Snow Covers impact on Antarctic Sea Ice - Remote Sensing (SCASI-RS)

积雪对南极海冰的影响 - 遥感 (SCASI-RS)

• 批准号: 404762641
• 负责人: Dr. Nina Maaß
• 金额: --
• 依托单位: Alfred-Wegener-Institut (AWI) Helmholtz-Zentrum für Polar- und Meeresforschung
• 依托单位国家: 德国
• 项目类别: Infrastructure Priority Programmes
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2023-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/404762641?language=en
• 关键词: Snow; Covers; impact; Antarctic; Sea

Antarctic sea ice is generally covered with snow, and thus the snow properties determine the surface characteristics of the ice and influence the interaction between atmosphere and ocean.Snow-ice formation is much more common in the Antarctic than in the Arctic and contributes significantly to the sea ice mass balance. Additionally, information on snow depth and density are required to derive ice thickness from altimeter measurements. However, so far knowledge on Antarctic snow on sea ice mainly originates from individual field measurements and ship observations. On larger scales, snow depth can also be retrieved from passive microwave satellites measuring at 19 and 37GHz frequency, but validation of the method and investigation of error sources are ongoing work. In the Snow Covers impact on Antarctic Sea Ice (SCASI) project, we aim for quantifying the amount and distribution of snow on sea ice, as well as the physical properties of snow and their temporal evolution. The overall goal is to develop a new and consistent snow data product for Antarctic sea ice that represents various length scales and different seasons. In order to achieve this and to bridge the scales from point measurements to satellite footprints, we synthesize field observations, satellite remote sensing and numerical modeling. A widely-used snow cover model that has been successfully applied for modeling snow in alpine regions is the one-dimensional SNOWPACK model. In the SCASI project, we bring together Swiss and German partners to further develop a sea ice version of SNOWPACK and to combine it with in-situ and buoy measurements as well as passive microwave satellite observations. The SCASI-Remote Sensing (SCASI-RS) project deals with the satellite remote sensing part of SCASI. In SCASI-RS, we compare SNOWPACK simulations with in-situ measurements to identify suitable cases for validation of satellite retrievals. By combining SNOWPACK with emission models we can simulate microwave radiation and investigate the impact of snow properties on the retrieval methods. This will not only be done for the microwave frequencies at 19 and 37GHz, used for snow depth retrievals so far, but also for a lower frequency of 1.4 GHz. Global satellite observations at 1.4GHz have been available since 2009, and we investigate whether snow depth in the Antarctic can also be derived from this very low microwave frequency, as it has been suggested for the Arctic recently. Due to the distinct differences of the ice and snow conditions, however, the results may not be transferred directly to Antarctic regions.The resulting product will be useful for sea ice and radiation models, altimetry-based ice thickness retrievals and other research that depends on information on snow on sea ice, for example regarding biological production or geo-chemical cycles.

南极海冰通常被雪覆盖，因此雪的性质决定了冰的表面特征，并影响大气和海洋之间的相互作用。冰雪的形成在南极比在北极更为普遍，并对海冰质量平衡作出了重大贡献。此外，要从高度计测量得到冰的厚度，还需要雪的深度和密度的信息。然而，到目前为止，关于南极海冰上的雪的知识主要来自个别的实地测量和船舶观测。在更大的尺度上，也可以从19 ghz和37GHz频率的被动微波卫星上反演雪深，但方法的验证和误差源的研究仍在进行中。在雪盖对南极海冰的影响（SCASI）项目中，我们的目标是量化海冰上雪的数量和分布，以及雪的物理性质及其时间演变。总体目标是开发一种新的、一致的、代表不同长度尺度和不同季节的南极海冰积雪数据产品。为了实现这一目标，并在从点测量到卫星足迹的尺度上架起桥梁，我们综合了实地观测、卫星遥感和数值模拟。一维SNOWPACK模型是目前广泛应用并成功应用于高寒地区积雪模拟的积雪模型。在SCASI项目中，我们将瑞士和德国的合作伙伴聚集在一起，进一步开发海冰版本的SNOWPACK，并将其与现场和浮标测量以及被动微波卫星观测相结合。SCASI-遥感（SCASI- rs）项目涉及SCASI的卫星遥感部分。在SCASI-RS中，我们将SNOWPACK模拟与原位测量进行比较，以确定验证卫星检索的合适案例。将SNOWPACK与发射模型相结合，模拟微波辐射，研究积雪性质对反演方法的影响。这不仅适用于目前用于雪深检索的19 GHz和37GHz的微波频率，也适用于1.4 GHz的较低频率。自2009年以来，1.4GHz的全球卫星观测已经可用，我们研究了南极的雪深是否也可以从这个非常低的微波频率中得出，就像最近对北极提出的那样。然而，由于冰雪条件的明显差异，结果可能无法直接转移到南极地区。由此产生的产品将有助于海冰和辐射模型、基于测高的冰厚检索以及其他依赖海冰上的雪的信息的研究，例如关于生物生产或地球化学循环的研究。