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FIGURE 11 in Computational fluid dynamics modeling of fossil ammonoid shells
FIGURE 11. Plots of pressure overlain with water velocity vectors for the Serpenticone and Oxycone shells at both 15 cm/s (A) and 5 cm/s (B) inlet velocities. At 15 cm/s the flow around the Serpenticone shell is more chaotic and there is a buildup of pressure at around the trailing coils compared to the Oxycone shell. This difference mostly disappears at 5 cm/s.
FIGURE 9 in Computational fluid dynamics modeling of fossil ammonoid shells
FIGURE 9. Water velocity around the Sphenodiscus shell at inlet velocities of 15 cm/s (A) and 5 cm/s (B). Areas of slow water velocity caused by viscous interactions are larger to the sides and immediately behind the shell at the lower velocity because water is less readily shed.
Modeling the Emission of Energetic Neutral Atoms in Titan's Dynamic Magnetospheric Environment
<p>Data for the manuscript "Modeling the Emission of Energetic Neutral Atoms in Titan's Dynamic Magnetospheric Environment" by Tippens et al., (2024). See README.txt for a description of the data files included here.</p>
Model configuration files and forcing data for Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration
<p>This repository includes the model configuration files, input data, and forcing data used for simulations in Bieri et al. (2025) - <em>Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration.</em></p> <ul> <li>forcing.tar.gz - Compressed folder containing HRLDAS Noah-MP model forcing NetCDF files <ul> <li>These forcing files were derived from the NASA Global Land Data Assimilation System (GLDAS; Beaudoing et al. 2020)</li> <li>The compressed file contains 3-hourly forcing files for the entire simulation period (01 Jun 2000 to 31 Dec 2019)</li> </ul> </li> <li>wrfinput_d01 - NetCDF file used as HRLDAS input file in HRLDAS Noah-MP simulations <ul> <li>Generated from WRF WPS (https://github.com/wrf-model/WPS)</li> </ul> </li> <li>Namelist files <ul> <li>namelist.hrldas.ROOT - Model namelist settings used for ROOT experiment</li> <li>namelist.hrldas.SOIL - Model namelist settings used for SOIL experiment</li> <li>namelist.hrldas.GW - Model namelist settings used for GW experiment</li> <li>namelist.hrldas.CONTROL - Model namelist settings used for FD (CONTROL) experiment</li> </ul> </li> </ul>
Dynamic HD Model Relative Orography Corrections
<p>Relative orography corrections for MPI's Dynamic HD model version 3.0.</p>
A Layer-averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation and Sensitivity Exploration
<p>Selected model output data for supporting this paper.</p> <p>List of Files:</p> <p>2dtracer.tar.gz: correlated tracer test</p> <p>rh3d.tar.gz: 3D Rossby-Haurwitz Wave</p> <p>modon.tar.gz: Colliding Modons</p> <p>jwss.tar.gz: Jablonowski-Williamson Baroclinic Steady State</p> <p>jwbw_1d.tar.gz: 1D data output from Jablonowski-Williamson Baroclinic Wave</p> <p>jwbw_2d.tar.gz: 2D data output from Jablonowski-Williamson Baroclinic Wave</p> <p>dcmip31.tar.gz: DCMIP3-1 nonhydrostatic gravity wave</p> <p>Klemp15.tar.gz: Nonhydrostatic Mountain Waves in Klemp et al. 2015</p> <p>held-suarez.tar.gz: Held-Suarez dry climate (post-processed data for plotting, the raw daily data are too large to upload)</p> <p>jwbwvr.tar.gz: Variable-Resolution modeling of the Jablonowski-Williamson Baroclinic Wave</p> <p> </p> <p>see https://doi.org/10.5281/zenodo.3544795 for a companion work</p> <p>References:</p> <p>Zhang, Y., J. Li, R. Yu, S. Zhang, Z. Liu, J. Huang, and Y. Zhou, 2019: A Layer-Averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation, and Sensitivity Exploration. <em>Journal of Advances in Modeling Earth Systems</em>, <strong>11,</strong> 1685-1714.</p>
Data for the Carbon Erosion Dynamics Model (CE-DYNAM)
<p>Data on soil erosion by rainfall and runoff and data on the turnover rates between carbon pools on land of the Rhine catchment for the period 1850-2005. This dataset belongs to the model code that will be published in the near future along with a paper in submission to the GMD journal.</p>
