An unsolved problem in plasma turbulence is how energy is dissipated at small scales. Particle collisions are too infrequent in hot plasmas to provide the necessary dissipation. Simulations either treat the fluid scales and impose an ad hoc form of dissipation (e.g., resistivity) or consider dissipation arising from resonant damping of small amplitude disturbances where damping rates are found to be comparable to that predicted from linear theory. Here, we report kinetic simulations that span the macroscopic fluid scales down to the motion of electrons. We find that turbulent cascade leads to generation of coherent structures in the form of current sheets that steepen to electron scales, triggering strong localized heating of the plasma. The dominant heating mechanism is due to parallel electric fields associated with the current sheets, leading to anisotropic electron and ion distributions which can be measured with NASA's upcoming Magnetospheric Multiscale mission. The motion of coherent structures also generates waves that are emitted into the ambient plasma in form of highly oblique compressional and shear Alfven modes. In 3D, modes propagating at other angles can also be generated. This indicates that intermittent plasma turbulence will in general consist of both coherent structures and waves. However, the current sheet heating is found to be locally several orders of magnitude more efficient than wave damping and is sufficient to explain the observed heating rates in the solar wind.

Global hybrid (electron fluid, kinetic ions) and fully kinetic simulations of the magnetosphere have been used to show surprising interconnection between shocks, turbulence, and magnetic reconnection. In particular, collisionless shocks with their reflected ions that can get upstream before retransmission can generate previously unforeseen phenomena in the post shocked flows: (i) formation of reconnecting current sheets and magnetic islands with sizes up to tens of ion inertial length. (ii) Generation of large scale low frequency electromagnetic waves that are compressed and amplified as they cross the shock. These "wavefronts" maintain their integrity for tens of ion cyclotron times but eventually disrupt and dissipate their energy. (iii) Rippling of the shock front, which can in turn lead to formation of fast collimated jets extending to hundreds of ion inertial lengths downstream of the shock. The jets, which have high dynamical pressure, "stir" the downstream region, creating large scale disturbances such as vortices, sunward flows, and can trigger flux ropes along the magnetopause. This phenomenology closes the loop between shocks, turbulence, and magnetic reconnection in ways previously unrealized. These interconnections appear generic for the collisionless plasmas typical of space and are expected even at planar shocks, although they will also occur at curved shocks as occur at planets or around ejecta. V C 2014 AIP Publishing LLC. [http://dx.

High resolution kinetic simulations of collisionless plasma driven by shear show the development of turbulence characterized by dynamic coherent sheetlike current density structures spanning a range of scales down to electron scales. We present evidence that these structures are sites for heating and dissipation, and that stronger current structures signify higher dissipation rates. Evidently, kinetic scale plasma, like magnetohydrodynamics, becomes intermittent due to current sheet formation, leading to the expectation that heating and dissipation in astrophysical and space plasmas may be highly nonuniform and patchy.

Three-dimensional kinetic simulations of magnetic reconnection for parameter regimes relevant to the magnetopause current layer feature the development of turbulence, driven by the magnetic and velocity shear, and dominated by coherent structures including flux ropes, current sheets, and flow vortices. Here, we propose a new approach for computing the global reconnection rate in the presence of this complexity. The mixing of electrons originating from separate sides of the magnetopause layer is used as a proxy to rapidly identify the magnetic topology and track the evolution of magnetic flux. The details of this method are illustrated for an asymmetric current layer relevant to the subsolar magnetopause and for a flow shear dominated layer relevant to the lower latitude magnetopause. While the three-dimensional reconnection rates show a number of interesting differences relative to the corresponding two-dimensional simulations, the time scale for the energy conversion remains very similar. These results suggest that the mixing of field lines between topologies is more easily influenced by kinetic turbulence than the physics responsible for the energy conversion.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi‐model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA‐2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

Abstract. The United Nations Framework Convention on Climate Change (UNFCCC) invited the scientific community to explore the impacts of a world in which anthropogenic global warming is stabilized at only 1.5 • C above preindustrial average temperatures. We present a projection of future tropical cyclone statistics for both 1.5 and 2.0 • C stabilized warming scenarios with direct numerical simulation using a high-resolution global climate model. As in similar projections at higher warming levels, we find that even at these low warming levels the most intense tropical cyclones become more frequent and more intense, while simultaneously the frequency of weaker tropical storms is decreased. We also conclude that in the 1.5 • C stabilization, the effect of aerosol forcing changes complicates the interpretation of greenhouse gas forcing changes.

Abstract. It has become increasingly common for researchers to utilize methods that identify weather features in climate models. There is an increasing recognition that the uncertainty associated with choice of detection method may affect our scientific understanding. For example, results from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) indicate that there are a broad range of plausible atmospheric river (AR) detectors and that scientific results can depend on the algorithm used. There are similar examples from the literature on extratropical cyclones and tropical cyclones. It is therefore imperative to develop detection techniques that explicitly quantify the uncertainty associated with the detection of events. We seek to answer the following question: given a “plausible” AR detector, how does uncertainty in the detector quantitatively impact scientific results? We develop a large dataset of global AR counts, manually identified by a set of eight researchers with expertise in atmospheric science, which we use to constrain parameters in a novel AR detection method. We use a Bayesian framework to sample from the set of AR detector parameters that yield AR counts similar to the expert database of AR counts; this yields a set of “plausible” AR detectors from which we can assess quantitative uncertainty. This probabilistic AR detector has been implemented in the Toolkit for Extreme Climate Analysis (TECA), which allows for efficient processing of petabyte-scale datasets. We apply the TECA Bayesian AR Detector, TECA-BARD v1.0.1, to the MERRA-2 reanalysis and show that the sign of the correlation between global AR count and El Niño–Southern Oscillation depends on the set of parameters used.

Three-dimensional brain imaging through cutting-edge MRI technology allows assessment of physical and chemical tissue properties at sub-millimeter resolution. In order to improve brain understanding as part of diagnostic tasks using MRI images, other imaging modalities to obtain deep cerebral structures and cytoarchitectural boundaries have been investigated. Under availability of postmortem samples, the fusion of MRI to brain histology supports more accurate description of neuroanatomical structures since it preserves microscopic entities and reveal fine anatomical details, unavailable otherwise. Nonetheless, histological processing causes severe tissue deformation and loss of the brain original 3D conformation, preventing direct comparisons between MRI and histology. This paper proposes an interactive computational pipeline designed to register multimodal brain data and enable direct histology-MRI correlation. Our main contribution is to develop schemes for brain data fusion, distortion corrections, using appropriate diffeomorphic mappings to align the 3D histological and MRI volumes. We describe our pipeline and preliminary developments of scalable processing schemes for highresolution images. Tests consider a postmortem human brain, and include qualitatively and quantitatively results, such as 3D visualizations and the Dice coefficient (DC) be-tween brain structures. Preliminary results show promising DC values when comparing our scheme results to manually labeled neuroanatomical regions defined by a neurosurgeon on MRI and histology data sets. DC was computed for the left caudade gyrus (LC), right hippocampus (RH) and lateral ventricles (LV).