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i-Box (Innsbruck Box) – processed eddy-covariance data: 10-min statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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. </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

i-Box (Innsbruck Box) – processed eddy-covariance data: 3-min statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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. </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

i-Box (Innsbruck Box) – processed eddy-covariance data: 5-min statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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. </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

i-Box (Innsbruck Box) – processed eddy-covariance data: 30-min statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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 </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

i-Box (Innsbruck Box) – processed eddy-covariance data: 15-min statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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. </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

i-Box (Innsbruck Box) – processed eddy-covariance data: 30-s statistics

Abstract 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).   Data description Station locations 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. <ul> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> <li> 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) </li> </ul> Further information about station locations can be found in Rotach et al. (2017) and Lehner et al. (2021). Temporal coverage 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. Instrumentation 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). <ul> <li> 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 </li> <li> SF8: CSAT3 at 6.1, CSAT3 and KH20 (until September 2020) or Irgason (since September 2020) at 11.2 m </li> <li> SF1: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 6.8 m </li> <li> NF10: CSAT3 and KH20 (until June 2020) or Irgason (since June 2020) at 5.7 m </li> <li> NF27: CSAT3 at 1.5 (since September 2017), CSAT3 and KH20 (until November 2016) or Irgason (since September 2017) 6.8 m </li> </ul> Further information about the instrumentation can be found in Rotach et al. (2017), Lehner et al. (2021), and in the ACINN database: <ul> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> <li> 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> </li> </ul> Data processing 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). 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-1 for the horizontal wind components, 10 m s-1 for the vertical wind velocity, and 50 g m3 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. Quality flags are based on the criteria described in Stiperski and Rotach (2016): <ul> <li> -1: More than 10% of the raw data within the averaging period are replaced during the quality control. </li> <li> 0: More than 90% of the raw data fulfill the quality control criteria. </li> <li> 1: In addition to fulfilling the quality control criteria, the skewness is within the range -2–2 and the kurtosis is less than 8. </li> <li> 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) </li> </ul> Data files <ul> <li> i-Box_sites.pdf contains a map of the i-Box stations. </li> <li> list_variables.pdf contains a list of variable names with a short description. </li> <li> 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. </li> </ul> Acknowledgments 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. References 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 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 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 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 Moore CJ (1986) Frequency response corrections for eddy correlation systems. Boundary-Layer Meteorol 37:17–35, DOI 10.1007/BF00122754 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 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 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. 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 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 Wyngaard, J.C. (1973). On surface layer turbulence. In D.A. Haugen (Ed.), Workshop on Micrometeorology, American Meteorological Society, pp. 101–150.

opencc-by-4.0Apr 2022View details →

Weak s-process

Collection of certified trajectories, covering a wide range of weak s-process conditions. Every trajectory comes with the selected initial abundances and other key information, such as the reference of the publication, the stellar region from where it was extracted, the mass of the star and its metallicity. FREQUENTLY ASKED QUESTIONS Q: Can I use these trajectories for nuclear sensitivity studies and/or to compute ejected stellar yields? A: These trajectories can be used for nuclear sensitivity studies, but they cannot be used to compute stellar yields.

Dataset for Paper: A System for Processing and Recognition of Greek Byzantine and Post-Byzantine Documents

Dataset for the paper: "A System for Processing and Recognition of Greek Byzantine and Post-Byzantine Documents", P. Kaddas, K. Palaiologos, B. Gatos, V. Katsouros, K. Christopoulou, 17th International Conference on Document Analysis and Recognition (ICDAR), San Jose, California, USA The dataset consists of 57 pages from the third edition of the Greek New Testament published by Robert Estienne (1503–1559), who was appointed “Royal Typographer” by the King of France François I (1494–1547). Robert Estienne produced this edition in 1550 using the grecs du roi typeface, produced by Claude Garamont on the basis of the Greek minuscule style of the calligrapher Angelos Vergikios (1505–1569) from Crete, who active copying Greek manuscripts in Venice and France. The dataset consists of 2045 cropped text line images in .png format with their corresponding OCR in .txt format, where 1431 used for training, 204 for validation and 410 for test. Initial images acquired from: https://bibles-online.net/flippingbook/1550/

openother-openMay 2023View details →

[SZESLR] Semi-automated Systematic Literature Review (SLR) Design and P-graph (Process Graph Theory) SLR Database

