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364 results for “Convection”
Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model"
<p>Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model" by Shuhei Matsugishi and Masaki Satoh doi: 10.1029/2021MS002636</p>
Variations of Subgrid-scale Turbulent Fluxes in the Convective Boundary Layer at Gray Zone Resolutions
<p>This dataset contains the data used in the submitted manuscript of Liu and Zhou 2022 JAS. Please refer to the manuscript for the detailed description of the dataset.</p>
Driving Forces of Extreme Updrafts Associated with Convective Bursts in the Eyewall of a Simulated Tropical Cyclone
<p>The model-simulated data used in this study are uploaded here. Due to the large number, the original simulation data are available on request (qnn_nancy@yahoo.com).</p>
Processed microphysical profiles of convective cloud scenes from satellite over ATTO
<p class="MsoNormal">We present a new approach of analyzing and interpreting vertical profiles of cloud microstructure obtained by satellite remote sensing. The method is based on a spectral bin microphysics adiabatic parcel model and aims to elucidate the effects of aerosols on the evolution of convective clouds and related microphysical processes, including the activation of cloud condensation nuclei (CCN), the growth of cloud droplets, and the formation of precipitation. Characteristic features in the vertical profiles of effective radius (<em><span>r</span></em><sub>e</sub>) and temperature (<em>T</em>) reveal different microphysical zones in convective clouds related to the change increase of <em><span>r</span></em><sub>e</sub> with decreasing <em>T</em>. The classification of the different microphysical zones includes the (1) condensational growth of droplets, (2) growth by coalescence, (3) rainout, (4) secondary droplet activation zone (<em>SAZ</em>), (5) mixed-phase of ice particles and water droplets and (6) glaciation of the cloud. The detection of the <em>SAZ</em> is introduced here for the first time. This method allows us to identify the activation of aerosol particles above cloud base and their role in the invigoration of deep convective clouds.</p>
Type IIP Supernova Progenitors. III. Blue to Red Supergiant Ratio in Low-metallicity Models with Convective Overshoot (Dataset)
<p>MESA input and output files associated with the published journal article Wagle et al. (2020; doi:10.3847/1538-4357/ab8bd5). We used MESA version r-10398 and MESA SDK version 20180822 to run these models.</p> <p>The "MESA_inputs.tar.gz" file contains work directories for initial mass of 13 solar mass and several overshoot parameter (f) values as listed in Table 2 of the published article. The models can be run directly from each working directory ("f_*") by making (./mk) and then running MESA (./rn), after instantiating MESA SDK. The run-script ("rn") is modified to start a MESA run from the pre-main-sequence (preMS) stage through core-collapse (CC) stage, if the LOGS and photos directories are absent. Otherwise, it restarts MESA from the latest "photo" binary file saved in the photos directory (that is, it assumes that the previous run was interrupted and restarts the run. So, to start a fresh run delete the "LOGS" and "photos" directories.) Each working directory has "run_star_extras.f" file which is modified to save the compactness parameters, mu_4, M_4 as extra history columns, as well as, to implement additional temporal resolution constraints as explained in section 2.2 of the article. Any other combination of mass and f-value from Table 2 of the article can be run by changing initial_mass in "inlist_control" file, and overshoot values in "inlist_f*" file.</p> <p>Each "*M_z0.006_f_*.tar.xz" file has a "LOGS" directory that contains corresponding "history.data", "profile.data" at core-collapse (CC) stage and saved model ("*.mod") at CC stage for each mass and f-value combination from Table 2 of the paper. (Note: Please copy the tar.xz files for each mass in a separate folder before decompressing them, in order to avoid overwriting the folders with the same f-values.) The LOGS directory also contains a folder "png_plots" that has saved ".png" files generated by "inlist_pgstar". These files can be used to generate stellar evolution movies using the "images_to_movie.sh" script available in the MESA SDK.</p> <p> </p>
CM1 files for JGR-Atmospheres Paper Sensitivities of Cross-Tropopause Transport in Midlatitude Overshooting Convection to the Lower Stratosphere Environment
