The relative sensitivity of convective simulations to perturbations in initial conditions and microphysics parameters

Deep convective cloud systems are one of the leading contributors to weather related disasters, provide much of the fresh water used by society, and contribute significantly to the interactions among weather and climate. Convection is known to be influenced strongly by the characteristics of its environment, including the vertical structure of temperature, moisture, and wind. It has also been shown in many numerical modeling studies to be sensitive to the assumptions made in the representation of cloud processes.

 

This presentation will explore the relative influence of environmental (extrinsic) factors and cloud microphysical parameter (intrinsic) uncertainty in the evolution of tropical deep convection. The effect of both types of factor on the energy and water cycle, as well as on convective dynamics and heating, are shown. Ensemble Monte Carlo experiments quantify convective storm sensitivity, while ensemble data assimilation experiments provide traceability from convective outcomes to control factors. The results have implications for modeling, data assimilation, and the design of future observing systems.