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Achtemeier, G. L.: The Use of Insects as Tracers for “Clear-Air” Boundary-Layer Studies by Doppler Radar, J. Atmos. Ocean. Tech., 8, 746–765, https

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Achtemeier, G. L.: The Use of Insects as Tracers for “Clear-Air”
Boundary-Layer Studies by Doppler Radar, J. Atmos. Ocean.
Tech., 8, 746–765,
https://doi.org/10.1175/1520-0426(1991)008<0746:TUOIAT>2.0.CO;2, 1991. a, b, c

Aoki, M., Iwai, H., Nakagawa, K., Ishii, S., and Mizutani, K.: Measurements of
Rainfall Velocity and Raindrop Size Distribution Using Coherent Doppler
Lidar, J. Atmos. Ocean. Tech., 33, 1949–1966,
https://doi.org/10.1175/JTECH-D-15-0111.1, 2016. a

Biswas, S. K., Chandrasekar, V., Sahoo, S., and Lakshmi, A. K.: Study of a
Convective Event During the Relampago Field Experiment Using Spectral
Polarimetry, in: IGARSS 2022 – 2022 IEEE International Geoscience and Remote
Sensing Symposium, Kuala Lumpur, Malaysia, 17–22 July 2022, 6534–6537, https://doi.org/10.1109/IGARSS46834.2022.9884392,
2022. a

Bonin, T. A. and Alan Brewer, W.: Detection of Range-Folded Returns in Doppler
Lidar Observations, IEEE Geosci. Remote S., 14, 514–518,
https://doi.org/10.1109/LGRS.2017.2652360, 2017. a

Bonin, T. A., Choukulkar, A., Brewer, W. A., Sandberg, S. P., Weickmann, A. M., Pichugina, Y. L., Banta, R. M., Oncley, S. P., and Wolfe, D. E.: Evaluation of turbulence measurement techniques from a single Doppler lidar, Atmos. Meas. Tech., 10, 3021–3039, https://doi.org/10.5194/amt-10-3021-2017, 2017. a, b


Browning , K. and Wexler , R. : The determination of kinematic property of a
wind field using Doppler radar , J. Appl . Meteorol .
Clim . , 7 , 105–113 , 1968 .   a , b , c

Bühl, J., Leinweber, R., Görsdorf, U., Radenz, M., Ansmann, A., and Lehmann, V.: Combined vertical-velocity observations with Doppler lidar, cloud radar and wind profiler, Atmos. Meas. Tech., 8, 3527–3536, https://doi.org/10.5194/amt-8-3527-2015, 2015. a

Chandra , A.   S. , Kollias , P. , Giangrande , S.   E. , and Klein , S.   A. : long – Term
observation of the Convective Boundary Layer Using Insect Radar Returns at
the SGP ARM Climate Research Facility , J. Climate , 23 , 5699–5714 ,
https://doi.org/10.1175/2010jcli3395.1 , 2010 .   a , b , c

Chandrasekar, V., Chen, H., and Philips, B.: Principles of High-Resolution
Radar Network for Hazard Mitigation and Disaster Management in an Urban
Environment, J. Meteorol. Soc. Jpn.. Ser. II, 96A,
119–139, https://doi.org/10.2151/jmsj.2018-015, 2018. a

Clifton, A. and Wagner, R.: Accounting for the effect of turbulence on wind
turbine power curves, in: Journal of Physics: Conference Series, vol. 524, p.
012109, IOP Publishing, https://doi.org/10.1088/1742-6596/524/1/012109, 2014. a

Cordoba, M., Dance, S. L., Kelly, G. A., Nichols, N. K., and Waller, J. A.:
Diagnosing atmospheric motion vector observation errors for an operational
high-resolution data assimilation system, Q. J. Roy.
Meteor. Soc., 143, 333–341, https://doi.org/10.1002/qj.2925,
2017. a

Dawson, D. T., Mansell, E. R., and Kumjian, M. R.: Does Wind Shear Cause
Hydrometeor Size Sorting?, J. Atmos. Sci., 72, 340–348, https://doi.org/10.1175/JAS-D-14-0084.1, 2015. a

Dias Neto, J.: The Tracing Convective Momentum Transport in Complex Cloudy
Atmospheres Experiment – Level 1, Zenodo [data set], https://doi.org/10.5281/zenodo.6926483,
2022a. a, b

Dias Neto, J.: The Tracing Convective Momentum Transport in Complex Cloudy
Atmospheres Experiment – Level 2, Zenodo [data set], https://doi.org/10.5281/zenodo.6926605,
2022b. a, b

