Start Date

10-3-2017 2:00 PM

End Date

10-3-2017 3:30 PM

Abstract Text

The Purple Crow Lidar is a large aperture lidar, capable of retrieving water vapor profiles into the stratosphere. Water vapor in the upper Troposphere-Lower Stratosphere (UTLS) region is of particular importance in understanding Earth's radiative budget and atmospheric dynamics, making accurate UTLS measurements crucial. A comparison campaign with the NASA/GSFC ALVICE mobile lidar in the spring of 2012 showed PCL water vapor measurements were consistently larger than those of ALVICE in the lower stratosphere, prompting an investigation to characterize the system. The investigation looks into how changes to the data processing approach, as well as applying additional instrumental corrections, would affect the water vapor mixing ratio. We also look into a retrieval of the mixing ratio using optimal estimation method (OEM), which should provide greater insight into the associated data processing parameters and uncertainties.

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Mar 10th, 2:00 PM Mar 10th, 3:30 PM

P07. Characterizing the Purple Crow Lidar to investigate potential sources of wet bias

The Purple Crow Lidar is a large aperture lidar, capable of retrieving water vapor profiles into the stratosphere. Water vapor in the upper Troposphere-Lower Stratosphere (UTLS) region is of particular importance in understanding Earth's radiative budget and atmospheric dynamics, making accurate UTLS measurements crucial. A comparison campaign with the NASA/GSFC ALVICE mobile lidar in the spring of 2012 showed PCL water vapor measurements were consistently larger than those of ALVICE in the lower stratosphere, prompting an investigation to characterize the system. The investigation looks into how changes to the data processing approach, as well as applying additional instrumental corrections, would affect the water vapor mixing ratio. We also look into a retrieval of the mixing ratio using optimal estimation method (OEM), which should provide greater insight into the associated data processing parameters and uncertainties.