Articles | Volume 15, issue 13
https://doi.org/10.5194/amt-15-4023-2022
© 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/amt-15-4023-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Instabilities, Dynamics, and Energetics accompanying Atmospheric Layering (IDEAL): high-resolution in situ observations and modeling in and above the nocturnal boundary layer
Smead Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA
Dale Lawrence
CORRESPONDING AUTHOR
Smead Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA
David Fritts
CORRESPONDING AUTHOR
GATS, Boulder, CO, USA
Ling Wang
CORRESPONDING AUTHOR
GATS, Boulder, CO, USA
Thomas Lund
CORRESPONDING AUTHOR
GATS, Boulder, CO, USA
William Brown
CORRESPONDING AUTHOR
Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Dragan Zajic
CORRESPONDING AUTHOR
Meteorology Division, Dugway Proving Ground, Dugway, UT, USA
Lakshmi Kantha
CORRESPONDING AUTHOR
Smead Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA
Related authors
Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Abhiram Doddi, Tyler Mixa, and Masanori Yabuki
Atmos. Meas. Tech., 16, 3561–3580, https://doi.org/10.5194/amt-16-3561-2023, https://doi.org/10.5194/amt-16-3561-2023, 2023
Short summary
Short summary
Doppler radars can be used to estimate turbulence kinetic energy dissipation rates in the atmosphere. The performance of various models is evaluated from comparisons between UHF wind profiler and in situ measurements with UAVs. For the first time, we assess a model supposed to be valid for weak stratification or strong shear conditions. This model provides better agreements with in situ measurements than the classical model based on the hypothesis of a stable stratification.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
Short summary
Short summary
This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Jonathan Hamilton, Gijs de Boer, Abhiram Doddi, and Dale A. Lawrence
Atmos. Meas. Tech., 15, 6789–6806, https://doi.org/10.5194/amt-15-6789-2022, https://doi.org/10.5194/amt-15-6789-2022, 2022
Short summary
Short summary
The DataHawk2 is a small, low-cost, rugged, uncrewed aircraft system (UAS) used to observe the thermodynamic and turbulence structures of the lower atmosphere, supporting an advanced understanding of the physical processes that regulate weather and climate. This paper discusses the development, performance, and sensing capabilities of the DataHawk2 using data collected during several recent field deployments.
Hubert Luce, Lakshmi Kantha, and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 16, 5091–5101, https://doi.org/10.5194/amt-16-5091-2023, https://doi.org/10.5194/amt-16-5091-2023, 2023
Short summary
Short summary
The potential ability of clear air radars to measure turbulence kinetic energy (TKE) dissipation rate ε in the atmosphere is a major asset of these instruments because of their continuous measurements. In the present work, we successfully tested the relevance of a model relating ε to the width of the Doppler spectrum peak and wind shear for shear-generated turbulence and we provide a physical interpretation of an empirical model in this context.
Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Abhiram Doddi, Tyler Mixa, and Masanori Yabuki
Atmos. Meas. Tech., 16, 3561–3580, https://doi.org/10.5194/amt-16-3561-2023, https://doi.org/10.5194/amt-16-3561-2023, 2023
Short summary
Short summary
Doppler radars can be used to estimate turbulence kinetic energy dissipation rates in the atmosphere. The performance of various models is evaluated from comparisons between UHF wind profiler and in situ measurements with UAVs. For the first time, we assess a model supposed to be valid for weak stratification or strong shear conditions. This model provides better agreements with in situ measurements than the classical model based on the hypothesis of a stable stratification.
Ulrike Egerer, John J. Cassano, Matthew D. Shupe, Gijs de Boer, Dale Lawrence, Abhiram Doddi, Holger Siebert, Gina Jozef, Radiance Calmer, Jonathan Hamilton, Christian Pilz, and Michael Lonardi
Atmos. Meas. Tech., 16, 2297–2317, https://doi.org/10.5194/amt-16-2297-2023, https://doi.org/10.5194/amt-16-2297-2023, 2023
Short summary
Short summary
This paper describes how measurements from a small uncrewed aircraft system can be used to estimate the vertical turbulent heat energy exchange between different layers in the atmosphere. This is particularly important for the atmosphere in the Arctic, as turbulent exchange in this region is often suppressed but is still important to understand how the atmosphere interacts with sea ice. We present three case studies from the MOSAiC field campaign in Arctic sea ice in 2020.
