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143 results for “Boundary layer”
Generative convective parametrization of a dry atmospheric boundary layer
<p>The repository contains simulation snapshots of a dry convective boundary layer (CBL). The snapshots comprise horizontal snapshots of vertical velocity (w) and buoyancy (b) field at three heights, namely z/h(t) = 0.2, 0.5, 1.0. Further, the Python scripts for the Generative Adversarial Network (GAN) are also provided, as well as the DNS renormalization procedure.</p>
Bonanza Creek LTER: Annual Active Layer Depths from 2004 to Present in the Boundary Fire Fireline near Fairbanks, Alaska
In 2004 the Boundary Fire burned an area within the Caribou Poker Creeks Research Watershed providing an opportunity to study various fire effects. When wildfire burns through a northern black spruce forest there is usually a subsequent increase in depth of thaw, due to the reduction in the depth of the organic layer. The construction of firelines with heavy machinery involves the complete removal of the organic layer and results in an even greater increase in active layer. This study was designed as a long-term comparison between depth of thaw on firelines, burned and unburned black spruce forest underlain by ice rich permafrost. This study will allow us to compare thaw depths from recent firelines to those studied at the Wickersham and Bonanza Creek fireline study sites. Within the fireline bulldozers were used to knock down and in some cases remove, the trees and organic layer. Within the safety zone an area approximately 30 m x 30 m was cleared to mineral soil. After the fire was out an excavator was used to return the organic material to the fireline and safety zones.
Centre frequencies and uncertainties for "Evidence for a kilometre-scale seismically slow layer atop the core-mantle boundary from normal modes"
<p>A table containing the centre frequencies and uncertainties used for the study presented in "Evidence for a kilometre-scale seismically slow layer atop the core-mantle boundary from normal modes". This table is the same as is contained in the supplementary materials of that paper.</p> <p>Russell, S., Irving, J. C. E., Jagt, L., & Cottaar, S. (2023). Evidence for a kilometer-scale seismically slow layer atop the core-mantle boundary from normal modes. Geophysical Research Letters, 50, e2023GL105684. <a href="https://doi.org/10.1029/2023GL105684">https://doi.org/10.1029/2023GL105684</a></p>
Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves_for JGR submission
<p>This folder contains preprocessed data, data processing scripts, Reynolds Averaged Navier Stokes (RANS) simulation scripts, and plotting scripts that produce the results in the manuscript entitled, "Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves," for submission to Journal of Geophysical Research Oceans by Trowbridge, Helfrich, Reeder, Medley, Chang, Jan, Ramp, and Yang.</p> <p> </p>
Marine plastics alter the organic matter composition of the air-sea boundary layer, with influences on CO2 exchange: a large-scale analysis method to explore future ocean scenarios
<p>Microplastics are substrates for microbial activity and can influence biomass production. This has potentially important implications in the sea-surface microlayer, the marine boundary layer that controls gas exchange with the atmosphere and where biologically produced organic compounds can accumulate. In the present study, we used six large scale mesocosms to simulate future ocean scenarios of high plastic concentration. Each mesocosm was filled with 3 m3 of seawater from the oligotrophic Sea of Crete, in the Eastern Mediterranean Sea. A known amount of standard polystyrene microbeads of 30 μm diameter was added to three replicate mesocosms, while maintaining the remaining three as plastic-free controls. Over the course of a 12-day experiment, we explored microbial organic matter dynamics in the sea-surface microlayer in the presence and absence of microplastic contamination of the underlying water. Our study shows that microplastics increased both biomass production and enrichment of carbohydrate-like and proteinaceous marine gel compounds in the sea-surface microlayer. Importantly, this resulted in a 3 % reduction in the concentration of dissolved CO2 in the underlying water. This reduction was associated to both direct and indirect impacts of microplastic pollution on the uptake of CO2 within the marine carbon cycle, by modifying the biogenic composition of the sea's boundary layer with the atmosphere.</p>
Modelling of Stably Stratified Atmospheric Boundary Layers with Varying Stratifications
<p>This repository contains data that was used for publishing article called <a href="https://link.springer.com/article/10.1007%2Fs10546-020-00527-8"><em>Modelling of Stably Stratified Atmospheric Boundary Layers with Varying Stratifications</em></a>. The repository compliments the publication in the sense that it provides qualitative insight for comparison and exploration.</p> <p><strong>Keywords</strong>: GABLS1, Open data, Stably-stratified turbulence, Turbulence parametrization</p> <p>The data is stored inside sixteen files. The file names are split into a part that describes variables and part that describes simulation. Here's an example of a file name:</p> <p>budgets.cr0375.csv</p> <p>The first part <em>budgets</em> refers to variables inside the file and the second part <em>cr0375</em> refers to forcing conditions (in this example cooling rate of 0.375 Kelvin per hour) used in the simulation.