Surface Wind Monitoring at Small Regional Airport
Tallennettuna:
| Julkaisussa: | Atmosphere vol. 16, no. 8 (2025), p. 917-935 |
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| Päätekijä: | |
| Muut tekijät: | , |
| Julkaistu: |
MDPI AG
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| Aiheet: | |
| Linkit: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Tagit: |
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|---|---|---|---|
| 001 | 3243977155 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2073-4433 | ||
| 024 | 7 | |a 10.3390/atmos16080917 |2 doi | |
| 035 | |a 3243977155 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231428 |2 nlm | ||
| 100 | 1 | |a Choma Ladislav | |
| 245 | 1 | |a Surface Wind Monitoring at Small Regional Airport | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This study focuses on surface wind analysis at the small regional airport in Svidnik, used primarily for pilot training under daytime VFR conditions. Due to the complex local terrain and lack of prior meteorological data, an automatic weather station was installed, collecting over 208,000 wind measurements over a two-year period at ten-minute intervals. The dataset was processed using hierarchical filtering and statistical selection, and visualized via wind rose diagrams. The results confirmed a dominant southeastern wind component, supporting the current runway orientation (01/19). However, a less frequent easterly wind direction was identified as a safety concern, causing turbulence near the runway due to terrain and vegetation. This is particularly critical for trainee pilots during final approach and landing. Statistical analysis showed that easterly winds, though less common, appear year-round with a peak in summer. Pearson correlation and linear regression confirmed a significant relationship between the number of easterly wind days and their measurement frequency. Daytime winds were stronger than nighttime, justifying the focus on daylight data. The study provides practical recommendations for training flight safety and highlights the value of localized wind monitoring at small airports. The presented methodology offers a framework for improving operational awareness and reducing risk in complex environments. | |
| 653 | |a Wind direction | ||
| 653 | |a Meteorological data | ||
| 653 | |a Aircraft accidents & safety | ||
| 653 | |a Topography | ||
| 653 | |a Airports | ||
| 653 | |a Vegetation | ||
| 653 | |a Training | ||
| 653 | |a Pilot training | ||
| 653 | |a Automatic weather stations | ||
| 653 | |a Daytime | ||
| 653 | |a Statistical methods | ||
| 653 | |a Surface wind | ||
| 653 | |a Risk reduction | ||
| 653 | |a Statistics | ||
| 653 | |a Aviation meteorology | ||
| 653 | |a Turbulence | ||
| 653 | |a Accuracy | ||
| 653 | |a Risk management | ||
| 653 | |a Aircraft landing | ||
| 653 | |a Winds | ||
| 653 | |a Aviation | ||
| 653 | |a Data processing | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Monitoring | ||
| 653 | |a Flight training | ||
| 653 | |a Pilots | ||
| 653 | |a Visual flight rules | ||
| 653 | |a Flight safety | ||
| 653 | |a Wind measurement | ||
| 653 | |a Sensors | ||
| 653 | |a Daylight | ||
| 653 | |a Runways | ||
| 653 | |a Landing behavior | ||
| 653 | |a Easterlies | ||
| 653 | |a Wind shear | ||
| 653 | |a Wind analysis | ||
| 653 | |a Terrain | ||
| 700 | 1 | |a Antosko Matej | |
| 700 | 1 | |a Korba, Peter | |
| 773 | 0 | |t Atmosphere |g vol. 16, no. 8 (2025), p. 917-935 | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243977155/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3243977155/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243977155/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |