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Full Workshop Agenda, (PDF, 197 KB)

AI 2020 Presentations Index
Title Presenter / Affiliation Session
Information on the 2nd NOAA AI Workshop: Logistics, Timeline and Structure, (PPTX, 8.33 MB) Kevin Garrett - NOAA/NESDIS/STAR, Local Organizing Committee Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Welcoming remarks and introduction of keynote speakers Harry Cikanek - NOAA/NESDIS, STAR Director Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Keynote Address, NOAA AI: Realizing Transformational Advances in Mission Performance and Our Culture of Innovation RADM Timothy Gallaudet - NOAA, Deputy NOAA Administrator Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Keynote Address Stephen Volz - NOAA, NESDIS Assistant Administrator Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Keynote Address, (PDF, 2.49 MB) Nicole LeBoeuf - NOAA, NOS Acting Assistant Administrator Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
NOAA AI Implementation Plan, (PPTX, 40.97 MB) Bill Michaels - NOAA, NMFS Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Efforts in NOAA to Leverage Modern AI techniques for Satellite Data Exploitation and NWP, (PPTX, 169.55 MB) Sid Boukabara - NOAA/NESDIS, STAR Principal Scientist Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Machine Learning at ECMWF, (PPTX, 15.98 MB) Peter Dueben - ECMWF Session 1: Overview Talks, Part 1,
Thursday, 30 July 2020
Data Science and Machine Learning at the UK Met Office, (PPTX, 23.94 MB) Samantha Adams - UKMO Session 2: Fundamentals of AI, Part 1
Chairs: Dave Turner (NOAA. ESRL), Jebb Stewart (NOAA, ESRL),
Thursday, 6 August 2020
Recent Machine Learning Research at NCAR, (PPTX, 39.84 MB) Sue Ellen Haupt - NCAR Session 2: Fundamentals of AI, Part 1
Chairs: Dave Turner (NOAA. ESRL), Jebb Stewart (NOAA, ESRL),
Thursday, 6 August 2020
Data-driven (super-) parametrization using deep learning: Experimentation with a multi-scale Lorenz 96 system and transfer learning, (PPTX, 5.68 MB) Ashesh Chattopadhyay - Rice U. Session 2: Fundamentals of AI, Part 1
Chairs: Dave Turner (NOAA. ESRL), Jebb Stewart (NOAA, ESRL),
Thursday, 6 August 2020
NOAA Center for AI (NCAI) Introduction, (PPTX, 60.95 MB) Bill Michaels - AI S&T Chair, Mary Wohlgemuth - NCEI Director, Eric Kihn - NCEI CCOG Director, Rob Redmon - NCAI Acting Director, LCDP XI Session 3: Looking Ahead (Using AI for NOAA mission), Part 1
Chairs: Bill Michaels (NOAA, NMFS), John Ten Hoeve (Office of Organizational Excellence),
Thursday, 13 August 2020
Artificial Intelligence for Advanced Earth Science Information Systems Jacqueline Le Moigne - NASA Session 4: AI/ML for Post-Processing and Data dissemination, Part 1
Chairs: Greg Dusek (NOAA/NOS), Andre van der Westhuysen (IMSG at NWS/NCEP/EMC),
Thursday, 20 August 2020
Using Random Forests to Create Probabilistic Next-Day Severe Weather Guidance from NWP Ensembles, (PPTX, 112.77 MB) Eric Loken - OU CIMMS/OU Session 4: AI/ML for Post-Processing and Data dissemination, Part 1
Chairs: Greg Dusek (NOAA/NOS), Andre van der Westhuysen (IMSG at NWS/NCEP/EMC),
Thursday, 20 August 2020
Modeling Clouds From Sub-grid to Global Scales with Deep Generative Models Tianle Yuan - NASA GSFC/UMBC JCET Session 4: AI/ML for Post-Processing and Data dissemination, Part 1
Chairs: Greg Dusek (NOAA/NOS), Andre van der Westhuysen (IMSG at NWS/NCEP/EMC),
Thursday, 20 August 2020
Combining data assimilation and machine learning for weather forecasting, (PPTX, 8.67 MB) Alan Geer - ECMWF Session 5: AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD) ,
Thursday, 27 August 2020
Viewing Climate Signals through an AI Lens, (PDF, 5.59 MB) Elizabeth Barnes - CSU Session 5: AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD) ,
Thursday, 27 August 2020
Video and Image Analytics for Marine Environments (VIAME), a Do-it-yourself AI Toolkit, (PDF, 5.62 MB) Matthew Dawkins - Kitware Inc Session 5: AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD),
