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94 results for “eddy covariance”
Data from: Lower-cost eddy covariance for CO2 and H2O fluxes over grassland and agroforestry
<p>This datasets contains eddy covariance fluxes calculated with EddyPro, average (co)spectra from EddyPro and meteorological data from the measurement campaigns conducted in Mariensee, Lower Saxony (Germany) in 2020 and 2021. The results were presented in the paper "Lower-cost eddy covariance for CO2 and H2O fluxes over grassland and agroforestry"; <a href="https://doi.org/10.5194/amt-2024-30">https://doi.org/10.5194/amt-2024-30</a>. </p> <p>For more information on the data see the accompanying paper. Note that the eddy covariance data are not filtered, quality checked or gap-filled in these files!</p>
CO2 Flux partioning in a Eddy Covariance tower of marsh ecosystem (Fuente Duque) in Doñana Biological Reserve
<p>This dataset consists of the estimated data of the CO2 flux partition: assimilation or gross primary production (GPP) and heterotrophic or ecosystem respiration (Reco), as well as the standard deviation of each estimate. These data have been estimated from the data provided by the ICTS of the Doñana Biological Reserve of the eddy covariance tower located in Fuente Duque, in the Hinojos marsh in the period between October 2020 and December 2022.</p>
Mass and energy fluxes from the US-Jo2 AmeriFlux eddy covariance tower in Tromble Weir experimental watershed at the Jornada Basin LTER site, 2010-ongoing
This data package contains metadata for, and links to, 30-minute mass and energy flux data collected at an eddy covariance tower in the Tromble Weir Watershed area of the Jornada Basin in southern New Mexico, USA. These data are used to quantify the water and energy balances in a small experimental watershed, including observational studies to calculate groundwater recharge as a water balance residual, to build relations between soil moisture state and ET flux, and to quantify land-atmosphere interactions and improve our understanding of the eddy covariance method. Additionally, they have been used in modeling studies as a validation of model performance. The .csv files included in this package list and describe the data entities and variables present in data files archived at the AmeriFlux data repository (site US-Jo2; http://ameriflux.lbl.gov/sites/siteinfo/US-Jo2). The data at AmeriFlux include the 30-minute mass and energy fluxes calculated from 20 Hz data collected at the Tromble Weir Watershed tower. Instrument descriptions and detailed procedures are found in the references listed in the Methods section of this EDI package. This is an ongoing dataset that will be updated annually.
An Excel spreadsheet including eddy covariance, meteorological, and tidal data measured at Yunxiao mangrove flux tower.
<p>An Excel spreadsheet including eddy covariance, meteorological, and tidal data at Yunxiao mangrove flux tower required to reproduce key findings in Figures 4-9 in the main text (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.</p>
Eddy covariance data processing workflow example utilizing openeddy and REddyProc R packages
<p>The example dataset is provided within the folder structure required by the workflow files (version 2025-04-27; amended on 2025-07-31) related to the R package openeddy version 0.0.0.9009. Only files needed for successful processing are included. It is shared here as part of a data processing example at <a href="https://github.com/lsigut/EC_workflow">https://github.com/lsigut/EC_workflow</a> to overcome the file size limitation of GitHub.</p>
TEAMx-PC22 (TEAMx pre-campaing 2022) - ACINN Distributed temperature sensing, fluxes from eddy covariance measurements, and auxiliary measurements from and at the i-Box station (VF-0) Kolsass
