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

Abstract

Abstract. Some of the Aircraft Meteorological Data Relay (AMDAR) data include a turbulence metric of the derived equivalent vertical gust (DEVG), in addition to wind and temperature. As the cube root of the eddy dissipation rate (EDR) is the International Civil Aviation Organization standard turbulence reporting metric, we attempt to retrieve the EDR from the DEVG for more reliable and consistent observations of aviation turbulence globally. Using the DEVG in the AMDAR archived from October 2015 to September 2018 covering a large portion of the Southern Hemisphere and North Pacific and North Atlantic Oceans, we convert the DEVG to the EDR using two methods, after conducting quality control procedures to remove suspicious turbulence reports in the DEVG. The first method is to remap the DEVG to the EDR using a lognormal mapping scheme, while the second one is using the best-fit curve between the EDR and DEVG developed in the previous study. The DEVG-derived EDRs obtained from the two methods are evaluated against in situ EDR data reported by United States-operated carriers. For two specified regions of the trans-Pacific Ocean and Europe, where both the DEVG-derived EDRs and in situ EDRs were available, the DEVG-derived EDRs obtained by the two methods are generally consistent with in situ EDRs, with slightly better statistics by the first method than the second one. This result is encouraging for extending the aviation turbulence data globally with the single preferred EDR metric, which will contribute to the improvement of global aviation turbulence forecasting as well as to the construction of the climatology of upper-level turbulence.

Estimating fine-scale changes in turbulence using the movements of a flapping flier

“…Indeed, this proportionality is often used in meteorology to estimate the dissipation rate from ultrasonic anemometers (e.g. [35]), and similar approaches have been used to measure clear air turbulence using the eddy dissipation rate from aircraft [26,27]. We, therefore, took the proportionality of the fit for the power law relationship (between the power and the frequency (−5/3) as a measure of the turbulent energy.…”

“…It is clear from flying in aircraft that turbulence can cause fluctuations in altitude and body motion. In fact, the clear air turbulence has been estimated using routine measurements of aircraft motion [26] and the variation in vertical acceleration [27]. Similarly, Laurent et al [2] showed that there was a linear relationship between the body accelerations of a single 5 kg golden eagle ( Aquila chrysaetos ) during gliding flight and the atmospheric turbulence (specifically, the body accelerations exhibited power spectra characteristic of turbulence and that increased in proportion to the turbulence intensity).…”

The implications of costly airflows for space-use and movement decisions in birds

“…Nonetheless, the good agreement between turbulence estimates from the anemometer measurements, the pilot's scores, reanalysis data and proxy values, gives confidence in our overall approach and demonstrates that simple proxies can be employed to assess turbulence strength at fine scales. Our proxies are similar in concept to those developed for aviation (Kim et al, 2020), demonstrating the widespread utility of measurements derived from onboard accelerometers and pressure sensors.…”

“…Indeed, this proportionality is often used in meteorology to estimate the dissipation rate from ultrasonic anemometers (e.g. Oncley et al, 1996), and similar approaches have been used to measure clear air turbulence using the eddy dissipation rate from aircraft (Huang et al, 2019, Kim et al, 2020. We therefore took the proportionality of the fit for the power law relationship (between the power and the frequency (-5/3) as a measure of the turbulent energy.…”

“…This is analogous to the turbulence observations that are routinely provided verbally by pilots in the form of pilot reports (PIREPs). Here, the turbulence level is determined by a pilot's subjective experience of the aircraft response to turbulence (Kim et al, 2020). Computations of our qualitative measure of turbulence strength were conducted in Python version 2.7.15 (Van Rossum, 2007) (see supplementary material for the code).…”