Evaluation of a Cloud-Scale Lightning Data Assimilation Technique and a 3DVAR Method for the Analysis and Short-Term Forecast of the 29 June 2012 Derecho Event

Abstract

This work evaluates the short-term forecast (#6 h) of the 29-30 June 2012 derecho event from the Advanced Research core of the Weather Research and Forecasting Model (WRF-ARW) when using two distinct data assimilation techniques at cloud-resolving scales (3-km horizontal grid). The first technique assimilates total lightning data using a smooth nudging function. The second method is a three-dimensional variational technique (3DVAR) that assimilates radar reflectivity and radial velocity data. A suite of sensitivity experiments revealed that the lightning assimilation was better able to capture the placement and intensity of the derecho up to 6 h of the forecast. All the simulations employing 3DVAR, however, best represented the storm's radar reflectivity structure at the analysis time. Detailed analysis revealed that a small feature in the velocity field from one of the six selected radars in the original 3DVAR experiment led to the development of spurious convection ahead of the parent mesoscale convective system, which significantly degraded the forecast. Thus, the relatively simple nudging scheme using lightning data complements the more complex variational technique. The much lower computational cost of the lightning scheme may permit its use alongside variational techniques in improving severe weather forecasts on days favorable for the development of outflow-dominated mesoscale convective systems.

Improvement of RAMS precipitation forecast at the short-range through lightning data assimilation

“…In recent years, several studies have shown the positive impact that lightning assimilation has on the weather forecast and especially on the precipitation forecast (Alexander et al, 1999;Chang et al, 2001;Papadopulos et al, 2005;Mansell et al, 2007;Fierro et al, 2013;Giannaros et al, 2016).…”

“…Recently, Giannaros et al (2016) implemented a similar approach in the Weather Research and Forecasting (WRF) model, showing the positive and statistically robust impact of the lightning data assimilation on the 24 h rainfall forecast for eight convective events over Greece. Fierro et al (2013) and Qie et al (2014) introduced two lightning data assimilation schemes for the WRF model intervening on the mixing ratios of the hydrometeors (water vapour in the case of Fierro et al, 2013, and ice crystals, graupel and snow in Qie et al, 2014). Both studies, which are performed at cloud resolving scales, show that lightning assimilation improves the precipitation forecast.…”

“…The assimilation scheme is similar to that of Fierro et al (2013), with few modifications to account for different spatial and temporal resolutions of the two studies and for the different model suites. In addition, the methodology presented in this paper is designed to be used in real-time NWP.…”

An Improved QPE over Complex Terrain Employing Cloud-to-Ground Lightning Occurrences

“…Lightning data have also been used in models as a proxy for deep convection to improve parameters related to cold clouds and precipitation (Alexander et al 1999;Pessi and Bussinger 2009;Fierro et al 2012). Studies employing data assimilation (Alexander et al 1999;Pessi and Bussinger 2009;Fierro et al 2012) have utilized nudging techniques to improve forecasting and analysis for some extreme events.…”

“…Studies employing data assimilation (Alexander et al 1999;Pessi and Bussinger 2009;Fierro et al 2012) have utilized nudging techniques to improve forecasting and analysis for some extreme events. More recently, scientists have investigated the utility of lightning observations for identifying convective events at several spatial scales for which they conclude that the assimilation of lightning favorably impacts several model variables as well as initial conditions (Apodaca et al 2014;Fierro et al 2014).…”