Articles | Volume 14, issue 3
Atmos. Meas. Tech., 14, 2167–2183, 2021
https://doi.org/10.5194/amt-14-2167-2021

Special issue: Aeolus data and their application (AMT/ACP/WCD inter-journal...

Atmos. Meas. Tech., 14, 2167–2183, 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 et al.

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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
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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.