Thursday, 27 August 2020
Generating High Temporal and Spatial Microwave Hurricane Image Products Using Artificial intelligence and Machine Learning Technique, (PDF, 4.09 MB) Likun Wang - RTi at NESDIS/STAR Session 5: AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD),
Thursday, 27 August 2020
AI Quality Control of NOAA Tide Gauge Observations, (PPTX, 3.45 MB) Gregory Dusek - NOAA/NOS Session 6: AI/ML for Information Extraction from Data, Part 1
Chairs: Philippe Tissot (Texas A&M University, Corpus Christi), Jebb Stewart (NOAA, ESRL),
Thursday, 3 September 2020
Artificial Intelligence and Deep Machine learning for Passive Acoustic Monitoring at NOAA Fisheries, (PPTX, 16.67 MB) Ann Allen, Manuel Castellote, Shannon Rankin - NOAA/NMFS/PIFSC, NOAA/NMFS/AFSC, NOAA/NMFS/SWFSC Session 6: AI/ML for Information Extraction from Data, Part 1
Chairs: Philippe Tissot (Texas A&M University, Corpus Christi), Jebb Stewart (NOAA, ESRL),
Thursday, 3 September 2020
Trustworthy AI for High Impact Weather Prediction, (PPTX, 24.81 MB) Amy McGovern - OU Session 7: Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA),
Thursday, 10 September 2020
Machine Learning for Model Error Inference and Correction, (PDF, 1.96 MB) Massimo Bonavita - ECMWF Session 7: Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA),
Thursday, 10 September 2020
Ensemble Oscillation Correction (EnOC): Leveraging oscillatory modes to improve forecasts of chaotic systems, (PDF, 1.15 MB) Eviatar Bach - UMD Session 7: Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA),
Thursday, 10 September 2020
Cost Sensitive Loss Function for Machine Learning, (PPTX, 1.24 MB) Richard Berk - U. Penn Session 7: Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA),
Thursday, 10 September 2020
Which strategies did my neural network learn?, (PPTX, 127.71 MB) Imme Ebert-Uphoff - CIRA Session 8: Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google),
Thursday, 17 September 2020
ClimateNet: an expert-labelled open dataset and Deep Learning architecture for enabling high-precision analyses of extreme weather, (PPTX, 121.37 MB) Karthik Kashinath - Lawrence Berkeley National Lab Session 8: Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google),
Thursday, 17 September 2020
The AI for Earth System Science Hackathon: Challenge Problems and Lessons Learned, (PPTX, 26.42 MB) David Gagne - NCAR Session 8: Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google),
Thursday, 17 September 2020
"AI for Science" program at Argonne NL, (PPTX, 21.65 MB) Ian Foster - ANL Session 8: Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google),
Thursday, 17 September 2020
The role of machine learning in a seamless modeling approach from weather to climate time scales, (PDF, 13.06 MB) V. Balaji - NOAA/GFDL Session 10: AI/ML for Post-Processing and Data dissemination, Part 2
Chairs: Nikunj Oza (NASA), Allen Huang (UW-Madison),
Thursday, 24 September 2020
Elucidating Ecological Complexity: Unsupervised Learning determines global marine eco-provinces, (PDF, 51.24 MB) Maike Sonnewald - NOAA/GFDL Session 10: AI/ML for Post-Processing and Data dissemination, Part 2
Chairs: Nikunj Oza (NASA), Allen Huang (UW-Madison),
Thursday, 24 September 2020
Accelerating Google's Flood Forecasting Initiative with Tensor Processing Units, (PDF, 4.26 MB) Vova Anisimov, Anudhyan Boral, Lily Hu, Sella Nevo, Damien Pierce, Yusef Shafi Session 10: AI/ML for Post-Processing and Data dissemination, Part 2
Chairs: Nikunj Oza (NASA), Allen Huang (UW-Madison),
Thursday, 24 September 2020
