Session 1 – Uncertainties in Representation of Model Processes
Uncertainties in Representation of Microphysics – Hugh Morrison
Uncertainties in Model Initial Conditions – Aaron Johnson
Uncertainties in Representation of Model Processes – Ming Xue
Use of Stochastic Modeling to Determine Predictability – Judith Berner
Session 2 – Uncertainties in Measurements
Uncertainties in Ground-based Radar Observations – Guifu Zhang
Uncertainties in Products Derived from Radar – Alexander Ryzhkov
Uncertainties in In-Situ Observations of Cloud Microphysics – Greg McFarquhar
Uncertainties in Quantitative Precipitation Estimation – Jian Zhang
Satellite Data Assimilation and Microphysics – Thomas Jones
Session 3 – Variational, Ensemble and Hybrid Data Assimilation
Data Assimilation of Satellite Observations – Jason Otkin
Uncertainties in Data Assimilation of Observations – Xuguang Wang
NCEP Modeling and Data Assimilation Plans – Jacob Carley
Stochastic Approaches in the High Resolution Rapid Refresh Ensemble – Isidora Jankov
Session 4 – Uncertainties Associated with Predictability Limitations
Numerical Simulations and Observational Analysis Related to Predictability – Chris Davis
Predictability and Data Assimilation – Fuqing Zhang
Ensemble Systems and Weather Prediction Applications – Glen Romine
Atmospheric Predictability – Dale Durran
Summary Documents
Data Assimilation and Variational Analysis