Dixit, V., Nuijens, L., and Helfer, K. C.: Counter-Gradient Momentum Transport
Through Subtropical Shallow Convection in ICON-LEM Simulations, J.
Adv. Model. Earth Sy., 13, e2020MS002352,
https://doi.org/10.1029/2020MS002352, 2021. a


Doviak, R. J. and Zrnic, D. S.: Doppler radar and weather observations: Second
edition, 2 edn., Dover Publications, Mineola, NY, ISBN-13 9780486450605,
ISBN-10 0486450600, 2006. a, b


Eberhard, W. L., Cupp, R. E., and Healy, K. R.: Doppler lidar measurement of
profiles of turbulence and momentum flux, J. Atmos. Ocean.
Tech., 6, 809–819, 1989. a

Elliott, D. L. and Cadogan, J. B.: Effects of wind shear and turbulence on wind
turbine power curves, Tech. Rep., Pacific Northwest Lab., Richland, WA (USA), https://ui.adsabs.harvard.edu/abs/1990wien.conf…10E (last access: 15 November 2022),
1990. a

Geerts , B. and Miao , Q. : The Use of Millimeter Doppler Radar Echoes to Estimate
Vertical Air Velocities in the Fair – Weather Convective Boundary Layer ,
J. Atmos . Ocean . Tech . , 22 , 225–246 ,
https://doi.org/10.1175/JTECH1699.1 , 2005 .   a

Ghate , V.   P. , Cadeddu , M.   P. , Zheng , X. , and O’Connor , E. : Turbulence in the
Marine Boundary Layer and Air Motions below Stratocumulus Clouds at the ARM
Eastern North Atlantic Site , J. Appl . Meteorol . Clim . ,
60 , 1495–1510 , https://doi.org/10.1175/jamc-d-21-0087.1 , 2021 .   a , b

Gimeno , L. , Nieto , R. , Vázquez , M. , and Lavers , D. : atmospheric river : a
mini – review , Front . Earth Sci . , 2 , 1–6 , https://doi.org/10.3389/feart.2014.00002 ,
2014 .   a

Gimeno, L., Vázquez, M., Eiras-Barca, J., Sorí, R., Stojanovic, M.,
Algarra, I., Nieto, R., Ramos, A. M., Durán-Quesada, A. M., and
Dominguez, F.: Recent progress on the sources of continental precipitation as
revealed by moisture transport analysis, Earth-Sci. Rev., 201,
103070, https://doi.org/10.1016/j.earscirev.2019.103070, 2020. a

Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., Pier Siebesma, A., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A. F., Pino, D., de Roode, S. R., and Vilà-Guerau de Arellano, J.: Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, Geosci. Model Dev., 3, 415–444, https://doi.org/10.5194/gmd-3-415-2010, 2010. a

Ishwardat, N.: Radar based horizontal wind profile retrieval techniques: DFT
applied to scanning Doppler radar measurements, Master’s thesis, Delft
University of Technology, the Netherlands,
http://resolver.tudelft.nl/uuid:a659654b-e76a-4513-a656-ecad761bdbc8 (last access: 15 November 2022),
2017. a

Kelley , N. D. , Jonkman , B. J. , and Scott , G. N. : Great Plains Turbulence Environment : Its Origins , Impact , and Simulation , University of North Texas Libraries , UNT Digital Library ,
https://digital.library.unt.edu/ark:/67531/metadc882034/ ( last access : 21   January 2023 ) , 2006 .   a

Kishtawal , C.   M. , Deb , S.   K. , Pal , P.   K. , and Joshi , P.   C. : estimation of
Atmospheric Motion Vectors from Kalpana-1 Imagers , J. Appl .
Meteorol . Clim . , 48 , 2410–2421 , https://doi.org/10.1175/2009JAMC2159.1 ,
2009 .   a

Klingebiel, M., Ghate, V. P., Naumann, A. K., Ditas, F., Pöhlker, M. L.,
Pöhlker, C., Kandler, K., Konow, H., and Stevens, B.: Remote Sensing of
Sea Salt Aerosol below Trade Wind Clouds, J. Atmos.
Sci., 76, 1189–1202, https://doi.org/10.1175/JAS-D-18-0139.1, 2019. a

Koning , A.   M. , Nuijens , L. , Bosveld , F.   C. , Siebesma , A. , van Dorp , P.   A. , and
Jonker , H. : Surface – layer Wind Shear and Momentum Transport From Clear – Sky to
Cloudy Weather Regimes Over Land , J. Geophys . Res.-Atmos . , 126 , e2021JD035087 , https://doi.org/10.1029/2021JD035087 , 2021 .   a

