Toward improved forecasts of sea-ice thickness

众所周知，近年来北极的冰面积一直在减少。人们对北极冰层厚度的变化知之甚少。这是因为海冰的厚度比从卫星上测量海冰的范围更难测量。海冰的厚度可以通过测量红外波段辐射的卫星传感器的数据来估算。由于卫星观测包含一些误差，因此应尽可能将其与其他信息来源相结合。在这项研究中，我们将产生海冰厚度预报相结合的信息从卫星传感器和数值模式。预测的准确性将通过将结果与独立观察结果进行比较来验证。特别令人感兴趣的是，能够生成可提供给船舶的海冰厚度预报，以确保在冰患沃茨的安全航行。研究结果将被传达到加拿大冰服务，使他们能够及时应用于真实的问题。大量的重点放在了所谓的“冰反馈机制”在减少北极海冰范围的作用。这就是冰融化允许更多开放水域暴露的机制，因为开放水域比冰更暗，它可以吸收更多来自太阳的热量，允许更多的冰融化。然而，关于海洋表层以下储存的热量可能对海冰产生的作用的研究才刚刚开始。这是特别困难的，因为在海洋中传递热量的漩涡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漩涡。在这里，我们将研究一个参数化的涡旋，称为NS-α模式，在北冰洋的环流和涡旋。 如果成功，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.