A simple relationship between global sea-level variations and global mean temperature is proposed and tested using synthetic data from a climate model. When applied to observed data from 1880–2000, the correlation is >0.99, explaining 98% of the variance. For future temperature scenarios, the relationship projects sea-level rise ranging from 75 to 190 cm for 1990–2100. Sea-level rise is influenced by both thermal expansion and ice melt. The dual model, which includes both a slow response (thermal expansion) and a rapid response (ice melt), provides a better fit to observed data than the original semiempirical method. The dual model captures the 20th-century sea-level rise and short-term variability, explaining 82% of the variance. The model also performs well for the past millennium, showing that the dual model can capture short-term responses and long-term trends. The dual model is applied to observed data, showing a strong correlation between global temperature and sea-level rise. The model parameters are determined by fitting to the data, and the results show that the dual model provides a better fit than the original method. The model also accounts for non-climatic contributions to sea-level rise, such as groundwater mining. The results suggest that sea-level rise will continue to increase in the 21st century, with projections ranging from 75 to 190 cm for 1990–2100. The model also shows that the thermal share in sea-level rise declines over the century, while the ice melt share increases. The results suggest that emissions reductions early in the century will be more effective in limiting sea-level rise than reductions later on. The model also highlights the importance of considering nonlinear ice-sheet responses, which could lead to faster sea-level rise than projected. The study concludes that the dual model provides a robust method for projecting future sea-level rise based on global temperature.A simple relationship between global sea-level variations and global mean temperature is proposed and tested using synthetic data from a climate model. When applied to observed data from 1880–2000, the correlation is >0.99, explaining 98% of the variance. For future temperature scenarios, the relationship projects sea-level rise ranging from 75 to 190 cm for 1990–2100. Sea-level rise is influenced by both thermal expansion and ice melt. The dual model, which includes both a slow response (thermal expansion) and a rapid response (ice melt), provides a better fit to observed data than the original semiempirical method. The dual model captures the 20th-century sea-level rise and short-term variability, explaining 82% of the variance. The model also performs well for the past millennium, showing that the dual model can capture short-term responses and long-term trends. The dual model is applied to observed data, showing a strong correlation between global temperature and sea-level rise. The model parameters are determined by fitting to the data, and the results show that the dual model provides a better fit than the original method. The model also accounts for non-climatic contributions to sea-level rise, such as groundwater mining. The results suggest that sea-level rise will continue to increase in the 21st century, with projections ranging from 75 to 190 cm for 1990–2100. The model also shows that the thermal share in sea-level rise declines over the century, while the ice melt share increases. The results suggest that emissions reductions early in the century will be more effective in limiting sea-level rise than reductions later on. The model also highlights the importance of considering nonlinear ice-sheet responses, which could lead to faster sea-level rise than projected. The study concludes that the dual model provides a robust method for projecting future sea-level rise based on global temperature.