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202 results for “water vapor”
Water Vapor Sorption Properties of Illinois Shales under Dynamic Water Vapor Conditions: Experimentation and Modeling
<p>Data sets for the Publication 'Water Vapor Sorption Properties of Illinois Shales under Dynamic Water Vapor Conditions: Experimentation and Modeling' in Water Resources Research.</p>
Corresponding Dataset of Advanced Water Vapor Radiometer Data for Juno Gravity Science
<p><br> Corresponding Dataset of Advanced Water Vapor<br> Radiometer Data for Juno Gravity Science<br> Troposphere Calibrations<br> README FILE<br> Dustin Buccino<br> August 24, 2021<br> Jet Propulsion Laboratory<br> California Institute of Technology</p> <p>=============================================================================<br> INTRODUCTION<br> =============================================================================</p> <p> This dataset contains high rate data collected by the Advanced Water<br> Vapor Radiometer (AWVR) at the Deep Space Network's Goldstone Complex in <br> California. This dataset is provided in order to supplement the submitted<br> article to the "Radio Science" journal</p> <p> Buccino, D.R., et al (2021), Performance of Earth Troposphere <br> Calibration Measurements with the Advanced Water Vapor Radiometer <br> for the Juno Gravity Science Investigation, Radio Science, submitted<br> October 2021.</p> <p> ******************************************************************<br> * ANY USERS OF JUNO GRAVITY SCIENCE DATA ARE HIGHLY ENCOURAGED *<br> * TO INSTEAD REFER TO THE OFFICIAL ARCHIVE ON THE NASA PLANETARY *<br> * DATA SYSTEM. THIS SUPPLEMENTAL DATA SET DOES NOT CONTAIN ANY *<br> * GRAVITY SCIENCE DATA; IT ONLY CONTAINS HIGHER RATE AWVR DATA *<br> ******************************************************************</p> <p> Additional Juno Gravity Science Data may be found at the Planetary Data<br> System:</p> <p> Buccino, D. R. (2016). Juno jupiter gravity science raw data set <br> V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS). <br> Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/<br> </p> <p>=============================================================================<br> ARCHIVE INFORMATION<br> =============================================================================</p> <p> This archive contains several data types, located within subdirectories.<br> <br> ROOT<br> `- PJ03/<br> <br> This directory contains all PJ-03 related data, including<br> path delay, path delay rate, calibration values, and frequency<br> residuals.<br> <br> `- PJ06/<br> <br> This directory contains all PJ-06 related data, including<br> path delay, path delay rate, and calibration values.<br> <br> `- PJ08/<br> <br> This directory contains all PJ-08 related data, including<br> path delay, path delay rate, and calibration values.<br> <br> `- ADEV/<br> <br> This directory contains troposphere scintillation Allan deviations<br> from each perijove. Files are named using the start time of the file,<br> in YYYYMMDDHHMM format, where YYYY is the year, MM is the month,<br> DD is the day of month, HH is the hour, and MM is the minute.<br> <br> `- STATS/<br> <br> This directory contains the Juno perijove frequency residual <br> statistics. Only one file is present in this directory.</p> <p>=============================================================================<br> FILE FORMAT<br> =============================================================================</p> <p> This dataset contains two separate file formats as described below.<br> ASCII plain-text files are given with the "*.txt" extension and the<br> comma-separated text files are given with the "*.csv" extension.</p> <p><br> TXT FILES<br> -------------------------------------------------------------------------</p> <p> The ASCII plain-text files are human-readable, space-delimited<br> text files. Each column is defined by a header row which provides<br> a description of each column. Additional comments may be optionally<br> specified by starting a row with the character "#".</p> <p> CSV FILES<br> -------------------------------------------------------------------------</p> <p> The Comma-Separated Value (CSV) files are plain-text files. Values in<br> each data file are separated using a comma ",". Each column is defined <br> by a header row which provides a description of each column.</p> <p><br> =============================================================================<br> FIGURE REPRODUCTION<br> =============================================================================</p> <p> This section will describe the data that are used to produce the figures<br> in the article that describes this dataset.</p> <p> FIGURE 1<br> -------------------------------------------------------------------------</p> <p> Figure 1 is a photograph and is not included in this dataset.</p> <p> FIGURE 2<br> -------------------------------------------------------------------------</p> <p> Figure 2 is produced using files within the "PJ03", "PJ06", and "PJ08"<br> directories.<br> <br> The first row of subfigures are produced by plotting the final three <br> columns of "pjXX_bt_zenith.txt" as a function of time.<br> <br> The second row of subfigures are produced by plotting the path delay<br> componets as a function of time from the "pjXX_pd_awvr.txt" and <br> "pjXX_pd_tsac.txt" data files.</p> <p><br> FIGURE 3<br> -------------------------------------------------------------------------</p> <p> Figure 3 is produced using files within the "PJ03", "PJ06", and "PJ08"<br> directories.<br> <br> The first row of subfigures are produced by plotting the last column<br> of "pjXX_freq_awvr.txt" and "pjXX_freq_tsac.txt".<br> <br> The second row of subfigures are produced by differencing the values.<br> <br> FIGURE 4<br> -------------------------------------------------------------------------</p> <p> Figure 4 is produced using files within the "ADEV" directory.