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1,670 results for “FORCE”
Data for manuscript "Evidence for large-scale climate forcing of dense shelf water variability in the Ross Sea"
<p>Relevant data shown in figures of the manuscript "Evidence for large-scale climate forcing of dense shelf water variability in the Ross Sea"</p>
Woody cover and geology as stabilising forces in semi-arid savannas
<p>Data accompanying the paper:</p> <p>L.M. Vermeulen, B. Verbist, K. Van Meerbeek, J. Slingsby, P.N. Bernardino, B. Somers. 2024. Woody cover and geology as stabilising forces in semi-arid savannas.</p>
The effect of uncertainty in humidity and model parameters on the prediction of contrail energy forcing
<p>Previous work has shown that while the net effect of aircraft condensation trails (contrails) on the<br>climate is warming, the exact magnitude of the energy forcing per meter of contrail remains uncertain.<br>In this paper, we explore the skill of a Lagrangian contrail model (CoCiP) in identifying flight<br>segments with high contrail energy forcing. We find that skill is greater than climatological<br>predictions alone, even accounting for uncertainty in weather fields and model parameters.</p> <p>We estimate the uncertainty in weather by using the ensemble ERA5 weather reanalysis from the European<br>Centre for Medium-Range Weather Forecasts (ECMWF) as Monte Carlo inputs to CoCiP. We unbias and correct<br>under-dispersion on the ERA5 humidity data by forcing a match to the distribution of in situ humidity<br>measurements taken at cruising altitude. We set aside CoCiP energy forcing estimates calculated using<br>one of the ensemble members as a proxy for ground truth, and report the skill of CoCiP in identifying<br>segments with large positive proxy energy forcing. We further estimate the uncertainty in the model<br>parameters in CoCiP by performing Monte Carlo simulations with CoCiP model parameters drawn from<br>uncertainty distributions consistent with the literature.</p> <p>When CoCiP outputs are averaged over seasons to form climatological predictions, the skill in<br>predicting the proxy is 44%, while the skill of per-flight CoCiP outputs is 84%. If these results carry<br>over to the true (unknown) contrail EF, they indicate that per-flight energy forcing predictions can<br>reduce the number of potential contrail avoidance route adjustments by 2x, hence reducing both the cost<br>and fuel impact of contrail avoidance.</p>
The Response of the Southern Ocean to Climatological Iceberg Freshwater Forcing
<p><strong>Data Availability Statement:</strong></p> <p>The data presented here are the model outputs for the study titled <em>"The Response of the Southern Ocean to Climatological Iceberg Freshwater Forcing."</em> Due to size limitations on data uploads, a coarser resolution dataset is provided. For access to the full-resolution dataset, please contact the corresponding author at <strong><a rel="noopener">jingwei.zhang@utas.edu.au</a></strong>.</p>
Supplementary material for "Moment tensor and point force estimation, with applications to earthquakes, landslides, and the 2017 DPRK nuclear explosion"
<p>This Zenodo archive contains supplementary data and code for the paper <strong>Moment tensor and point force estimation, with applications to earthquakes, landslides, and the 2017 DPRK nuclear explosion</strong> (submitted to <em>Geophysical Journal International</em>). The archive provides scripts and data to reproduce some of the figures and results presented in the paper / supplementary material.</p>
Small orbital forcing changes alter the ocean circulation of Earth's next future supercontinent: Simulations
<p>This dataset contains the simulations from the manuscript "Small orbital forcing changes alter the ocean circulation of Earth's next future supercontinent".</p> <p>From the methods section of the manuscript:<br>The simulations are carried out using the fully-coupled ocean-atmosphere general circulation model ROCKE-3D version Planet 1.0 (R3D1) (Way et al., 2017). The model is run at a horizontal resolution of 4 x 5 degrees and simulations were integrated for 5000 and 7000 years for PD and future forcing, respectively, to ensure they were in equilibrium. The topography and bathymetry is the one used by Way et al. (2021) in their simulation 2 (Aurica). This includes a fully dynamic ocean 4252 m deep and land elevations close to present day mean topography and elevations between 1 and 858 m.<br>Due to high uncertainties in its future evolution, atmospheric composition is kept constant at year 1850 levels, following the setup in Way et al. (2021): the atmosphere is dominated by nitrogen with 21% oxygen, 285 ppmv CO2, 0.3 ppmv N2O and 0.79 ppmv CH4, and no aerosols or ozone are included.<br>Two simulations are presented: PD_Aurica which which has present-day day-length (24 hrs) and insolation (1361 Wm-2) and F_Aurica where we apply orbital forcing consistent with 250 Ma into the future - day length is increased by 0.5 hrs and insolation is increased by 2.6 Wm-2 (see Way et al., 2021). </p> <p>PD_Aurica corresponds to the output files with the following names: ANN4500-4999.