Turbulence analysis on the flight of etihad airways in Bangka Island using the WRF case study May 4, 2016 B R T Andari 1,2 , N J Trilaksono 2 and M A Munandar 3 1 Master Program in Earth Science, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, ID 2 Weather and Climate Prediction Laboratory, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, ID 3 Aviation Meteorological Center, Badan Meteorologi Klimatologi dan Geofisika, ID 1. Introduction 2. Data and Methods 3. Result and Discussion 4. Conclusions 5. References [1] Eick D 2013 Turbulence Related Accidents & Incidents Natl. Transp. Saf. Board [2] Kim J H, Chun H Y, Sharman R D and Keller T L2011 Evaluations of Upper-Level Turbulence Diagnostics Performance Using the Graphical Turbulence Guidance ( GTG ) System and Pilot Reports ( PIREPs ) over East Asia J. Appl. Meteorol. Climatol. 1936–52 [3] Lane T P, Sharman R D, Trier S B, Fovell R G and Williams J K 2012 Recent advances in the understanding of near-cloud turbulence Bull. Am. Meteorol. Soc. 93 499–515 [4] Sharman R and Lane T 2016 Aviation Turbulence: Process , Detection, Prediction [5] Molarin K and Svensson G 2013 Case study of CAT over the North Atlantic Ocean [6] Keller J L 1981 Prediction and Monitoring of Clear-Air Turbulence: an Evaluation of the Applicability of the Rawinsonde System. J. Appl. Meteorol. 20 686–92 [7] Storer L N, Williams P D and Gill P G 2019 Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change Pure Appl. Geophys. 176 2081–95 [8] Ellrod G P and Knapp D I 1992 An Objective Clear-Air Turbulence Forecasting Technique: Verification and Operational Use Weather Forecast. 7 150–65 [9] Yang X, Fei J, Huang X, Cheng X, Carvalho L M V and He H 2015 Characteristics of mesoscale convective systems over China and its vicinity using geostationary satellite FY2 J. Clim. 28 4890–907 [10]Sharman R D, B.Cornman L, G.Meymaris, Pearson J and Farrar T 2014 Description and Derived Climatologies of Automated In Situ Eddy-Dissipation-Rate Reports of Atmospheric Turbulence J. Appl. Meteorol. Climatol. 1416–32 [11] Trier S B, Sharman R D dan Lane T P 2012 Influences of Moist Convection on a Cold-Season Outbreak of Clear-Air Turbulence ( CAT ) Mon. Weather Rev. 2477–97 1.Turbulence that occurs on Etihad Airways aircraft is a near cloud turbulence (NCT) event due to cloud growth to the west of the incident site and high updraft activity at the turbulence scene. 2.By using the EDR parameter which has a value of 0.05  2 3  −1 , Richardson number with a value of less than 0.25 and TI 1 with a maximum value of 4 x 10 -7 s -2 found that turbulence was in the strong category. Accurate estimates of disturbances due to weather factors in flight operations are important to be noticed because Indonesia is geographically located in the equatorial region so that it has effective solar radiation that makes convective clouds easy to form. Convective clouds can trigger turbulence then produce disruption and even accidents on flights. This research uses a case study on the Etihad Airways flight on the Bangka Island at May 4, 2016. At the time of the incident, there was turbulence at 39,000 feet altitude and the aircraft did not enter overcast area. The turbulence in this study is simulated using the Weather Research and Forecasting (WRF) model which is downscaled up to 3 km with a microphysic parameterization of WRF Single- Moment 6 Class (WSM6). Data • Sounding data on 04 May 2016 at the Pangkal Pinang meteorological station. • IR1 channel of Himawari-8 satellite image data is used to identify convective clouds that can cause turbulence • NCEP-FNL data from 03 May 2019 to 04 May 2016 Methods WRF Model Simulation and Verification.This research is limited to 01° S-04° S dan 103° E-107° E on May 4, 2016, at 06.40 UTC and uses WRF ARW 3.9.1. In this study verification in two steps, the first step is verification of quantitative meteorological parameters using correlation and linear regression values while the second step is qualitative verification using pattern match of cloud fraction from the output of Analysis of Atmospheric Conditions. To determine the effect of vertical wind shear, it is viewed from from the spatial plot of wind direction and speed at different heights. Also, it will be seen from the vertical plot of wind speed and hodograph. Futhermore, it will be spatially plotted the value of vertical wind shear and static stability at an altitude of 11.5 km to 12.25 km. and a vertical airflow plot of west-east and south-north at each altitude. Turbulence Identification.Turbulence can be identified using turbulent kinetic energy which can be used to calculate the eddy dissipation rate, Richardson number, and turbulence index Figure 1. Plot of convective nuclei distribution from IR channel 1 Himawari-8 satellite data from 06.10 UTC to 07.00 UTC, the vector is the wind direction of FNL 06.00 UTC data, the cross is the location of turbulence events and the rhombus is the location of the Pangkal Pinang meteorological station. 