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Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Prognostic Validation of a Neural Network Unified Physics Parameterization
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Applications of Deep Learning to Ocean Data Inference and Subgrid Parameterization
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Spatially Extended Tests of a Neural Network Parametrization Trained by Coarse‐Graining
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An overview of gradient descent optimization algorithms
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Author comment: The future of coastal monitoring through satellite remote sensing — R0/PR1
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Recommendation: The future of coastal monitoring through satellite remote sensing — R0/PR4
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Detecting Climate Signals Using Explainable AI With Single‐Forcing Large Ensembles
inferred← citeshttps://doi.org/10.1029/2021ms002496openalex-snapshot
Revealing the Impact of Global Heating on North Atlantic Circulation Using Transparent Machine Learning
inferred← citeshttps://doi.org/10.1029/2021ms002502openalex-snapshot
Sub‐Seasonal Forecasting With a Large Ensemble of Deep‐Learning Weather Prediction Models
inferred← citeshttps://doi.org/10.1029/2021ms002509openalex-snapshot
Learning to Correct Climate Projection Biases
inferred← citeshttps://doi.org/10.1029/2021ms002573openalex-snapshot
Controlled Abstention Neural Networks for Identifying Skillful Predictions for Classification Problems
inferred← citeshttps://doi.org/10.1029/2021ms002774openalex-snapshot
Using Simple, Explainable Neural Networks to Predict the Madden‐Julian Oscillation
inferred← citeshttps://doi.org/10.1029/2021ms002881openalex-snapshot
Using an Explainable Machine Learning Approach to Characterize Earth System Model Errors: Application of SHAP Analysis to Modeling Lightning Flash Occurrence
inferred← citeshttps://doi.org/10.1029/2021ms002941openalex-snapshot
Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks
inferred← citeshttps://doi.org/10.1029/2021ms002960openalex-snapshot
Explicit Physical Knowledge in Machine Learning for Ocean Carbon Flux Reconstruction: The pCO 2 ‐Residual Method
inferred← citeshttps://doi.org/10.1029/2022ea002348openalex-snapshot
Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks
inferred← citeshttps://doi.org/10.1029/2022ef003086openalex-snapshot
Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US
inferred← citeshttps://doi.org/10.1029/2022gl098173openalex-snapshot
Predicting Slowdowns in Decadal Climate Warming Trends With Explainable Neural Networks
inferred← citeshttps://doi.org/10.1029/2022gl098635openalex-snapshot
Incorporating Uncertainty Into a Regression Neural Network Enables Identification of Decadal State‐Dependent Predictability in CESM2
inferred← citeshttps://doi.org/10.1029/2022gl098663openalex-snapshot
Quantifying the Effect of Climate Change on Midlatitude Subseasonal Prediction Skill Provided by the Tropics
inferred← citeshttps://doi.org/10.1029/2022gl100727openalex-snapshot
Spring Regional Sea Surface Temperatures as a Precursor of European Summer Heatwaves
inferred← citeshttps://doi.org/10.1029/2022jd038365openalex-snapshot
Using Machine Learning With Partial Dependence Analysis to Investigate Coupling Between Soil Moisture and Near‐Surface Temperature
inferred← citeshttps://doi.org/10.1029/2022ms002995openalex-snapshot
Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States
inferred← citeshttps://doi.org/10.1029/2022ms003099openalex-snapshot
Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed
inferred← citeshttps://doi.org/10.1029/2022ms003162openalex-snapshot
Explainable Artificial Intelligence for Bayesian Neural Networks: Toward Trustworthy Predictions of Ocean Dynamics
inferred← citeshttps://doi.org/10.1029/2022ms003370openalex-snapshot
Machine Learning‐Derived Inference of the Meridional Overturning Circulation From Satellite‐Observable Variables in an Ocean State Estimate
inferred← citeshttps://doi.org/10.1029/2022ms003475openalex-snapshot
Detection and Attribution of Climate Change Using a Neural Network
inferred← citeshttps://doi.org/10.1029/2023ef003981openalex-snapshot
Changes in United States Summer Temperatures Revealed by Explainable Neural Networks
inferred← citeshttps://doi.org/10.1029/2023gc011018openalex-snapshot
Does Zircon Shape Retain Petrogenetic Information?
