3.1 What We Have Learned about Nocturnal MCS Environments from High-Temporal-Resolution PECAN Sounding Observations

Tuesday, 9 January 2018: 1:30 PM
Room 6A (ACC) (Austin, Texas)
Russ S. Schumacher, Colorado State Univ., Fort Collins, CO; and S. M. Hitchcock, M. D. Parker, M. C. Coniglio, C. L. Ziegler, and J. M. Peters

In the central United States, mesoscale convective systems (MCSs) are commonly observed at night, when atmospheric features such as near-surface stable layers and low-level jets are often in place. Yet detailed observations of the temporal evolution of these features, and how they influence MCS processes (and in turn, how the MCSs influence their environment) remain limited. One of the goals of the Plains Elevated Convection at Night (PECAN) field campaign in 2015 was to better observe and understand the interactions and feedbacks between MCSs and their environments, and one of the key observing strategies was to launch large quantities of radiosondes from both fixed and mobile platforms.

In total, approximately 1500 radiosonde profiles were collected during PECAN, with around 500 of those soundings taken in MCS environments on 13 different days. Cluster analysis reveals that soundings taken in pre-convective environments can generally be grouped into 3 categories: 1) those with a shallow inversion, an elevated low-level region of maximum 𝛉e and a largely unstable layer up to 500 mb; 2) those that maintain a daytime-like planetary boundary layer (PBL) and are moist neutral above the boundary layer; and 3) those that are moist neutral through the mid-levels and have a region of mid-level instability. Post-convective soundings demonstrate significantly more variability, from strong cold pools (consistent with gravity currents) to more complex structures suggestive of gravity waves, or gravity wave-current combinations.

In some cases, the observed profiles differ considerably from operational analyses and model simulations, particularly in terms of water vapor. These errors can in turn be related to errors in the predicted timing, location, and evolution of the MCSs by convection-allowing numerical models. These errors will be summarized, and we will discuss other opportunities for improving understanding and prediction of nocturnal MCSs that the PECAN sounding data make possible.

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