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4 results for “Inn valley”
Supplementary material (part 2): "Evaluation of AROME Model Valley Wind Simulations in the Inn Valley, Austria"
<p><em>Part 2</em> of supplementary material for the Master's Thesis: "Evaluation of AROME Model Valley Wind Simulations in the Inn Valley, Austria" (Wibmer 2024, available <a href="https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-151801">here</a>).</p> <p>Due to memory constraints, the supplementary material consists of two parts:</p> <ul> <li><em><strong>Part 1: </strong></em>(available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>) Includes Python scripts and model setup files, along with the first part of the datasets, including ERA-reanalysis data, observational data, and the preprocessed AROME model output (NetCDF files) of the <em>0.5-km</em> simulation.</li> <li><em><strong>Part 2: </strong></em>Includes the preprocessed AROME model output (NetCDF files) of the <em>1.0-km </em>and <em>2.5-km</em> simulations (see description below).</li> </ul> <p>To reproduce part of the figures, users must download the Python scripts and the preprocessed AROME model datasets (NetCDF files). <br>The Python scripts should be placed in the same parent folder because some of them depend on each other <strong>(!! Important !!).</strong><br>Original AROME model output files (GRIB2 format) are not published due to their large size.</p> <p>The naming convention for the AROME simulations uses OP* (where * represents the grid spacing in meters) to differentiate the model runs based on their horizontal<br>grid spacing:</p> <ul> <li><strong><em>OP2500:</em></strong> for 2.5 km</li> <li><em><strong>OP1000: </strong></em>for 1.0 km</li> <li><em><strong>OP500:</strong></em> for 0.5 km</li> </ul> <h3><strong>Datasets Part 2</strong></h3> <p>Due to memory constraints, the datasets needed for the analyses are split up into two parts. The second part of the supplementary material contains:</p> <ul> <li><strong>datasets_OP1000.tar.xz</strong>: Contains the preprocessed AROME-Aut model output data (NetCDF files) of the <em>1.0-km</em> simulation. </li> <li><strong>datasets_OP2500.tar.xz</strong>: Contains the preprocessed AROME-Aut model output data (NetCDF files) of the <em>2.5-km</em> simulation. </li> </ul> <p>The datasets of the<em> 0.5-km</em> simulation (<strong>datasets_OP500.tar.xz</strong>)<strong> </strong>can be found in Part 1 of the supplementary material (available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>).<br>The NetCDF datasets of the performed AROME-Aut simulations are packaged and compressed into <code><em><strong>.tar.xz</strong></em></code> files.<br>The Python scripts, available <a href="https://doi.org/10.5281/zenodo.10849397" target="_blank" rel="noopener">here</a>, require these NetCDF datasets for plotting and analyses routines.<br>The provided NetCDF datasets are preprocessed from the <em>GRIB2</em> output of the AROME-Aut simulations. <br>For the scripts to function properly, you need to adjust the path to the datasets within <code><strong>path_handling.py</strong></code><strong>.</strong></p> <p>Each <strong><code>datasets_OP*.tar.xz</code></strong> file contains NetCDF files for different type of levels: <em>surface, hybridPressure </em>(model levels)<em>, isobaricInhPa </em>(pressure levels),<em> meanSea </em>(mean sea level)<em>, heightAboveGround </em>(constant height levels)<em>. </em> The following naming convention for the datasets is used:</p> <ul> <li><strong>ds_OP*_<em>var</em>_hybridPressure_<em>[lon1, lon2, lat1, lat2]</em>.nc</strong>: Contains data on <em>hybrid pressure model levels</em> for a specific variable (<em>var</em>; e.g., <em>u, v, z, pres, q, t</em>) for the geographical extent defined in the brackets. </li> <li><strong>ds_OP*_interp_hybridPressure_<em>(lon,lat)</em>.nc</strong>: Combined dataset on <em>hybrid pressure model levels.