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195 results for “Coupled models”
Data and scripts (1) for Storkey et al, "Resolution dependence of interlinked Southern Ocean biases in global coupled HadGEM3 models", GMD (2024)
<p><br> ================================================================<br> Data and scripts for producing plots from Storkey et al (2024):<br> "Resolution dependence of interlinked Southern Ocean biases in<br> global coupled HadGEM3 models"<br> ================================================================</p> <p>The plots in the paper consist of 10-year mean fields from the third <br>decade of the spin up and timeseries of scalar quantities for the first<br>150 years of the spin up. The data to produce these plots are stored<br>in the MEANS_YEARS_21-30 and TIMESERIES_DATA directories respectively.</p> <p>Note that due to the size limit on records on Zenodo, the 10-year mean <br>output from the N216-ORCA12 integration has been stored as a separate<br>record.</p> <p>Scripts to produce the plots are in SCRIPT, with section definitions<br>in SECTIONS. Bespoke plotting scripts are included in SCRIPT. They use<br>python 3 including the Matplotlib, Iris and Cartopy packages. The <br>plotting of the timeseries data used the Marine_Val VALSO-VALTRANS <br>package which is available here:</p> <p> https://github.com/JMMP-Group/MARINE_VAL/tree/main/VALSO-VALTRANS </p> <p>Much of the processing of the model output data was performed with the<br>CDFTools package, which is available here:</p> <p> https://github.com/meom-group/CDFTOOLS</p> <p>and the NCO package:</p> <p> https://web.mit.edu/course/13/13.715/nco-2.8.1/doc/</p>
Model's configuration for paper "Dynamic and Thermodynamic coupling between the Atmosphere and Ocean near the Kuroshio Current and Extension System"
<p>Here are the data used for the SKRIPS simulations. </p>
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (3 of 3)
<p>DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes the files necessary for nudging the currents towards Copernicus GLORYS12V1 reanalysis values in a simulation from 1 September to 31 December 2013.</p> <p>The remaining input files for this period are available at <a href="https://doi.org/10.5281/zenodo.12752190" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12752190</a> and <a href="https://doi.org/10.5281/zenodo.12734049" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12734049</a>.</p> <p>Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at <a href="https://doi.org/10.5281/zenodo.12752091" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12752091</a>. CPP header and runtime parameter files for the biogeochemistry module are available upon request.</p> <p>Sample output files (from the physics and biogeochemistry modules) are available at <a href="https://doi.org/10.5281/zenodo.12744506" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12744506</a> and <a href="https://doi.org/10.5281/zenodo.12746262" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12746262</a>.</p>
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: output files (1 of 2)
<p>DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes daily-mean output of all (ocean circulation, sea ice, and biogeochemistry) modules for September 2013, when the simulation was initialized. Similar files for January 2015 are available at <a href="https://doi.org/10.5281/zenodo.12746262" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12746262</a>.</p> <p>Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at <a href="https://doi.org/10.5281/zenodo.12752091" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12752091</a>. CPP header and runtime parameter files for the biogeochemistry module are available upon request.</p> <p>Sample input files for physics-only simulations are available at <a href="https://doi.org/10.5281/zenodo.12752190" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12752190</a>, <a href="https://doi.org/10.5281/zenodo.12734049" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12734049</a>, and <a href="https://doi.org/10.5281/zenodo.12735153" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12735153</a>. Input files for the biogeochemistry module are available upon request.</p>
Figure S1: 2022 HTHH Volcano Tsunami. Air-Ocean Coupled Model
<p>Model of the air-coupled tsunami showing barometric pressure data (lower panel) from the Caribbean and adjacent region stations (indicated by yellow stars) that were used in this study. Satellite image data was used to measure the radiation of the Lamb wave (barometric pressure). A numerical model of the Lamb wave that includes all variables that contribute to the modification of the propagation of the wave, such as wind and topography. Followed by a model of the Lamb wave-generated tsunami, showcasing the differences in wave energy between the Pacific Ocean and the Atlantic Ocean, as well as in the Caribbean Sea. The x-axis on the Pressure anomaly (Lamb Wave) graph in the lower panel shows time in hours from the Hunga Tonga–Hunga Haʻapai eruption (Adjusted from Sepulveda et al., 2023).</p>
A General Optimization Model for Coupling Topology and Nodal Coordinates in Large-Scale Biorthogonal Tensegrity Structures
Open the record for dataset details and reuse information.
