Gu, Z. and Ubachs, W.: A Systematic Study of Rayleigh-Brillouin
Scattering in Air, N
2, and O
2 gases, J. Chem. Phys.,
141, 1–11,
https://doi.org/10.1063/1.4895130, 2014.
a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons,
A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati,
G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146,
1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
a
Horanyi, A., Cardinali, C., Rennie, M., and Isaksen, L.: The Assimilation of
Horizontal Line-of-Sight Wind Information into the ECMWF Data
Assimilation and Forecasting System. Part I: The Assessment of Wind
Impact, Q. J. Roy. Meteor. Soc., 141,
1223–1232,
https://doi.org/10.1002/qj.2430, 2015.
a
Isaksen, L., Bonavita, M., Buizza, R., Fisher, M., Haseler, J., Leutbecher, M., and Raynaud, L.: Ensemble of data assimilations at ECMWF, ECMWF technical memorandum, Number 636,
https://doi.org/10.21957/obke4k60, 2010.
a,
b,
c,
d
Marseille, G.-J., Stoffelen, A., and Barkmeijer, J.: A Cycled Sensitivity
Observing System Experiment on Simulated Doppler Wind Lidar Data during
the 1999 Christmas Storm “Martin”, Tellus A, 60 A, 249–260,
https://doi.org/10.1111/j.1600-0870.2007.00290.x, 2007.
a
Marseille, G.-J., Stoffelen, A., and Barkmeijer, J.: Impact Assessment of
Prospective Spaceborne Doppler Wind Lidar Observation Scenarios, Tellus A, 60A, 234–248,
https://doi.org/10.1111/j.1600-0870.2007.00289.x, 2008.
a
Martin, A., Weissmann, M., Reitebuch, O., Rennie, M., Geiß, A., and Cress, A.: Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents, Atmos. Meas. Tech., 14, 2167–2183,
https://doi.org/10.5194/amt-14-2167-2021, 2021.
a,
b,
c
Matsushita, Y., Kado, D., Kohma, M., and Sato, K.: Relation between the interannual variability in the stratospheric Rossby wave forcing and zonal mean fields suggesting an interhemispheric link in the stratosphere, Ann. Geophys., 38, 319–329,
https://doi.org/10.5194/angeo-38-319-2020, 2020.
a
Reitebuch, O.: The Spaceborne Wind Lidar Mission ADM-Aeolus, in: Atmospheric Physics, Research Topics in Aerospace, edited by: Schumann, U., Springer, Berlin, Heidelberg, Germany,
https://doi.org/10.1007/978-3-642-30183-4_49, 2012.
a
Rennie, M., Tan, D., Andersson, E., Poli, P., Dabas, A., De Kloe, J.,
Marseille, G.-J., and Stoffelen, A.: Aeolus Level-2B Algorithm theoretical
basis document – Mathematical description of the Aeolus Level-2B processor,
Documentation for Level-2B processor version 3.30, available at:
https://confluence.ecmwf.int/display/AEOL/L2B+processor+documentation+and+datasets (last access: 17 May 2021), 2020.
a,
b,
c,
d
Šavli, M., Žagar, N., and Anderson, J.: Assimilation of Horizontal
Line-of-Sight Winds with a Mesoscale EnKF Data Assimilation System,
Q. J. Roy. Meteor. Soc., 144, 2133–2155,
https://doi.org/10.1002/qj.3323, 2018.
a
Stoffelen, A., Pailleux, J., Kallen, E., Vaughan, J. M., Isaksen, L., Flamant, P., Wergen, W., Andersson, E., Schyberg, H., Culoma, A., Meynart, R., Endemann, M., and Ingmann, P.: The Atmospheric Dynamics Mission for Global Wind Field Measurement, B. Am. Meteorol. Soc., 86,
73–87,
https://doi.org/10.1175/BAMS-86-1-73, 2005.
a,
b
Stoffelen, A., Marseille, G.-J., Bouttier, F., Vasiljevic, D., de Haan, S.,
and Cardinali, C.: ADM-Aeolus Doppler Wind Lidar Observing System
Simulation Experiment, Q. J. Roy. Meteor. Soc., 132, 1927–1947,
https://doi.org/10.1256/qj.05.83, 2006.
a
Tan, D. G. H. and Andersson, E.: Simulation of the Yield and Accuracy of Wind
Profile Measurements from the Atmospheric Dynamics Mission (ADM-Aeolus), Q. J. Roy. Meteor. Soc., 131, 1737–1757,
https://doi.org/10.1256/qj.04.02, 2005.
a
Tan, D. G. H., Andersson, E., Fisher, M., and Isaksen, L.: Observing-System
Impact Assessment Using a Data Assimilation Ensemble Technique: Application
to the ADM–Aeolus Wind Profiling Mission, Q. J. Roy. Meteor. Soc., 133, 381–390,
https://doi.org/10.1002/qj.43, 2007.
a
Tan, D. G. H., Andersson, E., De Kloe, J., Marseille, G.-J., Stoffelen, A.,
Poli, P., Denneulin, M. L., Dabas, A., Huber, D., Reitebuch, O., Flamant, P.,
Le Rille, O., and Nett, H.: The ADM-Aeolus Wind Retrieval Algorithms,
Tellus A, 60A, 191–205,
https://doi.org/10.1111/j.1600-0870.2007.00285.x, 2008.
a
Tenti, G., Boley, C. D., and Desai, R. C.: On the kinetic model
description of Rayleigh-Brillouin scattering from molecular gases, Can.
J. Phys., 52, 285,
https://doi.org/10.1139/p74-041, 1974.
a
Weiler, F., Kanitz, T., Wernham, D., Rennie, M., Huber, D., Schillinger, M., Saint-Pe, O., Bell, R., Parrinello, T., and Reitebuch, O.: Characterization of dark current signal measurements of the ACCDs used on-board the Aeolus satellite, Atmos. Meas. Tech. Discuss. [preprint],
https://doi.org/10.5194/amt-2020-458, in review, 2020.
a,
b
Weissmann, M. and Cardinali, C.: The impact of airborne Doppler lidar
observations on ECMWF forecasts, ECMWF technical memorandum, Number 505,
https://doi.org/10.21957/3zjzqeh1a, 2006.
a
Weissmann, M., Langland, R. H., Cardinali, C., Pauley, P. M., and Rahm, S.:
Influence of airborne Doppler wind lidar profiles near Typhoon Sinlaku on
ECMWF and NOGAPS forecasts, Q. J. Roy. Meteor. Soc., 138, 118–130,
https://doi.org/10.1002/qj.896, 2012.
a
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, 3nd edn., Elsevier Academic Press, Cambridge, MA, USA, 2011. a
Witschas, B., Lemmerz, C., Geiß, A., Lux, O., Marksteiner, U., Rahm, S., Reitebuch, O., and Weiler, F.: First validation of Aeolus wind observations by airborne Doppler wind lidar measurements, Atmos. Meas. Tech., 13, 2381–2396,
https://doi.org/10.5194/amt-13-2381-2020, 2020.
a