<p><strong>Introduction</strong></p> <p>During the TEAMx-precampaign (TEAMx-PC22) in summer 2022, the Innsbruck Box (i-Box) station at the valley floor in Kolsass (CS-VF0) was extended by a vertical array with fiber-optic distributed temperature sensing (DTS). The i-Box is a testbed for studying boundary layer processes in highly complex terrain (<a href="http://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-15-00246.1">Rotach et al. (2017)</a> and <a href="https://fileshare.uibk.ac.at/f/9f1101851849439483de/">i-Box WIKI</a> for further information). The mountain boundary layer is investigated using a 17 m high tower with multi-level observations of turbulence, wind speed, and temperature. DTS measurements with a spatio-temporal resolution of 0.127 m and 1 s were added to these profile measurements. The combination of DTS measurements and point observations has the capability of resolving sub-meso scale motions (<a href="https://doi.org/10.1007/s10546-021-00618-0">Pfister et al. 2021</a>) and can reveal processes within the boundary layer during the morning and evening transition (<a href="https://doi.org/10.1029/2020GL092238">Fritz et al. 2021</a>).</p> <p>The aim of TEAMx-PC22 was to test new instruments, new instrument configurations and new measurement sites to support the planning of the main TEAMx observational campaign (TOC) in 2024/2025. More details about TEAMx can be found at <a href="http://www.teamx-programme.org">http://www.teamx-programme.org</a> as well as in <a href="https://doi.org/10.15203/99106-003-1">Serafin et al. (2020)</a> and in <a href="https://doi.org/10.1175/bams-d-21-0232.1">Rotach et al. (2022)</a>.</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p><strong>1. Location</strong></p> <p>The i-Box valley-floor site is located on the almost flat floor near the town of Kolsass within the Inn Valley roughly 20 km east-north-east of Innsbruck. The site is characterized by different types of agricultural land. The 17-m high tower is a full energy-balance station and is instrumented with three vertical levels of turbulence measurements. The exact location is 47.305341°N, 11.62219°E (UTM: 698215.03 E, 5242420.95 N) at 545 m above mean sea level.</p> <p><strong>2. Temporal coverage</strong></p> <p>The TEAMx-PC22 lasted from mid-May 2022 to early October 2022. The i-Box station is running continuously, however, the provided data only covers the period when DTS data is available. The DTS array was running during the following periods:</p> <ul> <li>08.06.-14.06.2022</li> <li>28.06.-18.07.2022</li> </ul> <p><strong>3. Instrument details</strong></p> <p><em><strong>Distributed temperature sensing</strong></em></p> <p>For spatially continuous measurements of vertical temperature profiles at this tower, a DTS array was installed. Temperatures were measured with two channels at 1~Hz with a spatial resolution of 0.127~m. The used DTS instrument was an Ultima-HS (Silixa Ltd., Hertfordshire, UK) which was combined with a fibre-optic cable (900 µm outer diameter; AFL Telecommunications, Spartanburg, SC, USA) consisting of a bend-optimised optical fiber (125 µm with 50 µm core), buffered with Kevlar in a white plastic jacket. The fiber-optic cable was installed vertically towards the west of the tower such that two temperature profiles could be measured simultaneously. For the full array the approximately 450 m long fiber-optic cable was running from one DTS channel through a warm and cold reference bath towards the tower, then up and down the 17-m tower, and back through the baths towards the second channel. Accordingly, the array could be measured in both directions. For mounting at the top and bottom of the tower PVC pipes (diameter 15 cm) were used. The setup with two channels allows for sampling the array in both directions. Before entering the reference baths roughly 200 m were left on the spool slightly affecting signal-to-noise ratio. The vertical array was mapped by cooling packs. Both reference baths observed at the beginning and end of each fiber-optic cable yielded to four reference sections at two temperatures. The array was a double-ended configuration observed as two single-ended configurations which is different from the manufacturer's provided double-ended mode (<a href="https://doi.org/10.3390/s20082235">des Tombe et al. 2020</a>, <a href="https://doi.org/10.5194/essd-14-885-2022">Lapo et al. 2022</a>). Reference temperature probes were PT100 from