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07 Dec 2018 • Read : 3817 x ,


Analysis of Atmospheric Conditions during Lion Air JT-610 Aircraft Accidents


The tragic accident Lion Air JT-610 aircraft in Karawang waters has stolen the world's attention. How could it not, there was an accident October 29, 2018 it happened about ten minutes after takeoff and killed 182 passengers, 2 drivers, and 5 crew members in Karawang waters (Kompas, 2018) . To respond the incident, the Atmospheric Science and Technology Center (PSTA) conducted an analysis of the atmospheric conditions during the Lion Ait JT 610 plane crash which crashed at around 6:35 p.m. in Karawang waters about 12 minutes after taking off from Jakarta to Pangkal Pinang ( BBC News, 2018; Detik News, 2018) with locations located at 05 o 46 "15 'LS and 107 o 07" 16' BT and experiencing contact loss at elevation 2,500 meters above sea level (CNN Indonesia, 2018).


As is known, this unfortunate event is not the first event in Indonesia. Previously, a number of airplane accidents had hit Indonesian airlines, whether they caused casualties or not. Based on data from the National Transportation Safety Commission (NTSC), flight accidents are divided into two categories: accident <!-- em--> and serious incident. Accident <!-- em--> refers to unforeseen events related to aircraft operations since take off <!-- em--> to landing <!-- em--> which result in fatalities. Whereas serious <!-- em--> incident <!-- em--> refers to accidents that are operational but do not cause casualties (Pakan, 2008).

1.  Weather is the Third Rank of Accident Causes

In general, aircraft accidents can be caused by four factors: human, technical, environmental, and facilities. Based on data on aviation accident investigations in 2010-2016, the largest aircraft accidents caused by human factors were 67.12 percent (Figure 1). Even so, environmental factors cannot be ignored because the weather factor ranks third, namely 12.33 percent, such as turbulence, wind shear, storm, and other causes of airplane accidents in Indonesia (NTSC, 2016 ).

Therefore, understanding of weather / meteorological information is very necessary because it will be a consideration in determining the route of potential hazards that can occur both when taking off, in flight , <!-- em--> or > landing <!-- em-->. The role of meteorological observers has become urgent in delivering flight meteorological information to various related parties for the effectiveness and safety of aviation.

The recipients of meteorological information include: aircraft operators, aircraft personnel, flight navigation service units, search and rescue service units, and airport organizers (Law No.1 2009, 2009). While the information conveyed includes: wind speed and direction, cloud type, air temperature, current weather conditions, air pressure, visibility. <!-- em--> This information can be obtained from Automated Weather Observation System <!-- em--> (AWOS), which constantly updates data to the plane, for example for landing.

Figure 1. Aviation accident investigations, causes and types of events investigated for flight accidents in 2010-2016.

2. Meteorological Causes of Accidents

There are several meteorological parameters that can cause aircraft accidents both during take off, in flight <!-- em--> and landing <!-- em-->, so meteorological parameters often become workloads and loads mental for the pilot. The most dominant meteorological parameters that burden the pilot and crew during flight are wind, visibility or visibility, and atmospheric stability (Abadi Dwi Saputra, 2015).

Changes in wind direction and speed when <!-- em--> and landing <!-- em--> in the form of downburst <!-- em--> can hit the plane so that it disturbs the position and movement stability. Limitations of visibility or visibility can also potentially cause fatal errors such as the case of the Sukhoi SSJ 100 plane which crashed into Mount Salak in 2012 (Kompas, 2012). Atmospheric stability is also the reason for flight accidents because it is related to the presence of clouds, causing turbulence.

One of the strongest turbulence that is deceptive but can be fatal to the aircraft is the phenomenon of Clear Air Turbulence (CAT). CAT is heavy turbulence that occurs suddenly in a cloudless area which causes a loud pounding on the plane like turbulence in cirrus clouds, inside and around lenticular <!-- em--> clouds and on clean air around a storm (< em> thunderstorms <!-- em-->). CAT does not include turbulence caused by storms, low temperature inversion, heat, strong surface wind, or local terrain features (SKYbrary, 2018).

In general, CAT is caused by terrain and jet flow ( jet stream <!-- em-->). The field factor is related to the surface which can interfere with the horizontal flow of air above it and cause turbulence. The severity of turbulence depends on the strength of air flow, terrain roughness, rate of change and contour curvature, and elevation of the plateau above the surrounding plains.

In addition, complex lightning storms can also be a cause of CAT because of the presence of Cumulonimbus <!-- em--> cloud cells (Cb) which have strong vertical currents. Based on incident data on aircraft interference, CAT has a height of around 5,000 feet above the peak of Cb. Whereas jet stream <!-- em--> is often found in high latitudes, namely fast and narrow moving air currents, usually near the tropopause layer (troposphere and stratospheric boundary layer-red), which is produced by temperature gradients between air masses.

