verification

Verification Image i12_series_cnt_E90_f012

Developing a State-of-the-Art Verification Toolkit

Forecasts get better each year, but there is always room for improvement. They must be scrutinized for what went right and, more importantly, what didn’t. Verification, the testing and evaluation process of a forecast, is a critical component of improvement. Evaluation findings provide needed information to end users, supplying them with objective data about the quality or accuracy of the forecasts.

The DTC verification team supports testing and evaluation activities by providing the open source Model Evaluation Tools (MET) software package and support. It provides the capability to do traditional, spatial, or tropical cyclone verification. Enhancements in this package now give users more flexibility and control over particular conditions they want to test and evaluate. The user community, which includes university researchers, government agencies and operational centers, relies on this technology and service, and is growing nationally and internationally. MET was recently included in a Docker container to lower the learning curve for new users.

For more information and to download the software (and container), please see the MET homepage

Team

Primary Contact

Scientists

Software Engineers

Questions about verification methods and MET: met_help@ucar.edu

Publications

Clark, A., R. Bullock, T. Jensen, M. Xue, F. Kong, 2014: Application of object-based time-domain diagnostics for tracking precipitation systems in convection-allowing models. Wea. Forecasting, 29, 517-542.

Clark, A.J. S. Kain, P. T. Marsh, J. Correia Jr., M. Xue, and F. Kong, 2012: Forecasting tornado pathlengths using a three-dimensional object identification algorithm applied to convection-allowing forecasts. Wea. Forecasting, 27, 1090–1113, doi:10.1175/WAF-D-11-00147.1.[BB1] 

Wolff, J.K., M. Harrold, T. Fowler, J. Halley Gotway, L. Nance, and B. G. Brown. 2014: Beyond the basics: Evaluating model-based precipitation forecasts using traditional, spatial, and object-based methods. Weather and Forecasting, 29, 1451-1472.