Abstract
Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE times PREC parameterization, applied in a non-CPM on a coarser grid. The LPI’s implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE times PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of 4.8% in flash rate by the end of the century, in opposition to a projected increase of 17.4% as projected using the CAPE times PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.
Highlights
Current lightning climate simulations mainly rely on parameterizations, which relate climate model output to observed lightning (Clark et al 2017), but rarely closely reflect the physical mechanisms leading to lightning
The lightning potential index (LPI) outperforms the CAPE × PREC resulting in PSSs of respectively 0.93 and 0.77 for the hourly timescale and 0.84 and 0.73 for the daily timescale
The small scale spatial variability is poorly reproduced by both parameterizations (MSSS of −0.14 for the LPI and -0.25 for the CAPE × PREC)
Summary
Current lightning climate simulations mainly rely on parameterizations, which relate climate model output to observed lightning (Clark et al 2017), but rarely closely reflect the physical mechanisms leading to lightning. The spatio-temporal scales, and the diversity of mechanisms related to lightning flashes do not allow global climate models for its explicit representation. The mechanism dominating thunderstorm electrification is known as the non-inductive charging mechanism (Reynolds et al 1957; Takahashi 1978; Saunders 1993; Saunders and Peck 1998; Latham et al 2007). It implies electric charge separation through rebounding collision between small ice crystals growing by water vapor diffusion and graupel pellets growing by accretion of supercooled water droplets (Yair 2008). The cloud will, be characterized by multiple large cloud layers
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