bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimates of Present and Future Asthma Emergency Department Visits Associated With Exposure to Oak, Birch, and Grass Pollen in the United States
Authors: Neumann James E. , Anenberg Susan C. , Weinberger Kate R. , Amend Meredith , Gulati Sahil , Crimmins Allison , Roman Henry , Fann Neal , Kinney Patrick L. 
Published: December 2018

AbstractPollen is an important environmental cause of allergic asthma episodes. Prior work has established a proof of concept for assessing projected climate change impacts on future oak pollen exposure and associated health impacts. This paper uses additional monitor data and epidemiologic functions to extend prior analyses, reporting new estimates of the current and projected future health burden of oak, birch, and grass pollen across the contiguous United States. Our results suggest that tree pollen in the spring currently accounts for between 25,000 and 50,000 pollen‐related asthma emergency department (ED) visits annually (95% confidence interval: 14,000 to 100,000), roughly two thirds of which occur among people under age 18. Grass pollen in the summer season currently accounts for less than 10,000 cases annually (95% confidence interval: 4,000 to 16,000). Compared to a baseline with 21st century population growth but constant pollen, future temperature and precipitation show an increase in ED visits of 14% in 2090 for a higher greenhouse gas emissions scenario, but only 8% for a moderate emissions scenario, reflecting projected increases in pollen season length. Grass pollen, which is more sensitive to changes in climatic conditions, is a primary contributor to future ED visits, with the largest effects in the Northeast, Midwest, and Southern Great Plains regions. More complete assessment of the current and future health burden of pollen is limited by the availability of data on pollen types (e.g., ragweed), other health effects (e.g., other respiratory disease), and economic consequences (e.g., medication costs).
Increasingly Powerful Tornadoes in the United States
Authors: Elsner James B. , Fricker Tyler , Schroder Zoe 
Published: December 2018

AbstractStorm reports show an upward trend in the power of tornadoes. Quantifying the magnitude of the increase is difficult given diurnal and seasonal influences on tornadoes embedded within natural variations and made worse by changes in practices for rating damage. Here the authors solve this problem by fitting a statistical model to a metric of tornado power during the period 1994–2016. They find an increase of 5.5% [(4.6, 6.5%), 95% CI] per year in power controlling for the diurnal cycle, seasonality, natural climate variability, and the switch to a new damage scale. A portion of the trend is attributed to long‐term changes in convective storm environments involving dynamic and thermodynamic variables and their interactions. Increasing power is occurring in environments where the effect of convective available potential energy is enhanced by increasing vertical wind shear. However, a majority of the trend is not attributable to changes in storm environments.
Recurrence‐Based Quantification of Dynamical Complexity in the Earth's Magnetosphere at Geospace Storm Timescales
Authors: Donner Reik V. , Balasis Georgios , Stolbova Veronika , Georgiou Marina , Wiedermann Marc , Kurths Jürgen 
Published: December 2018

AbstractMagnetic storms are the most prominent global manifestations of out‐of‐equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we utilize several innovative data analysis techniques enabling a quantitative nonlinear analysis of the nonstationary behavior of the disturbance storm time (Dst) index together with some of the main drivers of its temporal variability, the VBSouth electric field component, the vertical component of the interplanetary magnetic field, Bz, and the dynamic pressure of the solar wind, Pdyn. Using recurrence quantification analysis and recurrence network analysis, we obtain several complementary complexity measures that serve as markers of different physical processes underlying quiet and storm time magnetospheric dynamics. Our approach discriminates the magnetospheric activity in response to external (solar wind) forcing from primarily internal variability and highlights the case‐specific nature of interdependencies between the Dst index and its potential drivers that need to be accounted for in future improved space weather forecasting models.
Empirical Modeling of the Equatorward Boundary of Auroral Precipitation Using DMSP and DE 2
Authors: Landry R. G. , Anderson P. C. 
Published: December 2018

AbstractA new model of the equatorward boundary of the diffuse aurora has been developed using observations of precipitating particles made by the Defense Meteorological Satellite Program (DMSP) from 1987 to 2012 as well as Dynamics Explorer 2 (DE 2), which operated from August 1981 to February 1983. Using a local multilinear regression algorithm, we investigated the use of different combinations of magnetometer indices and solar wind coupling functions with different averaging periods and weights to find the best parameterization for a model of the equatorward boundary of the aurora. We find that weighted averages of the AE index and the solar wind coupling function dΦMP/dt both outperform the often used Kp index. Using conjunction events where two DMSP satellites cross the auroral boundary at nearly the same time, we show that these models are better at extrapolating the auroral boundary to different local times than previous models.
Ionospheric GNSS Imagery of Seismic Source: Possibilities, Difficulties, and Challenges
Authors: Astafyeva E. , Shults K. 
Published: December 2018

