Abstract. Atmospheric fronts are a widely used conceptual model in meteorology, most encountered as two-dimensional (2-D) front lines on surface analysis charts. The three-dimensional (3-D) dynamical structure of fronts has been studied in the literature by means of “standard” 2-D maps and cross-sections and is commonly sketched in 3-D illustrations of idealized weather systems in atmospheric science textbooks. However, only recently the feasibility of objective detection and visual analysis of 3-D frontal structures and their dynamics within numerical weather prediction (NWP) data has been proposed, and such approaches are not yet widely known in the atmospheric science community. In this article, we investigate the benefit of objective 3-D front detection for case studies of extratropical cyclones and for comparison of frontal structures between different NWP models. We build on a recent gradient-based detection approach, combined with modern 3-D interactive visual analysis techniques, and adapt it to handle data from state-of-the-art NWP models including those run at convection-permitting kilometer-scale resolution. The parameters of the detection method (including data smoothing and threshold parameters) are evaluated to yield physically meaningful structures. We illustrate the benefit of the method by presenting two case studies of frontal dynamics within mid-latitude cyclones. Examples include joint interactive visual analysis of 3-D fronts and warm conveyor belt (WCB) trajectories, and identification of the 3-D frontal structures characterising the different stages of a Shapiro-Keyser cyclogenesis event. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment the surface charts by providing additional pertinent information in the vertical dimension. A second application illustrates the effect of convection on 3-D cold front structure by comparing data from simulations with parameterised and explicit convection and shows that convection could strengthen the cold front. Finally, we consider “secondary fronts” that commonly appear in UK Met Office surface analysis charts. Examination of a case study shows that for this event the secondary front is not a temperature-based but purely a humidity-based feature. We argue that the presented approach has great potential to be beneficial for more complex studies of atmospheric dynamics and for operational weather forecasting.
Abstract. Atmospheric fronts are a widely used conceptual model in meteorology, most encountered as two-dimensional (2-D) front lines on surface analysis charts. The three-dimensional (3-D) dynamical structure of fronts has been studied in the literature by means of “standard” 2-D maps and cross-sections and is commonly sketched in 3-D illustrations of idealized weather systems in atmospheric science textbooks. However, only recently the feasibility of objective detection and visual analysis of 3-D frontal structures and their dynamics within numerical weather prediction (NWP) data has been proposed, and such approaches are not yet widely known in the atmospheric science community. In this article, we investigate the benefit of objective 3-D front detection for case studies of extratropical cyclones and for comparison of frontal structures between different NWP models. We build on a recent gradient-based detection approach, combined with modern 3-D interactive visual analysis techniques, and adapt it to handle data from state-of-the-art NWP models including those run at convection-permitting kilometer-scale resolution. The parameters of the detection method (including data smoothing and threshold parameters) are evaluated to yield physically meaningful structures. We illustrate the benefit of the method by presenting two case studies of frontal dynamics within mid-latitude cyclones. Examples include joint interactive visual analysis of 3-D fronts and warm conveyor belt (WCB) trajectories, and identification of the 3-D frontal structures characterising the different stages of a Shapiro-Keyser cyclogenesis event. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment the surface charts by providing additional pertinent information in the vertical dimension. A second application illustrates the relation between convection and 3-D cold front structure by comparing data from simulations with parameterised and explicit convection. Finally, we consider “secondary fronts” that commonly appear in UK Met Office surface analysis charts. Examination of a case study shows that for this event the secondary front is not a temperature-dominated but a humidity-dominated feature. We argue that the presented approach has great potential to be beneficial for more complex studies of atmospheric dynamics and for operational weather forecasting.