Benjamin Witschas, Sonja Gisinger, Stephan Rahm, Andreas Dörnbrack, David C. Fritts, and Markus Rapp
Atmos. Meas. Tech., 16, 1087–1101, https://doi.org/10.5194/amt-16-1087-2023, https://doi.org/10.5194/amt-16-1087-2023, 2023
Short summary
Short summary
In this paper, a novel scan technique is applied to an airborne coherent Doppler wind lidar, enabling us to measure the vertical wind speed and the horizontal wind speed along flight direction simultaneously with a horizontal resolution of about 800 m and a vertical resolution of 100 m. The performed observations are valuable for gravity wave characterization as they allow us to calculate the leg-averaged momentum flux profile and, with that, the propagation direction of excited gravity waves.
Natalie Kaifler, Bernd Kaifler, Markus Rapp, and David C. Fritts
Atmos. Chem. Phys., 23, 949–961, https://doi.org/10.5194/acp-23-949-2023, https://doi.org/10.5194/acp-23-949-2023, 2023
Short summary
Short summary
We used a lidar to measure polar mesospheric clouds from a balloon floating in the upper stratosphere. The thin-layered ice clouds at 83 km altitude are perturbed by waves. The high-resolution lidar soundings reveal small-scale structures induced by the breaking of those waves. We study these patterns and find that they occur very often. We show their morphology and discuss associated dynamical physical processes, which help to interpret case studies and to guide modelling.
Jonathan Hamilton, Gijs de Boer, Abhiram Doddi, and Dale A. Lawrence
Atmos. Meas. Tech., 15, 6789–6806, https://doi.org/10.5194/amt-15-6789-2022, https://doi.org/10.5194/amt-15-6789-2022, 2022
Short summary
Short summary
The DataHawk2 is a small, low-cost, rugged, uncrewed aircraft system (UAS) used to observe the thermodynamic and turbulence structures of the lower atmosphere, supporting an advanced understanding of the physical processes that regulate weather and climate. This paper discusses the development, performance, and sensing capabilities of the DataHawk2 using data collected during several recent field deployments.
Natalie Kaifler, Bernd Kaifler, Markus Rapp, and David C. Fritts
Earth Syst. Sci. Data, 14, 4923–4934, https://doi.org/10.5194/essd-14-4923-2022, https://doi.org/10.5194/essd-14-4923-2022, 2022
Short summary
Short summary
We measured polar mesospheric clouds (PMCs), our Earth’s highest clouds at the edge of space, with a Rayleigh lidar from a stratospheric balloon. We describe how we derive the cloud’s brightness and discuss the stability of the gondola pointing and the sensitivity of our measurements. We present our high-resolution PMC dataset that is used to study dynamical processes in the upper mesosphere, e.g. regarding gravity waves, mesospheric bores, vortex rings, and Kelvin–Helmholtz instabilities.
Neil P. Hindley, Nicholas J. Mitchell, Neil Cobbett, Anne K. Smith, Dave C. Fritts, Diego Janches, Corwin J. Wright, and Tracy Moffat-Griffin
Atmos. Chem. Phys., 22, 9435–9459, https://doi.org/10.5194/acp-22-9435-2022, https://doi.org/10.5194/acp-22-9435-2022, 2022
Short summary
Short summary
We present observations of winds in the mesosphere and lower thermosphere (MLT) from a recently installed meteor radar on the remote island of South Georgia (54° S, 36° W). We characterise mean winds, tides, planetary waves, and gravity waves in the MLT at this location and compare our measured winds with a leading climate model. We find that the observed wintertime winds are unexpectedly reversed from model predictions, probably because of missing impacts of secondary gravity waves in the model.
