<p><strong>Abstract.</strong> Emissions of methane (CH₄) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH₄ budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH₄ columns can help to narrow down some of the uncertainties in the tropical CH₄ emission budget. We use proxy column retrievals of atmospheric CH₄ (XCH₄) from the Japanese Greenhouse gases Observing SATellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5&amp;thinsp;&amp;times;&amp;thinsp;0.625) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH₄ are less sensitive to scattering due to clouds and aerosol than full physics retrievals but the method assumes that the global distribution of carbon dioxide (CO₂) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH₄ data products that are determined using different model CO₂ fields. We infer monthly emissions from GOSAT XCH₄ data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010&amp;ndash;2016 range from 75 (72&amp;ndash;78)&amp;thinsp;Tg&amp;thinsp;yr^&amp;minus;1 to 80 (78&amp;ndash;83)&amp;thinsp;Tg&amp;thinsp;yr^&amp;minus;1, dependent on the proxy XCH₄ data used, with larger differences in northern hemisphere Africa than southern hemisphere Africa. We find a robust positive linear trend in tropical African CH₄ emissions for our seven-year study period, with values of 1.5 (1.1&amp;ndash;1.9)&amp;thinsp;Tg&amp;thinsp;yr^&amp;minus;1 or 2.1 (1.7&amp;ndash;2.5)&amp;thinsp;Tg&amp;thinsp;yr^&amp;minus;1, dependent on the CO₂ data product used in the proxy retrieval. A substantial portion of this increase is due to a short-term increase in emissions of 3&amp;thinsp;Tg&amp;thinsp;yr^&amp;minus;1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data we find this increase in CH₄ emission is consistent with an increase in wetland extent due to increased inflow from the White Nile. We find a strong seasonality in emissions across northern hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH₄ emissions from the wetland area of the Congo basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.</p>