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  • Posts
    • New Paper Published: Tim Higgins Leads Study Generating a 1,000-Member Diffusion Ensemble for Atmospheric River Forecasting
    • Aneesh Subramanian Co-Directs FERS Summer School on AI and Machine Learning for Earth System Modeling
    • Congratulations Dr. Ziqi Yin! Successful PhD Defense on Greenland Ice Sheet Surface Melt
    • Dr. Timothy Higgins Launches Operational AI-Based Ensemble Forecasting System for West Coast Atmospheric Rivers
    • Applications Open: FERS Summer School on AI and Machine Learning for Earth System Modeling and Prediction
    • Luke Howard Defends His PhD Thesis
    • Aneesh Subramanian Recognized as an Exceptional Graduate Faculty Mentor
  • Publications
    • Generating a 1000-Member Ensemble of Integrated Water Vapor Transport Forecasts with Diffusion
    • Identifying Energy Balance Drivers of Greenland Ice Sheet Surface Melt Using Causal Discovery
    • Persistent SST anomaly vs. dynamical ocean model in winter weather forecasts: Global Ensemble Prediction System versions 5 and 6 over the North Pacific and North Atlantic
    • Sensitivity of the 2023 Asian Summer Monsoon Water Vapor Transport to Arabian Sea Surface Temperature Anomalies
    • Data‐Driven Probabilistic Air‐Sea Flux Parameterization
    • Skillful subseasonal Indian Ocean marine heatwave forecasts using a neural network
    • Physics-Based Versus AI Weather Prediction Models: A Comparative Performance Assessment of Atmospheric River Prediction
    • Marine Heatwaves in the Arabian Sea: Drivers and Impacts on Atmospheric Circulation and Extreme Precipitation
    • Modulation of tropical cyclone intensity by current–wind interaction
    • Salinity-Driven Barrier Layer Dynamics in the Equatorial Pacific: An Observational and CMIP6 Analysis
    • Adaptive Sampling of the Upper Ocean by Autonomous Floats During Atmospheric River Precipitation
    • Subsurface marine heat waves and coral bleaching in the southern red sea linked to remote forcing
    • Toward an integrated pantropical ocean observing system
    • Building Machine Learning Challenges for Anomaly Detection in Science
    • Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift
    • Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction
    • Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction
    • Earth, Wind, and Fire: Are Boulder’s Extreme Downslope Winds Changing?
    • Engaging K-12 Learners in Data Annotation for AI Climate Models
    • Evaluating a Hybrid Ensemble Data Assimilative coupled Physical-Biogeochemical Ecosystem Model of the Red Sea
    • Koopman operator theory for enhanced Pacific SST forecasting
    • New Climate Change Center of Saudi Arabia: Advancing Understanding and Prediction for the Arabian Peninsula Climate
    • The fate of Greenland Ice Sheet supraglacial lakes in a warm and cool year
    • Enhanced regional ocean ensemble data assimilation through atmospheric coupling in the SKRIPS model
    • Subseasonal Potential Predictability of Horizontal Water Vapor Transport and Precipitation Extremes in the North Pacific
    • Causal Analysis Discovers an Enhanced Impact of Tropical Western Pacific on Indian Summer Monsoon Subseasonal Anomalies
    • Advancing Atmospheric River Science and Inspiring Future Development of the Atmospheric River Reconnaissance Program
    • Enhanced Regional Ocean Ensemble Data Assimilation Through Atmospheric Coupling in the SKRIPS Model
    • Greenland Ice Sheet wide supraglacial lake evolution and dynamics: insights from the 2018 and 2019 melt seasons
    • Impact of atmospheric rivers on Arctic sea ice variations
    • Time Series Classification of Supraglacial Lakes Evolution over Greenland Ice Sheet
    • Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling: A Summary of Results
    • Increase in MJO predictability under global warming
    • Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework
    • Balancing Volume, Temperature, and Salinity Budgets During 2014–2018 in the Tropical Pacific Ocean State Estimate
    • A Machine Learning Augmented Data Assimilation Method for High-Resolution Observation
    • A variational Bayesian approach for ensemble filtering of stochastically parametrized systems
    • Assessing the Impact of Ocean In Situ Observations on MJO Propagation Across the Maritime Continent in ECMWF Subseasonal Forecasts
