Observations of a squall line and its near environment using high-frequency rawinsonde launches during VORTEX2

Rawinsonde data were collected before and during passage of a squall line in Oklahoma on 15 May 2009 during the Second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). Nine soundings were released within 3 h, allowing for unprecedented analysis of the squall line's internal structure and nearby environment. Four soundings were released in the prestorm environment and they document the following features: low-level cooling associated with the reduction of solar isolation by a cirrus anvil; abrupt warming (1.5 K in 30 min) above the boundary layer, which is probably attributable to a gravity wave; increases in both low-level and deep-layer vertical wind shear within 100 km of the squall line; and evidence of ascent extending at least 75 km ahead of the squall line. The next sounding was released ~ 5 km ahead of the squall line's gust front; it documented a moist absolutely unstable layer within a 2-km-deep layer of ascent, with vertical air velocity of approximately 6 m s^-1. Another sounding was released after the gust front passed but before precipitation began; this sounding showed the cold pool to be ~ 4 km deep, with a cold pool intensity C ≈ 35 m s^-1, even though this sounding was located only 8 km behind the surface gust front. The final three soundings were released in the trailing stratiform region of the squall line, and they showed typical features such as: "onion"-shaped soundings, nearly uniform equivalent potential temperature over a deep layer, and an elevated rear inflow jet. The cold pool was 4.7 km deep in the trailing stratiform region, and extended ~ 1 km above the melting level, suggesting that sublimation was a contributor to cold pool development. A mesoscale analysis of the sounding data shows an upshear tilt to the squall line, which is consistent with the cold pool intensity C being much larger than a measure of environmental vertical wind shear ΔU. This dataset should be useful for evaluating cloud-scale numerical model simulations and analytic theory, but the authors argue that additional observations of this type should be collected in future field projects.