Lightning Prediction with a mesoscale atmospheric model

Predicting the probability of lightning strikes, particularly under very hot weather, can be useful for assess the risk of natural ignitions. The present study aims to assess the performance of the Cloud Electrification and Lightning Scheme (CELLS) [1] coupled to the Meso-NH atmospheric mesoscale model [2] in simulating Cloud-to-Ground (CG) flashes. For this purpose, a simulation of a case study in which many lightning strikes were observed was carried out. The multiple extreme fire event that occurred on June 17, 2017 (including the Pedrogão Grande wildfire) was chosen as case study. According to the Portuguese official report, nine ignition points were reported during that afternoon, some of them caused by lightnings. The simulation was configured with two nested domains of 4 km and 1 km horizontal resolution and 50 vertical levels, with the innermost domain centred in the area where forest fires occurred. The description of the electrical state of a thunderstorm is based on the monitoring of the electrical charge densities, the computation of the electric field and the production of lightning flashes. The cloud charging involves mostly the non-inductive mechanism, and both Intra-Cloud (IC) and Cloud-to-Ground (CG) flashes are considered. The model reproduced an extreme dry thunderstorm environment, responsible for a perfect scenario to natural ignition and fire propagation. The spatial distribution of Meso-NH-CELLS simulated CG lightning showed a good agreement with the lightning flashes observed by the iberic lightning detection system. These results are very promising, indicating the possibility of correctly diagnose lightnings using weather prediction models at high resolutions