Evaluation of WRF Forecasts of Tornadic and Nontornadic Outbreaks When Initialized with Synoptic-Scale Input

Shafer, Chad M.; Mercer, Andrew E.; Doswell, Charles A.; Richman, Michael B.; Leslie, Lance M.

doi:10.1175/2008mwr2597.1

Cited by 44 publications

(46 citation statements)

References 61 publications

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“…The low-level SRH, can vary dramatically over short distances, due to topographically channeled flow (e.g., Braun and Monteverdi, 1991;Bosart et al, 2006). The selection of these parameters is consistent with the approach adopted in previous studies (Droegemeier et al, 1993;Johns et al, 1993;Rasmussen and Blanchard, 1998;Brooks et al, 2003;Doswell and Evans, 2003;Thompson et al, 2003;Shafer et al, 2009;Matsangouras et al, 2011aMatsangouras et al, , 2012Sioutas et al, 2012). Table 1.…”

Section: T Matsangouras Et Al: Effect Of Topography On Tornadogesupporting

confidence: 69%

Numerical modeling and analysis of the effect of complex Greek topography on tornadogenesis

Matsangouras

Pytharoulis

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Tornadoes have been reported in Greece over recent decades in specific sub-geographical areas and have been associated with strong synoptic forcing. While it has been established that meteorological conditions over Greece are affected at various scales by the significant variability of topography, the Ionian Sea to the west and the Aegean Sea to the east, there is still uncertainty regarding topography's importance on tornadic generation and development.The aim of this study is to investigate the role of topography in significant tornadogenesis events that were triggered under strong synoptic scale forcing over Greece. Three tornado events that occurred over the last years in Thebes (Boeotia, 17 November 2007), Vrastema (Chalkidiki, 12 February 2010) and Vlychos (Lefkada, 20 September 2011) were selected for numerical experiments. These events were associated with synoptic scale forcing, while their intensities were T4-T5 (on the TORRO scale), causing significant damage. The simulations were performed using the non-hydrostatic weather research and forecasting model (WRF), initialized by European Centre for Medium-Range Weather Forecasts (ECMWF) gridded analyses, with telescoping nested grids that allow for the representation of atmospheric circulations ranging from the synoptic scale down to the mesoscale. In the experiments, the topography of the inner grid was modified by: (a) 0 % (actual topography) and (b) −100 % (without topography), making an effort to determine whether the occurrence of tornadoes -mainly identified by various severe weather instability indices -could be indicated by modifying topography. The principal instability variables employed consisted of the bulk Richardson number (BRN) shear, the energy helicity index (EHI), the storm-relative environmental helicity (SRH), and the maximum convective available potential energy (MCAPE, for parcels with maximum θ e ). Additionally, a model verification was conducted for every sensitivity experiment accompanied by analysis of the absolute vorticity budget.Numerical simulations revealed that the complex topography constituted an important factor during the

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Section: T Matsangouras Et Al: Effect Of Topography On Tornadogesupporting

confidence: 69%

Numerical modeling and analysis of the effect of complex Greek topography on tornadogenesis

Matsangouras

Pytharoulis

2014

Nat. Hazards Earth Syst. Sci.

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“…Generally speaking, the troughs associated with the NTOs all have a positive tilt that is far less amplified. The amplification of these tilts in the TO events suggests an increase in storm-relative environmental helicity (SREH) and vertical bulk shear in the TOs, as in previous work (e.g., M09; S09; Shafer et al 2010).…”

Section: A Interpretation Of the Synoptic Pattern Compositessupporting

confidence: 68%

“…Most NTO composites had marginal shear and SREH magnitudes relative to the TO composites both in the original composite fields and in the WRF simulations of the composites. The study revealed a classical synopticscale pattern for a typical major TO with minor deviations (e.g., the tilt of the trough at 850 mb), but several types of NTOs resulted from the analysis, likely attributable to the known seasonality of NTOs (Shafer et al 2010). Overall, the results demonstrate clear synopticscale differences between the two outbreak types, and the WRF simulations support that conclusion.…”

Section: Discussionsupporting

confidence: 56%

“…6b). This seasonality has been characterized in previous work (Shafer et al 2010) and is important in the current study as well, given that the synoptic environments governing summer and spring midlatitude conditions are considerably different (Hsu and Wallace 1976;S09). The zonal pattern in NTO2 is an indication of how highly variable the constituent members are for that cluster, suggesting that many different meteorological conditions may be responsible for the representative spring NTO.…”

Section: A Interpretation Of the Synoptic Pattern Compositesmentioning

confidence: 78%

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Synoptic Composites of Tornadic and Nontornadic Outbreaks

Mercer¹,

Shafer²,

Doswell³

et al. 2011

Mon. Wea. Rev.

