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At least 307 records · Page 17

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Effects of Resolution and Spectral Nudging in Simulation the Effects of Wintertime Atmospheric River Landfalls in the Western US

Landfalling atmospheric rivers (ARs) play a crucial role in the climate of the US Pacific coast region as they are frequently related with heavy precipitation and flash flooding events. Thus, the capability of climate models to accurately simulate AR landfalls and their key hydrologic effects is an important practical concern for WUS, from flood forecasting to future water resources projections. In order to examine the effects of model configuration, including the resolution and spectral nudging, in simulating the climatology of key weather events in the conterminous US, a NASA team has performed a hindcast experiment using the GEOS5 global and the NU-WRF regional models for Nov 1999 - Oct 2010. This study examines the skill of these hindcasts, with different models and their configurations, in simulating key footprints of landfalling ARs in the WUS region. Using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis, we have analyzed the observed and simulated precipitation and temperature anomalies associated with wintertime AR landfalls along the US Pacific coast. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, and Taylor diagrams in four WUS Bukovsky regions. Results show that the AR-related anomalies of precipitation is more reliable than of surface temperatures. Model skill also varies according to regions. The AR temperature anomalies are well simulated in most of the WUS region except PNW. For precipitation, simulations with finer spatial resolution tend to generate larger spatial variability and agree better with the PRISM data in most regions. Such a resolution dependence of spatial variability is not found for temperatures; e.g., the MERRA2 reanalysis often outperforms, with similar spatial variability and higher pattern correlations with the PRISM data, finer-resolution NU-WRF runs in simulating temperature variations within subregions. Results from this study will be summarized to assist future (regional) climate experiments for climate change impact assessments and developing adaptationmitigation strategies, the key elements of the National Climate Assessment.

Simulation↗

Niche-DE: niche-differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions

Existing methods for analysis of spatial transcriptomic data focus on delineating the global gene expression variations of cell types across the tissue, rather than local gene expression changes driven by cell-cell interactions. We propose a new statistical procedure called niche-differential expression (niche-DE) analysis that identifies cell-type-specific niche-associated genes, which are differentially expressed within a specific cell type in the context of specific spatial niches. We further develop niche-LR, a method to reveal ligand-receptor signaling mechanisms that underlie niche-differential gene expression patterns. Niche-DE and niche-LR are applicable to low-resolution spot-based spatial transcriptomics data and data that is single-cell or subcellular in resolution.

59 BASIC BIOLOGICAL SCIENCES↗

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling. Dynamic spatial-temporal dependencies in traffic data make traffic flow forecasting to be a challenging task. Most existing research cannot model dynamic spatial and temporal correlations to achieve well-forecasting performance. The multi-head self-attention mechanism is a valuable method to capture dynamic spatial-temporal correlations, and combining it with graph convolutional networks is a promising solution. Therefore, we propose a multi-head self-attention spatiotemporal graph convolutional network (MSASGCN) model. It can effectively capture local correlations and potential global correlations of spatial structures, can handle dynamic evolution of the road network, and, in the time dimension, can effectively capture dynamic temporal correlations. Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. Compared with advanced traffic flow forecasting methods, our model also has a performance improvement and a more stable prediction performance. We also discuss some problems and challenges in traffic forecasting.

