Crameri, F., Shephard, G. E., and Heron, P. J.: The misuse of colour in
science communication, Nat. Commun., 11, 5444, https://doi.org/10.1038/s41467-020-19160-7, 2020.
de Kloe, J., Stoffelen, A., Tan, D., Andersson, E., Rennie, M., Dabas, A.,
Poli, P., and Huber, D.: Aeolus data innovation science cluster DISC
ADM-Aeolus Level-2B/2C processor input/output data definitions interface
control document, ESA, 134 pp.,
https://earth.esa.int/eogateway/documents/20142/37627/Aeolus-L2B-2C-Input-Output-DD-ICD.pdf (last access: 21 April 2023),
2023.
Dudhia, J.: Numerical study of convection observed during the winter monsoon
experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46,
3077–3107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2, 1989.
ESA: A guide to Aeolus range bin settings, Earth online,
https://earth.esa.int/eogateway/news/a-guide-to-aeolus-range-bin-settings (last access: 24 December 2022), 2020.
ESA: ESA Aeolus online dissemination, ESA [data set],
https://aeolus-ds.eo.esa.int/oads/access/collection/L2B_Wind_Products (last access: 5 September 2022), 2021.
ESA: Facts and figures,
https://www.esa.int/Applications/Observing_the_Earth/Aeolus/Facts_and_figures, last access: 24 December 2022.
Garrett, K., Liu, H., Ide, K., Hoffman, R. N., and Lukens, K. E.:
Optimization and impact assessment of Aeolus HLOS wind data assimilation in
NOAA's global forecast system, Q. J. Roy. Meteor. Soc., 148, 2703–2716,
https://doi.org/10.1002/qj.4331, 2022.
Guo, J., Liu, B., Gong, W., Shi, L., Zhang, Y., Ma, Y., Zhang, J., Chen, T., Bai, K., Stoffelen, A., de Leeuw, G., and Xu, X.: Technical note: First comparison of wind observations from ESA's satellite mission Aeolus and ground-based radar wind profiler network of China, Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, 2021.
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with
an explicit treatment of entrainment processes, Mon. Weather Rev., 134,
2318–2341, https://doi.org/10.1175/MWR3199.1, 2006.
Hu, M., Ge, G., Zhou, C., Stark, D., Shao, H., Newman, K., Beck, J., and
Zhang, X.: GSI user's guide version 3.7, Developmental Testbed Center (DTC),
147 pp.,
https://dtcenter.org/sites/default/files/GSIUserGuide_v3.7_0.pdf (last access: 21 April 2023), 2018.
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM
IMERG final precipitation L3 half hourly 0.1 degree x 0.1 degree V06,
Goddard Earth Sciences Data and Information Services Center (GES DISC) [data
set], https://doi.org/10.5067/GPM/IMERG/3B-HH/06, 2019.
Ingmann, P. and Straume, A. G.: ADM-Aeolus mission requirements document,
ESA, 57 pp.,
https://esamultimedia.esa.int/docs/EarthObservation/ADM-Aeolus_MRD.pdf (last access: 21 April 2023), 2016.
Janjić, T., Bormann, N., Bocquet, M., Carton, J. A., Cohn, S. E., Dance,
S. L., Losa, S. N., Nichols, N. K., Potthast, R., Waller, J. A., and Weston,
P.: On the representation error in data assimilation, Q. J. Roy. Meteor.
Soc., 144, 1257–1278, https://doi.org/10.1002/qj.3130, 2018.
Jiménez, P. A., Dudhia, J., González-Rouco, J. F., Navarro, J.,
Montávez, J. P., and García-Bustamante, E.: A revised scheme for the WRF surface layer formulation, Mon. Weather Rev., 140, 898–918, https://doi.org/10.1175/MWR-D-11-00056.1, 2012.
Kain, J. S.: The Kain–Fritsch convective parameterization: An update, J.
Appl. Meteorol. Clim., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Krisch, I., Hindley, N. P., Reitebuch, O., and Wright, C. J.: On the derivation of zonal and meridional wind components from Aeolus horizontal line-of-sight wind, Atmos. Meas. Tech., 15, 3465–3479, https://doi.org/10.5194/amt-15-3465-2022, 2022.
Laroche, S. and St-James, J.: Impact of the Aeolus level-2b horizontal
line-of-sight winds in the Environment and Climate Change Canada global
forecast system, Q. J. Roy. Meteor. Soc., 148, 2047–2062, https://doi.org/10.1002/qj.4300, 2022.
Lukens, K. E., Ide, K., Garrett, K., Liu, H., Santek, D., Hoover, B., and Hoffman, R. N.: Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty, Atmos. Meas. Tech., 15, 2719–2743, https://doi.org/10.5194/amt-15-2719-2022, 2022.
Marinescu, P. J., Cucurull, L., Apodaca, K., Bucci, L., and Genkova, I.: The
characterization and impact of Aeolus wind profile observations in NOAA's
regional tropical cyclone model (HWRF), Q. J. Roy. Meteor. Soc., 148,
3491–3508, https://doi.org/10.1002/qj.4370, 2022.
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.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102,
16663–16682, https://doi.org/10.1029/97JD00237, 1997.
Pourret, V., Šavli, M., Mahfouf, J.-F., Raspaud, D., Doerenbecher, A.,
Bénichou, H., and Payan, C.: Operational assimilation of Aeolus winds in
the Météo-France global NWP model ARPEGE, Q. J. Roy. Meteor. Soc.,
148, 2652–2671, https://doi.org/10.1002/qj.4329, 2022.
