealiasing Algorithm Derived from the WSR-88D Open Radar Product Generator

Photographic Visualization of Weather Forecasts with Generative Adversarial Networks

A Deep Learning Filter for the Intraseasonal Variability of the Tropics

Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network

Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability

Atmospheric Pattern–Based Predictions of S2S Sea Level Anomalies for Two Selected U.S. Locations

Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in Geoscience

O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach

GRRIEn Analysis: A Data Science Cheat Sheet for Earth Scientists Learning from Global Earth Observations

Correcting Subseasonal Forecast Errors with an Explainable ANN to Understand Misrepresented Sources of Predictability of European Summer Temperatures

Uncertainty Calibration of Passive Microwave Brightness Temperatures Predicted by Bayesian Deep Learning Models

Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis

Creating and Evaluating Uncertainty Estimates with Neural Networks for Environmental-Science Applications

Artificial Intelligence for the Earth Systems: Recent submissions

Understanding Cloud Systems’ Structure and Organization Using a Machine’s Self-Learning Approach ﻿

Masthead ﻿

Exploring Randomly Wired Neural Networks for Climate Model Emulation ﻿

Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder ﻿

A Deep Learning–Based Velocity Dealiasing Algorithm Derived from the WSR-88D Open Radar Product Generator ﻿

Photographic Visualization of Weather Forecasts with Generative Adversarial Networks ﻿

A Deep Learning Filter for the Intraseasonal Variability of the Tropics ﻿

Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks ﻿

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network ﻿

Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability ﻿

Atmospheric Pattern–Based Predictions of S2S Sea Level Anomalies for Two Selected U.S. Locations ﻿

Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in Geoscience ﻿

O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments ﻿

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing ﻿

Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach ﻿

GRRIEn Analysis: A Data Science Cheat Sheet for Earth Scientists Learning from Global Earth Observations ﻿

Correcting Subseasonal Forecast Errors with an Explainable ANN to Understand Misrepresented Sources of Predictability of European Summer Temperatures ﻿

Uncertainty Calibration of Passive Microwave Brightness Temperatures Predicted by Bayesian Deep Learning Models ﻿

Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis ﻿

Creating and Evaluating Uncertainty Estimates with Neural Networks for Environmental-Science Applications ﻿

Understanding Cloud Systems’ Structure and Organization Using a Machine’s Self-Learning Approach

Masthead

Exploring Randomly Wired Neural Networks for Climate Model Emulation

Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder

A Deep Learning–Based Velocity Dealiasing Algorithm Derived from the WSR-88D Open Radar Product Generator

Photographic Visualization of Weather Forecasts with Generative Adversarial Networks

A Deep Learning Filter for the Intraseasonal Variability of the Tropics

Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network

Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability

Atmospheric Pattern–Based Predictions of S2S Sea Level Anomalies for Two Selected U.S. Locations

Carefully Choose the Baseline: Lessons Learned from Applying XAI Attribution Methods for Regression Tasks in Geoscience

O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach

GRRIEn Analysis: A Data Science Cheat Sheet for Earth Scientists Learning from Global Earth Observations

Correcting Subseasonal Forecast Errors with an Explainable ANN to Understand Misrepresented Sources of Predictability of European Summer Temperatures

Uncertainty Calibration of Passive Microwave Brightness Temperatures Predicted by Bayesian Deep Learning Models

Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis

Creating and Evaluating Uncertainty Estimates with Neural Networks for Environmental-Science Applications