Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-885-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-885-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Feb 2022
Data description paper |
| 24 Feb 2022
| 24 Feb 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
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
Anita Freundorfer
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Antonia Fritz
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
now at: Institute for Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
Johann Schneider
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Johannes Olesch
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Wolfgang Babel
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
Christoph K. Thomas
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
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Cited articles
Abraham, C. and Monahan, A. H.: Spatial Dependence of Stably Stratified
Nocturnal Boundary-Layer Regimes in Complex Terrain, Bound.-Lay.
Meteorol., 177, 19–47, https://doi.org/10.1007/s10546-020-00532-x, 2020. a, b, c, d
Acevedo, O. C., Costa, F. D., Oliveira, P. E., Puhales, F. S., Degrazia, G. A.,
and Roberti, D. R.: The influence of submeso processes on stable boundary
layer similarity relationships, J. Atmos. Sci., 71,
207–225, https://doi.org/10.1175/JAS-D-13-0131.1, 2014. a, b
Brantley, S. L., Goldhaber, M. B., and Ragnarsdottir, K. V.: Crossing disciplines and scales to understand the
critical zone, Elements, 3, 307–314, https://doi.org/10.2113/gselements.3.5.307,
2007. a
Browning, K. A. and Wexler, R.: The Determination of Kinematic Properties of a
Wind Field Using Doppler Radar, J. Appl. Meteorol., 7, 105–113,
https://doi.org/10.1175/1520-0450(1968)007<0105:TDOKPO>2.0.CO;2, 1968. a
Cava, D., Mortarini, L., Giostra, U., Richiardone, R., and Anfossi, D.: A
wavelet analysis of low-wind-speed submeso motions in a nocturnal boundary
layer, Q. J. Roy. Meteorol. Soc., 143, 661–669,
https://doi.org/10.1002/qj.2954, 2017. a, b
Cava, D., Mortarini, L., Anfossi, D., and Giostra, U.: Interaction of Submeso Motions in the Antarctic Stable Boundary Layer, Bound.-Lay. Meteorol., 171, 151–173, https://doi.org/10.1007/s10546-019-00426-7, 2019. a, b, c
des Tombe, B., Schilperoort, B., and Bakker, M.: EStimation of Temperature and
Associated Uncertainty from Fiber-Optic Ramen-Spectrum Distributed
Temperature Sensing, Sensors, 20, 2235–2256, https://doi.org/10.3390/s20082235, 2020. a, b, c
Euser, T., Luxemburg, W. M. J., Everson, C. S., Mengistu, M. G., Clulow, A. D., and Bastiaanssen, W. G. M.: A new method to measure Bowen ratios using high-resolution vertical dry and wet bulb temperature profiles, Hydrol. Earth Syst. Sci., 18, 2021–2032, https://doi.org/10.5194/hess-18-2021-2014, 2014. a
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The shuttle radar topography mission, Rev. Geophys., 45, 1–33,
https://doi.org/10.1029/2005RG000183, 2007. a
Freundorfer, A., Lapo, K., Schneider, J., and Thomas, C. K.: Distributed sensing of wind direction using fiber-optic cables, J. Atmos. Ocean. Technol., 38, 1871–1883, https://doi.org/10.1175/JTECH-D-21-0019.1, 2021. a, b, c
Higgins, C., Wing, M., Kelley, J., Sayde, C., Burnett, J., and Holmes, H.: A high resolution measurement of the morning ABL transition using distributed temperature sensing and an unmanned aircraft system, Environ. Fluid Mech., 18, 683–693, https://doi.org/10.1007/s10652-017-9569-1, 2018. a