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Tornadic and nontornadic outbreaks occur within the United States and elsewhere around the world each year with devastating effect. However, few studies have considered the physical differences between these two outbreak types. To address this issue, synoptic-scale pattern composites of tornadic and nontornadic outbreaks are formulated over North America using a rotated principal component analysis (RPCA). A cluster analysis of the RPC loadings group similar outbreak events, and the resulting map types represent an idealized composite of the constituent cases in each cluster. These composites are used to initialize a Weather Research and Forecasting Model (WRF) simulation of each hypothetical composite outbreak type in an effort to determine the WRF's capability to distinguish the outbreak type each composite represents.Synoptic-scale pattern analyses of the composites reveal strikingly different characteristics within each outbreak type, particularly in the wind fields. The tornado outbreak composites reveal a strong low-and midlevel cyclone over the eastern Rockies, which is likely responsible for the observed surface low pressure system in the plains. Composite soundings from the hypothetical outbreak centroids reveal significantly greater bulk shear and storm-relative environmental helicity values in the tornado outbreak environment, whereas instability fields are similar between the two outbreak types. The WRF simulations of the map types confirm results observed in the composite soundings.

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“…Simulations of the top 50 TOs and NTOs from D06 were conducted at 24-, 48-, and 72-h lead times (see Shafer et al 2009 for a detailed review of the simulation process). One NTO event, 5 July 1980, had a 1200 UTC valid time (as opposed to the 0000 UTC valid time for the remaining 99 cases), so it was rejected.…”

Section: A Data and Wrf Model Simulationmentioning

confidence: 99%

Objective Classification of Tornadic and Nontornadic Severe Weather Outbreaks

Mercer

Shafer

Doswell

et al. 2009

Monthly Weather Review

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Tornadoes often strike as isolated events, but many occur as part of a major outbreak of tornadoes. Nontornadic outbreaks of severe convective storms are more common across the United States but pose different threats than do those associated with a tornado outbreak. The main goal of this work is to distinguish between significant instances of these outbreak types objectively by using statistical modeling techniques on numerical weather prediction output initialized with synoptic-scale data. The synoptic-scale structure contains information that can be utilized to discriminate between the two types of severe weather outbreaks through statistical methods. The Weather Research and Forecast model (WRF) is initialized with synopticscale input data (the NCEP-NCAR reanalysis dataset) on a set of 50 significant tornado outbreaks and 50 nontornadic severe weather outbreaks. Output from the WRF at 18-km grid spacing is used in the objective classification. Individual severe weather parameters forecast by the model near the time of the outbreak are analyzed from simulations initialized at 24, 48, and 72 h prior to the outbreak. An initial candidate set of 15 variables expected to be related to severe storms is reduced to a set of 6 or 7, depending on lead time, that possess the greatest classification capability through permutation testing. These variables serve as inputs into two statistical methods, support vector machines and logistic regression, to classify outbreak type. Each technique is assessed based on bootstrap confidence limits of contingency statistics. An additional backward selection of the reduced variable set is conducted to determine which variable combination provides the optimal contingency statistics. Results for the contingency statistics regarding the verification of discrimination capability are best at 24 h; at 48 h, modest degradation is present. By 72 h, the contingency statistics decline by up to 15%. Overall, results are encouraging, with probability of detection values often exceeding 0.8 and Heidke skill scores in excess of 0.7 at 24-h lead time.

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Evaluation of WRF Forecasts of Tornadic and Nontornadic Outbreaks When Initialized with Synoptic-Scale Input

Cited by 44 publications

References 61 publications

Numerical modeling and analysis of the effect of complex Greek topography on tornadogenesis

Numerical modeling and analysis of the effect of complex Greek topography on tornadogenesis

Synoptic Composites of Tornadic and Nontornadic Outbreaks

Objective Classification of Tornadic and Nontornadic Severe Weather Outbreaks

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