A Multiscale Analysis of Convective Envelope Predictability and Convective System Sensitivity in the Maritime Continent

Abstract

Within the PISTON DRI PI will study how changes in convection at small scales affect the larger scale convective envelope, and how do convective sensitivities change with variations in the large-scale conditions. Communication between scales conduct high-resolution (1.5 - 2 km), large domain (2000 km x 2000 km x 25 km domain), three-week weather simulations centered over the South China Sea. 3-5 different canonical combinations or regimes of CAPE, shear, SST, and aerosol content consistent with variability associated with the passage of a tropical wave will be analyzed through a very large ensemble of small-domain (100 km x 100 km x 25 km), simple, semi-idealized simulations that run highly efficiently, in which the predominant factors impacting shallow through deep convection using a Bayesian Markov chain Monte Carlo (MCMC) algorithms approach will be identified. The MCMC factors will be used to guide further mesoscale simulations. Mesoscale ensemble members generated by perturbing one or more of the dominant controls of convective variability will be analyzed to determine how variability on small scales affects mesoscale convective organization and, in turn, the factors that influence the larger scale environment and flow. Finally, results from all of the simulations will be utilized in developing hypotheses that describe the impacts of the small scales on the overall convective envelope. These hypotheses will be useful in guiding the measurement objectives in field campaigns including PISTON and CAMPEx, and the observational data from these campaigns will be used to evaluate the hypotheses.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 23, 2016
Source ID
N000141613093

Entities

People

  • Susan van den Heever

Organizations

  • Colorado State University
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Computational Fluid Dynamics (CFD)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference