Monday, 13 January 2020
Hall B (Boston Convention and Exhibition Center)
The planetary boundary layer (PBL) is the lowest ~ 1-2 km of the atmosphere that is strongly influenced by the Earth's surface through turbulent mixing. The PBL controls the fluxes of mass, energy, and momentum between the surface and the free troposphere, which is extremely important in driving larger-scale atmospheric dynamics. Additionally, PBL depth is a key physical parameter of the PBL affected by numerous physical processes within the boundary layer. The PBL depth also varies significantly across different geographical regions, over time, and during different weather conditions. Most conventional passive satellite sensors fail to observe the PBL due to attenuation or limited vertical resolution, which hinders proper characterization of PBL thermodynamic properties and depth detection. The Global Navigation Satellite System (GNSS) radio occultation (GNSS-RO) provides high vertical resolution soundings necessary for PBL depth detection over both land and ocean in all-weather conditions. In addition, the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) constellation - with six satellites in precessing orbits - provides the necessary diurnal cycle coverage for this endeavor. In this study, COSMIC RO and Atmospheric Radiation Measurement (ARM) radiosonde profiles from 2007 to 2013 were analyzed to estimate the diurnal cycle of the PBL vertical structure and its depth over the Southern Great Plains (SGP) in the US, across ~ 9,000 square miles spanning north-central Oklahoma and south-central Kansas. Significant diurnal variations in the terrestrial PBL were observed in both radiosondes and the colocated COSMIC RO profiles. Seasonal changes in the PBL depth diurnal cycles were also characterized. The limitations of COSMIC RO soundings inside the PBL, along with the expected improvement of PBL diurnal characterization from the newly launched COSMIC-2 soundings, will also be discussed. Such PBL diurnal and seasonal changes can be further incorporated into boundary layer parameterizations to help improve weather and climate model prediction.
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