the Ultmia-HS itself. DTS data was calibrated using the weighted-least squares approach described in <a href="https://doi.org/10.3390/s20082235">des Tombe et al. (2020)</a> and implemented in the <em>dtscalibration</em> software package (<a href="https://doi.org/10.5281/zenodo.7111585">des Tombe et al. 2022</a>) and all processing was completed using the <em>pyfocs</em> software package (<a href="https://doi.org/10.5281/zenodo.7111585">Lapo and Freundorfer 2020</a>) . As the fiber-optic cable runs through both calibration baths before and after the array creating four locations within a temperature controlled environment. Of those locations three are used for calibration (every time step) and the fourth is used for validation. A schematic of the setup is given within the files.</p> <p>After calibration a mean bias of -0.05 K and root mean squared difference of 0.22 K was determined with the validation water bath.</p> <p>Unfortunately the mounting towards the west created an artifact as the tower was partially shading the fiber-optic cable creating unphysical temperature gradients. Accordingly, data from 04.00 - 09.00 UTC should not be used for data analysis. The given data is only a single fiber of the paired vertical sections on the 17-m tower. Artifacts from the plastic ring holders are removed from the fiber.</p> <p>The DTS experiment was named the Innsbruck DTS Experiment (InnDEX22), hence, data names were chosen accordingly. But keep in mind that InnDEX22 was part of TEAMx-PC22.</p> <p><em><strong>i-Box tower</strong></em></p> <p>Full site description and all data exceeding the DTS observations can be found on <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a>. Utilized and uploaded data are mainly within three categories: eddy covariance (EC) fluxes at level 1 (4 m agl) and at level 2 (8.7 m agl) and low-frequency data:</p> <ul> <li>EC flux level 1:<br>Combination of ultrasonic anemometer CSAT3 (orientation from North: 30°) and infrared gas analyzer EC150 from Campbell Scientific</li> <li>EC flux level 2:<br>Ultrasonic anemometer CSAT3 (orientation from North: 30°) from Campbell Scientific</li> <li>low-frequency data: <ul> <li>pressure: Setra 278 (Setra Systems, Inc., Boxborough, Maine, USA) at 1.4 m agl</li> <li>radiation: ventilated CGR4 pyrgeometers and CMP21 pyranometers (Kipp & Zonen, Delft, Netherlands) at 2 m agl</li> <li>temperature profile: Rotronic HC2-S3 actively ventilated at 2, 4, 8.7, and 16.9m</li> <li>wind profile: 2D ultrasonic anemometer Gill Windsonic4 at 2, 4, 6, and 12m</li> </ul> </li> </ul> <p>For the EC processing further quality criteria can be applied to assure good data quality. More information on processing of data and quality criteria is given here:</p> <ul> <li>EC fluxes processing:<br>Averaging interval of 30 min performed by the software <a href="https://www.geos.ed.ac.uk/homes/jbm/micromet/EdiRe/">EdiRe</a><br>Processing includes despiking; double-rotation of the wind components; detrending with a recursive filter and a time constant of 200 s; and applying frequency-response corrections, heat-flux corrections for humidity effects, oxygen corrections for KH20, and WPL corrections. The datafile contains several quality flags and added as description within the netcdf files; zero-plane displacement height of 0 m</li> <li>EC flux Quality Criteria (QC) flags: <ul> <li>-1: all data</li> <li>0: excluding instrument malfunction</li> <li>1: additionally skewness within range (-2 to 2) and kurtosis <8 following Vickers and Mahrt 1997</li> <li>2: additionally exclude non-stationary data</li> </ul> </li> <li>EC flux Flags: <ul> <li>0: data ok</li> <li>1: data not ok (see description of individual flag for further details)</li> </ul> </li> </ul> <p><strong>4. Data file structure</strong></p> <p><em><strong>Zip folders</strong></em></p> <p>Different data sets were generated, as measurements had different temporal resolutions or different sets of parameter. Accordingly the following data is given:</p> <ul> <li>DTS data (1 s): InnDEX22_distributed_temperature_sensing.zip</li> <li>EC flux level 1 (30 min): InnDEX22_EC_flux_lvl1.zip</li> <li>EC flux level 2 (30 min): InnDEX22_EC_flux_lvl1.zip</li> <li>Low-frequency data (1 min): InnDEX22_low_frequency_data.zip</li> </ul> <p><em><strong>File format</strong></em></p> <p>Each above mentioned folder is filled with netcdf files. One for each day. Global information contains location, instrument type etc. Parameter description is given as attributes for each parameter.