URSI GASS 2023, Sapporo, Japan, 19 – 26 August 2023

Total Lightning Distribution and Heavy Rainfall Characteristics Associated With MulticellularThunderstorms
Debrupa Mondal(1), Yasuhide Hobara(1,2), Hiroshi Kikuchi(2), Jeff Lapierre(3)(1) University of Electro-Communications, Tokyo, Japan; e-mail: debrupamondaljam@gmail.com;
hobara@ee.uec.ac.jp(2) Center for Space Science and Radio Engineering, University of Electro-Communications, Tokyo, Japan;
e-mail: hkikuchi@uec.ac.jp(3) Earth Networks, Germantown, MD 20874, USA; e-mail: jlapierre@easrthnetworks.com

Abstract
Recently, detailed spatio-temporal analysis, using X-band
multi-parameter radar-derived 3D volume scan and total
lightning data in Japan, have shown the peak IC (In-Cloudlightning) occurs 5-10 mins prior to maximum ground
precipitation for individual cells of a thunderstorm during
heavy rainfall events, which can be useful for monitoringand short-time prediction of ground precipitation. But wefound merging and/ or splitting between the cells with total
lightning distribution, is a common phenomenon ofmulticellular TSs (ThunderStorms) which needs to betaken into account for more accurately predicting the storm
evolution. In this paper, we have analyzed the preliminary
observation results of two isolated, multicellular TS eventswith heavy precipitation (~100 mm) that showed merging
and splitting between cells in their life cycle. The abrupt
decrease or increase of IC lightning and precipitation
volume at the time steps of splitting and merging
respectively, were normalized with consideration of cellarea ratio (before and after merging or separation), which
resulted in a reasonable and similar trend for time series
plot of IC vs ground precipitation. We also obtained a timelag between the peak IC and ground PV after applying thecorrection criteria. Thus, the proposed method will bepromising for prediction and nowcasting the heavy ground
precipitation using lightning data for multicellular TSs.

1Introduction

With the rising intensity and severity of short-term heavy
rainfall events, the need for accurate earlier prediction ofoccurrence as well as the quantitative parameter such as
amount of rainfall is becoming obvious. Investigating thecorrelation and spatio-temporal dependencies ofprecipitation along with total lightning studies have shownthat total lightning data can be used as a precursor of heavy
precipitation [1-3]. There are studies which examined therelationship between total lightning behavior and radarreflectivity data to examine the signature of thunderstorm
intensity for mesoscale convective events such as squll
lines (line of thunderstorms), supercells [4, 5] as well as
precipitation characteristics for convective multicell
thunderstorms [6]. Multicellular thunderstorms possess
cells in different stages of their life cycle (developing stage,

mature stage, dissipation stage) at a time. During apreliminary study for isolated thunderstorms, we observedthat merging between cells and splitting of a cell during thethunderstorm’s life cycle is a common phenomenon. Since
these merging and splitting lead to a sudden change in theconsidered cell area, while using the spatial and temporal
distribution of total lightning data for prediction, there is ahigh chance of false forecasting. This study attempts amethodology for the more accurate evaluation of temporaldependence of total lightning (mainly IC) and groundrainfall.

2Observational Data
2.1 eXtended RAdar Information Network(XRAIN)
In this study we have collected precipitation data from theMinistry of Land, Infrastructure, Transport, and Tourism’s
eXtended RAdar Information Network which cover mostparts of Japan around 14 major cities. The network is
composed of 26 C-band radars and 39 X-band
multiparameter (X-MP) radars. The X-MP radars produce
3D volume scan data ranging from 0° to 20° by scanning
twelve elevation angles.
X-band and C-band radar-derived high resolution(temporal resolution=1min, spatial resolution=250m)
composite ground rainfall intensity data (mm/h) is alsocollected from XRAIN.

2.2 Japanese Total Lightning Network (JTLN)
Total lightning data associated with the events werecollected from JTLN which consists of 16 Earth Networks
Total Lightning Sensors over Japan (Figure 1 showing 11sensors, data set in 2017) deployed by the University ofElectro-Communications and jointly operated with EarthNetwork.
These ground-based sensors can detect lightning pulses
over a very wide frequency range, from 1 Hz to 12 MHzi.e., from ELF to HF series with 500 m spatial resolution.
We have collected total lightning (TL) parameters such as
types of lightning (IC (In-Cloud) and CG (Cloud toGround)), time of occurrence (UT), location (latitudelongitude) for each lightning discharge.

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Figure 1. JTLN sensor distribution over Japan

3Results

We have analyzed high-resolution precipitation data andtotal lightning activity during the life cycle of two
multicellular thunderstorm events with heavy groundrainfall (max ~100mm/h) that occurred on June 2, 2022 in
Gunma prefecture (event 1) and August 22, 2020 in Gifu
prefecture (event 2) in Japan.

