Preprints
https://doi.org/10.5194/egusphere-2022-1033
https://doi.org/10.5194/egusphere-2022-1033
 
12 Oct 2022
12 Oct 2022
Status: this preprint is open for discussion.

A method for generating a quasi-linear convective system suitable for observing system simulation experiments

Jonathan D. Labriola1,2 and Louis J. Wicker1 Jonathan D. Labriola and Louis J. Wicker
  • 1National Severe Storms Laboratory, Norman, Oklahoma, 73072, United States
  • 2National Research Council, Washington, DC, 20001, United States

Abstract. To understand the impact of different assimilated observations on convection-allowing model forecast skill, a diverse range of observing system simulation experiment (OSSE) case studies are required (different storm modes and environments). Many previous convection-allowing OSSEs predicted the evolution of an isolated supercell generated via a warm air perturbation in a horizontally homogenous environment. This study introduces a new methodology where a quasi-linear convective system is generated in a highly-sheared and modestly unstable environment. Wind, temperature, and moisture perturbations superimposed on a horizontally homogeneous environment simulate a cold front that initiates an organized storm system that spawns multiple mesovortices. Mature boundary layer turbulence is also superimposed onto the initial environment to account for typical convective scale uncertainties.

Creating an initial forecast ensemble remains a challenge for convection-allowing OSSEs because mesoscale uncertainties are difficult to quantify and represent. The generation of the forecast ensemble is described in detail. 24 hour full-physics simulations (e.g., radiative forcing, surface friction, microphysics) initialize the forecast ensemble. The simulations assume different surface conditions to alter surface moisture and heat fluxes and modify the effects of friction. The subsequent forecast ensemble contains robust non-gaussian errors that persist until corrected by the data assimilation system. An example OSSE suggests a combination of radar and conventional (surface and soundings) observations are required to produce a skilled quasi-linear convective system forecast, which is consistent with real case studies. The OSSE framework introduced in this study will be used to understand the impact of assimilated environmental observations on forecast skill.

Jonathan D. Labriola and Louis J. Wicker

Status: open (until 07 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1033', Anonymous Referee #1, 10 Nov 2022 reply
  • RC2: 'Comment on egusphere-2022-1033', Anonymous Referee #2, 21 Nov 2022 reply

Jonathan D. Labriola and Louis J. Wicker

Data sets

A Method for Generating a Quasi-Linear Convective System Suitable for Observing System Simulation Experiments: Dataset Jonathan Labriola and Louis Wicker https://zenodo.org/record/7126769#.Yz8RwuzMI88

Model code and software

A Method for Generating a Quasi-Linear Convective System Suitable for Observing System Simulation Experiments Jonathan Labriola and Louis Wicker https://zenodo.org/record/7109050#.Yz8ReezMI88

Jonathan D. Labriola and Louis J. Wicker

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Short summary
Observing system simulation experiments (OSSEs) are simulated case studies used to understand how different assimilated weather observations impact forecast skill. This study introduces the methods used to create an OSSE for a tornadic quasi-linear convective system event. These steps provide an opportunity to simulate a realistic high-impact weather event and can be used to encourage a more diverse set of OSSEs.