15A.2 Sensitivity of the Structural Evolution of Hurricane Sandy to Variations in Storm Track

Thursday, 26 January 2017: 3:45 PM
Conference Center: Tahoma 3 (Washington State Convention Center )
Alex Kowaleski, Valparaiso University, Valparaiso, IN; and J. L. Evans

Hurricane Sandy (2012) underwent a long and complex extratropical transition (ET) before its devastating landfall on the New Jersey coast late on 29 October.  Sandy interacted with two troughs that affected its ET process and its track: an upper-tropospheric trough over the eastern Gulf of Mexico on 26 and 27 October, and a larger mid-tropospheric trough over the southeastern United States on 29 and 30 October. During the second trough interaction on 29 October, Sandy acquired warm seclusion characteristics, which contributed to its secondary intensity peak before landfall (Galarneau et al. 2013; Dan et al. 2015).

Galarneau et al. (2013) concluded that the track of Sandy was critical to its intensification on 29 October. Sandy’s northwest motion allowed it to axisymmetrize lower-tropospheric potential vorticity (PV) generated over the Gulf Stream into its inner core. This finding, in conjunction with previous studies showing that ET is highly sensitive to the tropical cyclone track relative to a mid-latitude trough (e.g., Hanley et al. 2001; Hart et al. 2006), prompt an investigation into how realistic changes in Sandy’s track relative to the mid-latitude trough and the Gulf Stream would have affected the structural evolution of Sandy before landfall.

We investigate a variety of potential structural evolutions of Hurricane Sandy using high-resolution Weather Research and Forecasting (WRF) simulations.  This requires choosing representative global model forecasts for the WRF initial and boundary conditions. We employ four global ensemble prediction systems: ECMWF, NCEP, UKMO, and CMC.  To select global model forecasts that are representative of different storm outcomes, we first perform regression mixture-model clustering (Gaffney et al. 2007) to partition the complete set of ensemble forecasts of Sandy. We use forecasts initialized at 00 UTC 25 October and verifying in a 60-hour segment between 00 UTC 28 October and 12 UTC 30 October (Fig. 1a; Kowaleski and Evans 2016). Each track cluster is associated with a unique structural evolution in Cyclone Phase Space (Hart 2003; Fig 1b). We then select ECMWF ensemble members that take similar tracks to each cluster-mean track (Fig. 1a) to drive the high-resolution WRF simulations. Intercomparisons of these simulations are used to elucidate the factors leading to differences in the evolution of Hurricane Sandy.

We also run two control simulations to compare to the representative cluster simulations. The first control simulation uses ECMWF ERA-Interim Reanalysis data for the initial and lateral boundary conditions. The second control simulation uses an ECMWF ensemble member that has a similar track and synoptic evolution to the observed evolution of Sandy. WRF simulations used in this study are triple-nested with two vortex-following nests and a 4 kilometer innermost nest. All simulations are initialized at 00 UTC 27 October and run through 00 UTC 1 November.

After all simulations are run, we investigate how the structural evolution of Sandy before landfall varies with storm track. Plots and cross sections of temperature, equivalent potential temperature, vertical motion, and divergence are analyzed to determine differences in structural evolution among simulations.

Differences in structural evolution among simulations are quantified using calculations of Eliassen-Palm (EP) heat and momentum flux vectors and Eddy PV flux vectors (Molinari et al. 1995; Hart et al. 2006). We examine how the EP and Eddy PV fluxes, and the secondary circulation response to these forcings, vary with differences in storm track relative to the mid-latitude trough. For each simulation, we show whether the EP and Eddy PV flux evolutions and the secondary circulation response are more similar to the warm seclusion evolution or the pure cold-core evolution diagnosed by Hart et al. (2006).

We also analyze how differences in the track of Sandy relative to the Gulf Stream affect its ET process. We show how changes in the track of Sandy affect the frontogenesis and PV generation along the Gulf Stream diagnosed by Galarneau et al. (2013). Calculations of PV and PV flux are used to show the relationship between the track of Sandy and how cyclonic PV generated along the frontogenesis axis is axisymmeterized into the core of Sandy. 



Dan, F. U., L. I. Pengyuan, and F. U. Gang, 2015: An observational and modeling study of extratropical transition of Hurricane Sandy in 2012. Journal of Ocean University of China, 14, 783-794, doi: http://dx.doi/org/10.1007/s11802-015-2770-2.

Gaffney, S. J., A. W. Robinson, P. Smith, S. J. Camargo, and M. Ghil, 2007: Probabilistic clustering of extratropical cyclones using regression mixture models. Climate Dynamics, 29, 423-440, doi: http://dx.doi.org/10.1007/s00382-007-0235-z.

Galarneau, T. J., C. A. Davis, and M. A. Shapiro, 2013: Intensification of Hurricane Sandy (2012) through Extratropical Warm Core Seclusion. Mon. Wea. Rev., 141, 4296-4321, doi: http://dx.doi.org/10.1175/MWR-D-13.00181.1.

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Hart, R. E., 2003: A Cyclone Phase Space Derived from Thermal Wind and Thermal Asymmetry. Mon. Wea. Rev., 131, 585-616, doi: 10.1175/1520-0493(2003)131<0585:ACPSDF>2.0.CO;2.

Hart, R. E., J. L. Evans, and C. Evans, 2006: Synoptic composites of the extratropical transition life cycle of North Atlantic tropical cyclones: factors determining posttransition evolution. Mon. Wea. Rev., 134, 553-578, doi: http://dx.doi.org/10.1175/MWR3082.1.

Kowaleski, A. M. and J. L. Evans, 2016: Regression mixture model clustering of multi-model ensemble forecasts of Hurricane Sandy: Partition characteristics. Mon. Wea. Rev (In press).

Molinari, J., S. Skubis, and D. Vollaro, 1995: External influences on hurricane intensity. Part III: Potential vorticity structure. J. Atmos. Sci., 52, 3593-3606, doi: http://dx.doi.org/10.1175/1520-0469(1995)052<3593:EIOHIP>2.0.CO;2.

Figure 1. For 60-hour track forecast segments initialized at 00 UTC 25 October and verifying between 00 UTC 28 October and 12 UTC 30 October: (a) Mean track per track cluster and (b) mean Cyclone Phase Space path per track cluster. Dots indicate storm position and storm structure at 00 UTC 30 October. The most populous cluster (magenta) is bolded. The best-track and the Cyclone Phase Space path calculated from ECMWF ERA-Interim reanalysis data are shown in black.

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