Patricia A. Cleary, Gijs de Boer, Joseph P. Hupy, Steven Borenstein, Jonathan Hamilton, Ben Kies, Dale Lawrence, R. Bradley Pierce, Joe Tirado, Aidan Voon, and Timothy Wagner
Earth Syst. Sci. Data, 14, 2129–2145, https://doi.org/10.5194/essd-14-2129-2022, https://doi.org/10.5194/essd-14-2129-2022, 2022
Short summary
Short summary
A field campaign, WiscoDISCO-21, was conducted at the shoreline of Lake Michigan to better understand the role of marine air in pollutants. Two uncrewed aircraft systems were equipped with sensors for meteorological variables and ozone. A Doppler lidar instrument at a ground station measured horizontal and vertical winds. The overlap of observations from multiple instruments allowed for a unique mapping of the meteorology and pollutants as a marine air mass moved over land.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
Short summary
Short summary
This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Cited articles
Alaoui-Sosse, S., Durand, P., Medina, P., Pastor, P., Lothon, M., and Cernov, I.: OVLI-TA: An Unmanned Aerial System for Measuring Profiles and Turbulence in the Atmospheric Boundary Layer, Sensors, 19, 581, https://doi.org/10.3390/s19030581, 2019. a
Altstädter, B., Platis, A., Wehner, B., Scholtz, A., Wildmann, N., Hermann, M., Käthner, R., Baars, H., Bange, J., and Lampert, A.: ALADINA – an unmanned research aircraft for observing vertical and horizontal distributions of ultrafine particles within the atmospheric boundary layer, Atmos. Meas. Tech., 8, 1627–1639, https://doi.org/10.5194/amt-8-1627-2015, 2015. a
Balsley, B. B., Frehlich, R. G., Jensen, M. L., Meillier, Y., and Muschinski, A.: Extreme Gradients in the Nocturnal Boundary Layer: Structure, Evolution, and Potential Causes, J. Atmos. Sci., 60, 2496–2508, https://doi.org/10.1175/1520-0469(2003)060<2496:EGITNB>2.0.CO;2, 2003. a, b, c, d
Balsley, B. B., Frehlich, R. G., Jensen, M. L., and Meillier, Y.: High-Resolution In Situ Profiling through the Stable Boundary Layer: Examination of the SBL Top in Terms of Minimum Shear, Maximum Stratification, and Turbulence Decrease, J. Atmos. Sci., 63, 1291–1307, https://doi.org/10.1175/JAS3671.1, 2006. a, b, c
Balsley, B. B., Lawrence, D. A., Woodman, R. F., Fritts, D. C., Balsley, B. B., Lawrence, D. A., and Woodman, R. F.: Fine-Scale Characteristics of Temperature, Wind, and Turbulence in the Lower Atmosphere (0–1,300 m) Over the South Peruvian Coast, Bound.-Lay. Meteorol., 147, 165–178, https://doi.org/10.1007/s10546-012-9774-x, 2013. a
Balsley, B. B., Lawrence, D. A., Fritts, D. C., Wang, L., Wan, K., and Werne, J.: Fine Structure, Instabilities, and Turbulence in the Lower Atmosphere: High-Resolution In Situ Slant-Path Measurements with the DataHawk UAV and Comparisons with Numerical Modeling, J. Atmos. Ocean. Tech., 35, 619–642, https://doi.org/10.1175/JTECH-D-16-0037.1, 2018. a, b, c, d, e, f
Barat, J.: Some Characteristics of Clear-Air Turbulence in the Middle Stratosphere, J. Atmos. Sci., 39, 2553–2564, https://doi.org/10.1175/1520-0469(1982)039<2553:SCOCAT>2.0.CO;2, 1982. a, b, c, d
Båserud, L., Flügge, M., Bhandari, A., and Reuder, J.: Characterization of the SUMO turbulence measurement system for wind turbine wake assessment, Energy Proced., 53, 173–183, https://doi.org/10.1016/j.egypro.2014.07.226, 2014. a
Båserud, L., Reuder, J., Jonassen, M. O., Kral, S. T., Paskyabi, M. B., and Lothon, M.: Proof of concept for turbulence measurements with the RPAS SUMO during the BLLAST campaign, Atmos. Meas. Tech., 9, 4901–4913, https://doi.org/10.5194/amt-9-4901-2016, 2016. a, b
