Samuel Degelia-March 8-Convective Meteorology (Mesoscale Dynamics) Seminar

Convective Meteorology (Mesoscale Dynamics) Seminar

Evaluating of the Impact of Assimilating PECAN Observations on Forecasts of Nocturnal Convection Initiation: A Case Study and Ongoing Systematic Experiments

Samuel Degelia

Friday, March 8th

3:00pm/NWC 5600

Numerical weather prediction models often fail to correctly forecast convection initiation (CI) at night in the Great Plains. To improve our understanding of such events, researchers collected unique observations from thermodynamic and kinematic profilers as part of the Plains Elevated Convection at Night (PECAN) experiment. The assimilation of these observations can aid in analyses of key features that are not easily observed by conventional datasets This talk presents forecasts of a nocturnal CI event from PECAN in which assimilating the PECAN dataset improves the timing, location, and orientation of CI. Specifically, radio wind profilers and rawinsondes are shown to be the most impactful instrument by enhancing the moisture advection into the region of CI. Assimilating thermodynamic profiles collected by AERIs increases midlevel moisture and improves the ensemble probability of CI. Assimilating Doppler lidar and surface data only slightly improves the CI forecast by enhancing the convergence along an outflow boundary that partially forces the nocturnal CI event. Our findings suggest that a mesoscale network of profiling and surface instruments can greatly improve short-term forecasts of nocturnal convection.

However, the strong forcing mechanisms for the 26 June event are well-captured by each experiment in the case study. It is unclear whether assimilating the PECAN dataset could improve convergence mechanisms for other CI events, or if the observation impacts would be as large when the mechanisms are not well-captured. As nocturnal convection can be initiated by many other features such as atmospheric bores or internal gravity waves, we will also present work that is ongoing to expand the observation sensitivity experiments to a variety of CI events from PECAN. The goal of this ongoing systematic study is to evaluate the impact of co-locating thermodynamic and kinematic profilers with the operational rawinsonde network. To facilitate this work, an object-based method will also be presented that quantifies timing, location, and orientation errors for CI forecasts.