This study investigates the impact of nonlinear vertical land motion (VLM) on relative sea-level (RSL) changes, highlighting its significant role in coastal projections. Vertical land motion, which can be linear or nonlinear, influences regional RSL changes, often differing from climate-driven absolute sea-level changes. The research uses a probabilistic reconstruction of VLM from 1995 to 2020 to assess its contribution to RSL changes up to 2150. The results show that nonlinear VLM can drive RSL changes of up to 50 cm by 2150 and increase uncertainty in projections by up to 1 m on a regional scale. The study emphasizes the importance of incorporating nonlinear VLM in sea-level change projections to better understand future coastal impacts. The study combines GNSS data, tide gauge records, and satellite altimetry to reconstruct VLM. A Bayesian principal component analysis is used to estimate linear trends and common modes of variability, with auto-correlated Gaussian Random Walks modeling temporal variations. The reconstruction provides a detailed 3D VLM map, revealing regional variations in subsidence and uplift. The results show that VLM contributes significantly to RSL changes, with subsidence rates in regions like the Gulf of Mexico and Australia being higher than GIA model estimates. Nonlinear VLM is particularly significant in tectonically active regions, where it can offset absolute sea-level changes. The study also compares VLM reconstructions with IPCC AR6 projections, showing that VLM explains a significant fraction of RSL variance. The inclusion of nonlinear VLM increases the uncertainty in RSL projections, especially in regions with high subsidence rates. The research underscores the need for more accurate VLM data, particularly in areas with high subsidence, to improve future sea-level projections. The findings highlight the importance of considering nonlinear VLM in climate models to better predict coastal impacts and manage risks associated with rising sea levels.This study investigates the impact of nonlinear vertical land motion (VLM) on relative sea-level (RSL) changes, highlighting its significant role in coastal projections. Vertical land motion, which can be linear or nonlinear, influences regional RSL changes, often differing from climate-driven absolute sea-level changes. The research uses a probabilistic reconstruction of VLM from 1995 to 2020 to assess its contribution to RSL changes up to 2150. The results show that nonlinear VLM can drive RSL changes of up to 50 cm by 2150 and increase uncertainty in projections by up to 1 m on a regional scale. The study emphasizes the importance of incorporating nonlinear VLM in sea-level change projections to better understand future coastal impacts. The study combines GNSS data, tide gauge records, and satellite altimetry to reconstruct VLM. A Bayesian principal component analysis is used to estimate linear trends and common modes of variability, with auto-correlated Gaussian Random Walks modeling temporal variations. The reconstruction provides a detailed 3D VLM map, revealing regional variations in subsidence and uplift. The results show that VLM contributes significantly to RSL changes, with subsidence rates in regions like the Gulf of Mexico and Australia being higher than GIA model estimates. Nonlinear VLM is particularly significant in tectonically active regions, where it can offset absolute sea-level changes. The study also compares VLM reconstructions with IPCC AR6 projections, showing that VLM explains a significant fraction of RSL variance. The inclusion of nonlinear VLM increases the uncertainty in RSL projections, especially in regions with high subsidence rates. The research underscores the need for more accurate VLM data, particularly in areas with high subsidence, to improve future sea-level projections. The findings highlight the importance of considering nonlinear VLM in climate models to better predict coastal impacts and manage risks associated with rising sea levels.