1. LIGHTNING CLIMATOLOGY AROUND JAKARTA
BASED ON 13-YEARS SYNOP OBSERVATION AND ITS RELATION TO
GSMaP RAINFALL DATA
Ardhi Adhary Arbain1 , Cecep Sujana1 and Shuichi Mori2
1Agency for the Assessment and Application of Technology (BPPT), Indonesia
2Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Japan
The 4th Global Precipitation Measurement (GPM) Asia Workshop
on Precipitation Data Application Technique
13-14 January 2014, Tokyo, Japan

2. Why is study about lightning important ?

3. Background
Lightning could be a good precursor for strong winds and heavy rainfall (Price et al. 2009)
Lightning data could be used as a proxy of the presence and the absence of deep convection
(Mansell et al. 2006).
~ 1-day lag
Price et al. 2009
Mansell et al. 2006
Observed Rainfall Simulation without
Lightning
Simulation with Lightning Data

4. Why is Indonesian Maritime Continent
(in particular, Jakarta area) important for this study ?

5. Background
Bogor  322 days of lightning in one year
Bandung  218 days of lightning in one year
Christian et al. 2003 (OTD/satellite observation)
Hidayat and Ishii, 1998 (ground observation)
Jakarta
Bandung
Bogor
Lightning frequency over Indonesian Maritime Continent (IMC) is quite high (Hidayat and
Ishii 1998, Zoro 1999, Petersen and Rutledge 2001, Christian et al. 2003, Takayabu 2006,
etc.).
Jakarta capital city area is the most populous region in Indonesia
and the center of vital facilities and activities of Indonesian people.

6. Recently, Virts et al. (2013a, b) showed
comprehensive lightning climatology on
diurnal, intraseasonal, and seasonal
variations based on WWLLN. However,
they also reported a problem with
WWLLN detection efficiency (< 10%)
and LIS/OTD small sampling (< 0.1% of
the time fly over tropics) because
lightning is quite local and sporadic
phenomena.
Therefore, we firstly examine in situ
lightning data based on SYNOP
observed by BMKG (Indonesian Met
Office)
Background
Virts et al. 2013
a)
b)
c)
(flashes/km2yr)
(strokes/km2yr)

7. Objectives
• Clarify the climatology of lightning and meso-scale
characteristics of thunderstorm over IMC, in
particular over the capital city Jakarta where social
damage is quite serious.
• Investigate the relationship of lightning events with
GSMaP rainfall in terms of :
 Inter-annual variation
 Seasonal variation
 Intra-seasonal variation

8. Datasets
Main Data :
• SYNOP datasets (2000 – 2012, 8 stations around Jakarta, from
the total of 140 stations)
• GSMaP MVK v5.222.1 daily rainfall products with spatial
resolution of 0.1x0.1 degree (2001 – 2009)
• TRMM Lightning Imaging Sensor (not used in this
presentation)
Additional Data :
• Real Time Multivariate MJO Index (2000 – 2012)
• ETOPO1 Global Relief Model gridded dataset (1-arc minute)

9. Area of Interest
Tanjung Priok
Jakarta Observatory
Soekarno-
Hatta
Citeko
Serang
Tanjung Karang
Curug
Cirebon
Husein Sastranegara
Atang Sanjaya
Halim Perdanakusumah
Bandung Geof.
Darmaga
≥ 10 years data (8 stations)
< 10 years data (5 stations)
meters
INDIAN OCEAN
SUMATERA
JAVA
INDIAN OCEAN
JAVA SEA

10. Lightning Climatology
• All station has 13 years observation data, except for Jakarta Observatory (12 years) and Tj. Priok (11 years)
• Lightning day analysis  at least one lightning event observed in one day (TS, LT Code etc)
• Line plot  color indicates the elevation of stations
Citeko
Cirebon
Tj Karang
Serang
Curug
Jakarta
INDIAN OCEAN
JAVA SEA
%100. x
TotalDay
ayLightningD
qMonthlyFre =

11. Lightning Climatology vs Elevation
• High elevation (Mountainous region)  Frequency peaks in November and April
• Low elevation (Coastal region)  Frequency peaks in November, February and April
Citeko
Cirebon
Tj Karang
Serang
Curug
Jakarta
INDIAN OCEAN
JAVA SEA

12. Lightning Climatology vs Proximity to Sea
• Lightning events are more frequent over inland region than coastal region
Citeko
Cirebon
Tj Karang
Serang
Curug
Jakarta
INDIAN OCEAN
JAVA SEA

13. Temporal Distribution of Lightning Events
Jakarta Tj. Priok (2m) Jakarta Soekarno Hatta (8m)
Serang (40m) Curug (46m) Jatiwangi (50m)
Citeko (300m)Tj. Karang (96m)
Elevation≥50m
Elevation10-50mElevation<10m Jakarta Obs. (8m)
LightningFrequencyisMoreDistributed

14. Lightning Events Temporal Distribution
Proximity to Sea < 10km Proximity to Sea 10-50 km
Proximity to Sea ≥ 50km Further from the sea, lightning events
become more frequent and distributed
throughout the year
StrongLaNinaYear
Strong La Nina increase the frequency
of lightning events at all locations in 2010
El Nino years : 2002, 2004, 2006, 2009
La Nina years : 2000, 2005, 2007, 2008, 2010, 2011
GSMaP Rainfall

15. Lightning Events vs Active MJO Phases
IMCIndian Ocean Western Pacific
• Lightning events become most frequent during phase 3 (Indian
ocean), then gradually decreased until phase 5 (IMC)
Lightning Freq. Anomaly = (Lightning Freq. during MJO – Averaged Lightning Freq.)x100% Citeko
Cirebon
Tj Karang
Serang
Curug
Jakarta
INDIAN OCEAN
JAVA SEA

16. Summary and Discussion
• The high variability of lightning events around Jakarta are affected
much by local conditions e.g. topography, proximity to sea etc.
• Seasonal Variation  The highest frequency of lightning events is
occurred just before and after the peak of rainy season (boreal
winter) over inland region. Meanwhile, coastal region has the most
frequent lightning during the peak of rainy season (probably
affected by Cross Equatorial Monsoon Surge, Hattori et al. 2011)
• Inter-annual Variation  Strong La Nina increased the frequency
and temporal distribution of lightning events.
• Intra-seasonal Variation  Lightning frequency increases much
while active MJO occurred over Indian Ocean (Phase 3), and it
gradually decreases while MJO’s passing through Indonesian
Maritime Continent (Phase 4 and 5)

17. Summary and Discussion
(Morita et al. 2006)
We found that the lightning frequency
was at its highest during Phase 3 of
MJO (Indian Ocean) in parallel with
maximum rainfall.
Schematic of MJO life cycle described by
Morita et al. (2006) indicates that lightning
events become more frequent just before
and after the mature stage of MJO.
High local variability of lightning over
IMC probably caused such different
results.

18. Future Study
• Further analysis of lightning events by utilizing SYNOP data
from many other stations in Indonesia.
• Further analysis of lightning events in more detailed scale
(both spatial and temporal) using TRMM LIS, VLF Receiver and
Dual-Polarimetric Radar.
• Further investigation of the relationship between lightning
events and other meteorological/oceanographical parameters
(surface temperature, SST, etc.) and phenomena (IOD, Tropical
Waves, etc.).

19. Thank You !
どうもありがとうございました