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11 results for “boundary estimation”
Datasets For "Estimating Maximum Extent of Auroral Equatorward Boundary using Historical and Simulated Surface Magnetic Field Data", Blake et al. (2020), JGR
<p>Datasets and sample Python codes for the 2020 paper <em>"Estimating Maximum Extent of Auroral Equatorward Boundary using Historical and Simulated Surface Magnetic Field Data"</em>, by Blake et al., submitted to the Journal of Gephysical Research, Space Physics. </p> <p>Up-to-date Python codes can be found at <a href="https://github.com/TerminusEst/Auroral_Boundary_Geomag">https://github.com/TerminusEst/Auroral_Boundary_Geomag</a></p> <p>The complete SWMF simulation folders (including parameter and log files etc.) can be requested from <a href="https://ccmc.gsfc.nasa.gov/index.php">NASA's Community Coordinated Modeling Center</a>.</p> <p>#########</p> <p><strong>Data/ </strong>contains the following:</p> <p><strong>Data/HIST_DATA.txt </strong>contains the minimum Dst values and calculated maximum extents of the auroral equatorward boundaries for 25 years of INTERMAGNET data (1991-2016). The fourth column is the standard deviation of the calculated auroral boundary in degrees. </p> <p><strong>Data/Boundary_Fits.csv </strong>contains the calculated minimum Dst values, and calculated auroral boundaries using Method 1 and Method 2 (see main paper's ttext), for each of the 15 SWMF simulations. Also included are the uncertainties for each calculation.</p> <p><strong>Data/SWMF_outputs/ </strong>contains 15<strong> </strong>.txt files,<strong> </strong>each of which correspond to an SWMF simulation of the same name given in Table 1 in the main text. These data are for the magnetic longitude, magnetic latitude and maximum calculated <em>E<sub>H</sub> </em>(V/km) for each simulation.</p> <p>#########</p> <p><strong>Codes/ </strong>contains two python scripts, and some sample data. These scripts correspond to Section 2 in the main text:</p> <p>1) <strong>Boundary_Calc.py</strong> calculates the extent of the auroral boundary using magnetic latitudes and maximum calculated <em>E<sub>H</sub></em> values from multiple INTERMAGNET sites. </p> <p>2) <strong>Efield_Calc.py </strong>calculates the E-field for a single INTERMAGNET site using the Quebec 1-D resistivity model.</p> <p>A more detailed description of these codes can be found here: <a href="https://github.com/TerminusEst/Auroral_Boundary_Geomag">https://github.com/TerminusEst/Auroral_Boundary_Geomag</a></p> <p> </p>
Data Sets: Estimating scalar turbulent fluxes with slow-response sensors in the stable atmospheric boundary layer
<p>Date of data analysis: Statistical analyses conducted throughout the 2023 year </p><p>Information about funding sources that supported the collection of the data:</p><p>The research was supported by the Cooperative Institute for Modeling the Earth System at Princeton University under Award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, and by the US National Science Foundation under award number AGS 2128345. Also, it was supported by the National Defense Science and Engineering Graduate Fellowship from the U.S. Department of Defense and Army Research Office. Similarly, the National Science Foundation provided support to complete the PHOXMELT field studies (Grant PLR- 1417914) to collect the data. Also, the study was supported by the U.S. National Science Foundation (NSF-AGS-2028633) and the Department of Energy (DE-SC0022072).</p><p>The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration.</p><p>This dataset contains the observational data for the two field experiments (Barrow and Wendell) in .nc file format.</p>
Limitations of Catchment Area Estimates and River Basin Boundaries from CWC and WRIS
<p>The following files are included:<br> [Item 1 'share_stations.txt'] list of 100 stations used in this study and their attributes, pipe(|) delimited<br> [Item 2 'share_hydrosheds_rivers'] one shapefile of HydroSHEDS river network up to Farakka<br> [Item 3 'share_merit_rivers'] one shapefile of MERIT river network up to Farakka<br> [Item 4 'share_hydrosheds_reloc'] one shapefile of relocated stations, HydroSHEDS network<br> [Item 5 'share_merit_reloc'] one shapefile of relocated stations, MERIT network<br> [Item 6 folder 'share_bounds'] shapefiles of delineated catchment boundaries associated with each station (100 total)<br> [Item 7 'share_station_maps.pdf'] PDF file of maps showing location of each station and associated catchment boundary (100 pages)<br> </p>
Relative Random Errors in the Convective Atmospheric Boundary Layer Estimated by the Relaxed Filtering Method from Large Eddy Simulations
<p>Data supporting the paper "How representative are uncrewed aircraft system measurements of the convective boundary layer?" by Brian R. Greene, Leia M. Otterstatter, and Scott T. Salesky, submitted to Geophysical Research Letters in 2024. Data are postprocessed from large-eddy simulations of the convective atmospheric boundary layer that are used to produce the figures within the paper. Details on the production of these files are included in the supplementary informatin of this paper.</p>
Candidate-species delimitation in Desmognathus salamanders reveals gene flow across lineage boundaries, confounding phylogenetic estimation and clarifying hybrid zones