Modelling runoff from green roofs using Deep Neural Networks, (PDF, 1.02 MB) Elhadi Abdalla - NTNU Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Fine-Delineated Tropical Cyclone Detection from Geostationary Satellites and IBTrACS data using Advanced Neural Networks, (PDF, 26.2 MB) Ata Akbari Asanjan - Universities Space Research Association Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Pixel-wise Deep Sequence learning for wildfire spread prediction in Alberta, Canada, (PDF, 2.08 MB) Xinli Cai - University of Alberta Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Using deep super-resolution for high resolution precipitation images, (PDF, 5.76 MB) Xinli Cai - University of Alberta Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Lightning prediction in the Atlantic offshore region, (PDF, 1.01 MB) John Cintineo - University of Wisconsin -- Madison Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Connecting ocean physical and biogeochemical properties with the spatial distribution of mesopelagic fish abundance, (PDF, 3.85 MB) Donglai Gong - Virginia Institute of Marine Science - William & Mary Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Using Data Mining Decision Tree Method to Identify the Optimal Fire Detection Thresholds, (PDF, 876 KB) Yingxin Gu - IMSG at NOAA/NESDIS/STAR Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Application of Advanced Deep Learning Algorithms in Precipitation Estimation from Multiple Sources of Information, (PDF, 11.3 MB) Negin Hayatbini - University of California, Irvine Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Low Cloud Detection for the GOES ABI using a Random Forest Classifier, (PDF, 15.65 MB) John Haynes - CIRA / Colorado State University Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
3D Convolutional Deep Learning for Coastal Fog Predictions, (PDF, 1.68 MB) Hamid Kamangir - Texas A&M University-Corpus Christi Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Verification of a Machine Learning Algorithm in the Prediction of Flash Flooding, (PDF, 2.61 MB) Mark Klein - NWS/Weather Prediction Center Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Utilizing CNN's to produce Quantitative Precipitation Estimates, (PDF, 2.09 MB) Micheal Simpson - University of Oklahoma Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: application to Himawari-8, (PDF, 4.6 MB) Tianning Su - UMD Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR),
Tuesday, 29 September 2020
First steps toward a machine-learning based moist physics parameterization by coarse-graining, (PDF, 18.54 MB) Jeremy McGibbon - Vulcan Session 12: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD) ,
Thursday, 1 October 2020
Operational In-Field Forecasting using Online Sequential Extreme Learning Machines, (PPTX, 25.75 MB) Carlos Gaitan - Benchmark Labs Session 12: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD) ,
Thursday, 1 October 2020
Representing Aerosol-Cloud Interactions Using Machine Learning Techniques in Energy Exascale Earth System Model, (PDF, 15.13 MB) Po-Lun Ma - PNNL Session 12: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD) ,
Thursday, 1 October 2020
Robustness of NN Emulations of Radiative Transfer Parameterizations in a State-of-the-Art GCM, (PPTX, 105.85 MB) Alex Belochitski - IMSG at NOAA/NCEP/EMC Session 12: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD) ,
Thursday, 1 October 2020
Overview of AI activities at IBM Weather, (PPTX, 45.58 MB) John Williams - IBM Weather Session 13: AI/ML for Data Fusion/Assimilation, Part 1
Chairs: Peter Jan van Leeuwen (CSU), Steve Penny (NOAA PSD/CIRES),
Thursday, 15 October 2020
Overview of AI activities at Google, (PPTX, 79.38 MB) Jason Hickey - Google Session 13: AI/ML for Data Fusion/Assimilation, Part 1
Chairs: Peter Jan van Leeuwen (CSU), Steve Penny (NOAA PSD/CIRES),
Thursday, 15 October 2020
Automated Analysis of Satellite Imagery in Support of Severe Weather Nowcasting, (PPTX, 195.04 MB) Michael Pavolonis - NOAA/NESDIS/STAR Session 13: AI/ML for Data Fusion/Assimilation, Part 1
Chairs: Peter Jan van Leeuwen (CSU), Steve Penny (NOAA PSD/CIRES),
Thursday, 15 October 2020