AbstractUp to now, the possibility to obtain images of seismic source from ionospheric Global Navigation Satellite Systems (GNSS) measurements (seismo‐ionospheric imagery) has only been demonstrated for giant earthquakes with moment magnitude Mw ≥ 9.0. In this work, we discuss difficulties and restrictions of this method, and we apply for the first time the seismo‐ionospheric imagery for smaller earthquakes. The latter is done on the example of the Mw7.4 Sanriku‐oki earthquake of 9 March 2011. Analysis of 1‐Hz data of total electron content (TEC) shows that the first coseismic ionospheric disturbances (CID) occur ~470–480 s after the earthquake as TEC enhancement on the east‐northeast from the epicenter. The location of these first CID arrivals corresponds to the location of the coseismic uplift that is known as the source of tsunamis. Our results confirm that despite several difficulties and limitations, high‐rate ionospheric GNSS data can be used for determining the seismic source parameters for both giant and smaller/moderate earthquakes. In addition to these seismo‐ionospheric applications, we raise several fundamental questions on CID nature and evolution, namely, one of the most challenging queries—can moderate earthquake generate shock‐acoustic waves?
The 22 July 2009 Total Solar Eclipse: Modeling D Region Ionosphere Using Narrowband VLF Observations
Authors: Venkatesham K. , Singh Rajesh , Maurya Ajeet K. , Dube Adarsh , Kumar Sushil , Phanikumar D. V. 
Published: December 2018

AbstractWe present D region ionospheric response to 22 July 2009 total solar eclipse by modeling 19.8‐kHz signal from NWC very low frequency (VLF) navigational transmitter located in the Australia. NWC VLF signal was received at five stations located in and around eclipse totality path in the Indian, East Asian, and Pacific regions. NWC signal great circle paths to five stations are unique having eclipse coverage from no eclipse to partiality to totality regions, and the signal is exclusively confined in the low and equatorial regions. Eclipse‐induced modulations in NWC signal have been modeled by using long‐wave propagation capability code to obtain D region parameters of reflection height (H′) and sharpness factor (β). Long‐wave propagation capability modeling showed an increase in H′ of about 2.3 km near central line of totality, 3.0 km in the region near to totality fringe, and 2.4 to 3.0 km in the region under partial eclipse. Using H′ and β, Wait ionosphere electron density (Ne) profile at the daytime altitude of 75 km showed a decrease in Ne by about 58% at a station near totality central line, whereas at totality fringe and in partial eclipse region decrease in the Ne was between 63% and 71% with respect to normal time values. The eclipse associated variations in the H′, β, and Ne are less in low‐latitude region as compared to midlatitude. The study contributes to explain observations of wave‐like signature in the D region during an eclipse and difference in the eclipse effect in the different latitude‐longitude sectors.
Identification and Extraction of Seasonal Geodetic Signals Due to Surface Load Variations
Authors: Larochelle S. , Gualandi A. , Chanard K. , Avouac J.‐P. 
Published: December 2018

AbstractDeformation of the Earth's surface associated with redistributions of continental water mass explains, to first order, the seasonal signals observed in geodetic position time series. Discriminating these seasonal signals from other sources of deformation in geodetic measurements is essential to isolate tectonic signals and to monitor spatio‐temporal variations in continental water storage. We propose a new methodology to identify and extract these seasonal signals. The approach uses a variational Bayesian Independent Component Analysis (vbICA) to extract the seasonal signals and a gravity‐based deformation model to identify which of these signals are caused by surface loading. We test the procedure on two study areas, the Arabian Peninsula and the Nepal Himalaya, and find that the technique successfully extracts the seasonal signals with one or two independent components, depending on whether the load is stationary or moving. The approach is robust to spatial heterogeneities inherent to geodetic measurements and can help extract systematic errors in geodetic products (e.g., draconitic errors). We also discuss how to handle the degree‐1 deformation field present in the geodetic data set but not captured by the gravity‐based model.
Spatial Distribution of Melt Season Cloud Radiative Effects Over Greenland: Evaluating Satellite Observations, Reanalyses, and Model Simulations Against In Situ Measurements
Authors: Wang Wenshan , Zender Charles S. , van As Dirk , Miller Nathaniel B. 
Published: December 2018

AbstractArctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large‐scale data sets we analyze are all around 10 W/m2. Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA‐2), ERA‐Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L‐shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA‐2, ERA‐Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA‐2 best captures the observed interstation changes, captures most of the observed cloud‐radiation physics, and largely reproduces both albedo and cloud properties. The warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.
A Practical Single‐Channel Algorithm for Land Surface Temperature Retrieval: Application to Landsat Series Data
Authors: Wang Mengmeng , Zhang Zhengjia , Hu Tian , Liu Xiuguo 
Published: December 2018

AbstractThe single‐channel (SC) algorithm has been widely used to retrieve land surface temperature from Landsat series data for its simplicity and requirement of only one thermal infrared channel. The main error sources of the existing SC algorithms are the linearization of the Planck's function and atmospheric correction. This paper proposed a practical SC (PSC) algorithm to retrieve land surface temperature from Landsat series data aiming at avoiding the aforementioned error sources. The sensitivity of the PSC algorithm to the input parameters was analyzed. The performance of the proposed PSC algorithm was compared with the most commonly used SC algorithm (the generalized SC, GSC) using a simulation data set and satellite measurements. Results showed that the PSC algorithm was less sensitive to uncertainties in the input parameters than the GSC algorithm. When validated with the simulation data set, the root‐mean‐square error (RMSE) of the PSC algorithm was 1.23 K, with an improvement by 0.57 K compared with the GSC algorithm. For the validation with 71 clear‐sky Landsat 8 images, the RMSE of the PSC algorithm was 1.77 K when using the measurements from U.S. surface radiation budget network as real values. Compared with the GSC algorithm, the RMSE improvement for the PSC algorithm was 0.47 K. We conclude that the PSC algorithm is more accurate than the GSC algorithm and the sensitivity to input parameters in the PSC algorithm is weaker than in the GSC algorithm.
Mesospheric Temperature During the Extreme Midlatitude Noctilucent Cloud Event on 18/19 July 2016
Authors: Kaifler N. , Kaifler B. , Wilms H. , Rapp M. , Stober G. , Jacobi C. 
Published: December 2018

AbstractA rare noctilucent cloud (NLC) event was observed at 48.8∘ N, 13.7∘ E above GERman Experimental Seismic System station in southern Germany on 18/19 July 2016 using the Compact Rayleigh Autonomous Lidar. Strong southward winds due to a quasi 2‐day planetary wave allowed for the influx of mesospheric polar air to midlatitudes on this day. The NLC observed by lidar was preceded by strong NLC displays in Cloud Imaging and Particle Size (CIPS) Experiment satellite images above the North Sea and by strong mesospheric summer radar echoes 800 km north of the lidar site and was also observed visually in central Europe. The NLC occurred at low altitude and was bright and thin with strong oscillations in altitude and brightness. Darkness allowed for high‐resolution temperature measurements at NLC altitudes. The ice particles were embedded in the upper part of a cold region with temperatures below 150 K. Significantly higher temperatures were found directly above the cloud with large vertical temperature gradients of 25 K/km at the top boundary. Spectral analysis reveals that NLC particles existed within cold phases of gravity waves within a region of high static stability. In order to study the evolution of NLC brightness in this environment, we drive the microphysical model Community Aerosol and Radiation Model for Atmospheres with lidar temperature soundings. We find that NLC particles can survive and grow in the conditions defining this midlatitude event. We conclude that the ice particles did not nucleate at the site of observation but were meridionally transported and vertically confined to a thin layer due to a large vertical temperature gradient, wind reversal, and low levels of mesospheric turbulence.
The Importance of Capturing Topographic Features for Modeling Groundwater Flow and Transport in Mountainous Watersheds
Authors: Wang Chao , Gomez‐Velez Jesus D. , Wilson John L. 
Published: December 2018

AbstractPhysics‐based distributed hydrological models that include groundwater are widely used to understand and predict physical and biogeochemical processes within watersheds. Typically, due to computational limitations, watershed modelers minimize the number of elements used in domain discretization, smoothing or even ignoring critical topographic features. We use an idealized model to investigate the implications of mesh refinement along streams and ridges for modeling three‐dimensional groundwater flow and transport in mountainous watersheds. For varying degrees of topographic complexity level (TCL), which increases with the level of mesh refinement, and geological heterogeneity, we estimate and compare steady state baseflow discharge, mean age, and concentration of subsurface weathering products. Results show that ignoring lower‐order streams or ridges diminishes flow through local flow paths and biases higher the contribution of intermediate and regional flow paths, and biases baseflow older. The magnitude of the bias increases for systems where permeability rapidly decreases with depth and is dominated by shallow flow paths. Based on a simple geochemical model, the concentration of weathering products is less sensitive to the TCL, partially due to the thermodynamic constraints on chemical reactions. Our idealized model also reproduces the observed emergent scaling relationship between the groundwater contribution to streamflow and drainage area, and finds that this scaling relationship is not sensitive to mesh TCL. The bias effects have important implications for the use of hydrological models in the interpretation of environmental tracer data and the prediction of biogeochemical evolution of stream water in mountainous watersheds.
Velocities, Residence Times, Tracer Breakthroughs in a Vegetated Lysimeter: A Multitracer Experiment
Authors: Benettin Paolo , Queloz Pierre , Bensimon Michaël , McDonnell Jeffrey J. , Rinaldo Andrea 
Published: December 2018

