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59 results for “FLEXPART”
FLEXPART 10.4 output for "Occurrence and backtracking of microplastic mass loads including tire wear particles in Northern Atlantic air"
<p>The dataset consists of three (3) files:</p> <p>-- track3h.txt shows the position of the research vessel in each of the seven (7) ship tracks/campaigns in 3-hour resolution in ascii format structured in columns as follows:</p> <p>YEAR, MONTH, DAY, HOUR, MINUTE, SECOND, LONGITUDE, LATITUDE, SHIP TRACK NUMBER</p> <p>-- FLEXPART_720x360_fine.tar.gz shows the footprint emission sensitivities for fine particles (as described in the paper) in a gridded netCDF format of 0.5 degrees resolution for 80 release points matching the coordinates and times in the track3h.txt file.</p> <p>-- FLEXPART_720x360_coarse.tar.gz shows the footprint emission sensitivities for coarse particles (as described in the paper) in a gridded netCDF format of 0.5 degrees resolution for 80 release points matching the coordinates and times in the track3h.txt file.</p>
FLEXPART–ERA-Interim simulations with 3 million parcels globally (1979–2019)
<p><strong>Description</strong><br> This data set contains FLEXPART simulations driven with the reanalysis ERA-Interim from 1 February 1979 to 30 August 2019. The simulations cover the entire globe (90°S to 90°N and 180°E to 179°W) with 3 million homogeneously distributed air parcels representing the entire mass in the atmosphere. </p> <p><strong>Software</strong><br> The following software versions were used: </p> <ul> <li><strong>flex_extract v.7.1.2-dev</strong> (<a href="https://www.flexpart.eu/browser/flex_extract.git/?rev=3ca4c3ef0fa2a11ccf5a1c69e336b0893e2cb6a3">this version</a>); see Tipka et al. (2020) for details. </li> <li><strong>FLEXPART v10.4</strong> (<a href="https://www.flexpart.eu/browser/flexpart.git/?rev=3d7eebf7c4909f59db5ec32c524f88fb846e9fe5">this version</a>); see Pisso et al. (2019) for details. </li> </ul> <p><strong>Forcing data</strong><br> FLEXPART was driven with global reanalysis from ERA-Interim (Dee et al., 2011). The ERA-Interim reanalysis was downloaded and pre-processed using flex_extract v.7.1.2 (Tipka et al., 2020) using 6-hourly reanalyses at 00, 06, 12, and 18 UTC supplemented with 3- and 9-hourly forecasts (03 UTC and 09 UTC are taken from the forecasts initialised at 00UTC; and 15 UTC and 21 UTC are taken from the forecasts at 12 UTC). The settings are detailed in <em>CONTROL_EI_1deg.global</em>. The output of flex_extract were <em>EIgYYYYMMDDHH </em>files for each time step from 1 February 1979 to 30 August 2019 on a global 1° grid and contain the following variables: u, v, etadot, t, q, qc, sp, sshf, ewss, nsss, ssr, lsp, cp, sd, msl, tcc, 10u, 10v, 2t, 2d, z, lsm, sdor, cvl, cvh, sr; where the first 6 variables are available on 60 model layers. <br> <br> <strong>Simulations</strong><br> Simulations with FLEXPART v10.4 were performed in forward mode and subdivided into annual chunks; i.e. simulations for each year were started on December 1st 00 UTC of the previous year and run through to January 5th 18 UTC of the following year in order to run all years in parallel. For example, simulations for the year 2000 were started on December 1st 1999 at 00 UTC and run through to January 5th 2001 18 UTC. The overlap in December guarantees a coherent evaluation of each year with trajectories expanding up to 30 days into the past. <br> <br> Table 1 shows the main settings of the FLEXPART simulations as set in options/COMMAND and options/RELEASES.</p> <table align="left"> <caption><strong>Table 1: Main simulation settings</strong> (set in options/COMMAND; flags not listed here are set to 'off' [0] and in options/RELEASES; note that dates have been omitted for comprehension).