Evaluating the impacts of climate change on severe local storms in the United States through idealized dynamical downscaling method

Abstract:

Associated with extreme surface wind gusts, hail and tornadoes, severe local storms (SLS) pose serious social and economic threat to the United States (US). In this study, the potential impacts of anthropogenic warming on SLS will be projected using a dynamical downscaling method conducted by the high resolution (4 km) Weather Research and Forecasting (WRF) model. Before the dynamical downscaling is conducted, two kinds of downscaling methods, namely daily reinitialization and monthly continuous run, are tested. In the daily reinitialized condition experiments, it is found the WRF can reasonably capture shortwave structures and well reproduce the prescribed environments within 6 hours. This indicates 6 hours are enough for spin up in the daily reinitialization experiments. However, the simulated SLS activities in the 6-hour spin up experiments are still slightly different to that in the 12-hour spin up experiments, and ensembles using different spin up time are still suggested in the daily reinitialization experiments. Although spectral nudging was applied, the large scale conditions as well as SLS related environments have slightly drifted away from the prescribed conditions in the monthly continuous run, which can eventually affect the spatial distribution of SLS frequency. The nudging experiments may suppress the activity of shortwave structures, thus the simulated SLS related environments and detected SLS activities are weaker in the monthly continuous run compared with daily reinitialization experiments. The simulated diurnal cycle and intensity of detected SLS are similar in these two kinds of downscaling methods. Moreover, some previous studies used monthly averaged rather than real time soil data in the downscaling. Here we tested whether the monthly averaged soil data can affect the simulated SLS activity. It is found that if the monthly averaged soil data are linearly interpolated to daily, the small soil moisture departures from real time data are still able to slightly modulate SLS related environments over central and eastern US, e.g., convective available potential energy (CAPE). However, there is no significant relationship between the soil moisture difference and SLS activity. Based on the above analysis, daily reinitialization with 6-hour spin up will be used in the coming global warming downscaling experiments. Two sets of climatology that determine SLS related environments, i.e., historical and global warming condition in 2xCO₂/4xCO₂, conducted by the Community Earth System Model (CESM) idealized experiments, will be dynamically downscaled by the WRF in a 4 km horizontal resolution. In the downscaling, the last 10 years of CESM simulated idealized climates will be downscaled. Based on the outputs from idealized historical and global warming experiments, the effects of anthropogenic warming on SLS activities will be analyzed.