Bell, T. M., Klein, P., Wildmann, N., and Menke, R.: Analysis of flow in complex terrain using multi-Doppler lidar retrievals, Atmos. Meas. Tech., 13, 1357–1371,
https://doi.org/10.5194/amt-13-1357-2020, 2020.
a,
b
Bingöl, F., Mann, J., and Foussekis, D.: Conically scanning lidar error in complex terrain, Meteorol. Z., 18, 189–195,
https://doi.org/10.1127/0941-2948/2009/0368, 2009.
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,
c
Bonin, T. A., Carroll, B. J., Hardesty, R. M., Brewer, W. A., Hajny, K., Salmon, O. E., and Shepson, P. B.: Doppler Lidar Observations of the Mixing Height in Indianapolis Using an Automated Composite Fuzzy Logic Approach, J. Atmos. Ocean. Tech., 35, 473–490,
https://doi.org/10.1175/JTECH-D-17-0159.1, 2018.
a,
b,
c
Damelin, S. B. and Hoang, N. S.: On Surface Completion and Image Inpainting by Biharmonic Functions: Numerical Aspects, International Journal of Mathematics and Mathematical Sciences, 2018,
https://doi.org/10.1155/2018/3950312, 2018.
a
Drew, D. R., Barlow, J. F., and Lane, S. E.: Observations of wind speed profiles over Greater London, UK, using a Doppler lidar, J. Wind Eng. Ind. Aerod., 121, 98–105,
https://doi.org/10.1016/j.jweia.2013.07.019, 2013.
a
Eaton, B., Gregory, J., Drach, B., Taylor, K., Hankin, S., Blower, J., Caron, J., Signell, R., Bentley, P., Rappa, G., Höck, H., Pamment, A., Juckes, M., Raspaud, M., Randy Horne, T. W., Blodgett, D., Zender, C., Lee, D., Hassell, D., Snow, A. D., Kölling, T., Allured, D., Jelenak, A., Soerensen, A. M., Gaultier, L., Herlédan, S., Manzano, F., Bärring, L., Barker, C., and Bartholomew, S.: NetCDF Climate and Forecast (CF) Metadata Conventions, version 1.11,
https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.pdf (last access: 27 August 2024), 2023.
a,
b
Erdmann, A. and Gasch, P.: Code for Erdmann and Gasch: Modular wind profile retrieval software for heterogeneous Doppler lidar measurements (AtmoProKIT v1.1), Zenodo [code],
https://doi.org/10.5281/zenodo.14844632, 2026a.
a
Erdmann, A. and Gasch, P.: Doppler lidar validation data for Erdmann and Gasch: Modular wind profile retrieval software for heterogeneous Doppler lidar measurements, Zenodo [data set],
https://doi.org/10.5281/zenodo.14844887, 2026b.
a
Fernando, H. J. S., Mann, J., Palma, J. M. L. M., Lundquist, J. K., Barthelmie, R. J., Belo-Pereira, M., Brown, W. O. J., Chow, F. K., Gerz, T., Hocut, C. M., Klein, P. M., Leo, L. S., Matos, J. C., Oncley, S. P., Pryor, S. C., Bariteau, L., Bell, T. M., Bodini, N., Carney, M. B., Courtney, M. S., Creegan, E. D., Dimitrova, R., Gomes, S., Hagen, M., Hyde, J. O., Kigle, S., Krishnamurthy, R., Lopes, J. C., Mazzaro, L., Neher, J. M. T., Menke, R., Murphy, P., Oswald, L., Otarola-Bustos, S., Pattantyus, A. K., Rodrigues, C. V., Schady, A., Sirin, N., Spuler, S., Svensson, E., Tomaszewski, J., Turner, D. D., van Veen, L., Vasiljević, N., Vassallo, D., Voss, S., Wildmann, N., and Wang, Y.: The Perdigão: Peering into microscale details of mountain winds, B. Am. Meteorol. Soc., 100, 799–819,
https://doi.org/10.1175/bams-d-17-0227.1, 2019.
a
Gasch, P., Wieser, A., Lundquist, J. K., and Kalthoff, N.: An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions, Atmos. Meas. Tech., 13, 1609–1631,
https://doi.org/10.5194/amt-13-1609-2020, 2020.
