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20 results for “atmospheric circulation”
Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation
<p>Here is the surface mass balance calculated from a offline subsurface model, that is used in the paper Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation.<br> More data are available by contacting nichsen@space.dtu.dk</p>
Phanerozoic global climatic fields simulated using the FOAM ocean-atmosphere general circulation model
<p>These files contain the output of Phanerozoic global climate simulations conducted using the coupled ocean-atmosphere FOAM general circulation model. They are available every 20 Myrs between 540 Ma and 0 Ma, both included. All simulations have been conducted using identical boundary conditions; pCO2: 2240 ppm, solar luminosity: 1368 W m-2, vegetation: rocky desert, orbital configuration: null eccentricity and minimum obliquity. Only the continental configuration was varied from one time slice to the other (sensitivity test to the continental configuration), using the reconstructions of Scotese and Wright (https://www.earthbyte.org/paleodem-resource-scotese-and-wright-2018/).</p> <p>The reader is referred to the associated paper for a full description of the model and boundary conditions.</p> <p>All file names use the following pattern: "[age]rd_1368W_EccN_[model_component]_2240ppm.nc", with [age], the age expressed in million years ago, and [model_component] being 'atmos', 'ocean' or 'coupl' (atmospheric and oceanic components, plus coupler).</p>
Dataset for "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation"
<p>These documents are supplements to the "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation" paper published by the same authors in The Planetary Science Journal in 2022.</p> <p>Are made available:</p> <p>-the Supporting Information document on the performed sensitivity study,<br> "paper_mtWRF_lake_RT_220825_SI.pdf"</p> <p>-the Fortran source code of the radiative transfer module developed for this work,<br> "module_ra_gray.F"</p> <p>-all the netCDF simulation outputs and a list describing their parameters,<br> "run-##.nc.gz"<br> "list_simulations_2D_paper2022_RT_zenodo.pdf"</p> <p>-the Python codes to plot figures from the netCDF output files,<br> "mtwrf_analysis_#D_#.py"</p>
Data & figures: Comparison between Large-Scale Observed and Simulated Antarctic Sea-Ice Variability Response to Changes in Atmospheric and Oceanic Circulation
<p>These are the model data, key figures, and Python code generated during the project titled “Comparison between Large-Scale Observed and Simulated Antarctic Sea-Ice Variability Response to Changes in Atmospheric and Oceanic Circulation." This project was undertaken during a 3-month research scholarship at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, funded by the Helmholtz Visiting Researcher Grant, a program promoted by the Helmholtz Information and Data Science Academy (HIDA). Statistical methods pertain to the coupling of sea surface temperature and Antarctic sea-ice interactions. These methods can be applied to observations, reanalysis, and earth system model data</p>
Data and GrADS scripts for "Effect of atmospheric circulation on surface air temperature trends in years 1979-2018" (forthcoming in Climate Dynamics)
<p>Data and GrADS scripts associated with "Effect of atmospheric circulation on surface air temperature trends in years 1979-2018", forthcoming in Climate Dynamics.</p> <p>The README file, the scripts and the GrADS data descriptor files are in the file "circulation.zip". Unpacking this with "unzip circulation.zip" creates the directory "circulation" together with the individual files.</p> <p>The three netcdf data files (T_anomalies_ERA5_1979-2018.nc, T_anomalies_circ_1979-2018.nc and T_trends_CMIP5_42mod_1979-2018.nc) must be downloaded to the same "circulation" directory for the GrADS scripts to work.</p> <p>See the README file within "circulation.zip" for further information.</p> <p> </p>
Global Catastrophic Effects on Future Climate due to Increasing Total Solar Irradiance. A General Atmospheric Circulation Analysis.
<p>10-yr CESM run with standard TSI (BGCN_T31_g37.cam.h0*)</p> <p>10-yr CESM run with TSI +10% (BGCN_T31_g37_TSI10p.cam.h0*)</p>
Data for: Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model
<p>This dataset, provided in NetCDF format, supports the research presented in the paper titled "Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model." Please contact Dr. Sun (ltsun@rams.colostate.edu) if you have any questions.</p>
Atmospheric circulation sensitivity to changes in the vertical structure of polar warming
<p>This is the dataset used to make main figures of Atmospheric circulation sensitivity to changes in the vertical structure of polar warming (2021), GRL (<em>in preparation</em>).</p> <p>Please refer to the method section.</p> <p>1. The name of GRAM experiments, bot, mid1, mid2, and mid3 indicate L990, L850, L700, and L550 forcing respectively. Depending on the forcing amplitude, it varies 1X to 5.5X. The control run for GRAM is ctl_GRAM.nc.</p> <p>2. There are additional data for L990 and L650 for AM2 experiments. The control run for AM2 is ctl_AM2.nc.</p> <p>3. kernel_GRAM.mat = the radiative Kerel which is the OLR response to incremental increases in temperature of 1 K at each vertical level and the surface, based on GRaM (Lowest level is the surface kernel).</p> <p> </p> <p>Arctic domain averaged monthly temperature kernel data for figure 2d :</p> <p>1. ERA-Interim (Huang et al. 2017); the original data can be obtained from <a href="https://huanggroup.wordpress.com/research/">https://huanggroup.wordpress.com/research/</a>.</p> <p>2. GFDL-AM2 Aquaplanet (Feldl et al. 2017); the original data can be obtained from <a href="https://climate.rsmas.miami.edu/data/radiative-kernels">https://climate.rsmas.miami.edu/data/radiative-kernels</a>.</p>
Code and Data to support "Atmospheric circulation-constrained model sensitivity recalibrates Arctic climate projections"
<p><a href="https://zenodo.org/api/files/b2d03cf8-c9e1-4ffb-8120-eb08237612e6/sic.sep.5member.dat">sic.sep.5member.dat</a> contains direct binary data of spatial monthly averaged sea ice concentrations for 1979 January to 2020 December from the CESM2 wind-nudging runs.</p> <p><a href="https://zenodo.org/api/files/b2d03cf8-c9e1-4ffb-8120-eb08237612e6/cism2.exp.smb.01.nc">cism2.exp.smb.01.nc</a> to <a href="https://zenodo.org/api/files/b2d03cf8-c9e1-4ffb-8120-eb08237612e6/cism2.exp.smb.01.nc">cism2.exp.smb.05.nc</a> contain netcdf files of annual averaged surface mass balance output from the CESM2-CISM2 wind-nudging runs between 1979 and 2020.</p> <p>topal&ding_code1.py - data preparation Python code</p> <p>topal&ding_code2.py - creating the main text and supplementary figures.</p>
Data and Supplementary Plots for A Shallow Water Model Exploration of Atmospheric Circulation on Sub-Neptunes
<p>This repository contains geopotential maps, zonal wind plots, gifs, and data for the ensemble of possible sub-Neptunes presented in the main manuscript. The data, individual plots, and plot grids are based on the averages of the last 100 simulated days. The data are in the pickle format (see https://docs.python.org/3/library/pickle.html)<br> The gifs are based on the last 1000 simulated hours. These figures and gifs support the analysis presented in the main manuscript.</p>
Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"
<p>Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> ===========================================================</p> <p>This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models.</p> <p>Generating Plots<br> ---------------</p> <p>The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour.</p> <p><em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script.</p> <p>Source Code Modifications<br> ----------------</p> <p><strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow.</p> <p><strong>MPAS</strong></p> <p>The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.</p>
Data from: "Injection strategy - a driver of atmospheric circulation and ozone response to stratospheric aerosol geoengineering" by Bednarz et al. (2023)
<p>Data from: "Injection strategy - a driver of atmospheric circulation and ozone response to stratospheric aerosol geoengineering" by Bednarz et al. (2023), which has been accepted for publication in Atmospheric Chemistry and Physics.</p>
Data for "Machine Learning Parameterization of Subgrid-Scale Orographic Gravity Wave Drag in a Middle-Atmosphere General Circulation Model" by Lu et al., submitted to JAMES, 2022.
<p>The NetCDF data file involving the decision tree strucutre attributes of the random forest emulator.</p> <p>gcm_regressors/<br> The data file involving the decision tree strucutre attributes (in NetCDF format)</p>
Gravity Wave Morphology During the 2018 Sudden Stratospheric Warming Simulated by a Whole Neutral Atmosphere General Circulation Model
<p>This dataset includes a complete set of raw data, metadata and saved session data which is necessary for re-producing figures in a paper entitled "Gravity Wave Morphology During the 2018 Sudden Stratospheric Warming Simulated by a Whole Neutral Atmosphere General Circulation Model" submitted to the Journal of Geophysical Research - Atmosphere.</p>
Influence of thermospheric impacts of solar activity on the general circulation and long-period planetary waves in the middle atmosphere
