Analysis to evaluate and improve model performance in the Central Arctic: Unique perspectives from autonomous platforms during MOSAiC

这项研究将使用一项新兴技术，即无人驾驶飞机系统来收集测量数据，目的是改善北极系统的天气和气候模型。它是国际MOSAiC（北极气候研究多学科漂流观测站）计划的一部分，这是一项广泛的实地工作，将一艘破冰船冻结成海冰整整一年，作为一个研究平台，对北极高海拔地区的大气、海洋和冰系统进行全面研究。这个项目的独特和潜在的变革方面是，无人驾驶飞机在小的空间和时间尺度上收集数据，提供关于温度、湿度和风的变化的新信息。此外，迄今为止，对这些变量在海冰断裂上的直接测量非常有限。因此，这项研究将解决我们目前预测能量如何在大气和下面的冰和海面之间转移的能力中的一个重要的误差来源。与参与MOSAiC野外工作的合作科学家提供的信息一起，研究人员将评估一系列与北冰洋中部关键过程的模型模拟性能有关的假设。调查人员还将在学校和其他场所进行公开讲座，通过使用无人驾驶飞机系统的视频和照片，利用人们对使用新技术的兴趣和兴奋。他们将通过研究生和博士后科学家的参与来支持对早期职业科学家的培训。调查人员将部署一个无人驾驶飞机系统来测量大气温度、风、湿度以及地表反照率。飞行将从冬季中期（2月）到夏末（8月）进行，以捕捉大气和海冰表面的可变条件，并将包括对低层大气的常规分析，热力学量和表面反照率的空间测绘，以及对铅上方低层大气结构的测绘。这些数据将与其他科学家收集的大气、海洋和冰的测量数据进行评估，这些数据是MOSAiC（北极气候研究多学科漂流观测站）项目的一部分，旨在解决与模拟北冰洋中部关键过程的建模工具性能有关的假设。这些问题包括大气和地表参数的亚网格尺度变率及其对模式模拟的地表能量收支的影响；海冰中的铅对从海洋到大气的能量转移的影响以及模式如何表示这种转移；以及垂直分辨率在北极大气模拟中的重要性及其对云和地表能量收支模拟的影响。研究人员将把无人机系统的观测结果与各种模拟进行比较，从全球产品到使用区域北极系统模型（RASM）完成的全耦合区域模拟，再到详细的高分辨率单列和2D建模。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This study will use an emerging technology, unmanned aircraft systems, to collect measurements with the goal of improving weather and climate models of the Arctic system. It is part of the international MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) program, an extensive field effort to freeze an icebreaker into sea ice for an entire year to serve as a research platform for a comprehensive study of the atmosphere, ocean and ice system in the high Arctic. The unique and potentially transformative aspect of this project is that unmanned aircraft collect data at small spatial and temporal scales, providing new information about variability in temperature, humidity, and winds. In addition, direct measurements of these variables over breaks in the sea ice have been very limited to date. Therefore, this study will address a significant source of error in our current ability to forecast how energy is transferred between the atmosphere and underlying ice and sea surface. Together with information from collaborating scientists participating in the MOSAiC field effort, the investigators will evaluate a series of hypotheses related to the performance of model simulations of key processes over the central Arctic Ocean. The investigators will also give pubic lectures at schools and other venues, capitalizing on interest and excitement in use of new technology though use of videos and photos of the unmanned aircraft systems. They will support training for early career scientists by involving graduate students and postdoctoral scientists.The investigators will deploy an unmanned aircraft system to measure atmospheric temperature, winds, and humidity, as well as surface albedo. Flights will take place from mid-winter (February) through late summer (August) to capture variable conditions in both the atmosphere and sea ice surface and will include routine profiling of the lower atmosphere, spatial mapping of thermodynamic quantities and surface albedo, and mapping of the lower atmospheric structure over leads. This data will be evaluated with measurements of the atmosphere, ocean and ice collected by other scientists as part of the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) project to address hypotheses related to the performance of modeling tools in simulating key processes over the central Arctic Ocean. These include questions about sub-grid scale variability of atmospheric and surface parameters and its influence on model-simulated surface energy budget; the influence of leads in the sea ice on energy transfer from the ocean to the atmosphere and how models represent this transfer; and the importance of vertical resolution in simulation of the Arctic atmosphere and its impact on the simulation of clouds and the surface energy budget. The investigators will compare observations from unmanned aerial systems to a variety of simulations, ranging from global products to fully-coupled regional simulations completed using the Regional Arctic System Model (RASM) to detailed single-column and 2D modeling at high resolution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.