(c) Széchenyi István University and Artificial Intelligence National Laboratory (MILAB) A proposed semi-automated Systematic Literature Review (SLR) design has been deployed to conduct an exhaustive literature review on contributions concerning applications of the P-graph framework as a case study. The P-graph framework (<a href="https://p-graph.org/">https://p-graph.org</a>) was initially conceived for solving problems related to the synthesis of chemical processes; in particular, the framework has been useful for developing sustainable and resilient systems. The current contribution includes the P-graph SLR database itself, and additionally, the Python scripts used to generate such results. The case study has been selected in view of the authors’ familiarity with the P-graph framework, and because they maintain a manually-collected database of works on the subject. The contributions concerning the framework are easily distinguishable from others involving similar methodologies. It was observed that the implementation of the proposed SLR design extended prior review papers on the P-graph framework and provided additional information on authors and institutions devoted to research on this subject. Generally, it is expected that the dataset will assist researchers, scholars, and practitioners concerned with industrial sustainability in streamlining their literature reviews, thus accelerating the acquisition of pertinent publications that could advance and enrich their own research works on such a subject. Moreover, it is expected that, with proper adaptation, the proposed semi-automated SLR design can be applied to conduct literature reviews in other scientific fields whose results can be validated against existing reviews when available. The normalized P-graph database hereby presented thus can be used as a source of validated information for researchers. The P-graph database was uploaded in various file formats that support database management software (e.g. Zotero .RIS) as well as an "EasyHandle" MS Office (.XLSX) file.

opencc-byMay 2023View details →

Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Intermediary Result

The intermediary result of the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".

opencc-byMay 2023View details →

Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Category Confusion Matrix

Resulting category confusion matrix for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".

opencc-byMay 2023View details →

Evaluation of a simple score-based Natural Language Processing (NLP) algorithm: Result

The result for the experiment "Evaluation of a simple score-based Natural Language Processing (NLP) algorithm".

Dataset for surface waves height prediction through the video and image processing

Image-based study of surface waves is a long lasting topic in ocean science and remote sensing. We believe that modern computers and new programming techniques can make a break-through in this area.   This dataset provides some video files of surface wind waves of two kinds. First is a video snapshot of a quite large area. Second one is a zoom-in video of a spar-buoy (a stick) located in this field. According to the zoom-in video we may see the actual height of the wave in this particular point. This should be treated as a reliable data and so it can be used to calibrate the brightness field. I.e. the users of this dataset are welcome to train their model to obtain the height of the wave out of its brightness on the zoom-out large-area videos.   All video files are readable by a conventional software. Records were taken at mild wind conditions in a gulf (fjord or skerry) of the Ladoga Lake. See "readme.pdf" for the details

Fifradina dataset for radiative thermal neutron-capture processes in cryogenic detectors (CRAB)

The emission of \(\gamma\)-rays after a neutron capture in a cryogenic detector can generate mono-energetic nuclear recoils in the sub-keV regime, of direct interest for the calibration of Dark Matter and Coherent Elastic Neutrino Nucleus Scattering experiments. Accurate predictions of the nuclear recoil spectra induced by neutron captures require taking into account the interplay between the development in time of the de-excitation γ-cascade of the target nucleus and that of the associated atomic collisions in matter. Detailed simulations coupling the FIFRELIN code for the description of the γ-cascades and the Iradina code for the modelling of the fast atomic movements in matter have been described in G. Soum-Sidikov and al. (CRAB collaboration), Study of collision and γ-cascade times following neutron-capture processes in cryogenic detectorset al. 2023. doi :10.48550/arXiv.2305.10139. URL<a href="http://https://doi.org/ 10.48550/arXiv.2305.10139"> https://doi.org/ 10.48550/arXiv.2305.10139</a> This dataset acts as supplemental material to this article. It provides detailed nuclear de-excitation cascades with associated total recoil energies for: <ul> <li>Al (n, \(\gamma\)) in Al2O3</li> <li>Si (n, \(\gamma\)) in Si</li> <li>Ge (n, \(\gamma\)) in Ge</li> <li>W (n, \(\gamma\)) in CaWO4</li> </ul>

opencc-zeroMay 2023View details →

dryad40/100

Data for: Chronic exposure to odors at naturally occurring concentrations triggers limited plasticity in early stages of Drosophila olfactory processing