Calmer, R., Roberts, G. C., Preissler, J., Sanchez, K. J., Derrien, S., and O'Dowd, C.: Vertical wind velocity measurements using a five-hole probe with remotely piloted aircraft to study aerosol–cloud interactions, Atmos. Meas. Tech., 11, 2583–2599, https://doi.org/10.5194/amt-11-2583-2018, 2018. a
Chimonas, G.: Steps, waves and turbulence in the stably stratified planetary boundary layer, Bound.-Lay. Meteorol., 90, 397–421, https://doi.org/10.1023/A:1001709029773, 1999. a, b, c
Clayson, C. A. and Kantha, L.: On Turbulence and Mixing in the Free Atmosphere Inferred from High-Resolution Soundings, J. Atmos. Ocean. Tech., 25, 833–852, https://doi.org/10.1175/2007JTECHA992.1, 2008. a
Coulman, C. E.: Vertical profiles of small-scale temperature structure in the atmosphere, Bound.-Lay. Meteorol., 4, 169–177, https://doi.org/10.1007/BF02265230, 1973. a
Coulman, C. E., Vernin, J., and Fuchs, A.: Optical seeing–mechanism of formation of thin turbulent laminae in the atmosphere, Appl. Optics, 34, 5461–5474, https://doi.org/10.1364/AO.34.005461, 1995. a, b
Dalaudier, F., Sidi, C., Crochet, M., and Vernin, J.: Direct Evidence of “Sheets” in the Atmospheric Temperature Field, J. Atmos. Sci., 51, 237–248, https://doi.org/10.1175/1520-0469(1994)051<0237:DEOITA>2.0.CO;2, 1994. a, b, c
de Boer, G., Ivey, M., Schmid, B., Lawrence, D., Dexheimer, D., Mei, F., Hubbe, J., Bendure, A., Hardesty, J., Shupe, M. D., McComiskey, A., Telg, H., Schmitt, C., Matrosov, S. Y., Brooks, I., Creamean, J., Solomon, A., Turner, D. D., Williams, C., Maahn, M., Argrow, B., Palo, S., Long, C. N., Gao, R., and Mather, J.: A Bird’s-Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska, B. Am. Meteorol. Soc., 99, 1197–1212, https://doi.org/10.1175/BAMS-D-17-0156.1, 2018. a
de Boer, G., Diehl, C., Jacob, J., Houston, A., Smith, S. W., Chilson, P., Schmale III, D. G., Intrieri, J., Pinto, J., Elston, J., Brus, D., Kemppinen, O., Clark, A., Lawrence, D., Bailey, S. C. C., Sama, M. P., Frazier, A., Crick, C., Natalie, V., Pillar-Little, E., Klein, P., Waugh, S., Lundquist, J. K., Barbieri, L., Kral, S. T., Jensen, A. A., Dixon, C., Borenstein, S., Hesselius, D., Human, K., Hall, P., Argrow, B., Thornberry, T., Wright, R., and Kelly, J. T.: Development of community, capabilities and understanding through unmanned aircraft-based atmospheric research: The LAPSE-RATE campaign, B. Am. Meteorol. Soc., 101, E684–E699, https://doi.org/10.1175/bams-d-19-0050.1, 2019. a
Doddi, A.: Insitu Sensing and Analysis of Turbulence – Investigation to Enhance Fine-Structure Turbulence Observation Capabilities of Autonomous Aircraft Systems, PhD thesis, Ann Arbor, https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/kp78gh76n (last access: 18 April 2022), 2021. a, b
Eaton, F. D., Nastrom, G. D., Masson, B. S., Hahn, I. L., McCrae, K. A., Nowlin, S. R., and Berkopec, T. L.: Radar and aircraft observations of a layer of strong refractivity turbulence, P. SPIE, 3381,
https://doi.org/10.1117/12.323944, 1998. a
Fairall, C. W., White, A. B., and Thomson, D. W.: A stochastic model of gravity-wave-induced clear-air turbulence, J. Atmos. Sci., 48, 1771–1790, https://doi.org/10.1175/1520-0469(1991)048<1771:ASMOGW>2.0.CO;2, 1991. a, b