Supplementary data to Schmiester et al. *Efficient parameterization of large-scale dynamic models based on relative measurements*
<p>This archive contains Supplementary data to the manuscript <em>Efficient parameterization of large-scale dynamic models based on relative measurements</em> by Leonard Schmiester, Yannik Schälte, Fabian Fröhlich, Jan Hasenauer and Daniel Weindl.</p>
Data-driven physics-based modeling of pedestrian dynamics
<p>Python package to create physics-based pedestrian models from crowd measurements</p> <p>Github: <a href="https://github.com/c-pouw/physics-based-pedestrian-modeling">https://github.com/c-pouw/physics-based-pedestrian-modeling</a></p>
SeisSol model setup input files and supplement videos for the 3D dynamic rupture models of Wirp et al. 2024
<p>Data required to run the dynamic rupture models presented in Wirp, S. A., Gabriel, A.-A., Ulrich, T., Lorito, S. (2024). The README.txt file contains detailed information about the data and data format.</p>
SOIL-WATERGRIDS v1, mapping dynamic changes in soil moisture and depth of water table from 1970 to 2014, dataset and modelling
<p>SOIL-WATERGRIDS is a comprehensive data product of the monthly estimates of volumetric soil water content at three depths within the root zone and the depth of the water table globally gridded at a resolution of 0.25x025 degree per grid cell from 1970 to 2014. The SOIL-WATERGRIDS data product also provides the full-scale global model (BRTSim, https://sites.google.com/site/thebrtsimproject/home) that allows third party users to assess the entire volumetric soil water content and water table dynamics from land surface to 50 m depth. </p> <p>This package includes a Technical Documentation with the details about the use of the data product.</p>
Statistical analysis code for output from a model used to simulate foot-and-mouth disease dynamics in the United Kingdom
<p>Epidemics can sometimes be managed through reductions of host density, such as social distancing for human diseases, reducing plant density through cultural and genetic means, and host culling for epizootics. These approaches allow for a certain density of hosts to remain within a targeted area. By contrast, total ring depopulation is often used as a management strategy for emerging infectious diseases in livestock. In this study, we explore the trade-offs of a density-based culling strategy to determine if fewer livestock farms can be culled within rings while maintaining a decrease in disease transmission. To do so, we evaluated a farm-density-based ring culling strategy to control foot-and-mouth disease (FMD) in the United Kingdom. This strategy may allow for some farms within rings around infected premises (IPs) to escape depopulation, with the aim to prevent over-culling during outbreaks. Using a spatially-explicit, stochastic, state-transition simulation algorithm originally developed by Keeling et al. 2001 to model FMD spread in the United Kingdom, we simulated this reduced-farm-density, or "target density" strategy. We modeled FMD disease spread in four counties in the UK (Aberdeenshire, Cumbria, Devon, and North Yorkshire) that have different farm demographies. We ran 740,000 simulations in a full-factorial analysis of epidemic impact measurements (i.e. culled animals, culled farms, epidemic length) and cull strategy parameters (i.e. target farm density, daily farm cull capacity, cull radius). We found that all of the cull strategy parameters were drivers of epidemic impact. We found that outbreaks in Cumbria had higher epidemic impacts and were more likely to take off compared with other counties with more outbreaks being likely to take off in Cumbria. Most importantly, in all counties, our proposed target density strategy was more effective at combatting FMD compared with traditional 'total ring depopulation' when considering average culled animals and culled farms. The differences in epidemic impact between the counties are likely driven by farm demography, especially differences in cattle and farm density. This target density strategy can be applied to many different systems, including other livestock and agricultural systems, to reduce host density as opposed to over-culling hosts.</p>
