Multiscale aspects of the 26–27 April 2011 tornado outbreak. Part II: Environmental modifications and upscale feedbacks arising from latent processes

One of the most prolific tornado outbreaks ever documented occurred on 26–27 April 2011 and comprised three successive episodes of tornadic convection that culminated with the development of numerous long-track, violent tornadoes over the southeastern U.S. during the afternoon of 27 April. This notorious afternoon supercell outbreak was preceded by two quasi-linear convective systems (hereafter QLCS1 and QLCS2), the first of which was an anomalously severe nocturnal system that rapidly grew upscale during the previous evening. In this Part II, we use a series of RUC 1-h forecasts and output from convection-permitting WRF-ARW simulations configured both with and without latent heat release to investigate how environmental modifications and upscale feedbacks produced by the two QLCSs contributed to the evolution and exceptional severity of this multi-episode outbreak.QLCS1 was primarily responsible for amplifying the large-scale flow pattern, inducing two upper-level jet streaks, and promoting secondary surface cyclogenesis downstream from the primary baroclinic system. Upper-level divergence markedly increased after QLCS1 developed, which yielded strong isallobaric forcing that rapidly strengthened the low-level jet (LLJ) and vertical wind shear over the warm sector and contributed to the system’s upscale growth and notable severity. Moreover, QLCS2 modified the mesoscale environment prior to the supercell outbreak by promoting the downstream formation of a pronounced upper-level jet streak, altering the midlevel jet structure, and furthering the development of a highly ageostrophic LLJ over the Southeast. Collectively, the flow modifications produced by both QLCSs contributed to the notably favorable shear profiles present during the afternoon supercell outbreak.

Inclination Estimates from Off-Axis GRB Afterglow Modelling

For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is the afterglow from an ultra-relativistic jet. Where this afterglow is observed, it will likely be viewed off-axis, such as the afterglow following GW170817/GRB 170817A. The temporal behaviour of an off-axis observed GRB afterglow can be used to reveal the lateral jet structure, and statistical model fits can put constraints on the various model free-parameters. Amongst these parameters is the inclination of the system to the line of sight. Along with the GW detection, the afterglow modelling provides the best constraint on the inclination to the line-of-sight and can improve the estimates of cosmological parameters, for example, the Hubble constant, from GW-EM events. However, modelling of the afterglow depends on the assumed jet structure and—often overlooked—the effects of lateral spreading. Here we show how the inclusion of lateral spreading in the afterglow models can affect the estimated inclination of GW-EM events.

Inclination Estimates from Off-Axis GRB Afterglow Modelling

For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is the afterglow from an ultra-relativistic jet. Where this afterglow is observed, it will likely be viewed off-axis, such as the afterglow following GW170817/GRB 170817A. The temporal behaviour of an off-axis observed GRB afterglow can be used to reveal the lateral jet structure, and statistical model fits can put constraints on the various model free-parameters. Amongst these parameters is the inclination of the system to the line of sight. Along with the GW detection, the afterglow modelling provides the best constraint on the inclination to the line-of-sight and can improve the estimates of cosmological parameters e.g. the Hubble constant, from GW-EM events. However, modelling of the afterglow depends on the assumed jet structure and, often overlooked, the effects of lateral spreading. Here we show how the inclusion of lateral spreading in the afterglow models can affect the estimated inclination of GW-EM events.

Learning Latent Jet Structure

We summarize our recent work on how to infer on jet formation processes directly from substructure data using generative statistical models. We recount in detail how to cast jet substructure observables’ measurements in terms of Bayesian mixed membership models, in particular Latent Dirichlet Allocation. Using a mixed sample of QCD and boosted tt¯ jet events and focusing on the primary Lund plane observable basis for event measurements, we show how using educated priors on the latent distributions allows to infer on the underlying physical processes in a semi-supervised way.

Impact of scale, nuclear PDF and temperature variations on the interpretation of medium-modified jet production data from the LHC

In this paper we present a study of in-medium jet modifications performed with JEWEL and PYTHIA 6.4, focusing on the uncertainties related to variations of the perturbative scales and nuclear parton distribution functions (PDFs) and on the impact of the initial and crossover temperature variations of the medium. The simulations are compared to LHC data for the jet spectrum and the nuclear modification factor. We assess the interplay between the choice of nuclear PDFs and different medium parameters and study the impact of nuclear PDFs and the medium on the jet structure via the Lund plane.