There were CADRE-related presentations at the Unifying Innovations in Forecasting Capabilities Workshop (UIFCW) 2025 (* indicates CADRE-funded):

*Benneh, Michael et al. Advancing aerosol data assimilation with the Unified Forecast System (UFS)-Aerosols/JEDI by assimilating CALIOP aerosol profiles.

Chen, Zhihong and Xuguang Wang. Investigation of data driven background ensemble covariance from Graphcast toward Hurricane data assimilation and prediction

Chiao, Sen. Two decades of partnership with NOAA Line Offices: Challenges and Opportunities with the NOAA Center for Atmospheric Sciences and Meteorology (NCAS-M)

*Johnson, Aaron and Xuguang Wang. Understanding sampling error characteristics in ensemble-based estimates of land-atmosphere coupled background error covariances in a dryline CI case study

Kim, Yushin and Xuguang Wang. Impact of Assimilating Atmospheric Boundary Layer Observations on the Rapid Intensification of Hurricane Idalia (2023) in the HAFS-JEDI Framework

Knisely, Joseph. Obstacles for High-Resolution HAFS over the Entire Atlantic Basin.

*van Leeuwen, Peter Jan. On the efficient implementation of non-Gaussian observation errors in existing DA schemes

Padmanabhan, Thiruvengadam, Xuguang Wang and Yongming Wang. Improving Background Error Covariance and Square Root Estimation with the Convolution Neural Network (CNN) in the Gain Form Ensemble Transform Kalman filter (GETKF)

Poterjoy, Jonathan. Toward High-Frequency Bayesian Assimilation in the UFS Using Local Particle Filters

*Santer, Henry and Jonathan Poterjoy. Non-parametric Estimates of Sea Ice Concentration Observation Errors using CICE6 and Kernel Embeddings of Conditional Distributions

*Wang, Xuguang. CADRE progress and plans or data assimilation panel discussion

*Wang, Yongming and Xuguang Wang. Generating Cost-Saving Surrogate Background Ensemble with GNN-based MAPcast for Estimating Multi-Scale Background Error Covariances