</p> <p><strong>Variables</strong>:</p> <ul> <li>mean wind speed and mean potential temperature (<em>first_order_stat</em>)</li> <li>variance and covariance variables that describe turbulence properties (<em>second_order_stat)</em></li> <li>variables in the turbulent kinetic energy and half the temperature variance equations <em>(budgets</em>)</li> <li>contain values for model coefficients that can be used for calculating second order statistics <em>(lambda_beta_coeffs)</em></li> </ul> <p><strong>Simulations</strong>:</p> <ul> <li>cooling rate at the surface 0.25 Kelvin per hour <em>(cr025)</em></li> <li>cooling rate at the surface 0.375 Kelvin per hour <em>(cr0375)</em></li> <li>cooling rate at the surface 0.5 Kelvin per hour (<em>cr05)</em></li> <li>cooling rate at the surface 1.0 Kelvin per hour <em>(cr1)</em></li> </ul> <p><strong>Note</strong>: The results presented in the repository are taken after the ninth hour of the simulation while the results in the published paper is averaged between the eight and ninth hour. This difference should be negligible.</p>
Developing Digital Image Processing methods to quantify internal and interfacial convection in the Hele-Shaw cell, with applications to the laboratory ice-ocean boundary layer
<p>This dataset provides the video and image files obtained from Schlieren optical experiment 3 performed in the <span>Laboratoire de Glaciologie (GLACIOL)</span> at the Universite de libre Bruxelles. A document detailing the visual data and supporting figures is presented (DataOverview.pdf). </p>
Dataset of publication "Investigation of the discharge coefficient in the laminar boundary layer regime of critical flow Venturi nozzles calibrated with different gases including hydrogen"
<p>The attached files contain experimental raw data and fluid properties for the nozzles 1 and 2 mentioned in the paper. The data in the attached files can be used to calculate the Cd values published in the paper.</p>
Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control.
<p>This project contains the data obtained as a result of the Preludium Grant no 2022/45/N/ST8/01425 of the Polish National Science Centre fundings. Within the "Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control" project, two main research tasks were defined:<br> 1. Implementation of porous FW-H analogy into the developed aeroacoustic code.<br> 2. Validation of the porous FW-H analogy implementation against analytical solutions for elementary sources.</p> <p>The resutls from these tasks are uploaded here. The details of the data are included in the EOP_medata_2.docx document uploaded. </p>
Data for: Nonlinear dynamics of the near-shore boundary layer of a large lake (Lake Geneva)
<p>We examined near-shore and pelagic current variability in Lake Geneva, a large and deep lake in western Europe, using observations from several measurement locations and a three dimensional numerical model, based on the period 2014–2016. The data include measurements from Acoustic Doppler Current Profiler (ADCP) campaigns and vertical temperature profiles along with the corresponding modelling results. The model used in this study is based on the MIT General Circulation Model (MITgcm, <a href="http://mitgcm.org/">http://mitgcm.org/</a>, <a href="https://doi.org/10.1029/96JC02775">https://doi.org/10.1029/96JC02775</a>).</p>
Unstable Ion Composition Boundary Layer Crossings
<p>A list of unstable ion composition boundary layer crossings by the MAVEN spacecraft, separated into three categories. "Snowplow" events have discrete parcels of low energy escaping heavy ion plasma interspersed with more energetic magnetosheath plasma. "Plume" events have higher energy escaping heavy ions with a beam-like distribution, interspersed with magnetosheath plasma. "Unclassified" events do not neatly fit in either of these categories. </p>
Atmospheric sounding of the boundary layer over alpine glaciers using fixed-wing UAVs
<p>Additional code and data for the paper by Groos et al. entitled "Atmospheric sounding of the boundary layer over alpine glaciers using fixed-wing UAVs"</p> <p>Correspondence: Alexander R. Groos (alexander.groos@fau.de)</p> <p><br>The repository contains:<br>(1) The raw data (log files) for each UAV-based atmospheric sounding<br>(2) The postprocessed and reformatted data for each sounding and vertical profile<br>(3) The commented R-Scripts for data processing, analysis and visualisation<br>(4) A subset of the meteorological data from the nearby weather stations</p> <p><br>Description of sub-folders:</p> <p>-aws_data<br>-- aws_fisistock.txt # meteorological data from AWS Fisistock for the period of the campaign<br>-- aws_gandegg.txt # meteorological data from AWS Gandegg for the period of the campaign<br>-- aws_sackhorn.txt # meteorological data from AWS Sackhorn for the period of the campaign</p> <p>- processed_data<br>-- kanderfirn_2021-06-16_10:45_p1_pprz.tab # meteorological data for first profile/descent at about <br>-- kanderfirn_2021-06-16_10:45_p2_fr.tab # flight recorder data for second profile/descent at about 10:45 CEST<br>-- kanderfirn_2021-06-16_10:45_p2_pprz.tab # meteorological data for second profile/descent at about 10:45 CEST<br>-- kanderfirn_2021-06-16_10:45_pprz.tab # meteorological data for the entire sounding (first and second profile/descent) at about 10:45 CEST<br>-- .<br>-- .<br>-- .<br>-- kanderfirn_2021-06-16_16:50_p1_pprz.tab # meteorological data for first profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_p2_fr.tab # flight recorder data for second profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_p2_pprz.tab # meteorological data for second profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_pprz.tab # meteorological data for the entire sounding (first and second profile/descent) at about 16:50 CEST<br>-- kanderfirn_soundings_2021-06-16.csv # summary table of vertical profiles (1 m height intervals): one column for each profile/descent and variable<br>-- kanderfirn_turbulence_2021-06-16.csv # summary table of vertical turbulence profiles (1 m height intervals): one column for each profile/descent</p> <p>- raw_data<br>-- fr_kanderfirn_2021-06-16_10:45.LOG # flight recorder data from the sounding at about 10:45 CEST (binary file)<br>-- .