<p>This dataset contains model output files and examples of scripts for depicting figures related to the article "Influence of thermospheric impacts of solar activity on the general circulation and long-period planetary waves in the middle atmosphere " by A.V. Koval, N. M. Gavrilov, A. I. Pogoreltsev, N. O. Shevchuk.</p> <p><br> Contents:<br> Output data from model simulations averaged over 16 pairs of model runs with high and low solar activity:</p> <p><br> gh_m1_hsa5.dx, gh_m1_lsa5.dx – amplitudes of the geopotential height variations in g.p.m. at high and low solar activity caused by long-period PW modes with zonal wavenumber 1 averaged over 80 time subintervals selected from pairs of the MUAM runs (structure described in w1_tp1_hsa.ctl, w1_tp1_lsa.ctl).<br> gh_m2_hsa5.dx, gh_m2_lsa5.dx, gh_m3_hsa5.dx, gh_m3_lsa5.dx, gh_m4_hsa5.dx, gh_m4_lsa5.dx – the same but for zonal wavenumbers 2,3,4.<br> gh_m1_disp_dif5.dx – dispersion of differences in corresponding wave amplitudes between high and low solar activitiy (w1_tp1_disp.ctl).<br> gh_m2_disp_dif5.dx, gh_m3_disp_dif5.dx, gh_m4_disp_dif5.dx – the same but for zonal wavenumbers 2,3,4.<br> index_refr1_1_5.dx, index_refr1_2_5.dx, index_refr1_3_5.dx, index_refr1_4_5.dx – the zonal-mean quasi-geostrophic complex refractivity index squared (RI2) for PW modes with zonal wavenumbers 1-4 (ind_refr1_1.ctl).<br> uq_vwres1_pv_Jan_1_5.dx, uq_vwres1_pv_Jan_2_5.dx, uq_vwres1_pv_Jan_3_5.dx, uq_vwres1_pv_Jan_4_5.dx – the Eliassen-Palm flux for PW modes with zonal wavenumbers 1-4 (uqep1_vwres_1.ctl).<br> zw_a0_grads5_hsa.dx, tp_a0_grads5_hsa.dx – zonal-mean zonal wind in m/s and temperature in K for December – February averaged over 16-member ensemble of model runs for high solar activity (m0_zw5_hsa.ctl, m0_tp5_hsa.ctl).<br> zw_a0_grads5_lsa.dx, tp_a0_grads5_lsa.dx – the same but for the low solar activity<br> disp_U_dif5_.dx, disp_T_dif5_.dx – dispersion of differences in zonal wind and temperature between high and low solar activitiy for December – February averaged over 16-member ensemble of model runs (tp1_disp.ctl).<br> Additional data including outputs from separate model runs are available from the authors upon request.</p>
Selected data analyzed in the JGR Atmosphere manuscript "Atmospheric meridional circulation between South Asia and Tibetan Plateau caused by the change of planetary boundary layer depth."
<p>1. The PBL depth dataset including the PBL type (the convective boundary layer, the neutral boundary layer, and the stable boundary layer) and the calculated the PBL depths at the 19 stations for the 2013-2015 summers.</p> <p>2. The control experiment (WRF-CTL) and the MEP experiment (WRF-MEP) simulations results including PBL depth and geopotential height at 500 hPa at 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 and hourly sensible and latent heat. The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day.</p>
Selected data analyzed in the JGR Atmosphere manuscript "Atmospheric meridional circulation between South Asia and Tibetan Plateau caused by the change of planetary boundary layer depth."
<p>1. The PBL depth dataset including the PBL type (the convective boundary layer, the neutral boundary layer, and the stable boundary layer) and the calculated the PBL depths at the 19 stations for the 2013-2015 summers.</p> <p>2. The control experiment (WRF-CTL) and the MEP experiment (WRF-MEP) simulations results including PBL depth and geopotential height at 500 hPa at 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 and hourly sensible, latent heat and thermal radiation (net longwave radiation). The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day.</p>
Ivanciu et al., 2020 - Effects of prescribed CMIP6 ozone on simulating the Southern Hemisphere atmospheric circulation response to ozone depletion
<p>Model data used in the analysis published in the study by Ivanciu et al., 2020 "Effects of prescribed CMIP6 ozone on simulating the Southern Hemisphere atmospheric circulation response to ozone depletion". The data was produced using the coupled climate model FOCI (Flexible Ocean and Climate Infrastructure, Matthes et al., 2020). An overview of the available fields can be found in the README.md file.</p>
The data for "Climatology of the Residual Mean Circulation of the Martian Atmosphere and Contributions of Resolved and Unresolved Waves Based on a Reanalysis Dataset" by A. Asumi, K. Sato, M. Kohma, and Y. Hayashi in JGR, Planet
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LBA-ECO CD-01 Simulated Atmospheric Circulation, CO2 Variation, Tapajos: August 2001
We have investigated mesoscale variations of atmospheric CO2 over a heterogeneous landscape of forests, pastures, and large rivers during the Santarem Mesoscale Campaign (SMC) of August 2001. The variations of atmospheric CO2 concentration were simulated using the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS) with four nested grids that included a 1-km finest grid centered on the Flona Tapajos. Surface fluxes of CO2 were prescribed in the model using idealized diurnal cycles over forest and pasture vegetation derived from flux tower observations, and over surface water using a value suggested by in situ measurements in the Amazon region. The distribution of vegetation types was derived from the 1-km International Geosphere-Biosphere Programme (IGBP) land-cover dataset version 2.0. Our simulation ran from the 1st through the 15th of August 2001, which was concurrent with the SMC. Evaluation against flux tower observations and the SMC field measurements shows that, in many respects, the model captures observed meteorological variables and CO2 concentrations reasonably well. The results also suggest that the local topography, differences in roughness length between water and land, the T shape juxtaposition of Amazon and Tapajos Rivers, and the resulting horizontal and vertical wind shears, all facilitated the generation of local mesoscale circulations. Possible mechanisms producing a lower level convergence line near the east bank of the Tapajos River during strong trade-wind conditions are also explored. Our modeling study is helping us to understand observed patterns of CO2 fluxes and concentration distribution obtained from flux towers and light aircraft.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.