</p> <p><strong>6. Contact</strong></p> <p>Contact lena.pfister(at)uibk.ac.at for any questions regarding the data set.</p> <p><em><strong>Acknowledgements</strong></em></p> <p>Special thanks to the "Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung" (IMK-IFU), KIT-Campus Alpin, Garmisch-Partenkirchen, for lending us the DTS measurement device for TEAMx-PC22.</p> <p><strong>7. References</strong></p> <p>Fritz, A. M., Lapo, K., Freundorfer, A., Linhardt, T., & Thomas, C. K. (2021): Revealing the morning transition in the mountain boundary layer using fiber-optic distributed temperature sensing. <em>Geophysical Research Letters</em>, 48, e2020GL092238. <a href="https://doi.org/10.1029/2020GL092238">https://doi.org/10.1029/2020GL092238</a></p> <p>des Tombe, B., Schilperoort, B., Bakker, M. (2020): Estimation of Temperature and Associated Uncertainty from Fiber-Optic Raman-Spectrum Distributed Temperature Sensing. <em>Sensors</em>, 20, 2235. <a href="https://doi.org/10.3390/s20082235">https://doi.org/10.3390/s20082235</a></p> <p>des Tombe, Bas François, & Schilperoort, Bart. (2022): Dtscalibration Python package for calibrating distributed temperature sensing measurements (v1.1.2). <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.7111585">https://doi.org/10.5281/zenodo.7111585</a></p> <p>Pfister, L., Lapo, K., Mahrt, L., Thomas, C.K. (2021): Thermal Submesoscale Motions in the Nocturnal Stable Boundary Layer. Part 1: Detection and Mean Statistics. <em>Boundary-Layer Meteorol</em> 180, 187–202. <a href="https://doi.org/10.1007/s10546-021-00618-0">https://doi.org/10.1007/s10546-021-00618-0</a></p> <p>Lapo, K., Freundorfer, A., (2020): klapo/pyfocs v0.5: Fully-functional python package intended for atmospheric deployments of distributed temperature sensing. <em>Zenodo</em>, <a href="https://doi.org/10.5281/zenodo.7111585">https://doi.org/10.5281/zenodo.7111585</a></p> <p>Lapo, K., Freundorfer, A., Fritz, A., Schneider, J., Olesch, J., Babel, W., and Thomas, C. K. (2022): The Large eddy Observatory, Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing, <em>Earth Syst. Sci. Data</em>, 14, 885–906 <a href="https://doi.org/10.5194/essd-14-885-2022">https://doi.org/10.5194/essd-14-885-2022</a></p> <p>Serafin, S., M. W. Rotach, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. De Wekker, M. Evans, V. Grubišić, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Raudzens Bailey, J. Schmidli, G. Wohlfahrt, B. Zardi, (2020): Multi-scale transport and exchange processes in the atmosphere over mountains: Programme and experiment. <em>Innsbruck University Press</em>. <a href="https://doi.org/10.15203/99106-003-1">https://doi.org/10.15203/99106-003-1</a></p> <p>Rotach, M. W., S. Serafin, H. C. Ward, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. D. Wekker, V. Grubišic, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Bailey, J. Schmidli, C. Wittmann, G. Wohlfahrt, D. Zardi, (2022): A collaborative effort to better understand, measure, and model atmospheric exchange processes over mountains. <em>Bulletin of the American Meteorological Society</em>, 103, E1282–E1295. <a href="https://doi.org/10.1175/bams-d-21-0232.1">https://doi.org/10.1175/bams-d-21-0232.1</a></p>
Eddy Covariance dataset for BR-IAB: Instituto Arruda Botelho - Wooded Cerrado and Mixed Agriculture
