Seasonal-to-Decadal Predictability of Arctic Sea Ice

随着2007年夏季浮冰的开放，人们对海冰状况的短期、季节性和十年预测或预测的兴趣增加了。科学界用于研究该系统在这些时间尺度上的可预测性的方法包括通过再分析（有或没有数据同化）强迫与大气场耦合的冰-海洋模式，从观测中获得初始条件的全耦合环流模式，或统计模式和启发式或混合方法。对于短期预报（1-2天），热力学效应不太重要，不需要完全耦合的模型。在这种情况下，预报技巧依赖于精确的初始条件、表面大气应力以及海冰和表面海洋物理的准确表示。对于季节预报来说，准确的初始条件以及冰-海-气物理和反馈的良好表现同样至关重要。对于年代际预估，失去了对初始条件的敏感性，预测技能依赖于冰-海-大气物理的准确表示，以及内部变率和外部强迫（如CO2、臭氧、气溶胶、大气顶部的太阳辐照度等）的准确表示。这项研究计划的长期目标是改善北冰洋海冰的短期至十年预测或预测。该提案的具体目标是改善海冰的物理特性（漂移和变形）；从观测数量和再分析数据（冰速、浓度、厚度和低层/高层大气环流）量化潜在的可预测性；确定负责观测可预测性的关键指标，并评估全球气候模式是否正确模拟了这些指标（指出模式改进和预报改进的领域）；量化与海洋热通量（白令海峡和巴伦支海开口的横向和通过对流和Ekman动力学的垂直）相关的可预测性的潜在改进。这项工作的完成将有助于更好地理解预测技巧和潜在的可预测性。这项工作的新颖之处在于，它直接从观察中评估可预测性。这是至关重要的，因为模型的模拟平均状态中的小偏差可能导致可预测性的重大损失。这项研究计划将使加拿大处于一个独特的位置，为当地居民和工业改善海冰预报，允许在北极更安全的操作，这变得越来越容易导航。它还将减少这些变化何时更有可能发生的时间表上的不确定性。

With the opening of the summer pack ice in 2007, there has been an increased interest in short-term, seasonal and decadal forecasting or projections of sea ice conditions. Methods used in the community to study the predictability of the system on these time scales include coupled ice-ocean models forced with atmospheric fields from reanalyses (with or without data assimilation), fully coupled General Circulation Models with initial conditions derived from observations, or statistical models and heuristic or mixed approaches. For short-term forecasting (1-2 days), thermodynamic effects are less important and fully coupled models are not necessary. In this case, forecasting skill relies on the specification of accurate initial conditions, surface atmospheric stresses and an accurate representation of sea ice and surface ocean physics. For seasonal forecasting, accurate initial conditions are again crucial along with a good representation of ice-ocean-atmosphere physics and feedbacks. For decadal projections, the sensitivity to initial conditions is lost, and predictive skill relies on an accurate representation of the ice-ocean-atmosphere physics, as well as accurate representation of internal variability and external forcing such as CO2, ozone, aerosol, solar irradiance at the top-of-the-atmosphere, etc. The long-term objectives of this research program are to improve short-term to decadal forecasts or projections of sea ice in the Arctic Ocean. The specific objectives of the proposal are to improve sea ice physics (drift and deformation); to quantify potential predictability from observed quantities and reanalysis data (ice speed, concentration, thickness and lower/upper atmospheric circulation); to identify key metrics responsible for predictability in observations and assess whether those metrics are correctly simulated in Global Climate Models (pointing to area of model improvements and improved forecasts); to quantify potential improvements in predictability associated with ocean heat flux (both lateral in the Bering Strait and Barents Sea Opening and vertical via convection and Ekman dynamics). The completion of this work will lead to a better understanding of forecast skill and potential predictability. The novelty in this work is that it assesses predictability directly from observations. This is crucial given that small biases in the simulated mean state of models can lead to significant loss of predictability. This research program will place Canada in a unique position to improve sea ice forecasts for local populations and industry, allowing for safer operations in an Arctic, that is becoming increasingly accessible to navigation. It will also reduce uncertainties in the timeline for when these changes are more likely to occur.