Cao, Yang↗

Macro vs. Micro: Relating the Spectral Properties of Vesta and the HED Meteorite

We present the main results obtained comparing the visible-near infrared (VIS-NIR) spectra Vesta s surface with howardites, eucrites, diogenites (HED). HEDs are commonly associated with Vesta s composition based on spectral similarities. Because of such association, much effort is being made to merge the information from HEDs as well as Vestoids - with that from Vesta to characterize the lithologic diversity of the surface of this asteroid and to infer clues regarding its thermal history. However, while the HEDs are a class of meteorites well studied in the laboratory, the only spectral data available for Vesta until now were telescopic observations which are limited in terms of observation conditions, spatial resolution and Signal to Noise Ratio. The Dawn spacecraft, orbiting around Vesta since July 2011, is performing detailed observations of this body and thus improving our knowledge of its properties. Dawn s scientific payload includes an imaging spectrometer, VIR-MS, sensitive to the VIS-NIR spectral range. VIR-MS began acquiring spectra during the approach phase started in May 2011 and will continue its observations through July 2012 when the spacecraft will depart Vesta to travel to Ceres. The VIR-MS spatial resolution depends upon the mission phase (approach, survey, high altitude, low altitude). However, spectra acquired by VIR-MS have already exceeded the spatial resolution of ground-based telescopic observations, with resolution in the approach phase ranging from 2.5 up to 0.8 km/pixel. Moreover, the observations are uniformly distributed in latitude and longitude allowing us to have a global view of Vesta s crust spectral properties. Using the information provided by VIR spectra, we studied the distribution of the spectral heterogeneities on the surface and we used our findings to perform a comparison with HEDs spectra in the VIS-NIR spectral range searching for analogies and/or incompatibilities. In our analysis, we focused on a method to compare the results obtained at microscopic scale on HEDs samples and the one obtained at macroscopic scale on the surface of Vesta. Finally, we discuss our results in the context of vestan thermal history. The intent of this study is to improve our understanding of the connection between Vesta and the HED samples, which is one of the primary Dawn scientific objectives. This work is supported by an Italian Space Agency (ASI) grant and by NASA through the Dawn project and a Dawn at Vesta Participating Scientist grant.

Ammannito, E.↗

Comparison of satellite based cloud retrieval methods for cirrus and stratocumulus

One difficulty in using satellite remote sensing data is the spatial variability of cloud properties on scales smaller than most meteorological satellite fields of view (approx. 4 to 8 km). The variation is examined of satellite derived cloud cover as a function of the satellite sensor spatial resolution for seven cloud cover retrieval methods: (1) Reflectance threshold; (2) Temperature threshold; (3) ISCCP; (4) HBTM (Hybrid Bispectral Threshold Method); (5) NCLE; (6) Spatial coherence; and (7) Functional Box Counting. The first two methods are simple single spectral thresholds which specify a satellite pixel as cloud filled if the measured reflectance is greater than the threshold, or if the measured equivalent blackbody temperature is less than the threshold. The next three methods are bispectral, using one visible wavelength window channel and one thermal infrared wavelength window. The final two algorithms rely on the spatial variability within the cloud field to determine cloud cover. Spatial coherence assumes only that the cloud field occurs in a single layer and that the clouds are optically thick in the infrared window. LANDSAT Thematic Mapper (TM) data is used to test the spatial resolution dependence of the cloud algorithms. The ISCCP bispectral threshold applied to the full resolution data is used as the reference or truth cloud cover, after which the retrieval methods are applied to the spatial resolutions. Studies of the fraction of pixels in the scene at cloud edge, and of the profile of reflectance and temperature near cloud edges indicate an uncertainty in the reference cloud fraction of 1 to 5 percent.

Parker, Lindsay↗

Influence of Entrainment on Centimeter-Scale Cloud Microphysics in Marine Stratocumulus Clouds Observed during CSET

Abstract Cloud microphysical relationships observed during the Cloud System Evolution in the Trades (CSET) campaign held between Northern California and Hawaii were analyzed to study the effects of entrainment and subsequent mixing of free-tropospheric and cloudy air on cloud microphysical properties of marine stratocumulus clouds. The data measured by Holographic Detector for Clouds (HOLODEC) were extensively used because they could provide the 3D positions and sizes of droplets within sample volume on the centimeter scale, making it possible to explore the 3D spatial distribution of droplets, which has not been possible for conventional cloud probes. This study focused on analyzing the 3D spatial distribution of droplets and visual traits of inhomogeneous mixing and on quantifying the relationship between 3D spatial distributions and traits of inhomogeneous mixing. Two types of spatial distributions are compared. The first is measured droplet spatial distribution and the second type is generated randomly distributed droplets using the Monte Carlo approach, that is, to analyze whether or not clustering is strong enough to classify as a clustered distribution for a hologram. The difference between the two types of spatial distributions depends on whether they are affected by entrainment and mixing. The holograms observed near the cloud top, where the effects of entrainment and mixing would be immediate, showed relatively high confidence in the significance test for spatially clustered populations of droplets. Moreover, spatially clustered holograms appeared to exhibit stronger visual traits of inhomogeneous mixing than perfectly randomly distributed holograms only when observed near the cloud top. On the other hand, these characteristics did not appear for holograms observed deeper into the cloud where the effects of entrainment and mixing would be reduced. Such 3D structural characteristics of droplet distributions seem to be consistent with vertical circulation mixing.

