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An Improved Algorithm for Low-Level Turbulence Forecasting.
- Source :
- Journal of Applied Meteorology & Climatology; Jun2018, Vol. 57 Issue 6, p1249-1263, 15p, 3 Charts, 7 Graphs, 1 Map
- Publication Year :
- 2018
-
Abstract
- A low-level turbulence (LLT) forecasting algorithm is proposed and implemented within the Graphical Turbulence Guidance (GTG) turbulence forecasting system. The LLT algorithm provides predictions of energy dissipation rate (EDR; turbulence dissipation to the one-third power), which is the standard turbulence metric used by the aviation community. The algorithm is based upon the use of distinct log-Weibull and lognormal probability distributions in a statistical remapping technique to represent accurately the behavior of turbulence in the atmospheric boundary layer for daytime and nighttime conditions, respectively, thus accounting for atmospheric stability. A 1-yr-long GTG LLT calibration was performed using the High-Resolution Rapid Refresh operational model, and optimum GTG ensembles of turbulence indices for clear-air and mountain-wave turbulence that minimize the mean absolute percentage error (MAPE) were determined. Evaluation of the proposed algorithm with in situ EDR data from the Boulder Atmospheric Observatory tower covering a range of altitudes up to 300 m above the surface demonstrates a reduction in the error by a factor of approximately 2.0 (MAPE = 55%) relative to the current operational GTG system (version 3). In addition, the probability of detection of typical small and large EDR values at low levels is increased by approximately 15%-20%. The improved LLT algorithm is expected to benefit several nonconventional turbulence-prediction sectors such as unmanned aerial systems and wind energy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15588424
- Volume :
- 57
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Journal of Applied Meteorology & Climatology
- Publication Type :
- Academic Journal
- Accession number :
- 130461211
- Full Text :
- https://doi.org/10.1175/JAMC-D-17-0337.1