Development and Validation of an End-to-End Simulator and Gas Concentration Retrieval Processor Applied to the MERLIN Lidar Mission

Abstract

In the context of MERLIN (MEthane Remote LIdar missioN), a French–German spatial lidar mission dedicated to monitoring the atmospheric methane content, two software programs have been developed: LIDSIM (LIDar SIMulator) and PROLID (PROcessor LIDar). The objectives are to assess whether the instrument design meets the performance requirements and to study the sensitivity of this performance to geophysical parameters. LIDSIM is an end-to-end mission simulator and PROLID is a retrieval processor that provides mole fractions of methane in dry air, averaged over an atmospheric column. These two tools are described in this paper. Results of the validation tests and the first full orbit simulations are reported. Merlin target performance does not seem to be reachable but breakthrough performance is reached.

Impact of Meteorological Uncertainties in the Methane Retrieval Ground Segment of the MERLIN Lidar Mission

“…It records the signals corresponding to the energies emitted in these beams and those backscattered by the ground or a cloud [9]. The ground processing of these records allows us to estimate the DAOD f ull (Differential Atmospheric Optical Depth over the entire optical path) from the normalised ratio between the energies of the two beams and the SSE (Scattering Surface Elevation) from the assessment of the time elapsed between the emission and reception of the signals (for a description of how such estimates are made, see MERLIN ATBD [5] or Cassé et al [6]). Then, XCH r 4 , the mole fraction of methane to dry air averaged over the atmospheric column, is retrieved from the following relations derived from the Beer-Lambert law:…”

“…where X G (p) denotes the mole fraction profile with respect to dry air, g(lat, p) the gravity at the target location (determined by its latitude and pressure), M d the molar mass of dry air, T(p) the temperature profile, q(p) the specific humidity profile and σ e f f G (ν 0 , p, T) an average (over the spectral distribution of the laser emission around wavenumber ν 0 ) of the absorption cross sections [6]. The absorption cross sections are computed from the GEISA2015 spectroscopic database [10] with specific improvements made by work carried out in the framework of the MERLIN mission [11,12].…”

“…The simulation is for a complete orbit. It is based on meteorological data from 6 May 2019 between 3:30 UT and 5:08 UT and on realistic reflectivity data (for more details, see Cassé et al [6]) but assumes a constant value of 1780 ppb for methane content. Although there is no simulation of instrumental noise, due to the limited numerical accuracy when encoding the file representing the data transmitted to the ground segment, filtering of shots with a signal-to-noise ratio greater than 1 is necessary to eliminate the shots for which there is no signal.…”

“…Figure 8 shows the mean and the standard deviation of the fifty differences between XCH r 4 (the mole fraction of methane to dry air averaged over the atmospheric column) obtained with Equation (1) for a set of meteorological parameters and its reference value [6]. This reference is defined as the pressure-averaged actual methane content provided by ECMWF with the weighting function WF CH 4 (p) calculated for the set of meteorological parameters from the unperturbed initial state.…”

“…The data processing is described in the MERLIN ATBD (Algorithm Theoretical Basis Document, an internal project document) [5]. The LMD (Laboratoire de Météorologie Dynamique) has designed two software packages, LIDSIM (LIDar SIMulator) and PROLID (PROcessor LIDar) [6], to investigate the sensitivity of MERLIN performance to different geophysical parameters by inverting simulated data orbits from realistic data and noise for the different processes.…”