Dusky Salamanders (genus Desmognathus) currently comprise only 22 described, extant species. However, recent mitochondrial and nuclear estimates indicate the presence of up to 49 candidate species based on ecogeographic sampling. Previous studies also suggest a complex history of hybridization between these lineages. Studies in other groups suggest that disregarding admixture may affect both phylogenetic inference and clustering-based species-delimitation. With a dataset comprising 233 Anchored Hybrid Enrichment (AHE) loci sequenced for 896 Desmognathus specimens from all 49 candidate species, we test three hypotheses regarding i) species-level diversity, ii) hybridization and admixture, and iii) misleading phylogenetic inference. Using phylogenetic and population-clustering analyses considering gene flow, we find support for at least 47 candidate species in the phylogenomic dataset, some of which are newly characterized here while others represent combinations of previously named lineages that are collapsed in the current dataset. Within these, we observe significant phylogeographic structure, with up to 64 total geographic genetic lineages, many of which hybridize either narrowly at contact zones or extensively across ecological gradients. We find strong support for both recent admixture between terminal lineages and ancient hybridization across internal branches. This signal appears to distort concatenated phylogenetic inference, wherein more heavily admixed terminal specimens occupy apparently artifactual early diverging topological positions, occasionally to the extent of forming false clades of intermediate hybrids. Additional geographic and genetic sampling and more robust computational approaches will be needed to clarify taxonomy, and to reconstruct a network topology to display evolutionary relationships in a manner that is consistent with their complex history of reticulation. --
Bio-Optic bio-shortwave model code, initial conditions, river and boundary forcing for "Estimating the seaonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea" paper.
<p>Bio-Optic bio-shortwave model code, initial conditions, river and boundary forcing as well as selected model output used for analysis and producing figures in the paper "Estimating the seaonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea". Contact Bronwyn Cahill if you have questions at: bronwyn.cahill@io-warnemuende.de</p>
Candidate-species delimitation in Desmognathus salamanders reveals gene flow across lineage boundaries, confounding phylogenetic estimation and clarifying hybrid zones
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Data from: Multilocus phylogeny and Bayesian estimates of species boundaries reveal hidden evolutionary relationships and cryptic diversity in Southeast Asian monitor lizards
Recent conceptual, technological, and methodological advances in phylogenetics have enabled increasingly robust statistical species delimitation in studies of biodiversity. As the variety of evidence purporting species diversity has increased, so too have the kinds of tools and inferential power of methods for delimiting species. Here we showcase an organismal system for a data-rich, comparative molecular approach to evaluating strategies of species delimitation among monitor lizards of the genus Varanus. The water monitors (Varanus salvator Complex), a widespread group distributed throughout Southeast Asia and southern India, have been the subject of numerous taxonomic treatments, which have drawn recent attention due to the possibility of undocumented species diversity. To date, studies of this group have relied on purportedly diagnostic morphological characters, with no attention given to the genetic underpinnings of species diversity. Using a 5-gene dataset, we estimated phylogeny and used multilocus genetic networks, analysis of population structure, and a Bayesian coalescent approach to infer species boundaries. Our results contradict previous systematic hypotheses, reveal surprising relationships between island and mainland lineages, and uncover novel, cryptic evolutionary lineages (i.e. new putative species). Our study contributes to a growing body of literature suggesting that, used in concert with other sources of data (e.g., morphology, ecology, biogeography), multilocus genetic data can be highly informative to systematists and biodiversity specialists when attempting to estimate species diversity and identify conservation priorities. We recommend holding in abeyance taxonomic decisions until multiple, converging lines of evidence are available to best inform taxonomists, evolutionary biologists, and conservationists.
Data from: Multilocus phylogeny and Bayesian estimates of species boundaries reveal hidden evolutionary relationships and cryptic diversity in Southeast Asian monitor lizards
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Inverse estimation of spatiotemporal flux boundary conditions in unsaturated water flow modeling
<p>Data used in field case study in the paper titled "Inverse estimation of spatiotemporal flux boundary conditions in unsaturated water flow modeling".</p>
Dataset related to paper: Estimation through direct turbulence measurements of the Nocturnal Boundary Layer Height over the Central Amazon Forest.
<p>This dataset contains one year (2022) of observational data collected at the ATTO ( Amazon Tall Tower Observatory) Project in the Central Amazon region. Please consult the README file for a description of the dataset.</p>
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.