remote sensing Article Multi-Variable Classification Approach for the Detection of Lightning Activity Using a Low-Cost and Portable X Band Radar Vincenzo Capozzi 1,2,3 , Mario Montopoli 2,3,* , Vincenzo Mazzarella 1,3 , Anna Cinzia Marra 2, Nicoletta Roberto 2, Giulia Panegrossi 2, Stefano Dietrich 2 and Giorgio Budillon 1 1 Department of Science and Technology, University of Naples “Parthenope”, Centro Direzionale di Napoli, 80143 Napoli, Italy; [email protected] (V.C.); [email protected] (V.M.); [email protected] (G.B.) 2 Institute of Atmospheric Sciences and Climate, National Research Council, 00133 Rome, Italy; [email protected] (A.C.M.); [email protected] (N.R.); [email protected] (G.P.); [email protected] (S.D.) 3 Centre of Excellence CETEMPS, University of L’Aquila, 67100 L’Aquila, Italy * Correspondence: [email protected]; Tel.: +39-06-45488-353 Received: 1 October 2018; Accepted: 8 November 2018; Published: 13 November 2018 Abstract: This work proposes a multi-parameter method for the detection of cloud-to-ground stroke rate (SRCG) associated to convective cells, based on the measurements of a low-cost single-polarization X-band weather radar. To train and test our procedure, we built up a multi-year dataset, collecting 1575 radar reflectivity volumes that were acquired in the pilot study area of Naples metropolitan environment matched with the LIghtning NETwork (LINET) strokes and meteorological in-situ data. Three radar-based variables are extracted simultaneously for each rain cell and properly merged together, using “ad hoc” classification methods, to produce an estimation of the expected lightning activity for each rain cell. These variables, proxies of mixed-phase particles and ice amount into a convective cell, are combined into a single label to cluster the SRCG into two categories: SRCG = 0 (no production of strokes) or SRCG > 0 (stroke production), respectively. Overall, the main results are comparable with those that were obtained from more advanced radar systems, showing a Critical Success Index of 0.53, an Equitable Threat Score of 0.34, a Frequency Bias Index of 1.00, a Heidke Skill Score of 0.42, a Hanssen-Kuiper Skill Score of 0.42, and an area under the curve of probability of detection as a function of false alarm rate (usually referred as ROC curve) equal to 0.78. The developed technique, although with some limitations, outperforms those based on the use of single stroke proxy parameters. Keywords: weather radar; lightning detection; convective rain cells; detection methods 1. Introduction Cloud-to-ground (CG) strokes are a natural hazard having a large impact on human activities. They involve, in fact, very strong electrical currents (up to dozen of kAmperes), and, for this reason, they constitute a serious threat for human safety as well, as they may adversely affect industrial productions, transport activities (especially the air traffic routing) and power lines [1,2]. The information about the spatial and temporal occurrence of CG strokes is typically provided by in situ ground-based electromagnetic stroke detection systems, which perform direct measurements through extremely-low (ELF) to very-low (VLF) frequency and very-high (VHF) to extremely-high (EHF) frequency sensors. According to [3,4], the ground-based lightning network systems are able to detect CG Remote Sens. 2018, 10, 1797; doi:10.3390/rs10111797 www.mdpi.com/journal/remotesensing Remote Sens. 2018, 10, 1797 2 of 26 stroke discharges with a spatial resolution as high as up to 100 m and with a detection efficiency up to 95%, although these performances depend on the network density and the type of sensors. The real-time surveillance of stroke occurrence can also rely on weather radar measurements, which are able to track and characterize the three-dimensional (3D) structure of rain cells, thus allowing for identifying the developing cycle of cells and the areas much prone to stroke activity, even before the occurrence of the first lightning event (e.g., [5]). Therefore, the set-up of a reliable, affordable, and accessible radar-based stroke detection system, complementary to traditional ground-based stroke networks, can be very useful for risk prevention and for safety of human life, goods and services. In addition, a stand-alone radar-based stroke detection system could cover those areas where data from lightning networks are not freely accessible or where their detection efficiency levels are not constant over large domains, due to the irregular distribution of lightning sensors. This work is aimed at proposing a new algorithm for the radar-based detection of stroke activity based on a multi-variable approach. To explain our approach, it is useful to briefly summarize the atmosphere electrification mechanisms and the radar-based approaches so far proposed in the state of the art literature. Electrification mechanisms in thunderstorms are explained following the widely accepted Non-Inductive Charging (NIC) theory, whose evidences have been supported by many laboratory studies, as well as by field