A detection of convectively induced turbulence using in situ aircraft and radar spectral width data

  • Jung Hoon Kim
  • , Ja Rin Park
  • , Soo Hyun Kim
  • , Jeonghoe Kim
  • , Eunjeong Lee
  • , Seungwoo Baek
  • , Gyuwon Lee

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

A commercial aircraft, departing from Seoul to Jeju Island in South Korea, encountered a convectively induced turbulence (CIT) at about z = 2.2 km near Seoul on 28 October 2018. At this time, the observed radar reflectivity showed that the convective band with cloud tops of z = 6–7 km passed the CIT region with high values of spectral width (SW; larger than 4 m s–1). Using the 1 Hz wind data recorded by the aircraft, we estimated an objective intensity of the CIT as a cube root of eddy dissipation rate (EDR) based on the inertial range technique, which was about 0.33–0.37 m2/3 s-1. Radar-based EDR was also derived by lognormal mapping technique (LMT), showing that the EDR was about 0.3–0.35 m2/3 s-1 near the CIT location, which is consistent with in situ EDR. In addition, a feasibility of the CIT forecast was tested using the weather and research forecast (WRF) model with a 3 km horizontal grid spacing. The model accurately reproduced the convective band passing the CIT event with an hour delay, which allows the use of two methods to calculate EDR: The first is using both the sub-grid and resolved turbulent kinetic energy to infer the EDR; the second is using the LMT for converting absolute vertical velocity (and its combination with the Richardson number) to EDR-scale. As a result, we found that the model-based EDRs were about 0.3–0.4 m2/3 s-1 near the CIT event, which is consistent with the estimated EDRs from both aircraft and radar observations.

Original languageEnglish
Article number726
Pages (from-to)1-22
Number of pages22
JournalRemote Sensing
Volume13
Issue number4
DOIs
StatePublished - 2 Feb 2021

Keywords

  • Convectively induced turbulence
  • Eddy dissipation rate
  • In situ aircraft data
  • Numerical weather prediction
  • Radar spectral width

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