Search Results

You are looking at 1 - 5 of 5 items for :

  • Model performance/evaluation x
  • RELAMPAGO-CACTI: High Impact Weather in Subtropical South America x
  • All content x
Clear All
Timothy J. Lang, Eldo E. Ávila, Richard J. Blakeslee, Jeff Burchfield, Matthew Wingo, Phillip M. Bitzer, Lawrence D. Carey, Wiebke Deierling, Steven J. Goodman, Bruno Lisboa Medina, Gregory Melo, and Rodolfo G. Pereyra

of lightning was continuing to occur. b. Network installation and operation In late 2017, a predeployment site survey was performed with the assistance of the Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba (FAMAF-UNC). As a result of that site survey, as well as network performance modeling ( Chmielewski and Bruning 2016 ), LMA stations ended up being hosted on a mixture of publicly and privately held sites, with a mixture of background noise levels (from −65 dBm

Restricted access
T. Connor Nelson, James Marquis, Adam Varble, and Katja Friedrich

likely directly impacting the observed precipitating convection, or lack thereof, during the RELAMPAGO-CACTI CI missions. Though incorrect model forecasts of CI were inherent to the definition of a Null event, it was beyond the current scope of our study to present a complete analysis of model shortcomings. Our analysis allows for the discernment of important observed near-cloud environmental profiles supporting or suppressing CI, and motivates a thorough investigation into model performance for a

Restricted access
Sujan Pal, Francina Dominguez, María Eugenia Dillon, Javier Alvarez, Carlos Marcelo Garcia, Stephen W. Nesbitt, and David Gochis

model. The IMERG precipitation product was interpolated to WRF-Hydro grid (1 km × 1 km) and used for the simulations IMERG-E–WRFHydro, IMERG-L–WRFHydro, and IMERG-F–WRFHydro (see Table 1 ). Table 1. Experimental set up used in this study to evaluate the performance of different meteorological forcing data and models. 3) ERA5 reanalysis data and GFS data ERA5 is the recent (2016) reanalysis data produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) with a horizontal resolution

Restricted access
Hernán Bechis, Paola Salio, and Juan José Ruiz

Regional Reanalysis (NARR). A detection procedure suitable for high-resolution numerical models is presented by Clark et al. (2015) . Their algorithm includes image processing and pattern recognition techniques applied to various meteorological fields, and machine learning algorithms to further refine the results. This last step helps to better distinguish drylines from other low-level boundaries such as cold fronts intersecting a dryline, weak cold fronts, among others. In the literature, several

Free access
Zachary S. Bruick, Kristen L. Rasmussen, and Daniel J. Cecil

are able to form, which would be more capable of supporting large hail. Of course, updraft strength is not only a product of thermodynamic instability, but is also affected by dynamic contributions such as storm rotation (e.g., Dennis and Kumjian 2017 ), as well as hydrometeor loading and entrainment. However, deep vertical wind shear was evaluated and there were no significant differences between the hail categories, with very similar means overall ( Table 2 ). Fig . 13. As in Fig. 12 , but

Free access