3.1 Event 1 Analysis: Consideration ofSplitting
For the detailed analysis of this thunderstorm, we took
every 5-min full volume scan data of Yattajima radar(36.2647 E, 139.1972 N) and produced Constant Altitude
Plan Position Indicator (CAPPI) plots. To visualize theevolution of the precipitation core, maximum radarreflectivity projection on the horizontal plane (NS-EW)
with the spatial distribution of total lightning activity wasproduced.

The panels of Figure 2 show the projection of maximum
radar reflectivity on the horizontal plane with the spatial
distribution of IC (blue circle), +CG (red asterisk), -CG(black asterisk) for the time steps before, during and after
splitting of the cell. The horizontal axis represents the WE distance (km) from the radar location and the vertical axis
represents the N-S distance (km) from the radar (the radaris located at (0,0)).
During the TS, IC lightning started occurring at around17:30, near the northwest of the radar location (20 km W,10 km N) which gradually moved south-eastward and thenumber of IC lightning also increased gradually. Around
18:15 a compact IC lightning core is observed. Around
18:20 the IC lightning flashes start concentrating in two
adjacent separate cores and at 18:25 two separate cores areobserved. The southward core diminishes in the next 5mins
whereas the northward core is sustained till 18:45 and IC
lightning gradually decreases.
Next, we have analyzed the temporal evolution of groundprecipitation volume (PV) with the TL, IC, and CG rates.
Figure 3(a) shows the time series of ground PV (solid blueline) and IC pulse rates (black dashed line) per 5 min for
the analyzed cell. The peak of IC (around 703 pulses/5 min)occurred around 18:15 and then a sudden drop in flash rate
was observed at 18:20 which resulted from the splitting ofcells (blue dashed vertical line shows the time of splitting).
To resolve this, during tracking a precipitation cell that isseparated into two cells at time t, we have considered thefollowing area correction process. If at the time step (t-5min), the cell area is a and in the next time step i.e. at t, themain cell area becomes a after splitting, and theprecipitation volume drops from PV at (t-5) to PV at t, thencorrected PV ( PV ') will be
PV2 a1(1)PV2′
a2
The IC flash rate is also corrected similarly by multiplying
with the same area ratio.
121

2

2

Figure 3(a) Temporal evolution of ground PV and IC pulse
rate

Figure 2. Maximum radar reflectivity projections on thehorizontal plane along with the lightning distributions

Figure 3(b) shows the temporal evolution of ground PV andIC lightning same as Figure 3(a) but considering area
correction after splitting. The shaded portion represents thevalues that are not the real values. This correction resulted

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Xplore under the license granted by the “Agreement Granting URSI and IEICE Rights Related to Publication of ScholarlyWork.”

in a similar temporal dependence trend as well as a time lagof 5 min between IC peak and ground precipitation peak.

Figure 3(b) Temporal evolution of ground PV and IC pulse
rate considering area correction

3.2 Event 2 Analysis: Consideration ofMerging
For the detailed analysis using the 5-min full volume scandata we considered Bisai radar (35.2994 E, 136.7344 N)
data for this thunderstorm.
During this multicellular TS, IC lightning started occurringaround 16:30 at two cell locations, one in northeast
direction of radar (35-40 km N, 10 km E) and the other one
in northwest (10 km W, 35 km N) of radar location. Around16:50 both the cores became well developed withconcentrated IC distribution. The left cell starts shiftingslightly north-eastward from 16:45 and around 16:55 as theIC pulses tend to shift westward for the right cell also, boththe cells start merging. At 17:00 JST both the cells arecompletely merged. Figure 4 shows the maximum radarreflectivity projections on horizontal plane along with thelightning distribution same as Figure 2 for the time steps
before, during and after merging of the cells.

We have analyzed the temporal evolution of ground
precipitation volume (PV) with the TL, IC, and CG rates
for both the cells of this thunderstorm. Figure 5(a) andFigure 6(a) show the time series of ground PV with IC andCG flash rates per 5 min for the leftward cell and right one
respectively. For the left one, with an IC lightning jump,observed at 16:50 (a rapid increase from nearly 187 pulses
to 487 pulses in the next 5 min), the ground PV also
increased very rapidly within this 5 min. For the rightward
cell, both IC and ground PV start increasing gradually withtime and similarly at 16:50 a sharp increase in IC pulse rateand PV are observed. Though for both the cells ground
precipitation peak comes 10 min later than the peak IC, thespatial distribution shows that these lightning jumps may
be the result of merging between the cells around 16:55(blue dashed vertical line shows the time of merging).
To verify this, we have carried out the similar area
correction process mentioned for splitting. Figures 5(b) and6(b) show the temporal evolution of corrected ground PV,
IC and CG flash rates for the two cells analyzed here.

Figure 5(a) Temporal evolution of ground PV, IC and CG
flash rates of left cell

Figure 5(b) Temporal evolution of corrected ground PV,
IC and CG flash rates

Figure 4. Maximum radar reflectivity projections on
horizontal plane along with the lightning distributions

Figure 6(a) Temporal evolution of ground PV, IC and CG
flash rates of right cellThis paper's copyright is held by the author(s). It is published in these proceedings and included in any archive such as IEEE
Xplore under the license granted by the “Agreement Granting URSI and IEICE Rights Related to Publication of ScholarlyWork.”precipitation using TL, it is very important to analyze such
events for a more accurate prediction of ground rainfall. In
this current study, we demonstrate that, PV multiplicationby area ratio normalizes these abrupt changes to someextent and successfully obtain the precursory signature ofheavy rainfall for multicellular thunderstorms. Therefore,
our proposed methodology will be promising to improve
the prediction and nowcasting of heavy rainfall using
lightning data.

Acknowledgements
Figure 6(b) Temporal evolution of corrected ground PV,IC and CG flash rates
In Figure 5(b) and Figure 6(b) the values of ground PV, ICand CG flash rates are real values from 16:30 to 16:50, theshaded area represents the values of these parameters thatare corrected from the time of merging (16:55 JST). We
found that for the left cell, the lightning jump after 16:50
may be a false one. The IC lightning increased only from
187 flashes to around 192 flashes (not real value) in thenext 5 min. The peak IC lightning and peak ground PVobserved at 17:00 JST and 17:10 JST respectively. Theoccurrence of peaks remained the same whereas the peak
precipitation volume became sufficiently low, from
5.73×105 m3 (real value) to around 2.26×105 m3.
For the rightward cell also, instead of nearly 200 flash
increase in 5min, we found the flash rate increase may be
only 279 pulses/5 min to 289 pulses/5 min after 16:50.
Though after correction, the peak of PV (16:50) comes
earlier than the peak IC (17:00), a continuous high rainfall
trend is observed until 17:10. For this cell from spatial
distribution we observe a compact core around 16:50, andthe IC flashes start decreasing and shifting a bit westward
afterward. If we consider this time step (16:50) as themature stage of the cell, in the next time steps i.e. in thedissipation stage the cell area may decrease. Since forcorrection, we are considering the area of the cell in theprevious time step of merging (here, the area of the maturestage), it may result in a higher than actual IC flash rate.

4Discussion

We acknowledge the support from the Ministry ofEducation, Culture, Sports, Science, and Technology(AiQuSci Scholarship). The authors are grateful to theMinistry of Land, Infrastructure, Transport and Tourism
for providing XRAIN data and also to the KDDI
foundation for supporting partially this research project.
The authors also thank P. Le Floch and E. DiGangi of EN,
Tada Farm, Noshiro City Children’s Center, Niigata
Science Museum, NAOJ Mizusawa, JAIST, Gunma Univ.,
Rissho Univ., ISEE (Nagoya Univ.), NIT Tsuyama
College, Kochi Univ., Ama town, Yamaguchi Univ., TokaiUniv. for their help JTLN observations in Japan.

References[1] B. Gungle, E. P. Krider, “Cloud-to-ground Lightningand Surface Rainfall in Warmseason Florida
Thunderstorms,” Journal of Geophysical Research:Atmospheres, 111, 2006.
[2] T. Ogawa, Y. Hobara, H. Iwasaki, S. Heckman, M.
Stock, “Statistical Study of The Relationship Between
Total Lightning and Heavy Rainfall,” 16th
International Conference on Atmospheric Electricity,Nara, Japan, 2018
[3] C. Liu, C. Sloop, S. Heckman, “Application ofLightning in Predicting High Impact Weather,”OBS/IMO/TECO-2014.
[4] S. M. Steiger, R.E. Orville, L.D. Carey, “Totallightning signatures of thunderstorm intensity over
North Texas, Part II: Mesoscale convective systems,”
Mon. Weather Rev. 2007, 135, 3303–3324.

Liu et al [3] showed continuous monitoring of total
lightning data, in particular IC lightning makes it possible
to track and predict the various properties of high-impact[5] L. D. Carey, M. J. Murphy, T. L. McCormick, N. W. S.
weather events. Earlier for the isolated thunderstorm events
Demetriades, “Lightning location relative to storm
analysis, we found that consideration of a smaller spatialstructure in a leading-line, trailing-stratiform mesoscale
scale (individual cell) rather than the storm scale, resulted
convective system,” JGR Atmospheres, 110, Isssue D3,
in a peak of IC (or, IC lightning jump) occurrence nearly2005.
5~10 min earlier than peak ground PV which may be used
as a precursory parameter for short-term prediction of[6] J. Sun, J. Chai, L. Leng, G. Xu, “Analysis of Lightning
maximum ground rainfall. But for the multicellularand Precipitation Activities in Three Severe Convective
thunderstorms having merging between cells and/or
Events Based on Doppler Radar and Microwave
splitting of a cell in their life cycle, tracking of total
Radiometer over the Central China Region,”lightning data may give false lightning jump or a sudden
Atmosphere, 2019, 10(6), 298.
drop in lightning. So, for the short-term prediction of heavy
This paper's copyright is held by the author(s). It is published in these proceedings and included in any archive such as IEEE
Xplore under the license granted by the “Agreement Granting URSI and IEICE Rights Related to Publication of ScholarlyWork.”