Fernando, H. J. S., Pardyjak, E. R., Di Sabatino, S., Chow, F. K., De Wekker, S. F. J., Hoch, S. W., Hacker, J., Pace, J. C., Pratt, T., Pu, Z., Steenburgh, W. J., Whiteman, C. D., Wang, Y., Zajic, D., Balsley, B., Dimitrova, R., Emmitt, G. D., Higgins, C. W., Hunt, J. C. R., Knievel, J. C., Lawrence, D., Liu, Y., Nadeau, D. F., Kit, E., Blomquist, B. W., Conry, P., Coppersmith, R. S., Creegan, E., Felton, M., Grachev, A., Gunawardena, N., Hang, C., Hocut, C. M., Huynh, G., Jeglum, M. E., Jensen, D., Kulandaivelu, V., Lehner, M., Leo, L. S., Liberzon, D., Massey, J. D., McEnerney, K., Pal, S., Price, T., Sghiatti, M., Silver, Z., Thompson, M., Zhang, H., and Zsedrovits, T.: The materhorn : Unraveling the intricacies of mountain weather, B. Am. Meteorol. Soc., 96, 1945–1968, https://doi.org/10.1175/BAMS-D-13-00131.1, 2015. a, b, c
Frehlich, R., Meillier, Y., Jensen, M. L., and Balsley, B.: Turbulence Measurements with the CIRES Tethered Lifting System during CASES-99: Calibration and Spectral Analysis of Temperature and Velocity, J. Atmos. Sci., 60, 2487–2495, https://doi.org/10.1175/1520-0469(2003)060<2487:TMWTCT>2.0.CO;2, 2003. a, b, c, d
Fritts, D. C. and Rastogi, P. K.: Convective and dynamical instabilities due to gravity wave motions in the lower and middle atmosphere: Theory and observations, Radio Sci., 20, 1247–1277, https://doi.org/10.1029/RS020i006p01247, 1985. a
Fritts, D. C. and Wang, L.: Gravity wave-fine structure interactions. Part II: Energy dissipation evolutions, statistics, and implications, J. Atmos. Sci., 70, 3735–3755, https://doi.org/10.1175/JAS-D-13-059.1, 2013. a, b, c, d
Fritts, D. C., Wang, L., Werne, J., Lund, T., and Wan, K.: Gravity Wave Instability Dynamics at High Reynolds Numbers. Part I: Wave Field Evolution at Large Amplitudes and High Frequencies, J. Atmos. Sci., 66, 1126–1148, https://doi.org/10.1175/2008JAS2726.1, 2009a. a
Fritts, D. C., Wang, L., Werne, J., Lund, T., and Wan, K.: Gravity Wave Instability Dynamics at High Reynolds Numbers. Part II: Turbulence Evolution, Structure, and Anisotropy, J. Atmos. Sci., 66, 1149–1171, https://doi.org/10.1175/2008JAS2727.1, 2009b. a
Fritts, D., Wang, L., Lund, T., and Thorpe, S.: Multi-scale dynamics of Kelvin–Helmholtz instabilities. Part 1. Secondary instabilities and the dynamics of tubes and knots, J. Fluid Mech., 941, A30, https://doi.org/10.1017/jfm.2021.1085, 2022. a
Fritts, D., Wang, L., Thorpe, S., and Lund, T.:. Multi-scale dynamics of Kelvin–Helmholtz instabilities. Part 2. Energy dissipation rates, evolutions and statistics, J. Fluid Mech., 941, A31, https://doi.org/10.1017/jfm.2021.1086, 2022b. a
Fua, D., Chimonas, G., Einaudi, F., and Zeman, O.: An Analysis of Wave-Turbulence Interaction, J. Atmos. Sci., 39, 2450–2463, https://doi.org/10.1175/1520-0469(1982)039<2450:AAOWTI>2.0.CO;2, 1982. a
Gage, K. S. and Balsley, B. B.: On the scattering and reflection mechanisms contributing to clear air radar echoes from the troposphere, stratosphere, and mesophere, Radio Sci., 15, 243–257, https://doi.org/10.1029/RS015i002p00243, 1980. a
Gage, K. S. and Green, J. L.: Evidence for specular reflection from monostatic VHF radar observations of the stratosphere, Radio Sci., 13, 991–1001, https://doi.org/10.1029/RS013i006p00991, 1978. a
Gong, J. and Geller, M. A.: Vertical fluctuation energy in United States high vertical resolution radiosonde data as an indicator of convective gravity wave sources, J. Geophys. Res., 115, D11110, https://doi.org/10.1029/2009JD012265, 2010. a
