Extreme Summer Convection in South America

Abstract

Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data are used to indicate mechanisms responsible for extreme summer convection over South America. The three-dimensional reflectivity field is analyzed to define three types of extreme echo, deep convective cores, wide convective cores, and broad stratiform regions. The location and timing of these echoes are sensitive to midlatitude synoptic disturbances crossing the Andes. At the leading edges of these disturbances the nocturnal South American low-level jet (SALLJ) transports moisture along the eastern edge of the Andes from the tropical to the subtropical part of the continent. Where the SALLJ rises over lower but steep mountains on the east side of the southern central Andes, deep and wide convective cores are triggered in the evening. When the SALLJ withdraws to the north as the disturbance passes, nocturnal triggering occurs in the northeastern foothills of the central Andes. Extreme convection over the Amazon basin takes the form of broad stratiform regions that evolve from systems with wide convective cores moving into the center of the region from both the southwest and northeast. The systems from the northeast form at the northeast coast and are likely squall lines. Along the coast of the Brazilian Highlands, diurnal/topographic forcing leads to daytime maxima of deep convective cores followed a few hours later by wide convective cores. Wide convective cores and broad stratiform regions form in the South Atlantic convergence zone (SACZ) with a diurnal cycle related to continental heating.

Lattice Boltzmann simulations of a strongly interacting two-dimensional Fermi gas

“…To this end, we define the amplitude b i (t) as the distance from the center where the density has dropped by a factor e −1 , and we initialize the particle distribution function according to (18,21) with δb i (0) ≃ 10 −2 or smaller. We then track the time evolution of the combinations δB(t), δQ(t) and perform a fit of this evolution using the analytically derived model functions (23,24), obtaining best-fit values for the coefficients w B , w Q , Γ B , Γ Q,0 , Γ Q,1 as a function of ω ⊥ τ R in the process. The extracted values for these coefficients are displayed in Fig.1 along with the analytically calculated results.…”

“…However, by inspecting the analytic solutions given in Eqns. (23), (24), one could try to engineer initial conditions for the cloud that would maximize the amplitude δ, thus presumably leading to a better signal to noise ratio for extracting Γ Q,1 in the hydrodynamic limit. We intend to pursue this direction in a follow-up study.…”

“…(20,23,24) in LB simulations at finite volume and resolution. These transient phenomena could be due to 'overtones' to the hydrodynamic sloshing, breathing and quadrupole modes, with higher frequencies and damping rates than the fundamental modes.…”

“…The non-hydrodynamic mode is a feature that is common to evolution equations beyond Navier-Stokes (such as second-order hydrodynamics, cf. [24,25]). …”

Longitudinal decorrelation of anisotropic flows in heavy-ion collisions at the CERN Large Hadron Collider

“…The anisotropies are characterized in terms of the Fourier coefficients of the azimuth distributions which are referred to as anisotropic flows or harmonic flows. Relativistic hydrodynamical models have been very successful in describing the observed anisotropic flows [5][6][7][8][9] and in understanding the space-time evolution of the QGP fireball. Detailed comparisons between hydrodynamical model calculations and experimental data on anisotropic flows have provided unprecedented constraints on the transport properties, such as the shear viscosity to entropy density ratio, of the hot and dense QGP formed in high-energy heavy-ion collisions.…”