</em> The data is bilinearly interpolated to the specified location <em>(lon, lat)</em>.</li> <li><strong>ds_OP*_<em>var</em>_surface_<em>whole</em>.nc</strong>: Contains data on <em>model surface </em>for a specified variable (<em>var</em>; e.g., <em>z, sp, t, tcc</em>) for the <em>whole </em>available domain extent.</li> <li><strong>ds_OP*_heightAboveGround_instant_<em>whole</em>.nc</strong>: Combined dataset on <em>height levels </em>(e.g., <em>2-m and 10-m</em>) for the <em>whole </em>available domain extent.</li> <li><strong>ds_OP*_<em>var</em>_meanSea_<em>whole</em>.nc</strong>: Contains data on <em>mean sea level</em> for specified variable (<em>var;</em> e.g., <em>prmsl</em>) for the <em>whole</em> available domain extent. </li> </ul> <p>The original GRIB2 files are not provided due to their large size. For further information about the GRIB2 files or the NetCDF datasets, please feel free to contact me.</p>
TEAMx-PC22 (TEAMx pre-campaign 2022) – DWD AWS dataset for the Inn Valley exit area
<p>This dataset contains data measured at 5 automatic weather stations operated by the German Meteorological Service (DWD) during the TEAMx pre-campaign 2022. More details about TEAMx can be found at <a href="http://www.teamx-programme.org/">http://www.teamx-programme.org</a>.</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p><strong>1. Measurement location, instrumentation and measured variables</strong></p> <p>The following table lists the station locations and available measurements. Data of the automatic weather stations is provided from the given start date until 19.10.2022 23:50 at a temporal resolution of 10min. If not noted otherwise, wind, temperature, humidity and pressure are measured at 2m above ground, precipitation at 1m above ground.</p> <table> <thead> <tr> <th scope="col">Station name</th> <th scope="col">start of deployment</th> <th scope="col">location and elevation</th> <th scope="col">instruments</th> <th scope="col">measured variables</th> </tr> </thead> <tbody> <tr> <td>Brannenburg</td> <td>24.06.2022</td> <td> <p>47.742360 N</p> <p>12.121712 E</p> <p>456 m MSL</p> </td> <td> <p>LTS2000, HMP45d, Gill,</p> <p>mSonic3, PTB330, CNR4,</p> <p>Pluvio, HFP01SC</p> </td> <td> <p>U_xm,V_xm,W_xm (2m*,4m,10m*)</p> <p>T, TX, TN, RH, P, RR, GSR, RSR, ALR, SLR</p> </td> </tr> <tr> <td>Flintsbach</td> <td>02.06.2022</td> <td> <p>47.728401 N</p> <p>12.127413 E</p> <p>468 m MSL</p> </td> <td>LTS2000, HMP45d, Thies</td> <td>WDIR, WSPEED, T, TX, TN, RH</td> </tr> <tr> <td>Hohe Asten</td> <td>02.06.2022</td> <td> <p>47.703476 N</p> <p>12.115288 E</p> <p>1226 m MSL</p> </td> <td>LTS2000, HMP45d, Thies</td> <td>WDIR, WSPEED, T, TX, TN, RH</td> </tr> <tr> <td>Kiefersfelden</td> <td>05.06.2022</td> <td> <p>47.607147 N</p> <p>12.202737 E</p> <p>473 m MSL</p> </td> <td> <p>LTS2000, HMP45d, Thies,</p> <p>PTB110</p> </td> <td>WDIR, WSPEED, T, TX, TN, RH, P</td> </tr> <tr> <td>Oberaudorf</td> <td>05.06.2022</td> <td> <p>47.654282 N</p> <p>12.180008 E</p> <p>466 m MSL</p> </td> <td>LTS2000, HMP45d, Thies</td> <td>WDIR, WSPEED, T, TX, TN, RH</td> </tr> </tbody> </table> <p> </p> <p> </p> <p><em>Variable abbreviations: U_xm, V_xm=horizontal wind components xm above ground, W=vertical wind component, WDIR=wind direction [°], WSPEED= wind speed [m/s], T=average temperature [°C], TX=maximum temperature [°C], TN=minimum temperature [°C], RH=relative humidity [%], P=pressure [hPa], GSR=global shortwave radiation [W/m<sup>2</sup>], RSR=reflected shortwave radiation [W/m<sup>2</sup>], ALR=atmospheric longwave radiation [W/m<sup>2</sup>], SLR= surface longwave radiation [W/m<sup>2</sup>]</em></p> <p> </p> <p> </p> <p><strong>* </strong>due to quality issues, wind components in 2 and 10m at Brannenburg will be made available at a later date.