Abstract: Melt pond has important influence on sea ice. Owning to the scarcity of field observation data, there are still large uncertainties in melt pond parameterization schemes of current sea ice models, and this is one of the key factors degrading the accuracy of sea ice simulation. This research presents the melt pond parameter estimation based on the adjoint model technique. For the first time, based on the automatic differentiation tool, the adjoint model of TOPO melt pond scheme in CICE6 sea ice model was attained. Through the sensitivity test based on the adjoint model, the drainage rate parameter with the largest sensitivity was chosen as the candidate parameter. A parameter adjustment scheme was constructed using the forward model, the TOPO adjoint model and the L-BFGS optimization program. The drainage rate parameter in the first-year ice and multi-year ice region were adjusted separately, and the optimized parameters were then used to produce the new simulation results. Our results show that, compared with the simulation with default model parameter, the root mean square error of the melt pond fraction in the first-year ice region is reduced from 12.97% to 5.29%, a reduction of 59.21%. For the multi-year ice region, the root mean square error of the melt pond fraction is reduced from 11.96% to 7.76%, a reduction of 35.11%. The parameter estimation scheme can effectively adjust the model parameters and improve the melt pond fraction simulation, which lays the foundation to achieve the parameter optimization and simultaneous multi-parameter estimation for the whole Arctic.