3 .1 Convective cloud identification using the Himawari-8 Satellite Convective cloud growth is heading northwest at 06.40 UTC to 07.00 UTC to the west of the turbulence event location according to the wind direction. This is following the results of Sharman and Lane [4] who state that convective turbulence can be associated with activity outside the convective cloud called near cloud turbulence (NCT). 3 .2 WRF Model Verification Figure 2. Scatter-plot of WRF model results with sounding data at the Pangkal Pinang meteorological station on May 4, 2016, with (a) wind direction parameters, (b) wind speed parameters, and (c) temperature parameters. The correlation value between WRF and observation obtained : • wind direction is 0.6 • wind speed is -0.03 • temperature is 0.81 3 .3 Atmospheric conditions during the Turbulence Incident Figure 3. Convective nuclei distribution 06.40 UTC with a cross are the locations of turbulence events. Figure 4. Plot of wind direction at 11.5 km (green vector) and 12.25 km (black vector) and wind speed (shaded) at a) 06.30 UTC and b) 06.40 UTC with a cross are the locations of turbulence events. This shows that there was wind shear vertically but without changes in wind direction between altitudes at 06.40 UTC in the study area. Figure 5. Plot of wind speed on May 4, 2016, vertical to the altitude of 06.40 UTC at the turbulence event location (-2.375 ° N and 105,812 ° E) with a gray rectangle representing the height of the aircraft when experiencing turbulence (a) and hodograph plot on May 4, 2016, at 06.40 UTC at the turbulence scene (-2.375 ° N and 105,812 ° E) a) b) Figure 6. Plot of vertical wind shear at 06.10 UTC to 07.00 UTC at an altitude of 11.5 km to 12.25 km with the black box representing the time of turbulence and the cross is the location of the turbulence event and the rhombus sign is the location of the Pangkal Pinang meteorological station. South-North West-East Figure 7.Plot of south north and west-east vertical airflow versus altitude with dashed line is the location of turbulence (-2.375 LS, 105.812 BT) and the yellow mark is the altitude of the aircraft when experiencing turbulence. Figure 8. Static stability plot on 4 May 2016 at 06.00 UTC to 07.00 UTC at an altitude of 11.5 km to 12.25 km with a black box showing the time of turbulence and across is the location of turbulence events and a rhombus is the location of the Pangkal Pinang meteorological station. the WRF model and the convective nuclei of Himawari 8 satellite imagery 3 .4 Quantification of Turbulence Intensity Parameters Figure 9. Turbulent kinetic energy (a), Richardson number (b) and Turbulent index 1 (c) on May 4, 2016 at 06.40 UTC at an altitude of 11.5 km to 12.25 km. Figure 11. The vertical plot of Richardson number on May 4, 2016, at (a) 06.30UTC and (b) 06.40UTC with the dotted line is the location of turbulence and the brown box shows the height of the aircraft when experiencing turbulence. During the turbulence, the TKE value at the time of the turbulence is 5 m 2 /s 2 so it has an EDR value of 0.05  2 3  −1 . Meanwhile, Ri value is less than 0.25 and TI 1 with a maximum value of 4 x 10 -7 s -2 found that turbulence was in the strong category. WRF Himawari-8 From quantitative verification using wind direction and wind speed parameters that have positive linear regression and a quite good correlation and qualitative verification using pattern match between cloud fraction and convective nuclei distribution has the same pattern match so that it can be said that the WRF model can simulate turbulence at the time and area of study. a) b) c) There is vertical wind shear value and the static stability at the location of the incident is quite low at an altitude of 11.5 km to 12.25 km with turbulence occurring at 06.40 UTC. This indicates that the atmosphere is unstable. When turbulence occurs at 06.40 UTC, the value of vertical airflow vertical airflow of south-north and west-east shows a significant increase in updraft than before and after turbulence. View publication stats View publication stats