a,
b,
c,
d,
e
Gasch, P., Kasic, J., Maas, O., and Wang, Z.: Advancing airborne Doppler lidar wind profiling in turbulent boundary layer flow – an LES-based optimization of traditional scanning-beam versus novel fixed-beam measurement systems, Atmos. Meas. Tech., 16, 5495–5523,
https://doi.org/10.5194/amt-16-5495-2023, 2023.
a,
b
Handwerker, J., Barthlott, C., Bauckholt, M., Belleflamme, A., Böhmländer, A., Borg, E., Dick, G., Dietrich, P., Fichtelmann, B., Geppert, G., Goergen, K., Güntner, A., Hammoudeh, S., Hervo, M., Hühn, E., Kaniyodical Sebastian, M., Keller, J., Kohler, M., Knippertz, P., Kunz, M., Landmark, S., Li, Y., Mohannazadeh, M., Möhler, O., Morsy, M., Najafi, H., Nallasamy, N. D., Oertel, A., Rakovec, O., Reich, H., Reich, M., Saathoff, H., Samaniego, L., Schrön, M., Schütze, C., Steinert, T., Vogel, F., Vorogushyn, S., Weber, U., Wieser, A., and Zhang, H.: From initiation of convective storms to their impact – the Swabian MOSES 2023 campaign in southwestern Germany, Front. Earth Sci., 13,
https://doi.org/10.3389/feart.2025.1555755, 2025.
a,
b
Hervo, M. and Coen, M.: Custom collection of Doppler lidar wind data from Payerne between 1 Jun and 31 Aug 2023, ACTRIS Cloud remote sensing data centre unit (CLU) [data set],
https://cloudnet.fmi.fi/instrument/a3c0f804-d91e-4966-9efb-aef54b9f2cd1 (last access: 4 March 2026), 2024. a
Kawabata, T., Iwai, H., Seko, H., Shoji, Y., Saito, K., Ishii, S., and Mizutani, K.: Cloud-resolving 4D-Var assimilation of Doppler wind lidar data on a meso-gamma-scale convective system, Mon. Weather Rev., 142, 4484–4498,
https://doi.org/10.1175/mwr-d-13-00362.1, 2014.
a
Kayser, M., Päschke, E., Detring, C., Lehmann, V., Beyrich, F., and Leinweber, R.: Standardized Doppler lidar processing for operational use in a future network, DACH2022, Leipzig, Deutschland, 21–25 Mar 2022, DACH2022-209,
https://doi.org/10.5194/dach2022-209, 2022.
a
Kunz, M., Abbas, S. S., Bauckholt, M., Böhmländer, A., Feuerle, T., Gasch, P., Glaser, C., Groß, J., Hajnsek, I., Handwerker, J., Hase, F., Khordakova, D., Knippertz, P., Kohler, M., Lange, D., Latt, M., Laube, J., Martin, L., Mauder, M., Möhler, O., Mohr, S., Reitter, R. W., Rettenmeier, A., Rolf, C., Saathoff, H., Schrön, M., Schütze, C., Spahr, S., Späth, F., Vogel, F., Völksch, I., Weber, U., Wieser, A., Wilhelm, J., Zhang, H., and Dietrich, P.: Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains, Front. Earth Sci., p. 1886,
https://doi.org/10.3389/feart.2022.999593, 2022.
a
Manninen, A. J., O'Connor, E. J., Vakkari, V., and Petäjä, T.: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817–827,
https://doi.org/10.5194/amt-9-817-2016, 2016.
a
Mense, T. H., Höffner, J., Baumgarten, G., Eixmann, R., Froh, J., Mauer, A., Munk, A., Wing, R., and Lübken, F.-J.: 3D wind observations with a compact mobile lidar based on tropo- and stratospheric aerosol backscatter, Atmos. Meas. Tech., 17, 1665–1677,
https://doi.org/10.5194/amt-17-1665-2024, 2024.
a
Neto, J. D. and Castelao, G. P.: lidarwind: A Python package for retrieving wind profiles from Doppler lidar observations, J. Open Source Softw., 8, 4852,
https://doi.org/10.21105/joss.04852, 2023.