<p>Initial conditions to run the CM1 model simulations used in the JGR-Atmospheres Paper <em>Sensitivities of Cross-Tropopause Transport in Midlatitude Overshooting Convection to the Lower Stratosphere Environment</em>. The namelist.input file contains the initial conditions used to run the simulations, and the input sounding files (input_sounding_st_plume, input_sounding_st_noplume, input_sounding_dt_plume, input_sounding_dt_noplume) are the initial soundings used to run the CM1 model for each of the four different stratospheric environments. </p>
Lagrangian Heavy Precipitation Events in convection-permitting Regional Climate Models over the Alps and in the Mediterranean
<p>The csv datafile contains a set of heavy precipitation events identified in cpRCMs.</p> <p>Each of the entries represents an event and is described with detailed properties:</p> <p>'Start Date [YYYYMMDD.HOUR/24]', 'Latitude [°]', 'Longitude [°]',<br> 'Duration [h]', 'Volume [km² h]', 'P99(pr) [mm h-1]',<br> 'P90(pr) [mm h-1]', 'P75(pr) [mm h-1]',<br> 'P50(pr) [mm h-1]', 'P25(pr) [mm h-1]',<br> 'P10(pr) [mm h-1]', 'Total Precipitation [m3]',<br> 'Maximum Precipitation [mm h-1$]',<br> 'Mean Precipitation [mm h-1$]', 'Direction [°]',<br> 'Distance Traveled [km]', 'Eccentricity [-]', 'Track Eccentricity [-]',<br> 'Mean Ellipsicity [-]', 'Track Ellipsicity [-]', 'Mean Major Angle [°]',<br> 'Track Major Angle [°]', 'Mean Major Axis [-]', 'Track Major Axis [-]',<br> 'My Orientation [°]', 'My Track Orientation [°]', 'max(Elevation) [m]',<br> 'min(Elevation) [m]', 'Start Year [YYYY]', 'Start Month [MM]',<br> 'LandFallSea [-]', 'Scenarios', 'Models', 'situations', 'Ensemble',<br> 'Speed [km h$^{-1}$]', 'Mean(Area) [km²]', 'orographic [-]',<br> 'Severity [-]', 'I/O OBS [-]', 'Region [-]', 'orographic1500 [-]',<br> 'orographic2000 [-]', 'orographic2500 [-]', 'orographic3000 [-]']</p>
How well does a convection-permitting climate model represent the reverse orographic effect of extreme hourly precipitation? - Observed precipitation data
<p>The dataset contains the rain gauge hourly rainfall series used in the paper "How well does a convection-permitting climate model represent the reverse orographic effect of extreme hourly precipitation?". Each rain gauge series is saved in one Matlab variable, organized as a structure S with five fields:</p> <p>S.name: the identification name of the rain gauge station</p> <p>S.vals_mm: series of hourly rainfall in millimeter</p> <p>S.time_utc: time steps series, in UTC time</p> <p>S.elev_m: elevation of the station, in m a.s.l.</p> <p>S.xy_utm: station coordinates X and Y in meter in the Reference system WGS84/UTM zone 32N</p>
Effect of Soil Moisture on Future Heatwaves over Eastern China: Convection-Permitting Regional Climate Simulations
<p>Data used in the manuscript "Effect of Soil Moisture on Future Heatwaves Over Eastern China: Convection-Permitting Regional Climate Simulations" which will be submitted to Journal of Geophysical Research: Atmospheres.</p>
Advancing Wood Quality with Convective Vacuum Drying and its Influence on Multiple Properties of Mangifera Indica L. Timber
<p>This study explores the impact of convective vacuum drying on the quality of Mangifera indica L. timber, focusing on key parameters such as drying rate, time, and alterations in mechanical, physical, and anatomical properties. By significantly reducing moisture content, this method aims to enhance basic density, reduce volumetric shrinkage, and improve mechanical strength. Additionally, the study examines potential anatomical changes, including vessel and fiber dimensions, and assesses the overall suitability of convective vacuum drying for improving timber quality for industrial applications.</p>
Data from: Moist heatwaves intensified by entrainment of dry air that limits deep convection
<p>Moist heatwaves in the tropics and subtropics pose substantial risks to society, yet the dynamics governing their intensity are not fully understood. The onset of deep convection arising from hot, moist near-surface air has been thought to limit the magnitude of moist heatwaves. Here, we use reanalysis data, and output from the Coupled Model Intercomparison Project Phase 6 and model entrainment perturbation experiments, to show that entrainment of unsaturated air in the lower-free troposphere (roughly 1--3 km above the surface) limits deep convection, thereby allowing much higher near-surface moist heat. Regions with large-scale subsidence and a dry lower-free troposphere, such as coastal areas adjacent to hot and arid land, are thus particularly susceptible to moist heat waves. Even in convective regions such as the northern Indian Plain, southeast Asia, and interior South America, the lower-free tropospheric dryness strongly affects the maximum surface wet-bulb temperature. As the climate warms, the dryness (relative to saturation) of the lower-free tropospheric air increases; this allows for a larger increase of extreme moist heat, further elevating the likelihood of moist heatwaves.</p>