CAT can have an impact on aircraft structure damage, physical accidents of flight crews or passengers, and disruption of aircraft crew performance. Airplane accidents that have occurred due to CAT in Indonesia are Airbus A330-200 aircraft (Etihad Airways EY 474) on May 4, 2016 around Bangka Island. The plane with 24 passengers and 7 crew members aired from Abu Dhabi International Airport to Soekarno-Hatta International Airport, Jakarta based on report (Nistanto, 2016) through passengers who were victims of a plane accident. Again, CAT is a type of turbulence that is difficult to detect even by pilots because it occurs suddenly in a clear sky without clouds.

3. Clear Air Turbulence

CAT can have an impact on aircraft structure damage, physical accidents of flight crews or passengers, and disruption of aircraft crew performance. Airplane accidents that have occurred due to CAT in Indonesia, namely the Airplane flight, how to detect CAT? CAT can be identified by calculating Richardson numbers (Ri). In fact, Ri is commonly used as a method for predicting CAT on most commercial and military aircraft flight levels. Ri magnitude shows atmospheric ability to maintain turbulence by calculating the ratio between static and wind shear ( wind shear) <!-- em--> vertically. Ri estimates turbulence based on the relationship between a significant CAT area and a stable static air area with strong A330-200 shear <!-- em--> vertical (Etihad Airways EY 474) on May 4, 2016 around Bangka Island. The plane with 24 passengers and 7 crew members aired from Abu Dhabi International Airport to Soekarno-Hatta International Airport, Jakarta based on report (Nistanto, 2016) through passengers who were victims of a plane accident. Again, CAT is a type of turbulence that is difficult to detect even by pilots because it occurs suddenly in a clear sky without clouds (Keller, 1981).

Ri has a low number when wind shear <!-- em--> is high, whereas Ri is high when stability is high in the stratosphere (Office, 2004). Previous research has shown that Ri is useful for predicting turbulence, as evidenced by the calculation threshold value approaching 4, exceeding the critical point (Rc = 0.25) which proves that there is sudden or sudden turbulence known as CAT (Widseth & Morss, 1999).

4. Downburst and Microburst

Figure 2. Microburst illustration when the aircraft is landing


Microburst <!-- em--> is often associated with cumulus clouds and Cb. However, not all of these types of clouds will produce microburst <!-- em-->, making it difficult to detect mocroburst. <!-- em--> Based on previous research, radar doplers can be used to detect inside convective clouds and air movement so that they can alert the potential of microburst <!-- em-->. In addition, the Wind-Vector Potential-Temperature Energy Analysis (WPEA) and X-band dual-polarization <!-- em--> radar methods can also be used to analyze downburst formation characteristics <!-- em--> em> (Wang et al. 2018) by performing a combination of analysis based on conventional observation data and analysis of environmental conditions that trigger downburst.

By paying attention to some weather disturbances that cause aircraft accidents, the research is focused on detecting turbulence (CAT), downburst and microburst, atmospheric stability, by analyzing various data, such as cloud data from the Himawari Satellite (cloud growth, cloud top temperature) , and differences in cloud brightness), radiosonde, and data processing from SADEWA LAPAN.


Cloud data used to analyze atmospheric conditions include: cloud growth data, thickness of clouds and cloud top temperatures from the Himawari Satellite. In addition, Radiosonde data in Cengkareng is also used from University Wyoming <!-- em--> ( http: //weather.uwyo .edu / upperair / sounding.html ) is also used to see atmospheric conditions at 7.00 WIB on October 29 2018.

Also described are wind conditions and Ri's calculations with limited experiments using the WRF weather model ( and Research Forecasting <!-- em-->). Determination of the Ri value is used to determine turbulence, where the atmosphere is said to experience turbulence when the number Ri is less than the critical number Richardson <!-- em--> (Rc = 0.25). Determination of turbulence by calculating Richardson number <!-- em--> (Ri) is solved by the equation as follows:



1. Keberadaan Awan

Himawari IR 1 shows the cloud peak temperature associated with the presence of Cb clouds. The results show at 20.00-21.00 UTC (03.00-04.00 WIB) at the crash site (red dot in Figure 3) there are clouds with peak temperatures ranging from 210-230 K or equivalent to –63 to -43 o <!-- sup--> C, starting at 5.00 WIB the cloud at the location point has begun to disappear until 06.50 WIB (Figure 3 and Figure 4).

