Seasonal evolution of Ku- and Ka-band backscattering horizon over snow on first-year and multiyear sea ice

近40年来，利用连续的被动微波卫星飞行任务提供的长期数据记录绘制了北冰洋海冰面积图；显示出自1979年以来冰消退的速度加快。人们对海冰也变薄了多少知之甚少，部分原因是缺乏类似的长期和一致的海冰厚度数据记录。雷达高度计，例如自2010年4月以来搭载在欧洲空间局(欧空局)的S低温卫星2号上的雷达高度计，以及作为国家空间研究中心和印度空间研究组织联合飞行任务的一部分于2013年2月发射的SARAL/AltiKa卫星，目前正在提供泛北极(或AltiKa高达81.5北纬)厚度观测。然而，在使用这些数据时，一个关键的不确定性是雷达实际上能穿透到覆盖的积雪有多远。一般假设雷达回波来自Ku波段(CS2)的冰雪界面和Ka波段(AltiKa)的雪-空气界面。利用这些信息，再加上对上覆积雪深度和密度的假设，科学家们就可以在假设流体静力平衡的情况下，将雷达回波转换为总冰层厚度。然而，现场证据对这一普遍假设提出了质疑，即使对于均匀的积雪也是如此。更复杂的是，对积雪的深度和密度缺乏了解。通常，积雪深度和密度信息是基于20世纪80年代在厚厚的多年冰上建造的气候学而得到的。然而，随着海冰覆盖总面积的减少，北极盆地现在出现了更大比例的第一年海冰。第一年冰上的雪往往比多年冰上的更咸，因此它可能会对雷达回波产生重大影响。此外，北极某些地区的秋季和冬季冻结期推迟了几周到几个月，缩短了积雪的持续时间。鉴于目前的不确定性，很难准确评估海冰厚度的年际变化和长期变化。由于海冰是气候变化的重要指标，在北极能源和淡水平衡中发挥着基础性作用，是海洋生态系统的关键组成部分，因此提高雷达测高厚度的精度至关重要。该项目的目的正是通过在Ku和Ka频段的整个年度周期上对雷达穿透深度进行地面观测，从秋季结冰到冬季积雪变质和夏季融化。这些信息与详细的积雪特征一起，将使我们能够评估积雪、积雪形态和积雪盐度的变化如何影响Ku和Ka波段的渗透系数。马赛克漂流站提供了一个独特的机会，可能是唯一的机会，以获得涉及一致的现场、航空和卫星数据的基准数据集。对这些信息的分析将使科学家能够更好地描述积雪的物理特性(在不同类型的冰之上)如何影响Ka和Ku波段雷达的穿透。重要的是，我们将能够评估第一年(大于几厘米的海冰)和多年海冰上积雪的季节性演变。马赛克还提供了全年观测积雪深度和密度的机会，这将使人们能够评估通常用于雷达测高厚度反演的气候假设的有效性，并为验证积雪深度产品提供数据。这些活动对于改进在北极发现的许多冰雪条件下的雷达测高海冰厚度是必不可少的。

Arctic sea ice area has been mapped for nearly four decades using the long-term data record provided by successive passive microwave satellite missions; showing an accelerated pace of ice loss since 1979. Less is known about how much the ice has also thinned, in part because of the lack of a similarly long-term and consistent data record on sea ice thickness. Radar altimeters, such as the one flown on the European Space Agency (ESA)'s CryoSat-2 (CS2) since April 2010, and the SARAL/AltiKa satellite, launched in February 2013 as part of a joint mission by the Centre National d'Etudes Spatiales (CNES) and the Indian Space Research Organization (ISRO), are now providing pan-Arctic (or up to 81.5N for AltiKa) thickness observations. However, one key uncertainty in using these data is how far the radar actually penetrates into the overlying snow cover. The general assumption has been that the radar return is from the snow-ice interface at Ku-band (CS2) frequencies, and from the snow-air interface at Ka-band (AltiKa) frequencies. Using this information together with assumptions on the depth of the overlying snow pack and its density, scientists can then convert the radar returns into total ice thickness assuming hydrostatic equilibrium. However, field evidence has put this general assumption into question, even for a homogeneous snowpack. A further complication is the lack of knowledge on how deep the snow pack is and its density. Typically, snow depth and density information based on a climatology constructed over thick multiyear ice in the 1980s have been used. However, as the total area in the sea ice cover has declined, there is now a larger proportion of first-year sea ice in the Arctic Basin. Snow over first-year ice tends to be more saline than over multiyear ice, and as such it has the potential for a significant impact on the radar returns. In addition, autumn and winter freeze-up has been delayed by several weeks to months in certain regions of the Arctic, shortening the duration for accumulation of snow. Given these current uncertainties, it is difficult to accurately assess how sea ice thickness is changing from year to year and over the long-term.Because sea ice is an important indicator of climate change, plays a fundamental role in the Arctic energy and freshwater balance, and is a key component of the marine ecosystem, it is essential that we improve the accuracy of thickness retrievals from radar altimetry. This project aims to do just that by making ground-based observations of the radar penetration depth over a full annual cycle at both Ku- and Ka-band frequencies, from autumn freeze-up, through winter snow metamorphism and summer melt. This information, together with detailed snow pack characteristics, will allow us to assess how changes in snow accumulation, snow morphology and snow salinity impact Ku- and Ka-band penetration factors. The MOSAiC drifting station provides a unique opportunity, possibly the only opportunity, to obtain a benchmark dataset that involves coherent field, airborne and satellite data. Analysis of this information will enable scientists to better characterize how the physical properties of the snow pack (above different ice types) influence the penetration of Ka and Ku band radar. Importantly, we will be able to evaluate the seasonal evolution of the snow pack over first-year (sea ice greater than a few cm) and multiyear sea ice. MOSAiC additionally provides the opportunity for year-round observations of snow depth and density that will allow for assessment of the validity of climatological assumptions typically employed in thickness retrievals from radar altimetry and provide data for validation of snow depth products. These activities are essential in order to improve sea ice thickness retrievals from radar altimetry over the many ice and snow conditions found in the Arctic.