<br> <br> Each individual file within the "ADEV" directory contains the Allan <br> deviation. Each Allan deviation is plotted on a log-log scale and is<br> color-mapped to the calendar date. The file naming convention gives<br> the calendar date of data collection, with the filenames starting with<br> YYYYMMDD, where YYYY is 4-digit year, MM is 2-digit month, and DD is<br> 2-digit day of month in UTC time.</p> <p> FIGURE 5<br> -------------------------------------------------------------------------</p> <p> Figure 5 is produced using files within the "PJ03" directory. The<br> frequency residual from the "pj03_resid_awvr.csv" and<br> "pj03_resid_tsac.csv" is simply plotted as a function of time.<br> <br> FIGURE 6<br> -------------------------------------------------------------------------</p> <p> Figure 6 is produced using files within the "STATS" directory. This <br> directory contains a single file, "AWVR_stats_jul2021_v3.csv" and<br> contains the root-mean-square of the frequency residuals from Juno <br> perijove passes. The root-mean-square of the frequency residuals<br> are plotted using a bar plot and the percent improvement is plotted <br> with a scatterplot.<br> </p> <p>=============================================================================<br> ACKNOWLEDGMENTS<br> =============================================================================</p> <p>This work was carried out at the Jet Propulsion Laboratory, <br> California Institute of Technology, under contract with the National <br> Aeronautics and Space Administration. Government sponsorship acknowledged.</p> <p>=============================================================================<br> PRIMARY POINT OF CONTACT<br> =============================================================================</p> <p>Dustin Buccino<br> Jet Propulsion Laboratory<br> Planetary Radar and Radio Sciences<br> (818) 393 - 1072<br> Dustin.R.Buccino@jpl.nasa.gov</p> <p>=============================================================================<br> ACRONYMS AND ABBREVIATIONS<br> =============================================================================</p> <p> ASCII American Standard Code for Information Interchange<br> DOY Day of year<br> DSN Deep Space Network<br> JPL Jet Propulsion Laboratory<br> NAIF Navigation Ancillary Information Facility<br> NASA National Aeronautics and Space Administration<br> PDS Planetary Data System<br> RS Radio Science<br> RSS Radio Science Subsystem<br> SIS Software Interface Specification<br> TXT Text file<br> UTC Universal Time, Coordinated<br> </p>
Data and code for the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration
<p>Data and code for the manuscript <em>Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration</em> accepted for publication to<em> </em> <em>Earth and Space Science</em> in October 2021.</p> <p>The dataset contains 7 month of total losses (transmitted - received power levels) and retrieved water vapor density from a 4.87 km long full-duplex E-band commercial microwave link (CML) operating at 73.5 and 83.5 GHz in Prague, CZ. The CML was operated as a part of a mobile phone backhaul. Furthermore, observations of air temperature, and air relative humidity from sites close to the CML end nodes are provided. Finally, theoretical gaseous attenuation calculated from the air temperature and relative humidity is included as a part of the dataset.</p> <p>Data are stored in semicolon-delimited csv files. Time stamps are in UTC time in the format yyyy-mm-dd HH:MM:SS. All time series are regular and have 5-min temporal resolution. Metadata are stored in text files.</p> <p>The code is in a form of R Markdown files and html notebooks. Results presented in the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration and in its Supporting information are fully reproducible using this dataset.</p>
Retrieving accurate precipitable water vapor based on GNSS multi-antenna PPP with an ocean-based dynamic experiment
<p>GNSS-derived PWVs during a 4-day shipborne experiment are included in this repository. There are four solutions with four different processing strategies, namely PPP without constraints (Conventional), with baseline length constraint only (Bl), with common ZTD constraint only (Com), and with both baseline length and common ZTD constraints (Bl+Com). The suffix 'Smooth' in the file names represents the PWV results after backward smoothing.</p>
ENSO influence on water vapor transport and thermodynamics over Northwestern South America
<p>Datasets used, generated and analysed during the study "ENSO influence on water vapor transport and thermodynamics over Northwestern South America"</p>
Aerosol, Temperature and Water Vapor profiling during the BIOSPHERE Athens Campaign (June-August 2023) - NTUA
<p>Level 2 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE (June - August 2023). </p>
Long-term climate impacts of large stratospheric water vapor perturbations: Postprocessed WACCM data (Part 3)
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Long-term climate impacts of large stratospheric water vapor perturbations: Postprocessed MiMA data (Part 2)
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Eddy flux measurements and transfer velocities of momentum, sensible heat, water vapor, and sulfur dioxide at Scripps Pier
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Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"
<p>Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"<br> </p>
Hunga Tonga-Hunga Ha'apai stratospheric water vapor from Vaisala RS41 radiosondes
The Hunga Tonga-Hunga Ha'apai volcanic eruption on 15 January 2022 injected unprecedented amounts of water vapor into the stratosphere (Vömel et al., 2022). This data set contains observations using Vaisala RS41 radiosondes obtained in the weeks following the eruption, which were launched as part of the operational upper air network and distributed through the WMO Global Telecommunication System (GTS). It also includes one research sounding using the Cryogenic Frostpoint Hygrometer launched at the Maïdo Observatory at Reunion one week after the eruption. Vömel H., S. Evan, and M. Tully (2022): Water vapor injection into the stratosphere by Hunga Tonga-Hunga Ha'apai, Science, 377, 1444-1447, doi: 10.1126/science.abq2299.