Neural Networks for Postprocessing Ensemble Weather Forecasts, (PDF, 1.03 MB) Sebastian Lerch - KIT Session 15: AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan),
Thursday, 22 October 2020
What is 'AI-Ready' Open Data?, (PDF, 364 KB) Tyler Christensen - NOAA/NOS/IMO Session 15: AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan),
Thursday, 22 October 2020
Improving Passive Acoustic Monitoring Applications to the Endangered Cook Inlet Beluga Whale, (PPTX, 7.55 MB) Ming Zhong - Microsoft Session 15: AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan),
Thursday, 22 October 2020
Leveraging NWP for Operational Machine Learning Predictions for Coastal and Environmental Stakeholders, (PPTX, 16.87 MB) Philippe Tissot - Texas A&M University, Corpus Christi Session 15: AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan),
Thursday, 22 October 2020
AI and Clouds at Microsoft, (PPTX, 1.26 MB) Justin Worrilow - Microsoft Session 16: AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL) ,
Thursday, 29 October 2020
Improving CFS Precipitation and 2m Temperature Anomaly Outlooks from Week-1 to Week-6 with Machine Learning, (PPTX, 3.03 MB) Yun Fan - NCEP/CPC Session 16: AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL) ,
Thursday, 29 October 2020
Shifting to AI for Passive Acoustic Monitoring of the Endangered Cook Inlet Beluga Whale, (PPTX, 8.7 MB) Manuel Castellote - NOAA AFSC and UW Session 16: AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL) ,
Thursday, 29 October 2020
Precipitation forecasting through NWP correction considering the Korean Peninsula terrain, (PPTX, 17.56 MB) Se-Young Yun - KAIST Session 16: AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL) ,
Thursday, 29 October 2020
NIMS R&D strategy for Alpha Weather, (PPTX, 19.22 MB) Hyesook Lee - KMA Session 17: AI/ML for Post-Processing and Data dissemination, Part 4
Chairs: Andre van der Westhuysen (IMSG at NWS/NCEP/EMC), William Collins (LBNL, UC Berkeley),
Thursday, 5 November 2020
ML for post processing model output at EMC, (PPTX, 4.55 MB) Vladimir Krasnopolsky - NOAA/NCEP/EMC Session 17: AI/ML for Post-Processing and Data dissemination, Part 4
Chairs: Andre van der Westhuysen (IMSG at NWS/NCEP/EMC), William Collins (LBNL, UC Berkeley),
Thursday, 5 November 2020
Applying satellite observations of tropical cyclone internal structures to rapid intensification forecast with machine learning, (PPTX, 10.27 MB) Hui Su - JPL/Caltech Session 17: AI/ML for Post-Processing and Data dissemination, Part 4
Chairs: Andre van der Westhuysen (IMSG at NWS/NCEP/EMC), William Collins (LBNL, UC Berkeley),
Thursday, 5 November 2020
A Practical Introduction to Deep Learning for the Earth System Sciences using PyTorch, (PDF, 57.66 MB) David Hall - NVIDIA Session 18: Tutorial 3,
Tuesday, 10 November 2020
Machine learning for detection of climate extremes: New approaches to uncertainty quantification, (PDF, 53.35 MB) William Collins - LBNL, UC Berkeley Session 19: AI/ML for Environmental Data, Image, and Signal Processing, Part 2
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD),
Thursday, 12 November 2020
Analysis of Multispectral Land Surface Reflectance Time-Series for Detecting and Classifying Land Cover Change, (PDF, 1.21 MB) Srija Chakraborty - NASA GSFC/ USRA Session 19: AI/ML for Environmental Data, Image, and Signal Processing, Part 2
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD),
Thursday, 12 November 2020
Super-Resolution of VIIRS-Measured Ocean Color Products Using Deep Convolutional Neural Network, (PDF, 5.14 MB) Xiaoming Liu - NOAA/NESDIS/STAR Session 19: AI/ML for Environmental Data, Image, and Signal Processing, Part 2
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD),
Thursday, 12 November 2020
Exploring the Frontiers of Deep Learning for Earth and Space, (PPTX, 183.75 MB) David Hall - NVIDIA Session 20: Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi),
Thursday, 19 November 2020