a
O’Connor, E. J., Illingworth, A. J., Brooks, I. M., Westbrook, C. D., Hogan, R. J., Davies, F., and Brooks, B. J.: A Method for Estimating the Turbulent Kinetic Energy Dissipation Rate from a Vertically Pointing Doppler Lidar, and Independent Evaluation from Balloon-Borne In Situ Measurements, J. Atmos. Ocean. Tech., 27, 1652–1664,
https://doi.org/10.1175/2010jtecha1455.1, 2010.
a
Päschke, E., Leinweber, R., and Lehmann, V.: An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial, Atmos. Meas. Tech., 8, 2251–2266,
https://doi.org/10.5194/amt-8-2251-2015, 2015.
a,
b,
c,
d,
e,
f,
g,
h
Pentikäinen, P., O'Connor, E. J., and Ortiz-Amezcua, P.: Evaluating wind profiles in a numerical weather prediction model with Doppler lidar, Geosci. Model Dev., 16, 2077–2094,
https://doi.org/10.5194/gmd-16-2077-2023, 2023.
a
Pichugina, Y. L., Banta, R. M., Bonin, T., Brewer, W. A., Choukulkar, A., McCarty, B. J., Baidar, S., Draxl, C., Fernando, H. J. S., Kenyon, J., Krishnamurthy, R., Marquis, M., Olson, J., Sharp, J., and Stoelinga, M.: Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin, J. Appl. Meteorol. Clim., 58, 1633–1656,
https://doi.org/10.1175/JAMC-D-18-0244.1, 2019.
a,
b,
c
Päschke, E. and Detring, C.: Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation, Atmos. Meas. Tech., 17, 3187–3217,
https://doi.org/10.5194/amt-17-3187-2024, 2024.
a,
b,
c,
d,
e,
f,
g
Rahlves, C., Beyrich, F., and Raasch, S.: Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation, Atmos. Meas. Tech., 15, 2839–2856,
https://doi.org/10.5194/amt-15-2839-2022, 2022.
a,
b,
c,
d,
e,
f,
g,
h
Robey, R. and Lundquist, J. K.: Behavior and mechanisms of Doppler wind lidar error in varying stability regimes, Atmos. Meas. Tech., 15, 4585–4622,
https://doi.org/10.5194/amt-15-4585-2022, 2022.
a,
b,
c,
d,
e,
f,
g
Rucker, M., Banta, R. M., and Steyn, D. G.: Along-Valley Structure of Daytime Thermally Driven Flows in the Wipp Valley, J. Appl. Meteorol. Clim., 47, 733–751,
https://doi.org/10.1175/2007jamc1319.1, 2008.
a,
b
Rye, B. J. and Hardesty, R. M.: Discrete spectral peak estimation in incoherent backscatter heterodyne lidar. I. Spectral accumulation and the Cramer-Rao lower bound, IEEE T. Geosci. Remote Sens., 31, 16–27,
https://doi.org/10.1109/36.210440, 1993a.
a
Rye, B. J. and Hardesty, R. M.: Discrete spectral peak estimation in incoherent backscatter heterodyne lidar. II. Correlogram accumulation, IEEE T. Geosci. Remote Sens., 31, 28–35,
https://doi.org/10.1109/36.210441, 1993b.
a
Schmithüsen, H., Engelmann, R., and Radenz, M.: Custom collection of Doppler lidar wind data from Neumayer Station between 1 Jan and 27 Nov 2024, ACTRIS Cloud remote sensing data centre unit (CLU) [data set],
https://cloudnet.fmi.fi/instrument/e166bb0b-5e92-46ce-adb8-73ed38ecc459 (last access: 4 March 2026), 2024.
a,
b
Smalikho, I. N. and Banakh, V. A.: Measurements of wind turbulence parameters by a conically scanning 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,
b
Steinheuer, J., Detring, C., Beyrich, F., Löhnert, U., Friederichs, P., and Fiedler, S.: A new scanning scheme and flexible retrieval for mean winds and gusts from Doppler lidar measurements, Atmos. Meas. Tech., 15, 3243–3260,
https://doi.org/10.5194/amt-15-3243-2022, 2022.
a,
b,
c,
d,
e,
f,
g
Teschke, G. and Lehmann, V.: Mean wind vector estimation using the velocity–azimuth display (VAD) method: an explicit algebraic solution, Atmos. Meas. Tech., 10, 3265–3271,
https://doi.org/10.5194/amt-10-3265-2017, 2017.
a,
b
Träumner, K., Damian, T., Stawiarski, C., and Wieser, A.: Turbulent structures and coherence in the atmospheric surface layer, Bound.-Lay. Meteorol., 154, 1–25,
https://doi.org/10.1007/s10546-014-9967-6, 2015.
a,
b
Tucker, S. C., Senff, C. J., Weickmann, A. M., Brewer, W. A., Banta, R. M., Sandberg, S. P., Law, D. C., and Hardesty, R. M.: Doppler Lidar Estimation of Mixing Height Using Turbulence, Shear, and Aerosol Profiles, J. Atmos. Ocean. Tech., 26, 673–688,
https://doi.org/10.1175/2008JTECHA1157.1, 2009.
a,
b,
c
Tukiainen, S., Siipola, T., Leskinen, N., and O'Connor, E.: Cloudnet – an ACTRIS data repository for cloud remote sensing observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20005,
https://doi.org/10.5194/egusphere-egu24-20005, 2024.
a
Vakkari, V., Manninen, A. J., O'Connor, E. J., Schween, J. H., van Zyl, P. G., and Marinou, E.: A novel post-processing algorithm for Halo Doppler lidars, Atmos. Meas. Tech., 12, 839–852,
https://doi.org/10.5194/amt-12-839-2019, 2019.
a
van der Walt, S., Colbert, S. C., and Varoquaux, G.: The NumPy Array: A Structure for Efficient Numerical Computation, Comput. Sci. Eng., 13, 22–30,
https://doi.org/10.1109/MCSE.2011.37, 2011.
a
Wagner, T. J., Turner, D. D., Heus, T., and Blumberg, W. G.: Observing Profiles of Derived Kinematic Field Quantities Using a Network of Profiling Sites, J. Atmos. Ocean. Tech., 39, 335–351,
https://doi.org/10.1175/jtech-d-21-0061.1, 2022.
a,
b
Wang, H., Barthelmie, R. J., Clifton, A., and Pryor, S. C.: Wind measurements from arc scans with Doppler wind lidar, J. Atmos. Ocean. Tech., 32, 2024–2040,
https://doi.org/10.1175/JTECH-D-14-00059.1, 2015.
a,
b,
c
Wang, H., Barthelmie, R. J., Pryor, S. C., and Brown, G.: Lidar arc scan uncertainty reduction through scanning geometry optimization, Atmos. Meas. Tech., 9, 1653–1669,
https://doi.org/10.5194/amt-9-1653-2016, 2016.
a
Werner, C.: Doppler wind lidar, in: Lidar – range-resolved optical remote sensing of the atmosphere, chap. 12, Springer Science & Business Media, New York, NY, 326–354,
https://doi.org/10.1007/b106786, 2005.
a,
b
Wieser, A. and Gasch, P.: Doppler lidar measurements from Villingen-Schwenningen, August 2023, Swabian MOSES 2023, Level 0 netCDF files, Zenodo [data set],
https://doi.org/10.5281/zenodo.14844286, 2025e.
a
Wieser, A. and Gasch, P.: Doppler lidar measurements from Villingen-Schwenningen, July 2023, Swabian MOSES 2023, Level 0 netCDF files, Zenodo [data set],
https://doi.org/10.5281/zenodo.14844229, 2025f.
a
Wieser, A. and Gasch, P.: Doppler lidar measurements from Villingen-Schwenningen, June 2023, Swabian MOSES 2023, Level 0 netCDF files, Zenodo [data set],
https://doi.org/10.5281/zenodo.14844019, 2025g.
a
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J., Groth, P., Goble, C., Grethe, J. S., Heringa, J., t Hoen, P. A., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A., Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M. A., Thompson, M., Van Der Lei, J., Van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.: Comment: The FAIR Guiding Principles for scientific data management and stewardship, Sci. Data, 3,
https://doi.org/10.1038/sdata.2016.18, 2016.
a
Zentek, R., Kohnemann, S. H. E., and Heinemann, G.: Analysis of the performance of a ship-borne scanning wind lidar in the Arctic and Antarctic, Atmos. Meas. Tech., 11, 5781–5795,
https://doi.org/10.5194/amt-11-5781-2018, 2018.
a,
b,
c,
d
