A tutorial session for CADRE-JEDI-Edu was led by Aaron Johnson, Nick Gasperoni and Henry Santer. Additionally, there were the following presentations of CADRE-funded research:

Benneh, Michael: UFS/JEDI LiDAR DA – LiDAR Forward Operator Development

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

Kubalek, Daniel: Combining Data-driven and Physics-based Background Ensemble in Data Assimilation.

Pruett, Chandler: Improving Forecasts of Hurricane Beryl (2024) Genesis through Assimilation of All-Sky Infrared Radiances.

Santer, Henry: Fully non-Parametric Ensemble Data Assimilation: Idealized and Sea Ice Model Experiments Using Data-driven Estimates of Likelihood Functions.

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

Johnson, Aaron: Improving land-atmosphere background error covariance estimation toward RRFS strongly coupled data assimilation. 

Wang, Yongming: MAPCast: A Convection Allowing Emulator Toward Multi-Scale Data Assimilation.