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176 results for “evaporation”
Global lake evaporation volume (GLEV) dataset
<p>--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>For an interactive interface of the dataset (Google Earth Engine App), please see <a href="https://zeternity.users.earthengine.app/view/glev">https://zeternity.users.earthengine.app/view/glev</a></strong></p> <p>--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>There are three csv files in this dataset. Each file has 409 columns and 1427687 rows.</p> <p><strong>1. 0_evaporation_rate.csv</strong><br> The first column is Hylak_id from <a href="https://www.hydrosheds.org/page/hydrolakes">HydroLAKES v1.0 dataset</a>.<br> The rest 408 columns contain monthly evaporation rate (mm per day) from Jan 1985 to Dec 2018.<br> <strong>2. 1_openwater_area.csv</strong><br> The first column is Hylak_id.<br> The rest 408 columns contain monthly open water area (square meters) from Jan 1985 to Dec 2018.<br> <strong>Note </strong>that this is not the surface area of lake as shown in the above GEE App.<br> It is the open water area by removing the lake ice coverage.<br> The surface area dataset is available <a href="https://drive.google.com/file/d/1ltWmB_Gj8jcFeDU3mpdGJXOx3uyVYcqN/view?usp=sharing">here</a>.<br> <strong>3. 2_evaporation_volume.csv</strong><br> The first column is Hylak_id.<br> The rest 408 columns contain monthly evaporation volume (thousand cubic meter per month) from Jan 1985 to Dec 2018.</p> <p>--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>To use this dataset, citation of the following paper is recommended:</strong><br> Zhao, G., Li, Y., Zhou, L., Gao, H. (2022) Evaporative water loss of 1.42 million global lakes. <em>Nature Communications</em>. <a href="https://doi.org/10.1038/s41467-022-31125-6">https://doi.org/10.1038/s41467-022-31125-6</a></p> <p>The detailed algorithms associated with the development of GLEV can be found in:<br> Zhao, G., and H. Gao (2019), Estimating reservoir evaporation losses for the United States: Fusing remote sensing and modeling approaches, <em>Remote Sensing of Environment</em>, 226, 109-124. <a href="https://doi.org/10.1016/j.rse.2019.03.015">https://doi.org/10.1016/j.rse.2019.03.015</a><br> Zhao, G., and H. Gao (2018), Automatic correction of contaminated images for assessment of reservoir surface area dynamics. <em>Geophysical Research Letters</em>, 45, 6092-6099. <a href="https://doi.org/10.1029/2018GL078343">https://doi.org/10.1029/2018GL078343</a></p>
Chromium evaporation and weight gain measurements
<p>Data set of experimental data on chromium release and weight gain during high temperature oxidation of AISI 441 stainless steel.</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>
Incorporating plant access to groundwater in existing global, satellite-based evaporation estimates
<p>This repository contains data used in the paper "Incorporating plant access to groundwater in existing global, satellite-based evaporation estimates".</p> <p>This repository includes the following netcdf files: 1) daily evaporation based on GLEAM-Hydro [mm/d], 2) daily evaporation based on GLEAM v3 [mm/d], 3) annual-mean groundwater-sourced evaporation (E_GW) [mm/year], and 4) temporally averaged groundwater contribution fraction (f_GW) [-].</p>
Terrestrial Lidar Point Cloud Data for: Evaporation and condensation dynamics within saturated epiphyte communities in a Quercus virginiana forest
<p><span>Terrestrial lidar scans were captured using a BLK360 scanner (Leica Geosystems, Norcross, GA, USA) which has a range of 0.5 – 45 m and measurement rate up to 680,000 points s<sup>−1</sup> at the high-resolution setting. A georeferenced, 3-D point cloud of the study site was generated from 12 scans, approximately 50 m apart in both horizontal directions. Scans were performed in orientations intended to maximize branch exposure to the scanner and to scan during optimal weather conditions to minimize occlusion of features due to noise or movement generated by wind. Scan co-registration was done in Leica Geosystem’s Cyclone Register 360 software using its Visual Simultaneous Localization and Mapping algorithm (Visual SLAM) and resulted in relatively low overall co-registration error ranging from 0.005-0.009 m. From this study site point cloud, manual straight-line measurements from the ground to the sensors were made using Leica’s Cyclone Register 360 software.</span></p>
Data for: Changes in evapotranspiration, transpiration and evaporation across natural and managed landscapes in the Amazon, Cerrado and Pantanal biomes
