Thermodynamic and Non-thermodynamic Controls on Deep Convection in ARM Observations

Abstract

Deep convection remains one of the most challenging processes to represent in weather and climate models. This is in part due to multiple controlling factors, including thermodynamic, dynamic and aerosol effects.This project will create a framework based on Atmospheric Radiation Measurement Program (ARM) observations, using which the relative influence of thermodynamic, dynamic and aerosol effects on deep convection will be assessed. This framework—called the “precipitation-buoyancy framework”—will expand upon a previously identified empirical buoyancy measure that constrains the thermodynamic influence on tropical precipitation. This project will also integrate the precipitation-buoyancy framework into the ARM model diagnostics package to identify convection-related process errors in climate models.

Prior work with observations from Department of Energy (DOE) ARM sites from the Tropical Western Pacific (TWP) and Green Ocean Amazon (GoAmazon2014/5) field campaign identified a buoyancy measure. This measure condenses multiple thermodynamic influences on deep convection into a single metric. This project will test the efficacy of this buoyancy measure across a wider range of environments (tropical and sub-tropical; oceanic and continental) using ARM site observations. Data from recent ARM field campaigns will be heavily utilized; these campaigns include Cloud, Aerosol, and Complex Terrain Interactions (CACTI), GoAmazon2014/5, and Tracking Aerosol Convection Interactions Experiment (TRACER). To improve the statistics, these field campaign data will be supplemented with long-term measurements from the Southern Great Plains (SGP) and TWP ARM sites. The buoyancy framework will be refined by accounting for non-thermodynamic controls on convection, including dynamical (e.g., wind shear, orography, sea-breeze convergence) and aerosol effects. By controlling for thermodynamic factors, the precipitation-buoyancy framework will more precisely evaluate the dynamical and aerosol effects on convection. This project will use multi-instrument ARM observations, including radiosondes, surface meteorological instruments, precipitation and cloud radars, radar wind profilers, and aerosol observing systems. The buoyancy framework integrated into the ARM model diagnostics package will identify optimal parameter regimes for interim versions of DOE’s Energy Exascale Earth System Model (E3SM). The targeted outcome of this project is a broad framework for representing deep convection dependence on its environment, and a roadmap toward representing these effects in climate models.