Simulating UNder ice Shelf Extreme Topography (SUNSET)
Lead Research Organisation:
British Antarctic Survey
Department Name: Science Programmes
Abstract
Global average sea level is rising at an ever-accelerating rate. Given the huge economic and societal impacts of this change, accurate forecasts of sea level are urgently needed to inform policymakers considering mitigation and adaptation strategies. Melting of the Antarctic and Greenland ice sheets currently contributes about one third of sea-level rise. The future of this melting is highly uncertain, and the worst-case scenario involves a substantial ice-sheet contribution to dangerous sea-level rise.
The largest ice-sheet contribution to sea level occurs when the ocean melts the base of ice shelves (floating extensions of the grounded ice sheet), increasing the flow of grounded ice into the ocean. The melt rate of ice shelves is determined by the transfer of heat from the ocean towards the ice. Recently, extreme topographic features, including step-like terraces and 1-10 km wide channels, have been discovered to be ubiquitous on the underside of rapidly melting ice shelves. These features significantly modify the patterns and rates of melting, and so are crucial to predicting sea level. However, such features are generally too small to be resolved in climate models and their effect must be understood and explicitly built into these models.
We will investigate how extreme topography on the underside of ice shelves changes ocean currents and melting. Beneath ice shelves with a smooth, gradually sloping base, melting can be viewed as a vertical process, and this is how it is currently represented in climate models. However, observations show that melting on the steeply sloping sides of extreme ice topography is actually horizontal, and much faster than the melting of a smooth ice base. In addition, turbulent ocean eddies generated by extreme topographic features will mix warm water up towards the ice, further enhancing the melting.
We will observe the influence of extreme ice topography beneath an Antarctic ice shelf using pressurised hot water to drill through more than a kilometre of ice, enabling access to the ocean cavity beneath. We will study the controls on melting using a targeted suite of the latest observational measurements: radar and sonar to track the ice topography and melting, and acoustic ocean current profiling and a string of temperature sensors to monitor the mixing of ocean heat towards the ice. This will provide a unique dataset of the close interaction between ocean mixing and ice melting.
We will then combine these observations with a hierarchy of computer simulations to develop a new representation of the effect of extreme ice topography in climate models. We will first simulate the flow around extreme topographic features using high-resolution large-eddy simulations, which resolve the ocean turbulence. This will provide insight into the mixing of warm water to the ice base, and its interaction with melting. We will then use an ocean model to study the role of ice channel geometry on the melt rate and flow properties. Using these simulations, we will develop mathematical formulae to represent the influence of extreme ice topography. We will implement these formulae into the ocean model and test its ability to represent the influence of extreme ice topography in climate models.
The largest ice-sheet contribution to sea level occurs when the ocean melts the base of ice shelves (floating extensions of the grounded ice sheet), increasing the flow of grounded ice into the ocean. The melt rate of ice shelves is determined by the transfer of heat from the ocean towards the ice. Recently, extreme topographic features, including step-like terraces and 1-10 km wide channels, have been discovered to be ubiquitous on the underside of rapidly melting ice shelves. These features significantly modify the patterns and rates of melting, and so are crucial to predicting sea level. However, such features are generally too small to be resolved in climate models and their effect must be understood and explicitly built into these models.
We will investigate how extreme topography on the underside of ice shelves changes ocean currents and melting. Beneath ice shelves with a smooth, gradually sloping base, melting can be viewed as a vertical process, and this is how it is currently represented in climate models. However, observations show that melting on the steeply sloping sides of extreme ice topography is actually horizontal, and much faster than the melting of a smooth ice base. In addition, turbulent ocean eddies generated by extreme topographic features will mix warm water up towards the ice, further enhancing the melting.
We will observe the influence of extreme ice topography beneath an Antarctic ice shelf using pressurised hot water to drill through more than a kilometre of ice, enabling access to the ocean cavity beneath. We will study the controls on melting using a targeted suite of the latest observational measurements: radar and sonar to track the ice topography and melting, and acoustic ocean current profiling and a string of temperature sensors to monitor the mixing of ocean heat towards the ice. This will provide a unique dataset of the close interaction between ocean mixing and ice melting.
We will then combine these observations with a hierarchy of computer simulations to develop a new representation of the effect of extreme ice topography in climate models. We will first simulate the flow around extreme topographic features using high-resolution large-eddy simulations, which resolve the ocean turbulence. This will provide insight into the mixing of warm water to the ice base, and its interaction with melting. We will then use an ocean model to study the role of ice channel geometry on the melt rate and flow properties. Using these simulations, we will develop mathematical formulae to represent the influence of extreme ice topography. We will implement these formulae into the ocean model and test its ability to represent the influence of extreme ice topography in climate models.
