Toward improved forecasts of sea-ice thickness

众所周知，北极的冰层面积近年来一直在减少。人们对北极冰层厚度的变化知之甚少。这是因为海冰厚度比卫星海冰范围更难测量。可以使用测量红外波段辐射的卫星传感器的数据来估计海冰厚度。由于卫星观测包含一些误差，应尽可能将它们与其他信息来源结合起来。在这项研究中，我们将结合来自卫星传感器的信息和来自数值模式的信息来生成海冰厚度预测。预测的准确性将通过将结果与独立观测进行比较来验证。特别令人感兴趣的是，能够对海冰厚度进行预测，以提供给船只，以确保在冰川泛滥的水域安全航行。研究结果将被传达给加拿大冰雪服务机构，以便及时应用于实际问题。人们非常重视所谓的“冰-反照率反馈机制”在减少北极海冰面积方面的作用。这就是融化的冰允许更多的开阔水域暴露出来的机制，因为开阔的水域比冰更暗，它可以吸收更多来自太阳的热量，从而允许更多的冰融化。然而，了解储存在海洋表层下的热量可能对海冰起到的作用的工作才刚刚开始。这尤其困难，因为海洋中传递热量的涡旋的大小随着纬度的增加而减小，因此需要精细的数值网格来捕捉北极的涡流。在这里，我们将研究一种关于北冰洋环流和涡旋的参数化，称为NS-Alpha模式。如果成功，该参数化可用于气候模拟，作为政府间气候变化专门委员会使用的套件的一部分。

It is well known that the ice extent in the Arctic has been decreasing in recent years. It is much less well known how the thickness of the ice in the Arctic is changing. This is because sea ice thickness is more difficult to measure than sea ice extent from satellites. Sea ice thickness can be estimated using data from a satellite sensor that measures radiation in the infrared band. Because satellite observations contain some error, they should be combined with other sources of information when possible. In this research we will generate sea ice thickness forecasts by combining the information from the satellite sensor with that from a numerical model. The accuracy of the forecasts will be verified by comparing the results with independent observations. It is of particular interest to be able to generate forecasts of sea ice thickness that can be given to ships, to ensure safe navigation in ice-infested waters. Results from the research will be communicated to the Canadian Ice Service such that they can be applied to real problems in a timely manner.A great deal of emphasis has been placed on the role of the so called 'ice-albedo feedback mechanism' in decreasing sea ice extent in the Arctic. This is the mechanism by which melting ice allows for more open water to be exposed, and because the open water is darker than the ice it can absorb more of the heat from the sun, allowing more ice to melt. However, work has only begun on understanding the role the heat stored below the surface layer in the ocean may play on the sea ice. This is particularly difficult because the size of the eddies which transfer heat in the ocean decreases with increasing latitude, so fine numerical meshes are required to capture the eddies in the Arctic. Here we will investigate a parameterization for the eddies, called the NS-alpha model, on the circulation and eddies in the Arctic ocean. If successful, the parameterization can be used for climate simulations as part of the suite used by the Intergovernmental Panel on Climate Change.