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15,572 results for “timescale”
Supporting data for von Fromm et al. (2023) Controls on timescales of soil organic carbon persistence across sub-Saharan Africa
<p>This file contains the supporting data for<em> von Fromm et al. (2024) Controls on timescales of soil organic carbon persistence across sub-Saharan Africa, Global Change Biology</em>, <a href="https://doi.org/10.1111/gcb.17089">https://doi.org/10.1111/gcb.17089</a></p> <p>We used wet soil chemistry data from <em>Vågen et al., 2021</em> (<a href="https://doi.org/10.34725/DVN/66BFOB">https://doi.org/10.34725/DVN/66BFOB</a>). In addition, we added newly measured radiocarbon data, extracted global climate data, gross primary productivity and quantified soil mineralogy based on X-ray powder diffraction data. Turnover time for carbon (mean C age) was calculated from Δ14C (‰) values by using an one-pool model. For more details about the sampling, calculations, and units see the associated publication. To reproduce all analysis, including calculating the mean C age, please visit the author's github page: <a href="https://github.com/SophievF/AfSIS_14C">https://github.com/SophievF/AfSIS_14C</a>. </p> <p>The dataset is also part of the International Soil Radiocarbon Database (<a href="https://soilradiocarbon.org/">https://soilradiocarbon.org/</a>).</p>
Air-sea CO2 equibration timescales for Bach et al. 'Testing the climate intervention potential of ocean afforestation using the Great Atlantic Sargassum Belt''
<p>Data for the timescales of CO2 equilibration in the Great Atlantic <i>Sargassum</i> Belt from Fig. 3a and 3c of Bach et al. 2021 'Testing the climate intervention potential of ocean afforestation using the Great Atlantic <i>Sargassum</i> Belt'. </p><p>The data includes two files. The first file, tco2tres.nc, contains the 2-dimensional mapped 1 degree latitude x l degree longitude annual mean air-sea CO2 equilibration timescale<i> (T</i>co2<i>) </i>in months (from Figure 3a) and the annual mean ratio of the CO2 equilibration timescale to the surface residence time (<i>T</i>co2<i>/T</i>res) (from Figure 3c). The second file, tco2_seasonal.nc, contains the seasonal mean CO2 equilibration timescales, from Supplementary Figure 5.</p>
An Improved Coupled Data Assimilation System with a CGCM Using Multi-Timescale High Efficiency EnOI-Like Filtering
<p>Coupled data assimilation (CDA) combining coupled models and observations plays a critical role in climate studies by producing a four-dimensional estimation of Earth system states. However, traditional CDA algorithms while being expensive lack sufficient representation of multi-scale background flows. Here, a Multi-timeScale High-Efficiency Approximate EnKF (MSHea-EnKF) has been implemented in the global fully coupled climate model of the Geophysical Fluid Dynamics Laboratory. It consists of stationary, low-frequency, and high-frequency filters constructed from the timeseries of a single model solution, with improved representation for low-frequency background error statistics and enhanced computational efficiency. The MSHea-EnKF is evaluated in a biased twin experiment framework with synthetic “observations” produced by the other coupled model, Community Earth System Model, and a three-decade coupled analysis experiment with real observations. Results show that while computationally costing only a small fraction of traditional ensemble CDA, the MSHea-EnKF significantly improves the assimilation quality due to better representation of the slow-varying background flows in the filtering. The coupled analysis of MSHea-EnKF also improves the estimation of the Atlantic meridional overturning circulation, including better standard deviation distribution and mass transport at the Rapid section. These results of MSHea-EnKF on prevalent resolution coupled model with high computational efficiency promises its further applications to high-resolution coupled model data assimilation and reanalysis which will greatly advance our understanding for seamless weather-climate analysis and predictions.Coupled data assimilation (CDA) combining coupled models and observations plays a critical role in climate studies by producing a four-dimensional estimation of Earth system states. However, traditional CDA algorithms while being expensive lack sufficient representation of multi-scale background flows. Here, a Multi-timeScale High-Efficiency Approximate EnKF (MSHea-EnKF) has been implemented in the global fully coupled climate model of the Geophysical Fluid Dynamics Laboratory. It consists of stationary, low-frequency, and high-frequency filters constructed from the timeseries of a single model solution, with improved representation for low-frequency