</caption> <thead> <tr> <th scope="col">options/COMMAND</th> </tr> </thead> <tbody> <tr> <th scope="row">LDIRECT</th> <td>1</td> <td> <p>Simulation direction in time; 1 (forward)</p> </td> </tr> <tr> <th scope="row"> <p>LOUTSTEP</p> </th> <td>10800</td> <td> <p> Interval of model output (s)</p> </td> </tr> <tr> <th scope="row"> <p>LOUTSAMPLE</p> </th> <td>900</td> <td> <p>Interval of output sampling (s), higher stat. accuracy with shorter intervals</p> </td> </tr> <tr> <th scope="row"> <p>LSYNCTIME</p> </th> <td>900</td> <td> <p> All processes are synchronized to this time interval (s)</p> </td> </tr> <tr> <th scope="row">CTL</th> <td>2</td> <td> <p>CTL>1, ABL time step = (Lagrangian timescale (TL))/CTL, uses LSYNCTIME if CTL<0</p> </td> </tr> <tr> <th scope="row"> <p>IFINE</p> </th> <td>4</td> <td> <p>Reduction for time step in vertical transport, used only if CTL>1</p> </td> </tr> <tr> <th scope="row">IOUT</th> <td>1</td> <td> <p>Output type: [1]mass 2]pptv 3]1&2 4]plume 5]1&4, +8 for NetCDF output</p> </td> </tr> <tr> <th scope="row"> <p>IPOUT</p> </th> <td>1</td> <td> <p>Particle position output: 0] no 1] every output 2] only at end 3] time averaged</p> </td> </tr> <tr> <th scope="row"> <p>LSUBGRID</p> </th> <td>1</td> <td> <p>Increase of ABL heights due to sub-grid scale orographic variations; 1] on</p> </td> </tr> <tr> <th scope="row"> <p>LCONVECTION</p> </th> <td>1</td> <td> <p>Switch for convection parameterization; 1] on</p> </td> </tr> <tr> <th scope="row"> <p>MDOMAINFILL</p> </th> <td>1</td> <td> <p>Switch for domain-filling, if limited-area particles generated at boundary</p> </td> </tr> <tr> <th scope="row">options/RELEASES</th> </tr> <tr> <th scope="row"> <p>NSPEC</p> </th> <td>1</td> <td> <p>Total number of species</p> </td> </tr> <tr> <th scope="row"> <p>SPECNUM_REL</p> </th> <td>1</td> <td> <p>Species numbers in directory SPECIES</p> </td> </tr> <tr> <th scope="row"> <p>LON1</p> </th> <td>-179.00</td> <td> <p>Left longitude of release box -180 < LON1 <180</p> </td> </tr> <tr> <th scope="row"> <p>LON2</p> </th> <td>180.00</td> <td> <p>Right longitude of release box, same as LON1</p> </td> </tr> <tr> <th scope="row">LAT1</th> <td>-90.00</td> <td> <p>Lower latitude of release box, -90 < LAT1 < 90</p> </td> </tr> <tr> <th scope="row">LAT2</th> <td>90.00</td> <td> <p>Upper latitude of release box same format as LAT1</p> </td> </tr> <tr> <th scope="row">Z1</th> <td>0.00</td> <td> <p>Lower height of release box meters/hPa above reference level</p> </td> </tr> <tr> <th scope="row">Z2</th> <td>10000.00</td> <td> <p>Upper height of release box meters/hPa above reference level</p> </td> </tr> <tr> <th scope="row">ZKIND</th> <td>1</td> <td> <p>Reference level 1=above ground, 2=above sea level, 3 for pressure in hPa</p> </td> </tr> <tr> <th scope="row"> <p>PARTS</p> </th> <td> <p>3000000</p> </td> <td> <p>Total number of particles to be released</p> </td> </tr> <tr> <th scope="row">COMMENT</th> <td> <p>"globalRELEASE"</p> </td> <td> <p>Comment, written in the outputfile </p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Stored outputs</strong><br> Parcel positions and characteristics were stored at each 3-hourly time step in binary files names as <em>partposit_YYYYMMDDHH0000. </em>These files contain the following variables for each of the 3 million parcels:</p> <ul> <li>parcel id (a unique parcel identity number)</li> <li>longitude</li> <li>latitude</li> <li>height</li> <li>time step</li> <li>orography</li> <li>potential vorticity</li> <li>specific humidity</li> <li>density</li> <li>height of the surrounding boundary layer</li> <li>height of the surrounding troposphere</li> <li>temperature</li> <li>mass.