Accelerating biodiversity surveys with computer vision: successes and challenges, (PPTX, 37.81 MB) Dan Morris - Microsoft AI for Earth Session 20: Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi),
Thursday, 19 November 2020
Counting Belugas from Space: Can we use very high resolution satellite imagery to accurately assess the critically endangered beluga whale population in Cook Inlet, Alaska?, (PPTX, 30.31 MB) Kimberly Goetz - NOAA/NMFS/AFSC/MML Session 20: Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi),
Thursday, 19 November 2020
Tackling challenges of Ocean Exploration with Machine Learning and Artificial Intelligence, (PPTX, 23.65 MB) Matt Dornback - NOAA/OAR/OER Session 20: Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi),
Thursday, 19 November 2020
Using Neural Networks as Model Physics Components in Numerical Weather Prediction, (PPTX, 9.04 MB) Vladimir Krasnopolsky - NOAA/NCEP/EMC Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University),
Thursday, 3 December 2020
Challenges associated with training a machine-learning based moist physics parameterization by coarse-graining in a model with topography, (PPTX, 14.24 MB) Spencer Clark - Vulcan, Inc./NOAA GFDL Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University),
Thursday, 3 December 2020
Exploring Various Machine Learning Techniques for Emulating Simplified Physical Parameterizations in the Community Atmosphere Model, (PPTX, 20.15 MB) Garrett Limon - University of Michigan Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University),
Thursday, 3 December 2020
Predicting Algal Bloom Toxicity in Lake Erie: Lessons From Machine Learning, (PPTX, 14.4 MB) Theodore A.D. Slawecki - LimnoTech Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University),
Thursday, 3 December 2020
Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions Janni Yuval - MIT Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University),
Thursday, 3 December 2020
Cloud classification with unsupervised deep learning, (PDF, 2.04 MB) Takuya Kurihana - University of Chicago Session 23: Poster Session II,
Tuesday, 15 December 2020
Convection Classification in a Future Climate: What did Deep Learning Really Learn?, (PDF, 7.64 MB) Maria Molina - National Center for Atmospheric Research Session 23: Poster Session II,
Tuesday, 15 December 2020
Engaging Freshmen Undergraduates in AI on Cloud Imagery and Model Output, (PDF, 1.06 MB) Alexandra Jones - UMD Session 23: Poster Session II,
Tuesday, 15 December 2020
Preparing for the Future: Development of an Open-Source Workflow for AI driven Acoustic Data Analysis, (PDF, 670 KB) Shannon Rankin - Southwest Fisheries Science Center, NMFS Session 23: Poster Session II,
Tuesday, 15 December 2020
AI in the US Inland Waterways industry, (PDF, 4.43 MB) David Sathiaraj - Trabus Technologies Session 23: Poster Session II,
Tuesday, 15 December 2020
Online bias correction of weather models using machine learning, (PDF, 1.98 MB) Oliver Watt-Meyer - Vulcan, Inc. Session 23: Poster Session II,
Tuesday, 15 December 2020
Automatic Extraction of Internal Wave Signature from Multiple Satellite Sensors based on Deep Convolutional Neural Networks, (PDF, 9.53 MB) Shuangshang Zhang - University of Maryland Eastern Shore Session 23: Poster Session II,
Tuesday, 15 December 2020
Development of machine learning based downscaling methods for wildfire risk, (PDF, 1.37 MB) Rackhun Son - Gwangju Institute of Science and Technology Session 23: Poster Session II,
Tuesday, 15 December 2020
Combining spatio-temporal weather and crop data for network-based inference on the international wheat trade, (PDF, 1.62 MB) Srishti Vishwakarma - University of Maryland Center for Environmental Science Appalachian Laboratory Session 23: Poster Session II,
Tuesday, 15 December 2020
MLOps platforms to address the complexities of delivering a ML/AI product, (PDF, 1.13 MB) Pamela Perez - GAMA-1 Technologies Session 23: Poster Session II,
Tuesday, 15 December 2020