AbstractFlow velocities, residence times, and tracer breakthroughs at the lysimeter scale are affected by matrix properties and preferential flow. Despite their relevance to transport processes, however, the relative timing of preferential flow, and its link to transit times through the soil block, is still poorly described. Here we present and analyze tracer data from a 2.5 m3 vegetated lysimeter experiment where 18 mm of isotopically labeled water was added as a pulse and then followed with a series of tracer‐free controlled rainfall events for 5 months. A solution of two fluorobenzoid acid tracers was also injected and tracked. Time series of soil water samples at three different depths and bottom drainage samples were collected and analyzed. Unlike past lysimeter experiments, a willow tree grown within the lysimeter exerted strong evapotranspiration fluxes. By comparative analysis of soil water and bottom drainage samples, we show the presence of both translatory and preferential flow features reflecting the interplay of slow vertical percolation and fast recharge through macropores. We found that water ponding and evaporating from the top of the lysimeter after irrigation prompted samples to be highly and irregularly fractionated. Comparative analyses of multitracer breakthroughs (adjusted by removing fractionation effects) showed that fluorobenzoid acid tracers reached the bottom of the lysimeter earlier than the isotopes, likely due to the effect of plant uptake. Our results underscore the essential role of models to interpret tracer behavior and, critically, the importance of future experiments aimed at measuring the ages of the water abstracted by vegetation.
Electric field calculation and grading ring design for 750 kV four‐circuits transmission line on the same tower with six cross‐arms
Authors: Huo Feng , Zhang Peng , Yu Yiliang , Liu Qin , Chu Lei , Wang Xuezong 
Published: December 2018

The transmission corridors can be effectively saved using 750 kV four‐circuit transmission line on the same tower. In order to reduce the corona level, structure optimisation of fittings plays an important role in the transmission line design. In this study, the electric field distribution of 750 kV transmission line on six cross‐arms tower was calculated based on finite element method, and the influences of pipe diameter, ring diameter and installation position of the grading ring were analysed. The results show that the increase of pipe diameter can reduce the electric field strength of grading ring while the increase of installation position and decrease of ring diameter are important to protect the end fitting of composite insulator. When using grading ring with the pipe diameter of 100 mm, the ring diameter of 700–900 mm and the installation position of 150–250 mm, the electric field strength can be controlled in a reasonable range. These results can provide references for the grading ring design of 750 kV four‐circuit transmission line on the same tower.
An Accurate Automated Local Similarity Factor-Based Neural Tree Approach toward Tissue Segmentation of Newborn Brain MRI
Authors: Jaware Tushar H. , Khanchandani K. B. , Zurani Anita 
Published: December 2018

Background Segmentation of brain MR images of neonates is a primary step for assessment of brain evolvement. Advanced segmentation techniques used for adult brain MRI are not companionable for neonates, due to extensive dissimilarities in tissue properties and head structure. Existing segmentation methods for neonates utilizes brain atlases or requires manual elucidation, which results into improper and atlas dependent segmentation.
Objective The primary objective of this work is to develop fully automatic, atlas free, and robust system to segment and classify brain tissues of newborn infants from magnetic resonance images.
Study Design In this study, we propose a fully automatic, atlas-free pipeline based Neural Tree approach for segmentation of newborn brain MRI which utilizes resourceful local resemblance factor such as concerning, connectivity, structure, and relative tissue location. Physical collaboration and uses of an atlas are not required in proposed method and at the same time skirting atlas-associated bias which results in improved segmentation. Proposed technique segments and classify brain tissues both at global and tissue level.
Results We examined our results through visual assessment by neonatologists and quantitative comparisons that show first-rate concurrence with proficient manual segmentations. The implementation results of the proposed technique provided a good overall accuracy of 91.82% for the segmentation of brain tissues as compared with other methods.
Conclusion The pipelined-based neural tree approach along with local similarity factor segments and classify brain tissues. The proposed automated system have higher dice similarity coefficient as well as computational speed.