Presented on March 9, 2022, by

Dr. Ya-Chien Feng
Earth Scientist
Department of Atmospheric Sciences & Technology
Pacific Northwest National Laboratory (PNNL)

Abstract:

The development of clouds and convection are highly sensitive to the small change of the water vapor in both observations and numerical simulations. Quantifying the natural variability of the moisture at mesoscales is challenging but is needed for data interpretation, data assimilation and future observation network development. This study aims to advance the understanding of the finer horizontal variability and vertical structures of water vapor in both clear and storm conditions from ground-based remote sensing instruments, weather radars and lidars.

Weather radars can provide high resolution refractivity retrievals of near-surface air, in addition to the standard reflectivity, radial velocity and dual-polarimetric observations.  Radar-retrieved refractivity depicts the near-surface moisture distribution at the meso-gamma scale.  This study presents a novel examination of moisture variability in a moisture-rich summertime tropical coastal region in Taiwan. Refractivity analyses demonstrate how a moisture field varies with the different synoptic-scale flows, complex local physiography, and various storm types. MicroPulse Differential absorption lidar (MPD) provides high spatiotemporal resolution of water vapor in the lower atmosphere.  A network of MPD was deployed in Oklahoma during the spring and summer of 2019. The difference of water vapor between 1 to 4 km height above the surface among the five MPDs about 40-100 km apart is examined under pre-storm and clear weather environments. The characteristics of moisture variability and its spatiotemporal representativeness are analyzed and integrated with the vertical wind and temperature observations from 3-hr resolution radiosondes, ground-based GPS integrated water vapor and the storm locations revealed from radars.

Moisture variability observed from radars and lidars

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