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252 results for “Variability Modelling”
Dataset of "Annual Cycle of Gravity Wave Variability Derived from a High-Resolution Martian General Circulation Model" (1/3)
<p>This dataset contains the GrADS data of high-resolution Mars GCM results used for figures in the paper "Annual Cycle of Gravity Wave Variability Derived from a High-Resolution Martian General Circulation Model" by T. Kuroda, E. Yiğit and A.S. Medvedev.</p> <p>Each file contains two-dimensional (X: longitude, Y: latitude) data of surface pressure (Ps) and dust opacity in infrared wavelength (tau), and three-dimensional (X: longitude, Y: latitude, Z:sigma-level) data of temperature (T), zonal wind velocity (u), meridional wind velocity (v) and vertical wind velocity (w). Each tar.xz file contains snapshots of those data in every 1/6 Sol for Ls of 30 degrees.</p> <p>data000rdc.tar.xz: for Ls=000-030 (61 Sols)</p> <p>data030rdc.tar.xz: for Ls=030-060 (66 Sols)</p> <p>data060rdc.tar.xz: for Ls=060-090 (67 Sols)</p>
Data and analysis for "Fldgen v1.0: An Emulator with Internal Variability and Space-Time Correlation for Earth System Models"
<p>This is an archive of the raw data and analysis source code for the paper "Fldgen v1.0: An Emulator with Internal Variability and Space-Time Correlation for Earth System Models". The archive contains:</p> <ul> <li><strong>devel.Rmd : </strong>Source code for the worksheet that contains the early development and figures for the paper.</li> <li><strong>devel.html</strong> : HTML rendering of devel.Rmd</li> <li><strong>lg-ensemble-stats.Rmd </strong>: Source code for the worksheet that contains the statistical analysis described in the paper.</li> <li><strong>lg-ensemble-stats.html</strong> : HTML rendering of lg-ensemble-stats.Rmd</li> <li><strong>cc-analysis.Rmd </strong>: Analysis of the compromise conjecture raised by some readers of the paper</li> <li><strong>cc-analysis.nb.html</strong> : HTML rendering of cc-analysis.Rmd</li> <li><strong>data.tar.bz2 </strong>: Input data for the analyses above.</li> </ul> <p>The source code in this archive is written in R and requires the R runtime environment. It also uses the fldgen package, version 1.0.0, which is available at <a href="https://github.com/JGCRI/fldgen">https://github.com/JGCRI/fldgen</a></p> <p> </p>
Ocean bottom pressure variability: Can it be reliably modeled?
<p>Data set for articleen</p>
Mid-Holocene ENSO Variability reduced by northern African vegetation changes: a model intercomparison study
<p>This dataset contains model outputs from four climate models: EC-Earth, iCESM, UofT-CCSM4 and GISS. For each model, data is provided for three simulations: pre Industrial (PI), reference mid-Holocene without Green Sahara (MH_PMIP), and mid-Holocene with Green Sahara (MH_GS). For each simulation, data is provided for the variables: surface temperature, precipitation and zonal wind strength.</p>
Supplementary material 1 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Supplementary material 3 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Supplementary material 2 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Figure 3 in Potential geographic distribution niche modeling based on bioclimatic variables of three species of Temnomastax Rehn and Rehn, 1942 (Orthoptera: Eumastacidae)
Figure 3. Potential geographic distribution predicted by DOMAIN model to Temnomastax ricardoi Descamps, 1973 (blue), and Temnomastax tigris (Burr, 1899) (green). Darkest regions represent higher probabilities of occurrence than clearest regions. (■) Temnomastax ricardoi Descamps, 1973 records; (▲) Temnomastax tigris (Burr, 1899) records.
Figure 2 in Potential geographic distribution niche modeling based on bioclimatic variables of three species of Temnomastax Rehn and Rehn, 1942 (Orthoptera: Eumastacidae)
Figure 2. Potential geographic distribution predicted by DOMAIN model to Temnomastax hamus Rehn and Rehn, 1942 (green). Darkest regions represent higher probabilities of occurrence than clearest regions. On the left is marked the Andes in red, orange and yellow. (●) species records.