</li> </ul> <p>One <em>partposit_YYYYMMDDHH0000 </em>file is 172 MB. All files for a month are compressed in monthly archives (as <em>fp-eraint-global_v104_rYYYY_partposit_YYYYMM.tar.gz</em>)<em> </em>and sum up to 393 GB for each annual simulation. The output of the entire simulation spanning 1979–2019 sums up to 17 TB. <br> <br> <strong>Metadata </strong><br> The metadata of each annual simulation is stored in a compressed<em><strong> </strong>fp-eraint-global_v104_rYYYY_meta.tar.gz<strong> </strong></em>archive. Metadata archives contain all namelists (all files from the <em>options</em> folder), invariant simulation outputs (such as <em>header</em>), and job outputs. For easy reference, the atmospheric mass at the time of initialisation is stored in a separate text file <em>atm_mass.txt</em>). The average atmospheric mass is 5.09205935e18 kg; each parcel thus represents approximately 1.697353e12 kg of air. <br> <br> <strong>Post-processing</strong><br> The simulations were setup and their outputs were stored in a way so that post-processing with the Heat- And MoiSture Tracking framEwoRk (HAMSTER, Keune et al., 2022) is possible without further changes. HAMSTER constructs multi-day backward trajectories for a region of interest and facilitates the identification of, e.g., precipitation origins. <br> <br> <strong>Contact and data access</strong><br> Only metadata is uploaded to this repository due to space constraints; access to the full data set can be obtained by contacting the corresponding author Jessica Keune via jessica.keune[at]ugent.be. <br> <br> <strong>References</strong><br> Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, et al. (2011). The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. <em>Quarterly Journal of the Royal Meteorological Society</em>, <em>137</em>(656), 553-597.<br> Keune, J., Schumacher, D. L., & Miralles, D. G. (2022). A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models. <em>Geoscientific Model Development</em>, <em>15</em>(5), 1875-1898.<br> Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., et al. (2019). The Lagrangian particle dispersion model FLEXPART version 10.4. <em>Geoscientific Model Development</em>, <em>12</em>(12), 4955-4997.<br> Tipka, A., Haimberger, L., & Seibert, P. (2020). Flex_extract v7. 1.2–a software package to retrieve and prepare ECMWF data for use in FLEXPART. <em>Geoscientific Model Development</em>, <em>13</em>(11), 5277-5310.</p>
Global FLEXPART-ERA5 simulations using 30 million atmospheric parcels since 1980
<h2><strong>Abstract</strong></h2> <p>This database compiles the outputs of the global experiment performed with the Lagrangian particle dispersion model FLEXPART since 1980. The experiment was conducted using the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) and homogeneously dividing the atmosphere into 30 million particles. The database can be used to investigate global moisture and heat transport and to establish sink-source relationships.</p> <h2><strong>Input data</strong></h2> <p>The data employed for FLEXPART running was the ERA5 reanalysis dataset from the ECMWF (Hersbach et al., 2020). To feed the model, the input data was downloaded and pre-processed by using the software Flex_extract v7.1 (Tipka et al., 2020).</p> <p>The original available ERA5 resolution is 0.1-degree and 1-hour. For this experiment, ERA5 input data was retrieved for the global area (90ᵒS to 90ᵒN and 180ᵒW to 180ᵒE) at a 0.5-degree horizontal resolution for 137 level from the surface to 1 hPa and a 3-hour temporal resolution (00, 03, 06, 09, 12, 15,18 and 21 UTC).</p> <p>The data is stored in individual GRIB files for each time step, following the name criteria "EAYYMMDDHH". The size of each file is approximately 530 MB. The variables included in each file are: temperature, specific humidity, u- and v-wind components, Eta-coordinate vertical velocity, divergence, specific cloud liquid water content, specific cloud ice water content, and the logarithm of surface pressure on model levels; and 2m temperature an dew-point temperature, 10m u and v wind component, geopotential, land-sea mask, mean sea level pressure, snow depth, the standard deviation of orography, surface pressure, total cloud cover, convective precipitation, large-scale precipitation, surface sensitive heat flux, eastward and northward turbulent surface stress and surface net solar radiation at the surface level.