A methodology for sensitivity analysis of spatial features in forecasts: the stochastic kinetic energy backscatter scheme. (28th March 2019)

• Record Type: Journal Article
• Authors: Marzban, Caren; Tardif, Robert; Sandgathe, Scott; Hryniw, Natalia
• Is Part Of: Meteorological applications. Volume 26:Number 3(2019)
• Page Start: 454
• Page End: 467
• Publication Date: 2019-03-28
• Subjects: analysis of variance -- NWP -- parametrization -- sensitivity analysis -- statistical models; Meteorology -- Periodicals; Meteorological services -- Periodicals; 551.5
• DOI: 10.1002/met.1775
• Languages: English
• ISSNs: 1350-4827

Abstract

Abstract : Stochastic kinetic energy backscatter schemes (SKEBSs) are introduced in numerical weather forecast models to represent uncertainties related to unresolved subgrid‐scale processes. These schemes are formulated using a set of parameters that must be determined using physical knowledge and/or to obtain a desired outcome. Here, a methodology is developed for assessing the effect of four factors on spatial features of forecasts simulated by the SKEBS‐enabled Weather Research and Forecasting model. The four factors include two physically motivated SKEBS parameters (the determining amplitude of perturbations applied to stream function and potential temperature tendencies), a purely stochastic element (a seed used in generating random perturbations) and a factor reflecting daily variability. A simple threshold‐based approach for identifying coherent objects within forecast fields is employed, and the effect of the four factors on object features (e.g. number, size and intensity) is assessed. Four object types are examined: upper‐air jet streaks, low‐level jets, precipitation areas and frontal boundaries. The proposed method consists of a set of standard techniques in experimental design, based on the analysis of variance, tailored to sensitivity analysis. More specifically, a Latin square design is employed to reduce the number of model simulations necessary for performing the sensitivity analysis. Fixed effects and random effects models are employed to assess the main effects and the percentage of the total variability explained by the four factors. It is found that the two SKEBS parameters do not have an appreciable and/or statistically significant effect on any of the examined object features. Abstract : All numerical models have parameters whose values are often set in an ad hoc fashion, and so it is important to assess how these parameters affect the output of the model. The output of many models often contain "objects, " examples of which are shown in the figure. This paper proposes a methodology for assessing how the model parameters affect specific features of such objects.