Figure 1 in Potential geographic distribution niche modeling based on bioclimatic variables of three species of Temnomastax Rehn and Rehn, 1942 (Orthoptera: Eumastacidae)
Figure 1. Male specimens of some studied species. (a) Temnomastax hamus Rehn and Rehn, 1942 from Minas Gerais, Brazil; (b) Temnomastax ricardoi Descamps, 1973 and (c) Temnomastax tigris (Burr, 1899) from Mato Grosso do Sul, Brazil (photos used with permission of the authors: Marcos Cesar Campis (a) and Paulo Robson de Souza (c).
Data for the manuscript entitled "AMOC variability and watermass transformations in the AWI climate model" by Sidorenko et al. 2021, submitted to JAMES
<p>Data is stored in a SHELVE persistent storage as produced in Python 3.7.4. The visualisation example is provided in a Jupyter Python Notebook.</p>
ReplicationPackage-Effects of Variability in Models: A Family of Experiments
<p>The replication package consists of raw data, processed data, experimental material, questionnaires, and analysis for the paper "Effects of Variability in Models: A Family of Experiments"</p>
Modeling the Day-to-Day Variability of Midnight Equatorial Plasma Bubbles with SAMI3/WACCM-X
<p>SAMI3/WACCM-X output files</p>
Model output for "Catchment coevolution and the geomorphic origins of variable source area hydrology"
<p>Model output supporting "Catchment coevolution and the geomorphic origins of variable source area hydrology" for submission to Water Resources Research. The Python package DupuitLEM v1.1-alpha (DOI: 10.5281/zenodo.7620978) contains the models and scripts used to generate and post-process output.</p>
Highly variable (no clear pattern). All portions of the dorsal views were equally used. In head images the area around the eye, the top of the head, the snout and the throat were all used in similar proportions. P. carbonelli Variable for both views. Snout and middle of the dorsum used in dorsal view. Top of the head most frequently (but not strictly) used in lateral view. P. guadarramae Whole body used for dorsal view (but variable); either throat (most common) or ear region used in head lateral views. P. hispanicus Variable. Anterior portion of snout used more frequently than in other species for both dorsal and head lateral views. P. liolepis Highly variable. Whole body used in most dorsal images, area around the eye and throat used in head lateral views, but other patterns common. P. lusitanicus Highly variable. All parts of the dorsum used (but frequently the most posterior part); area around the ear frequently used in head lateral images. P. tunesiacus Highly variable. Dorsal area near the insertion of the posterior limbs used more frequently than in other species; different regions of the head used, often simultaneously. P. Ʋaucheri Highly variable. Different regions of dorsum (from head to the posterior region) used in dorsal images, all portions of the head, but most frequently the throat, used in lateral images. P. Ʋirescens Highly variable. All parts of both images used. Head and anterior part of the dorsum more used than in other species. in Identification of morphologically cryptic species with computer vision models: wall lizards (Squamata: Lacertidae: Podarcis) as a case study
Highly variable (no clear pattern). All portions of the dorsal views were equally used. In head images the area around the eye, the top of the head, the snout and the throat were all used in similar proportions. P. carbonelli Variable for both views. Snout and middle of the dorsum used in dorsal view. Top of the head most frequently (but not strictly) used in lateral view. P. guadarramae Whole body used for dorsal view (but variable); either throat (most common) or ear region used in head lateral views. P. hispanicus Variable. Anterior portion of snout used more frequently than in other species for both dorsal and head lateral views. P. liolepis Highly variable. Whole body used in most dorsal images, area around the eye and throat used in head lateral views, but other patterns common. P. lusitanicus Highly variable. All parts of the dorsum used (but frequently the most posterior part); area around the ear frequently used in head lateral images. P. tunesiacus Highly variable. Dorsal area near the insertion of the posterior limbs used more frequently than in other species; different regions of the head used, often simultaneously. P. Ʋaucheri Highly variable. Different regions of dorsum (from head to the posterior region) used in dorsal images, all portions of the head, but most frequently the throat, used in lateral images. P. Ʋirescens Highly variable. All parts of both images used. Head and anterior part of the dorsum more used than in other species.