<p>The micrometeorological variables were measured using slow (rainfall, temperature, relative humidity, net radiation, soil heat flux, and soil moisture at 1 Hz) and fast (wind speed and direction, water and carbon dioxide molar fractions at 20 Hz) instrumentation. The instruments were fixed on a 24-meter-high metal tower, which was equipped with a data acquisition and storage system. Despite the tower height, the main pieces of equipment were positioned below the maximum tower height due to footprint restrictions and lightning protection (16 m). The flux tower was operated between 2018 and 2021. The tower is listed with the site ID BR-IAB on the Ameriflux platform (https://ameriflux.lbl.gov/sites/siteinfo/BR-IAB). The site is located in the city of Itirapina, within the state of São Paulo, Brazil (22° 10.2517' S, 47° 52.2567' W).</p>
Carbon and energy Eddy-covariance fluxes dataset collected at La Guette peatland (23 ha, Loiret, France)
<p>Fluxes and energy data measured by Eddy-covariance on La Guette peatland (ec1). Measurements start on 20-01-2017 and are regularly updated with new data. Data include carbon dioxide fluxes (CO2, µmol/m²/s), methane fluxes (CH4, µmol/m²/s), sensible heat fluxes (H, W/m²), latent heat fluxes (LE, W/m²) and evapotranspiration (ETR, mm/h).</p> <p>Zip file contain :</p> <ul> <li>metadata file (TOUR_en.json) which describe stations, sensors, variables and process</li> <li>csv file contain time series data for all variables by station</li> </ul> <p>Additional information on the measurement can be found in this website : <a href="https://data-snot.cnrs.fr/data-access/">https://data-snot.cnrs.fr/data-access/</a></p> <p>We also recommend to contact sno-tourbieres to talk about data acquisition and use : <a href="mailto:contact.sno-tourbieres@cnrs-orleans.fr">contact.sno-tourbieres@cnrs-orleans.fr</a></p>
Carbon and energy Eddy-covariance fluxes dataset collected at Frasne peatland (192ha, Jura Mountains, France)
<p>luxes and energy data measured by Eddy-covariance at Frasne peatland (ec1). Measurements start on 20-07-2018 and are regularly updated with new data. Data include carbon dioxide fluxes (CO2, µmol/m²/s), methane fluxes (CH4, µmol/m²/s), sensible heat fluxes (H, W/m²), latent heat fluxes (LE, W/m²) and evapotranspiration (ETR, mm/h).</p> <p>Zip file contain :</p> <ul> <li>metadata file (TOUR_en.json) which describe stations, sensors, variables and process</li> <li>csv file contain time series data for all variables by station</li> </ul> <p>Additional information on the measurement can be found in this website : <a href="https://data-snot.cnrs.fr/data-access/">https://data-snot.cnrs.fr/data-access/</a></p> <p>We also recommend to contact sno-tourbieres to talk about data acquisition and use : <a href="mailto:contact.sno-tourbieres@cnrs-orleans.fr">contact.sno-tourbieres@cnrs-orleans.fr</a></p>
Data set supporting journal article: Markwitz, C. and Siebicke, L.: "Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany", Atmos. Meas. Tech., 2019
<p>This data set contains evapotranspiration data obtained by a conventional eddy covariance set-up and a low-cost eddy covariance set-up as described in the research article: Markwitz, C. and Siebicke, L.: "Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany", Atmos. Meas. Tech., 2019.</p> <p>The data set contains all necessary data needed to replicate figures and analysis presented in the research article. The data sets are sorted and named according to the figure the data were used for. </p>
Raw Eddy-Covariance data
<p>This dataset contains the raw eddy-covariance data used in the paper "Relaxed eddy accumulation outperforms Monin-Obukhov flux models under non-ideal conditions"</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 2-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 2-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 2-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_2min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 1-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 1-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 1-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_1min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 10-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 10-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 10-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_10min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 3-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 3-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10:<a