<br>-- .<br>-- .<br>-- fr_kanderfirn_2021-06-16_16:50.LOG # flight recorder data from the sounding at about 16:50 CEST (binary file)<br>-- pprz_kanderfirn_2021-06-16_10:45.LOG # meteorological data from the sounding at about 10:45 CEST (human readable text file)<br>-- .<br>-- .<br>-- .<br>-- pprz_kanderfirn_2021-06-16_16:50.LOG # meteorological data data from the sounding at about 16:50 CEST (human readable text file)</p> <p>- R_scripts<br>-- figures.R # Script to create Figures 5, 6, 8, 9, 10, 11, 12<br>-- lapse_rate.R # Script to calculate lapse rates and surface-based inversions (includes code for Figures 7 and B1)<br>-- postprocessing.R # Script to reformat preprocessed and preselected pprz-files<br>-- turbulence.R # Script for the calculation of the turbulence proxy from the recorded roll rate</p>
Measurement and prediction of bottom boundary layer hydrodynamics under modulated oscillatory flows
<p>Experimental and numerical model data pertaining to the manuscript "Measurement and prediction of bottom boundary layer<br> hydrodynamics under modulated oscillatory flows" accepted for publication in Coastal Engineering (<a href="https://doi.org/10.1016/j.coastaleng.2021.103954">https://doi.org/10.1016/j.coastaleng.2021.103954</a>)</p> <p>Please read the README.txt file for more information.</p>
Data and scripts for reproducing "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer"
<p>This is the accompanying data and Python scripts to reproduce the figures in "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer", submitted to Flow, Turbulence and Combustion.</p>
Dataset of "Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer"
<p>Dataset of the article "Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer" (<a href="https://doi.org/10.1016/j.applthermaleng.2023.120621">https://doi.org/10.1016/j.applthermaleng.2023.120621</a>). The dataset contains:</p> <p>- the velocity fields, measured with Particle Image Velocimetry, for the case of the boundary layer without actuation, with actuation with a steady jet, and for the best individual obtained after the optimization of the pulsed jet parameters.</p> <p>- the parameters of the individuals generated in the optimization process.</p>
Datasets used in "Verifying Operational Forecasts of Land-Sea Breeze and Boundary Layer Mixing Processes"
<p>Zip file containing datasets used in "Verifying Operational Forecasts of Land-Sea Breeze and Boundary Layer Mixing Processes". In particular, wind magnitude and direction data from automatic weather stations, the Australian Burea of Meteorology's official edited forecast, and unedited ACCESS and ECMWF model data. Data in NETCDF format. </p>
Supplementary Material: A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer
<p>Supplementary material for <em>Energies</em> <strong>2016</strong>, <em>9</em>, 366; doi:10.3390/en9050366:</p> <p><strong>Video S1:</strong> Normalized instantaneous streamwise velocity field both on a vertical plane (<em>x</em>-<em>z</em>) going through the center of the turbine and on a horizontal plane at the equator height of the turbine (Note: the physical time corresponding to this video is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p> <p><strong>Video S2:</strong> Normalized instantaneous streamwise velocity field on a horizontal plane at the equator height of the turbine for two cases: when the turbine starts to operate (top) and when the flow has reached statistically steady condition (bottom) (Note: the physical time corresponding to both videos is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p>
Data Sets: Estimating scalar turbulent fluxes with slow-response sensors in the stable atmospheric boundary layer
<p>Date of data analysis: Statistical analyses conducted throughout the 2023 year </p><p>Information about funding sources that supported the collection of the data:</p><p>The research was supported by the Cooperative Institute for Modeling the Earth System at Princeton University under Award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, and by the US National Science Foundation under award number AGS 2128345. Also, it was supported by the National Defense Science and Engineering Graduate Fellowship from the U.S. Department of Defense and Army Research Office. Similarly, the National Science Foundation provided support to complete the PHOXMELT field studies (Grant PLR- 1417914) to collect the data. Also, the study was supported by the U.S. National Science Foundation (NSF-AGS-2028633) and the Department of Energy (DE-SC0022072).</p><p>The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration.</p><p>This dataset contains the observational data for the two field experiments (Barrow and Wendell) in .nc file format.</p>
Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parameterization in WRF
<p>This repository contains namelists needed to reproduce the WRF(V4.4) simulations analyzed in "Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parameterization in WRF"</p>
Data of Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface
<p>data and code for paper 'Water Vapor Flux-Profile Relationship in the Stable Boundary Layer over the Sea Surface'</p>
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Allen Brain Atlas
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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.