Figure 3 The peak temperature of the cloud every hour from 02.00 - 06.00 WIB on October 29, 2018

Figure 4. The peak temperature of the cloud every ten minutes from 05.00 - 05.50 WIB on October 29, 2018

2. Cloud thickness

Cloud thickness is calculated from the difference between the IRB and IR2 TBB values. The smaller the difference in TBB value, the clouds are thicker. Figure 5 shows that on October 28 at 2:00 a.m. there was a thick cloud at the crash site (red dot). This cloud is thicker until 03.00 WIB and starting at 04.00 WIB the cloud decays and runs low until 05.00 WIB.

Figure 5. Thickness of clouds every hour from 02.00 - 05.00 WIB on October 29, 2018

Based on the TBB IR1-IR2 value, it appears that since 06.00 WIB there are thinner clouds around the crash site (red dot). This thinner cloud is expanding around the location until 06.20 WIB, and at 6.50 there is no thick cloud at the scene.

Figure 6. Cloud thickness every ten minutes from 05.00 - 05.50 WIB on October 29, 2018


3. Pertumbuhan Awan

Figure 7 Growth of clouds every hour, starting at 02.00 - 06.00 WIB on October 29, 2018

Figure 7 describes the growth process of clouds growing from 02.00-06.00 WIB. It can be seen that the clouds grew around the area where the Lion Air JT 610 crashed from 02.00 to 04.00 WIB and peaked at 04.00 WIB. The clouds then begin to decay at 05.00-06.00 WIB, or about 33 minutes before the incident. More detailed analysis of cloud growth conditions is carried out every 10 minutes and is explained in Figure 8.

Figure 8 Cloud grows per 10 minutes starting from 06.10 - 06.30 WIB on October 29, 2018

Cloud growth every 10 minutes starting at 06.10 WIB illustrates that on 23 minutes before the event, the cloud looks clean ( clear <!-- em-->). This also happens in the 20th, 30th, 40th and 50th minutes. This condition has remained the same since 05.00 WIB, so to prove the influence of weather conditions in the upper troposphere on the fall of Lion Air JT 610 aircraft, analysis of other weather conditions is needed around the clouds grow.

4. Vertical Profile and Atmospheric Stability

Figure 9 Sounding data in Cengkareng at 07.00 WIB on 29 October 2018

The sounding data at 07.00 WIB showed the height of the cloud base at the observation location, which was at an altitude level of 985 hPa with a temperature of 23.3 o <!-- sup--> C, where at this height the air parcel reached saturation after adiabatic dry removal. The amount of energy available to lift the air parcel vertically is 816 J / kg. This value falls into the category of positive <!-- em--> which is the lowest category compared to large CAPE <!-- em--> and extreme CAPE, <!-- em--> where the higher the CAPE value, the more vertical speeds high in storm areas.

Negative values on the air parcel lift index (Lifting Index, or LI-red written) indicate the degree of tropospheric instability. The increasingly negative LI value indicates that the troposphere is increasingly unstable and the parcel will be more easily lifted from the boundary layer of the atmosphere. The LI value indicates the severity of the storm when a storm is formed. KI is an index used as a marker for potential vertical motion or convection of air masses. The greater the value of K-Index (KI), the greater the potential for convection. A KI value below 20 indicates a small chance of a storm.

Total-Totals Index (TT) is an index to determine the convection process which is a combination of vertical totals and cross-totals <!-- em--> indexes. The greater the TT index value indicates the more unstable atmospheric conditions. The TT index value of less than 50 indicates a fairly stable atmospheric condition with the potential for small gutur growth. Severe Weather Threat Index <!-- em--> (SWEAT) is an index to see the potential for bad weather. SWEAT value 203 shows the potential for small bad weather.

5. WRF Weather Model Experiment Results (Weather Research and Forecasting)

An experimental simulation of meteorological conditions in the area of the crash of the JT 610 aircraft using a high resolution WRF model is 1 km at an altitude of 875 - 1000 m and 1400-1500 m with the parameters of the Brunt Vaisala and Richardson Number frequency values. The Brunt-Vaisala frequency value is at an altitude of 875-1000 m which is around 0.008-0.016 / s (figure 10). Likewise at an altitude of 875-1000 m, the Frequency value Brunt Vaisala <!-- em--> is in the range 0.008-0.016 / s (figure 11).

Figure 10. Value of Brunt Vaisala Frequency at an altitude of 875-1000 km every ten minutes at 06.00-06.50 WIB on 29 October 2018

Figure 11. Value of Brunt Vaisala Frequency at an altitude of 1400-1500 km every ten minutes at 06.00-06.50 WIB on October 29 2018

The Ri parameter simulation results show that at an altitude of 875-1000 m and 1400-1500 m Ri values at the scene have reached more than 16. Ri is used to detect atmospheric stability and turbulence. Ri values of more than 16 at the scene indicate that atmospheric conditions are very stable or not turbulent.