Unlocking GOES: A Statistical Framework for Quantifying the Evolution of Convective Structure in Tropical Cyclones, (PDF, 1.62 MB) Trey McNeely - Carnegie Mellon University Session 23: Poster Session II,
Tuesday, 15 December 2020
A Deep Learning Approach for Intelligent Thinning of Satellite Data, (PDF, 11.46 MB) Sarvesh Garimella - ACME AtronOmatic Session 24: AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR) ,
Thursday, 17 December 2020
Automation-assisted segmentation to expedite 3D coral mapping, (PPTX, 509.34 MB) Hugh Runyan - SIO/UCSD Session 24: AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR) ,
Thursday, 17 December 2020
A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology, (PPTX, 18.32 MB) Mark Veillette - MIT Lincoln Laboratory Session 24: AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR) ,
Thursday, 17 December 2020
Precipitation downscaling using conditional super-resolution based deep neural network., (PPTX, 13.69 MB) Jiali Wang - Argonne National Laboratory Session 24: AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR) ,
Thursday, 17 December 2020
Using Deep Learning to Generate Synthetic Radar Fields from GOES ABI and GLM, (PPTX, 96.16 MB) Kyle Hilburn - CIRA/CSU Session 25: AI/ML for Data Fusion/Assimilation, Part 2
Chairs: Steve Penny (NOAA PSD/CIRES), Kayo Ide (UMD),
Thursday, 7 January 2021
Deep Multi-Sensor Domain Adaptation on Active and Passive Satellite Remote Sensing Data, (PDF, 3.56 MB) Sanjay Purushotham - UMBC Session 25: AI/ML for Data Fusion/Assimilation, Part 2
Chairs: Steve Penny (NOAA PSD/CIRES), Kayo Ide (UMD),
Thursday, 7 January 2021
A satellite-station blended daily surface air temperature dataset for the Tibetan Plateau, (PDF, 8.41 MB) Yuhan (Douglas) Rao - CISESS/NCICS/NCSU Session 25: AI/ML for Data Fusion/Assimilation, Part 2
Chairs: Steve Penny (NOAA PSD/CIRES), Kayo Ide (UMD),
Thursday, 7 January 2021
Retrieving Chlorophyll concentration from GOES-16 ABI using Deep Learning Techniques, (PDF, 3.7 MB) Guangming Zheng - NOAA/NESDIS/STAR Session 26: AI/ML for Information Extraction from Data, Part 2
Chairs: Shannon Rankin (Southwest Fisheries Science Center, NMFS), Matt Dornback (NOAA/OAR/OER),
Thursday, 21 January 2021
Kick: Shift-N-Overlap Cascades of Transposed Convolutional Layer for Better Autoencoding Reconstruction on Remote Sensing Imagery, (PDF, 8.83 MB) Seungkyun Hong - Korea Institute of Science and Technology Information Session 26: AI/ML for Information Extraction from Data, Part 2
Chairs: Shannon Rankin (Southwest Fisheries Science Center, NMFS), Matt Dornback (NOAA/OAR/OER),
Thursday, 21 January 2021
Deriving Fire Radiative Power from Numerical Weather Models and Satellites using Machine Learning Methods, (PPTX, 65.28 MB) Christina Kumler - CIRES/NOAA/GSL Session 27: AI/ML for Information Extraction from Data, Part 3
Chairs:Guangming Zheng (NOAA/NESDIS/STAR),
Thursday, 28 January 2021
Effects of Balancing Dataset on Support Vector Machine Performance for Tropical Cyclone Intensity Predictions, (PPTX, 1.7 MB) Mu-Chieh Ko - NOAA/AOML/HRD Session 27: AI/ML for Information Extraction from Data, Part 3
Chairs:Guangming Zheng (NOAA/NESDIS/STAR),
Thursday, 28 January 2021
What can we learn from Random Forest in the context of the tropical cyclone rapid intensification problem?, (PPTX, 22.36 MB) Chris Slocum - NOAA/NESDIS/STAR Session 27: AI/ML for Information Extraction from Data, Part 3
Chairs:Guangming Zheng (NOAA/NESDIS/STAR),
Thursday, 28 January 2021
Cloud Cover Nowcasts from Process-Based Statistical Models, (PPTX, 5.5 MB) Chuyen Nguyen - Naval Research Laboratory Session 28: Machine Learning Tools and Best Practices, Part 2,
Thursday, 4 February 2021
Radiant MLHub: Advancing Utilization of AI Applications on Earth Observations with Benchmark Training Datasets, (PDF, 57.59 MB) Hamed Alemohammad - Radiant Earth Foundation Session 28: Machine Learning Tools and Best Practices, Part 2,