inferred← citeshttps://doi.org/10.1029/2023gl106137openalex-snapshot
Using Explainable Artificial Intelligence to Quantify “Climate Distinguishability” After Stratospheric Aerosol Injection
inferred← citeshttps://doi.org/10.1029/2023gl106278openalex-snapshot
Physical Insights From the Multidecadal Prediction of North Atlantic Sea Surface Temperature Variability Using Explainable Neural Networks
inferred← citeshttps://doi.org/10.1029/2023gl108099openalex-snapshot
Combining Neural Networks and CMIP6 Simulations to Learn Windows of Opportunity for Skillful Prediction of Multiyear Sea Surface Temperature Variability
inferred← citeshttps://doi.org/10.1029/2023jc019851openalex-snapshot
The Rossby Normal Mode as a Physical Linkage in a Machine Learning Forecast Model for the SST and SSH of South China Sea Deep Basin
inferred← citeshttps://doi.org/10.1029/2023wr035009openalex-snapshot
Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains
inferred← citeshttps://doi.org/10.1029/2023wr035088openalex-snapshot
Intercomparison of Deep Learning Architectures for the Prediction of Precipitation Fields With a Focus on Extremes
inferred← citeshttps://doi.org/10.1029/2023wr036297openalex-snapshot
Viewing Soil Moisture Flash Drought Onset Mechanism and Their Changes Through XAI Lens: A Case Study in Eastern China
inferred← citeshttps://doi.org/10.1029/2024ef004540openalex-snapshot
How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences
inferred← citeshttps://doi.org/10.1029/2024gl108479openalex-snapshot
Exploring the Relative Importance of the MJO and ENSO to North Pacific Subseasonal Predictability
inferred← citeshttps://doi.org/10.1029/2024gl110651openalex-snapshot
Predictability Limit of the 2021 Pacific Northwest Heatwave From Deep‐Learning Sensitivity Analysis
inferred← citeshttps://doi.org/10.1029/2024gl112118openalex-snapshot
An Interpretable Deep Inference Model With Dynamic Constraints for Forecasting the Evolution of Sea Surface Variables in the South China Sea
inferred← citeshttps://doi.org/10.1029/2024gl114136openalex-snapshot
On the Importance of Learning Non‐Local Dynamics for Stable Data‐Driven Climate Modeling: A 1D Gravity Wave‐QBO Testbed
inferred← citeshttps://doi.org/10.1029/2024gl114428openalex-snapshot
Uncovering Deformation Prior to Analogue Megathrust Earthquakes With Explainable Artificial Intelligence
inferred← citeshttps://doi.org/10.1029/2024jb028774openalex-snapshot
Testing Driving Mechanisms of Megathrust Seismicity With Explainable Artificial Intelligence
inferred← citeshttps://doi.org/10.1029/2024jd042147openalex-snapshot
Predicting Cloud‐To‐Ground Lightning in the Western United States From the Large‐Scale Environment Using Explainable Neural Networks
inferred← citeshttps://doi.org/10.1029/2024jg008610openalex-snapshot
A Neural Network‐Based Estimate of the Seasonal to Inter‐Annual Variability of the Lake Superior Carbon Cycle
inferred← citeshttps://doi.org/10.1029/2024jh000327openalex-snapshot
Exploring a Data‐Driven Approach to Identify Regions of Change Associated With Future Climate Scenarios
inferred← citeshttps://doi.org/10.1029/2024ms004262openalex-snapshot
Circumpolar Transport and Overturning Strength Inferred From Satellite Observables Using Deep Learning in an Eddying Southern Ocean Channel Model
inferred← citeshttps://doi.org/10.1029/2024ms004487openalex-snapshot
Gaussian Framework and Optimal Projection of Weather Fields for Prediction of Extreme Events
inferred← citeshttps://doi.org/10.1029/2024ms004915openalex-snapshot
Full‐Depth Reconstruction of Long‐Term Meridional Overturning Circulation Variability From Satellite‐Measurable Quantities via Machine Learning
inferred← citeshttps://doi.org/10.1029/2024wr039553openalex-snapshot
Foundation Models as Assistive Tools in Hydrometeorology: Opportunities, Challenges, and Perspectives
inferred← citeshttps://doi.org/10.1029/2025ea004331openalex-snapshot
Artificial Neural Network Model of High‐Latitude Ionospheric Electric Potential: Hemispheric and Equinoctial Asymmetries
inferred← citeshttps://doi.org/10.1029/2025ef006108openalex-snapshot
Projections of Lightning‐Ignited Wildfire Risk in the Western United States
inferred← citeshttps://doi.org/10.1029/2025jh000769openalex-snapshot
Leveraging Sparse Autoencoders to Reveal Interpretable Features in Geophysical Models
inferred← citeshttps://doi.org/10.1029/2025wr041753openalex-snapshot
Coupling Intuitive Physics Into Deep Learning for Soil Moisture Flow Processes Learning
inferred← citeshttps://doi.org/10.1029/2026gl123315openalex-snapshot
Uncertainty‐Aware Machine Learning for Onset of Deep Convection: Under what Conditions Are Trigger Predictions More Reliable?