MAgPIE v4.3.x model run outputs including dynamic forestry sector
<p>Archive of runs produced for the forestry paper using MAgPIE 4.3.1+</p> <p><a href="https://github.com/magpiemodel/magpie">Model Code</a></p> <p><a href="https://rse.pik-potsdam.de/doc/magpie/4.3/index.htm">Model documentation</a></p> <p><a href="https://github.com/magpiemodel/tutorials">Model tutorials</a></p>
Development of a global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M)
<p>Seasonal and interannual variations in global wetland area is a strong driver of fluctuations in global methane (CH<sub>4</sub>) emissions. Current maps of global wetland extent vary with wetland definition, causing substantial disagreement and large uncertainty in estimates of wetland methane emissions. To reconcile these differences for large-scale wetland CH<sub>4</sub> modeling, we developed a global Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset at ~25 km resolution at equator (0.25 arc-degree) at monthly time-step for 2000-2018. WAD2M combines a time series of surface inundation based on active and passive microwave remote sensing at coarse resolution (~25 km) with six static datasets that discriminate inland waters, agriculture, shoreline, and non-inundated wetlands. We exclude all permanent water bodies (e.g. lakes, ponds, rivers, and reservoirs), coastal wetlands (e.g., mangroves and seagrasses), and rice paddies to only represent spatiotemporal patterns of inundated and non-inundated vegetated wetlands. Globally, WAD2M estimates the long-term maximum wetland area at 13.0 million km<sup>2</sup> (Mkm<sup>2</sup>), which can be separated into three categories: mean annual minimum of inundated and non-inundated wetlands at 3.5 Mkm<sup>2</sup>, seasonally inundated wetlands at 4.0 Mkm<sup>2</sup> (mean annual maximum minus mean annual minimum), and intermittently inundated wetlands at 5.5 Mkm<sup>2</sup> (long-term maximum minus mean annual maximum). WAD2M has good spatial agreements with independent wetland inventories for major wetland complexes, i.e., the Amazon Lowland Basin and West Siberian Lowlands, with high Cohen’s kappa coefficient of 0.54 and 0.70 respectively among multiple wetlands products. By evaluating the temporal variation of WAD2M against modeled prognostic inundation (i.e., TOPMODEL) and satellite observations of inundation and soil moisture, we show that it adequately represents interannual variation as well as the effect of El Niño-Southern Oscillation on global wetland extent. This wetland extent dataset will improve estimates of wetland CH<sub>4</sub> fluxes for global-scale land surface modeling. </p> <p> </p> <p>Update: Oct.08.2021</p> <p>Documentation for WAD2M Version 2.0 can be found at <a href="https://drive.google.com/file/d/1adoAnuqu6uBWnTYKI8u_S4OAQSdgOtd6/view?usp=sharing">WAD2M_V2_update</a></p>
Test-particle simulations for "Quantifying the influence of bars on action-based dynamical modelling of disc galaxies"
<p>This contains the test-particle simulations of barred galaxies with varying bar properties (bar strength, pattern speed) which have been used in the manuscript "Quantifying the influence of bars on action-based dynamical modelling of disc galaxies" by Ghosh, S., Trick, W. H., Green G. M. (2022).</p> <p>For details for the datasets, please see the README.md file.</p> <p>For any further information, please feel free to contact Ghosh, Soumavo (ghosh@mpia.de).</p> <p> </p>
Multi-proxy agreement on Atlantic circulation dynamics since the last ice age: Model output data
<p>This dataset contains model output for the simulations presented in: <em>"Multi-proxy agreement on Atlantic circulation dynamics since the last ice age"</em>.</p> <p> </p>
Effects of temporal abiotic drivers on the dynamics of an allometric trophic network model