Meteorology & Atmospheric Sciences↗

The effects of context on multidimensional spatial cognitive models

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Dupnick, E. G.↗

Carrier generation, recombination, trapping, and transport in semiconductors with position-dependent composition

The spatial variation of the chemical composition of a semiconductor modifies the ideal one-electron energy band model as well as the Shockley equations for carrier recombination and transport in two important ways. The random component of the spatial variation introduces localized states in the energy gap by perturbing the band states. The nonrandom component gives rise to the position dependences of the conduction and valence band edges or the electron affinity and the energy gap. This paper gives the modifications of the Shockley equations from these two effects as well as an example of the steady-state recombination rate from distributed gap states in junction solar cells

Sah, C.-T.↗

Effects of Spatial Resolution on the Simulated Dust Aerosol Lifecycle: Implications for Dust Event Magnitude and Timing in the NASA GEOS-5 AGCM

The NASA GEOS-5 atmospheric transport model simulates global aerosol distributions with an online aerosol module. GEOS-5 may be run at various horizontal spatial resolutions depending on the research application. For example, long integration climate simulations are typically run at 2 deg or 1 deg grid spacing, whereas aerosol reanalysis and forecasting applications may be performed at O.5 deg or 0.25 deg resolutions. In this study, we assess the implications of varying spatial resolution on the simulated aerosol fields, with a particular focus on dust. Dust emissions in GEOS-5 are calculated with one of two parameterizations, one based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GO CART) model and another based on the Dust Entrainment and Deposition (DEAD) model. Emission fluxes are parameterized in terms of the surface wind speed, either the 10-m (GO CART) or friction (DEAD) wind speed. We consider how surface wind speeds and thus the dust emission rates are a function of the model spatial resolution. We find that spatial resolution has a significant effect on the magnitude of dust emissions, as higher resolution versions of the model have typically higher surface wind speeds. Utilizing space-borne observations from MISR, MODIS, and CALIOP, we find that simulated Aerosol Optical Thickness (AOT) distributions respond differently to spatial resolution over the African and Asian source regions, highlighting the need to regional dust emission tuning. When compared to ground-based observations from AERONET, we found improved timing of dust events with as spatial resolution was increased. In an attempt to improve the representation of the dust aerosol lifecycle at coarse resolutions, we found that incorporating the effects of sub-grid wind variability in a course resolution simulation led to improved agreement with observed AOT magnitudes, but did not impact the timing of simulated dust events.

Nowottnick, E.↗

A semi-analytical model of RF condensation that can handle localized power depositions

A nonlinear effect, RF (radio frequency) condensation, can be used to facilitate RF stabilization of magnetic islands. Previously studied semi-analytical models for RF condensation are suited mainly for broad deposition profiles and are unable to handle power depositions that are localized in the interior of a magnetic island. The power deposition profile of electron cyclotron waves, in particular, can be highly localized near a cyclotron resonance. Here, a model is developed that can handle both localized profiles and broad profiles. This allows a comparison of RF condensation for narrow vs broad deposition profiles, and it allows a study of the dependence of RF condensation of localized deposition profiles on key parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Role of Intersections in Fracture Connectivity

Networks of intersecting fractures often provide the flow paths through subsurface reservoirs. Assessing network connectivity is challenging because fracture intersections compose a vanishingly small fraction of the network void volume. In this paper, motivated by 3D X-ray imaging of the simplest element of fracture network, that is, two orthogonal fractures, we perform a percolation and finite-size scaling analysis to study the connectivity provided by fracture intersections. The conditions when an intersection enhances connectivity across a sample depend on spatial correlations in the fracture aperture distributions, on the stress state, and on the direction of flow. Here we consider three flow directions: (a) across intersections, (b) parallel to intersections and (c) around corners. For (a), intersections provide minimal enhancement of connectivity because they contribute little additional void area. For (b), intersections increase the probability of a connected path near threshold by enabling 3D connected pathways that are not possible in parallel fractures. Flow around corners, (c), is fundamentally the result of the intersection connecting two fractures in series and spatial correlations are broken around corners, suppressing the connectivity relative to (a). When the connected fractures are stressed equally, a joint percolation threshold emerges that continues to have scale invariance. However, when the fractures are stressed unequally, the system has mixed percolation without clearly defined percolation thresholds. In all cases, percolation probabilities are found to be scale dependent which has important consequences for the connectivity of larger fracture networks composed of the fundamental element studied here.