Is the isotopic composition of precipitation a robust indicator for reconstructions of past tropical cyclones frequency? A case study on Réunion Island from rain and water vapor isotopic observations
<p>Isotopic composition of precipitation and water vapor and LMDZ-iso and ECHAM6-wiso simulations associated with the manuscript:</p> <p>Françoise Vimeux, Camille Risi, Christelle Barthe, Sören François, Alexandre Cauquoin, Olivier Jossoud, Jean-Marc Metzger, Olivier Cattani, Bénédicte Minster, and Martin Werner (2024). Is the isotopic composition of precipitation a robust indicator for reconstructions of past tropical cyclones frequency? A case study on Réunion Island from rain and water vapor isotopic observations. Journal of Geophysical Research: Atmospheres, 129, e2023JD039794. https://doi.org/10.1029/2023JD039794</p>
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
<p>Code to reproduce the work in the manuscript ' A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest', Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, Feijuan Li, submitted to GMD.</p>
Atmospheric water vapor stable isotopes at Lulang, southeastern Tibetan Plateau
<p>These data had been published in the following paper. If you use them, please cite this paper.</p> <p>M. Chen, J. Gao, L. Luo, A. Zhao, X. Niu, W. Yu, Y. Liu, G. Chen, Temporal variations of stable isotopic compositions in atmospheric water vapor on the Southeastern Tibetan Plateau and their controlling factors, Atmospheric Research, 2024, 107328, https://doi.org/10.1016/j.atmosres.2024.107328.</p>
Dataset for the manuscript of the "Permeability evolution of methane and water vapor when simultaneously transporting in shale"
<p>Dataset for the manuscript of the "Permeability evolution of methane and water vapor when simultaneously transporting in shale"</p>
IsoRSM simulation data for the Simulation of water isotopes in combustion-derived vapor emissions in winter
<p>The two files are the IsoRSM simulation results of the temperature, humidity and water vapor isotopes in Salt Lake City (January, 2017) and Beijing (January, 2007) with different emission rates of combustion-derived vapor. The data is used in the paper "Simulation of water isotopes in combustion-derived vapor emissions in winter".</p>
Compensating atmospheric adjustments reduce the volcanic forcing from Hunga stratospheric water vapor enhancement
<p>The uploaded scripts and data generate the figures of the manuscript "Compensating atmospheric adjustments reduce the volcanic forcing from Hunga stratospheric water enhancement."</p>
Silica solubility and molecular speciation in water vapor at 400-800°C
<p>This dataset is accompanying with the manuscript "Silica solubility and molecular speciation in water vapor at 400-800°C". It contains analytical data on quartz solubility experiments and the data were used in the study tthemodynamics of silica in hydrothermal water vapor.</p>
WATER VAPOR UPTAKE AND MICROWAVE HEATING OF MAGNETITE / ALUMINUM FUMARATE COMPOSITES
<p>Dataset contains original raw data used for analysis presented in the paper " WATER VAPOR UPTAKE AND MICROWAVE HEATING OF MAGNETITE / ALUMINUM FUMARATE COMPOSITES" submitted for publication. Additional data files are available from the corresponding author upon reasonable request.</p>
Data used in the manuscript "Pioneering evidence of the dynamics of water vapor and CO2 fluxes in Sahara Desert soils"
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