Convection-Allowing and Convection-Parameterizing Ensemble Forecasts of a Mesoscale Convective Vortex and Associated Severe Weather Environment

Abstract

An analysis of a regional severe weather outbreak that was related to a mesoscale convective vortex (MCV) is performed. The MCV-spawning mesoscale convection system (MCS) formed in northwest Kansas along the southern periphery of a large cutoff 500-hPa low centered over western South Dakota. As the MCS propagated into eastern Kansas during the early morning of 1 June 2007, an MCV that became evident from multiple data sources [e.g., Weather Surveillance Radar-1988 Doppler (WSR-88D) network, visible satellite imagery, wind-profiler data, Rapid Update Cycle 1-hourly analyses] tracked through northwest Missouri and central Iowa and manifested itself as a well-defined midlevel short-wave trough. Downstream of the MCV in southeast Iowa and northwest Illinois, southwesterly 500-hPa winds increased to around 25 m s21 over an area with southeasterly surface winds and 500-1500 J kg21 of surface-based convective available potential energy (CAPE), creating a favorable environment for severe weather. In the favorable region, multiple tornadoes occurred, including one rated as a category 3 storm on the enhanced Fujita scale (EF3) that caused considerable damage. In the analysis, emphasis is placed on the role of the MCV in leading to a favorable environment for severe weather. In addition, convection-allowing forecasts of the MCV and associated environmental conditions from the 10-member Storm-Scale Ensemble Forecast (SSEF) system produced for the 2007 NOAA Hazardous Weather Testbed Spring Experiment are compared to those from a similarly configured, but coarser, 30-member convection-parameterizing ensemble. It was found that forecasts of the MCV track and associated environmental conditions (e.g., midlevel winds, low-level wind shear, and instability) were much better in the convection-allowing ensemble. Errors in the MCV track from convectionparameterizing members likely resulted fromwestward displacement errors in the incipientMCS. Furthermore, poor depiction of MCV structure and maintenance in convection-parameterizing members, which was diagnosed through a vorticity budget analysis, likely led to the relatively poor forecasts of the associated environmental conditions. The results appear to be very encouraging for convection-allowing ensembles, especially when environmental conditions lead to a high degree of predictability for MCSs, which appeared to be the case for this particular event. ABSTRACT An analysis of a regional severe weather outbreak that was related to a mesoscale convective vortex (MCV) is performed. The MCV-spawning mesoscale convection system (MCS) formed in northwest Kansas along the southern periphery of a large cutoff 500-hPa low centered over western South Dakota. As the MCS propagated into eastern Kansas during the early morning of 1 June 2007, an MCV that became evident from multiple data sources [e.g., Weather Surveillance Radar-1988 Doppler (WSR-88D) network, visible satellite imagery, wind-profiler data, Rapid Update Cycle 1-hourly analyses] tracked through northwest Missouri and centr...

Factors Influencing the Development and Maintenance of Nocturnal Heavy-Rain-Producing Convective Systems in a Storm-Scale Ensemble

“…Using the equitable threat score (ETS) with a 50-km neighborhood around each grid point, as described by Clark et al (2010a), we find that all members produce skillful forecasts of 25.4 mm of precipitation in 6 h. The ETS is highest at short lead times, decreasing to a minimum at hour 24 and then increasing slightly at hour 30 (Fig. 6a).…”

“…Constructing subsets of members that have contrasting properties and analyzing the differences between those subsets can also reveal important information about the weather systems of interest; this method was used by Reinecke and Durran (2009), Schumacher (2011), and Hanley et al (2011. Herein, we will use a combination of manual and statistical diagnosis, along the same lines as the analysis of Clark et al (2010b), to investigate the processes that were most favorable for, or detrimental to, the development of extreme precipitation in association with an MCV on 9-11 June 2010. Section 2 will provide an overview of this event, and section 3 will outline the data and methods used in the study.…”

“…4b,f,j) shows the ensemble probability of 25 mm or more (where the probability is simply the percentage of ensemble members predicting that amount at each grid point), and the third column from the left (Figs. 4c,g,k) shows the probability-matched mean, which is intended to reflect the precipitation distribution associated with the ensemble mean but to retain the amplitude of the individual members (e.g., Ebert 2001;Clark et al 2009). For each of the three nights, the SSEF had several members that predicted 25 mm of precipitation at or near the location where it was observed (Figs.…”

“…Individual members are shown in different colors; ARPS members and those without radar data assimilation are excluded from the analysis. The ETS was calculated using a 50-km neighborhood around each grid point, as described by Clark et al (2010a). Higher ETS indicates a better forecast, with 1 representing a perfect forecast and zero representing no skill.…”

An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment

“…We believe that these challenges are formidable, but that the motivation for developing CAM ensembles is strong. Aspects of CAM forecasts that are improved relative to convection-parameterizing forecasts, such as statistical properties of convective rainfall (e.g., Davis et al 2004) and the depiction of the diurnal precipitation cycle (Clark et al 2007(Clark et al , 2009Weisman et al 2008), strongly suggest that CAM ensemble forecasts would be more representative of possible future atmospheric states than coarser convectionparameterizing ensembles [e.g., the National Centers for Environmental Prediction's (NCEP) Short-Range Ensemble Forecast (SREF) system (Du et al 2006)]. …”