</p> <p><strong><em>2. Data corrections</em></strong></p> <p>Basic quality checks were applied to the data. Missing values are indicated by NA.</p> <p><strong>3. Data file structure</strong></p> <p>The data are provided in separate .txt files for each station. Files are tab separated. The first column lists the date in the format year-month-day hour:minutes:second. The following column names correspond to the variables listed in section 1.</p> <p><strong>4. Contact</strong></p> <p>Contact Katrin.sedlmeier(at)dwd.de.at for any questions regarding the data set.</p>
Supplementary material (part 2) for "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley"
<p>Part 2 of the supplementary material for the master's thesis "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley." (Deidda 2023, available at <a href="https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436">https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436</a>). The supplementary material consists in two parts: part 1 includes scripts, datasets, model setup files and figures (available at <a href="https://zenodo.org/records/8089010">https://zenodo.org/records/8089010</a>), while part 2 includes the model output needed to create the figures (see description below).</p><p>This directory contains part of the model output used for the thesis. The model used is WRF-ARW version 4.4 (Skamarock et al. 2021). Information on the model setup is available in the thesis, Section 2.2. For storage limitations, only the files needed to create the graphs presented in the thesis are available.</p><p>The file format is <i>type_domain_date.nc </i>where <i>domain</i> is "d01" or "d02" (respectively for the outer or inner domain, see Section 2.2 in the thesis), while <i>type</i> is "wrfout", "mean_out", or "Averaged", where:</p><ul><li>"wrfout" is the instantaneous WRF output;</li><li>"mean_out" is the time-averaged WRF output, computed using the fork <a href="https://github.com/matzegoebel/WRFlux">WRFlux</a>.</li><li>"Averaged" is a combination of time-averaged and instantaneous outputs. These files were created using the the script <i>Create_intermediate_files.py, </i>available in the <a href="https://zenodo.org/records/8089010">software directory </a>(in Scripts.zip). These files were computed to have a lighter and WRF-like formatted data containing the averaged fields needed for the analysis.</li></ul>
Prehistoric Mining sites in the Lower Inn Valley - Federal Monuments Office documentation of the project Austrian Science Fund project "Prehistoric copper production in the eastern and central Alps" (I 1670)
<p>The dataset contains all tables and RDF-triples created based on the following Federal Monuments Office Documentations</p> <ul> <li>87002.15.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5243460"> https://zenodo.org/record/5243460</a></li> <li>87002.16.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5244755"> https://zenodo.org/record/5244755</a></li> <li>87002.17.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5244794"> https://zenodo.org/record/5244794</a></li> <li>87007.15.01_Bergbaurevier_Schwaz_Brixlegg: <a href="https://zenodo.org/record/5236664"> https://zenodo.org/record/5236664</a></li> <li>87007.16.01_Bergbaurevier_Schwaz_Brixlegg: <a href="https://zenodo.org/record/5243123"> https://zenodo.org/record/5243123</a></li> <li>87009.16.01_Erzaufbereitungsplatz_Schrofen: <a href="https://zenodo.org/record/5243416"> https://zenodo.org/record/5243416</a></li> </ul>
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