In this section
@article{Wong:2025:10.21105/joss.09282,
author = {Wong, HL and Palacios, R and Gryspeerdt, E},
doi = {10.21105/joss.09282},
journal = {Journal of Open Source Software},
title = {rojak: A Python library and tool for aviation turbulence diagnostics},
url = {http://dx.doi.org/10.21105/joss.09282},
volume = {10},
year = {2025}
}
TY - JOUR
AB - Aviation turbulence is atmospheric turbulence occurring at length scales large enough (ap proximately 100m to 1km) to affect an aircraft (Sharman, 2016). According to the National Transport Safety Board (NTSB), turbulence experienced whilst onboard an aircraft was theleading cause of accidents from 2009 to 2018 (NTSB, 2021). Clear air turbulence (CAT) is a form of aviation turbulence which cannot be detected by the onboard weather radar. Thus, pilots are unable to preemptively avoid such regions. In order to mitigate this safety risk, CAT diagnostics are used to forecast turbulent regions such that pilots are able to tactically avoidthem.rojak is a parallelised Python library and command-line tool for using meteorological data to forecast CAT and evaluating the effectiveness of CAT diagnostics against turbulence observations. Currently, it supports,1. Computing turbulence diagnostics on meteorological data from the European Centrefor Medium-Range Weather Forecasts’s (ECMWF) ERA5 reanalysis on pressure levels(Hersbach, 2023). Moreover, it is easily extendable through a software update to supportother types of meteorological data.2. Retrieving and processing turbulence observations from Aircraft Meteorological DataRelay (AMDAR) data archived at the National Oceanic and Atmospheric Administration(NOAA)(NCEP Meteorological Assimilation Data Ingest System (MADIS), 2024) andAMDAR data collected via the Met Office MetDB system (Met Office, 2008)3. Computing 27 different turbulence diagnostics, such as the three-dimensional fronto genesis equation (Bluestein, 1993), turbulence index 1 and 2 (Ellrod & Knapp, 1992),negative vorticity advection (Sharman et al., 2006), and Brown’s Richardson tendencyequation (Brown, 1973).4. Converting turbulence diagnostic values into the eddy dissipation rate (EDR) — the International Civil Aviation Organization’s (ICAO) official metric for reporting turbulence (Meteorological Service for International Air Navigati
AU - Wong,HL
AU - Palacios,R
AU - Gryspeerdt,E
DO - 10.21105/joss.09282
PY - 2025///
SN - 2475-9066
TI - rojak: A Python library and tool for aviation turbulence diagnostics
T2 - Journal of Open Source Software
UR - http://dx.doi.org/10.21105/joss.09282
UR - https://doi.org/10.21105/joss.09282
VL - 10
ER -