Assimilation of Lightning Data Using a Nudging Method Involving Low-Level Warming

Abstract

This study presents a new method for assimilating lightning data into numerical models that is suitable at convection-permitting scales. The authors utilized data from the Earth Networks Total Lightning Network at 9-km grid spacing to mimic the resolution of the Geostationary Lightning Mapper (GLM) that will be on the Geostationary Operational Environmental Satellite-R (GOES-R). The assimilation procedure utilizes the numerical Weather Research and Forecasting (WRF) Model. The method (denoted MU) warms the most unstable low levels of the atmosphere at locations where lightning was observed but deep convection was not simulated based on the absence of graupel. Simulation results are compared with those from a control simulation and a simulation employing the lightning assimilation method developed by Fierro et al. (denoted FO) that increases water vapor according to a nudging function that depends on the observed flash rate and simulated graupel mixing ratio. Results are presented for three severe storm days during 2011 and compared with hourly NCEP stage-IV precipitation observations. Compared to control simulations, both the MU and FO assimilation methods produce improved simulated precipitation fields during the assimilation period and a short time afterward based on subjective comparisons and objective statistical scores (;0.1, or 50%, improvement of equitable threat scores). The MU generally performs better at simulating isolated thunderstorms and other weakly forced deep convection, while FO performs better for the case having strong synoptic forcing. Results show that the newly developed MU method is a viable alternative to the FO method, exhibiting utility in producing thunderstorms where observed, and providing improved analyses at low computational cost.

A simple lightning assimilation technique for improving retrospective WRF simulations

“…The slightly higher bias in NoSuppress compared to CTRL results from forcing deep convection in lightning grid cells without suppressing incorrectly placed convection, leading to excess rainfall. Similar increased biases have been seen in convective-permitting WRF simulations that used lightning assimilation without suppression [e.g., Fierro et al ., 2012 ; Fierro et al ., 2015 ; Marchand and Fuelberg , 2015 ]; however, suppression techniques become more complicated when convection is explicitly resolved.…”

Evaluation of deep convective transport in storms from different convective regimes during the DC3 field campaign using WRF‐Chem with lightning data assimilation

“…In the Fierro et al studies the Q v increase was confined at midlevels within the graupel‐rich, mixed phase region between 253 K and 273 K. In this study, however, Q v was increased over a slightly deeper layer rooted at lower levels, namely, between 285 K and 261 K. These isotherms correspond, respectively, to the lifted condensation level and the level of maximum vertical velocity. This change was motivated by the findings of Marchand and Fuelberg [] and Fierro et al [], which suggest that increasing Q v in the lower troposphere (below 700 hPa) instead of the mixed‐phase region allows convection to become more quickly rooted in the PBL and, in turn, better represents weakly forced moist convection. The value of C is based on the gridded number of flashes.…”

Continuous Assimilation of Lightning Data Using Time‐Lagged Ensembles for a Convection‐Allowing Numerical Weather Prediction Model

“…The first studies, which investigated means to assimilate total lightning data at convection‐allowing and convection‐resolving scales, were reported by Fierro and Reisner () and Fierro et al (, 2014), wherein incremental increases in water vapor mass were applied in the mixed‐phase region to locally enhance thermal buoyancy, which, ultimately, promoted the development of updrafts at observed lightning locations. Marchand and Fuelberg () used a temperature nudging method to warm the boundary layer to hasten the development of convection where lightning flashes are observed. Qie et al () employed the nudging function of Fierro et al () to adjust ice‐phase hydrometeor mass where lightning was observed.…”