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176 results for “evaporation”
Dataset of "Molecular dynamics of evaporative cooling of water clusters"
<p>The cooling of water clusters through evaporation into a vacuum is studied using classical molecular dynamics with the SPC water model, and the results are compared with semimacroscopic theory. A model based on the Hertz–Knudsen equation underestimates the cooling rates. A modified approach, which accounts for the Kelvin equation, provides better results. While the rotational temperature of the clusters is in equilibrium with their internal temperature, the translational temperature of the clusters “as individual particles” remains unchanged.</p>
Bonanza Creek LTER: Hourly Evaporation measurements at Core Sites from 1988 to Present in the Bonanza Creek Experimental Forest near Fairbanks, Alaska
This study is a survey of the vegetation of the 35 control sites in Bonanza Creek LTER. The 35 sites represent replicates each of six successional stages of primary succession on the floodplain of the Tanana River and four stages of succession uplandsas well as a few recently burned sites. Data include percent cover of all species and count based on twenty 1 m2 or 4 m2 plots. Plots in young stages of succession were remeasured every 1 to 2 years; those in older stages every 3 to 5 years. Some information on biomass in these stages is available. Although most sites were established in 1988 some sites have vegetation plots that have been sampled periodically since 1965. 2009 was the last year of sampling using visual estimates of percent cover. In 2007 a new point framing system was developed and is now used for collecting vegetation data from these sites.
Evaporation Estimates for Long Key C-MAN Weather Station, Florida Bay (FCE) from July 1998 to May 2004
This file contains data from the National Data Buoy Office Coastal-Meteorological Automated Network (C-MAN) weather station near Long Key, in Florida Bay (LONF1, 24deg 50min 36sec N, 80deg 51min 42sec W). The time period is 1600 EST February 6, 2004 through 0700 EST May 28, 2004. The record is a combination of NDBO data (wind speed, air pressure, air temperature water temperature) and Harbor Branch data (relative humidity) needed to calculate evaporative water loss. The file is one of several from this location. Together, they can be used to estimate of hourly, daily, monthly, seasonal and annual evaporation rates. Calculations include hourly water loss and cumulative water loss. Times are Eastern Standard.
Locally verified evaporation data from a NOAA evaporation pan at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1953-1979
This data package contains locally verified monthly total pan evaporation data from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. The evaporation pan measurements commenced in 1953 and ended in 1979 when the instrument was decommissioned. Pan evaporation observations were made using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from records retrieved from NOAA in ~1995 and have since undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. There is no further data from this decommissioned instrument, so this dataset is now complete and data will no longer be updated here. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal (https://www.ncdc.noaa.gov/cdo-web/datasets/GSOM/stations/GHCND:USC00294426/detail - monthly pan evaporation data are available back to 1930, but there may be data issues prior to 1953).
The effect of solvent on convectively-driven silica particle assembly: Decoupling surface tension,viscosity, and evaporation rate
<p>Dataset associated with 'The effect of solvent on convectively-driven silica particle assembly: Decoupling surface tension, viscosity, and evaporation rate’.</p> <p>The data is based on the figures below, published in the linked article (see the doi).</p> <p><strong>- Figure 1. S</strong>egmented and raw images of dip-coated films. <strong>(images, .TIF)</strong></p> <p><strong>- Figure 2. </strong>Calculated surface coverages <strong>(data, .csv)</strong></p> <p><strong>- Figure 3. </strong>Rheology on SiO<sub>2</sub>-iPrOH-Glycerol mixtures & SEM micrographs of particle films. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure 4. </strong>SEM micrographs of silica helices films. <strong>(images, .TIF)</strong></p> <p><strong>- Figure S1. </strong>Measured evaporated masses of each solvent as a function of time. <strong>(data, .csv)</strong></p> <p><strong>- Figure S2. </strong>TEM micrographs of SiO2 seeds and measured particle diameters. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure S3. </strong>TEM micrographs of SiO particles and measured particle diameters. <strong>(data, .csv; images, .TIF)</strong></p> <p><strong>- Figure S4. </strong>Calculated solvent fractions as a function of time. <strong>(data, .csv)</strong></p> <p><strong>- Figure S5.</strong> Rheology of i-PrOH-glycerol mixtures.<strong> (data, .csv)</strong></p>
Evaluation of a wind tunnel designed to investigate the response of evaporation to changes in the incoming longwave radiation at a water surface
<p>Experimental Record of a Longwave-Evaporation experiment. The record to be referenced in a forthcoming scientific paper.</p>