Highly variable. Mid-portion of the dorsum used frequently (although other areas as well). Tip of the snout used often, but area around the ear and throat are also relevant. P. carbonelli Variable. In the dorsal view, the tip of the snout is frequently used. In the head lateral view, the tip of the snout is also com- monly used, as well as the most posterior region of the head. P. guadarramae Variable. Mid portion of the dorsum and tip of the snout are the regions used more frequently in dorsal and head lateral views, respectively. P. hispanicus Variable. The head and most anterior part of the dorsum are frequently used in the dorsal view. Snout and/or top of posterior region of head used. P. liolepis Variable. Different parts of the dorsum are used, whereas the tip of the snout is used in most head lateral images. P. lusitanicus Anterior dorsum, in the dorsal view, and both snout and posterior side of the head (in head lateral views) frequently used. P. tunesiacus Variable. Tip of the snout and posterior part of the trunk more used than in other species; snout and top head region behind the eye used with some frequency. P. Ʋaucheri Highly variable. All parts of the dorsum used in dorsal images, various parts of the head (but frequently snout and throat combined) used in head lateral images. P. Ʋirescens Highly variable. All portions of the dorsum used in dorsal images, region around and behind the ear more used than in other species for head lateral images. in Identification of morphologically cryptic species with computer vision models: wall lizards (Squamata: Lacertidae: Podarcis) as a case study
Highly variable. Mid-portion of the dorsum used frequently (although other areas as well). Tip of the snout used often, but area around the ear and throat are also relevant. P. carbonelli Variable. In the dorsal view, the tip of the snout is frequently used. In the head lateral view, the tip of the snout is also com- monly used, as well as the most posterior region of the head. P. guadarramae Variable. Mid portion of the dorsum and tip of the snout are the regions used more frequently in dorsal and head lateral views, respectively. P. hispanicus Variable. The head and most anterior part of the dorsum are frequently used in the dorsal view. Snout and/or top of posterior region of head used. P. liolepis Variable. Different parts of the dorsum are used, whereas the tip of the snout is used in most head lateral images. P. lusitanicus Anterior dorsum, in the dorsal view, and both snout and posterior side of the head (in head lateral views) frequently used. P. tunesiacus Variable. Tip of the snout and posterior part of the trunk more used than in other species; snout and top head region behind the eye used with some frequency. P. Ʋaucheri Highly variable. All parts of the dorsum used in dorsal images, various parts of the head (but frequently snout and throat combined) used in head lateral images. P. Ʋirescens Highly variable. All portions of the dorsum used in dorsal images, region around and behind the ear more used than in other species for head lateral images.
A New GFSv15 based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability
<p>Data and analysis scripts for figures of Journal article (A New GFSv15 based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability)</p>
Variable Stoichiometry Effects on Glacial/Interglacial Ocean Model Biogeochemical Cycles and Carbon Storage - MODEL OUTPUT
<p>This is the repository for the model output and controls pertaining to the simulation experiments performed in "Variable Stoichiometry Effects on Glacial/Interglacial Ocean Model Biogeochemical Cycles and Carbon Storage" by Nathaniel Fillman, Andreas Schmittner, and Karin Kvale. Citation and DOI for parent publication will be updated here when available.<br> See https://github.com/fillmann/variable-stoichiometry for model code.</p>
data shown in manuscript "WRF-Comfort: Simulating micro-scale variability of outdoor heat stress at the city scale with a mesoscale model"
<blockquote> <p>data shown in manuscript "WRF-Comfort: Simulating micro-scale variability of outdoor heat stress at the city scale with a mesoscale model"</p> </blockquote>
Development of a Prediction Model for Intraoperative Blood Pressure Variability
ClinicalTrials.gov study NCT05698433. IPD Sharing: NO. Countries: 1. Publications: 0.
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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.