contributor author | Muñoz-Esparza, Domingo | |
contributor author | Sharman, Robert | |
date accessioned | 2019-09-19T10:06:50Z | |
date available | 2019-09-19T10:06:50Z | |
date copyright | 4/2/2018 12:00:00 AM | |
date issued | 2018 | |
identifier other | jamc-d-17-0337.1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4261673 | |
description abstract | AbstractA 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. | |
publisher | American Meteorological Society | |
title | An Improved Algorithm for Low-Level Turbulence Forecasting | |
type | Journal Paper | |
journal volume | 57 | |
journal issue | 6 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAMC-D-17-0337.1 | |
journal fristpage | 1249 | |
journal lastpage | 1263 | |
tree | Journal of Applied Meteorology and Climatology:;2018:;volume 057:;issue 006 | |
contenttype | Fulltext | |