Sea-level fingerprints, the spatial patterns of sea level change resulting from rapid melting of glaciers and ice sheets, play an important role in understanding past and projecting future changes in relative sea level (RSL). Over century timescales, the viscous flow of Earth’s interior is a small component of the total deformation due to ice loading in most regions, so fingerprints computed using elastic Earth models are accurate. However, in regions where the viscosity is orders of magnitude lower than the global average, the viscous component of deformation can be significant, in which case it is important to consider models of viscoelastic deformation. There is evidence that the glaciated regions of Alaska, Western Canada and USA, and the Southern Andes are situated on top of mantle regions in which the local viscosity is several orders of magnitude lower than typical global mean values. The goal of this work is to determine the importance of viscous flow in computing RSL fingerprints associated with future ice mass loss from these regions. Version 5.0 of the Randolph Glacier Inventory is used to estimate the ice load distribution required for calculating sea-level fingerprints. For the glaciated regions that have lower than average viscosity, fingerprints were calculated using an elastic Earth model and a 3D viscoelastic model to quantify the influence of viscous flow on the predicted sea level changes. Using glacier mass loss values for the intermediate future climate scenario Representative Concentration Pathway (RCP) 4.5, the global sea level response was computed at 2100 CE relative to 2010 CE due to melting from all glacier regions. On comparing the results of the two models it was found that ice-load-induced viscous flow contributes significantly (more than a few cm) to the RSL fingerprints only in near-field regions. However, in these regions, the non-elastic contribution can be 10s of cm. For example, at Juneau, USA the elastic calculation gave relative sea level changes of ∼ −45 cm, compared to ∼ −120 cm based on the viscoelastic calculation.

A rapidly melting ice sheet produces a distinctive geometry of sea level (SL) change. Thus, a network of SL observations may, in principle, be used to infer sources of meltwater flux. We outline a new method, based on a Kalman smoother, for using tide gauge observations to estimate the individual sources of global SL change. The Kalman smoother technique iteratively calculates the maximum likelihood estimate of Greenland and West Antarctic ice sheet melt rates at each time step, and it allows for data gaps while also permitting the estimation of non-linear trends. We have also implemented a fixed multi-model Kalman filter that allows us to rigorously account for additional contributions to SL changes, such as glacial isostatic adjustment and thermal expansion. We report on a series of detection experiments based on synthetic SL data that explore the feasibility of extracting source information from SL records before applying the new methodology to historical tide gauge records. In the historical tide gauge study we infer a global mean SL rise of ~1.5 ± 0.5 mm/yr up to 1970, followed by an acceleration to a rate of ~2.0 ± 0.5 mm/yr in 2008. In addition to its connection to SL, Greenland and its large ice sheet act as a barrier to storm systems traversing the North Atlantic. As a result of the interaction with Greenland, low-pressure systems located in the Irminger Sea, between Iceland and Greenland, often produce strong low-level winds. Through a combination of modeling and the analysis of rare in-situ observations, we explore the evolution of a lee cyclone that resulted in three high-speed-wind events in November 2004. Understanding Greenland’s role in these events is critical in our understanding of local weather in this region.

A rapidly melting ice sheet produces a distinctive geometry of sea level (SL) change. Thus, a network of SL observations may, in principle, be used to infer sources of meltwater flux. We outline a new method, based on a Kalman smoother, for using tide gauge observations to estimate the individual sources of global SL change. The Kalman smoother technique iteratively calculates the maximum likelihood estimate of Greenland and West Antarctic ice sheet melt rates at each time step, and it allows for data gaps while also permitting the estimation of non-linear trends. We have also implemented a fixed multi-model Kalman filter that allows us to rigorously account for additional contributions to SL changes, such as glacial isostatic adjustment and thermal expansion. We report on a series of detection experiments based on synthetic SL data that explore the feasibility of extracting source information from SL records before applying the new methodology to historical tide gauge records. In the historical tide gauge study we infer a global mean SL rise of ~1.5 ± 0.5 mm/yr up to 1970, followed by an acceleration to a rate of ~2.0 ± 0.5 mm/yr in 2008. In addition to its connection to SL, Greenland and its large ice sheet act as a barrier to storm systems traversing the North Atlantic. As a result of the interaction with Greenland, low-pressure systems located in the Irminger Sea, between Iceland and Greenland, often produce strong low-level winds. Through a combination of modeling and the analysis of rare in-situ observations, we explore the evolution of a lee cyclone that resulted in three high-speed-wind events in November 2004. Understanding Greenland’s role in these events is critical in our understanding of local weather in this region.