Abstract. Atmospheric fronts are a widely used conceptual model in meteorology, most encountered as two-dimensional (2-D) front lines on surface analysis charts. The three-dimensional (3-D) dynamical structure of fronts has been studied in the literature by means of “standard” 2-D maps and cross-sections and is commonly sketched in 3-D illustrations of idealized weather systems in atmospheric science textbooks. However, only recently has the feasibility of the objective detection and visual analysis of 3-D frontal structures and their dynamics within numerical weather prediction (NWP) data been proposed, and such approaches are not yet widely known in the atmospheric science community. In this article, we investigate the benefit of objective 3-D front detection for case studies of extra-tropical cyclones and for comparison of frontal structures between different NWP models. We build on a recent gradient-based detection approach, combined with modern 3-D interactive visual analysis techniques, and adapt it to handle data from state-of-the-art NWP models including those run at convection-permitting kilometre-scale resolution. The parameters of the detection method (including data smoothing and threshold parameters) are evaluated to yield physically meaningful structures. We illustrate the benefit of the method by presenting two case studies of frontal dynamics within mid-latitude cyclones. Examples include joint interactive visual analysis of 3-D fronts and warm conveyor belt (WCB) trajectories, as well as identification of the 3-D frontal structures characterizing the different stages of a Shapiro–Keyser cyclogenesis event. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment the surface charts by providing additional pertinent information in the vertical dimension. A second application illustrates the relation between convection and 3-D cold-front structure by comparing data from simulations with parameterized and explicit convection. Finally, we consider “secondary fronts” that commonly appear in UK Met Office surface analysis charts. Examination of a case study shows that for this event the secondary front is not a temperature-dominated but a humidity-dominated feature. We argue that the presented approach has great potential to be beneficial for more complex studies of atmospheric dynamics and for operational weather forecasting.
Ensemble simulations have become a standard in numerical weather prediction (NWP). However, ensemble simulations generate large amounts of data, and their comprehensive analysis remains challenging. We introduce a feature-based NWP ensemble analysis method based on the well-established conceptual model of atmospheric fronts. Recent developments in front detection techniques have enabled a reliable, robust, and objective identification of three-dimensional (3-D) frontal structures in NWP data.We advance detection of individual front features towards front-feature-based time series analysis and ensemble clustering. We track 3-D fronts of a selected cyclone system to create time series of frontal attributes. These frontal attributes characterize properties of the tracked front, for example, the maximum strength of the temperature gradient across the frontal zone, the average slope of the 3-D frontal structure or associated upward motion. The obtained time series provide a compact overview of the development of front characteristics. For ensemble analysis, we generate such time series for the cyclone system as represented in the different ensemble members. Time series distance measures including dynamic time warping can then be utilized to analyze similarities and differences of frontal development in the ensemble, for example, for front-feature-based ensemble cluster analysis. Also, a time window similarity search enables users to select a specific event of interest (for example, a sudden increase in frontal strength) in one of the ensemble members and to search for similar events in other members.Integrated in the 3-D visual analysis framework Met.3D, our approach facilitates a comprehensive analysis of the spatiotemporal development of 3-D atmospheric fronts and thus contributes to the challenge of rapidly analyzing large ensemble weather predictions.  
Visualization is an important and ubiquitous tool in the daily work of atmospheric researchers and weather forecasters to analyse data from simulations and observations. Visualization research has made much progress in recent years, for instance, with respect to techniques for ensemble data, interactivity, 3-D depiction, and feature-detection. Met.3D is an open-source research software aiming at making novel interactive, 3-D, feature-based, and ensemble visualization techniques accessible to the meteorological community (code repository, conda package, and documentation available at https://met3d.wavestoweather.de). Since its first public release in 2015, Met.3D has been used in multiple visualization research projects targeted at atmospheric science applications, and has evolved into a feature-rich visual analysis tool facilitating rapid exploration of atmospheric simulation data. The software is based on the concept of “building a bridge” between “traditional” 2-D visual analysis techniques and interactive 3-D techniques powered by modern graphics hardware. It allows users to analyse data using combinations of feature-based displays (e.g., atmospheric fronts and jet streams), “traditional” 2-D maps and cross-sections, meteorological diagrams, ensemble displays, and 3-D visualization including direct volume rendering, isosurfaces and trajectories, all combined in an interactive 3-D context. Met.3D has in recent years been advanced within the German research projects “Waves to Weather (W2W)” and “Climate, Climatic Change, and Society (CLICCS)”. In this presentation, we will present the current state of the Met.3D software and discuss recent updates we consider beneficial for the weather forecasting community, including use of open forecast data and interactive visual analysis of forecast 3-D cloud fields and other volumetric data.
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