Gossard, E. E., Chadwick, R. B., Detman, T. R., and Gaynor, J.: Capability of Surface-Based Clear-Air Doppler Radar for Monitoring Meteorological Structure of Elevated Layers, J. Appl. Meteorol. Clim., 23, 474–485, https://doi.org/10.1175/1520-0450(1984)023<0474:COSBCA>2.0.CO;2, 1984. a
Hunt, J. C. R., Kaimal, J. C., and Gaynor, J. E.: Some observations of turbulence structure in stable layers, Q. J. Roy. Meteor. Soc., 111, 793–815, https://doi.org/10.1002/qj.49711146908, 1985. a, b
Kantha, L., Lawrence, D., Luce, H., Hashiguchi, H., Tsuda, T., Wilson, R., Mixa, T., and Yabuki, M.: Shigaraki UAV-Radar Experiment (ShUREX): overview of the campaign with some preliminary results, Progress in Earth and Planetary Science, 4, 19, https://doi.org/10.1186/s40645-017-0133-x, 2017. a
Kantha, L., Luce, H., Hashiguchi, H., and Doddi, A.: Atmospheric structures in the troposphere as revealed by high-resolution backscatter images from MU radar operating in range-imaging mode, Progress in Earth and Planetary Science, 6, 32, https://doi.org/10.1186/s40645-019-0274-1, 2019. a, b
Knievel, J. C., Liu, Y., Hopson, T. M., Shaw, J. S., Halvorson, S. F., Fisher, H. H., Roux, G., Sheu, R.-S., Pan, L., Hacker, J. P., Vernon, E., Gallagher Iii, F. W., and Pace, J. C.: Mesoscale Ensemble Weather Prediction at U.S. Army Dugway Proving Ground, Utah, Weather Forecast., 32, 2195–2216, https://doi.org/10.1175/WAF-D-17-0049.1, 2017. a
Kohma, M., Sato, K., Tomikawa, Y., Nishimura, K., and Sato, T.: Estimate of Turbulent Energy Dissipation Rate From the VHF Radar and Radiosonde Observations in the Antarctic, J. Geophys. Res.-Atmos., 124, 2976–2993, https://doi.org/10.1029/2018JD029521, 2019. a
Lawrence, D. A. and Balsley, B. B.: Design of a low-cost UAS for high-resolution atmospheric sensing, in: AIAA Infotech at Aerospace (I at A) Conference, Boston, Massachusetts, 19–22 August 2013, https://doi.org/10.2514/6.2013-4669, 2013. a, b, c, d
Lawrence, D. A., Frew, E. W., and Pisano, W. J.: Lyapunov Vector Fields for Autonomous Unmanned Aircraft Flight Control, J. Guid. Control Dynam., 31, 1220–1229, https://doi.org/10.2514/1.34896, 2008. a
Liu, Y., Warner, T. T., Bowers, J. F., Carson, L. P., Chen, F., Clough, C. A., Davis, C. A., Egeland, C. H., Halvorson, S. F., Huck, T. W., Lachapelle, L., Malone, R. E., Rife, D. L., Sheu, R.-S., Swerdlin, S. P., and Weingarten, D. S.: The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part I: Overview of the Modeling System, the Forecast Products, and How the Products Are Used, J. Appl. Meteorol. Clim., 47, 1077–1092, https://doi.org/10.1175/2007JAMC1653.1, 2008. a
Luce, H., Crochet, M., Dalaudier, F., and Sidi, C.: Interpretation of VHF ST radar vertical echoes from in situ temperature sheet observations, Radio Sci., 30, 1003–1025, https://doi.org/10.1029/95RS00713, 1995. a, b
Luce, H., Fukao, S., Yamamoto, M., Sidi, C., and Dalaudier, F.: Validation of Winds Measured by MU Radar with GPS Radiosondes during the MUTSI Campaign, J. Atmos. Ocean. Tech., 18, 817–829, https://doi.org/10.1175/1520-0426(2001)018<0817:VOWMBM>2.0.CO;2, 2001. a, b
Luce, H., Kantha, L., Hashiguchi, H., Lawrence, D., Yabuki, M., Tsuda, T., and Mixa, T.: Comparisons between high-resolution profiles of squared refractive index gradient M2 measured by the Middle and Upper Atmosphere Radar and unmanned aerial vehicles (UAVs) during the Shigaraki UAV-Radar Experiment 2015 campaign, Ann. Geophys., 35, 423–441, https://doi.org/10.5194/angeo-35-423-2017, 2017. a
