Comparison of Convective Boundary Layer Characteristics from Aircraft and Wind Lidar Observations

Bianca Adler Karlsruhe Institute of Technology, Karlsruhe, Germany

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Olga Kiseleva Karlsruhe Institute of Technology, Karlsruhe, Germany

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Norbert Kalthoff Karlsruhe Institute of Technology, Karlsruhe, Germany

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Andreas Wieser Karlsruhe Institute of Technology, Karlsruhe, Germany

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Abstract

During the Convective Storm Initiation Project experiment, which was conducted in summer 2005 in southern England, vertical velocity in the convective boundary layer (CBL) was measured simultaneously with a research aircraft and a wind lidar. The aircraft performed horizontal flight legs approximately parallel to the prevailing wind direction and centered over the lidar. This measurement setup allows for the comparing of CBL characteristics (CBL depth zi, integral length scale lw, spectral peak wavelength λm, and vertical velocity variance σw2) from temporal (lidar) and spatial (aircraft) measurements. For this, the lidar time series are transferred into space using the mean wind. While the statistics of the aircraft data are all based on the 34-km flight legs, the averaging interval for the lidar is either 1 h or a longer period that corresponds to the 34-km leg. Although the lw and λm values from aircraft and lidar measurements are in the same range (100–200 and 500–2000 m) and agree well on the average, the correlation for individual legs is very low (R2 < 0.17). One possible explanation is the large uncertainty that arises from the transfer of the lidar time series to space. For σw2, the agreement between aircraft and lidar is better for individual legs (R2 ≥ 0.63), but the mean absolute difference in σw2 is about 2.5 times as large as the statistical error. We examine the nonstationarity and heterogeneity for the lidar and aircraft samples and can exclude these as the major sources for the large differences between lidar and aircraft data.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bianca Adler, bianca.adler@kit.edu

Abstract

During the Convective Storm Initiation Project experiment, which was conducted in summer 2005 in southern England, vertical velocity in the convective boundary layer (CBL) was measured simultaneously with a research aircraft and a wind lidar. The aircraft performed horizontal flight legs approximately parallel to the prevailing wind direction and centered over the lidar. This measurement setup allows for the comparing of CBL characteristics (CBL depth zi, integral length scale lw, spectral peak wavelength λm, and vertical velocity variance σw2) from temporal (lidar) and spatial (aircraft) measurements. For this, the lidar time series are transferred into space using the mean wind. While the statistics of the aircraft data are all based on the 34-km flight legs, the averaging interval for the lidar is either 1 h or a longer period that corresponds to the 34-km leg. Although the lw and λm values from aircraft and lidar measurements are in the same range (100–200 and 500–2000 m) and agree well on the average, the correlation for individual legs is very low (R2 < 0.17). One possible explanation is the large uncertainty that arises from the transfer of the lidar time series to space. For σw2, the agreement between aircraft and lidar is better for individual legs (R2 ≥ 0.63), but the mean absolute difference in σw2 is about 2.5 times as large as the statistical error. We examine the nonstationarity and heterogeneity for the lidar and aircraft samples and can exclude these as the major sources for the large differences between lidar and aircraft data.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bianca Adler, bianca.adler@kit.edu
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  • Attié, J.-L., and P. Durand, 2003: Conditional wavelet technique applied to aircraft data measured in the thermal internal boundary layer during sea breeze events. Bound.-Layer Meteor., 106, 359382, https://doi.org/10.1023/A:1021262406408.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Banta, R. M., and Coauthors, 2013: Observational techniques: Sampling the mountain atmosphere. Mountain Weather Research and Forecasting, F. Chow, S. De Wekker, and B. Snyder, Eds., Springer, 409–530.