Pu, Z., Zhang, L., and Emmitt, G. D.: Impact of airborne Doppler Wind Lidar
data on numerical simulation of a tropical cyclone, Geophys. Res. Lett., 37,
L05801, https://doi.org/10.1029/2009GL041765, 2010.
Pu, Z., Zhang, L., Zhang, S., Gentry, B., Emmitt, D., Demoz, B., and Atlas,
R.: The impact of Doppler wind lidar measurements on high-impact weather
forecasting: Regional OSSE and data assimilation studies in: Data
Assimilation fo
r Atmospheric, Oceanic and Hydrologic Applications (Vol. III), edited by: Park, S. K. and Xu, L., Springer, Cham, 259–283, https://doi.org/10.1007/978-3-319-43415-5_12, 2017.
Rani, S. I., Jangid, B. P., Kumar, S., Bushair, M. T., Sharma, P., George,
J. P., George, G., and Das Gupta, M.: Assessing the quality of novel Aeolus
winds for NWP applications at NCMRWF, Q. J. Roy. Meteor. Soc., 148, 1344–1367, https://doi.org/10.1002/qj.4264, 2022.
Reitebuch, O., Lemmerz, C., Nagel, E., Paffrath, U., Durand, Y., Endemann,
M., Fabre, F., and Chaloupy, M.: The airborne demonstrator for the
direct-detection Doppler wind lidar ALADIN on ADM-Aeolus. Part I: Instrument
design and comparison to satellite instrument, J. Atmos. Ocean Tech., 26,
2501–2515, https://doi.org/10.1175/2009JTECHA1309.1, 2009.
Reitebuch, O., Lemmerz, C., Lux, O., Marksteiner, U., Rahm, S., Weiler, F.,
Witschas, B., Meringer, M., Schmidt, K., Huber, D., Nikolaus, I., Geiss, A.,
Vaughan, M., Dabas, A., Flament, T., Stieglitz, H., Isaksen, L., Rennie, M.,
de Kloe, J., Marseille, G.-J., Stoffelen, A., Wernham, D., Kanitz, T.,
Straume, A.-G., Fehr, T., von Bismark, J., Floberghagen, R., and Parrinello,
T.: Initial assessment of the performance of the first wind lidar in space
on Aeolus, in: EPJ Web of Conferences, Volume 237, The 29th International
Laser Radar Conference (ILRC29), Heifei, Anhui Province, China, 24–28 June
2019, EPJ Web Conf., 237, 01010, https://doi.org/10.1051/epjconf/202023701010, 2020.
Rennie, M. P. and Isaksen, L.: The NWP impact of Aeolus level-2b winds at
ECMWF, ECMWF, Technical memorandum no. 864, 110 pp., https://doi.org/10.21957/alift7mhr, 2020.
Rennie, M. P., Isaksen, L., Weiler, F., de Kloe, J., Kanitz, T., and
Reitebuch, O.: The impact of Aeolus wind retrievals on ECMWF global weather
forecasts, Q. J. Roy. Meteor. Soc., 147, 3555–3586, https://doi.org/10.1002/qj.4142, 2021a.
Rennie, M. P., Stoffelen, A., Khaykin, S., Osprey, S., Wright, C., Banyard,
T., Straume, A. G., Reitebuch, O., Krisch, I., Parrinello, T., von Bismarck,
J., and Wernham D.: Demonstrated Aeolus benefits in atmospheric sciences,
in: 2021 IEEE International Geoscience and Remote Sensing Symposium
(IGARSS), Brussels, Belgium, 11–16 July 2021, IEEE, 763–766, https://doi.org/10.1109/IGARSS47720.2021.9554267, 2021b.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner,
J., Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X.-Y.: A
description of the advanced research WRF model version 4, National Center
for Atmospheric Research (NCAR), No. NCAR/TN-556+STR, 145 pp., https://doi.org/10.5065/1dfh-6p97, 2019.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek,
M., Gayno, G., Wegiel, J., and Cuenca, R. H.: Implementation and
verification of the unified NOAH land surface model in the WRF model, 14.2a, in: 20th Conference on Weather Analysis and Forecasting/16th Conference on
Numerical Weather Prediction (20WAF16NW), Seattle, Washington, U.S., 12–15
January 2004,
https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm, 2004.
WMO: Guide to meteorological instruments and methods of observation, 2014
edn., World Meteorological Organization (WMO), Geneva, Switzerland, 1177 pp., https://doi.org/10.25607/OBP-432, 2017.
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.
Witschas, B., Lemmerz, C., Geiß, A., Lux, O., Marksteiner, U., Rahm, S., Reitebuch, O., Schäfler, A., and Weiler, F.: Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics, Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, 2022.
Wu, S., Sun, K., Dai, G., Wang, X., Liu, X., Liu, B., Song, X., Reitebuch, O., Li, R., Yin, J., and Wang, X.: Inter-comparison of wind measurements in the atmospheric boundary layer and the lower troposphere with Aeolus and a ground-based coherent Doppler lidar network over China, Atmos. Meas. Tech., 15, 131–148, https://doi.org/10.5194/amt-15-131-2022, 2022.
Zhang, L. and Pu, Z.: An Observing System Simulation Experiment (OSSE) to
assess the impact of Doppler wind lidar (DWL) measurements on the numerical
simulation of a tropical cyclone, Adv. Meteorol., 2010, 1–14, https://doi.org/10.1155/2010/743863, 2010.
Zuo, H., Hasager, C. B., Karagali, I., Stoffelen, A., Marseille, G.-J., and de Kloe, J.: Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia, Atmos. Meas. Tech., 15, 4107–4124, https://doi.org/10.5194/amt-15-4107-2022, 2022.