Thursday, 4 February 2021
Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars, (PPTX, 45.12 MB) Jitendra Kumar - Oak Ridge National Laboratory Session 29: AI/ML for Environmental Data, Image, and Signal Processing, Part 4,
Thursday, 11 February 2021
Machine Learning for Earth Science Data Systems, (PDF, 4.38 MB) Manil Maskey - NASA Session 29: AI/ML for Environmental Data, Image, and Signal Processing, Part 4,
Thursday, 11 February 2021
CoralNet: AI for Automatic Annotation of Benthic Imagery, (PDF, 24.95 MB) David Kriegman - UCSD Session 29: AI/ML for Environmental Data, Image, and Signal Processing, Part 4,
Thursday, 11 February 2021
How NOAA Fisheries Leveraged Competitions and Collaboration to Automate the Identification of Right Whales using Deep Learning, (PPTX, 12.7 MB) Christin Khan - NOAA/NMFS/NEFSC/READ/PSB Session 29: AI/ML for Environmental Data, Image, and Signal Processing, Part 4,
Thursday, 11 February 2021
Mapping Arctic Vegetation using Hyperspectral Airborne Remote Sensing Data, (PDF, 21.74 MB) Venkata S. Konduri - Northeastern University & Oak Ridge National Laboratory Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5,
Thursday, 18 February 2021
Deep learning-based precipitation retrieval using passive microwave observations, (PDF, 4.17 MB) Yeji Choi - SI Analytics Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5,
Thursday, 18 February 2021
A spatiotemporal quantification of the relative importance of indicator inputs for drought estimation, (PDF, 2.26 MB) Soni Yatheendradas - UMD/ESSIC & NASA/GSFC Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5,
Thursday, 18 February 2021
Development of a Machine Learning-Based Radiometric Bias Correction for NOAA's Microwave Integrated Retrieval System (MiRS), (PPTX, 12.85 MB) Yan Zhou - UMD/ESSIC/CISESS Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5,
Thursday, 18 February 2021
Radar Reflectivity Surface Rainfall Retrieval with cGAN Algorithm: An Idealized Study, (PPTX, 9.54 MB) Shujia Zhou - NASA GSFC Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5,
Thursday, 18 February 2021
Leveraging Azure AI in Environmental Sciences, (PDF, 10.52 MB) Brian Keith - Microsoft Session 31: Tutorial - Microsoft,
Tuesday, 23 February 2021
NOAA Fish Detector using AI: Fish species population management, (PDF, 2.97 MB) Anusua Trivedi - Microsoft Session 32: Tutorial - Microsoft,
Wednesday, 24 February 2021
Energy efficiency and security aspects of Smart Homes, (PPTX, 37.35 MB) Olivera Kotevska - Oak Ridge National Laboratory Session 33: AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC),
Thursday, 25 February 2021
Benefits of modeling interdependent environmental variables, streamflow and stream temperature, with deep learning Negin Hayatbini - Scripps/CW3E/UCSD Session 33: AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC),
Thursday, 25 February 2021
Benefits of modeling interdependent environmental variables, streamflow and stream temperature, with deep learning, (PDF, 1.93 MB) Jeffrey Sadler - USGS Session 33: AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC),
Thursday, 25 February 2021
Workshop Science Committee Panel: Achieving Efficiency and Added Value in Environmental Science Through AI: The power of Govt/Academia/Private Partnership, (PDF, 5.28 MB) Science Committee Panelists: Sid Boukabara (NOAA/NESDIS/STAR) Chair; Vladimir Krasnopolsky (NOAA/NWS/NCEP) Co-Chair; Jebb Stewart (NOAA/OAR/ESRL); Nikunj Oza (NASA/Ames and NASA/ESTO) ; Greg Dusek (NOS); Amy McGovern (Univ. Of Oklahoma, AMS AI Committee Member); Allen Huang (Univ. Of Wisconsin); Phillip Tissot (Texas A&M-Corpus Christi, AMS AI Committee Member); Sue E. Haupt (NCAR); Jason Hickey (Google Inc.); John Williams (The Weather Company, an IBM Business); David Hall (NVIDIA) Session 33: AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC),
Thursday, 25 February 2021
AI 2020 Recordings Index
Title Session
