Ice-layer Permeability Controls Runoff from Ice Sheets (IPCRIS)

格陵兰冰盖是世界上最大的海平面上升（约20%总上升）的单一来源，每年从冰盖损失的质量中有一半以上来自表面融水径流。这一比例及其幅度随着气候持续变暖而不断上升，但未来的预测以及对海平面上升影响的社会规划受到一个根本不确定性来源的破坏。在格陵兰冰盖的绝大多数积累区域，我们不知道有多少从表面融化产生的水重新冻结在下面的积雪（即多年积雪）或成为径流。当冰盖的表面融化时，下面的雪，积雪和不透水的冰的密度和温度联合收割机起来，决定融化的雪和积雪是否重新冻结，或者变成径流进入海洋。如果融水可以渗透到深度（例如，高达c.10米），并获得冷，低密度的积雪，它可以重新冻结，在气候变化和海平面上升之间创造一个重要的缓冲。或者，如果融化遇到相对温暖的积雪中的浅的不可渗透的冰层（它们本身是由先前的再冻结形成的），融化就不能到达冷的积雪，更多的融化将成为径流。仅这两种情况之间的差异就可能使世纪中期的冰盖径流量增加一倍。我们依靠对地表融化、再冻结和径流的模型模拟来准确预测格陵兰冰盖未来对海平面上升的贡献。然而，过去60年来，基于模型的冰盖年复冻能力估计值差异很大，破坏了它们向可靠的未来预测范围收敛的能力。不确定性的一个主要原因来自于模型对冰层渗透性所做的完全不同的假设，这些假设极大地改变了冰盖的再冻结能力。如果假定积雪中的冰层是不可渗透的（可渗透的），它们将抑制（允许）融水渗透到深处，减少（保持）再冻结能力，增加（减少）径流，从而增加（减少）预计的全球海平面上升。如果没有一个更好的处理冰层渗透性，现有的表面质量平衡模型不能提供可靠的预测未来的再冻结能力，从格陵兰冰盖的融水径流，离开冰盖的未来贡献海平面上升高度不确定。首先，我们需要知道雪和积雪的物理和热条件，这些条件控制着相对较薄的冰层（厚度<0.5米）的有效渗透性，因为在我们变暖的气候中，这些条件越来越多地决定着融水可以渗透的深度，从而控制着底层积雪的再冻结能力。为此，我们将进行温度控制的实验室实验，系统地模拟和监测雪/积雪/冰融化/再冻结/径流。其次，我们需要模拟雪和积雪中冰层的有效渗透性及其对外部和内部条件变化的敏感性，因为这些因素共同控制着有多少融化物重新冻结或成为径流。为此，我们的实验室工作将为模拟测量的北极冰盖积雪演变的建模提供新的发展。最后，我们将在格陵兰冰盖的冰盖尺度模型中纳入改进的冰层渗透性标准，以生成更准确的径流和再冻结模拟，并提高长期质量平衡模型预测的协调性，从而提高下一个世纪全球海平面上升的预测。最近的多个“异常”融化季节导致近地表冰层通过先前低密度的积雪扩散。这些极端情况将成为未来的新常态，因此迫切需要新的模型参数化，以有效地取代对质量平衡的层控制。

The Greenland Ice Sheet is the world's largest single source of barystatic sea-level rise (c.20% total rise) and more than half of the mass lost annually from the ice sheet comes from surface melt-water runoff. This proportion, and its magnitude, is rising with continued climate warming but future projections, and societal planning for sea level rise impacts, are undermined by a fundamental source of uncertainty. Across the vast majority of the accumulation area of the Greenland Ice Sheet, we do not know how much of the water produced from surface melting refreezes in underlying firn (i.e. multi-year snow) or becomes runoff. When the surface of an ice sheet melts, the density and temperature of underlying snow, firn and impermeable ice combine to determine whether melt refreezes in the underlying snow and firn, or becomes runoff to the ocean. If meltwater can percolate to depth (e.g. up to c.10 m) and access cold, low density firn, it can refreeze creating a significant buffer between climate change and sea-level rise. Alternatively, if melt encounters shallow impermeable ice layers (themselves created by previous refreezing) within relatively warm firn, melt cannot reach the cold firn and more melt will become runoff. The difference between these two scenarios alone could double ice sheet runoff by the middle of the 21st century. We rely on model simulations of surface melt, refreezing and runoff to accurately project the future contribution of the Greenland Ice Sheet to sea level rise. However, model-based estimates of the annual refreezing capacity of the ice sheet over the last six decades differ dramatically and undermines their ability to converge towards a reliable range of future projections. A major cause of uncertainty follows from the quite different assumptions that models make about ice layer permeability that dramatically alters the ice sheet refreezing capacity. If ice layers in firn are assumed to be impermeable (permeable), they will inhibit (allow) meltwater percolation to depth, diminish (maintain) refreezing capacity, increase (decrease) runoff and hence increase (decrease) projected global sea level rise. Without an improved treatment of ice layer permeability, existing surface mass balance models cannot provide reliable projections of the future refreezing capacity of, and melt-water runoff from, the Greenland Ice Sheet, leaving the ice sheet's future contribution to sea level rise highly uncertain. Firstly, we need to know the physical and thermal conditions of snow and firn that control the effective permeability of relatively thin ice layers (<0.5m thick) since within our warming climate these are increasingly determining the depth to which meltwater can percolate and hence control the refreezing capacity of the underlying firn. To this end we will undertake temperature-controlled laboratory experiments, systematically simulating and monitoring snow/firn/ice melt/refreezing/runoff. Secondly, we need to model the effective permeability of ice layers in snow and firn and their sensitivity to changing external and internal conditions since these together control how much melt refreezes or becomes runoff. For this, our lab work will inform novel developments to modelling to simulate measured arctic ice cap snowpack evolution. Finally we will incorporate improved ice layer permeability criteria within ice sheet scale models of the Greenland Ice Sheet to generate more accurate simulations of runoff and refreezing during melt extremes and improve harmonisation of long-term mass balance model projections, consequently improving global sea level rise predictions over the next century. Multiple recent "exceptional" melt seasons have caused near surface ice layers to proliferate through previously low density firn. These extremes will be the new norm in the future so new model parameterisations are urgently required that can effectively characterise ice layer control on mass balance.