Whirling Hexagons and Defect Chaos in Hexagonal Non-Boussinesq Convection

We study hexagon patterns in non-Boussinesq convection of a thin rotating layer of water. For realistic parameters and boundary conditions we identify various linear instabilities of the pattern. We focus on the dynamics arising from an oscillatory side-band instability that leads to a spatially disordered chaotic state characterized by oscillating (whirling) hexagons. Using triangulation we obtain the distribution functions for the number of pentagonal and heptagonal convection cells. In contrast to the results found for defect chaos in the complex Ginzburg-Landau equation and in inclined-layer convection, the distribution functions can show deviations from a squared Poisson distribution that suggest non-trivial correlations between the defects.Comment: 4 mpg-movies are available at http://www.esam.northwestern.edu/~riecke/lit/lit.html submitted to New J. Physic

Mean flow and spiral defect chaos in Rayleigh-Benard convection

We describe a numerical procedure to construct a modified velocity field that does not have any mean flow. Using this procedure, we present two results. Firstly, we show that, in the absence of mean flow, spiral defect chaos collapses to a stationary pattern comprising textures of stripes with angular bends. The quenched patterns are characterized by mean wavenumbers that approach those uniquely selected by focus-type singularities, which, in the absence of mean flow, lie at the zig-zag instability boundary. The quenched patterns also have larger correlation lengths and are comprised of rolls with less curvature. Secondly, we describe how mean flow can contribute to the commonly observed phenomenon of rolls terminating perpendicularly into lateral walls. We show that, in the absence of mean flow, rolls begin to terminate into lateral walls at an oblique angle. This obliqueness increases with Rayleigh number.Comment: 14 pages, 19 figure

Dust Devil Sediment Transport: From Lab to Field to Global Impact

The impact of dust aerosols on the climate and environment of Earth and Mars is complex and forms a major area of research. A difficulty arises in estimating the contribution of small-scale dust devils to the total dust aerosol. This difficulty is due to uncertainties in the amount of dust lifted by individual dust devils, the frequency of dust devil occurrence, and the lack of statistical generality of individual experiments and observations. In this paper, we review results of observational, laboratory, and modeling studies and provide an overview of dust devil dust transport on various spatio-temporal scales as obtained with the different research approaches. Methods used for the investigation of dust devils on Earth and Mars vary. For example, while the use of imagery for the investigation of dust devil occurrence frequency is common practice for Mars, this is less so the case for Earth. Modeling approaches for Earth and Mars are similar in that they are based on the same underlying theory, but they are applied in different ways. Insights into the benefits and limitations of each approach suggest potential future research focuses, which can further reduce the uncertainty associated with dust devil dust entrainment. The potential impacts of dust devils on the climates of Earth and Mars are discussed on the basis of the presented research results

A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of the AVHRR AOT is increased during any particular month, along with its interannual correlation with the TOMS AI The latter easily exceeds the sampling threshold due to its greater ability to infer the aerosol load in the presence of clouds. Whether the TOMS AI should be regarded as a more reliable indicator of interannual variability depends upon the extent of contamination by sub-pixel clouds

Constraining the magnitude of the global dust cycle by minimizing the difference between a model and observations

Current estimates of global dust emission vary by over a factor of two. Here, we use multiple data types and a worldwide array of stations combined with a dust model to constrain the magnitude of the global dust cycle for particles with radii between 0.1 and 8 μm. An optimal value of global emission is calculated by minimizing the difference between the model dust distribution and observations. The optimal global emission is most sensitive to the prescription of the dust source region. Depending upon the assumed source, the agreement with observations is greatest for global, annual emission ranging from 1500 to 2600 Tg. However, global annual emission between 1000 and 3000 Tg remains in agreement with the observations, given small changes in the method of optimization. Both ranges include values that are substantially larger than calculated by current dust models. In contrast, the optimal fraction of clay particles (whose radii are less than 1 μm) is lower than current model estimates. The optimal solution identified by a combination of data sets is different from that identified by any single data set and is more robust. Uncertainty is introduced into the optimal emission by model biases and the uncertain contribution of other aerosol species to the observations

Phe 84 deletion of the PMP22 gene associated with hereditary motor and sensory neuropathy HMSN III with multiple cranial neuropathy: clinical, neurophysiological and magnetic resonance imaging findings

Hereditary motor and sensory neuropathy (HMSN) is a heterogeneous group of peripheral neuropathies which are diagnosed on the basis of clinical, electrophysiological and neuropathological findings. Among the hypertrophic demyelinating neuropathies, HMSN III is the most severe. It is often associated with de novo mutations in the genes encoding for peripheral myelin proteins. While peripheral nerve hypertrophy is an expected finding in HMSN III, cranial, nerve hypertrophy is exceptional. Here we describe a mutation in the PMP22 gene in a 19-year-old man with infantile onset of sensory motor polyneuropathy without family history and multiple cranial nerve hypertrophy shown by cranial magnetic resonance imaging