    • Crossref
    • Export Citation
  • Barlow, J. F., T. M. Dunbar, E. G. Nemitz, C. R. Wood, M. W. Gallagher, F. Davies, E. O’Connor, and R. M. Harrison, 2011: Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II. Atmos. Chem. Phys., 11, 21112125, https://doi.org/10.5194/acp-11-2111-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beyrich, F., and J.-P. Leps, 2012: An operational mixing height data set from routine radiosoundings at Lindenberg: Methodology. Meteor. Z., 21, 337348, https://doi.org/10.1127/0941-2948/2012/0333.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonin, T. A., W. G. Blumberg, P. M. Klein, and P. B. Chilson, 2015: Thermodynamic and turbulence characteristics of the southern Great Plains nocturnal boundary layer under differing turbulent regimes. Bound.-Layer Meteor., 157, 401420, https://doi.org/10.1007/s10546-015-0072-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonin, T. A., and Coauthors, 2017: Evaluation of turbulence measurement techniques from a single Doppler lidar. Atmos. Meas. Tech., 10, 30213039, https://doi.org/10.5194/amt-10-3021-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Browning, K. A., and Coauthors, 2007: The Convective Storm Initiation Project. Bull. Amer. Meteor. Soc., 88, 19391955, https://doi.org/10.1175/BAMS-88-12-1939.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brugger, P., K. Träumner, and C. Jung, 2016: Evaluation of a procedure to correct spatial averaging in turbulence statistics from a Doppler lidar by comparing time series with an ultrasonic anemometer. J. Atmos. Oceanic Technol., 33, 21352144, https://doi.org/10.1175/JTECH-D-15-0136.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caramori, P., P. Schuepp, R. Desjardins, and J. MacPherson, 1994: Structural analysis of airborne flux estimates over a region. J. Climate, 7, 627640, https://doi.org/10.1175/1520-0442(1994)007<0627:SAOAFE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caughey, S. J., and S. G. Palmer, 1979: Some aspects of turbulence structure through the depth of the convective boundary layer. Quart. J. Roy. Meteor. Soc., 105, 811827, https://doi.org/10.1002/qj.49710544606.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Corsmeier, U., R. Hankers, and A. Wieser, 2001: Airborne turbulence measurements in the lower troposphere onboard the research aircraft Dornier 128-6, D-IBUF. Meteor. Z., 10, 315329, https://doi.org/10.1127/0941-2948/2001/0010-0315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Desjardins, R. L., J. I. Macpherson, P. H. Schuepp, and F. Karanja, 1989: An evaluation of aircraft flux measurements of CO2, water vapor and sensible heat. Bound.-Layer Meteor., 47, 5569, https://doi.org/10.1007/BF00122322.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Drüe, C., and G. Heinemann, 2002: Turbulence structures over the marginal ice zone under flow parallel to the ice edge: Measurements and parameterizations. Bound.-Layer Meteor., 102, 83116, https://doi.org/10.1023/A:1012776719250.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emeis, S., 2011: Surface-Based Remote Sensing of the Atmospheric Boundary Layer. Atmospheric and Oceanographic Sciences Library, Vol. 40, Springer, 174 pp.

    • Crossref
    • Export Citation
  • Foken, T., R. Leuning, S. R. Oncley, and M. Mauder, 2012: Corrections and data quality control. Eddy Covariance: A Practical Guide to Measurement and Data Analysis, M. Aubinet, T. Vesala, and D. Papale, Eds., Springer, 85–131.

    • Crossref
    • Export Citation
  • Frehlich, R., 1997: Effects of wind turbulence on coherent Doppler lidar performance. J. Atmos. Oceanic Technol., 14, 5475, https://doi.org/10.1175/1520-0426(1997)014<0054:EOWTOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frehlich, R., and L. Cornman, 2002: Estimating spatial velocity statistics with coherent Doppler lidar. J. Atmos. Oceanic Technol., 19, 355366, https://doi.org/10.1175/1520-0426-19.3.355.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fuertes, F. C., G. V. Iungo, and F. Porté-Agel, 2014: 3D turbulence measurements using three synchronous wind lidars: Validation against sonic anemometry. J. Atmos. Oceanic Technol., 31, 15491556, https://doi.org/10.1175/JTECH-D-13-00206.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grund, C. J., R. M. Banta, J. L. George, J. N. Howell, M. J. Post, R. Richter, and A. M. Weickmann, 2001: High-resolution Doppler lidar for boundary layer and cloud research. J. Atmos. Oceanic Technol., 18, 376393, https://doi.org/10.1175/1520-0426(2001)018<0376:HRDLFB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grunwald, J., N. Kalthoff, F. Fiedler, and U. Corsmeier, 1998: Applications of different flight strategies to determine areally averaged turbulent fluxes. Contrib. Atmos. Phys., 71, 83302.

