Improving the Prediction of Nocturnal Convection Initiation using PECAN Field Observations and a GSI-based Multi-scale Data Assimilation System

The initiation of new convection at night produces localized heavy rainfall and severe weather hazards. While convection initiation (CI) in well-mixed, daytime boundary layers is often triggered along boundaries of surface convergence and is moderately well-understood, nocturnal CI is relatively unexplored. Since both the thermodynamic environments and the dynamic forcing mechanisms responsible for producing convection are fundamentally different at night, the impacts of storm-scale data assimilation (DA) cannot be assumed to be the same between night and day. As nocturnal convection is often elevated and initiated by features located above the surface, the assimilation of an unprecedented observation set collected during the Plains Elevated Convection at Night (PECAN) field project can provide key information for estimating such environments.

This study applies a GSI-based EnKF forecast system to a 26 June 2015 nocturnal CI event from the PECAN experiment to determine the impact of assimilating unique, high-frequency observations taken during the project including mobile surface platforms, thermodynamic profilers, thermodynamic profilers, and wind profilers. Improvements in elevated moisture layers by high frequency profilers such as the Atmospheric Emitted Radiance Interferometer (AERI) can improve analyses of buoyance and the pre-convective environment. Also, improvements in the low-level jet (LLJ) by Doppler Lidars and wind profilers can enhance convergence at the LLJ terminus and provide the forcing for nocturnal CI. Findings that will be presented at this conference include observation impact results from assimilating the above observations, as well as using observations from the field project for verification.