Role of Troposphere-Convection-Land Coupling in the Southwestern Amazon Precipitation Bias of the Community Earth System Model version 1 (CESM1)
<p>Necessary outputs and scripts for recreating the figures for the journal article with the same title.</p>
Training and testing data, associated code and estimators for emulating a convection scheme
<p>Data and code for a random-forest convection scheme associated with the paper:</p> <p>"Using machine learning to parameterize moist convection: potential for modeling of climate, climate change and extreme events"</p> <p>by Paul A. O'Gorman and John G. Dwyer (to appear in JAMES)</p>
Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/arXiv:1806.06869">Aerts et al. (2018)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4365/aaccfb">10.3847/1538-4365/aaccfb</a></p>
The C-flame Quenching by Convective Boundary Mixing in Super-AGB Stars and the Formation of Hybrid C/O/Ne White Dwarfs and SN Progenitors
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2013ApJ...772...37D/abstract">Denissenkov et al. (2013)</a>. MESA version 4631.</p> <p>Publication DOI: <a href="https://doi.org/10.1088/0004-637X/772/1/37">10.1088/0004-637X/772/1/37</a></p>
3D hydrodynamic simulations of C ingestion into a convective O shell: Animated visualisations
<p>Animated visualisations of the 3D simulations presented by Andrassy et al. (2019), arXiv:1808.04014.</p>
The observational signatures of convectively excited gravity modes in main-sequence stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2013MNRAS.430.1736S">The observational signatures of convectively excited gravity modes in main-sequence stars</a></p>
Modules for Experiments in Stellar Astrophysics (MESA): Convective Boundaries, Element Diffusion, and Massive Star Explosions
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018ApJS..234...34P/abstract">Modules for Experiments in Stellar Astrophysics (MESA): Convective Boundaries, Element Diffusion, and Massive Star Explosions</a></p>
The shape of convective core overshooting from gravity-mode period spacings
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018arXiv180202051P/abstract">The shape of convective core overshooting from gravity-mode period spacings</a></p>
The Physics of Changing Tectonic Regimes: Implications for the Temporal Evolution of Mantle Convection and the Thermal History of Venus
<p>Input and relevant data files for "The Physics of Changing Tectonic Regimes: Implications for the Temporal Evolution of Mantle Convection and the Thermal History of Venus." Each data set was used to generate figures in text, and was used with, or obtained from, CitcomS (v3.3).</p> <p> </p> <p>diagnostic.dat contains internal metrics [#step time Mobility Tint T_asthen_avg D U Uc RMS_Velocity]<br> Where #step is iteration number, time is the non dimensional diffusion time scale for the step, Mobility is defined in text, Tint is the mid mantle temperature (average), T_asthen_avg is the upper mantle temperature (average), D U Uc not used, and RMS_Velocity is the root mean square velocity.</p> <p> </p> <p>Nusselt.dat contains heat flow information [time, surface nusselt number, basal nusselt number].</p> <p>Time is the non dimensional diffusion time scale for the step. nusselt numbers are nondimesional heatflow from the surface (lithosphere) and base (core).<br> </p> <p>Melt2.dat contains melting information. #step is iteration number, time is the non dimensional diffusion time scale for the step,</p> <p>non-dimensional melt</p> <p> </p> <p>the input.* file is the model input file used with CitcomS (v3.3) that includes all parameters used for the reference case. Variations from this file are described in text.</p>
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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)
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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.