inferred← citeshttps://doi.org/10.1029/2026gl123658openalex-snapshot
Diagnosing Optimal Forcing of the Western North Pacific Anomalous Anticyclone in a Deep‐Learning Model
inferred← citeshttps://doi.org/10.1029/2026gl123802openalex-snapshot
Physically Consistent Reconstruction of Sparse Scatterometer Ocean Surface Wind Fields Based on Physics‐Guided Generative Learning
inferred← citeshttps://doi.org/10.1029/2026jd046634openalex-snapshot
Predicting and Explaining Lightning and Lightning‐Ignited Wildfires in Northern California With a Two‐Step Convolutional Neural Network Framework
inferred← citeshttps://doi.org/10.1029/2026jd047324openalex-snapshot
Features of Regional Compound Dry‐Hot Events Over the Yangtze River Basin in Warm Season and Related Mechanisms
inferred← citeshttps://doi.org/10.1038/s41467-021-24262-xopenalex-snapshot
Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets
inferred← citeshttps://doi.org/10.1038/s41561-025-01639-xopenalex-snapshot
Explainability can foster trust in artificial intelligence in geoscience
inferred← citeshttps://doi.org/10.1038/s41598-022-12167-8openalex-snapshot
Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data
inferred← citeshttps://doi.org/10.1038/s41598-023-35963-2openalex-snapshot
Explainable sequence-to-sequence GRU neural network for pollution forecasting
inferred← citeshttps://doi.org/10.1038/s42256-021-00374-3openalex-snapshot
Towards neural Earth system modelling by integrating artificial intelligence in Earth system science
inferred← citeshttps://doi.org/10.1038/s42256-022-00540-1openalex-snapshot
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models
inferred← citeshttps://doi.org/10.1038/s43017-023-00450-9openalex-snapshot
Differentiable modelling to unify machine learning and physical models for geosciences
inferred← citeshttps://doi.org/10.1038/s43247-021-00225-4openalex-snapshot
Training machine learning models on climate model output yields skillful interpretable seasonal precipitation forecasts
inferred← citeshttps://doi.org/10.1038/s43247-023-00872-9openalex-snapshot
Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data
inferred← citeshttps://doi.org/10.1080/02626667.2025.2530124openalex-snapshot
Uncovering the underlying drivers of West African monsoon variability: towards the development of efficient rainfall monitoring systems
inferred← citeshttps://doi.org/10.1080/23754931.2025.2579650openalex-snapshot
Forecasting Extreme Heat Events in Arid Regions Using a Physics-Informed Hybrid Deep Learning Model
inferred← citeshttps://doi.org/10.1088/1361-6501/ad6a77openalex-snapshot
Prediction of the minimum miscibility pressure for CO2 flooding based on a physical information neural network algorithm
inferred← citeshttps://doi.org/10.1088/1572-9494/ace17dopenalex-snapshot
Unpacking the black box of deep learning for identifying El Niño-Southern oscillation
inferred← citeshttps://doi.org/10.1088/1748-9326/ac0eb0openalex-snapshot
Bridging observations, theory and numerical simulation of the ocean using machine learning
inferred← citeshttps://doi.org/10.1088/1748-9326/ac9d4eopenalex-snapshot
Machine learning applications for weather and climate need greater focus on extremes
inferred← citeshttps://doi.org/10.1088/1748-9326/acc81aopenalex-snapshot
Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations
inferred← citeshttps://doi.org/10.1088/1748-9326/acdbe0openalex-snapshot
Towards interpreting machine learning models for predicting soil moisture droughts
inferred← citeshttps://doi.org/10.1088/1748-9326/ad984aopenalex-snapshot
Regionally optimized fire parameterizations using feed-forward neural networks