href="http://https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html"> https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 3-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_3min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 5-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 5-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 5-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_5min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 30-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 30-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 30-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_30min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processin</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p> <p> </p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 15-min statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 15-min statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 15-min statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_15min.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
i-Box (Innsbruck Box) – processed eddy-covariance data: 30-s statistics
<p><strong>Abstract</strong></p> <p>The dataset contains eddy-covariance data from five i-Box stations in the Austrian Inn Valley, which have been processed to 30-s statistics. The i-Box is a long-term measurement platform, including a small network of eddy-covariance stations in the lower Inn Valley, to study boundary-layer processes in mountainous terrain. More information about the i-Box can be found at <a href="https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en">https://www.uibk.ac.at/acinn/research/atmospheric-dynamics/projects/innsbruck-box-i-box.html.en</a> and in Rotach et al. (2017).</p> <p> </p> <p><strong>Data description</strong></p> <p><em>Station locations</em></p> <p>The present dataset contains processed data from five i-Box stations located in the Austrian Inn Valley. The Inn Valley is an approximately southwest-northeast oriented valley in the western part of Austria, with a depth of about 2000 m and a width of about 2 km at the valley floor. The locations of the sites are shown in the overview figure i-Box_sites.pdf.</p> <ul> <li> <p>VF0 is located at the almost flat valley floor. The site is surrounded by grassland and agricultural fields. (47.305°N, 11.622°E, 545 m MSL)</p> </li> <li> <p>SF8 is located at the foot of the north sidewall next to a steep embankment between an agricultural field and a concrete parking lot. (47.326°N, 11.652°E, 575 m MSL)</p> </li> <li> <p>SF1 is located on an almost flat plateau running along the northern valley sidewall. The site is mainly surrounded by grassland and agricultural fields. (47.317°N, 11.616°E, 829 m MSL)</p> </li> <li> <p>NF10 is located on an approximately 10 deg slope on the south sidewall, covered by grassland. (47.300°N, 11.673°E, 930 m MSL)</p> </li> <li> <p>NF27 is located on a steep, grass-covered slope on the south sidewall, with a slope angle of about 25 deg. (47.288°N, 11.631°E, 1009 m MSL)</p> </li> </ul> <p>Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021).</p> <p><em>Temporal coverage</em></p> <p>The dataset contains processed data between 2014 and 2020. Some instruments were replaced and new instruments were added during this period. Data gaps occur as a result of instrument malfunctions and maintenance.</p> <p><em>Instrumentation</em></p> <p>Each station is equipped with at least one sonic anemometer and a gas analyzer. The instrumentation usually consists of a CSAT3 sonic anemometer (Campbell Scientific, USA) and KH20 Krypton hygrometer (Campbell Scientific) or an EC150 open-path infrared gas analyzer (Campbell Scientific). In 2020, several of the instruments were replaced with an Irgason (Campbell Scientific), which combines an open-path infrared gas analyzer with a sonic anemometer. Pressure, air temperature, and humidity used for calculating flux corrections are measured with Setra 278 sensors (Setra Systems, USA) and Rotronic HC2A-S temperature and humidity probes (Rotronic, Switzerland).