</p> <h2><strong>Software and running</strong></h2> <p>The software used for the simulations is the Lagrangrian particle dispersion model FLEXPART on version 10.4 (Pisso et al., 2019). The software is configured for a global experiment, and the simulations were obtained from 1980 to the present with a temporal resolution of 3-h. For the experiment, 30 million particles were homogeneously distributed on the global area, and their trajectories were followed according to the model configuration specified in the COMMAND and RELEASES files. The complete period is distributed in individual annual experiments, with each annual experiment obtained continuously running the model from October of the previous year to December of that year.</p> <h2><strong>Outputs characteristics</strong></h2> <p>The outputs were stored in individual GRIB files for each time step, with the file name following the naming convention "partposit_YYYYMMDDHH". Each file has a size of 1,76 GB, and the total size of the annual experiment is 6 TB. Each file contains information about each particle of the experiment: the particle identification number (particle ID), the particle's position (latitude, longitude, and altitude), topographic height, potential vorticity, specific humidity, air density, atmospheric boundary layer height, and temperature. The file corresponding to the 1st January 2023 at 00UTC is provided in this repository as an example. Due to the size of each file, the complete dataset is accessible by personal contact (see <em>Data Access</em> section). </p> <h2><strong>Post-process and applications</strong></h2> <p>The dataset presented here allows for the analysis of moisture and heat transport in the atmosphere for any region of the world up to 3-h temporal resolution and different horizontal resolutions. The transport may be established between sources and sinks, both in a forward or backward tracking in time. Currently, two open-source post-processing options developed within the EPhyslab-UVigo group are available for the analysis of these data: TROVA (Fernadez-Alvarez et al., 2022) and LATTIN (Perez-Alarcón et al., 2024) with different moisture tracking calculation options, and the latter including tools for heat transport analysis. Both options allow different methodologies (those most widely used) for the moisture transport analysis. The studies can be configured for any region of the planet, specifying it by a NetCDF 2-D mask, and the moisture transport can be set for different time periods (from 1 to 15 days, being from 8 to 10 days the periods most commonly applied according to the mean residence time of water vapor in the atmosphere). For further discussion on the residence time of water vapor in the atmosphere and its application for Lagrangian studies see Gimeno et al. (2021) and Nieto and Gimeno (2019).</p> <h2><strong>Example of application</strong></h2> <p>J. C. Fernández-Álvarez, M. Vázquez, A. Pérez-Alarcón, R. Nieto, L. Gimeno (2023) Comparison of moisture sources and sinks estimated with different versions of FLEXPART and FLEXPART-WRF models forced with ECMWF reanalysis data, Journal of Hydrometeorology, doi: 10.1175/JHM-D-22-0018.1.</p> <p>A. Pérez-Alarcón, R. Sorí, M. Stojanovic, M. Vázquez, R.M. Trigo, R. Nieto, L. Gimeno (2024) Assessing the Increasing Frequency of Heat Waves in Cuba and Contributing Mechanisms, Earth Systems and Environment, DOI: 10.1007/s41748-024-00443-8</p> <h2><strong>Validation</strong></h2> <p>The moisture transport analysis provided by this dataset was validated by Fernández-Alvarez et al. (2023) through an in-depth comparison with different versions of the model, horizontal resolutions and input data, including the ERA-Interim reanalysis from the ECMWF, which has been widely used for this purpose over the past decades.</p> <h2><strong>Data Access</strong></h2> <p>Data access is available by contacting the EPhysLab group via: rnieto[at]uvigo.gal or l.gimeno[at]uvigo.gal</p>
Data on the gravitational settling experiment and FLEXPART simulations output