background error statistics and enhanced computational efficiency. The MSHea-EnKF is evaluated in a biased twin experiment framework with synthetic “observations” produced by the other coupled model, Community Earth System Model, and a three-decade coupled analysis experiment with real observations. Results show that while computationally costing only a small fraction of traditional ensemble CDA, the MSHea-EnKF significantly improves the assimilation quality due to better representation of the slow-varying background flows in the filtering. The coupled analysis of MSHea-EnKF also improves the estimation of the Atlantic meridional overturning circulation, including better standard deviation distribution and mass transport at the Rapid section. These results of MSHea-EnKF on prevalent resolution coupled model with high computational efficiency promises its further applications to high-resolution coupled model data assimilation and reanalysis which will greatly advance our understanding for seamless weather-climate analysis and predictions.</p>
Supplemental Materials for "Schwarzschild and Ledoux are equivalent on evolutionary timescales"
<p>This Zenodo repository contains a .tar file which contains datasets which can be used along with the code in the associated Github repository (https://github.com/evanhanders/schwarzschild_or_ledoux, an copy of which is also included here as a .tar file) to create all of the static figures in the paper. The figures can be recreated with this data by using the Python scripts in the schwarzschild_or_ledoux/publication_figures/ folder of the Git repository. The data are as follows:<br> <br> <strong>Figure 1</strong>:</p> <ul> <li>early_slices.h5, late_slices.h5 - 2D slices through various planes in the simulation which show the dynamics at a few early and late times in the simulation.</li> <li>early_profiles.h5, late_profiles.h5 - 1D horizontally-average profiles at the times associated with the dynamics in the 'slices' files.</li> <li>early_scalars.h5, late_scalars.h5 - files that contain some various scalar info (e.g., where the boundary is determined by the Schwarzschild and Ledoux criteria) for the early and late dynamics.</li> </ul> <p> </p> <p><strong>Figure 2</strong> -</p> <ul> <li>1D horizontally-averaged profiles for the full simulation in the paper are output into the "merged_profiles.h5" file. The output cadence is once every freefall time, so there are roughly 20,000 time points for each profile. figure 2 uses the initial state and the state at t = 17,000.</li> </ul> <p><strong>Figure 3 </strong>-</p> <ul> <li>scalar_data.h5 contains scalar values inferred from merged_profiles.h5 at each point in time. This file can be re-created by the user by using the 'profile_to_scalar.py' file inside of the publication_figures/ folder in the repository.</li> </ul>
Data from: Hierarchical variation in phenotypic flexibility across timescales and associated survival selection shape the dynamics of partial seasonal migration
<p>Population responses to environmental variation ultimately depend on within-individual and among-individual variation in labile phenotypic traits that affect fitness, and resulting episodes of selection. Yet, complex patterns of individual phenotypic variation arising within and between time periods, and associated variation in selection, have not been fully conceptualised or quantified. We highlight how structured patterns of phenotypic variation in dichotomous threshold traits can theoretically arise and experience varying forms of selection, shaping overall phenotypic dynamics. We then fit novel multistate models to ten years of band-resighting data from European shags to quantify phenotypic variation and selection in a key threshold trait underlying spatio-seasonal population dynamics: seasonal migration versus residence. First, we demonstrate substantial among-individual variation alongside substantial between-year individual repeatability in within-year phenotypic variation ('flexibility'), with weak sexual dimorphism. Second, we demonstrate that between-year individual variation in within-year phenotypes ('supraflexibility') is structured and directional, consistent with the threshold trait model. Third, we demonstrate strong survival selection on within-year phenotypes, and hence on flexibility, that varies across years and sexes, including episodes of disruptive selection representing costs of flexibility. By quantitatively combining these results, we show how supraflexibility and survival selection on migratory flexibility jointly shape population-wide phenotypic dynamics of seasonal movement.</p>
Monthly-Mean Model Output for Paper Titled "Do Nudging Tendencies Depend on the Nudging Timescale Chosen in Atmospheric Models?"
