Today the societies face an unprecedented challenge trying to restrain the global warming. After the COP21 that took place in Paris in 2015, the signatory countries of the United Nations Framework Convention on Climate Change (UNFCCC) agreed on the limitation of greenhouse gases emissions allowing to limit the temperature increase under 1.5°C compared to the pre-industrial era. Yet, the scientific community believe that consideration should be given to the use of geo-engineering to keep global warming below the defined threshold. In this context, a recent CESBIO and CNRM-led study has shown that land cover management could be used as a mitigating lever against global warming. They demonstrated that the introduction of cover crops over the Europe could result in a cooling effect. Indeed, in most parts of Europe the albedo of vegetation is higher than the albedo of bare soil so in these areas, the introduction of cover crops over fallow periods leads to a negative radiative forcing proportional to the increase in albedo. Based on the use of remote sensing data, land cover databases, meteorological data, national agricultural statistics and ground measurements the authors established a cover crop introduction model that simulate the radiative forcing followed by the increase in albedo. Carrer & al (2018) showed that, according to a realistic scenario, cover crops could be introduced over 4.17% of the European surface resulting in a radiative forcing of 3.16MtCO2-eq.yr-1. Here we propose a deeper analysis of what climatic impact could be induced by the use of cover crops. Considering that cover crops are buried into the soil, the following increase in soil organic matter leads to the darkening of the ground which will affect the surface albedo and thus the radiative forcing. This effect is considered here. We also brought in a new implementation scenario of introduction to simulate all cases currently set up i.e., after a winter crop and before a summer crop but also between two summer crops and to get a more realistic estimation of the albedo effect. Also we refined our results by filtering the area covered by snow during cover crops implementation. So far we used snow-free satellite albedo data leading, as shown by Kaye and Quemada (2017) to wrong estimation of radiative forcing over areas and periods covered by snow.