Kosiba, K., Wurman, J., Richardson, Y., Markowski, P., Robinson, P., and
Marquis, J.: Genesis of the Goshen County, Wyoming, Tornado on 5 June 2009
during VORTEX2, Mon. Weather Rev., 141, 1157–1181,
https://doi.org/10.1175/MWR-D-12-00056.1, 2013. a


Kropfli, R.: Single Doppler radar measurements of turbulence profiles in the
convective boundary layer, J. Atmos. Ocean. Tech., 3,
305–314, 1986. a

Kumjian , M.   R. : Weather Radars , Springer International Publishing , 15–63 ,
Cham , https://doi.org/10.1007/978-3-319-72583-3_2 , 2018 .   a

Kumjian , M.   R. and Ryzhkov , A.   V. : The Impact of Size Sorting on the
Polarimetric Radar Variables , J. Atmos . Sci . , 69 , 2042–2060 , https://doi.org/10.1175/JAS-D-11-0125.1 , 2012 .   a

Lamb, D. and Verlinde, J.: Physics and Chemistry of Clouds, Cambridge
University Press, https://doi.org/10.1017/CBO9780511976377, 2011. a

Laurencin, C. N., Didlake Jr., A. C., Loeffler, S. D., Kumjian, M. R., and
Heymsfield, G. M.: Hydrometeor Size Sorting in the Asymmetric Eyewall of
Hurricane Matthew (2016), J. Geophys. Res.-Atmos., 125,
e2020JD032671, https://doi.org/10.1029/2020JD032671, 2020. a

Lhermitte, R. M.: Note on Wind Variability with Doppler Radar, J.
Atmos. Sci., 19, 343–346,
https://doi.org/10.1175/1520-0469(1962)019<0343:NOWVWD>2.0.CO;2, 1962. a


Lhermitte, R. M.: Note on the observation of small-scale atmospheric turbulence
by Doppler radar techniques, Radio Sci., 4, 1241–1246, 1969. a, b


Mann, J., Peña, A., Bingöl, F., Wagner, R., and Courtney, M.: Lidar
scanning of momentum flux in and above the atmospheric surface layer, J. Atmos. Ocean. Tech., 27, 959–976, 2010. a

Martner, B. E. and Moran, K. P.: Using cloud radar polarization measurements to
evaluate stratus cloud and insect echoes, J. Geophys. Res.-Atmos., 106, 4891–4897, https://doi.org/10.1029/2000JD900623,
2001. a

Miller, M. A., Yuter, S. E., Hoban, N. P., Tomkins, L. M., and Colle, B. A.: Detecting wave features in Doppler radial velocity radar observations, Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022, 2022. a

Naakka, T., Nygård, T., Vihma, T., Sedlar, J., and Graversen, R.:
Atmospheric moisture transport between mid-latitudes and the Arctic:
Regional, seasonal and vertical distributions, Int. J.
Climatol., 39, 2862–2879, https://doi.org/10.1002/joc.5988, 2019. a

Newman, J. F. and Clifton, A.: An error reduction algorithm to improve lidar turbulence estimates for wind energy, Wind Energ. Sci., 2, 77–95, https://doi.org/10.5194/wes-2-77-2017, 2017. a

Newman, J. F., Klein, P. M., Wharton, S., Sathe, A., Bonin, T. A., Chilson, P. B., and Muschinski, A.: Evaluation of three lidar scanning strategies for turbulence measurements, Atmos. Meas. Tech., 9, 1993–2013, https://doi.org/10.5194/amt-9-1993-2016, 2016. a


Peinke , J. , Barth , S. , Böttcher , F. , Heinemann , D. , and Lange , B. :
Turbulence , a challenge problem for wind energy , Physica A , 338 , 187–193 , 2004 .   a

Rennie, S. J., Illingworth, A. J., Dance, S. L., and Ballard, S. P.: The
accuracy of Doppler radar wind retrievals using insects as targets,
Meteorol. Appl., 17, 419–432,
https://doi.org/10.1002/met.174, 2010. a, b

Ritvanen , J. , O’Connor , E. , Moisseev , D. , Lehtinen , R. , Tyynelä , J. , and Thobois , L. : complementarity of wind measurement from co – locate x – band weather radar and Doppler lidar , Atmos . Meas . Tech . , 15 , 6507–6519 , https://doi.org/10.5194/amt-15-6507-2022 , 2022 .   a , b

