GeoRayos Project: Lightning warning in Argentina

M. Gabriela Nicora

CEILAP - UMI-IFAECI-CNRS 3351 UNIDEF (MINDEF - CONICET)

Buenos Aires, Argentina Gabriela@blueplanet.com.ar

Eldo E. Ávila FAMAF

Universidad Nacional de Córdoba, IFEG-CONICET

Córdoba, Argentina

Juan Lucas Bali Departamento de CRISIS

CITEDEF Buenos Aires, Argentina

Marcos Saucedo, Pedro Lohigorry, Luciano Vidal Servicio Meteorológico Nacional

Buenos Aires, Argentina

Pablo Vasquez Universidad Tecnologica Nacional

Buenos Aires, Argentina

Abstract

GeoRayos (http://georayos.citedef.gob.ar) is a Project to develop a forecast tool based

on lightning observation to anticipate the occurrence of severe weather with simple

infrastructure and small budget. It consists of the lightning activity detection related to

thunderstorms and the use of a Nowcasting algorithm to link flash rate and severe

weather at surface level.

Input data from GeoRayos are measurements based on lightning activity detected by

the Word Wide Lightning Location Network (WWLLN) and atmospheric electric field

measuring instruments (aka Ginkgos).

The expanded body of knowledge on lightning activity along República Argentina,

allowed us to determine the need for a tool to forecast severe weather in short time

periods; thus, GeoRayos was developed, evaluated and now it is a tool on a daily basis

at the National Meteorological Service (SMN).

GeoRayos Project, since its very origin, has been thought of as a tool for developing

countries because of its low cost and its design and implementation are not excessively

complex. It relies on IT tools easily available since it runs on internet servers and the

Ginkgos device can be built with accessible parts. It is particularly relevant to the

observing systems in developing countries since it can easily become a lightning

detection network.

Introduction

According to previous studies (Williams, 1994; 1989.2001, 2013; Price, 2013; Avila et

al, 2010), the lightning activity is associated with the dynamics and microphysics of

clouds storms and it can be correlated with different meteorological and climatic

parameters. Changes in the electrical activity may indicate changes in internal

processes thunderstorms.

For those countries like Argentina that do not have a national network of lightning

activity and don’t have radar information cover all the country, to have data base from

a global network like WWLLN is really powerful because it can use an unexpressive

data base, can cover all the region and can use this information not only for

applications on different aspects such as security and defense, but also in early

warning system and nowcasting for severe weather.

Furthemore, measuring the ambient electrostatic field It is particularly relevant to the

observing systems in developing countries since it be the first step in a lighting

network and can be built with accessible parts.

Data and methodology

The lightning data used by GeoRayos came from the World Wide Lightning Location

Network (WWLLN, see http://wwlln.net) which is a ground-based network with global

observations beginning in 2004. The WWLLN record is now long enough to support

studies of seasonal, diurnal, and synoptic lightning variability over most of the globe

(Hutchins et al., 2012, Virts et al., 2013). The WWLLN network consists of more than 70

stations, each of one receiving and processing the very low frequency (VLF) radio

waves generated by lightning. This network uses the time of group arrival technique to

detect spherical waveforms for lightning location within ~5 km and < 10 μs (Dowden

Richard L, Brundell James B, and Rodger Craig, 2002, 2008).

The GeoRayos algorithm clusters the lightning detected by WWLLN that lies within a

given spatial domain and a given lapse time. The clustering is done by the Density-

Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm (Ester et al.,

1996 ). One advantage of using a cluster algorithm is that it allows more flexibility in

the determination of storm regions, in contrast with a grid approach. (Nicora et al

,2015)

Each cluster that was determined by DBSCAN is considered as a Storm-Cluster (SC)

with an area equal to the minimum convex polygon that overlays all the lightning

associated to the cluster. After the identification of the SC, GeoRayos classified them

as Sparse and Dense according to the amount of lightning associated to it.

The classification in Sparse or Dense is based on the amount of lightning data

associated to the SC in the last two minutes (Storm Threshold). If the amount of

lightning is less than the Storm Threshold, the SC is considered as Sparse, otherwise, it

is classified as Dense.

The Dense SC is the candidates to develop severe weather and will be classified as

Severe Storms according to the time variation of the amount of lightning inside it. If

the lightning amount increase over time and the increasing rate over the last 2 minutes

is twice larger than the increasing rate in the previous 10 minutes. In this case, a

Lightning Jump (LJ) is identified and the SC is classified as Severe. Otherwise, the Dense

SC classification remains. Therefore, GeoRayos provides a collection of SC with the

classification of Sparse (green), Dense (yellow) and Severe (red) every 10 minutes.

Since August 2015, GeoRayos has been operative and being tested in SMN and

together with CITEDEF the project continues to grow by developing a Network for

Argentina.

GeoRayos also has a public web page http:// georayos.citedef.gob.ar in which the

general population can see, in real time, the lightning activity.(Figure 1)

Figure 1 GeoRayos page

Since January 2016 we started measure Vertical electric filed used "Field Mill" (Ginkgo)

entirely made in CITEDEF (Figure 2)

Figure 2 Ginkgo Field Mill

The sensitivity of a meter field is given by the minimal variation of the field intensity

which produces a measurable change in the sensor output concerned. Repeatability

measures the similarity between the outputs produced by the same entry after

different excursions in the measured intensity. With respect to scope, it refers to the

maximum physical value that can be measured with confidence. The accuracy of the

equipment will be greater the higher its sensitivity and repeatability.

The capacity to combine both simple information makes a powerful tool (Figure 3)

Figure 3 GeoRayos and Field Mill

Future Actions and Conclusions

We are planning to expand the Ginkgo network in stations at airports along the

country to improve the network and the knowledge of the atmospheric electrical

activity and the internal processes thunderstorms in the different regions of Argentina.

Acknowledgment

The authors wish to thank the World Wide Lightning Location Network

(http://wwlln.net), collaboration among over 60 universities and institutions, for

providing the lightning location data used in this paper. Also, the authors wish to thank

to, the National Meteorological Service (SMN), and the grants: SISTEMA DE ESTUDIO Y

DETECCIÓN DE RAYOS (03 NAC 022/15), PIDDEF 14/12 CARACTERIZACIÓN DE LA

ACTIVIDAD ELÉCTRICA ATMOSFÉRICA EN EL TERRITORIO ARGENTINO PIP 2013-2015 –

11220120100088, PROCESOS MICROFISICOS DE NUBES, ELECTRIFICACION, DESCARGAS

Y SUS EFECTOS EN EL CLIMA, CONICET and SECYT-UNC, The authors would like to

thank JICA (Japan International Cooperation Agency) by financial support of SAVER-Net

and CITEDEF.

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