MODE, the Method for Object-Based Diagnostic Evaluation, provides an object-based verification for comparing gridded forecasts to gridded observations. MODE may be used in a generalized way to compare any two fields containing data from which objects may be well defined. It has most commonly been applied to precipitation fields and radar reflectivity. The steps performed in MODE consist of:
- Define objects in the forecast and observation fields based on user-defined parameters.
- Compute attributes for each of those objects: such as area, centroid, axis angle, and intensity.
- For each forecast/observation object pair, compute differences between their attributes: such as area ratio, centriod distance, angle difference, and intensity ratio.
- Use fuzzy logic to compute a total interest value for each forecast/observation object pair based on user-defined weights.
- Based on the computed interest values, match objects across fields and merge objects within the same field.
- Write output statistics summarizing the characteristics of the single objects, the pairs of objects, and the matched/merged objects.
MODE may be configured to use a few different sets of logic with which to perform matching and merging. In this tutorial, we'll use the most simple approach, but users are encouraged to read the MET Users Guide for a more thorough description of MODE's capabilities.
View the usage statement for MODE by simply typing the following:
At a minimum, the input gridded fcst_file, the input gridded obs_file, and the configuration config_file must be passed in on the command line.
As with the other MET statistics tools, all gridded forecast and observation data must be interpolated to a common grid prior to processing. This may be done using the automated regrid feature in the Ensemble-Stat configuration file or by running copygb and/or wgrib2 first.