3D výstražný systém pro námrazu, clear-air turbulenci (CAT), konvektivně indukovanou turbulenci (CIT) nebo kroupy pro potřeby letectví
| Název práce v češtině: | 3D výstražný systém pro námrazu, clear-air turbulenci (CAT), konvektivně indukovanou turbulenci (CIT) nebo kroupy pro potřeby letectví |
|---|---|
| Název v anglickém jazyce: | 3D Meteoalarm for Icing, Clear Air Turbulence (CAT), Convective Induced Turbulence (CIT), or Hail |
| Klíčová slova: | námraza; clear air turbulence; konvektivní turbulence; kroupy; letectví; python |
| Klíčová slova anglicky: | icing, clear air turbulence, convective induced turbulence, hail, python, aviation |
| Akademický rok vypsání: | 2022/2023 |
| Typ práce: | bakalářská práce |
| Jazyk práce: | |
| Ústav: | Katedra fyziky atmosféry (32-KFA) |
| Vedoucí / školitel: | doc. Mgr. Peter Huszár, Ph.D. |
| Řešitel: | |
| Konzultanti: | Mgr. Aleš Kuchař, Ph.D. |
| Zásady pro vypracování |
| 1) Study the existing methods for analytical computation of such weather alarms from available weather data. Choose phenomenon from the list to focus on.
2) Propose the mathematical solution to such problem. 3) Design and implement algorithm(s) the solution using the NetCDF library in Python and other available libraries needed for such computation. 4) Integrate the algorithmic solution to an existing weather processing pipeline providing connection to visualization tools for the pilots. 5) Scale-up the solution to provide the required scale in volume and speed of computation needed by the real deployment (order of minutes for one computation every 15 minutes) 6) Experimentally verify that the method works good enough for practical usage by the pilots. |
| Seznam odborné literatury |
| [1] http://www.meteoalarm.eu
[2] Sharman, R. D., & Pearson, J. M. (2016). Prediction of energy dissipation rates for aviation turbulence: Part I. Forecasting Non-convective turbulence. Journal of Applied Meteorology and Climatology, JAMC-D-16-0205.1. http://doi.org/10.1175/JAMC-D-16-0205.1 [3] Krozel, J. A., Deierling, W., Sharman, R., & Williams, J. K. (2015). Detecting Convective Induced Turbulence via Total Lightning Sensing. In AIAA Guidance, Navigation, and Control Conference (pp. 1–12). Reston, Virginia: American Institute of Aeronautics and Astronautics. http://doi.org/10.2514/6.2015-1548 [4] Bernstein, B. C., McDonough, F., Politovich, M. K., Brown, B. G., Ratvasky, T. P., Miller, D. R., … Cunning, G. (2005). Current Icing Potential: Algorithm Description and Comparison with Aircraft Observations. Journal of Applied Meteorology, 44(7), 969–986. http://doi.org/10.1175/JAM2246.1 [5] Punge, H. J., Bedka, K. M., Kunz, M., & Reinbold, A. (2017). Hail frequency estimation across Europe based on a combination of overshooting top detections and the ERA-INTERIM reanalysis. Atmospheric Research, 198, 34–43. http://doi.org/10.1016/j.atmosres.2017.07.025 |
| Předběžná náplň práce v anglickém jazyce |
| The most important phenomenon like that are icing, CAT, CIT and hail. Such phenomenon does not need to be necessarily predicted and localized precisely in the atmosphere, but for practical use only rough location of such phenomenon must be predicted and visualized to the pilots as icons. Such functionality is currently provided by systems like Meteoalarm [1], however not in 3D and for different weather phenomenon. The computation must be fast enough to be usable for the pilots in real-time, technically limiting the computation to order of minutes. The volume of interest is the area of Europe from the ground to approximately 45000ft (~13km) height for 5 hours window to the future. Prediction of each of mentioned phenomenon requires a substantial amount of work, therefore the student can choose and focus only on one of the mentioned phenomenon. |