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Error budget of the MEthane Remote LIdar missioN (MERLIN) and its impact on the uncertainties of the global methane budget

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Marshall,  Julia
Satellite-based Remote Sensing of Greenhouse Gases, Dr. J. Marshall, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Bousquet, P., Pierangelo, C., Bacour, C., Marshall, J., Peylin, P., Ayar, P. V., et al. (2018). Error budget of the MEthane Remote LIdar missioN (MERLIN) and its impact on the uncertainties of the global methane budget. Journal of Geophysical Research: Atmospheres, 123, 11766-11785. doi:10.1029/2018JD028907.


Cite as: http://hdl.handle.net/21.11116/0000-0002-4A65-A
Abstract
MERLIN is a German‐French space mission, scheduled for launch in 2023 and built around an innovative LIDAR 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 thirty‐two scenarios. Observing System Simulation Experiments (OSSE) 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 lands 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 OSSE based on error scenarios for GOSAT reveal that MERLIN should perform better than GOSAT for most continental regions. The integration of error scenarios for MERLIN in another inversion system suggests similar results, albeit more optimistic in term of uncertainty reduction.