The study analyzes observational climate data for June–August 1977–2004 and simulations of current and future climate scenarios from a nested GCM/regional climate model system to assess the potential for extreme temperature change over the eastern United States. Observational evidence indicates that anomalously warm summers in the eastern United States coincide with anomalously cool eastern Pacific sea surface temperatures, conditions that are conducive to geopotential ridging over the east, less frequent precipitation, and lower accumulated rainfall. The study also found that days following nighttime rain are warmer on average than daytime rain events, emphasizing the importance of the timing of precipitation on the radiation balance. Precipitation frequency and eastern Pacific sea surface temperature anomalies together account for 57% of the 28-yr variance in maximum surface temperature anomalies. Simulation results show the sensitivity of maximum surface air temperature to the moist convection parameterization that is employed, since different schemes produce different diurnal cycles and frequencies of precipitation. The study suggests that, in order to accurately project scenarios of extreme temperature change, models need to realistically simulate changes in the surface energy balance caused by the interannual variation of these precipitation characteristics. The mesoscale model that was realistic in this respect predicted much warmer mean and maximum surface air temperatures for five future summers than the parallel GCM driving simulation.

Total lightning probability forecasts for 26 mostly springtime days and 27 summertime days were analyzed for their usefulness and economic value. The mostly springtime forecast days had a relatively high number of severe weather reports compared with the summertime forecast days. The lightning forecasts were made with a dynamic lightning forecast scheme (DLS), and each forecast dataset used lightning assimilation to hasten convective initiation and, in most cases, to improve short-term forecasts. A spatial smoothing parameter σ of 48 km yielded more skillful, reliable, and economically valuable hourly forecasts than other values of σ. Mostly springtime forecasts were more skillful and had more hours of useful skill than summertime forecasts, but the latter still demonstrated useful skill during the first two forecast hours. The DLS forecasts were compared to those obtained with the “McCaul” diagnostic scheme, which diagnoses lightning flash data. The DLS had significantly higher fractions skill scores than the McCaul scheme for or at least one event/flash (10 min)−1. Bias values of the forecast lightning fields with both schemes were overall small. Yet, DLS forecasts started in the early summer evening with RAP data did have positive bias, which was attributed to initial conditions within the RAP. Correlating fractions skill scores for lightning and precipitation indicated that more accurate forecasts of lightning were associated with more accurate precipitation forecasts for convection with a high, but not lower, number of severe weather reports.

A numerical investigation was conducted to assess the possible impact of desert dust and urban aerosols on a very intense and deadly thunderstorm that occurred within the Tel Aviv metropolitan area on 4 January 2020. For these purposes, the cloud drop nucleation scheme within the spectral (bin) microphysics scheme (SBM) in the Weather Research and Forecasting Model (WRF) was coupled with the GoCart (desert) dust model and with hourly surface observations of urban aerosols. Using SBM integrated mass contents and simulated vertical velocities, the dynamic lightning scheme was able to forecast lightning rates within thunderclouds developing in an environment of marine or marine/continental aerosols with dust and/or urban aerosol forcings. Of these aerosol forcings (or factors), the urban aerosols (pollution) intensified lightning rates in convective clouds forming at and just off the Israeli coastline (referred to as the Urban Aerosol Lightning Enhancement Effect; ULE). The inclusion of continental aerosols with dust and urban aerosol sources resulted in the simulation exhibiting the most intense lightning and precipitation storm (referred to as Large Aerosol Small Aerosol Invigoration Effect; LASI). Yet, a comparison of model results and observations suggests that it was the combination of desert dust and urban aerosols alone that focused storm development over western Tel Aviv. The result was that high lightning rates initially focused over western Tel Aviv were accompanied by and then succeeded by a period of heavy rain that led to deadly flooding.