campaigns (e.g., [6,7]). According to NIC theory, the most efficient conditions for charge separation within the updraft of a thunderstorm occur during the collision between graupel and ice crystals [8]. This mechanism takes place in the mixed-phase cloud region, which consists of a proper mix of supercooled liquid droplets, ice crystals, and water vapor [9]. Dual polarization radars have demonstrated, to some extent, to be able to segment a precipitating cloud, allowing for the separation of the mixed-phase regimes from the rest (e.g., [10,11]). In this respect, some previous works have highlighted a correlation between dual polarization radar variables and microphysical processes of stroke initialization [12–18]. However, most of the local weather services cannot afford dual polarization technology, and, on top of this, the increasing diffusion of small networks of single polarization X band radars for urban and small catchment monitoring is a demonstration of a constant interest toward these systems and the related applications [19]. The measurements that are provided by single polarization weather radars, although with some well-known limitations, can still provide some exploitable information for the hydrometeor detection in the mixed-phase region of a thunderstorm. In this respect, several studies [20–24] have found links between the presence of graupel at different environmental levels and the occurrence of a strong reflectivity core. These relationships have been synthetized into a radar-based stroke forecast criterion, named Isothermal Reflectivity Threshold (IRT), which is based on the occurrence of a determined reflectivity core (Z), usually 30 dBZ or 40 dBZ, at a certain environmental height typically represented by the level of −10 ◦C, −15 ◦C or −20 ◦C isotherms (T). The performance of the IRT method has been extensively evaluated [25–35], especially in the USA, after the introduction of the WSR-88D radar network. As a general result, these studies show that CG strokes occur within a time ranging from 4 to 45 min after the presence of certain reflectivity cores (ranging from 10 dBZ to 40 dBZ) at isothermal heights varying between 0 ◦C and −20 ◦C. The existing literature has also proposed also other radar-derived parameters for the stroke forecast, such as the Vertically Integrated Liquid (VIL) and the Vertically Integrated Ice (VII). The VIL product, introduced in [36], is an estimate of the liquid water mass content (excluding ice) along the convective column. Weather forecasters have traditionally used VIL to discriminate between weak and severe storms; the use of VIL for stroke prediction has been proposed for the first time in [37], for a storm that occurred in Oklahoma in June 1993. Another attempt to use VIL for stroke forecast has been performed in [38], for a dataset including 120 cells. The results of these two studies highlighted a low correlation degree between VIL and CG stroke occurrence. The VII product has been proposed in [14] to improve the low correlation with respect to the stroke activity that was found using VIL alone. VII provides a quantitative estimation of the amount of ice between the −10 ◦C and −40 ◦C Remote Sens. 2018, 10, 1797 3 of 26 isothermal levels. VII tool has been tested for stroke forecast purposes in [30,31]. Other approaches discussed in previous literature are the Differential Isothermal Height (DIH) and the “Larsen Area” (LA). The former has been defined in [39] as the difference between the height achieved by a given reflectivity core and a certain isothermal level. This difference can be considered as a proxy for the electric field development and the subsequent stroke discharge. The LA, in its original definition, introduced in [21], corresponds to a nearly horizontal area occupied by reflectivity echoes greater than 43 dBZ above 7 km height. In [5], some simple storm attributes, such as the maximum reflectivity value observed in the storm cell area, the maximum height reached by a determined reflectivity core within a cell and the storm area, have been evaluated as predictors of CG stroke occurrence. In [18], the relationship between ice water content of graupel (IWCg) and CG stroke activity has been investigated for eleven convective events. Finally, some radar-derived variables, such as the maximum reflectivity value, the reflectivity observed at the level of −10 ◦C isotherm, and the VIL product, have been merged with attributes from ground-based lightning network (i.e., the lightning density and the ideal lightning density) in a multi-sensors algorithm for CG stroke prediction [40]. Such algorithm has been included in the Multi-Radar Multi-Sensor (MRMS) system, developed at the National Severe Storms Laboratory and the University of Okhlahoma [41]. A summary of the results that were achieved by previous works focused on radar-based stroke prediction is summarized in Table1, in terms of some standard statistical scores, such as the Probability of Detection (POD), the False Alarm Rate (FAR), and the Critical Success Index (CSI).