Figure 12. Richardson Number value at an altitude of 875-1000 km every ten minutes at 06.00-06.50 WIB on October 29, 2018

Figure 13. Richardson Number value at an altitude of 1400-1500 km every ten minutes at 06.00-06.50 WIB on October 29, 2018

IV. Conclusion

A complete analysis of atmospheric conditions shows that at the time of the Lion Air JT-610 plane crash, there were no thick clouds ( clear sky <!-- em-->) and there was no cloud growth process around the site. The presence of thick clouds is formed in the early hours around 02.00 WIB and reaches a peak at 04.00 WIB and decays at 05.00 WIB. In addition, cloud growth does not occur at the time of an aircraft accident. Three phenomena that could potentially interfere with flight, namely CAT, downburst <!-- em-->, microburst <!-- em--> did not occur. So it can be concluded that there is no weather factor that has the potential to disrupt flights in the event of the Lion Air JT-610 plane crash.

This report was prepared by the Disaster Team for the Lion Air JT-610 accident:

  1. Dr. Teguh Harjama
  2. Dr. Ibnu Fathrio
  3. Dr. Lilik Slamet Suprihatin, M.Si.
  4. Farid Lasmono, ST
  5. Erma Yulihastin, M.Si.
  6. Risyanto, M.Sc.
  7. Haries Satyawardhana, M.Si
  8. Anis Purwaningsih, S.Si.
  9. Dita Fatria Andarini, S.Si.
  10. Shailla Rustiana, S.Si. M.Stat.

Responsible Agency: Head of LAPAN's Atmospheric Science and Technology Center.


Abadi Dwi Saputra, S. P. (2015). Pengaruh Kondisi Cuaca Penerbangan terhadap Beban Kerja Mental Pilot. Jurnal Transportasi , 159-168.

BBC News. (2018, Oktober 29). Pesawat Lion Air rite Jakarta-Pangkal Pinang jatuh di perairan Karawang. Retrieved from BBC News Indonesia:

CNN Indonesia. (2018, Oktober 29). CNN Indonesia. Retrieved from

Detik News . (2018, Oktober 30). Detik News. Retrieved from

Fujita, T. T. (1978). Manual of Downburst Identification for Project NIMROD. SMRP Research Paper, 156.

Great Britain Meteorological Office. (1994). Handbook of Aviation Meteorology. London: HMSO.

Keller, J. (1981). Prediction and Monitoring of Clear-Air. J. Appl. Meteor, 20, 686-692.

Komite Nasional Keselamatan Transportasi. (2016). Data Investigasi Kecelakaan Penerbangan Tahun 2010-2016. Jakarta: Media release KNKT.

Kompas. (2012, 12 18). Ini Tiga Kesalahan Fatal Pilot Sukhoi Superjet 100. Retrieved from

Kompas. (2018, Oktober 29). Total Jumlah Penumpang Lion Air JT 610 yang Jatuh 189 Orang. Retrieved from Kompas:

Nistanto, R. (2016, Mei 5). Retrieved from

NOAA. (2018). Downburst Wind Awareness. Retrieved from National Weather Service, National Oceanic and Atmospheric Administration:

Office, M. (2004). Clear Air Turbulance. London: Met Office.

Pakan, W. (2008). Faktor Penyebab Kecelakaan Penerbangan di Indonesia Tahun 2000-2006. Jurnal Penelitian Perhubungan Udara, 1-18.

SKYbrary. (2018, Agustus 11). Clear Air Turbulence (CAT). Retrieved from SKYbrary:

UU No.1 2009. (2009). Undang-Undang Republik Indonesia Nomor 1 Tahun 2009 tentang Penerbangan. Pasal 288.

Widseth, C., & Morss, D. (1999). Airbone Verification of Atmospheric Turbulance Using The Richardson Number. National Weather Digest, 23, 38-44.

Airplane accidents can also occur when taking off and landing due to low wind shear caused by downburst. Downburst <!-- em--> is a downdraft <!-- em--> which causes strong wind deviations (Fujita, 1978). Based on the spatial scale, downburst <!-- em--> which has a diameter of less than 4 km is called microburst <!-- em--> with wind speeds of more than 275 km / h and a span of 15-20 minutes (Great Britain Meteorological Office, 1994).

Significant changes in wind speed and direction when the microburst <!-- em--> phenomenon can endanger the aircraft both take off <!-- em--> and landing <!-- em-->. In the landing <!-- em--> stage (Figure 2), when the plane passes through the downdraft <!-- em--> zone, it will meet headwind <!-- em--> (front wind) so that the plane will be lifted. Inexperienced pilots will respond by lowering the speed of the aircraft. This can be dangerous because the aircraft will get tailwind <!-- em--> (wind from the tail) which causes the aircraft's lift power to drop so that the plane crashes (NOAA, 2018).

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