    • Search Google Scholar
    • Export Citation
  • Hasel, M., C. Kottmeier, U. Corsmeier, and A. Wieser, 2005: Airborne measurements of turbulent trace gas fluxes and analysis of eddy structure in the convective boundary layer over complex terrain. Atmos. Res., 74, 381402, https://doi.org/10.1016/j.atmosres.2004.06.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Higgins, C. W., M. Froidevaux, V. Simeonov, N. Vercauteren, C. Barry, and M. B. Parlange, 2012: The effect of scale on the applicability of Taylor’s frozen turbulence hypothesis in the atmospheric boundary layer. Bound.-Layer Meteor., 143, 379391, https://doi.org/10.1007/s10546-012-9701-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kaimal, J. C., and J. J. Finnigan, 1994: Atmospheric Boundary Layer Flows: Their Structure and Measurements. Oxford University Press, 304 pp.

    • Crossref
    • Export Citation
  • Kaimal, J. C., J. C. Wyngaard, D. A. Haugen, O. R. Coté, and Y. Izumi, 1976: Turbulence structure in the convective boundary layer. J. Atmos. Sci., 33, 21522169, https://doi.org/10.1175/1520-0469(1976)033<2152:TSITCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalthoff, N., M. Fiebig-Wittmaack, C. Meißner, M. Kohler, M. Uriarte, I. Bischoff-Gauß, and E. Gonzales, 2006: The energy balance, evapo-transpiration and nocturnal dew deposition of an arid valley in the Andes. J. Arid Environ., 65, 420443, https://doi.org/10.1016/j.jaridenv.2005.08.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalthoff, N., and Coauthors, 2013: KITcube—A mobile observation platform for convection studies deployed during HyMeX. Meteor. Z., 22, 633647, https://doi.org/10.1127/0941-2948/2013/0542.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, R. D., E. A. Smith, and J. I. MacPherson, 1992: A comparison of surface sensible and latent heat fluxes from aircraft and surface measurement in FIFE 1987. J. Geophys. Res., 97, 18 44518 453, https://doi.org/10.1029/92JD01048.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kronland-Martinet, R., J. Morlet, and A. Grossmann, 1987: Analysis of sound patterns through wavelet transforms. Int. J. Pattern Recognit. Artif. Intell., 1, 273302, https://doi.org/10.1142/S0218001487000205.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lambert, D., and P. Durand, 1998: Aircraft to aircraft intercomparison during SEMAPHORE. J. Geophys. Res., 103, 25 10925 123, https://doi.org/10.1029/97JC02199.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., 1986: Probing the Atmospheric Boundary Layer. Amer. Meteor. Soc., 269 pp.

    • Crossref
    • Export Citation
  • Lenschow, D. H., and P. L. Stephens, 1980: The role of thermals in the convective boundary layer. Bound.-Layer Meteor., 19, 509532, https://doi.org/10.1007/BF00122351.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., and L. Kristensen, 1985: Uncorrelated noise in turbulence measurements. J. Atmos. Oceanic Technol., 2, 6882, https://doi.org/10.1175/1520-0426(1985)002<0068:UNITM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., and B. B. Stankov, 1986: Length scales in the convective boundary layer. J. Atmos. Sci., 43, 11981209, https://doi.org/10.1175/1520-0469(1986)043<1198:LSITCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., J. C. Wyngaard, and W. T. Pennell, 1980: Mean field and second-moment budgets in a baroclinic, convective boundary layer. J. Atmos. Sci., 37, 13131326, https://doi.org/10.1175/1520-0469(1980)037<1313:MFASMB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., J. Mann, and L. Kristensen, 1994: How long is long enough when measuring fluxes and other turbulence statistics? J. Atmos. Oceanic Technol., 11, 661673, https://doi.org/10.1175/1520-0426(1994)011<0661:HLILEW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahrt, L., 1998: Flux sampling errors for aircraft and towers. J. Atmos. Oceanic Technol., 15, 416429, https://doi.org/10.1175/1520-0426(1998)015<0416:FSEFAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mann, J., and Coauthors, 2009: Comparison of 3D turbulence measurements using three staring wind lidars and a sonic anemometer. Meteor. Z., 18, 135140, https://doi.org/10.1127/0941-2948/2009/0370.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsham, J. H., C. J. Morcrette, K. A. Browning, A. M. Blyth, D. J. Parker, U. Corsmeier, N. Kalthoff, and M. Kohler, 2007: Variable cirrus shading during CSIP IOP 5. Part I: Effects on convective initiation. Quart. J. Roy. Meteor. Soc., 133, 16431660, https://doi.org/10.1002/qj.124.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mauder, M., R. L. Desjardins, and I. MacPherson, 2007: Scale analysis of airborne flux measurements over heterogeneous terrain in a boreal ecosystem. J. Geophys. Res., 112, D13112, https://doi.org/10.1029/2006JD008133.

