MERLIN (MEthane Remote sensing LIdar missioN) is a Franco-German space mission designed to provide weighted columns of atmospheric methane through an inversion of the lidar signal using a priori information on the atmospheric state. Uncertainties about the meteorological parameters of the observed scene used in the ground segment contribute to the error budget on the retrieved methane column. With the LIDSIM (LIDar SIMulator) data simulator and the PROLID (PROcessor LIDar) inversion processor developed for MERLIN, we perform an impact experiment using ECMWF (European Centre for Medium Weather Range Forecast) ensemble forecast data. In addition, we estimate the standard deviation of the error in the methane column due to the meteorological uncertainties to be about 0.6 ppb. In addition, we innovate by discussing the impact of interpolations both in time and space, focusing on vertical extrapolations under the topography by using state-of-the-art methods to determine from the scatter between these methods the range in which the actual profile should be. We conclude that, in areas where the topography variations exceed 10 m over 10 km, an additional random error of 0.1 ppb is due to our lack of knowledge of the adjustment of atmospheric profiles to terrain. Finally, we point out that further work needs to be performed on temporal interpolation. Indeed, the 3 h time interpolation of atmospheric tides can create regional biases of up to 2 ppm (which is a major problem for models trying to identify methane sinks and sources).