CADRE presence at AMS 2026

CADRE had a large presence at the 2026 AMS Annual Meeting in Houston.  See CADRE events below and memorable photos!

Sunday, 25 January 2026

25th Annual Student Conference

Data Assimilation and Numerical Weather Prediction Poster Session

(7:00pm) Alexis K. Dooley: Evaluating the Vertical Mixing Schemes in the Ocean Surface Boundary Layer in the Intensification Forecast of Hurricane Fiona (2022)

AI and Machine Learning Poster Session

(7:00pm) Jacob Peace: Using Random Forests in State Dependent Bias Correction Within Convection-Allowing Ensemble Systems

Monday, 26 January 2026

30th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS).

Session 1: Advances in Observations, Modeling and Data Assimilation

(9:00am) Zhaoxia Pu: Towards Strongly Coupled Land–Atmosphere Data Assimilation for Numerical Weather Prediction and Earth System Models

(9:30am) Steven Greybush: Exploring the potential of AI-NWP Ensembles for Sensitivity, Predictability, and DA for Winter Storms

Session 2: “Data-driven” Assimilation and Numerical Weather Prediction with AI

(10:45am) Conor John Lewellyn: Generative Data Assimilation for High-Resolution Weather State Estimation in Data Sparse Areas (Invited Presentation)

(11:00am) Ryan Keisler: AIDA: Operational AI Data Assimilation from Level 1 Observations (Invited Presentation)

(11:15am) Xuguang Wang: Advancing Multiscale Data Assimilation with Machine Learning

(11:30am) Peter Jan van Leeuwen: Leveraging data-assimilation ideas and tools in machine learning

(11:45am) Yongming Wang: MAPCast: A Convection Allowing Emulator for Multi-scale Data Assimilation

Joint Session with the 30th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS) and 25th Conference on Artificial Intelligence for Environmental Science

Joint Session J3 – Machine Learning and Artificial Intelligence in Data Assimilation and Next Generation of Weather Forecasting

(2:30pm) Peng-Xiang Lai: Missing Physics Estimation Using Data Assimilation and Machine Learning

(2:45pm) Zhihong Chen: Investigation of data driven background ensemble covariance from Graphcast toward Hurricane data assimilation and prediction

3pm Poster Session

Michael Kwadwo Benneh: NOAA Global Chemistry and Aerosol Forecast System (GCAFS): JEDI-Based 3D-Var Data Assimilation and a vertical profile comparison against CALIOP Extinction Profiles.

30th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS).

Session 4: Data Assimilation Methodology for Numerical Weather Prediction

(5:15pm) Jonathan Poterjoy: Toward High-Frequency Bayesian Assimilation for Global Weather Prediction Using Localized Particle Filters

Tuesday, 27 January 2026

30th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS).

Session J5: Multi-University Consortium for Advanced Data Assimilation Research and Education

(8:30am) Xingchao Chen: Improving Ensemble-Based Assimilation of All-Sky Infrared Radiances via Background-Error Covariance Enhancement

(8:45am) Henry Santer: Non-parametric Estimates of Sea Ice Concentration Observation Errors using CICE6 and Kernel Embeddings of Conditional Distributions

(9:00am) Max Carl Johncox: Assessing the Role of Snow Data Assimilation in Improving S2S Weather Forecasts and Extreme Event Prediction with UFS and JEDI

(9:15am) Joshua Wei Chen: Learning Multivariate Non-Gaussian Observation Error Models and Assessing their Impact on Iterative Data-Assimilation Methods

(9:30am) Aaron Johnson: Convection-allowing Ensemble-based Land-atmosphere Coupled Background Error Covariance and its Sampling Error: A Dryline Case Study

(9:45am) Yunji Zhang: Examining Correlation Structure using a Large GEFS Ensemble: An Example with Planetary Boundary Layer Height

Joint Session with the 30th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS) and Fifth Symposium on Community Modeling and Innovation

Joint Session J7 – Multi-University Consortium for Advanced Data Assimilation Research and Education – Part II

(1:45pm) Ethan Michael Schaefer: Exploring the Sensitivity of Heavy Snowfall Prediction in Northeast U.S. Winter Storms to JEDI Data Assimilation and Microphysics Parameters in MPAS

(2:00pm) Haotong Jing: Soil Moisture Data Impact in Coupled Land–Atmosphere Data Assimilation with UFS and JEDI

(2:15pm) Yu-Shin Kim: Impact of Assimilating Atmospheric Boundary Layer Observations on the Rapid Intensification of Hurricane Idalia (2023) in Self-cycled HAFS-JEDI System

(2:30pm) Daniel Lee Kubalek: Using U-NET-based Emulator to Increase Background Ensemble Members for Cost-Effectively Improving MLGETKF Cycling Data Assimilation

(2:45pm) Hyun-Sook Kim: Assessment of Ocean Observation Impacts on Coupled Hurricane Forecasts

3pm Poster Session

Braedon Stouffer: Assimilating Boundary Layer Depths Observed by WSR-88Ds to Improve the Prediction of a Derecho

Jacob Peace: State Dependent Bias Correction Within Convection-Allowing Ensemble Systems using Random Forests

Maria Nikolaitchik: DAPyR: An Open-Source Python Package for Data Assimilation Education and Research

Chandler Michael Pruett: Improving Tropical Cyclogenesis Prediction Using All-Sky Water-Vapor-Channel Infrared Radiance Data Assimilation

Brett Castro: Impact of Greenness Vegetation Fraction Perturbations on Convection-Allowing Ensemble-Based Land-Atmosphere Coupled Background Error Covariance

Ayoola Olumide Abe: Evaluating UFS and MPAS Forecast Performance of a High Impact Severe Storm Initiated by Dryline Cold Front Interaction

Feng Hsiao: Evaluating Hurricane Beryl (2024) Intensity Forecast in HAFS using with JEDI-based Dropsonde Data Assimilation

Wednesday, 28 January 2026

16th Conference on Transition of Research to Operations

Session 12B Advancing R2O and O2R in Weather Analysis and Forecast Systems: Technologies, Methodologies, and Approaches to Meet Evolving Forecasting Needs: Part IV of IV: Modeling and Data Assimilation

(5:15pm) Yongming Wang: Implementing Scale-Dependent Inflation (SDI) to Enhance Background Error Covariances within JEDI-based Simultaneous Multi-Scale Data Assimilation for RRFS