02 PETROLEUM↗

Insights into the Thermal Expansion of Amorphous Polymers

Here, we investigated the thermal expansion of amorphous polystyrene (PS) and poly(methyl methacrylate) (PMMA) homopolymers using the temperature dependence of spatial electron-density correlations. The strong and broad X-ray interference maxima arising from inter- and intramolecular correlation distances were distinct, maintaining their shape during the heating of the samples to 250 °C. Three maxima characteristic of electron density correlations between the backbones, substituents along the chain, and repeat-units were observed. A remarkable temperature dependence was identified in the largest correlation distances arising from the intermolecular interactions. Based on the temperature dependence of the correlation distances, the coefficients of molecular expansion were very close to the coefficients of thermal expansion. This study provides a simple yet accurate way to correlate macroscopic volume expansions with the molecular expansion obtained from wide-angle X-ray scattering (WAXS) data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction and experimental observation of damage dependent damping in laminated composite beams

The equations of motion are developed for laminated composite beams with load-induced matrix cracking. The damage is accounted for by utilizing internal state variables. The net result of these variables on the field equations is the introduction of both enhanced damping, and degraded stiffness. Both quantities are history dependent and spatially variable, thus resulting in nonlinear equations of motion. It is explained briefly how these equations may be quasi-linearized for laminated polymeric composites under certain types of structural loading. The coupled heat conduction equation is developed, and it is shown that an enhanced Zener damping effect is produced by the introduction of microstructural damage. The resulting equations are utilized to demonstrate how damage dependent material properties may be obtained from dynamic experiments. Finaly, experimental results are compared to model predictions for several composite layups.

Allen, D. H.↗

The timbre of Hawking gravitons: an effective description of energy transport from holography

Planar black holes in AdS, which are holographically dual to compressible relativistic fluids, have a long-lived phonon mode that captures the physics of attenuated sound propagation and transports energy in the plasma. We describe the open effective field theory of this fluctuating phonon degree of freedom. The dynamics of the phonon is encoded in a single scalar field whose gravitational coupling has non-trivial spatial momentum dependence. This description fits neatly into the paradigm of classifying gravitational modes by their Markovianity index, depending on whether they are long-lived. The sound scalar is a non-Markovian field with index 3 - d for a d-dimensional fluid. We reproduce (and extend) the dispersion relation of the holographic sound mode to quartic order in derivatives, constructing in the process the effective field theory governing its attenuated dynamics and associated stochastic fluctuations. We also remark on the presence of additional spatially homogeneous zero modes in the gravitational problem, which remain disconnected from the phonon Goldstone mode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. Here, we also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

97 MATHEMATICS AND COMPUTING↗

Science support for the Earth radiation budget experiment

The work undertaken as part of the Earth Radiation Budget Experiment (ERBE) included the following major components: The development and application of a new cloud retrieval scheme to assess errors in the radiative fluxes arising from errors in the ERBE identification of cloud conditions. The comparison of the anisotropy of reflected sunlight and emitted thermal radiation with the anisotropy predicted by the Angular Dependence Models (ADM's) used to obtain the radiative fluxes. Additional studies included the comparison of calculated longwave cloud-free radiances with those observed by the ERBE scanner and the use of ERBE scanner data to track the calibration of the shortwave channels of the Advanced Very High Resolution Radiometer (AVHRR). Major findings included: the misidentification of cloud conditions by the ERBE scene identification algorithm could cause 15 percent errors in the shortwave flux reflected by certain scene types. For regions containing mixtures of scene types, the errors were typically less than 5 percent, and the anisotropies of the shortwave and longwave radiances exhibited a spatial scale dependence which, because of the growth of the scanner field of view from nadir to limb, gave rise to a view zenith angle dependent bias in the radiative fluxes.

Coakley, James A., Jr.↗