Semi empirical sea level modelling Semi empirical sea level models (SEMs) exploit physically motivated empirical relationships between global sea level and certain drivers in the following global mean temperature. This model class evolved as a supplement to process based models (Rahmstorf (2007)) which were unable to fully represent all relevant processes. They thus failed to capture past sea level change (Rahmstorf et al. (2012)) and were thought likely to underestimate future sea level rise. Semi empirical models were found to be a fast and useful tool for exploring the uncertainties in future sea level rise consistently giving significantly higher projections than process based models. In the following different aspects of semi empirical sea level modelling have been studied. Models were first validated using various data sets of global sea level and temperature. SEMs were then used on the glacier contribution to sea level and to infer past global temperature from sea level data via inverse modelling. Periods studied encompass the instrumental period covered by…