MODE (Method for Object-based Diagnostic Evaluation)

More documents

Recommendations

Info

MODE output Attributes of composite observed and forecast objects and their relationships − EX: Area, Intensity, Volume, Location, Shape, + differences and ratios Attributes of single matched shapes (i.e., “Hits”) Attributes of single unmatched shapes (i.e., “False Alarms”, “Misses”) Attributes of interest to specific users (e.g., gaps between storms, for aviation strategic planning) Attributes can be summarized across many cases to − − − − Understand how forecasts represent the storm/precip climatology Understand systematic errors Document variability in performance in different situations Etc.
MODE Strengths and Weaknesses Strengths − Allows and quantifies spatial offsets − Gives credit to a “good enough” forecast − Tuned to particular object intensity and size Weaknesses − Many tunable parameters
Page 1 and 2: MODE (Method for Object-based Diagn
Page 3 and 4: MODE Object Identification 2 parame
Page 5 and 6: Fuzzy logic mergers Centroid distan
Page 7 and 8: Fuzzy logic mergers orientation
Page 9: Fuzzy logic matches Overlap Size ra
Page 13 and 14: June 1, 2005 ARW 2-km ARW 4-km Disp
Page 16 and 17: Gridded forecast example: Summary L
Page 18 and 19: Application examples: Distribution
Page 20 and 21: Quilt plots for different models
Page 22 and 23: Percent of single objects matched 1
Page 24: 2005 0513 2005 0601
Page 30 and 31: 14 12 hit 10 8 6 4 2 false alm miss
Page 33: 1 June 2005 9 Cases

MODE (Method for Object-based Diagnostic Evaluation)

Create successful ePaper yourself

Delete template?

Save as template?