Extended Abstract

New Model Evaluation Tools (MET) Software Capabilitiesfor QPF VerificationTressa L. FOWLER, Tara JENSEN, Edward I. TOLLERUD, John HALLEY GOTWAY,Paul OLDENBURG, and Randy BULLOCKNational Center for Atmospheric Research (NCAR, Boulder, CO USA)tressa@ucar.edu1. IntroductionVerification plays a crucial role in improvement of precipitation forecasts The Model EvaluationTools (MET) software was designed to provide the numerical weather prediction community withquality software incorporating the latest advances in forecast verification, including methods forverifying quantitative precipitation forecasts (QPF).The recent addition of probabilistic and ensemble verification capabilities to the MET softwarehas led to innovations demonstrated in the verification activities of two QPF projects in the UnitedStates. The Hydrometeorology Testbed (HMT) conducted an experiment examining heavy, prolongedwinter precipitation. Prediction of convective precipitation was one focus of the Hazardous WeatherTestbed (HWT) 2010 Spring Experiment. Examples from these projects demonstrating MET’s spatial,object-based verification of ensemble relative frequency (e.g. probability) and ensemble mean will bepresented and compared to traditional methods. In addition to verifying QPF, atmospheric river andradar reflectivity fields were evaluated using MET’s object based spatial verification. These examplesillustrate the enhanced diagnostic information available from spatial verification versus traditionalmetrics.2. MET SoftwareThe MET verification software is designed to provide the numerical weather predictioncommunity with a consistent means to verify model forecasts. Traditional verification measures forprecipitation are available in MET. For precipitation, traditional verification often utilizes skill scores,such as the Threat Score, computed for cases that exceed some minimum precipitation amount.Unfortunately, for this type of verification, a shift in time or space of the forecast precipitation area canlead to the so-called “double penalty”, where the forecast is a false alarm and observation is missedevent. Ensemble and probability forecasts contain more information than standard deterministicforecasts. Thus, though traditional methods and statistics can be applied, additional information is abenefit to the user.Recent additions to the MET software have enhanced the precipitation verification capabilitiesto address these issues. Ensemble means and probability values can be produced from a set of forecastsby a new MET preprocessing tool. Probabilistic forecasts are verified using traditional statistics such asBrier score, while ensemble mean and spread can be used to calculate the continuous ranked probabilityscore (CRPS). Additionally, both types of forecasts can be used in advanced spatial verificationtechniques.MET’s object based spatial verification software, MODE (Method for Object-based DiagnosticEvaluation; Davis et al, 2009), can use ensemble means or ensemble probabilities to define forecastobjects then compare these to objects identified in gridded observation fields. This software wasdeveloped on precipitation fields. However, it has also been successfully applied to other spatiallycoherent fields, such as radar echo top, atmospheric rivers, cloud percent, and winds.Although the software was created to work with the weather and research forecasting (WRF)model, MET can be used with any model in GRIB format. Users have reported success using MET with-189-