16 citations as recorded by crossref.

1. Interpretable EDR estimation from aircraft QAR data using deep learning and transform domain features Z. Zhuang et al. https://doi.org/10.1016/j.aei.2026.104512
2. Global response of upper-level aviation turbulence from various sources to climate change S. Kim et al. https://doi.org/10.1038/s41612-023-00421-3
3. Flight route EDR estimation using MHE to fuse three-dimensional wind information in the QAR data analysis H. Wei et al. https://doi.org/10.1371/journal.pone.0323147
4. Aviation Turbulence Forecasting over the Portuguese Flight Information Regions: Algorithm and Objective Verification M. Belo-Pereira https://doi.org/10.3390/atmos13030422
5. A Detection of Convectively Induced Turbulence Using in Situ Aircraft and Radar Spectral Width Data J. Kim et al. https://doi.org/10.3390/rs13040726
6. Aviation Turbulence Forecasting at Upper Levels with Machine Learning Techniques Based on Regression Trees D. Muñoz-Esparza et al. https://doi.org/10.1175/JAMC-D-20-0116.1
7. Characteristics of the derived energy dissipation rate using the 1 Hz commercial aircraft quick access recorder (QAR) data S. Kim et al. https://doi.org/10.5194/amt-15-2277-2022
8. Comparison of Eddy Dissipation Rate Estimated From Operational Radiosonde and Commercial Aircraft Observations in the United States H. Ko et al. https://doi.org/10.1029/2023JD039352
9. Estimating fine-scale changes in turbulence using the movements of a flapping flier E. Lempidakis et al. https://doi.org/10.1098/rsif.2022.0577
10. High-altitude balloon-launched uncrewed aircraft system measurements of atmospheric turbulence and qualitative comparison with infrasound microphone response A. Haghighi et al. https://doi.org/10.5194/amt-17-4863-2024
11. Estimation of Aircraft-Dependent Bumpiness Severity in Turbulent Flight H. Wang et al. https://doi.org/10.3390/app11041796
12. An 11-year analysis of in situ records of aviation-scale turbulence over Europe V. Gerogiannis & H. Feidas https://doi.org/10.1007/s00704-021-03676-z
13. The Optimization of Aircraft Acceleration Response and EDR Estimation Based on Linear Turbulence Field Approximation D. Wang et al. https://doi.org/10.3390/atmos12060799
14. Eddy Dissipation Rate in Aviation Applications for Estimation of Turbulence Intensity A. Ivanova https://doi.org/10.3103/S1068373925130059
15. Improving Numerical Weather Prediction–Based Near-Cloud Aviation Turbulence Forecasts by Diagnosing Convective Gravity Wave Breaking S. Kim et al. https://doi.org/10.1175/WAF-D-20-0213.1
16. Development and Evaluation of Global Korean Aviation Turbulence Forecast Systems Based on an Operational Numerical Weather Prediction Model and In Situ Flight Turbulence Observation Data D. Lee et al. https://doi.org/10.1175/WAF-D-21-0095.1