<p>Data accompanying the research paper 'Shape matters: long-range transport of microplastic fibers in the atmosphere' by Tatsii et al., 2023 accepted by ACS Environmental Science and Technology journal.</p> <p> </p> <p>The uploaded text file refers to the experimental data on gravitationsl settling of microplastic fibers and spheres.</p> <p>Tar archives contain the FLEXPART (Lagrangian particle dispersion model) simulations output considering low and high scavenging efficiencies.</p>
NASA_ACCDAM_FLEXPART_ERA5_BackTrajectory_28yrOzone_WNA
<p>We are planning to publish our model product on source-receptor relationship (SRR) simulations using FLEXPART-ERA5 in backward mode. This dataset spans 28 years (1994–2021) of ozone observations, covering altitudes from 900 hPa to 300 hPa over western North America.</p> <p>The resulting SRR allows users to investigate the similarities and differences in the origin locations of air parcels that contained, for instance, the highest and lowest ozone levels when sampled near or over western North America.</p> <p>We have uploaded an example of our product on this site, and the complete dataset will ultimately be archived at NASA's Atmospheric Science Data Center (ASDC). Specifically, this sample include: 1) a folder for one-month SRR with a corresponding readme file ("<a href="https://zenodo.org/api/records/14227019/draft/files/WUSA_201607_v2.zip/content" target="_blank" rel="noopener noreferrer">WUSA_201607_v2.zip</a>")<span>. 2) a monthly averaged NetCDF file with an accompanying readme file ("</span><a href="https://zenodo.org/api/records/14227019/draft/files/Example_montly_2001-02_NH.nc/content" target="_blank" rel="noopener noreferrer">Example_montly_2001-02_NH.nc</a><span>"). 3) three MATLAB scripts for binary-to-NetCDF conversion (connecting 1) and 2)). 4) the 28-year ozone data CSV file ("<a href="https://zenodo.org/api/records/14227019/draft/files/Receptor_western_NAmerica_ozone_obs_1994_2021_from900to300.csv/content" target="_blank" rel="noopener noreferrer">Receptor_western_NAmerica_ozone_obs_1994_2021_from900to300.csv</a>"). </span></p> <p>Additionally, we have prepared a to-be-submitted manuscript to describe this product in detail, including its associated applications.</p> <p> </p>
Simulations of FLEXPART-WRF used for testing TRansport Of water VApor (TROVA) software (Part II)
<p>Necessary data for carrying out the tests using TRansport Of water VApor (TROVA) software for backward in time. The TROVA software, was developed in Python and Fortran for the study of moisture sources and sinks. <span><span><span>In addition, the Python code is provided for the representation of the results.</span></span></span></p>
Zeppelin_BC_FLEXPART_2009
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2009.</p>
Zeppelin_BC_FLEXPART_2015
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2015.</p>
Zeppelin_BC_FLEXPART_2010
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2010.</p>
Zeppelin_BC_FLEXPART_2002
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2002.</p>
Zeppelin_BC_FLEXPART_2013
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2013.</p>
Zeppelin_BC_FLEXPART_2006
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2006.</p>
Zeppelin_BC_FLEXPART_2011
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2011.</p>
Zeppelin_BC_FLEXPART_2014
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2014.</p>
Zeppelin_BC_FLEXPART_2007
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2007.<br> </p>
Zeppelin_BC_FLEXPART_2003
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2003.</p>
Zeppelin_BC_FLEXPART_2008
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2008.</p>
Zeppelin_BC_FLEXPART_2005
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2005.</p>
Zeppelin_BC_FLEXPART_2012
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2012.</p>
Zeppelin_BC_FLEXPART_2004
<p>FLEXPART sensitivities at three vertical levels for twenty day simulations backward in time. <br> The Flexpart BC tracer model was used for simulating backwards the light-absorbing aerosol arriving at Zeppelin during 2004.</p>
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