Röttger, J. and Larsen, M. F.: UHF/VHF Radar Techniques for Atmospheric
Research and Wind Profiler Applications, American
Meteorological Society, Boston, MA, 235–281, https://doi.org/10.1007/978-1-935704-15-7_23, 1990. a

Sathe , A. and Mann , J. : A review of turbulence measurement using ground – base wind lidar , Atmos . Meas . Tech . , 6 , 3147–3167 , https://doi.org/10.5194/amt-6-3147-2013 , 2013 .   a

Sathe , A. , Mann , J. , Vasiljevic , N. , and Lea , G. : A six – beam method to measure turbulence statistic using ground – base wind lidar , Atmos . Meas . Tech . , 8 , 729–740 , https://doi.org/10.5194/amt-8-729-2015 , 2015 .   a , b , c

Siebesma, A. P. and Cuijpers, J. W. M.: Evaluation of Parametric Assumptions
for Shallow Cumulus Convection, J. Atmos. Sci., 52, 650–666, https://doi.org/10.1175/1520-0469(1995)052<0650:EOPAFS>2.0.CO;2, 1995. a

Smalikho , I. N. and Banakh , V. A. : measurement of wind turbulence parameter by a conically scan coherent Doppler lidar in the atmospheric boundary layer , Atmos . Meas . Tech . , 10 , 4191–4208 , https://doi.org/10.5194/amt-10-4191-2017 , 2017 .   a


Stull, R. B.: An Introduction to Boundary Layer Meteorology, 1 edn., edited by: Stull, R. B., Springer
Dordrecht, Dordrecht, ISBN 978-94-009-3027-8, 2003. a

van Stratum, B., Siebesma, P., Barkmeijer, J., and van Ulft, B.: Downscaling
HARMONIE-AROME with Large-Eddy simulation, Tech. Rep., Royal Netherlands
Meteorological Institute,
https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR378.pdf (last access: 15 November 2022),
2019. a

vanZanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S.,
Burnet, F., Cheng, A., Couvreux, F., Jiang, H., Khairoutdinov, M., Kogan, Y.,
Lewellen, D. C., Mechem, D., Nakamura, K., Noda, A., Shipway, B. J.,
Slawinska, J., Wang, S., and Wyszogrodzki, A.: Controls on precipitation and
cloudiness in simulations of trade-wind cumulus as observed during RICO,
J. Adv. Model. Earth Sy., 3, M06001,
https://doi.org/10.1029/2011MS000056, 2011. a

Velden, C., Daniels, J., Stettner, D., Santek, D., Key, J., Dunion, J.,
Holmlund, K., Dengel, G., Bresky, W., and Menzel, P.: Recent Innovations in
Deriving Tropospheric Winds from Meteorological Satellites, B.
Am. Meteorol. Soc., 86, 205–224, https://doi.org/10.1175/BAMS-86-2-205,
2005.
 a

Velden, C. S. and Bedka, K. M.: Identifying the Uncertainty in Determining
Satellite-Derived Atmospheric Motion Vector Height Attribution, J.
Appl. Meteorol. Clim., 48, 450–463,
https://doi.org/10.1175/2008JAMC1957.1, 2009. a

Wainwright, C. E., Stepanian, P. M., Reynolds, D. R., and Reynolds, A. M.: The
movement of small insects in the convective boundary layer: linking patterns
to processes, Scientific Reports, 7, 5438, https://doi.org/10.1038/s41598-017-04503-0,
2017. a, b

Wilson, D.: Doppler radar studies of boundary layer wind profile and turbulence
in snow conditions, B. Am. Meteorol. Soc.,
51, 759–785, http://www.jstor.org/stable/26253228 (last access: 15 November 2022),
1970. a

Wilson, J. W., Weckwerth, T. M., Vivekanandan, J., Wakimoto, R. M., and
Russell, R. W.: Boundary Layer Clear-Air Radar Echoes: Origin of Echoes and
Accuracy of Derived Winds, J. Atmos. Ocean. Tech., 11,
1184–1206, https://doi.org/10.1175/1520-0426(1994)011<1184:BLCARE>2.0.CO;2, 1994. a, b

Zemp , D. C. , Schleussner , C.-F. , Barbosa , H. M. J. , van der Ent , R. J. , Donges , J. F. , Heinke , J. , Sampaio , G. , and Rammig , A. : On the importance of cascade moisture recycling in South America , Atmos . Chem . Phys . , 14 , 13337–13359 , https://doi.org/10.5194/acp-14-13337-2014 , 2014 .   a