Kang, Y., Belušić, D., and Smith-Miles, K.: Classes of structures in the stable atmospheric boundary layer, Q. J. Roy. Meteor. Soc., 141, 2057–2069, https://doi.org/10.1002/qj.2501, 2015. a
Keller, C. A., Huwald, H., Vollmer, M. K., Wenger, A., Hill, M., Parlange, M. B., and Reimann, S.: Fiber optic distributed temperature sensing for the determination of the nocturnal atmospheric boundary layer height, Atmos. Meas. Tech., 4, 143–149, https://doi.org/10.5194/amt-4-143-2011, 2011. a
Kral, S. T., Reuder, J., Vihma, T., Suomi, I., Haualand, K. F., Urbancic,
G. H., Greene, B. R., Steeneveld, G.-J., Lorenz, T., Maronga, B., Jonassen,
M. O., Ajosenpää, H., Båserud, L., Chilson, P. B., Holtslag,
A. A. M., Jenkins, A. D., Kouznetsov, R., Mayer, S., Pillar-Little, E. A.,
Rautenberg, A., Schwenkel, J., Seidl, A. W., and Wrenger, B.: The Innovative
Strategies for Observations in the Arctic Atmospheric Boundary Layer Project
(ISOBAR) – Unique fine-scale observations under stable and very stable
conditions, B. Am. Meteorol. Soc., 102, E218–E243,
https://doi.org/10.1175/bams-d-19-0212.1, 2020. a
Lang, F., Belušic, D., and Siems, S.: Observations of wind-direction
variability in the nocturnal boundary layer, Bound.-Lay. Meterol., 166, 51–68, https://doi.org/10.1007/s10546-017-0296-4, 2018. a
Lapo, K.: Isolated submeso motion in the very stable boundary layer observed by Distributed Temperature Sensing, TIB [video], https://doi.org/10.5446/53539, 2021. a
Lapo, K. and Freundorfer, A.: klapo/pyfocs v0.5, Zenodo [code], https://doi.org/10.5281/zenodo.4292491, 2020. a, b, c, d
Lenschow, D. H., Wulfmeyer, V., and Senff, C.: Measuring Second- through
Fourth-Order Moments in Noisy Data, J. Atmos. Ocean. Tech., 17, 1330–1347,
https://doi.org/10.1175/1520-0426(2000)017<1330:MSTFOM>2.0.CO;2, 2000. a, b, c
Mahrt, L.: Mesoscale wind direction shifts in the stable boundary-layer,
Tellus, 60A, 700–705, https://doi.org/10.1111/j.1600-0870.2008.00324.x, 2008. a
Mahrt, L.: Variability and Maintenance of Turbulence in the Very Stable
Boundary Layer, Bound.-Lay. Meteorol., 135, 1–18,
https://doi.org/10.1007/s10546-009-9463-6, 2010. a
Mahrt, L.: Lee Mixing and Nocturnal Structure over Gentle Topography, J. Atmos. Sci., 74, 1989–1999, https://doi.org/10.1175/JAS-D-16-0338.1, 2017. a
Mahrt, L. and Thomas, C. K.: Surface Stress with Non-stationary Weak Winds and Stable Stratification, Bound.-Lay. Meteorol., 159, 3–21,
https://doi.org/10.1007/s10546-015-0111-z, 2016. a, b, c
Mahrt, L., Thomas, C. K., and Prueger, J.: Space–time structure of mesoscale
motions in the stable, Q. J. Roy. Meteor. Soc., 135, 67–75, https://doi.org/10.1002/qj.348, 2009. a, b, c, d
Mahrt, L., Pfister, L., and Thomas, C. K.: Small-Scale Variability in the
Nocturnal Boundary Layer, Bound.-Lay. Meteorol., 174, 81–98,
https://doi.org/10.1007/s10546-019-00476-x, 2020. a, b
Mortarini, L., Cava, D., Giostra, U., Denardin Costa, F., Degrazia, G.,
Anfossi, D., and Acevedo, O.: Horizontal meandering as a distinctive feature of the stable boundary layer, J. Atmos. Sci., 76,
3029–3046, https://doi.org/10.1175/JAS-D-18-0280.1, 2019. a, b
Peltola, O., Lapo, K., Martinkauppi, I., O'Connor, E., Thomas, C. K., and Vesala, T.: Suitability of fibre-optic distributed temperature sensing for revealing mixing processes and higher-order moments at the forest–air interface, Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, 2021. a, b, c, d