*F_AURICA_RAND_PD_03.nc<br>F_Aurica corresponds to the output files with the following names: ANN6500-6999.*F_AURICA_RAND_PD_01.nc</p> <p>The diagnostic files including AGC, AIJ, AIJK and AIJL in the filename contain atmospheric diagnostics and outputs, whereas those that include OIJ, OIJL, OJL and OTJ contain ocean diagnostics and outputs.</p> <p><span><span><span><a href="https://science.gsfc.nasa.gov/author/533569006/35432">Way M. J.</a></span></span><span>, </span></span><span><span><span><a href="https://science.gsfc.nasa.gov/author/830545035/35432">I. Aleinov</a></span></span><span>, </span></span><span><span>D. S. Amundsen</span><span>, </span></span><span><span><a title="See all authors for this publication">et al.</a> </span></span> <span>2017.</span> <span> "Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets." </span> <em>The Astrophysical Journal Supplement Series</em> <strong>231</strong> <span><strong>(1)</strong>: </span> <span>12</span> <span> [<a href="http://dx.doi.org/10.3847/1538-4365/aa7a06">10.3847/1538-4365/aa7a06</a>]</span></p> <p><span><span><span><a href="https://science.gsfc.nasa.gov/author/533569006/42520">Way M. J.</a></span></span><span>, </span></span><span><span>H. S. Davies</span><span>, </span></span><span><span>J. C. Duarte</span><span>, </span></span><span><span><a title="See all authors for this publication">et al.</a> </span></span> <span>2021.</span> <span> "The Climates of Earth’s Next Supercontinent: Effects of Tectonics, Rotation Rate, and Insolation." </span> <em>Geochemistry, Geophysics, Geosystems</em> <strong>22</strong> <span><strong>(8)</strong>: </span> <span> [<a href="http://dx.doi.org/10.1029/2021gc009983">10.1029/2021gc009983</a>]</span></p> <p> </p> <p> </p>
Data and Code for "Informative risk analyses of radiative forcing geoengineering require proper counterfactuals"
<p>This repository contains data and code necessary to generate the figures presented in the maunscript "Data and Code for “Informative risk analyses of radiative forcing geoengineering require proper counterfactuals”, submitted for publication to the Nature journal <em>Communications Earth & Environment</em>.</p>
Free Energy-based Refinement of DNA Force Field via Modification of Multiple Non-bonding Energy Terms
<p>Relevant files of the benchmark DNA simulations.</p> <p>*.xtc --> truncated OPESE trajectory file.</p> <p>*.tar --> compressed initial structures.</p> <p>*.mdp --> GROMACS molecular dynamics parameter file.</p> <p>*.dat --> PLUMED input file for OPESE simulation.</p> <p> </p>
A new parameterisation for homogeneous ice nucleation driven by highly variable dynamical forcings
<p>This archive contains the data associated with the preprint of the article <em>"A New Parameterization for Homogeneous Ice Nucleation Driven by Highly Variable Dynamical Forcings."</em> The collection includes datasets used to construct the initial conditions for forcing an air parcel model with ice physics, outputs produced by the parcel model, and data necessary for generating the plots presented in the paper. A README file is provided, offering a detailed explanation of the contents and structure of the archive,</p>
Data from: Sporadic sampling not climatic forcing drives observed early hominin diversity
The role of climate change in the origin and diversification of early hominins is hotly debated. Most accounts of early hominin evolution link observed fluctuations in species diversity to directional shifts in climate or periods of intense climatic instability. None of these hypotheses, however, have tested whether observed diversity patterns are distorted by variation in the quality of the hominin fossil record. Here, we present a detailed examination of early hominin diversity dynamics, including both taxic and phylogenetically corrected diversity estimates. Unlike past studies, we compare these estimates to sampling metrics for rock availability (hominin-, primate-, and mammal-bearing formations) and collection effort, in order to assess the geological and anthropogenic controls on the sampling of the early hominin fossil record. Taxic diversity, primate-bearing formations, and collection effort show strong positive correlations, demonstrating that observed patterns of early hominin taxic diversity can be explained by temporal heterogeneity in fossil sampling rather than genuine evolutionary processes. Peak taxic diversity at 1.9 million years ago (Ma) is a sampling artefact, reflecting merely maximal rock availability and collection effort. In contrast, phylogenetic diversity estimates imply peak diversity at 2.4 Ma and show little relation to sampling metrics. We find that apparent relationships between early hominin diversity and indicators of climatic instability are, in fact, driven largely by variation in suitable rock exposure and collection effort. Our results suggest that significant improvements in the quality of the fossil record are required before the role of climate in hominin evolution can be reliably determined.
