Spatial Forecast MethodsInter-Comparison Project -- ICP

Spring 2008 WorkshopNCAR Foothills Laboratory

Boulder, Colorado

Welcome !!

• Main objectives• Agenda• Subjective Evaluations• General (Topic-specific ) Discussion

Questions• Some other things to think about• Where do we go from here?

Main Objectives

• What can a forecaster learn from the results of each approach?– What are the pros and cons of each?– What user-specific needs are met?

General (topic) discussions

• How would one use results from each method?

• What information is given about scale?• Operational concerns?

– Summarizing multiple cases– Computational efficiency

• Uncertainty characterization

General Questions cont.

• Ease of interpretation• Appropriate applications

– Variables (e.g., precipitation, humidity, winds)– Domains– What information is needed for them to work– Can they characterize different attributes, and how?– Diagnostic information?

• Comparison of cases– How do they discern good vs. bad?

Focus on Fake Cases

• How do the methods handle the fake cases?

• Has anything been learned from the cases?

Other things to contemplate

• Categories– Filter Methods

• Scale-decomposition methods• Fuzzy/Neighborhood methods

– Motion Methods• Features-based methods• Field Morphing methods

– Not so easy to categorize Methods• FQI, CA, Composite, others?

Scale Questions• All methods can be run for different resolutions.• Filter Methods

– Scale-decomposition separates scale information– Fuzzy/Neighborhood do not separate scale information,

but do directly provide info on scales• Motion Methods

– Can information about scale be gleaned?– MODE uses quilt plots of threshold against convolution

radius. Similar to fuzzy.• Other Methods

– CA refers to numbers of clusters as “scale.”

Filter vs. Motion

Filter compares F and O fields at different scales, k, in the manner of

Where G is a traditional score (e.g., rmse)B is a filter (smoothing or band pass)

Gk (BF (F),BO (O))

Filter vs. Motion

Motion moves forecast field (or structures within the fields) in the manner:

Where s are coordinates in the domain of the image.

G(F(WF (s)),O(WO (s)))