A128-14
Assessment of lidar XCH4 measurements during ACT-America 2019 for boundary layer methane and emission model constraint

Friday, 11 December 2020: 11:09
Virtual
Rory Alistair Barton-Grimley1, Amin R Nehrir1, Zachary Barkley2, Susan A Kooi3 and James E Collins Jr3, (1)NASA Langley Research Center, Hampton, VA, United States, (2)The Pennsylvania State University, University Park, PA, United States, (3)SSAI, Hampton, VA, United States
Abstract:
Atmospheric methane is a potent and abundant greenhouse gas (GHG) with increasing importance due to rising emissions and their subsequent impact on radiative forcing, indicating an important driving role in climate change. The recent Earth Science Decadal Survey called for further understanding of the sources and sinks of atmospheric methane, the processes that will affect their future concentrations, and identified the need for advanced observing capabilities to elucidate these issues. HALO, a combined methane Differential Absorption Lidar and Aerosol/Cloud High Spectral Resolution Lidar participated in the ACT-America summer 2019 campaign to assist in constraining the emission and transport of GHGs. In this presentation we will discuss the utility of using an in-situ point measurement versus lidar column measurement for inventory and source identification applications. Comparisons between in-situ and lidar column measurements of methane will be made to assess whether point measurements are useful when the assumption of a well-mixed boundary layer, a practice commonly used, is not valid. We will also show that a lidar column measurement can apportion boundary layer methane from the column and has the ability to identify boundary layer enhancements in fair weather conditions using atmospheric backscatter signals, a measurement capability that has the potential to transform the observational strategies of future airborne carbon cycle science investigations. We will also present on the differences and utility of constraining emission models using an in-situ versus lidar column and asses the resulting uncertainties of each.