Biotic and anthropogenic forces rival climatic/abiotic factors in determining global plant population growth and fitness
<p>Multiple, simultaneous environmental changes, in climatic/abiotic factors, in interacting species, and in direct human influences, are impacting natural populations and thus biodiversity, ecosystem services, and evolutionary trajectories. Determining whether the magnitudes of the population impacts of abiotic, biotic, and anthropogenic drivers differ, accounting for their direct effects and effects mediated through other drivers, would allow us to better predict population fates and design mitigation strategies. We compiled 644 paired values of the population growth rate (lambda) from high and low levels of an identified driver from demographic studies of terrestrial plants. Among abiotic drivers, natural disturbance (not climate), and among biotic drivers, interactions with neighboring plants had the strongest effects on lambda. However, when drivers were combined into the three main types, their average effects on lambda did not differ. For the subset of studies that measured both the average and variability of the driver, lambda was more sensitive to one standard deviation of change in abiotic drivers relative to biotic drivers, but sensitivity to biotic drivers was still substantial. Similar impact magnitudes for abiotic/biotic/anthropogenic drivers holds for plants of different growth forms, for different latitudinal zones, and for biomes characterized by harsher or milder abiotic conditions, suggesting that all three drivers have equivalent impacts across a variety of contexts. Thus the best available information about the integrated effects of drivers on all demographic rates provides no justification for ignoring drivers of any of these three types when projecting ecological and evolutionary responses of populations and of biodiversity to environmental changes.</p>
Dataset for electromagnetic holding force of split core transformer
<p>Dataset for electromagnetic holding force of split core transformer grasping mechanism. Dataset is separated in two documents with "coil_test1" containing data from a single test at a primary AC current of 1000 A. "coil_test2" contain eight test samples at different secondary currents denoted by 1-8. </p>
Data and simulations files for the article "Accurate modeling and characterization of photothermal forces in optomechanics"
<p>Data and simulations files for the article "Accurate modeling and characterization of photothermal forces in optomechanics".</p>
Survey response of the H2020 Water-ForCE expert meeting on In situ calibration and validation of satellite products of water quality and hydrology
<p>These slides provide an overview of the expert survey held in advance of the H2020 Water-ForCE workshop:</p> <p><strong>In situ calibration and validation of satellite products of water quality and hydrology</strong></p> <p>which was held as three virtual meeting sessions on 17, 18 and 20th May 2021:</p> <ol> <li>Data availability, Accessibility and quality gaps</li> <li>Emerging technologies to address current gaps</li> <li>Data harmonization and sharing</li> </ol> <p>Source data have been removed from the graphs included in these slides but may be requested from the authors.</p> <p>The workshop and outcomes are part of the H2020 funded project Water-ForCE: Water Scenarios For Copernicus Exploitation. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101004186</p>
bd oxidase force field parameters
<p>Amber force field parameters for E. coli cytochrome bd oxidase (PDB: 6RKO)</p>
SNICAR related forcings for CICE/Icepack 2021.01.21
<p>SNICAR derived optical properties for use in the delta-Eddington radiation in CICE/Icepack.</p>
Lagrangian drifter output in the Southeast Indian Ocean using the Connectivity Modelling System output forced with TROPAC01