Luce, H., Kantha, L., Hashiguchi, H., Lawrence, D., and Doddi, A.: Turbulence kinetic energy dissipation rates estimated from concurrent UAV and MU radar measurements, Earth Planets Space, 70, 207, https://doi.org/10.1186/s40623-018-0979-1, 2018a. a
Luce, H., Kantha, L., Hashiguchi, H., Lawrence, D., Mixa, T., Yabuki, M., and Tsuda, T.: Vertical structure of the lower troposphere derived from MU radar, unmanned aerial vehicle, and balloon measurements during ShUREX 2015, Progress in Earth and Planetary Science, 5, 29, https://doi.org/10.1186/s40645-018-0187-4, 2018b. a
Mahrt, L.: Stratified Atmospheric Boundary Layers, Bound.-Lay. Meteorol., 90, 375–396, https://doi.org/10.1023/A:1001765727956, 1999. a
Muschinski, A. and Wode, C.: First In Situ Evidence for Coexisting Submeter Temperature and Humidity Sheets in the Lower Free Troposphere, J. Atmos. Sci., 55, 2893–2906, https://doi.org/10.1175/1520-0469(1998)055<2893:FISEFC>2.0.CO;2, 1998. a, b, c, d
Muschinski, A., Frehich, R., Jensen, M., Hugo, R., Hoff, A., Eaton, F., and Balsley, B.: Fine-Scale Measurements Of Turbulence In The Lower Troposphere: An Intercomparison Between A Kite- And Balloon-Borne, And A Helicopter-Borne Measurement System, Bound.-Lay. Meteorol., 98, 219–250, https://doi.org/10.1023/A:1026520618624, 2001a. a, b
Muschinski, A., Frehlich, R., Jensen, M., Hugo, R., Hoff, A., Eaton, F., and Balsley, B.: Fine-scale measurements of turbulence in the lower troposphere: An intercomparison between a kit-and balloon-borne, and a helicopter-borne measurement system, Bound.-Lay. Meteorol., 98, 219–250, https://doi.org/10.1023/A:1026520618624, 2001b. a
Parsons, D., Dabberdt, W., Cole, H., Hock, T., Martin, C., Barrett, A.-L., Miller, E., Spowart, M., Howard, M., Ecklund, W., Carters, D., Gage, K., and Wilson, J.: The Integrated Sounding System: Description and Preliminary Observations from TOGA COARE, B. Am. Meteorol. Soc., 75, 553–568, https://doi.org/10.1175/1520-0477(1994)075<0553:TISSDA>2.0.CO;2, 1994. a
Röttger, J.: Structure and dynamics of the stratosphere and mesosphere revealed by VHF radar investigations, Pure Appl. Geophys., 118, 494–527, https://doi.org/10.1007/BF01586465, 1980. a, b, c
Röttger, J. and Liu, C. H.: Partial reflection and scattering of VHF radar signals from the clear atmosphere, Geophys. Res. Lett., 5, 357–360, https://doi.org/10.1029/GL005i005p00357, 1978. a
Scipión, D. E., Lawrence, D. A., Milla, M. A., Woodman, R. F., Lume, D. A., and Balsley, B. B.: Simultaneous observations of structure function parameter of refractive index using a high-resolution radar and the DataHawk small airborne measurement system, Ann. Geophys., 34, 767–780, https://doi.org/10.5194/angeo-34-767-2016, 2016. a, b, c
Sidi, C., Lefrere, J., Dalaudier, F., and Barat, J.: An improved atmospheric buoyancy wave spectrum model, J. Geophys. Res.-Atmos., 93, 774–790, https://doi.org/10.1029/JD093iD01p00774, 1988. a
Smith, S. A., Fritts, D. C., and Vanzandt, T. E.: Evidence for a Saturated Spectrum of Atmospheric Gravity Waves, J. Atmos. Sci., 44, 1404–1410, https://doi.org/10.1175/1520-0469(1987)044<1404:EFASSO>2.0.CO;2, 1987. a
Tatarskii, V. I.: The effects of the turbulent atmosphere on wave propagation, Israel Program for Scientific Translations, Jerusalem, 1971. a
Tjernström, M., Balsley, B. B., Svensson, G., and Nappo, C. J.: The Effects of Critical Layers on Residual Layer Turbulence, J. Atmos. Sci., 66, 468–480, https://doi.org/10.1175/2008JAS2729.1, 2009. a, b, c