</p> <ul> <li> <p>VF0: CSAT3 and EC150 at 4.0 m, CSAT3 at 8.7 m, CSAT3 and KH20 (until July 2020) or Irgason (since July 2020) at 16.9 m</p> </li> <li> <p>SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m</p> </li> <li> <p>SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m</p> </li> <li> <p>NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m</p> </li> <li> <p>NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m</p> </li> </ul> <p>Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database:</p> <ul> <li> <p>VF0: <a href="https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html">https://acinn-data.uibk.ac.at/pages/i-box-kolsass.html</a></p> </li> <li> <p>SF8: <a href="https://acinn-data.uibk.ac.at/pages/i-box-terfens.html">https://acinn-data.uibk.ac.at/pages/i-box-terfens.html</a></p> </li> <li> <p>SF1: <a href="https://acinn-data.uibk.ac.at/pages/i-box-eggen.html">https://acinn-data.uibk.ac.at/pages/i-box-eggen.html</a></p> </li> <li> <p>NF10: <a href="https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html">https://acinn-data.uibk.ac.at/pages/i-box-weerberg.html</a></p> </li> <li> <p>NF27: <a href="https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html">https://acinn-data.uibk.ac.at/pages/i-box-hochhaeuser.html</a></p> </li> </ul> <p><em>Data processing</em></p> <p>Raw 20-Hz data were quality controlled and rotated into a streamline coordinate system using double rotation before block averaging the data to 30-s statistics, without previous filtering. Flux corrections were applied to the turbulence statistics, including a frequency response correction (Aubinet et al. 2012) with spectral models following Moore (1986), Højstrup (1981), and Kaimal et al. (1972); a sonic heat-flux correction of the vertical heat flux and the temperature variance (Schotanus et al. 1983); a WPL correction of the vertical moisture flux (Webb et al. 1980); and an Oxygen correction of the vertical moisture flux for data from Krypton hygrometers (van Dijk et al. 2003).</p> <p>The quality control procedures include the removal of data during periods of instrument malfunction as indicated by the instruments’ quality flags, a despiking, the removal of data points exceeding 30 m s<sup>-1</sup> for the horizontal wind components, 10 m s<sup>-1</sup> for the vertical wind velocity, and 50 g m<sup>3</sup> for water vapor density, and the removal of sonic temperature data outside the range -20 – 40°C. The removed data are replaced with random values drawn from a Gaussian distribution, with its mean and standard deviation calculated over a 30-s data window.</p> <p>Quality flags are based on the criteria described in Stiperski and Rotach (2016):</p> <ul> <li> <p>-1: More than 10% of the raw data within the averaging period are replaced during the quality control.</p> </li> <li> <p>0: More than 90% of the raw data fulfill the quality control criteria.</p> </li> <li> <p>1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8.</p> </li> <li> <p>2: In addition to the above criteria, the stationarity test by Foken and Wichura (1996) is below 30% and the uncertainty is less than 50% based on Stiperski and Rotach (2016) and Wyngaard (1973)</p> </li> </ul> <p><em>Data files</em></p> <ul> <li> <p>i-Box_sites.pdf contains a map of the i-Box stations.</p> </li> <li> <p>list_variables.pdf contains a list of variable names with a short description.</p> </li> <li> <p>SITENAME_30s.zip contains the processed turbulence statistics, split into yearly files. There is more than one file per year if the instrumentation changed during the year or because of memory restrictions during the processing.</p> </li> </ul> <p><em>Acknowledgments</em></p> <p>Data processing was performed in the framework of the TExSMBL (Turbulent Exchange in the Stable Mountain Boundary Layer) project funded by the Austrian Science Fund (FWF) under grant V 791-N. Data were processed on the LEO HPC infrastructure of the University of Innsbruck.