Statistical Modeling of Spatial Extremes

The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This article reviews recent progress in the statistical modeling of spatial extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The main types of statistical models thus far proposed, based on latent variables, on copulas and on spatial max-stable processes, are described and then are compared by application to a data set on rainfall in Switzerland. Whereas latent variable modeling allows a better fit to marginal distributions, it fits the joint distributions of extremes poorly, so appropriately-chosen copula or max-stable models seem essential for successful spatial modeling of extremes.Comment: Published in at http://dx.doi.org/10.1214/11-STS376 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Rejoinder to "Statistical Modeling of Spatial Extremes"

Rejoinder to "Statistical Modeling of Spatial Extremes" by A. C. Davison, S. A. Padoan and M. Ribatet [arXiv:1208.3378].Comment: Published in at http://dx.doi.org/10.1214/12-STS376REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Accuracy of core mass estimates in simulated observations of dust emission

We study the reliability of mass estimates obtained for molecular cloud cores using sub-millimetre and infrared dust emission. We use magnetohydrodynamic simulations and radiative transfer to produce synthetic observations with spatial resolution and noise levels typical of Herschel surveys. We estimate dust colour temperatures using different pairs of intensities, calculate column densities and compare the estimated masses with the true values. We compare these results to the case when all five Herschel wavelengths are available. We investigate the effects of spatial variations of dust properties and the influence of embedded heating sources. Wrong assumptions of dust opacity and its spectral index beta can cause significant systematic errors in mass estimates. These are mainly multiplicative and leave the slope of the mass spectrum intact, unless cores with very high optical depth are included. Temperature variations bias colour temperature estimates and, in quiescent cores with optical depths higher than for normal stable cores, masses can be underestimated by up to one order of magnitude. When heated by internal radiation sources the observations recover the true mass spectra. The shape, although not the position, of the mass spectrum is reliable against observational errors and biases introduced in the analysis. This changes only if the cores have optical depths much higher than expected for basic hydrostatic equilibrium conditions. Observations underestimate the value of beta whenever there are temperature variations along the line of sight. A bias can also be observed when the true beta varies with wavelength. Internal heating sources produce an inverse correlation between colour temperature and beta that may be difficult to separate from any intrinsic beta(T) relation of the dust grains. This suggests caution when interpreting the observed mass spectra and the spectral indices.Comment: Revised version, 17 pages, 17 figures, submitted to A&

The Two States of Star Forming Clouds

We examine the effects of self-gravity and magnetic fields on supersonic turbulence in isothermal molecular clouds with high resolution simulations and adaptive mesh refinement. These simulations use large root grids (512^3) to capture turbulence and four levels of refinement to capture high density, for an effective resolution of 8,196^3. Three Mach 9 simulations are performed, two super-Alfv\'enic and one trans-Alfv\'enic. We find that gravity splits the clouds into two populations, one low density turbulent state and one high density collapsing state. The low density state exhibits properties similar to non-self-gravitating in this regime, and we examine the effects of varied magnetic field strength on statistical properties: the density probability distribution function is approximately lognormal; velocity power spectral slopes decrease with field strength; alignment between velocity and magnetic field increases with field; the magnetic field probability distribution can be fit to a stretched exponential. The high density state is characterized by self-similar spheres; the density PDF is a power-law; collapse rate decreases with increasing mean field; density power spectra have positive slopes, P({\rho},k) \propto k; thermal-to-magnetic pressure ratios are unity for all simulations; dynamic-to-magnetic pressure ratios are larger than unity for all simulations; magnetic field distribution is a power-law. The high Alfv\'en Mach numbers in collapsing regions explain recent observations of magnetic influence decreasing with density. We also find that the high density state is found in filaments formed by converging flows, consistent with recent Herschel observations. Possible modifications to existing star formation theories are explored.Comment: 19 pages, 20 figure

The Density Variance Mach Number Relation in the Taurus Molecular Cloud

Supersonic turbulence in molecular clouds is a key agent in generating density enhancements that may subsequently go on to form stars. The stronger the turbulence - the higher the Mach number - the more extreme the density fluctuations are expected to be. Numerical models predict an increase in density variance with rms Mach number of the form: sigma^{2}_{rho/rho_{0}} = b^{2}M^{2}, where b is a numerically-estimated parameter, and this prediction forms the basis of a large number of analytic models of star formation. We provide an estimate of the parameter b from 13CO J=1-0 spectral line imaging observations and extinction mapping of the Taurus molecular cloud, using a recently developed technique that needs information contained solely in the projected column density field to calculate sigma^{2}_{rho/rho_{0}}. We find b ~ 0.48, which is consistent with typical numerical estimates, and is characteristic of turbulent driving that includes a mixture of solenoidal and compressive modes. More conservatively, we constrain b to lie in the range 0.3-0.8, depending on the influence of sub-resolution structure and the role of diffuse atomic material in the column density budget. We also report a break in the Taurus column density power spectrum at a scale of ~1pc, and find that the break is associated with anisotropy in the power spectrum. The break is observed in both 13CO and dust extinction power spectra, which, remarkably, are effectively identical despite detailed spatial differences between the 13CO and dust extinction maps. [ abridged ]Comment: 8 pages, 9 figures. Accepted for publication in A&

A method for reconstructing the variance of a 3D physical field from 2D observations: Application to turbulence in the ISM

We introduce and test an expression for calculating the variance of a physical field in three dimensions using only information contained in the two-dimensional projection of the field. The method is general but assumes statistical isotropy. To test the method we apply it to numerical simulations of hydrodynamic and magnetohydrodynamic turbulence in molecular clouds, and demonstrate that it can recover the 3D normalised density variance with ~10% accuracy if the assumption of isotropy is valid. We show that the assumption of isotropy breaks down at low sonic Mach number if the turbulence is sub-Alfvenic. Theoretical predictions suggest that the 3D density variance should increase proportionally to the square of the Mach number of the turbulence. Application of our method will allow this prediction to be tested observationally and therefore constrain a large body of analytic models of star formation that rely on it.Comment: 8 pages, 9 figures, accepted for publication in MNRA

On the interaction of a thin, supersonic shell with a molecular cloud

Molecular clouds (MCs) are stellar nurseries, however, formation of stars within MCs depends on the ambient physical conditions. MCs, over a free-fall time are exposed to numerous dynamical phenomena, of which, the interaction with a thin, dense shell of gas is but one. Below we present results from self-gravitating, 3-D smoothed particle hydrodynamics ({\small SPH}) simulations of the problem; seven realisations of the problem have been performed by varying the precollision density within the cloud, the nature of the post-collision shock, and the spatial resolution in the computational domain. Irrespective of the type of shock, a complex network of dense filaments, seeded by numerical noise, readily appears in the shocked cloud. Segregation of the dense and rarefied gas phases also manifests itself in a bimodal distribution of gas density. We demonstrate that the power-spectrum for rarefied gas is Kolomogorov like, while that for the denser gas is considerably steeper. As a corollary to the main problem, we also look into the possibly degenerative effect of the {\small SPH} artificial viscosity on the impact of the incident shell. It is observed that stronger viscosity leads to greater post-shock dissipation, that strongly decelerates the incident shock-front and promotes formation of contiguous structure, albeit on a much longer timescale. We conclude that too much viscosity is likely to enhance the proclivity towards gravitational boundedness of structure, leading to unphysical fragmentation.On the other hand, insufficient resolution appears to suppress fragmentation. Convergence of results is tested at both extremes, first by repeating the test case with more than a million particles and then with only half the number of particles in the original test case.Comment: 15 pages, 15 figures, and 1 Table; To appear in Monthly Notices to the RA