    • Search Google Scholar
    • Export Citation
  • Maurer, V., N. Kalthoff, A. Wieser, M. Kohler, M. Mauder, and L. Gantner, 2016: Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain. Atmos. Chem. Phys., 16, 13771400, https://doi.org/10.5194/acp-16-1377-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neff, W. D., 1990: Remote sensing of atmospheric processes over complex terrain. Atmospheric Processes over Complex Terrain, Meteor. Monogr., No. 23, Amer. Meteor. Soc., 173–228.

    • Crossref
    • Export Citation
  • Newman, J. F., T. A. Bonin, P. M. Klein, S. Wharton, and R. K. Newsom, 2016a: Testing and validation of multi-lidar scanning strategies for wind energy applications. Wind Energy, 19, 22392254, https://doi.org/10.1002/we.1978.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, J. F., P. M. Klein, S. Wharton, A. Sathe, T. A. Bonin, P. B. Chilson, and A. Muschinski, 2016b: Evaluation of three lidar scanning strategies for turbulence measurements. Atmos. Meas. Tech., 9, 19932013, https://doi.org/10.5194/amt-9-1993-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pantillon, F., A. Wieser, B. Adler, U. Corsmeier, and P. Knippertz, 2018: Overview and first results of the Wind and Storms Experiment (WASTEX): A field campaign to observe the formation of gusts using a Doppler lidar. Adv. Sci. Res., 15, 9197, https://doi.org/10.5194/asr-15-91-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pearson, G., F. Davies, and C. Collier, 2010: Remote sensing of the tropical rain forest boundary layer using pulsed Doppler lidar. Atmos. Chem. Phys., 10, 58915901, https://doi.org/10.5194/acp-10-5891-2010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Powell, D. C., and C. E. Elderkin, 1974: An investigation of the application of Taylor’s hypothesis to atmospheric boundary layer turbulence. J. Atmos. Sci., 31, 9901002, https://doi.org/10.1175/1520-0469(1974)031<0990:AIOTAO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seibert, P., F. Beyrich, S.-E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier, 2000: Review and intercomparison of operational methods for the determination of the mixing height. Atmos. Environ., 34, 10011027, https://doi.org/10.1016/S1352-2310(99)00349-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shuttleworth, W. J., 1988: Macrohydrology—The new challenge for process hydrology. J. Hydrol., 100, 3156, https://doi.org/10.1016/0022-1694(88)90180-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

    • Crossref
    • Export Citation
  • Tonttila, J., E. J. O’Connor, A. Hellsten, A. Hirsikko, C. O’Dowd, H. Järvinen, and P. Räisänen, 2015: Turbulent structure and scaling of the inertial subrange in a stratocumulus-topped boundary layer observed by a Doppler lidar. Atmos. Chem. Phys., 15, 58735885, https://doi.org/10.5194/acp-15-5873-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Torrence, C., and G. P. Compo, 1998: A practical guide to wavelet analysis. Bull. Amer. Meteor. Soc., 79, 6178, https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Träumner, K., C. Kottmeier, U. Corsmeier, and A. Wieser, 2011: Convective boundary-layer entrainment: Short review and progress using Doppler lidar. Bound.-Layer Meteor., 141, 369391, https://doi.org/10.1007/s10546-011-9657-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Träumner, K., T. Damian, C. Stawiarski, and A. Wieser, 2015: Turbulent structures and coherence in the atmospheric surface layer. Bound.-Layer Meteor., 154, 125, https://doi.org/10.1007/s10546-014-9967-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Treviño, G., and E. Andreas, 1996: On wavelet analysis of nonstationary turbulence. Bound.-Layer Meteor., 81, 271288, https://doi.org/10.1007/BF02430332.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Web of Science, 2018a: Wind lidar. Web of Science, accessed 17 December 2018, http://apps.webofknowledge.com/.

  • Web of Science, 2018b: Doppler lidar. Web of Science, accessed 17 December 2018, http://apps.webofknowledge.com/.

  • Wyngaard, J. C., 1973: On surface-layer turbulence. Workshop on Micrometeorology, D. A. Haugen, Ed., Amer. Meteor. Soc., 101–149.

  • Young, G., 1988: Turbulence structure in the convective boundary layer. Part I: Variability of normalized turbulence statistics. J. Atmos. Sci., 45, 719726, https://doi.org/10.1175/1520-0469(1988)045<0719:TSOTCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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