</p> <p><em>References</em></p> <p>Aubinet M, Vesala T, D P (eds) (2012) Eddy Covariance. A practical guide to measurements and data analysis. Springer, Dordrecht, DOI 10.1007/978-94-007-2351-1</p> <p>Højstrup J (1981) A simple model for the adjustment of velocity spectra in unstable conditions downstream of an abrupt change in roughness and heat flux. Boundary-Layer Meteorol 21:341–356, DOI 10.1007/bf00119278</p> <p>Kaimal JC, Wyngaard JC, Izumi Y, Coté OR (1972) Spectral characteristics of surface-layer turbulence. Q J R M Soc 98:563–589, DOI 10.1002/qj.49709841707</p> <p>Lehner M, Rotach MW, Sfyri E, Obleitner F (2021) Spatial and temporal variations in near-surface energy fluxes in an Alpine valley under synoptically undisturbed and clear-sky conditions. Q J R M Soc 147:2173–2196, DOI 10.1002/qj.4016</p> <p>Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754</p> <p>Rotach MW, Stiperski I, Fuhrer O, Goger B, Gohm A, Obleitner F, Rau G, Sfyri E, Vergeiner J (2017) Investigating exchange processes over complex topography—the Innsbruck Box (i-Box). Bull Amer Meteorol Soc 98:787–805, DOI 10.1175/BAMS-D-15-00246.1</p> <p>Schotanus P, Nieuwstadt FTM, de Bruijn HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boundary-Layer Meteorol 26:81–93, DOI 10.1007/BF00164332</p> <p>Stiperski, I. and Rotach, M.W. (2016) On the measurement of turbulence over complex mountainous terrain. Boundary-Layer Meteorology, 159, 97–121. DOI 10.1007/s10546-015-0103-z.</p> <p>Van Dijk A, Kohsiek W, de Bruin HAR (2003) Oxygen sensitivity of Krypton and Lyman-α hygrometers. J Atmos Ocean Technol 20:143–151, DOI 10.1175/1520-0426(2003)020¡0143:OSOKAL¿2.0.CO;2</p> <p>Webb EK, Pearman GI, R L (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R M Soc 106:85–100, DOI 10.1002/qj.49710644707</p> <p>Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.</p>
Observed and modelled GPP at 61 eddy covariance sites (2007-2018)
<p>In the frame of the ECOPROPHET project, data was collected from in situ observations, remote-sensing sources and models for 61 sites. The objective of this project was to improve our understanding of ecosystem productivity and the role of vegetation phenology as a key determinant of ecosystem carbon, water and energy balances. More info and publications can be found at http://ecoprophet.meteo.be<br> This dataset contains timeseries of observed GPP, modelled GPP (using 15 models), along with key hydrometeorological variables (shortwave radiation, air temperature, vapor pressure deficit and soil moisture).<br> The timeseries are at daily resolution, covering the period 2007-2018 (depending on the data availability per site).<br> The dataset is partly extracted from:</p> <ul> <li>FLUXNET2015 dataset (Pastorello et al., 2020) and the ICOS ’2018 drought initiative’ dataset (Drought 2018 Team<br> and ICOS Ecosystem Thematic Centre, 2019). Original dataset available at <a href="https://fluxnet.org/">https://fluxnet.org/</a> and <a href="https://www.icos-cp.eu/data-products/">https://www.icos-cp.eu/data-products/</a> YVR0-4898</li> <li>ERA5 product (Hersbach et al., 2020); Original dataset available at <a href="https://cds.climate.copernicus.eu/">https://cds.climate.copernicus.eu/</a></li> <li>MODIS: Original dataset available at <a href="https://modis.gsfc.nasa.gov/data/">https://modis.gsfc.nasa.gov/data/</a></li> <li>SPOT Vegetation/PROBA V: Original dataset available at <a href="https://land.copernicus.eu/global/">https://land.copernicus.eu/global/</a></li> <li>Downscaled GOME2 SIF product by Duveiller et al. (2020). Original dataset available at <a href="https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1">https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1</a></li> <li>FluxCom product ensemble (Jung et al., 2020). Original dataset available at <a href="http://fluxcom.org/">http://fluxcom.org/</a></li> </ul> <p><strong>File descriptions</strong>:<br> README.pdf : description<br> EcopropheciesMeta.txt : metadata<br> EcopropheciesDataset.txt : data</p> <p>More details and analysis of the data can be found in:<br> De Pue, J., Wieneke, Bastos, A., S., Barrios, J.M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers 2023, Agricultural and Forest Meteorology (submitted)</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.