<p>This dataset contains measurements of evapotranspiration and other meteorological variables (net radiation, air temperature, vapor pressure deficit, etc) from nine eddy covariance towers located in different ecosystems in the Amazon (natural Amazon forest, cropland and pastureland), Cerrado (natural savannah, irrigated and rainfed croplands) and Pantanal (natural forest, pastureland) biomes. It also contains estimates of transpiration that were calculated using two different approaches, the transpiration estimation algorithm (TEA) and the underlying water use efficiency method (uWUE).</p>
LES_data_With_and_Without_Evaporation
<p>LES simulation dataset for the cases:</p> <ol> <li>Oscillating wind stress with heat flux and evaporation included.</li> <li>Oscillating wind stress with heat flux without evaporation.</li> </ol>
Data set for figure 2-4 from publication "Missed Evaporation from Atmospherically Relevant Inorganic Mixtures Confounds Experimental Aerosol Studies",
<p>Data set for figure 2-4 from publication "Missed Evaporation from Atmospherically Relevant Inorganic Mixtures Confounds Experimental Aerosol Studies".</p>
CWFETB-China: Gridded dataset of consumptive water footprints, evaporation, transpiration, and associate benchmarks of crop production in China (2000-2018)
<p>The CWFETB-China is a 5-arcmin gridded dataset of monthly green and blue water footprint of crop production (WFCP), evaporation (E), transpiration (Tr), and associated unit WFCP benchmarks for 21 crops grown in China during 2000-2018. As compared to the existing gridded WFCP datasets, the CWFETB-China has four improvements: (i) It evaluated the effects of different water supply modes (irrigated or rain-fed) and irrigation practices (furrow, sprinkler, and micro-irrigation) on water consumption throughout the crop growth period. (ii) It distinguished between monthly blue and green water consumption via soil evaporation and crop transpiration. (iii) The dataset encompassed both the WFCP in m<sup>3 </sup>yr<sup>-1</sup> and the uWFCP in m<sup>3 </sup>ton<sup>-1</sup>. (iv) It identified uWFCP benchmarks that differentiated between various climatic zones and irrigation practices. The dataset is able to support for precise crop water productivity assessments, agricultural water-saving evaluations, the development of sustainable irrigation techniques, cropping structure optimisation, and crop-related interregional virtual water trade analysis.</p> <p> </p> <p>Format: NetCDF-4 (5 arcmin) or .xlsx files (benchmark data).</p> <p>Projected coordinate system: WGS 84</p>
STEAM evaporation and precipitation for potential vegetation and current land use scenarios
<p>This dataset contains global evaporation and precipitation data generated and described in the following research article:</p> <p><strong>Wang-Erlandsson, L., Fetzer, I., Keys, P. W., van der Ent, R. J., Savenije, H. H. G., and Gordon, L. J.: Remote land use impacts on river flows through atmospheric teleconnections, Hydrol. Earth Syst. Sci., 22, 4311–4328, https://doi.org/10.5194/hess-22-4311-2018, 2018.</strong></p> <p>The dataset includes evaporation and precipitation for a potential vegetation (pv) and a current land use scenario (cur) and comes in monthly resolution and a spatial grid of 1.5° over the period 2000 - 2013. The files are saved in MAT file format.</p> <p>In addition, it includes the data in NetCDF files regridded using cdo (remapnn) to 0.5° spatial resolution.</p>
Evaporative cooling driven by a Venturi tube revisited; Assessing the performance of different refrigerant-circulating pairs Data Sheet
<p>File data collected for article "Evaporative cooling driven by a Venturi tube revisited; Assessing the performance of different refrigerant-circulating pairs " in Origin format. Includes temperature measurements and graphs exposed in the article.</p>
Thermal evaporation as sample preparation for silver‐assisted laser desorption/ionization mass spectrometry imaging of cholesterol in amyloid tissues
<p><strong>Thermal evaporation as sample preparation </strong><strong>for </strong><strong>silver‐assisted laser desorption/ionization mass spectrometry imaging of cholesterol in amyloid tissues</strong></p> <p>MSI datasets in SCiLS Lab SL File (*.sl) or as flexImaging sequence (*.mis)</p>
Data from: Evaporation induced acoustic emissions in microfluidic vessels
<p>Fluid flow processes such as drainage and evaporation in porous media are crucial in geological and biological systems. The motion of the displacement front of a moving fluid through multi-phase interfaces is often associated with abrupt mechanical energy release, detectable as acoustic emissions. The exact origin of these pulses and their damping mechanisms are still subjects of debate. Here, we study the characteristics of such acoustic emissions during evaporation of water from artificial microfluidic vessels, inspired by the physiology of vascular water-transport in plants. From the extracted settling times of the recorded acoustic emissions, we identify three pulse types and attribute their origins to bubble formation, snap-off events and rapid pore invasion. We also show that the resonance frequencies between 10 and 70 kHz present in specific pulse types decrease with increasing vessel radius (ranging from 0.25 to 1.0 mm) and length (ranging from 2.5 to 10.0 mm). Our findings provide insight into evaporation-induced acoustic emissions from microfluidic systems, both natural and artificial, and their potential use in non-invasive inspection or vascular health monitoring.</p>
