Understanding the impact of radar and in situ observations on the prediction of a nocturnal convection initiation event on 25 june 2013 using an ensemble-based multiscale data assimilation system

Samuel K. Degelia, Xuguang Wang, David J. Stensrud, Aaron Johnson

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The initiation of new convection at night in the Great Plains contributes to a nocturnal maximum in precipitation and produces localized heavy rainfall and severe weather hazards in the region. Although previous work has evaluated numerical model forecasts and data assimilation (DA) impacts for convection initiation (CI), most previous studies focused only on convection that initiates during the afternoon and not explicitly on nocturnal thunderstorms. In this study, we investigate the impact of assimilating in situ and radar observations for a nocturnal CI event on 25 June 2013 using an ensemble-based DA and forecast system. Results in this study show that a successful CI forecast resulted only when assimilating conventional in situ observations on the inner, convection-allowing domain. Assimilating in situ observations strengthened preexisting convectionin southwestern Kansas by enhancing buoyancy and locally strengthening low-level convergence. The enhanced convection produced a cold pool that, together with increased convergence along the northwestern low-level jet (LLJ) terminus near the region of CI, was an important mechanism for lifting parcels to their level of free convection. Gravity waves were also produced atop the cold pool that provided further elevated ascent. Assimilating radar observations further improved the forecast by suppressing spurious convection and reducing the number of ensemble members that produced CI along a spurious outflow boundary. The fact that the successful CI forecasts resulted only when the in situ observations were assimilated suggests that accurately capturing the preconvective environment and specific mesoscale features is especially important for nocturnal CI forecasts.

Original languageEnglish (US)
Pages (from-to)1837-1859
Number of pages23
JournalMonthly Weather Review
Volume146
Issue number6
DOIs
StatePublished - Jun 2018

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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