Improvements in Nonconvective Aviation Turbulence Prediction for the World Area Forecast System

Abstract

For the next generation of the World Area Forecast System (WAFS), the global Graphical Turbulence Guidance (G-GTG) has been developed using global numerical weather prediction (NWP) model outputs as an input to compute a set of turbulence diagnostics, identifying strong spatial gradients of meteorological variables associated with clear-air turbulence (CAT) and mountain-wave turbulence (MWT). The G-GTG provides an atmospheric turbulence intensity metric of energy dissipation rate (EDR) to the 1/3 power (m2/3 s–1), which is the International Civil Aviation Organization (ICAO) standard for aircraft reporting. Deterministic CAT and MWT EDR forecasts are derived from ensembles of calibrated multiple CAT and MWT diagnostics, respectively, with the final forecast provided by the gridpoint-by-gridpoint maximum of the CAT and MWT ensemble means. In addition, a probabilistic EDR forecast is produced by the percentage agreement of the individual CAT and MWT diagnostics that exceed a certain EDR threshold for turbulence (i.e., multidiagnostic ensemble). Objective evaluations of the G-GTG against global in situ EDR measurement data show that both deterministic and probabilistic G-GTG significantly improve the current WAFS CAT product, mainly because the G-GTG takes into account turbulence from various sources related to CAT and MWT. The probabilistic G-GTG forecast is more reliable at predicting light-or-greater (EDR > 0.15)- than moderate-or-greater (EDR > 0.22)-level turbulence, although it suffers from overforecasting. This will be improved in the future when we use this methodology with NWP ensembles and more observation data will be available for calibration. We expect that the new G-GTG forecasts will be beneficial to aviation users globally.

Retrieval of Eddy Dissipation Rate from Derived Equivalent Vertical Gust included in Aircraft Meteorological Data Relay (AMDAR)

“…1 shows that the raw DEVG covers a large portion of the SH, Africa, Europe, and the trans-Pacific and trans-Atlantic Oceans. Given that in situ EDR represents a large portion of the NH Kim et al, 2018), this raw DEVG can complement the SH turbulence information. Reporting time window at the cruising level is generally between 7 and 21 minutes, and each DEVG is the maximum value over each time window (Gill, 2016).…”

“…Indeed, the International Civil Aviation Organization (ICAO) assigned EDR as the 5 preferred and standard metric for turbulence reporting (ICAO, 2001(ICAO, , 2010Sharman et al, 2014). The EDR has been widely used in evaluations of the performances of global turbulence forecasting systems (e.g., Pearson and Sharman, 2017;Sharman and Pearson, 2017;Kim et al, 2018;Lee and Chun, 2018), as well as in many case studies on turbulence (e.g., Trier et al, 2012;Bramberger et al, 2018;Trier and Sharman, 2018).…”

Multi‐diagnostic multi‐model ensemble forecasts of aviation turbulence

“…In this study the newest generation Graphical Turbulence Guidance system 3 (GTG3) is used (Sharman and Pearson, 2017), not only forecasting shear turbulence but also including MWT (Sharman and Pearson, 2017). Studies combining two deterministic models (the National Oceanic and Atmospheric Administration Global Forecast System and the Met Office Unified Model) producing GTG diagnostics have been carried out to produce non-convective turbulence forecasts (Kim et al, 2018). They created probabilistic forecasts by using probability density functions for each diagnostic rather than using the probabilities from an ensemble numerical weather prediction model.…”

Retrieval of eddy dissipation rate from derived equivalent vertical gust included in Aircraft Meteorological Data Relay (AMDAR)

“…Since the DEVG can contain misleading values during the ascent and descent phases, previous studies have only considered the cruise-level DEVG values (e.g., Gill, 2014;Kim and Chun, 2016;Meneguz et al, 2016;Kim et al, 2017). The turbulence information defined by the DEVG has been utilized in statistical analyses on aviation turbulence (e.g., Kim and Chun, 2016;Kim et al, 2017) and in evaluations of the performance of NWP-based turbulence forecasts (e.g., Gill, 2014;Gill and Buchanan, 2014;Kim and Chun, 2016). Currently, the DEVG algorithm has been implemented on several international air carriers such as the Qantas, South African, British Airways, and other European-based airline aircraft.…”