ET-WB: water balance-based estimations of terrestrial evaporation over global land and major global basins
<p>This is the readme file for the ET-WB dataset described in the ESSD paper "ET-WB: water balance-based estimations of terrestrial evaporation over global land and major global basins" from Xiong et al. (2023)<br> ET-WB dataset-The monthly water balance data from May 2002-December 2021 for the 168 river basins and global land from 23 precipitation, 29 runoff, and 7 terrestrial water storage changes datasets.<br> The five dimensions (236*169*23*7*29) of the matrix represent the time, regions, precipitation, terrestrial water storage changes, and runoff datasets used respectively.<br> ET-WB is distributed in three kind of formats: Mat (ET-WB.mat), NetCDF (ET_WB.nc), and Shapefile (ET_WB.shp) (only for the ensemble median value). All the formats share the same definitions of dimensions (as below), except for the ArcGIS shapefile that is provided for individual regions (168 river basins and global land excluding Antarctic and Greenland).<br> File shapefile.rar is the geospatial database of the study area that can be opened in ArcGIS software. </p> <p>Please find more details in the Readme file.</p>
Hydration and evaporative water loss of lizards change in response to temperature and humidity acclimation
<p>Data and code associated with the 2023 publication in the Journal of Experimental Biology (doi:10.1242/jeb.246459).</p>
Data from: Evaporation induced acoustic emissions in microfluidic vessels
Open the record for dataset details and reuse information.
Soil temperatures, lake temperature, lake depth, and evaporation pan depth and pan water temperature data from Toolik Field Station, Toolik Lake, Alaska for 2000.
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 1993.
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.
Photomicrographs of bedded halite and gypsum sand from the Bonneville Salt Flats and an evaporation pond
<p>Photomosaic images of thin sections and photomicrographs of evaporite features from the Bonneville Salt Flats. </p>
Evaporation and permeameter data hydraulic properties stony soil
<p>We used the evaporation method to determine the hydraulic conductivity and the retention curve of a soil sample. The principle of this method is to simultaneously measure the matric head at different depths and the water content of an initially saturated soil sample submitted to evaporation.</p> <p>The experiments were performed over cylindrical Plexiglas samples of 1 L (height: 65 mm), perforated at the bottom to allow saturation from below and open to atmosphere on the upper side to allow evaporation of the soil moisture. Four 6 mm-long ceramic tensiometers (SDEC230) were introduced at 10, 25, 40 and 55 mm in height, respectively denoted T1 to T4 (the reference level is located at the bottom of the sample). In order to avoid preferential flow due to the introduction of the tensiometers on a same vertical line, each hole of the sample was horizontally shifted of 12 degrees vis-à-vis the center of the tube. The tensiometers are connected through a tube to a pressure transducer (DPT-100, DELTRAN). The setup was filled with degased water. The variation in pressure of the drying soil was recorded every 15 min by a CR800 (CAMPBELL SCIENTIFIC). Tensions beyond the consolidation point were not taken into account. The consolidation point refers to the state from which the measured pressure head starts to decrease as bubbles appear and water vapour accumulates (typically 68 kPa cm in this case).</p> <p>The total water loss as a function of time was monitored by a balance (OHAUS) with a sensitivity of 0.2 g with an accuracy of 1 g with a time resolution of 15 min. A 50 W infrared lamp was positioned 1 m above the sample surface to slightly speed up the evaporation process. The light was turned off for the first 24 hours of every experiment, as the evaporation rate is already high in a saturated sample. A measuring campaign lasted until 3 of the 4 tensiometers ran dry (the tension sharply drops down to approximately a null value). At the end of the experiment, the sample was oven dried for 24 hours at 105°C to estimate the .</p>
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