Transcript TonyN.ppt
Ideas for NWS EPS Advancement Tony Eckel Naval Postgraduate School EPS Components I. Foundation: Observations, Data Assimilation, the Model(s), Model Resolution, … II. Ensemble: Initial Condition Perturbations, Model Perturbations, # of Members, … III. Exploitation: Post-processing, Products, Verification, User Education, … 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 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 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 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