<p>These tarballs contains monthly-mean model output, which was primarily what was presented in the AGU JAMES paper titled "Do nudging tendencies depend on the nudging timescale chosen in atmospheric models?". Also included are the scripts used to set up these simulations, allowing reproducibility of the portion of the paper that used 3-hourly output. The 3-hourly output was not included, as it totaled ~7TB.</p>
Replication data for: "Ultrafast energy exchange between two single Rydberg atoms on the nanosecond timescale"
<p>Replication data for Figure 3 and 4 of "Ultrafast energy exchange between two single Rydberg atoms on the nanosecond timescale"</p> <p>Preprint at: https://arxiv.org/abs/2111.12314</p> <p> </p>
Parameter variability across different timescales in the energy balance-based model and its effect on evapotranspiration estimation
<p>Our dataset is for the manuscript "Parameter variability across different timescales in the energy balance-based model and its effect on evapotranspiration estimation". It includes the instantaneous and daily <em>z<sub>0m</sub></em>, <em>z<sub>0h</sub></em>, <em>g<sub>s</sub></em>, and <em>EBR</em>, which are derived from FLUXNET2015 dataset. The training and test datasets for building the data-driven parameter models are also uploaded.</p>
Thermal Equilibrium States and Timescales of Lunar Cold Traps via Low-Temperature Thermoluminescence
<p>This data set contains induced thermoluminescence glow curves following the irradiation with 90Sr beta particles, ranging in absored radiatoon doses of ~70 to 52,800 Gy.</p> <p>The glow curve data are compiled in one .csv file.</p> <p>The column headers indicate the temperature in Kelvin (K) at which the TL intensity (Int) was recorded and the absorbed dose in Gray (Gy).</p>
Polluted White Dwarfs: Mixing Regions and Diffusion Timescales
<p>Tables of diffusion timescales and surface mass fractions in MESA models for polluted DA white dwarfs.</p> <p>Includes python interpolation routines and and example plotting script, along with inlists and instructions for reproducing the MESA runs that built these tables.</p> <p>If you wish to make use of these tables in your work, please cite this paper: <a href="http://adsabs.harvard.edu/abs/2019ApJ...872...96B">http://adsabs.harvard.edu/abs/2019ApJ...872...96B</a> </p>
Multiple Distinct Timescales of Rapid Adaptation in the Thalamocortical Circuit
<p><span>Data and code to accompany "Multiple Distinct Timescales of Rapid Adaptation in the Thalamocortical Circuit" by Yi Juin Liew<sup>*</sup>, Elaida D Dimwamwa<sup>*</sup>, Nathaniel C Wright, Yong Zhang, and Garrett B Stanley. </span></p>
Geochemical, timescales data in orthopyroxenes from Kizimen 2010 eruption and database of studies linking diffusion timescales with monitoring signals.
<p>This dataset comprises the geochemical data on whole rock analysis, melt inclusions, residual glasses, magnetites and orthopyroxenes in samples from the 2010 eruption of Kizimen volcano (Kamchatka), as well as the timescales modelled in the orthopyroxenes and a database of studies linking diffusion timescales with monitoring signals, associated with the publication: Ostorero, L., Balcone-Boissard, H., Boudon, G. <em>et al.</em> Correlated petrology and seismicity indicate rapid magma accumulation prior to eruption of Kizimen volcano, Kamchatka. <em>Commun Earth Environ</em> <strong>3</strong>, 290 (2022). https://doi.org/10.1038/s43247-022-00622-3</p> <p> </p>
Data and MATLAB files for: Timescale analyses of fluctuations in coexisting populations of a native and invasive tree squirrel
<p>1. Competition from invasive species is an increasing threat to biodiversity. In Southern California, the western gray squirrel (Sciurus griseus, WGS) is facing increasing competition from the fox squirrel (Sciurus niger, FS), an invasive congener.</p> <p>2. We used spectral methods to analyze 140 consecutive monthly censuses of WGS and FS within a 11.3 ha section of the California Botanic Garden. Variation in the numbers for both species and their synchrony was distributed across long timescales (> 15 months).</p> <p>3. After filtering out annual changes, concurrent mean monthly temperatures from nearby Ontario Airport (ONT) yielded a spectrum with a large semiannual peak and significant spectral power at long timescales (> 30 months). Squirrel-temperature cospectra showed significant negative covariation at long timescales (> 35 months) for WGS and smaller significant negative peaks at 6 months for both species.