Microbial methanogenesis, which produces methane, significantly contributes to global warming. The reaction is significantly influenced by the temperature, quality, and quantity of organic substrates. Understanding and predicting these factors are particularly important for animal manure storage, which accounts for 6% of total anthropogenic methane emissions. However, accurately estimating methane emission is difficult, as manure temperature varies significantly from the air temperature. The objective of the study was to i) develop a manure storage temperature model and incorporate it into the Manure-DNDC emission model, ii) validate Manure-DNDC using measurements of manure temperature and CH4 emissions from an earthen storage at a swine farm in Manitoba and iii) conduct a scenario analysis on the CH4 mitigation effect of frequent manure removal from an under-barn pit. The manure temperature model was developed using a surface energy balance approach and Fourier heat conduction. This was integrated into Manure-DNDC. The revised model accurately predicted both manure temperature (Willmott d-index > 0.91) and CH4 emissions (d > 0.92) using three years of observations. The scenario analysis showed that retention time in the under-barn pit substantially affected CH4 emissions, where shortening the retention time from 1 month to none yielded a 19.2% decrease in CH4 emissions over the whole storage cycle. Frequent manure removal in the warm season was, however, not necessary, as the temperature difference between the under-barn pit and outdoor storage was minimal. Finally, we recommend that a detailed simulation of organic substrates and microbial dynamics be included in future methanogenesis simulations for manure storage.