<p>Current ecological research and ecosystem management call for improved understanding of the abiotic drivers of community dynamics, including temperature effects on species interactions and biomass accumulation. Allometric trophic network (ATN) models, which simulate material (carbon) transfer in trophic networks from producers to consumers based on mass-specific metabolic rates, provide an attractive framework to study consumer-resource interactions from organisms to ecosystems. However, the developed ATN models rarely consider temporal changes in some key abiotic drivers that affect e.g. consumer metabolism and producer growth. Here, we evaluate how temporal changes in carrying capacity and light-dependent growth rate of producers and in temperature-dependent mass-specific metabolic rate of consumers affect ATN model dynamics, namely seasonal biomass accumulation, productivity and standing stock biomass of different trophic guilds, including age-structured fish communities. Our simulations of the pelagic Lake Constance (LC) food web indicated marked effects of temporally changing abiotic parameters on seasonal biomass accumulation of different guild groups, particularly among the lowest trophic levels (primary producers and invertebrates). While the adjustment of average irradiance had a minor effect, increasing metabolic rate associated with 1–2˚C temperature increase led to a marked decline of larval (0-year age) fish biomass, but to a substantial biomass increase of 2- and 3-year-old fish that were not predated by ≥4-year-old top predator fish, European perch. However, when averaged across the 100 simulation years, the inclusion of seasonality in abiotic drivers caused only minor changes in standing stock biomasses and productivity of different trophic guilds. Our results demonstrate the potential of introducing seasonality in and adjusting the average values of abiotic ATN model parameters to simulate temporal fluctuations in food-web dynamics, which is an important step in ATN model development aiming to e.g. assess potential future community-level responses to ongoing environmental changes.</p>
Accompanying empirical data for Kirchherr et al., 2023, "Bayesian multilevel hidden Markov models identify stable state dynamics in longitudinal recordings from macaque primary motor cortex"
<p>This repository contains data accompanying: Kirchherr et al., 2023, "Bayesian multilevel hidden Markov models identify stable state dynamics in longitudinal recordings from macaque primary motor cortex".</p> <p>Data collection methods:</p> <p>Two adult female rhesus macaques (Macaca mulatta) trained on a reaching, and grasping, and placing task served as the subjects. The animal handling as well as surgical and experimental procedures complied with European guideline (2010/63/UE) and authorized by the French Ministry for Higher Education and Research (project # 2016112713202878) in force on the care and use of laboratory animals, and were approved by the ethics committee CELYNE (comité d’éthique Lyonnais pour les neurosciences expérimentale, C2EA 42). After initial training, we performed a sterile surgery to implant six floating multielectrode arrays (FMA, Microprobes for Life Science, Gaithersburg, MD, USA) in the right (monkey 1) or left (monkey 2) cortical hemisphere. Each array was comprised of 32 platinum/iridium electrodes (impedance 0.5 MΩ at 1 kHz) with lengths ranging from 1 to 6 mm, and with an inter-electrode spacing of 400 μm. One electrode array was implanted in the primary motor cortex (M1), two were implanted in the ventral premotor cortex (F5), one in the dorsal premotor cortex (F2), and two in the prefrontal cortex (45a and 46/12r), as estimated according to a previous magnetic resonance imaging scan. For the purposes of this study, we analyzed data from the M1 array of each monkey.</p> <p>The wideband neural signal (bandpass filtered at 0.1 to 7500 kHz) was recorded at 30 kS/s, and amplified and digitized (16-bit; 0.192 μV resolution) with an Intan Tech-based (Intan Technologies, Los Angeles, CA, USA) open source acquisition system (Open Ephys; Siegle et al. 2017). This system uses a 256-channel Intan RHD2000 series acquisition board and 32-channel headstages (RHD2132). Spike detection was performed offline using Trisdesclous (Garcia & Pouzat,2015). The common reference was removed to reduce ambient noise. Spikes were then detected from each electrode using a threshold of 2 times the median absolute deviation (MAD), and analyzed as multi-unit activity (MUA) in 