In insects and mammals, olfactory experience in early life alters olfactory behavior and function in later life. In the vinegar fly Drosophila, flies chronically exposed to a high concentration of a monomolecular odor exhibit reduced behavioral aversion to the familiar odor when it is re-encountered. This change in olfactory behavior has been attributed to selective decreases in the sensitivity of second-order olfactory projection neurons (PNs) in the antennal lobe that respond to the overrepresented odor. However, since odorant compounds do not occur at similarly high concentrations in natural sources, the role of odor experience-dependent plasticity in natural environments is unclear. Here, we investigated olfactory plasticity in the antennal lobe of flies chronically exposed to odors at concentrations that are typically encountered in natural odor sources. These stimuli were chosen to each strongly and selectively excite a single class of primary olfactory receptor neuron (ORN), thus facilitating a rigorous assessment of the selectivity of olfactory plasticity for PNs directly excited by overrepresented stimuli. Unexpectedly, we found that chronic exposure to three such odors did not result in decreased PN sensitivity but rather mildly increased responses to weak stimuli in most PN types. Odor-evoked PN activity in response to stronger stimuli was mostly unaffected by odor experience. When present, plasticity was observed broadly in multiple PN types and thus was not selective for PNs receiving direct input from the chronically active ORNs. We further investigated the DL5 olfactory coding channel and found that chronic odor-mediated excitation of its input ORNs did not affect PN intrinsic properties, local inhibitory innervation, ORN responses, or ORN-PN synaptic strength; however, broad-acting lateral excitation evoked by some odors was increased. These results show that PN odor coding is only mildly affected by strong persistent activation of a single olfactory input, highlighting the stability of early stages of insect olfactory processing to significant perturbations in the sensory environment.

Input and output data for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 4)

The dataset contains: i. the meteorological forcing, hydrological boundary condition and chlorophyll-a files used as an input ii. the model output and skill produced for Experiment B2 (Deliverable 3.3 - Data assimilation in process-based models for algae bloom forecasting - Section 4)

opencc-by-4.0Mar 2022View details →

Main s-process

Collection of certified trajectories, covering a wide range of main s-process conditions. Every trajectory comes with the selected initial abundances and other key information, such as the reference of the publication, the stellar region from where it was extracted, the mass of the star and its metallicity. FREQUENTLY ASKED QUESTIONS Q1: What is the difference between  trajectory_C13pocket.dat and trajectory_TP.dat in the Cescutti_2018 folder? A1: trajectory_TP.dat was extracted from the He-intershell (the He and C-rich region between the H-rich convective envelope and the CO core), while trajectory_C13pocket.dat was extracted from the region where the 13C-pocket formed, just below the deepest penetration point of the convective envelope during the third dredge-up following the thermal-pulse. Moreover, trajectory_TP.dat was extracted during the helium-flash-driven thermal pulse, while trajectory_C13pocket.dat was extracted during the radiative burning of the 13C-pocket. Q2: Can I use these trajectories for nuclear sensitivity studies and/or to compute ejected stellar yields? A2: These trajectories can be used for nuclear sensitivity studies, but they cannot be used to compute stellar yields.

Raw data and analysis code for "Higher-order Process Matrix Tomography of a passively-stable Quantum SWITCH"

This folder contains the raw data and analysis coded need to reproduce all of the major results in the manuscript "Higher-order Process Matrix Tomography of a passively-stable Quantum SWITCH".

Processed data and scripts supporting the manuscript "Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma"

This submission contains the compiled count table, processed R objects and various scripts and output files accompanying our manuscript "Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma" (Nature Communications, 2023, https://doi.org/10.1038/s41467-023-38886-8)