Overview Talks, Part 1, (MP4, 1010.75 MB) Session 1,
30-Jul-20
Fundamentals of AI, Part 1
Chairs: Dave Turner (NOAA. ESRL), Jebb Stewart (NOAA, ESRL)
, (MP4, 671.68 MB)
Session 2,
6-Aug-20
Looking Ahead (Using AI for NOAA mission), Part 1
Chairs: Bill Michaels (NOAA, NMFS), John Ten Hoeve (Office of Organizational Excellence)
, (MP4, 968.72 MB)
Session 3,
13-Aug-20
AI/ML for Post-Processing and Data dissemination, Part 1
Chairs: Greg Dusek (NOAA/NOS), Andre van der Westhuysen (IMSG at NWS/NCEP/EMC)
Session 4,
20-Aug-20
AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD)
, (MP4, 454.88 MB)
Session 5,
27-Aug-20
AI/ML for Information Extraction from Data, Part 1
Chairs: Philippe Tissot (Texas A&M University, Corpus Christi), Jebb Stewart (NOAA, ESRL)
Session 6,
3-Sep-20
Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA)
, (MP4, 477.56 MB)
Session 7,
10-Sep-20
Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google)
, (MP4, 683.88 MB)
Session 8,
17-Sep-20
Tutorial 1: Tutorial on Video and Image Analytics for Marine Environments (VIAME), a Do-It-Yourself AI Toolkit, (MP4, 178.54 MB) Session 9,
22-Sep-20
AI/ML for Post-Processing and Data dissemination, Part 2
Chairs: Nikunj Oza (NASA), Allen Huang (UW-Madison)
, (MP4, 506.46 MB)
Session 10,
24-Sep-20
Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR)
, (MP4, 444.76 MB)
Session 11,
29-Sep-20
AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD)
, (MP4, 685.3 MB)
Session 12,
1-Oct-20
AI/ML for Data Fusion/Assimilation, Part 1
Chairs: Peter Jan van Leeuwen (CSU), Steve Penny (NOAA PSD/CIRES)
, (MP4, 750.87 MB)
Session 13,
15-Oct-20
Tutorial 2: Learning the Fundamentals of Machine Learning through Forecasting El Niño, (MP4, 125.3 MB) Session 14,
20-Oct-20
AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan)
, (MP4, 515.19 MB)
Session 15,
22-Oct-20
AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL)
, (MP4, 609.36 MB)
Session 16,
29-Oct-20
AI/ML for Post-Processing and Data dissemination, Part 4
Chairs: Andre van der Westhuysen (IMSG at NWS/NCEP/EMC), William Collins (LBNL, UC Berkeley)
, (MP4, 762.58 MB)
Session 17,
5-Nov-20
Tutorial 3: A Practical Introduction to Deep Learning for the Earth System Sciences using PyTorch, (MP4, 166.72 MB) Session 18,
10-Nov-20
AI/ML for Environmental Data, Image, and Signal Processing, Part 2
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD)
, (MP4, 214.89 MB)
Session 19,
12-Nov-20
Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi)
, (MP4, 758.86 MB)
Session 20,
19-Nov-20
Tutorial 4: Traditional Machine Learning Pipeline Applied to NWP Model Data, (MP4, 112.67 MB) Session 21,
1-Dec-20
AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University)
, (MP4, 513.47 MB)
Session 22,
3-Dec-20
Poster Session II, (MP4, 192.55 MB) Session 23,
15-Dec-20
AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR)
, (MP4, 657.89 MB)
Session 24,
17-Dec-20
AI/ML for Data Fusion/Assimilation, Part 2
Chairs: Steve Penny (NOAA PSD/CIRES), Kayo Ide (UMD)
, (MP4, 640.42 MB)
Session 25,
7-Jan-21
AI/ML for Information Extraction from Data, Part 2
Chairs: Shannon Rankin (Southwest Fisheries Science Center, NMFS), Matt Dornback (NOAA/OAR/OER)
, (MP4, 273.92 MB)
Session 26,
21-Jan-21
AI/ML for Information Extraction from Data, Part 3
Chairs:Guangming Zheng (NOAA/NESDIS/STAR)
, (MP4, 670.05 MB)
Session 27,
28-Jan-21
Machine Learning Tools and Best Practices, Part 2, (MP4, 334.85 MB) Session 28,
4-Feb-21
AI/ML for Environmental Data, Image, and Signal Processing, Part 4, (MP4, 538.84 MB) Session 29,
11-Feb-21
AI/ML for Environmental Data, Image, and Signal Processing, Part 5, (MP4, 521.43 MB) Session 30,
18-Feb-21
Tutorial 5 - Microsoft, (MP4, 99.86 MB) Session 31,
23-Feb-21
Tutorial 6 - Microsoft, (MP4, 75.27 MB) Session 32,
24-Feb-21
AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC)
, (MP4, 674.64 MB)
Session 33,
25-Feb-21

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