</p> <p>4. Simulations from a Lotka-Volterra model of two competing species indicates that the risk of extinction for the weaker competitor increases quickly as environmental noise shifts from short to long timescales.</p> <p>5. We analyzed the timescales of fluctuations in detrended mean annual temperatures for the time period 1915-2014 from 1218 locations across the continental USA. In the last two decades, significant shifts from short timescales to long timescales have occurred, changing from less than 3 years to 4-6 years.</p> <p>6. Our results indicate that (i) population fluctuations in co-occurring native and invasive tree squirrels are synchronous, occur over long timescales, and may be driven by fluctuations in environmental conditions; (ii) long timescale population fluctuations increase the risk of extinction in competing species, especially for the inferior competitor; and (iii) the timescales of interannual environmental fluctuations may be increasing from recent historical values. These results have broad implications for the impact of climate change on the maintenance of biodiversity.</p>
Radiocarbon, Tephra, and Paleomagnetic Data from 5 Northern North Atlantic Sediment Cores to support Reilly et al. 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic."
<p>Data in support of Reilly et al., 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic." Published in the Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>Excel file includes worksheets for the following data:</p> <p>Tabular versions of the Supplementary Data Tables from the associated publication:</p> <ul> <li>Supplementary Table S1 from Publication: 14C data from sediment cores used in study</li> <li>Supplementary Table S2 from Publication: 14C data used in the GREENICE15 Stack</li> <li>Supplementary Table S3 from Publication: Tephra data used in study</li> </ul> <p>Paleomagnetic Datasets for the Characteristic Remanent Magnetizations used in this study:</p> <ul> <li>Paleomagnetic Data for Core MD99-2264</li> <li>Paleomagnetic Data for Core MD99-2265</li> <li>Paleomagnetic Data for Core MD99-2266</li> <li>Paleomagnetic Data for Core MD99-2269</li> <li>Paleomagnetic Data for Core MD99-2322</li> </ul> <p>Independent radiocarbon based Age Models for 5 cores used in this study:</p> <ul> <li>Independent Age Model for Core MD99-2264</li> <li>Independent Age Model for Core MD99-2265</li> <li>Independent Age Model for Core MD99-2266</li> <li>Independent Age Model for Core MD99-2269</li> <li>Independent Age Model for Core MD99-2322</li> </ul> <p>PSV Dynamic Time Warping (DTW) solutions of 3 cores to target curve, as described in publication</p> <ul> <li>DTW solution for MD99-2265 to target curve</li> <li>DTW solution for MD99-2266 to target curve</li> <li>DTW solution for MD99-2322 to target curve</li> </ul> <p>GREENICE15 PSV Stack</p> <ul> <li>Age model for GREENICE15 Stack using combined radiocarbon dates and correlated equivalent depth scale</li> <li>Inclination, Declination, and alpha 95 for the GREENICE15 PSV Stack</li> </ul>
NICOCO simulation data for the article "Diagnostic method for atmosphere–ocean coupling over tropical oceans at the sub-seasonal timescale"
<p>This data set includes data from an 8-year integration on the atmosphere-ocean coupled model NICOCO from 1 January 2010 to 31 December 2017. All outputs are daily averages on 1 x 1 degrees resolution. Output variables are sea surface temperature (K) and column water vapor (kg m-2). </p>
Data from: Hierarchical variation in phenotypic flexibility across timescales and associated survival selection shape the dynamics of partial seasonal migration
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Neural timescales reflect behavioral demands in freely moving rhesus macaques
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The roles of moat width and outer eyewall contraction in affecting the timescale of eyewall replacement cycle
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Data from: Identifying timescales of change in vulture social networks
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Data from: Genomic analysis suggests that mitonuclear coevolution proceeds over rapid timescales in the Amazonian Pipra manakin complex
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