Petenko, I., Argentini, S., Casasanta, G., Genthon, C., and Kallistratova, M.:
Stable Surface-Based Turbulent Layer During the Polar Winter at Dome C,
Antarctica: Sodar and In Situ Observations, Bound.-Lay. Meteorol., 171,
101–128, https://doi.org/10.1007/s10546-018-0419-6, 2019. a
Petrides, A. C., Huff, J., Arik, A., Giesen, N. V. D., Kennedy, A. M., Thomas,
C. K., and Selker, J. S.: Shade estimation over streams using distributed
temperature sensing, Water Resour. Res., 47, 2–5,
https://doi.org/10.1029/2010WR009482, 2011. a
Pfister, L., Lapo, K., Sayde, C., Selker, J., Mahrt, L., and Thomas, C. K.:
Classifying the nocturnal atmospheric boundary layer into temperature and
flow regimes, Q. J. Roy. Meteor. Soc., 145,
1515–1534, https://doi.org/10.1002/qj.3508, 2019. a, b, c, d
Pillar-Little, E. A., Greene, B. R., Lappin, F. M., Bell, T. M., Segales, A. R., de Azevedo, G. B. H., Doyle, W., Kanneganti, S. T., Tripp, D. D., and Chilson, P. B.: Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO, using the CopterSonde 2 remotely piloted aircraft system in support of the LAPSE-RATE field campaign, Earth Syst. Sci. Data, 13, 269–280, https://doi.org/10.5194/essd-13-269-2021, 2021. a
Schilperoort, B., Coenders-Gerrits, M., Luxemburg, W., Jiménez Rodríguez, C., Cisneros Vaca, C., and Savenije, H.: Technical note: Using distributed temperature sensing for Bowen ratio evaporation measurements, Hydrol. Earth Syst. Sci., 22, 819–830, https://doi.org/10.5194/hess-22-819-2018, 2018. a
Selker, J. S., Thévenaz, L., Huwald, H., Mallet, A., Luxemburg, W.,
Giesen, N. V. D., Stejskal, M., Zeman, J., Westhoff, M., and Parlange, M. B.:
Distributed fiber-optic temperature sensing for hydrologic systems, Water Resour. Res., 42, 1–8, https://doi.org/10.1029/2006WR005326, 2006. a, b
Sigmund, A., Pfister, L., Sayde, C., and Thomas, C. K.: Quantitative analysis of the radiation error for aerial coiled-fiber-optic distributed temperature sensing deployments using reinforcing fabric as support structure, Atmos. Meas. Tech., 10, 2149–2162, https://doi.org/10.5194/amt-10-2149-2017, 2017. a
Stull, R. B.: An Introduction to Bound.-Lay. Meteorol., 1st Edn., Springer Netherlands, Dordrecht, The Netherlands, xiii, 666, ISBN9027727686, 1988. a
Sun, J., Mahrt, L., Banta, R. M., and Pichugina, Y. L.: Turbulence Regimes and
Turbulence Intermittency in the Stable Boundary Layer during CASES-99,
J. Atmos. Sci., 69, 338–351, https://doi.org/10.1175/JAS-D-11-082.1, 2012. a, b, c
Sun, J., Nappo, C. J., Mahrt, L., Belušic, D., Grisogono, B., Stauffer,
D. R., Pulido, M., Staquet, C., Jiang, Q., Pouquet, A., Yagüe, C.,
Galperin, B., Smith, R. B., Finnigan, J. J., Mayor, S. D., Svensson, G.,
Grachev, A. A., and Neff, W. D.: Review of wave-turbulence interactions in
the stable atmospheric boundary layer, Rev. Geophys., 53, 956–993,
https://doi.org/10.1002/2015RG000487, 2015. a, b, c, d, e, f
Sun, J., Takle, E. S., and Acevedo, O. C.: Understanding Physical Processes
Represented by the Monin-Obukhov Bulk Formula for Momentum Transfer,
Bound.-Lay. Meteorol., 177, 69–95, https://doi.org/10.1007/s10546-020-00546-5, 2020. a, b
Thomas, C. K.: Variability of Sub-Canopy Flow, Temperature, and Horizontal
Advection in Moderately Complex Terrain, Bound.-Lay. Meteorol., 139,
61–81, https://doi.org/10.1007/s10546-010-9578-9, 2011. a, b