Predicting evaporation from mountain streams -- data set
<p>These files constitute the data sets used for the analysis, and generation of figures and tables reported in the manuscript titled "Predicting evaporation from mountain streams" by Andras J. Szeitz and R. Dan Moore. The manuscript was submitted for publication in the journal 'Hydrological Processes'.</p>
Evaporation of materials from the molten salt reactor fuel under elevated temperatures - Dataset
<p>The release of fission product and salt compounds from a molten salt reactor fuel under accident conditions was investigated with coupled computer simulations. The thermodynamic modeling of the salt and fission product mixture was performed in The Gibbs Energy Minimization Software GEMS and the obtained compound vapor pressures were exchanged with the severe accident code MELCOR, where the evaporation from a salt surface located at the bottom of a confinement building was simulated. The fuel salt considered in the simulations was LiF-ThF<sub>4</sub>-UF<sub>4</sub> with fission products Cs and I. The composition of the fuel salt material was obtained from an equilibrium fuel cycle simulation of the salt using the EQL0D routine coupled to the Serpent 2 code. The results were compared to simulations using pure compound vapor pressures in the evaporation simulations. It was observed that by modeling the salt mixing the release of fission products and salt materials was reduced when compared to the pure compound simulations. The mixing effects in the salt, when compared to the pure compound simulation also affected evaporation temperatures and therefore the timing of the release of compounds. In an additional simulation in which the depressurization of the confinement was considered, the total evaporated mass of compounds increased due to increased mass transfer at the salt surface. The simulation process described in this paper can be used for a more comprehensive accident analysis of molten salt reactors once the detailed description of the reactor confinement and accident sequences are available and more fission product elements have been added to the analysis.</p>
Data set for paper "Ramparts around lakes on Titan impact winds and methane evaporation"
<p>Data and post-processing code used for the paper "Ramparts around lakes on Titan impact winds and methane evaporation", submitted to PSJ in 2024.</p> <p>Are made available:<br> - a list of the simulations (list_simulations_ramparts2D.pdf)<br> - the simulations' netCDF outputs (run-t##.nc.gz)<br> - the input files used to run the simulations (in input_files/)<br> - the post-processing python codes used to plot the figures (in post_processing_codes/)<br> - tables of latent heat flux and horizontal wind values (Tables_LH_and_Uwind.pdf)<br> - a gif of the horizontal wind in the reference run (u_wind_run-t04_speed.gif)<br> - a gif of the vertical wind in the reference run (w_wind_run-t04_speed.gif)</p>
evapoRe
<p>This repository provides access to a collection of evapotranspiration datasets, enabling researchers, scientists, and practitioners to conveniently access and utilize these valuable resources. The repository ensures easy retrieval of evapotranspiration data by providing clear documentation and instructions for downloading the datasets. With a diverse range of evapotranspiration data available, users can explore various spatial and temporal resolutions tailored to their specific research needs. This repository aims to facilitate the integration of evapotranspiration data into diverse applications, such as hydrological modeling, climate studies, and agricultural research, fostering scientific advancements and data-driven decision-making.</p>
Global Reservoir Evaporation Dataset
<p>This dataset contains the monthly evaporation rate and volumes for 7242 reservoirs from March 1984 to December 2016 across the world. The evaporation rate was calculated using the three datasets viz. (1) TerraClimate; (2) ERA5; (3) Princeton Global Forcings. The surface area of these reservoirs is obtained from the Global reservoir surface area dataset (GRSAD). The detailed descriptions for this dataset are presented in Tian et al (2021,2022). The basic information of the global reservoirs was provided by the Global Reservoir and Dam Database (GRanD).<br> When using the data, please cite the following references:<br> Tian, W., Liu, X., Wang, K., Bai, P., Liu, C., & Liang, X. (2022). Estimation of Global Reservoir Evaporation Losses. Journal of Hydrology, 127524.<br> Tian, W., Liu, X., Wang, K., Bai, P., & Liu, C. (2021). Estimation of reservoir evaporation losses for China. Journal of Hydrology, 596, 126142.</p>
Sensitivities to temperature and evaporative demand in wheat relatives
<p>Data used in the paper "Sensitivities to temperature and evaporative demand in wheat relatives" accepted by Journal of Experimental Botany.<br> There are three tables:</p> <ul> <li>Metadata: genotype information</li> <li>Definition: Definition, symbol and unit of the variables used</li> <li>Genotype variables: set of variables used for analyses, figures and tables in the article. </li> </ul>
Dataset for the "a parameterization for cloud organization and propagation by evaporation-driven cold pools edges"
<p>When the negatively buoyant air in the cloud downdrafts reaches the surface, it spreads out horizontally, producing cold pools. A cold pool can trigger new convective cells. However, when combined with the ambient vertical wind shear, it can also connect and upscale them into large mesoscale convective systems (MCS). Given the broad spectrum of scales of the atmospheric phenomenon involving the interaction between cold pools and the MCS, a parameterization was designed here. Then, it is coupled with a classical convection parameterization to be applied in an atmospheric model with an insufficient spatial resolution to explicitly resolve convection and the sub-cloud layer. A new scalar quantity related to the deficit of moist static energy detrained by the downdrafts mass flux is proposed. This quantity is subject to grid-scale advection, mixing, and a sink term representing dissipation processes. The model is then applied to simulate moist convection development over a large portion of tropical land in the Amazon Basin in a wet and dry-to-wet 10-days period. Our results show that the cold pool edge parameterization improves the organization, longevity, propagation, and severity of simulated MCS over the Amazon and other different continental areas.</p><p> </p>
Dataset for "A computational fluid dynamics—Population balance equation approach for evaporating cough droplets transport"
<p>Dataset for figures and tables of the article "A computational fluid dynamics—Population balance equation approach for evaporating cough droplets transport" submitted to "International Journal of Multiphase Flow".</p>
Soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature data from Toolik Field Station, Toolik Lake, Alaska for 2008.
Weather data file for Arctic Tundra LTER site at Toolik Lake. Only the sensors that are measured every 10 minutes and averaged every three hours are include, i.e. soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature.
Soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature data from Toolik Field Station, Toolik Lake, Alaska for 2009.
Weather data file for Arctic Tundra LTER site at Toolik Lake. Only the sensors that are measured every 10 minutes and averaged every three hours are include, i.e. soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature.
Soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature data from Toolik Field Station, Toolik Lake, Alaska for 1991.
Weather data files for Arctic Tundra LTER site at Toolik Lake, North Slope Alaska. Only the sensors that are measured every 10 minutes and averaged every three hours are include, i.e. soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature.
Soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature data from Toolik Field Station, Toolik Lake, Alaska for 2007.
Weather data file for Arctic Tundra LTER site at Toolik Lake. Only the sensors that are measured every 10 minutes and averaged every three hours are include, i.e. soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature.
Evaporation pan data from the Jornada Basin LTER weather station, 1983-ongoing
This package contains data from an evaporation pan at the Jornada Basin LTER weather station in southern New Mexico, USA. Surface evaporation is measured weekly to twice weekly using an evaporation pan compatible with standard National Weather Service evaporation measurements. Measurements are made twice per week during hot periods because of the high evaporation rate. The following data is collected: number of days between measurements, beginning and ending measurement period, current, minimum, and maximum water temperature; initial water level; final water level; rainfall since last evaporation measurement, and calculated evaporation (inches). Data collection is ongoing.
Piston-Expansion-Tube Videos Showing Droplet Evaporation
<p>Both videos show high speed recordings of the spontaneous condensation of small droplets of homogeneous size after rapidly expanding a cylindrical volume. After the expansion and droplet creation, the heat of the walls is evaporating the droplets again. The cameras optical axis is oriented parallel to the cylinder axis. A small square area of 8.5 mm side length next to the cylindrical wall is recorded. The particles are illuminated by a laser sheet of about 0.5 mm thickness. The recording frequency is 500 Hz.</p> <p>height/depht of the cylinder: 0.021 m<br> radius of the cylinder: 0.035 m<br> gas: Nitrogen<br> condensing component: n-Propanol<br> gas temperature before expansion: 299.0 K<br> cylinder inner surface temperature: 299.0 K<br> pressure before expansion: 1.0E5 Pa<br> pressure past espansion: 0.55E5 Pa<br> partial pressure of condensing component before expansion: 628 Pa<br> droplet radius past expansion: 100E-9 m</p> <p>Video 5E12nuclei.mp4:</p> <p>droplet concentration: 5E12 1/m³ (rough estimation)</p> <p>Video 8E10nuclei.mp4:</p> <p>droplet concentration: 8E10 1/m³ (counted in one of the video frames)</p> <p>The two different droplet concentrations are achieved solely by the speed of the expansion. The higher the speed, the more nuclei will be created.</p> <p>For more information see <a href="https://doi.org/10.5281/zenodo.4449246">https://doi.org/10.5281/zenodo.4449246</a> (diploma thesis, German language).</p>
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