10 ms bins. All electrodes in which at least one well-isolated spike waveform was detected were selected for the following analyses. We thus used a sample of 21 electrodes out of 32 for monkey 1, and 25 out of 32 electrodes for monkey 2. Custom made detection panels were used to record the moments when the monkey’s hand released the handle, the hand contacted the target object, and when the object was placed in the groove. An Omniplex 16-channel recording system (Plexon, Dallas, TX, USA) was used to simultaneously record these behavioral events. Trials were discarded if the response time (time between the go signal and handle release) was less than 100 or greater than 1500 ms, the reach duration (time between handle release and object contact) was less than 100 or greater than 1000 ms, or the placing duration (time between object contact and placing the object in the groove) was less than 100 or greater than 1200 ms, leaving 19 - 68 trials per day for monkey 1 (M = 43.9, SD = 15.46, N = 439; left: M = 14.8, SD = 5.74; center: M = 14.4, SD = 5.15; right: M = 14.7, SD = 7.73), and 23 - 49 per day for monkey 2 (M = 38.3, SD = 9.87, N = 383; left: M = 14.2, SD = 3.91; center: M = 10.8, SD = 3.55; right: M = 13.3, SD = 3.37).</p> <p><br> Abstract:</p> <p>Neural populations, rather than single neurons, may be the fundamental unit of cortical computation. Analyzing chronically recorded neural population activity is challenging not only because of the high dimensionality of activity in many neurons, but also because of changes in the recorded signal that may or may not be due to neural plasticity. Hidden Markov models (HMMs) are a promising technique for analyzing such data in terms of discrete, latent states, but previous approaches have either not considered the statistical properties of neural spiking data, have not been adaptable to longitudinal data, or have not modeled condition specific differences. We present a multilevel Bayesian HMM which addresses these shortcomings by incorporating multivariate Poisson log-normal emission probability distributions, multilevel parameter estimation, and trial-specific condition covariates. We applied this framework to multi-unit neural spiking data recorded using chronically implanted multi-electrode arrays from macaque primary motor cortex during a cued reaching, grasping, and placing task. We show that the model identifies latent neural population states which are tightly linked to behavioral events, despite the model being trained without any information about event timing. We show that these events represent specific spatiotemporal patterns of neural population activity and that their relationship to behavior is consistent over days of recording. The utility and stability of this approach is demonstrated using a previously learned task, but this multilevel Bayesian HMM framework would be especially suited for future studies of long-term plasticity in neural populations.</p>
A Mixed-Flux-Based Nodal Discontinuous Galerkin Method for 3D Dynamic Rupture Modeling
<p>This repository contains data produced by a mixed-flux-based discontinuous Galerkin method for 3D dynamic rupture modeling, using the software DRDG3D (<a href="https://github.com/wqseis/drdg3d">https://github.com/wqseis/drdg3d</a>). Input scripts for the SCEC/USGS dynamic rupture benchmark validation problems (<a href="https://strike.scec.org/cvws">https://strike.scec.org/cvws</a>) and other cases are hosted on DRDG3D's GitHub page. The preprint is published at ESS Open Archive (DOI: <a href="http://doi.org/10.1002/essoar.10512657.1">10.1002/essoar.10512657.1</a>).</p>
Celluloepidemiology: a novel paradigm for quantifying infectious disease dynamics through T-cell modelling on a population level
<p>T-cell receptor sequencing (TCR-seq) was performed on enriched CD8+ T-cells. TCR clonotype annotation was performed using MiXCR v.3.0.13 with the default input parameters.</p> <p>Full origin and method description available in:<br>Celluloepidemiology: a novel paradigm for quantifying infectious disease dynamics through T-cell modelling on a population level</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.