1. Ideas for NWS EPS Advancement
Tony Eckel
Naval Postgraduate School

2. EPS Components
Foundation: Observations, Data Assimilation, the Model(s), Model Resolution, …
Ensemble: Initial Condition Perturbations, Model Perturbations, # of Members, …
III. Exploitation: Post-processing, Products, Verification, User Education, …

3. Design all components based on Value first, Skill second
Evolving to “service paradigm” with focus on optimizing users’ decision processes requires different emphasis for measuring forecast quality since skill ≠value
Metrics of Value (e.g., ROCSS, VS, etc.) measure quality from user perspective
Metrics of Skill (e.g., BSS, CRPS, etc.) are important for scientific evaluation
Requires intimate relationship with users to understand their weather sensitivities and risk tolerances

4. Post-Processing
Truth: Must capture phenomena and scales of concern to user
Reforecast dataset required for robust calibration
Match EPS design (no short cuts!)
Length dependent upon capturing user phenomena
Down-scaling critical to value
Meteorological consistency within each member may be challenging issue

5. Thorough and Open Verification
Critical to building user confidence
Focused on user sensitivities
User-friendly: web-based, interactive, well documented, etc.
Continuously updated
Link with products and education

6. User Education
Need campaign (concerted effort) to teach users methods for optimal decision making given forecast uncertainty information
Broad-based: Specific users and general public
Include detailed strengths and weaknesses of the EPS