Abstract
The MEthane Remote sensing Lidar missioN (MERLIN), currently in phase C, is a joint cooperation between France and Germany on the development of a spatial Integrated Path Differential Absorption (IPDA) LIDAR (LIght Detecting And Ranging) to conduct global observations of atmospheric methane. This presentation will focus on the status of a LIDAR mission data simulator and processor developed at LMD (Laboratoire de Météorologie Dynamique), Ecole Polytechnique, France, for MERLIN to assess the performances in realistic observational situations.
Highlights
The major anthropogenic sources of CH4 are the emissions from energy production, landfills, waste treatment, cattle, rice fields and incomplete biomass burning
We present here the MERLIN measurement principles and the work developed within the MERLIN team at LMD in regards to the LIDAR signals simulation with LIDSIM (LIDar SIMulator) to be able to simulate the Level 0/1a data and the inversion of this signal done with PROLID (PROcessor LIDar) to obtain the Level 1b and Level 2 product, the column-weighted dry-air mixing ratios of CH4, referred to as XCH4, over the satellite sub-track
The core of LIDSIM determines the photoelectrons number from the signal and from the background. This step needs a great accuracy on spectroscopic information for the CH4 multiplet and for the H2O and CO2 in the vicinity of the two MERLIN wavelengths, two gases whose effects must be taken into account in the radiative transfer calculations
Summary
The major anthropogenic sources of CH4 are the emissions from energy production, landfills, waste treatment, cattle, rice fields and incomplete biomass burning. After carbon dioxide (CO2), methane (CH4) is the second anthropogenic greenhouse gas responsible for global warming. Understanding and monitoring the evolution of the mechanisms of sources and sinks of this gas in the atmosphere represents a major challenge to better anticipate the future climate. The goal of MERLIN is to obtain global measurements of the spatial and temporal gradients of atmospheric CH4 with a precision and accuracy sufficient to constrain methane fluxes significantly better than with the current observations made by passive optical radiometry techniques and limited in precision as well as in spatial and temporal coverage (cloud cover, aerosol interference, nighttime). In order to reduce the relative random error due mostly to the signal to noise ratio of the instrument, the data are going to be horizontally averaged over 50km along track
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