Collaborative Research: Combining Arctic Observing Network Observations and Remote Sensing Data to Understand Sea Ice Mass Balance and Albedo Feedbacks in a Changing Arctic

北极海冰正在经历显著和加速的变化，这在过去几十年中已被越来越详细地观察到。北极及其他地区的利益相关者受到这些变化对资源可及性、生态系统健康和地球的级联效应的影响。美国物理气候系统。规划缓解和适应战略需要提高对北极气候系统的预测能力。在理解反照率反馈在海冰损失中所起的作用方面，仍然存在巨大的差距，这使预测模式的发展变得混乱。该项目将利用在北极观测网络（AON）海冰站点收集的丰富数据集作为案例研究，跟踪它们在空间和时间上的移动，从而提高对太阳能吸收和分配对冰质量平衡的影响的理解。该方法将AON数据与先前野外活动的测量数据、大气再分析产品以及使用三维分辨海冰-海洋混合层耦合模型的高分辨率遥感数据相结合。我们的目标是以米尺度的分辨率量化这些地点周围10x10km研究区域内的太阳能沉积，确定太阳能随时间的变化（例如，海洋储存与冰底融化与侧向融化），并提高我们的分辨率比例模型的能力，以表示控制太阳能吸收和命运的过程。该模型明确地表示了关键的冰和海洋过程，如融化池形成、盐水排水、淡水平衡和上层海洋分层，为数据集成提供了一个工具，可以解释影响辐射传输和热储存的所有一级过程。初始化数据集的重要差距将通过集成建模方法来解决。将现场观测与模型状态进行反复比较，将有助于选择约束较差的初始条件，评估系统敏感性，并允许测试改进的模型参数化过程，如池塘演变。

Arctic sea ice is undergoing significant and accelerating change, which has been observed in increasing detail over the past several decades. Stakeholders in the Arctic and beyond are impacted by the cascading effects that these changes have on resource accessibility, ecosystem health, and earth?s physical climate system. Planning mitigation and adaptation strategies requires improvements in the ability to predict the arctic climate system. Confounding predictive model development are large gaps that remain in the understanding of the role albedo feedbacks are playing in sea ice loss.This project will improve the understanding the impacts of solar energy absorption and partitioning on ice mass balance by tracking Arctic Observing Network (AON) sea ice sites as they move through space and time, using the rich datasets being collected at the sites as case studies. The approach integrates AON data with measurements from prior field campaigns, atmospheric reanalysis products, and high resolution remote sensing data using a 3D resolved sea ice-ocean mixed layer coupled model. The objectives are to quantify the deposition of solar energy within a 10x10km study domain around the sites with meter-scale resolution, identify the fate of that solar energy over time (e.g. ocean storage vs. ice bottom melt vs. lateral melt), and improve the ability of our resolved scale model to represent the processes controlling solar absorption and fate. The model explicitly represents critical ice and ocean processes such as melt pond formation, brine drainage, freshwater balance, and upper ocean stratification, providing a tool for data integration that can account for all first order processes impacting radiative transfer and heat storage. Important gaps in initialization datasets will be addressed by an ensemble modeling approach. Iterative comparison of site observations with model states will inform the selection of poorly constrained initial conditions, evaluate system sensitivity, and allow testing of improved model parameterizations for processes such as pond evolution.