6533b834fe1ef96bd129cb0f

RESEARCH PRODUCT

Spatial Forecast Verification Methods Intercomparison Project: Application of the SAL Technique

Heini WernliMatthias ZimmerChristiane Hofmann

subject

Atmospheric ScienceMeasure (data warehouse)MeteorologyComputer scienceOrientation (computer vision)computer.software_genreForecast verificationDomain (software engineering)Feature (computer vision)Quantitative precipitation forecastPrecipitationData miningFocus (optics)computer

description

Abstract In this study, a recently introduced feature-based quality measure called SAL, which provides information about the structure, amplitude, and location of a quantitative precipitation forecast (QPF) in a prespecified domain, is applied to different sets of synthetic and realistic QPFs in the United States. The focus is on a detailed discussion of selected cases and on the comparison of the verification results obtained with SAL and some classical gridpoint-based error measures. For simple geometric precipitation objects it is shown that SAL adequately captures errors in the size and location of the objects, however, not in their orientation. The artificially modified (so-called fake) cases illustrate that SAL has the potential to distinguish between forecasts where intense precipitation objects are either isolated or embedded in a larger-scale low-intensity precipitation area. The real cases highlight that a quality assessment with SAL can lead to contrasting results compared to the application of classical error measures and that, overall, SAL provides useful guidance for identifying the specific shortcomings of a particular QPF. It is also discussed that verification results with SAL and other error measures should be interpreted with care if considering large domains, which may contain meteorologically distinct precipitation systems.

https://doi.org/10.1175/2009waf2222271.1