Articles | Volume 13, issue 9
https://doi.org/10.5194/nhess-13-2223-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-13-2223-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Sep 2013
Research article |
| 11 Sep 2013
Wind shear over the Nice Côte d'Azur airport: case studies
A. Boilley
GAME/CNRM (Météo-France/CNRS), UMR3589, 42, Av. G. Coriolis, 31057 Toulouse Cedex 1, France
Degréane-Horizon, 730 rue de l'initiative, 83390 Cuers, France
now at: MINES ParisTech, O.I.E. – Observation Impacts Energy, CS 10207 06904 Sophia-Antipolis Cedex, France
J.-F. Mahfouf
GAME/CNRM (Météo-France/CNRS), UMR3589, 42, Av. G. Coriolis, 31057 Toulouse Cedex 1, France
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Cited
17 citations as recorded by crossref.
- Prediction of a Pilot’s Invisible Foe: The Severe Low-Level Wind Shear A. Khattak et al. 10.3390/atmos14010037
- Observation and Numerical Simulation of Terrain-Induced Windshear at the Hong Kong International Airport in a Planetary Boundary Layer without Temperature Inversions P. Chan & K. Hon 10.1155/2016/1454513
- A Machine Learning-Based Model for Flight Turbulence Identification Using LiDAR Data Z. Zhuang et al. 10.3390/atmos14050797
- Wind Shear Prediction from Light Detection and Ranging Data Using Machine Learning Methods J. Huang et al. 10.3390/atmos12050644
- Assessing wind field characteristics along the airport runway glide slope: an explainable boosting machine-assisted wind tunnel study A. Khattak et al. 10.1038/s41598-023-36495-5
- Study on the influence of topography on wind shear numerical simulations based on WRF–CALMET X. Wang et al. 10.5194/gi-13-277-2024
- Historical analysis (2001–2019) of low‐level wind shear at the Hong Kong International Airport K. Hon & P. Chan 10.1002/met.2063
- Estimating Wind Shear Magnitude Near Runways at Hong Kong International Airport Using an Interpretable Local Cascade Ensemble Strategy A. Khattak et al. 10.1007/s13143-024-00351-x
- Wind speed vector restoration algorithm N. Baranov et al. 10.1051/epjconf/201817606012
- Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study L. Li et al. 10.3390/atmos11121342
- Observation and Numerical Simulation of a Windshear Case at an Airport in the Qinghai-Tibet Plateau P. Chan et al. 10.3390/app142310981
- Improving Lidar Windshear Detection Efficiency by Removal of “Gentle Ramps” K. Hon & P. Chan 10.3390/atmos12111539
- Explainable Boosting Machine: A Contemporary Glass-Box Strategy for the Assessment of Wind Shear Severity in the Runway Vicinity Based on the Doppler Light Detection and Ranging Data A. Khattak et al. 10.3390/atmos15010020
- Low-Level Wind Shear Characteristics and Lidar-Based Alerting at Lanzhou Zhongchuan International Airport, China L. Li et al. 10.1007/s13351-020-9134-6
- Assessment of Crosswind Speed over the Runway Glide Path Using an Interpretable Local Cascade Ensemble Approach Aided by Wind Tunnel Experiments A. Khattak et al. 10.3390/atmos14101561
- Inter-Comparison of Ensemble Forecasts for Low Level Wind Shear against Local Analyses Data over Jeju Area Y. Lee et al. 10.3390/atmos11020198
- Prediction of Low Level Wind Shear Using High Resolution Numerical Weather Prediction Model at the Jeju International Airport, Korea G. Kim et al. 10.12985/ksaa.2021.29.4.088
17 citations as recorded by crossref.
- Prediction of a Pilot’s Invisible Foe: The Severe Low-Level Wind Shear A. Khattak et al. 10.3390/atmos14010037
- Observation and Numerical Simulation of Terrain-Induced Windshear at the Hong Kong International Airport in a Planetary Boundary Layer without Temperature Inversions P. Chan & K. Hon 10.1155/2016/1454513
- A Machine Learning-Based Model for Flight Turbulence Identification Using LiDAR Data Z. Zhuang et al. 10.3390/atmos14050797
- Wind Shear Prediction from Light Detection and Ranging Data Using Machine Learning Methods J. Huang et al. 10.3390/atmos12050644
- Assessing wind field characteristics along the airport runway glide slope: an explainable boosting machine-assisted wind tunnel study A. Khattak et al. 10.1038/s41598-023-36495-5
- Study on the influence of topography on wind shear numerical simulations based on WRF–CALMET X. Wang et al. 10.5194/gi-13-277-2024
- Historical analysis (2001–2019) of low‐level wind shear at the Hong Kong International Airport K. Hon & P. Chan 10.1002/met.2063
- Estimating Wind Shear Magnitude Near Runways at Hong Kong International Airport Using an Interpretable Local Cascade Ensemble Strategy A. Khattak et al. 10.1007/s13143-024-00351-x
- Wind speed vector restoration algorithm N. Baranov et al. 10.1051/epjconf/201817606012
- Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study L. Li et al. 10.3390/atmos11121342
- Observation and Numerical Simulation of a Windshear Case at an Airport in the Qinghai-Tibet Plateau P. Chan et al. 10.3390/app142310981
- Improving Lidar Windshear Detection Efficiency by Removal of “Gentle Ramps” K. Hon & P. Chan 10.3390/atmos12111539
- Explainable Boosting Machine: A Contemporary Glass-Box Strategy for the Assessment of Wind Shear Severity in the Runway Vicinity Based on the Doppler Light Detection and Ranging Data A. Khattak et al. 10.3390/atmos15010020
- Low-Level Wind Shear Characteristics and Lidar-Based Alerting at Lanzhou Zhongchuan International Airport, China L. Li et al. 10.1007/s13351-020-9134-6
- Assessment of Crosswind Speed over the Runway Glide Path Using an Interpretable Local Cascade Ensemble Approach Aided by Wind Tunnel Experiments A. Khattak et al. 10.3390/atmos14101561
- Inter-Comparison of Ensemble Forecasts for Low Level Wind Shear against Local Analyses Data over Jeju Area Y. Lee et al. 10.3390/atmos11020198
- Prediction of Low Level Wind Shear Using High Resolution Numerical Weather Prediction Model at the Jeju International Airport, Korea G. Kim et al. 10.12985/ksaa.2021.29.4.088
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