    • Development of a Statistical Subseasonal Forecast Tool to Predict California Atmospheric Rivers and Precipitation Based on MJO and QBO Activity
    • Eddy-Mediated Mixing of Oxygen in the Equatorial Pacific
    • Impacts of Northeastern Pacific Buoy Surface Pressure Observations
    • Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated With Atmospheric Rivers Over the Western US
    • Observed and projected changes in snow accumulation and snowline in California's snowy mountains
    • Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference
    • Quantifying Causes of Arctic Amplification via Deep Learning Based Time-Series Causal Inference
    • Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach
    • Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-Variability-Aware Approach
    • Signals of northward propagating monsoon intraseasonal oscillations (MISOs) in the RegCM4.7 CORDEX-CORE simulation over South Asia domain
    • STint: Self-supervised Temporal Interpolation for Geospatial Data
    • Subseasonal prediction of impactful California weather in a hybrid dynamical-statistical framework
    • Subseasonal prediction of impactful California weather in a hybrid dynamical-statistical framework
    • Using Deep Learning for an Analysis of Atmospheric Rivers in a High-Resolution Large Ensemble Climate Data Set
    • Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
    • Atmospheric River Reconnaissance 2021: A Review
    • Annual Modulation of Diurnal Winds in the Tropical Oceans
    • Atmospheric River Reconnaissance Workshop Promotes Research and Operations Partnership
    • Focused Observations for Expanded Comprehension: Advancing Tropical Pacific Coupled Modeling and Process Understanding
    • Focusing and Defocusing of Tropical Cyclone Generated Waves by Ocean Current Refraction
    • Insights into the quantification and reporting of model-related uncertainty across different disciplines
    • Overcoming the Challenges of Ocean Data Uncertainty
    • Probabilistic Predictions from Deterministic Atmospheric River Forecasts with Deep Learning
    • Weakening of Indian Summer Monsoon Synoptic Activity in Response to Polar Sea Ice Melt Induced by Albedo Reduction in a Climate Model
    • Winter wet-dry weather patterns driving atmospheric rivers and Santa Ana winds provide evidence for increasing wildfire hazard in California
    • Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset
    • Data Gaps within Atmospheric Rivers over the Northeastern Pacific
    • Enhancing ensemble data assimilation into one-way-coupled models with one-step-ahead smoothing
    • Improved Forecast Skill Through the Assimilation of Dropsonde Observations From the Atmospheric River Reconnaissance Program
    • Initialized Earth System prediction from subseasonal to decadal timescales
    • Monthly Modulations of ENSO Teleconnections: Implications for Potential Predictability in North America
    • The Role of Air-Sea Interactions in Atmospheric Rivers: Case Studies Using the SKRIPS Regional Coupled Model
    • Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea
    • Towards implementing artificial intelligence post-processing in weather and climate: proposed actions from the Oxford 2019 workshop
    • Tropical Pacific Air-Sea Interaction Processes and Biases in CESM2 and Their Relation to El Nino Development
    • Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6)
    • A Road Map to IndOOS-2: Better Observations of the Rapidly Warming Indian Ocean
    • A Reliability Budget Analysis of CESM-DART
    • Estimation and prediction of the upper ocean circulation in the Bay of Bengal
    • Forecast Errors and Uncertainties in Atmospheric Rivers
    • Four Atmospheric Circulation Regimes Over the North Pacific and Their Relationship to California Precipitation on Daily to Seasonal Timescales
    • How Does El Nino-Southern Oscillation Change Under Global Warming-A First Look at CMIP6
    • Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz `96 Model
    • Seasonal-to-interannual prediction of North American coastal marine ecosystems: Forecast methods, mechanisms of predictability, and priority developments
    • Tropical climate variability in the Community Earth System Model: Data Assimilation Research Testbed
    • West Coast Forecast Challenges and Development of Atmospheric River Reconnaissance
    • Improving Atmospheric River Forecasts With Machine Learning
