Collaborative Research: Arctic Predictability

拟议的项目将回答北极环境变化研究的一个主要问题：“北极系统在多大程度上是可预测的？“该项目将利用地面气温、降水、海平面气压和海冰覆盖率的观测记录，量化近期（季节到十年）的可预测性。近期预测将被放置到一个框架的概率，根据最近的记录的变化，即将到来的时期（1，2，5，10？年）将看到温度，降水，压力和海冰变化的各种增量。 较长期的可预测性将根据一套全球气候模式的输出，以十年变化的可能性来量化，并将各种模式和强迫情景的可能性综合起来。 将评估低频变异性固有的潜在可预测性，并与全球研究的结果进行比较。 概率结果的空间映射将在一个网站上进行，该网站将允许用户构建特定时间片中选定变量阈值的概率分布的泛北极地图。 最后，我们将为耦合模式相互比较项目5（CMIP 5）的季节到年代际可预测性提供北极焦点，这将使海洋和表面变量（雪，冰）的初始状态中固有的北极可预测性的诊断成为可能。 拟议项目的更广泛影响在于用户社区（利益攸关方、规划者和北极社区）对结果的利用。 这项研究的成果将把北极观测和全球气候模型所掌握的北极变化科学与包括适应和减缓在内的“应对”部分联系起来。

The proposed project will respond to one of the driving questions of the Study of Environmental Arctic Change (SEARCH): "To what extent is the Arctic system predictable?" The project will quantify near-term (seasonal to decadal) predictability by drawing upon the observational records of surface air temperature, precipitation, sea level pressure and sea ice coverage. The near-term predictions will be placed into a framework of probabilities, based on the recent record of variability, that the upcoming period (1, 2, 5, 10? years) will see various increments of change of temperature, precipitation, pressure and sea ice. Longer-term predictability will be quantified in terms of decadal likelihoods of change based on output from a suite of global climate models, with the likelihoods integrated across models and forcing scenarios. Potential predictability inherent in low-frequency variability will be assessed and compared with results from global studies. Spatial mapping of the probabilistic results will be implemented at a website that will allow users to construct pan-Arctic maps of the probability-of-exceedance of a threshold of a selected variable in a particular timeslice. Finally, we will provide an Arctic focus for the seasonal-to-decadal predictability of the Coupled Model Intercomparison Project 5 (CMIP5), which will enable the diagnosis of Arctic predictability inherent in the initial states of the ocean and surface variables (snow, ice). The broader impacts of the proposed project lie in the utilization of the results by the user community (stakeholders, planners, and Arctic communities). The products of this study will link the science of Arctic change, as captured by Arctic observations and global climate models, with a "responding" component that includes adaptation and mitigation.