13 citations as recorded by crossref.

1. Improving the accuracy of short-term numerical weather forecasts for the territory of Belarus using the mesoscale WRF model and earth remote sensing data S. Lysenko & P. Zaiko https://doi.org/10.29235/1561-8323-2023-67-1-66-73
2. The impact of Aeolus winds on near-surface wind forecasts over tropical ocean and high-latitude regions H. Zuo & C. Hasager https://doi.org/10.5194/amt-16-3901-2023
3. Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile, and Leipzig, Germany H. Baars et al. https://doi.org/10.5194/amt-16-3809-2023
4. Assimilating Aeolus Satellite Wind Data on a Regional Level: Application in a Mediterranean Cyclone Using the WRF Model C. Stathopoulos et al. https://doi.org/10.3390/atmos14121811
5. A Short‐Term Regional Precipitation Prediction Model Based on Wind‐Improved Spatiotemporal Convolutional Network Y. Qiu et al. https://doi.org/10.1029/2022EA002411
6. Optimizing Aircraft Route Planning Based on Data-Driven and Physics-Informed Wind Field Predictions J. Ma et al. https://doi.org/10.3390/math13030367
7. Frequency-discriminator design rules for Incoherent Doppler Wind Lidar: FPI, fringe, and iodine under a unified framework J. Chen & C. Xie https://doi.org/10.1016/j.optcom.2025.132749
8. Assimilation of Aeolus Rayleigh‐Clear Winds Using a Footprint Operator in AROME‐Arctic Mesoscale Model M. Mile et al. https://doi.org/10.1029/2021GL097615
9. Wind observations from hot‐air balloons and the application in an NWP model E. de Bruijn et al. https://doi.org/10.1002/met.2128
10. Assimilating WIVERN windpseudo-observations in WRF model: an application to the outstanding case of the Medicane Ianos S. Federico et al. https://doi.org/10.5194/wcd-7-165-2026
11. Impact of WIVERN Wind Observations on ARPEGE Numerical Weather Prediction Model Forecasts Using an Ensemble of Data Assimilation Method N. Sasso et al. https://doi.org/10.1002/qj.4991
12. Validation of the Aeolus L2A products with the eVe reference lidar measurements from the ASKOS/JATAC campaign P. Paschou et al. https://doi.org/10.5194/amt-18-4731-2025
13. Exploring the Potential of Machine Learning Post-Processing to Generate ERA5-Consistent Atmospheric Profiles from Geostationary Satellite Retrievals D. Han et al. https://doi.org/10.3390/rs18142310