Thomas, C. K. and Selker, J.: Optical fiber-based distributed sensing methods, chap. 20, in: Springer Handbook of Atmospheric Measurements, edited by: Foken, T., 609–631, Springer Handbooks, Springer Nature Switzerland AG, https://doi.org/10.1007/978-3-030-52171-4_20, 2021. a, b, c, d
Thomas, C. K., Mayer, J. C., Meixner, F. X., and Foken, T.: Analysis of
low-frequency turbulence above tall vegetation using a Doppler sodar,
Bound.-Lay. Meteorol., 119, 563–587, https://doi.org/10.1007/s10546-005-9038-0,
2006. a
Thomas, C. K., Law, B. E., Irvine, J., Martin, J. G., Pettijohn, J. C., and
Davis, K. J.: Seasonal hydrology explains interannual and seasonal variation
in carbon and water exchange in a semiarid mature ponderosa pine forest in
central Oregon, J. Geophys. Res., 114, G04006,
https://doi.org/10.1029/2009JG001010, 2009. a
Thomas, C. K., Kennedy, A. M., Selker, J. S., Moretti, A., Schroth, M. H.,
Smoot, A. R., Tufillaro, N. B., and Zeeman, M. J.: High-resolution
fibre-optic temperature sensing: A new tool to study the two-dimensional
structure of atmospheric surface layer flow, Bound.-Lay. Meteorol.,
142, 177–192, https://doi.org/10.1007/s10546-011-9672-7, 2012. a, b, c, d, e, f, g, h
Tyler, S. W., Selker, J. S., Hausner, M. B., Hatch, C. E., Torgersen, T.,
Thodal, C. E., and Schladow, S. G.: Environmental temperature sensing using
Raman spectra DTS fiber-optic methods, Water Resour. Res., 45, 1–11,
https://doi.org/10.1029/2008WR007052, 2009. a, b
van de Giesen, N., Steele-Dunne, S. C., Jansen, J., Hoes, O., Hausner, M. B.,
Tyler, S., and Selker, J.: Double-ended calibration of fiber-optic raman
spectra distributed temperature sensing data, Sensors, Switzerland, 12,
5471–5485, https://doi.org/10.3390/s120505471, 2012. a, b, c, d
Van de Wiel, B. J. H., Vignon, E., Baas, P., van Hooijdonk, I. G., Van der
Linden, Steven, J. A., van Hooft, J. A., Bosveld, F. C., de Roode, S. R.,
Moene, A. F., and Genthon, C.: Regime Transitions in Near-Surface
Temperature Inversions: A Conceptual Model, J. Atmos. Sci., 74, 1057–1073, https://doi.org/10.1175/JAS-D-16-0180.1, 2017. a, b
van Ramshorst, J. G. V., Coenders-Gerrits, M., Schilperoort, B., van de Wiel, B. J. H., Izett, J. G., Selker, J. S., Higgins, C. W., Savenije, H. H. G., and van de Giesen, N. C.: Revisiting wind speed measurements using actively heated fiber optics: a wind tunnel study, Atmos. Meas. Tech., 13, 5423–5439, https://doi.org/10.5194/amt-13-5423-2020, 2020.
a, b, c, d, e
Wilczak, J. M., Oncley, S. P., and Stage, S. A.: Sonic anemometer tilt
correction algorithms, Bound.-Lay. Meteorol., 99, 127–150,
https://doi.org/10.1023/A:1018966204465, 2001. a
Zeller, M.-L., Huss, J.-M., Pfister, L., Lapo, K. E., Littmann, D., Schneider, J., Schulz, A., and Thomas, C. K.: The NY-Ålesund TurbulencE Fiber Optic eXperiment (NYTEFOX): investigating the Arctic boundary layer, Svalbard, Earth Syst. Sci. Data, 13, 3439–3452, https://doi.org/10.5194/essd-13-3439-2021, 2021. a, b
Short summary
The layer of air near the surface is poorly understood during conditions with weak winds. Further, it is even difficult to observe. In this experiment we used distributed temperature sensing to observe air temperature and wind speed at thousands of points simultaneously every couple of seconds. This incredibly rich data set can be used to examine and understand what drives the mixing between the atmosphere and surface during these weak-wind periods.
The layer of air near the surface is poorly understood during conditions with weak winds....
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