UCAR/NCAR – Earth Observing Laboratory: NCAR/EOL ISS Surface Meteorology Data, Version 1.0 [PRELIMINARY], UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.5065/D63N226P, 2017. a
van den Kroonenberg, A., Martin, T., Buschmann, M., Bange, J., and Vörsmann, P.: Measuring the Wind Vector Using the Autonomous Mini Aerial Vehicle M2AV, J. Atmos. Ocean. Tech., 25, 1969–1982, https://doi.org/10.1175/2008JTECHA1114.1, 2008. a
VanZandt, T. E., Green, J. L., Gage, K. S., and Clark, W. L.: Vertical profiles of refractivity turbulence structure constant: Comparison of observations by the Sunset Radar with a new theoretical model, Radio Science, 13, 819–829, https://doi.org/10.1029/RS013i005p00819, 1978. a, b
Wainwright, C. E., Bonin, T. A., Chilson, P. B., Gibbs, J. A., Fedorovich, E., and Palmer, R. D.: Methods for Evaluating the Temperature Structure-Function Parameter Using Unmanned Aerial Systems and Large-Eddy Simulation, Bound.-Lay. Meteorol., 155, 189–208, https://doi.org/10.1007/s10546-014-0001-9, 2015. a
Wildmann, N., Ravi, S., and Bange, J.: Towards higher accuracy and better frequency response with standard multi-hole probes in turbulence measurement with remotely piloted aircraft (RPA), Atmos. Meas. Tech., 7, 1027–1041, https://doi.org/10.5194/amt-7-1027-2014, 2014. a
Wilson, R., Dalaudier, F., and Luce, H.: Can one detect small-scale turbulence from standard meteorological radiosondes?, Atmos. Meas. Tech., 4, 795–804, https://doi.org/10.5194/amt-4-795-2011, 2011. a
Witte, B. M., Schlagenhauf, C., Mullen, J., Helvey, J. P., Thamann, M. A., and Bailey, S.: Fundamental Turbulence Measurement with Unmanned Aerial Vehicles (Invited), in: 8th AIAA Atmospheric and Space Environments Conference, AIAA AVIATION Forum, American Institute of Aeronautics and Astronautics, Reston, Virginia, 13–17 June 2016, https://doi.org/10.2514/6.2016-3584, 2016. a
Woodman, R. F. and Chu, Y.: Aspect sensitivity measurements of VHF backscatter made with the Chung-Li radar: Plausible mechanisms, Radio Sci., 24, 113–125, https://doi.org/10.1029/RS024i002p00113, 1989. a
Woodman, R. F. and Guillen, A.: Radar Observations of Winds and Turbulence in the Stratosphere and Mesosphere, J. Atmos. Sci., 31, 493–505, https://doi.org/10.1175/1520-0469(1974)031<0493:ROOWAT>2.0.CO;2, 1974.
a, b
Woods, J. D.: Wave-induced shear instability in the summer thermocline, J. Fluid Mech., 32, 791–800, https://doi.org/10.1017/S0022112068001035, 1968. a
Woods, J. D.: On Richardson's Number as a Criterion for Laminar-Turbulent-Laminar Transition in the Ocean and Atmosphere, Radio Science, 4, 1289–1298, https://doi.org/10.1029/RS004i012p01289, 1969. a
Xing-Sheng, L., Gaynor, J. E., and Kaimal, J. C.: A study of multiple stable layers in the nocturnal lower atmosphere, Bound.-Lay. Meteorol., 26, 157–168, https://doi.org/10.1007/BF00121540, 1983. a, b, c
Short summary
Small-scale turbulent structures are ubiquitous in the atmosphere, yet our understanding of their structure and dynamics is vastly incomplete. IDEAL aimed to improve our understanding of small-scale turbulent flow features in the lower atmosphere. A small, unmanned, fixed-wing aircraft was employed to make targeted observations of atmospheric columns. Measured data were used to guide atmospheric model simulations designed to describe the structure and dynamics of small-scale turbulence.
Small-scale turbulent structures are ubiquitous in the atmosphere, yet our understanding of...