The Method for Object-Based Diagnostic Evaluation (MODE) is an object-oriented verification technique that is part of the Model Evaluation Tools (MET) verification package developed by the Developmental Testbed Center (DTC) . Object-oriented verification methods have been developed in an attempt to better account for spatial discontinuities between forecast and observed precipitation as well as provide more specific information about forecast quality than can be obtained from traditional verification measures (threat score, bias, etc.) alone. These techniques are considered particularly useful for evaluating high resolution model guidance. Traditional verification methods often struggle to accurately assess the performance of high resolution models since even small spatial errors can result in the forecast being penalized twice (once for missing the observed precipitation and a second time for giving a false alarm). The goal of the MODE tool is to evaluate forecast quality in a manner similar to a forecaster completing a subjective forecast evaluation.

MODE identifies precipitation objects in both the forecast and observed fields at a number of different thresholds. It then uses a variety of object characteristics (ex: distance between objects, size of objects, angle of orientation, etc.) to determine the degree of similarity between objects in the forecast and observed fields. Objects that are found to be similar to one another are considered “matched”, while those that are not similar are considered “unmatched”. Unmatched objects in the forecast field are equivalent to a false alarm. Unmatched objects in the observed field are equivalent to a miss. Examples of the graphical verification output produced by MODE are below. Matched objects are indicated in the same color in both the forecast and the observed fields. In this case, the red, green, and light blue objects are matched with one another. Unmatched objects are always displayed in dark blue.

In addition to the graphical output, MODE also provides statistical information for each matched object. This information includes a parameter called the interest value, which is an overall measure of similarity between objects in the forecast and observed fields. The interest value ranges from 0 to 1, with a value of 0.70 required for objects to be considered matched. In addition to the interest value, MODE also provides information about the displacement distance, which is defined as the distance between the center of a forecast object and the center of the corresponding observed object.

MODE verification is available for Day 1, Day 2, and Day 3 forecasts of 24 hr precipitation valid at 1200 UTC. The preliminary verification uses MRMS radar-derived precipitation observations and is available the same day. The final verification uses Stage IV precipitation observations and is available two days later. In addition to the WPC forecast, verification is also available for model forecasts from the GFS, NAM, CMC, UKMET, NAM CONUS Nest, and the NCEP high resolution window runs (ARW and NMM), and a WPC-generated pseudo-bias corrected ensemble (ENSBC; see Appendix A of Novak et al. 2014). All forecasts and observations are re-gridded to the 20 km WPC grid prior to verification. In order to compare WPC forecasts to the model data available at the time they were generated, the forecast lead times are offset such that the 24 hr (Day 1), 48 hr (Day 2), and 72 hr (Day 3) WPC forecasts are compared to the 36 hr, 60 hr, and 84 hr model forecasts, respectively. Development of the MODE tool is ongoing; for a complete list of changes, please click here.

Davis, C., B. Brown, and R. Bullock, 2006: Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas. Mon. Wea. Rev., 134, 1772-1784.

Davis, C., B. Brown, and R. Bullock, 2006: Object-based verification of precipitation forecasts. Part II: Application to convective rain systems. Mon. Wea. Rev., 134, 1785-1795.


Model Evaluation Tools (MET) was developed at the National Center for Atmospheric Research (NCAR) through grants from the United States Air Force Weather Agency (AFWA) and the National Oceanic and Atmospheric Administration (NOAA). NCAR is sponsored by the United States National Science Foundation.