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American Geophysical Union, Journal of Geophysical Research: Atmospheres, 20(123), p. 11,766-11,785, 2018

DOI: 10.1029/2018jd028907

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Error Budget of the MEthane Remote LIdar missioN and Its Impact on the Uncertainties of the Global Methane Budget

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

MEthane Remote LIdar missioN (MERLIN) is a German-French space mission, scheduled for launch in 2024 and built around an innovative light detecting and ranging instrument that will retrieve methane atmospheric weighted columns. MERLIN products will be assimilated into chemistry transport models to infer methane emissions and sinks. Here the expected performance of MERLIN to reduce uncertainties on methane emissions is estimated. A first complete error budget of the mission is proposed based on an analysis of the plausible causes of random and systematic errors. Systematic errors are spatially and temporally distributed on geophysical variables and then aggregated into an ensemble of 32 scenarios. Observing System Simulation Experiments are conducted, originally carrying both random and systematic errors. Although relatively small (±2.9 ppb), systematic errors are found to have a larger influence on MERLIN performances than random errors. The expected global mean uncertainty reduction on methane emissions compared to the prior knowledge is found to be 32%, limited by the impact of systematic errors. The uncertainty reduction over land reaches 60% when the largest desert regions are removed. At the latitudinal scale, the largest uncertainty reductions are achieved for temperate regions (84%) and then tropics (56%) and high latitudes (53%). Similar Observing System Simulation Experiments based on error scenarios for Greenhouse Gases Observing SATellite reveal that MERLIN should perform better than Greenhouse Gases Observing SATellite for most continental regions. The integration of error scenarios for MERLIN in another inversion system suggests similar results, albeit more optimistic in terms of uncertainty reduction.