Articles | Volume 16, issue 21
https://doi.org/10.5194/amt-16-5091-2023
https://doi.org/10.5194/amt-16-5091-2023
Research article
 | 
02 Nov 2023
Research article |  | 02 Nov 2023

Statistical assessment of a Doppler radar model of TKE dissipation rate for low Richardson numbers

Hubert Luce, Lakshmi Kantha, and Hiroyuki Hashiguchi

Related authors

Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements
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

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the Equator
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024,https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Verification of weather-radar-based hail metrics with crowdsourced observations from Switzerland
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024,https://doi.org/10.5194/amt-17-4529-2024, 2024
Short summary
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024,https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024,https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Improving the Estimate of Higher Order Moments from Lidar Observations Near the Top of the Convective Boundary Layer
Tessa Rosenberger, David D. Turner, Thijs Heus, Girish N. Raghunathan, Timothy J. Wagner, and Julia Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-868,https://doi.org/10.5194/egusphere-2024-868, 2024
Short summary

Cited articles

Balsley, B. B., Svensson, G., and Tjernström, M.: On the Scale-dependence of the Gradient Richardson Number in the Residual Layer, Bound.-Lay. Meteorol., 127, 57–72, https://doi.org/10.1007/s10546-007-9251-0, 2008. 
Basu, S. and Holtslag, A. A. M.: Turbulent Prandtl number and characteristic length scales in stably stratified floaws: steady-state analytical solutions, Environ. Fluid Mech., 21, 1273–1302, https://doi.org/10.1007/s10652-021-09820-7, 2021. 
Basu, S. and Holtslag, A. A. M.: Revisiting and revising Tatarskii’s formulation for the temperature structure parameter CT2 in atmospheric flows, Environ. Fluid Mech., 22, 1107–1119, https://doi.org/10.1007/s10652-022-09880-3, 2022. 
Basu, S., He, P., and De Marco, A. W.: Parameterizing the energy dissipation rate in stably stratified flows, Bound.-Lay. Meteorol., 178, 167–184, https://doi.org/10.1007/s10546-020-00559-0, 2021. 
Doviak, R. J. and Zrnić, D. S.: Doppler radar and weather observations, Academic Press, San Diego, ISBN 012221420X, 9780122214202, 1984. 
Download
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.