    • A Sustained Ocean Observing System in the Indian Ocean for Climate Related Scientific Knowledge and Societal Needs
    • A Limited Role for Unforced Internal Variability in Twentieth-Century Warming
    • A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development
    • Composite physical-biological El Nino and La Nina conditions in the California Current System in CESM1-POP2-BEC
    • Contributors
    • Coupled effects of ocean current on wind stress in the Bay of Bengal: Eddy energetics and upper ocean stratification
    • El Nino-Like Physical and Biogeochemical Ocean Response to Tropical Eruptions
    • ENSO Bimodality and Extremes
    • Experimental Subseasonal-to-Seasonal (S2S) Forecasting of Atmospheric Rivers Over the Western United States
    • Integrated Observations of Global Surface Winds, Currents, and Waves: Requirements and Challenges for the Next Decade
    • Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction
    • Observational Needs Supporting Marine Ecosystems Modeling and Forecasting: From the Global Ocean to Regional and Coastal Systems
    • Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability
    • Predictability of US West Coast Ocean Temperatures is not solely due to ENSO
    • Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study
    • SKRIPS v1.0: a regional coupled ocean-atmosphere modeling framework (MITgcm-WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea
    • The Risks of Contracting the Acquisition and Processing of the Nation’s Weather and Climate Data to the Private Sector
    • Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design
    • Circulation Drivers of Atmospheric Rivers at the North American West Coast
    • Improving Weather Forecast Skill through Reduced-Precision Data Assimilation
    • Sensitivity Studies of the Red Sea Eddies Using Adjoint Method
    • Sensitivity Studies of the Red Sea Eddies Using Adjoint Method
    • Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin
    • Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin
    • Supplementary material to “Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design”
    • The Risks of Contracting the Acquisition and Processing of the Nation's Weather and Climate Data to the Private Sector (vol 99, pg 869, 2018)
    • GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations
    • A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS model
    • Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model
    • Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction
    • Impact of stochastic physics on tropical precipitation in the coupled ECMWF model
    • Maintaining Momentum in Climate Model Development
    • Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model
    • Stochastic representations of model uncertainties at ECMWF: state of the art and future vision
    • The role of wind gusts in upper ocean diurnal variability
    • Simulation of High-Resolution Precipitable Water Data by a Stochastic Model with a Random Trigger
    • The eddy kinetic energy budget in the Red Sea
    • The physical oceanographic environment during the CCE-LTER Years: Changes in climate and concepts
    • The skill of atmospheric linear inverse models in hindcasting the Madden-Julian Oscillation
    • Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden-Julian Oscillation
    • Diagnosing MJO hindcast biases in NCAR CAM3 using nudging during the DYNAMO field campaign
    • Eddies in the Red Sea: A statistical and dynamical study
    • The MJO and global warming: a study in CCSM4
    • A data assimilative perspective of oceanic mesoscale eddy evolution during VOCALS-REx
    • An Adjoint-Based Adaptive Ensemble Kalman Filter
    • Linear versus Nonlinear Filtering with Scale-Selective Corrections for Balanced Dynamics in a Simple Atmospheric Model
    • The Madden-Julian Oscillation in CCSM4
    • An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter
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Generating a 1000-Member Ensemble of Integrated Water Vapor Transport Forecasts with Diffusion

July 1, 2026·
Timothy B. Higgins
,
William E. Chapman
,
Aneesh C. Subramanian
,
Luca Delle Monache
· 0 min read
URL DOI
publication
Last updated on July 1, 2026
Identifying Energy Balance Drivers of Greenland Ice Sheet Surface Melt Using Causal Discovery May 30, 2026 →

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