Articles | Volume 14, issue 3
https://doi.org/10.5194/amt-14-2167-2021
https://doi.org/10.5194/amt-14-2167-2021
Research article
 | 
18 Mar 2021
Research article |  | 18 Mar 2021

Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents

Anne Martin, Martin Weissmann, Oliver Reitebuch, Michael Rennie, Alexander Geiß, and Alexander Cress

Related authors

Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts
Anne Martin, Martin Weissmann, and Alexander Cress
Weather Clim. Dynam., 4, 249–264, https://doi.org/10.5194/wcd-4-249-2023,https://doi.org/10.5194/wcd-4-249-2023, 2023
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Validation and Intercomparisons
Performance evaluation of MeteoTracker mobile sensor for outdoor applications
Francesco Barbano, Erika Brattich, Carlo Cintolesi, Abdul Ghafoor Nizamani, Silvana Di Sabatino, Massimo Milelli, Esther E. M. Peerlings, Sjoerd Polder, Gert-Jan Steeneveld, and Antonio Parodi
Atmos. Meas. Tech., 17, 3255–3278, https://doi.org/10.5194/amt-17-3255-2024,https://doi.org/10.5194/amt-17-3255-2024, 2024
Short summary
Uncertainties in temperature statistics and fluxes determined by sonic anemometer due to wind-induced vibrations of mounting arms
Zhongming Gao, Heping Liu, Dan Li, Bai Yang, Von Walden, Lei Li, and Ivan Bogoev
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-47,https://doi.org/10.5194/amt-2024-47, 2024
Revised manuscript accepted for AMT
Short summary
Impacts of anemometer changes, site relocations and processing methods on wind speed trends in China
Yi Liu, Lihong Zhou, Yingzuo Qin, Cesar Azorin-Molina, Cheng Shen, Rongrong Xu, and Zhenzhong Zeng
Atmos. Meas. Tech., 17, 1123–1131, https://doi.org/10.5194/amt-17-1123-2024,https://doi.org/10.5194/amt-17-1123-2024, 2024
Short summary
Validation of Aeolus L2B products over the tropical Atlantic using radiosondes
Maurus Borne, Peter Knippertz, Martin Weissmann, Benjamin Witschas, Cyrille Flamant, Rosimar Rios-Berrios, and Peter Veals
Atmos. Meas. Tech., 17, 561–581, https://doi.org/10.5194/amt-17-561-2024,https://doi.org/10.5194/amt-17-561-2024, 2024
Short summary
Estimating the turbulent kinetic energy dissipation rate from one-dimensional velocity measurements in time
Marcel Schröder, Tobias Bätge, Eberhard Bodenschatz, Michael Wilczek, and Gholamhossein Bagheri
Atmos. Meas. Tech., 17, 627–657, https://doi.org/10.5194/amt-17-627-2024,https://doi.org/10.5194/amt-17-627-2024, 2024
Short summary

Cited articles

Baars, H., Herzog, A., Heese, B., Ohneiser, K., Hanbuch, K., Hofer, J., Yin, Z., Engelmann, R., and Wandinger, U.: Validation of Aeolus wind products above the Atlantic Ocean, Atmos. Meas. Tech., 13, 6007–6024, https://doi.org/10.5194/amt-13-6007-2020, 2020. a
Baker, W. E., Atlas, R., Cardinali, C., Clement, A., Emmitt, G. D., Gentry, B. M., Hardesty, R. M., Källén, E., Kavaya, M. J., Langland, R., Ma, Z., Masutani, M., McCarty, W., Pierce, R. B., Pu, Z., Riishojgaard, L. P., Ryan, J., Tucker, S., Weissmann, M., and Yoe, J. G.: Lidar-Measured Wind Profiles: The Missing Link in the Global Observing System, B. Am. Meteorol. Soc., 95, 543–564, https://doi.org/10.1175/BAMS-D-12-00164.1, 2014. a
Bormann, N., Saarinen, S., Kelly, G., and Thépaut, J.-N.: The Spatial Structure of Observation Errors in Atmospheric Motion Vectors from Geostationary Satellite Data, Q. J. Roy. Meteor. Soc., 131, 706–718, https://doi.org/10.1175/1520-0493(2003)131<0706:TSSOOE>2.0.CO;2, 2003. a
Dabas, A., Denneulin, M., Flamant, P., Loth, C., Garnier, A., and Dolfi-Bouteyre, A.: Correcting winds measured with a Rayleigh Doppler lidar from pressure and temperature effects, Tellus A, 60, 206–215, https://doi.org/10.1111/j.1600-0870.2007.00284.x, 2008. a
Dirksen, R. J., Sommer, M., Immler, F. J., Hurst, D. F., Kivi, R., and Vömel, H.: Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde, Atmos. Meas. Tech., 7, 4463–4490, https://doi.org/10.5194/amt-7-4463-2014, 2014. a
Download
Short summary
This study provides an overview of validation activities to determine the Aeolus HLOS wind errors and to understand the biases by investigating possible dependencies and testing bias correction approaches. To ensure meaningful validation statistics, collocated radiosondes and two different global NWP models, the ECMWF IFS and the ICON model (DWD), are used as reference data. To achieve an estimate for the Aeolus instrumental error the representativeness errors for the comparisons are evaluated.