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

Why is study about lightning important ?

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

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

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.

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)

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

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)

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

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. xTotalDay

ayLightningDqMonthlyFre =

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

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

Temporal Distribution of Lightning Events Jakarta Tj. Priok (2m) Jakarta Soekarno Hatta (8m)

Serang (40m) Curug (46m) Jatiwangi (50m)

Citeko (300m) Tj. Karang (96m)

Elev

atio

n ≥

50m

Elev

atio

n 10

- 50m

El

evat

ion

< 10

m

Jakarta Obs. (8m) Lightning Frequency is M

ore Distributed

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 St

rong

La

Nin

a Ye

ar

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

Lightning Events vs Active MJO Phases

IMC Indian 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

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)

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.

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.).

Thank You !

どうもありがとうございました