<p>This dataset contains Lagrangian drifter trajectories from the Connectivity Modelling System (CMS) in the Southeast Indian Ocean. CMS was forced with ocean velocity fields from TROPAC01 and this experiment was focused on sources of the Leeuwin Current. TROPAC01 is a high-resolution ocean general circulation model, developed by the European Drakkar cooperation [Barnier et al., 2007] it is based on the NEMO [v3.2 Madec, 2008] code. Specifically, it is a 1/10 horizontal resolution model of the tropical Indo- Pacific region (spanning the area from 73°E - 63°W to 49°S - 31°N), nested within a half-degree global ocean/ sea-ice model. More information on the model configuration used for this experiment can be found in [van Sebille et al., 2014]. Using the velocity fields from TROPAC01 we then use the Connectivity Modelling System (CMS) v1.1 [Paris et al., 2013] to integrate the virtual particles in three-dimensional time-evolving flow.</p> <p>Version v1.0 of this dataset includes ascii raw model output of CMS trajectories and the forcing file (seed file) that enables a user to calculate absolute time of a particle's location. Variables are: particle_number, time, longitude, latitude, depth, exit_code.</p> <p>These experiments were executed by Christopher Bull of the ARC Centre of Excellence for Climate System Science (ARCCSS) research program "Mechanisms and attribution of past and future ocean circulation change", as part of Christopher's PhD candidature.</p> <p> </p> <p>References:</p> <p> Code and documentation for the CMS is available at:</p> <p> https://github.com/beatrixparis/connectivity-modeling-system</p> <p>Claire B. Paris, Judith Helgers, Erik van Sebille, Ashwanth Srinivasan, 2013.<br> Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean,<br> Environmental Modelling & Software, Volume 42, 2013, Pages 47-54, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2012.12.006.</p> <p>van Sebille, E., Sprintall, J., Schwarzkopf, F. U., Gupta, A. S., Santoso, A., England, M. H., Biastoch, A., and Böning, C. W. (2014), Pacific-to-Indian Ocean connectivity: Tasman leakage, Indonesian Throughflow, and the role of ENSO, <em>J. Geophys. Res. Oceans</em>, 119, 1365– 1382, doi:<a href="https://doi.org/10.1002/2013JC009525">10.1002/2013JC009525</a>.</p>
Dataset of: "Surface-Wave Dispersion in Partially Saturated Soils: the Role of Capillary Forces"
<p>This package contains the dataset of the paper entitled: Surface-Wave Dispersion in Partially Saturated Soils: the Role of Capillary Forces. Further information is given in the README files located within each folder.</p>
dataset for "Atomic force microscopy characterization of Polyester Grafted with poly(styrene sulfonate)"
<p>Atomic Force Microscopy (AFM) raw files of polycaprolactone (PCL) and polyethylene terephthalate (PET) non-functionalized and functionalized with poly(sodium 4-styrene sulfonate) (PNaSS) by thermal radical grafting, thermal radical grafting in the presence of redox initiator (Mohr's salt), and UV grafting. </p> <p>https://chemrxiv.org/engage/chemrxiv/article-details/60c75963842e650a5edb49f6</p> <p>DOI: 10.26434/chemrxiv.14687556</p>
Dataset for Journal of Applied Physics 130, 124502 (2021) - Force microscopy cantilevers locally heated in a fluid: temperature fields and effects on the dynamics
<p><strong>"Fig7.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 7 of the article.</p> <p><strong>"Fig7_data.mat "</strong>: Matlab files containing the data to plot figure 7 of the article.</p> <p><strong>"Fig7_plot.m "</strong>: Matlab scripts to plot the data of the Matlab files "Fig7_data.mat"</p> <p><strong>"Fig10.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 10 of the article.</p> <p><strong>"Fig13.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 13 (in the appendix) of the article.</p> <p> </p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.