Abstract
The CNES/DLRMERLINsatellite mission aims at measuring methane dry-air mixing ratio column (XCH4) and thus improving surface flux estimates. In order to get a 1% precision on XCH4measurements, MERLIN signal processing assumes an averaging of data over 50 km. The induced biases due to the non-linear IPDA lidar equation are not compliant with accuracy requirements. This paper analyzes averaging biases issues and suggests correction algorithms tested on realistic simulated scenes.
Highlights
Methane is the second most important anthropogenic greenhouse gas after carbon dioxide Error! Reference source not found
The French-German spatial mission MERLIN (Methane Remote Sensing Lidar Mission) aims at measuring the methane dry-air mixing ratio (XCH4) reaching unprecedented accuracy with targeted systematic error that is less than 0.2% relative error for all latitudes and all seasons
This study shows that it is possible to limit the bias induced by the averaging scheme when an appropriate bias correction is implemented
Summary
Methane is the second most important anthropogenic greenhouse gas after carbon dioxide Error! Reference source not found. Integrated Path Differential Absorption (IPDA) lidar measures the laser light (here short pulses) scattered back from the surface in order to retrieve the column content of a specific trace gas along the line of sight. Differential absorption uses the difference in transmission between the on-line signal with a wavelength set about the center of the CH4 absorption line and the off-line signal which wavelength is significantly less absorbed From these two signals the Differential Absorption Optical Depth (DAOD) of CH4 is computed and the corresponding XCH4 can be derived. In order to reach the targeted 1% relative random error on XCH4 measurements, the signal processing of MERLIN requires an horizontal averaging of data over 50 km along track. A comparative evaluation of the averaging schemes on realistic scenes is a key element to select the best approach (i.e. the least biased) for MERLIN processing
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