inferred← citeshttps://doi.org/10.1088/1748-9326/ade606openalex-snapshot
Learning physically interpretable deep networks from reanalysis data for medium-term regional PM2.5 forecasts
inferred← citeshttps://doi.org/10.1088/2632-2153/ae9af0openalex-snapshot
Pure and physics-guided deep learning approaches for spatio-temporal groundwater level prediction
inferred← citeshttps://doi.org/10.1088/2752-5295/ac7f4copenalex-snapshot
Long-term ENSO prediction with echo-state networks
inferred← citeshttps://doi.org/10.1088/2752-5295/aced60openalex-snapshot
Assessing decadal variability of subseasonal forecasts of opportunity using explainable AI
inferred← citeshttps://doi.org/10.1088/2752-5295/ad9b43openalex-snapshot
Future seasonal surface temperature predictability with and without ARISE-stratospheric aerosol injection-1.5
inferred← citeshttps://doi.org/10.1088/3049-4753/ae1b07openalex-snapshot
A deep learning approach for exploring the physical mechanisms of an flood event
inferred← citeshttps://doi.org/10.1093/gji/ggac369openalex-snapshot
Interpreting convolutional neural network decision for earthquake detection with feature map visualization, backward optimization and layer-wise relevance propagation methods
inferred← citeshttps://doi.org/10.1093/petrology/egae036openalex-snapshot
Machine Learning in Petrology: State-of-the-Art and Future Perspectives
inferred← citeshttps://doi.org/10.1098/rsta.2020.0091openalex-snapshot
Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop
inferred← citeshttps://doi.org/10.1098/rsta.2020.0093openalex-snapshot
Physics-informed machine learning: case studies for weather and climate modelling
inferred← citeshttps://doi.org/10.1109/c2i659362.2023.10430879openalex-snapshot
A Comprehensive Study on Earth System Science using Machine Learning and Process Mining
inferred← citeshttps://doi.org/10.1109/eeiss65394.2025.11085425openalex-snapshot
Multi-Time Window Runoff Prediction Based on Multi-Head Attention Model for Domestic Watershed
inferred← citeshttps://doi.org/10.1109/iaict55358.2022.9887508openalex-snapshot
A Review of Neural Networks for Buildings Occupancy Measurement
inferred← citeshttps://doi.org/10.1109/icmla61862.2024.00044openalex-snapshot
Towards Physically Consistent Deep Learning For Climate Model Parameterizations
inferred← citeshttps://doi.org/10.1109/ishc54333.2021.00028openalex-snapshot
Research on Climate Prediction Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/jas.2023.123537openalex-snapshot
Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
inferred← citeshttps://doi.org/10.1109/jiot.2025.3536460openalex-snapshot
CLinear: An Interpretable Deep Time-Series Forecasting Model for Periodic Time Series
inferred← citeshttps://doi.org/10.1109/mgrs.2021.3071139openalex-snapshot
IEEE GRSS Malaysia Chapter: Report of Activities for 2018-2020 [Chapters]
inferred← citeshttps://doi.org/10.1109/mgrs.2021.3078373openalex-snapshot
A Special Issue on Recent Progress in Developing Artificial Intelligence and Machine Learning Methodologies [From the Guest Editors]
inferred← citeshttps://doi.org/10.1109/mgrs.2024.3496478openalex-snapshot
When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system
inferred← citeshttps://doi.org/10.1109/tcyb.2025.3539990openalex-snapshot
Deep Learning for Ocean Forecasting: A Comprehensive Review of Methods, Applications, and Datasets
inferred← citeshttps://doi.org/10.1109/tgrs.2024.3386930openalex-snapshot
An Explainable Deep Learning Model for Daily Sea Ice Concentration Forecast
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