Codes and datasets associated with the paper "Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework"
<p>Here, you will find some of the codes, images, and datasets utilized in the article: </p> <p>Basu (2017). "Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework", Optical Engineering, 56(7), 071505 (https://doi.org/10.1117/1.OE.56.7.071505)</p> <p>WRF codes: namelist.wps, namelist.input, myoutfields.txt</p> <p>NCL codes: d02_terrain.ncl, wrf_SurfaceASTD_d02.ncl</p> <p>RADAR loop: KGRR.gif</p> <p>MATLAB codes: Plot_Buoy.m</p> <p>Note: buoy datasets are available publicly from https://www.ndbc.noaa.gov/ </p>
Experiments on the snowfall, temperature, and humidity to the Arctic summer snowstorm using ocean-ice couple model (POP2-CICE5) with JRA55-do and MERRA2 forcing
<p><span>In the Arctic, short-lived summer snowstorms can provide snow cover that can increase surface reflectivity and heat capacity. Despite their potential importance, little research has been done to understand the impact of summer snowstorms on basin-scale Arctic sea ice cover. Our observational analysis shows that a summer snowstorm event is accompanied by cyclonic ice drift, increases in surface albedo and surface air cooling that can persist for up to ~2 weeks, dampening sea ice loss. Specifically, multiple snowstorm events in a summer, on average, results in net increase in sea ice extent of ~0.2×106 km<sup>2</sup> by early September. Experiments with a sophisticated ice-ocean model framework indicate that the initial expansion of sea ice extent is driven by cyclonic wind-driven ice drifts driving sea ice southwards and increasing albedo around the summer ice edge, however the thermal effects from the associated snowfall and atmospheric conditions result in a stronger overall impact on basin-averaged sea ice extent at seasonal scales.</span></p> <p><span>Additional model experiments were carried out to isolate the physical processes contributing to the thermal response of Arctic sea ice to summer snowstorms. Our results show the impact of surface air cooling on sea ice extent is about 3.5 times larger than the snowfall/albedo response. However, our simulated albedo response is weaker than the observed response, likely due to the negligible difference in surface albedo between old snow and freshly fallen snow – a limiting factor in our analysis and a topic worthy of future focus.</span></p>
Simulations of Typhoon In-Fa (2106) and air-sea interactions using a coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system
<p>The Observation data supporting the result of our manucript submitted to JGR-Ocean.</p> <p> </p>
Supporting data to run the inverse model of coupled phosphorus, carbon and oxygen model.
<p>Supporting data to run the inverse model of coupled phosphorus, carbon and oxygen model. </p>
Data from: In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model
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Experiments on the snowfall, temperature, and humidity to the Arctic summer snowstorm using ocean-ice couple model (POP2-CICE5) with JRA55-do and MERRA2 forcing
Open the record for dataset details and reuse information.
Data from: A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and in situ study
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Data from: Coupled land use and ecological models reveal emergence and feedbacks in socio‐ecological systems
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Data from: Fruiting strategies of perennial plants: a resource budget model to couple mast seeding to pollination efficiency and resource allocation strategies
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Nanoparticle-coupled topical methotrexate effectively inhibits inflammation and induces re-modeling in pre-clinical psoriasis
GEO Series GSE126066. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
Perturb-map coupled with spatial transcriptomics identifies mutation associated gene signatures in a mouse model of lung adenocarcinoma
GEO Series GSE193460. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
Simulating and Evaluating the Global Aerosol Distributions with the Online Aerosol Coupled CAS-FGOALS Model
<p>We implement an existing aerosol module named Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) in the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System (CAS-FGOALS) model and simulate the global aerosol properties over 2002-2014. The CAS FGOALS modeling outputs associated with the work are stored here.</p>
Coupling the Rice Convection Model-Equilibrium to the Lyon– Fedder–Mobarry Global Magnetohydrodynamic Model
<p>Self-consistent inner-magnetosphere model is driven by inputs from the Lyon-Fedder- Mobarry global magnetohydrodynamic model.</p> <p>The expanded inner magnotospheric modeling region captures high-resolution bursty bulk flows in the plasma sheet.</p> <p>Realistic bursty bulk flows induced aurora patterns are simulated.</p> <p>This includes data and visualization methods that reproduce the figures in the manuscript. Please refer to README for details.</p> <p>Submitted to JGR for review. </p>
Monte-Carlo simulation of dike stability based on a coupled hydro-stability model
<p>With a large network of dikes that in the future will protect up to 15% of the worlds population from flooding, more extreme river discharges that result from climate change will dramatically increase the flood risk of these protected societies. Precise calculations of dike stability under adverse loading conditions will become increasingly important, though the hydrological impacts on dike stability, particularly the effects of groundwater flow, are often oversimplified in stability calculations. In order to better take account of groundwater flow processes, we use a coupled hydro-stability model to indicate relations between the geometry, subsurface materials, groundwater hydrology and stability of a dike. To calculate the stability, the most adverse drained loading conditions are applied to soil slip and basal sliding mechanisms. A database created by an extensive Monte Carlo analysis provides evidence for relations between geometry, material characteristics, hydrology and stability for three different failure processes. The database contains parameter combinations and the corresponding safety factor F. The database can be used to estimate failure probabilities for dike stretches that have not been assessed in detail, while including the uncertainties caused by a lack of in-situ data. </p>
ScienceDex guides
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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.