Performance Evaluation of an Explicit Lightning Forecasting System. Issue 10 (24th May 2018)

• Record Type: Journal Article
• Authors: Dafis, S.; Fierro, A.; Giannaros, T. M.; Kotroni, V.; Lagouvardos, K.; Mansell, E.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 10(2018)
• Page Start: 5130
• Page End: 5148
• Publication Date: 2018-05-24
• Subjects: lightning forecasting -- verification -- high‐impact weather; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2017JD027930
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: In this study, an explicit electrification and lightning parameterization scheme implemented within the Weather Research and Forecasting model (E‐WRF, Fierro et al., 2013, https://doi.org/10.1175/MWR‐D‐12‐00278.1 ) is evaluated against selected lightning diagnostic schemes. Convection‐permitting simulations of 10 high‐impact weather case studies over Greece are compared against lightning observations from the ZEUS ground‐based lightning detection network. The model's ability to accurately simulate these convective events is first evaluated through statistical scores of accumulated rainfall. The simulated flash origin density (FOD) fields are then assessed using statistical neighborhood methods. Overall, the simulated FOD fields have good agreement with the observations. Most of the lightning activity over the sea, however, is generally poorly forecasted. Lightning‐producing events over the sea near Greece mainly occur during the cold season. Thus, lightning forecast with E‐WRF appear to have better skill during the warm season. The simulated areal coverage of FOD using E‐WRF also reduces the false alarms of lightning activity both over land and sea compared to a well‐documented diagnostic lightning prediction scheme. Given its relatively low computational cost, these results support the potential use of E‐WRF for real‐time lightning predictions at convection‐allowing scales. Key Points: Lightning and precipitation verification procedures Explicit lightning forecasting outperforms empirically derived diagnostics